Bumblebee density in agroecosystems during thestarting stage of the colonies and its implications forpollination services

Eeva-Liisa Alanen

Licentiate thesis in agroecology

Faculty of Agriculture and Forestry

Department of Applied Biology

University of Helsinki

December 2009

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Current address: Finnish Environment InstituteEcosystem Change UnitP.O. Box 140FI-00251 HelsinkiFinlandemail: eeva-liisa.alanen@ymparisto.fi

Supervised by: Juha HeleniusUniversity of Helsinki

Irina HerzonUniversity of Helsinki

Front cover: Bombus pascuorum foraging on Taraxacum.

Photo: Eeva-Liisa Alanen

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Table of contents

ABSTRACT 4

1. MOTIVATION FOR THE STUDY 5

2. LITERATURE REVIEW 5

2.1. Pollination services at risk 5

2.2. Bumblebees as pollinators 7

2.3. The colony cycle of bumblebees 9

2.3.1. Queen overwintering 9

2.3.2. Queen foraging 11

2.3.3. Nest initiation 11

2.3.4. Colony growth 13

2.3.5. Reproduction 14

2.4. Environmental change and bumblebees 15

2.4.1. Changing agroecosystems 15

2.4.1.1. Habitat terminology 15

2.4.1.2. Landscape elements 16

2.4.1.3. On the importance of scale 17

2.4.1.4. Rarity and abundance in bumblebees 18

2.4.1.5. Agricultural landscapes in Finland 20

2.4.2. Climate change 22

2.4.2.1. Implications for plant flowering 23

2.4.2.2. The plant-pollinator timing mismatch 24

3. STUDY OBJECTIVES 26

4. MATERIALS AND METHODS 27

4.1. Study area 27

4.2. Weather conditions 28

4.3. Data collection 29

4.3.1. Line-transects 29

4.3.2. Bumblebee and food plant records 32

4.4. Data analysis 33

4.4.1. Rarefaction 33

4.4.2. Flower visits 33

4.4.3. Bumblebee densities 33

4.4.4. Landscape structure of the study areas 34

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5. RESULTS 35

5.1. Bumblebee phenology 35

5.2. Comparison of study areas 37

5.2.1. Differences in bumblebee records between study areas 37

5.2.2. Influence of the landscape structure on bumblebee densities 40

5.3. Food plants 41

5.3.1. Flower visits 41

5.3.2. Bumblebee density in relation to flower abundance 42

5.4. Role of habitat properties 44

5.4.1. Habitat type 44

5.4.1.1. Foraging and nest-seeking queens 44

5.4.1.2. Ecological species groups 46

5.4.2. Ditch type 47

5.4.3. Field margin width 48

5.4.4. Ruderal patch type 48

5.4.5. Forest margin direction 48

6. DISCUSSION 50

6.1. Ecological significance of findings 50

6.1.1. The interplay between queen phenology and food plant availability 50

6.1.2. Densities in the different habitat types and their fluctuation during the spring 52

6.1.3. Other properties of the line-transects important for high queen densities 56

6.1.4. Mitigation strategies targeted at the starting stage of bumblebee colonies 58

6.2. Methodological issues 60

6.2.1. Landscape analysis and the comparison of study areas 60

6.2.2. Future research needs 62

ACKNOWLEDGEMENTS 63

REFERENCES 64

APPENDICES

Appendix 1: The total counted lengths (m) in each study area and habitat type 78

Appendix 2: Bumblebee abundance in the study areas during each count 79

Appendix 3: Flower visits of the bumblebees 80

Appendix 4: The mean densities of species in each habitat type during each count 81

Appendix 5: The landscape structure of the study areas 82

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ABSTRACT

In this thesis, I discuss the factors controlling bumblebee populations, with special reference to queen foragingand nest initiation. I concentrate on the role of food plant availability and other habitat properties in agriculturallandscapes. Furthermore, the possible effects of climate change, such as timing mismatches in the plant-pollinator interaction of the overwintered bumblebee queens and their spring-flowering food plants, arediscussed.

Pollination is one of the key ecosystem services in agroecosystems. This service is provided especially by bees,such as the bumblebees (Bombus). During the spring months overwintered bumblebee queens are particularlyimportant. They are valuable pollinators of such plants as the apple (Malus x domestica) and the bilberry(Vaccinium myrtillus). Furthermore, the recent collapses of honey bee (Apis mellifera) colonies (CCP = ColonyCollapse Disorder), have raised concern among both the beekeepers themselves and farmers, whose crops relyon bee pollination. As a result of the CCP, the role of native pollinators has become even more important thanbefore. At the same time, as farmland biodiversity is decreasing worldwide largely due to agriculturalintensification, supporting sustained populations of bumblebees in intensively cultivated landscapes is of greatimportance.

By using a field data set, answers to three main questions were sought for. First, How is the interplay betweenqueen phenology and food plant availability in the study landscape?, second, What are the densities in thedifferent habitat types and how do they fluctuate during the spring? and third, Which other properties of theline-transects are important for high queen densities? The data of the study was collected in the spring of 2000in Lammi, southern Finland (61o 05’N, 24 o 00’E), using the line-transect method. The habitat types studiedwere: forest boundary between a forest and a field, forest boundary between a forest and a road, grassland field(field sown with grass and/or clover seed, either to be mown or used as pasture), garden, field margin betweentwo fields, field margin between a field and a road, streamside (= riparian corridor) (or other moist area with tallshrubs and trees and ruderal patch (semi-natural vegetation, such as barn surroundings or a small meadow).

During the four counts, 13 bumblebee species (including cuckoo bumblebees, Psithyrus) were recorded. Thetotal of the individuals observed was 3711. The proportion of nest-seeking queens was at its highest during thethird count (7.2 %). The early-emerging B. lucorum was the most abundant species. During the first count, 74.7% of the individuals belonged to this species complex, whereas by the fourth count the percentage had droppedto 44.8 %. The foraging individuals visited 28 plant species or genera, willows (Salix), dandelions (Taraxacum)and the Norway maple (Acer platanoides) being the most frequently visited ones. All of these are more suitablefor short-tongued, rather than long-tongued species. B. lucorum was particularly dominant on the maple.

The mean total density of bumblebee queens, counted over all transects, was 29.5 individuals per hectare duringthe first count and 67.5, 39.9 and 40.0 individuals/hectare during the other three counts. In early May the highestdensity of foraging queens was found in the riparian corridors and in late May on the grassland fields. In theformer habitat the mean area (m2) covered by flowering willows was the highest, whereas in the latter habitatthe mean coverage (%) of dandelions was the highest. Therefore,the density of foraging queens followed thepeak of flowering of the most important food plants. During the second count, both the willows and the mapleplayed an important role in attracting the bumblebees, the area covered by flowering A. platanoides beinghighest in gardens. The gardens supported relatively high densities of queens during all counts, but during thethird one in particular. In the case of field margin transects, those adjacent to the main ditches manifested thehighest queen density during the first two, and temporary field margins during the last two counts.

I suggest a network of open and shrubby field margins to be maintained or created, since this would benefit thebumblebees during their whole colony cycle, as well as other pollinating insects, such as butterflies. For early-emeging species willows are vitally important. For late-emerging species open field margins seem to hold ahigher value than streamsides or field margins adjacent to main ditches. They provide suitable forage plants,such as vetches (Vicia), for long-tongued species of bumblebees. These include B. distinguendus, a specieswhich has apparently decreased in Finland. Grassland field with flowering dandelions benefit both the queensand the first workers. Furthermore, including early-flowering species in the seed mixtures used in agri-environmental scheme measures would benefit the bumblebee colonies in their starting stage as well.

Key words: agricultural ecosystems, ecosystem services, native pollinators, bumblebee queens, food plants,nesting sites, landscape ecology, habitat management, climate change

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1. MOTIVATION FOR THE STUDY

Three main issues gave incentive to this study. First, bumblebees (Bombus: Hymenoptera, Apidae) play an

important functional role as pollinators in agroecosystems. However, the densities of many species have

declined in several countries during the past few decades (Williams 1986, Kosior et al. 2007, Colla & Packer

2008, Kleijn & Raemakers 2008). The reasons behind these declines, on one hand, and the root causes of rarity

in some of the rarer species, on the other, are not completely understood. It is safe to state, however, that

bumblebee populations can be supported by appropriate farmland management. As stated by Morandin et al.

(2007), bees can persist even in intensively cultivated agricultural areas, but it is still unclear whether such

populations are self-sustaining. Second, though most of the pollination in agroecosystems is performed by the

domesticated honey bee (Apis mellifera), the importance of alternative pollinators has been increasing due to the

recent problems in the beekeeping industry. As a consequence of these problems, a wide variety of wild and

cultivated plants may start suffering from pollination deficits (Steffan-Dewenter et al. 2005). Third, climate

change will pose its own threat to bumblebees. According to most scenarios, spring temperatures will change

most drastically due to the global warming and indeed such a trend is already visible (Kaukoranta & Hakala

2008). As bumblebee colonies are founded by overwintered bumblebee queens, it is likely that the starting stage

of the colony is and will be the most vulnerable part of the colony cycle in relation to such problems as timing

mismatches in the plant-pollinator relationship.

2. LITERATURE REVIEW

" ... Only healthy populations (precondition: e.g. a sufficient food basis) which have the possibility of reproducingsuccessfully (precondition: e.g. an area size adapted to the demands of the species and suitable habitat resources) safeguardthe survival of a species. Therefore, (if applied to the whole species community of an ecosystem) healthy populationsguarantee the conservation of biodiversity, but also of beneficial aspects (e.g. predation, parasitation, decomposition)on a high level. Therefore, the “physical fitness” of populations of wild animal and plant species typical in agro-ecosystemscan be estimated as a decisive measure for the seriousness of the conversion of consumer protection interests into actionwith regard to food production. " (Büchs 2003)

2.1. Pollination services at risk

Pollinators are sensitive bioindicators, which can reveal a lot about the state of the wider environment (Kevan

1999). In terms of agricultural sustainability, they contribute to the functional integrity of the system, as

suggested by Thompson (2007). They provide the arthropod-mediated ecosystem servive (AMES) of pollination

in agricultural landscapes (Isaacs et al. 2009). In general, world agriculture is becoming more pollinator

dependent, since an increasing share of agricultural land is being devoted to insect-pollinated crops (Aizen et al.

2008). Therefore, a landscape which is able to support healthy populations of pollinators is more likely to be

productive as well in the long run (Klein et al. 2007). In recent years, pollination as an ecosystem service has

been gaining increasing attention (Kremen et al. 2002).

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Recently a phenomenon, in which worker bees from honey bee colonies suddenly disappear,

named the ´Colony Collapse Disorder´ (CCP), has attracted a considerable amount of attention both from the

media and the general public. Although the abrupt disappearances of this kind are not new to the history of

apiculture, was the incidence of these events greatly increased in the United States during the summer of 2006.

Some European countries have since followed, reporting similar incidents. These collapses can obviously cause

great economic losses both for the beekeepers themselves and other farmers, who rely on bee pollination for

their crops. The current downhill of beekeeping has also to do with the import of cheap Chinese honey,

combined with the rising costs from varroa control (Watanabe 1994). Furthermore, beekeeping is mainly done

by ageing farmers as a side-business or a hobby, and rather few younger people are willing to start in the

business (source: Finnish Beekeepers´ Association).

The underlying cause(s) of these collapses are probably complex. Some studies point strongly to

viruses, such as the Israel acute paralysis virus (Cox-Foster et al. 2007). Other factors suggested span from other

diseases all the way to cellular phones. Whatever the exact causes turn out to be, the discussion seems to have

already led to a better understanding of the importance of alternative pollinators. This pollination need argument

can and has been used to justify conservation efforts of bumblebees and solitary bees (Williams 1995, Steffan-

Dewenter et al. 2005; but see Ghazoul 2005a,b). Outside the academia, the issue has been addressed by the UN

Food and Agricultural Organization (FAO 2007) as well as some NGOs (Non-Governmental Organizations)

(Spagenberg 2008).

A diverse native bee community is the best insurance for the pollination services of any crop, due

to the yearly fluctuations in the populations of individual species (Kremen et al. 2002). In general, a diverse

community of pollinators maintains a diverse plant community (Fontaine et al. 2006), and vice versa

(Biesmeijer et al. 2006). Furthermore, a diverse community of functional pollinator groups may increase seed

set in cultivated plants even within a season (Höhn et al. 2008). A striking example of the risks involved in the

reliance on honey bees as the sole pollinators comes from the almond (Prunus dulcis) growing region of the

Central Valley in California, USA. Large-scale monocultures of almond dominate the landscape, leaving little

space for the nesting and foraging habitats of solitary bees and bumblebees. Each spring, large numbers of

honey bee colonies need to be transported to the region to satisfy the pollination needs of the crop. In case of

problems with beekeeping, the almond industry may be facing a major crisis due to pollination deficits. In such

systems, more effort should be put into the development of alternative pollination methods, such as testing the

requirements of solitary bees (in the case of almond, Osmia lignaria) for overwintering and thereby optimazing

their emergence (Bosch et al. 2000).

A contrasting example with the almond system comes from the watermelon growing region of

the United States, in which this ´insurance value´ of native pollinators was studied by Winfree et al. (2008). The

results, both empirical and simulated, showed that native bees are the most important pollinators of this crop.

Empirical total pollen deposition was significantly correlated with native bee, but not with honey bee visitation.

Native bees were sufficient to pollinate the crop at a large majority of the studied farms, making this area better

buffered against honey bee losses than the Central Valley of California. Furthermore, the amount of deposited

pollen by native bees did not correlate with the distance to woodland nor with the proportion of woodland at a 2

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km radius. Therefore it is likely, that other species than wood-nesting solitary bees were responsible for the

pollination. This is in contrast with the situation in tropical ecosystems (Klein et al. 2003). Indeed, the source

areas of pollinators in temperate ecosystems are often other habitats than forests, such as meadows and other

patches of semi-natural vegetation (Öckinger & Smith 2007). In intensively cultivated landscapes, only minor

areas of such habitats remain. The density of solitary bees measured as individuals per hectare of landscape is

known to increase, as the percentage of refuge habitats in the landscape increases. Monotonic landscapes, in

contrast, support pollinator populations dominated by the honey bee (Banaszak 1992). As regards to

bumblebees, their species richness was positively correlated both with land use heterogeneity and the proportion

of grassland at a 10 x10 km square scale, in the landscape level study of Pywell et al. (2006). Westphal et al.

(2006), on the other hand, found no such effect.

Ricketts et al. (2008) present a synthesis of 23 crop pollination studies, representing 16 crops on

five continents. Pollination services were evaluated in relation to the distance from natural or semi-natural

habitats. Visitation rates declined steeply, reaching half of their maximum at a distance of 0.6 km from these

habitat patches. Pollinator species richness halfed at 1.5 km. Evidence of an actual decline in fruit and seed set

was less clear, but still visible. In an effort to connect such trends with crop yield, economic models for

pollination have been developed. Morandin & Winston (2006) present a cost-benefit model for canola (Brassica

campestris) production. Yield and therefore profit could be maximized in such landscapes, in which 30 % of

uncultivated land remained within a radius of 750 m from the field edges. In such landscapes, the seed set of

canola was higher due to the higher bee abundance in the fields. Furthermore, Kevan & Phillips (2001) present

an economic model, that can be used to measure some of the economic impacts of pollinator deficits.

2.2. Bumblebees as pollinators

In terms of the value or efficiency of different pollinators, it is important to realize that an observed visit by an

insect to a flower does not necessarily lead to its pollination. This is an important aspect to consider when

modelling plant-pollinator networks (Devoto et al. 2007). Thomson & Thomson (1992) suggested three groups

of pollinators in the context of pollen collection and deposition: ´the good, the bad and the ugly . Both the good

and the ugly pollinators collect large amounts of pollen. The good ones deposit this pollen efficiently during

subsequent visits, whereas the ugly ones steal most of it from the plant´s point of view. Finally, the bad

pollinators both collect and deposit minor amounts of pollen only. In a study made in the USA with four apple

(Malus x domestica) varieties (Golden Delicious, Starkrimson Delicious, Empire/MacIntosh and Rome), the

honey bee acted as an ugly and bumblebees as good pollinators. The authors conclude, that better pollination

service is achieved as a result of bumblebee visits, even when honey bees are present at the same time

(Thomson & Goodell 2001). Fruit crops hold high economic value worldwide and have been identified as the

most vulnerable crops in case of pollinator loss. In fact, possible pollination limitation already exists in the apple

(Gallai et al. 2009).

Bumblebees possess many other ecological as well as physiological properties that make them

valuable pollinators. In comparison with other insects, bumblebees are known to fly in harsher weather

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conditions. They are often observed flying in drizzle, something which at least butterflies and solitary bees

rarely do. Aften spells of heavy rain the foraging activity increases, in order to compensate for the lack of

energy inside the colony (Teräs 1976b, Lundberg 1980). This is because bumblebees do not collect large stores

inside the hive in the way that honey bees do, but live ´from the hand to the mouth´ instead (Heinrich 1979). A

continuous supply of forage plants is therefore needed and in turn, is continuosly pollinated by the bumblebees.

The bumblebee colony is started by an overwintered queen in the spring, when other pollinators

are still scarce. At this time, some honey bee colonies have died out during the winter and in the remaining ones

the bee numbers are at their lowest. Bumblebee queens, due to their large size and thermoregulatory ability, fly

even during such cold spells of weather, when other insects are inactive (Heinrich 1979). The cold tolerance is

better in the spring than in the autumn (Pekkarinen & Teräs 1977) and queens can fly in a colder weather than

workers (Heinrich 1979). According to Lundberg (1980), temperature poses a limit to flight activity in the

mornings, but in the evenings this limit is set by both the temperature and light. The wind speed limit for

foraging in bumblebees is rather high, around 13 m/s (Pekkarinen & Teräs 1977). In addition, bumblebees visit

more flowers per time unit than the honey bees do (from 10 to 20 flowers/minute on the average) (Heinrich

1979).

Bumblebees are strong fliers, which readily fly over less suitable foraging areas in order to find

more suitable ones. This is not true for all pollinating insects, such as the butterflies. In the study of Fry &

Robson (1994), the scarce copper (Lycaena virgaurea) avoided flying over areas of high vegetation. Saville et

al. (1997) carried out a corresponding mark-recapture study on bumblebees and found out, that the bees flied

over pine/spruce forests in order to find forage patches. The bees returned time after time to the same patch, that

is, they manifested patch-fidelity. Bhattacharya et al. (2003) conclude, that roads and railroads do not represent

major barriers for the movement of bumblebees. They may, however, further facilitate the separation of

populations due to this natural patch-fidelity of foragers.

Foraging distances of bumblebees can be up to kilometers, which has its implications for the gene

flow between isolated native plant populations on the positive side and the possible gene flow from GM crops

on the negative side (Kreyer et al. 2004). The foraging ranges of solitary bees are much smaller, in the range of

few hundred meters at most (Gathmann & Tscharntke 2002). In the experiment of Dramstad et al. (2003),

bumblebee workers significantly increased their use of a flower patch after their nests had been moved to more

than 100 m away from it. Some hypotheses have been presented, as to why bumblebees do not necessarily

collect the nectar very close to their nest. This may be an adaptation to avoid cuckoo bumblebees, or other

enemies and parasites (Dramstad 1996). Furthermore, since bumblebees are aiming to optimaze their energy

intake, it may be economic for them to fly even to a rather distant forage patch, in case this patch holds a high

energy value (Heinrich 1979).

Osborne et al. (1999) tracked B. terrestris in an agricultural landscape with harmonic radar and

indicated a mean foraging distance of 275 meters. This mean distance may vary greatly between species,

however. Walther-Hellwig & Frankl (2000) suggest, that differences may exist in the orientation capabilities of

bumblebees at the level of both species and individuals. In their experiment, B. terrestris performed the longest

foraging trips (mean 663 m) and B. muscorum the shortest (mean 55 m). B. lapidarius lied between these

extremes with 260 meters. Knight et al. (2005) indicated ranges between 450 and 758 meters for four common

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British species by using an interesting molecular method (see also Darvill et al. 2004). Variation between

individuals was large in B. lucorum and B. lapidarius. Stenström & Bergman (1998) used the mark-recapture

method for overwintered bumblebee queens, indicating large foraging areas in the case of this caste as well.

In small habitat fragments, the alteration of bumblebee behaviour may have implications for the

pollination of their food plants (Goverde et al. 2002). On the other hand, habitat fragmentation may act more

strongly on solitary bees (Steffan-Dewenter & Tscharntke 1999) than on bumblebees (Lopes & Buzato 2007)

due to the differences in foraging ranges. Furthermore, most of the declining species of solitary bees are habitat

and food plant specialists (Biesmeijer et al. 2006). This is a further argument in terms of the high potential of

bumblebees as (alternative) pollinators. Bumblebees manifest high connectance values in plant-pollinator

networks both in field studies (Forup et al. 2008) and simulations (Memmott et al. 2004) and should be seen as a

potential group to be included in ecological restoration projects. In the study of Dunne et al. (2002) on the

network structure and biodiversity loss in food webs, robustness increased with connectance. It appeared

independent of species richness and omnivory. As in other studies, the food webs were more robust to random

removals, than removals of species with most trophic connections.

Besides the apple, bumblebee queens are valuable pollinators of the currants (Ribes sp.) as well

as forest berries, such as the bilberry (Vaccinium myrtillus) and the lingonberry (V. vitis-idae) (Nousiainen et al.

1978). Motten (1986) studied the plant-pollinator network in a spring wildflower community in North Carolina,

USA. They detected pollinator-limited reproductive success in the subset of the community pollinated by

bumblebee queens, but not in the one pollinated by flies and solitary bees. Later in the season, the successful

seed production of the red clover (Trifolium pratense), for example, depends mainly on visits by long-tongued

bumblebee species (Teräs 1976a, Delaplane & Mayer 2000). Furthermore, many rare meadow plants, in

particular those with long corolla tubes, are strictly bumblebee pollinated, or at least their seed production is

significantly increased as a result of bumblebee visits (Kwak et al. 1996, Pekkarinen & Teräs 1998). In a

modern European agricultural landscape, it is for plant species ´very common to be rare´ (Bratli et al. 2006).

Therefore, the disappearance of bumblebees could have dramatic effects on plant populations.

2.3. The colony cycle of bumblebees

Temperate bumblebees form annual colonies, started by an overwintered queen in the spring. The colony cycle

goes through five stages: queen overwintering, queen foraging, nest initiation, colony growth and reproduction

(Fig. 1).

2.3.1. Queen overwintering

Bumblebee queens hibernate in the ground, preferring north-facing banks or slopes. In the spring, the first

overwintered queens are observed when the mean day temperature reaches + 4 oC and when this temperature

has stayed permanently above the freezing point (0 oC) for at least three weeks. The timing of the emergence

varies between species in southern and central Finland. For example B. lucorum emerges in late April, B.

pascuorum in early May and B. distinguendus in late May (Pekkarinen & Teräs 1977). In northern Finland all

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the species emerge simultaneously as the snow melts, in order to take advantage of the short growing season

(Pulliainen 1979).

Figure 1. The colony cycle of Bombus, modified from Pr s-Jones & Corbet (1991).

Hibernation, that is diapause, in bumblebees is assumed to be obligatory and terminated by a rise in

temperature. One would therefore expect that bumblebees need a period of chilling before post-diapause activity

can commence, which would in turn facilitate the synchronisation of the life cycle and prevent queens from

terminating diapause before spring. Hodek & Hodková (1988) and Hodek (1996) argue that this importance of

chilling in diapause termination has been overestimated, while Larrere et al. (1993) did find a minimal period in

their experiment. They were unable to break the diapause in B. terrestris queens with a rise in temperature alone

if the queens had hibernated for only 3 months, in which case it could only be terminated by anaesthetising the

queens with CO2. After 5 months, in contrast, a rise in temperature was sufficient to break the diapause.

Diapause survival and post-diapause performance in B. terrestris queens was experimentally

tested by Beekman & van Stratum (2000), in order to define the optimal conditions of commercial mass-rearing

for the purpose of greenhouse pollination. A treshold wet body weight (0.6 g) prior to the hibernation was

detected, below which the queens died. In the case of the surviving queens, weight did not affect their egg-

laying capability. The authors conclude, that the metabolic rate in diapausing queens is independent of

temperature, and that the duration of diapause is the most important determinant of survival. Preoviposition is

under the control of both temperature and time, so that high temperature during diapause and its long duration

lead to a shorter preoviposition period (= period before the start of eff-laying).

In addition, the diapause experience may affect colony characteristics, such as sex ratio and

colony lifetime. Beekman & van Stratum (2000) experimentally increased the diapause length from 0 to 4

nest initiation

colony growth

queen foraging

reproduction

queen overwintering

workers produced

queens andmalesproduced

males (andworkers) die

queenssearchfornestingsites

queenssearch forfoodplants

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months, in which case the total number of workers and colony lifetime increased, whereas the number of young

queens decreased. Furthermore, the shorter the diapause, the longer the time period until the first sexual was

produced. Non-diapause colonies would therefore be the most time-constrained ones in terms of reproduction.

2.3.2. Queen foraging

After emerging the queens immediately start foraging for nectar and pollen. Nectar is essential for gaining

energy and the proteins in the pollen are needed for the development of the ovaries (Pekkarinen & Teräs 1977).

Only a limited number of plant species flower in early spring, which opens a possibility for intensive

competition in the attraction pollinators. Therefore many early-flowering plants, such as the bilberry, secrete

generous amounts of nectar to attract their flower visitors. On the other hand, pollinators may compete with

each other. In bumblebee queens this competition may reduce the level of energy intake, which in turn can

postpone the onset of egg-laying (Heinrich 1979).

A parasite, which strongly affects the behaviour of foraging overwintered queens, is Sphaerularia

bombi, a parasitic worm known from almost all the species of bumblebees (Schmid-Hempel 2001). The

prevalence of infection can be high, varying between 12 to 90 % according to some estimates (Lundberg &

Svensson 1975, Pekkarinen & Teräs 1977, Pr s-Jones & Corbet 1991). The worm attacks young queens at their

overwintering sites and prevents the normal development of their ovular glands, therefore preventing egg-

laying. While the majority of conspesific healthy queens have already initiated a colony, the infested queens

continue foraging for their own needs only. Finally the weakened queens return to their overwintering sites and

die, giving the parasite an opportunity to spread further to other queens using the same site later on.

2.3.3. Nest initiation

Some days or weeks after emerging the queens begin to search for a nesting place, during which period they can

be seen flying in a typical zigzag pattern close to the ground and inspecting potential nesting sites more closely.

This behaviour is commonly used to indicate the nesting habitats, since actual bumblebee nests are difficult to

find (Fussell & Corbet 1992b, Svensson 2002). Osborne et al. (2008), however, argue that this very behaviour is

an indication of not yet having found a nest site and queens might spend more time searching in less suitable

habitats than in the better ones.

As to how exactly do the queens choose their nesting places, remains largely an open question.

Suzuki et al. (2007) built a model based on energy intake rate at known sites. The model worked well, when

using mid-May values, but failed when using those of late April. The authors present two reasons behind the

result. First, queens may indeed choose the sites based on the food availability that they experience, but colonies

become extinct in poor sites later in the season. Thus the net energy intake during May would affect colony

persistence. Second, queens may select to nest in their maternal nest locations, in which food availability will

increase again in May, unless the spatial distribution of flowers changes dramatically from year to another.

As regards to habitat types, nest-seeking queens were observed most frequently along forest and

field boundaries and in open uncultivated areas, whereas they were least frequent in forests and in clearings, in

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the study of Svensson (2002). Fields, pastures and road boundaries had intermediate frequencies. At the

landscape level, the relatively open landscape was most favoured by the queens. Differences among species

were detected in terms of both this favoured landscape type and habitat preferences. B. terrestris, B. lapidarius,

B. sylvarum and B. subterranius preferred open terrain, whereas B. lucorum and B. pascuorum preferred forest

boundaries. Withered grass and tussocks characterized the preferred nest-seeking patches in all of the species.

As an example of a rare species, Diekötter et al. (2006) identified ditch banks as an important nesting habitat for

B. muscorum. Potential sites in these kinds of habitats are more visible early in the season, before becoming

covered with protective vegetation. This means a trade-off in terms of early and late establishment (Kells &

Goulson 2003). Furthermore, bumblebee nests may suffer from farming activities. This is especially true when

it comes to species, which build their nests above the ground surface. Subterranean nests face different threats,

such as flooding. In addition, wet springs may be more detrimental to them than to above-ground nests due to

increased susceptibility to mold (Harder 1986).

Above-ground nesting species, such as B.ruderarius, often place their nests in tussocks of grass

and below-ground nesting species, such as B. soroeensis, in old rodent holes (Goulson 2003). In below-ground

nests, the tunnel leading to the nest cavity can even be half meter long (Pekkarinen & Teräs 1977). Some

species, such as B. pascuorum, make both kinds of nests. B. lucorum and B. hypnorum nests can also be found

in bird nest-boxes and buildings (Pekkarinen & Teräs 1977). Cavities with good insulation allow for the fast

development of the colony, since the larvae need a temperature of over 30 oC to develop (Heinrich 1979). B.

lapidarius, in particular, is known to prefer direct exposure to sun when choosing nesting sites (Kells &

Goulson 2003). Furthermore, based on the inner structure of the nest, can bumblebee species be divided into

pollen-storers and pocket-makers. The former are regarded as a more developed group, since they feed their

larvae by regurgitating a mix of pollen and nectar, in the same way as the honey bees do. They store the pollen

into used larval cells and wax cells, while the latter group builds small wax pockets, in which they store the

pollen pellets. Pollen-storers include, among others, B. lucorum, B. lapidarius, B. pratorum and B. hypnorum

and pocket-makers include B. hortorum, B. pascuorum, B. distinguendus and B. veteranus (Pekkarinen & Teräs

1977).

After finding a suitable site, the queen lays her first batch of eggs on a clump of pollen she has

collected. She then incubates the eggs by lying over them, while simultaneously drinking up nectar from the

wax pot she has constructed, keeping the temperature of the eggs up to 25 oC above the ambient temperature.

During incubation the queen actively regulates the temperature of her abdomen, which is in contrast with the

situation in flight, where only the thorax temperature is regulated. This is an energy consuming process

(Heinrich 1979) and a limited availability of food plants can therefore slow down colony development.

Artificial food supplementation with nectar and pollen has been shown to lead to larger colonies and higher

reproductive success, the latter being the actual measure of colony fitness. Increased food availability at the time

of colony initiation may not only accelerate colony growth, but also allow the founding queen to remain with

the brood for longer periods of time, therefore preventing attacks both by other bumblebee queens and cuckoo

bumblebees (Psithyrus) (Pelletier & McNeil 2003).

The competition for nesting places can be intense and several dead queens, killed by sequential

intruders, are sometimes found at their entrances in the spring (Pr s-Jones & Corbet 1991). Alternatively,

13

colonies formed by several species are a possible outcome, in case the first queen has already produced workers

(Heinrich 1979). Furthermore, the possible ngative effect of B. terrestris on the populations of other species

seems to be mainly through the competition for nesting sites. The species may either be able to usurp already

occupied nests or has an advantage due to its early emergence (Inoue et al. 2008). Other authors suggest, that

competition is of minor importance and varies substantially between years and habitats (Kells & Goulson 2003).

The level of parasitism by Psithyrus varies greatly between species and populations (Goulson 2003). In the

study of Bolotov & Kolosova (2006), the percentage of Psithyrus increased from 2-3 % to 15 % along the

Russian Karst – Karst-glacial landscape gradient. The pattern could not be completely explained by the

abundance of the hosts, although the connection was often distinct. In some cases Psithyrus numbers were low,

even though Bombus numbers were high.

Nest densities of bumblebees can be rather high in considering, how rarely nests are actually

found. Harder (1986) recorded up to 1 nest per 200 m2, while Knight et al. (2005) recorded densities in the

magnitude of some tens per square kilometer (26, 29, 68 and 117 for B. pratorum, B. terrestris, B. pascuorum

and B. lapidarius respectively). In the study of Osborne et al. (2008), the highest density of nests was recorded

in gardens (35.9 nests/ha). This approximates to one nest in every two gardens, in case there are 69

gardens/hectare, typical of the countryside in the study area. Non-linear habitats in general had significantly

fewer nests per unit area than linear habitats, whereas gardens with compost heaps/bins and bird nest boxes

supported more nests than expected. In terms of the linear habitats, fence lines (37.2) and hedgerows (29.5)

supported high numbers, while densities were lower in woodland edges (19.9). Grasslands (with vegetation > 10

cm), grasslands (with vegetation < 10 cm) and woodlands had 14.6, 11.4 and 10.8 nests respectively.

In terms of the availability of nest cavities, it would be interesting to know, in which habitats are

most of the old rodent holes found. There is some evidence that the activity of small mammal species, such as

bank voles (Clethrionomys glareolus), is greater near field boundaries (Tattersall et al. 2002). In the study of

Askew et al. (2007) small mammal populations in farm woodlands, permanent set-asides as well as two and six

meter wide field margins were compared. Greatest numbers were caught in the two meter field margins and

margins next to grasslands with tall, rather than low vegetation supported higher numbers. In the case of the

bank vole, highest numbers were detected in two meter margins next to tall grassland fields as well as those

with a two meter strip cut every two or three years. The field margins were, however, presumably too narrow or

too young for field voles (Microtus agrestis) to inhabit. The primary habitat of this species is unmanaged

grassland (Jepsen et al. 2005). In woodlands, large numbers of wood mice (Apodemus sylvaticus) were captured.

2.3.4. Colony growth

The diploid eggs laid by the queen develop into workers, which will start foraging after two days from

emerging. Since the foraging bees need only nectar for their own nutrition, all harvested pollen is carried to the

nest and fed to the larvae (Heinrich 1979). The total number of workers in a colony varies between species. In

Finland numbers can reach 300 in B. lucorum and B. lapidarius at the strongest time of the colonies (Pekkarinen

& Teräs 1977). Several factors can set a limit for the speed of colony growth, such as food plant availability,

weather factors and competition for food plants. In addtion, a variety of parasites and diseases occur on

14

bumblebees (McFarlane et al. 1995), which may lessen the ability of the infected individuals to utilize floral

information (Gegear et al. 2006). Furthermore, these parasites and diseases typically exhibit condition-

dependent virulence, so that weak individuals and colonies are more easily attacked than strong ones. This same

phenomenon is known from the honey bee and has been widely discussed in relation to the CCD. Newly

founded colonies may be especially susceptible, since weather conditions are often adverse for prolonged

periods of time at the beginning of the season (Brown et al. 2000).

Some diseases may infect both honey bees and bumblebees, such as the deformed wing virus

(DWV) (Genersch et al. 2006). A variety of nest parasites well known by beekeepers, such as the wax moth

(Aphomia sociella), attack bumblebees as well. Due to the global trade in honey bee packages and bee queens,

parasites and diseases readily disperse to new areas. Some of these, such as the small hive beetle (Aethina

tumida), may switch to bumblebees (Hoffmann et al. 2008). Another possible route of infection is from the

greenhouses. Nosema bombi, a gut parasite, seems to be more common in commercial colonies used for crop

pollination, than in the field. In the study of Colla et al. (2006) this pathogen was three times more prevalent

among bumblebees near greenhouses, than elsewhere. Another intestinal pathogen, Crithidia bombi, was

detected in 15 to 27 % of the wild bumblebees foraging close to greenhouses and in none of those collected

elsewhere by Brown et al. (2000).

Competition for food plants may limit the number of pollinator species and individuals, which

forage on a patch at any given time. Within bumblebees, competition occurs between the colonies of the same

species in particular and between those species with similar tongue lenghts, such as B. lucorum and B.

hypnorum (Teräs 1985) as well as B. lucorum and B. terrestris (Ings et al. 2005). As a result of competition, the

growth speed of the colonies remains below the physiological maximum (Heinrich 1979). The temporal and

spatial variation in the dispersion of floral resources, however, strongly controls the composition of bumblebee

communities, and may facilitate the coexistence of species (Ranta & Vepsäläinen 1981, Ranta & Tiainen 1982).

There are some habitats in which forage may be so abundant, that competition becomes a minor factor. Red

clover fields typically support many species for this reason (Ranta & Vepsäläinen 1981).

Competition occurs between bumblebees and other pollinating insects as well. It can sometimes

take a direct form, the honey bee being at times very aggressive on flowers. More usually competition takes the

indirect form of disturbance, in which case a slower forager is outcompeted by a faster one. In this context

bumblebees as fast foragers have an advantage in most cases. For example, syprhid fly densities are often low

where bumblebee densities are high (discussion with Jan-Peter Bäckman). Steffan-Dewenter & Tscharntke

(2000) did not find any evidence of strong competition between honey bees and other bees on meadows, while

Goulson & Sparrow (2008) did detect a reduced worker size of bumblebees in areas with honey bees. In the

study of Thomson (2006), the mean number of bumblebee foragers on a given transect increased in concert with

distance from introduced honey bee colonies.

2.3.5. Reproduction

Later in the summer new reproductive individuals (males and queens) are raised in bumblebee colonies. The

new queens being genetically identical to workers, the pathway of egg development is controlled by feeding.

15

Some colonies may produce males, some new queens and some both. Some colonies fail to raise either, in

which case the genes of the founder queen are not passed on to future generations. There are several factors

affecting the time of reproduction, such as the size of the colony, conflicts between the queen and her workers,

possible parasites and diapause length (see chapter 2.3.1. on the latter). Large colonies seem to be more

successful in terms of reproduction (Goulson 2003). Otti & Schmid-Hempel (2008) showed, that B. terrestris

colonies infected by N. bombi failed completely in producing sexual offspring.

Males emerge from haploid, unfertilized eggs and can therefore be produced also by the workers.

They do not forage for the colony, while the new queens can bring back pollen and nectar when sometimes

returning to the nest before mating. When mating has taken place the new queens search sites for hibernation

and the colony cycle is completed. On average only one new queen per colony will be successful in starting her

own colony the following spring, even if several hundreds of new queens are produced. Some individuals may

fail to find a suitable overwintering site and there will be some mortality during hibernation, while major factors

are the limited amount of suitable nesting sites and food plant availability the following spring (Heinrich 1979).

2.4. Environmental change and bumblebees

2.4.1. Changing agroecosystems

The agroecosystem is a key concept in agroecology (Gliessman 1997). Agricultural ecosystems possess several

features, that distinguish them from natural ecosystems. Cultivated fields, and monoculture fields in particular,

usually manifest low species diversities, the cycling of nutrients in them is fast and the level of nutrient-loss is

high (Tivy 1990). The field ecosystem, as one particular example of an agroecosystem, can be described by a

conceptual model, in which the flows of matter, energy and information are indicated. The subsystems in the

case of a spring cereal field, for example, would be represented by the crop plants, herbivores and decomposers

(Schulze & Mooney 1994). In such models, the pollinator component is often ignored, even though it has high

functional significance.

2.4.1.1. Habitat terminology

Such terms as ´habitat , ´patch , ´landscape , ´site´ and ´territory´ come up frequently in (landscape) ecological

literature, but it is not always clear, what is exactly meant in each case. Furthermore, there seems to much

confusion in the uses of habitat ´selection´, ´preference´, ´use´ and ´requirement . The following account is

based on Hall et al. (1997), Morrison et al. (1998) and Danielson (1999).

The combinations of different biotic and abiotic factors can indeed result into distinct habitat

types. Therefore the term habitat is an useful tool for classification. A patch is an area of a single habitat type

and patches of different types in turn combine into a landscape. From an animal’s point of view, either several

patches, one patch or part of a patch can be a site, which it needs to survive and to reproduce. The sufficient

amount of sites in a landscape is therefore the precondition of survival for any species. For territorial species, a

site corresponds with territory.

16

The term habitat selection should only be used when referring to the process by which innate

behavioural decisions are made by an animal searching for a suitable habitat patch. The result of this process

should be referred to as habitat preference. When a habitat preference has evolved, a species prefers some

habitat type(s) over other(s). The term habitat use can be used to express the presence of a habitat type in the

species’ habitat repertoire. No active decisions are made by the animal in question and in this case the frequency

in the repertoire equals the frequency in the environment. Habitat requirement is the appropriate term when

referring to the habitat types which are vital for the survival of a species.

It is important to realize, that each species has its own unique evolutionary history. In any habitat

patch the species are not only interacting both with the other species and the environment, but are limited by

their evolutionary histories. Furthermore, the history of the habitats themselves, such as the cultivation history

in the form of past crop rotation regimen, is a factor contributing to the level of species diversity in any

landscape (Burel et al. 1998). The structure of an agricultural landscape as a whole has a socio-economic

background (Baudry et al. 2003).

2.4.1.2. Landscape elements

From a perspective of landscape ecology, agricultural ecosystems consist of different landscape elements (Olson

1995). In intensively cultivated areas, linear landscape elements, such as ditches with their associated field

margins, provide structural and biological diversity important to many species, such as the declining Ortolan

bunting (Emberiza hortulana) (Vepsäläinen 2007). Different landscape indices can be used to describe this

landscape structure. For example, the number, size and shape of the different elements, the sequence in which

they appear in the landscape, the number of ecotones as well as landscape connectiviness, diversity and

evenness can be described (Olson 1995, Dramstad et al. 1996). Hietala-Koivu et al. (2004) studied the landscape

structure changes of a 100 hectare area in southern Finland, between the years of 1954 and 1997. They point out

to the marked homogenization of the landscape, as measured by Shannon’s diversity and evenness indices. At

the same time, the patch numbers, class areas as well as total edge lengths of ditch margins decreased, mainly

due to the subsurface drainage.

When one habitat type dominates the landscape, other habitat patches are said to be embedded in

a matrix (Olson 1995). To a large extent, central European agricultural landscapes fall into this category. For

example in the province of North Holland in the Netherlands, the landscape is clearly dominated by permanent

grass pastures grazed by sheep and dairy cows, cities and villages being embedded in this matrix (pers. obs.). In

Finland, as a very rough generalization, the spring cereal fields could be seen as the habitat type forming the

matrix in the very South of the country, whereas in the more northern parts this would be the coniferous forests.

Ecotones connect two habitat patches, that is landscape elements, with each other. The smallest

patches may consist entirely of ecotone (Hansen & di Castri 1992, Olson 1995). At a margin of a cultivated field

and a forest, wind speed grows in the forest, whereas the forest shades the field. These kinds of ecotones are

characterized by a mixture of species from both of the connecting habitats, which makes them species-rich

environments in many cases. Landscape connectiviness in general is an important concept when studying the

movements and dispersal of organisms in the landscape mosaic (Dramstad et al. 1996, With et al. 1997, Beier &

17

Noss 1998, Tischendorf & Fahrig 2000). Baudry et al. (2003) discussed the possibility of increasing this

connectivity by farming activities. They concluded that in any particular farming system, the physical and field

pattern constraints overweigh any minor changes caused by these activities and that the connectivity therefore

remains largely the same over years. Furthermore, they stressed the importance of forest patch localization in

terms of connectivity.

In intensively cultivated agricultural landscapes, field margins and riparian corridors can act as

ecological corridors of dispersal. Open field margins are important for meadow species (Dover et al. 1990, Fry

& Robson 1994), while riparian corridors can serve a similar function as regards to forest species (Haas 1995).

There is good evidence that bumblebees perceive and utilize such linear features as landmarks when foraging

(Cranmer 2004). A preference of bumblebees for linear features was also noted by Öckinger & Smith (2007),

who found higher densities of foraging bumblebees in them than in the neighboring semi-natural grassland,

despite the latter habitat having a greater diversity and abundance of flowering plants (see chapter 2.3.3. on nest

densities). In a review on the biodiversity value of non-cropped landscape elements (so-called green veining) in

Europe, the role of the linear elements was seen in connecting the different parts of the network, while the patch

elements were seen as nodes within the network of all elements. These nodes (such as meadow patches) support

a major part of the biodiversity found in the landscape (Grashof-Bokdam & van Langevelde 2004). In addition

to biodiversity benefits, linear elements may have other functional roles in the landscape, such as nutrient

capture along waterways (Ma et al. 2002).

2.4.1.3. On the importance of scale

Different study scales are used in landscape ecology, depending on the objectives of the study as well as the size

and mobility of the study organism (Urban et al. 1987, Olson 1995, Roland & Taylor 1997, Morrison et al.

1998, Saab 1999). The mechanisms influencing the composition of animal communities may be inferred from

the patch to the landscape scale (Thomas 2000). As a generalization, the smaller and the more immobile the

species in question is, the more precise should be the scale (McGarigal & Marks 1994).

When studying the quality of field margin vegetation from the point of view of a butterfly, for

instance, the vegetation should be mapped more accurately than when studying the significance of the same

field margin for a bird or a mammal (Olson 1995, Hewison et al. 2001). In the case of the butterfly the crucial

question is, whether suitable nectar as well as larval food plants are available in the habitat. Furthermore, even a

slight increase in the windiness of a field margin can make it less attractive for butterflies (Kuussaari et al.

2007). A bird, such a starling, perceives the landscape in a different manner. For its populations to thrive, the

share of permanent pastures of the landscape has to be sufficient, since its insect food is found in this habitat.

Furthermore, it needs old trees or nest boxes for breeding (Rintala 2007). However, even different pollinating

insects may respond to landscape context at different scales (Steffan-Dewenter et al. 2002) and no general rules

relating species diversity to habitat or landscape features exist. Furthermore, the yearly fluctuations of

populations call for long-term studies, before any reliable picture of scale-dependence can be acquired

(Jeanneret et al. 2003a,b).

18

The importance of scale becomes evident when considering disturbance in ecosystems. In forest

ecosystems the downfall of an individual tree can be regarded as a small-scale disturbance, whereas an

extensive forest fire can be regarded as a large-scale one (Urban et al. 1987). In the context of agroecology,

major disturbances include farming activities taking place in the agricultural landscape. In the study of Burel et

al. (1998), the diversity of various groups of organisms was compared along an land-use intensity gradient.

Breeding passerines, woody plants and small mammals appeared as the taxa being least affected by agricultural

intensification. The scale of study can vary from a chosen study plot inside an agricultural field all the way up to

the landscape level (Fig. 2). In this same hierarchy framework, the speed of change grows towards the level of

the plot. Individual farmers change the landscape both during one season when cultivating and harvesting their

fields and from one year to another by crop rotations (Olson 1995, Tiainen et al. 2004). Political decisions take

place at much higher levels of the hierarchy, however, even at an international level. This takes place mostly

through the common agricultural policy (CAP) of the EU.

Figure 2. The hierarchy levels of agroecosystem study, modified from Tiainen et al. (2004). The speed of landscapeprocesses and change grows towards the plot level, whereas the number of levels and actors in the decision making processgrows towards the landscape level.

2.4.1.4. Rarity and abundance in bumblebees

Bumblebee populations have suffered declines in several countries in the past few decades (Williams 1986,

Allen-Wardell at al. 1998) and Finland is no exception (Söderman 1999). As regards to species occurring

mainly in agricultural landscapes, the populations of B. distinguendus and B. ruderarius have possibly

decreased (Söderman & Leinonen 2003), whereas B. humilis is classified as being a near threatened species in

our country (Rassi et al. 2001). At the same time, B. veteranus and B. subterranus have apparently dispersed to

new areas (Söderman 1999). The declines are now widely regarded as a consequence of changing land-use

practices and intensified agriculture in particular (Williams 1986, Goulson 2003). The resources needed by

bumblebees are first, a suitable site for starting the colony (Fussell & Corbet 1992b, Svensson 2002) and

changelevels

19

second, a continuous supply of suitable flowers to provide nectar and pollen during the whole colony cycle

(Fussell & Corbet 1992a, Mänd 2000), both of which can be lacking in modern agricultural landscapes

(Goulson 2003). However, the discussion on the exact mechanisms behind the declines continues. Controversial

issues include the significance of tongue length and diet breadth (Goulson & Darvill 2004, Goulson et al. 2005,

Williams 2005). Recently, Kleijn & Raemakers (2008) approached the question by comparing museum

specimens prior to the 1950´s and specimens from a present study in the UK, Belgium and the Netherlands.

They found that the number of plant taxa in the pollen loads taken of declining species was almost one-third

lower than that of stable species.

Two concepts, rarity and abundance, are of central importance in relation to the distribution

patterns of species. The classification is from rare to common in the former case and from scarce to abundant in

the latter. The difference between these two concepts is easier to understand, when looking at a distribution

pattern at two different scales, for example at that of a habitat patch and that of the national level. According to

Williams (1988), common bumblebee species, such as B. pascuorum and B. lapidarius, are generalists in

relation to habitat type. These species readily exploit man-made environments, such as gardens (Goulson et al.

2006). In Great Britain they are almost ubiquitous (´occurring anywhere´) in the southern part of the country, in

other words, they have a wide distribution. This is not to say, that they appear in high numbers at any particular

location. Rare species, such as B. ruderarius and B. jonellus, are restricted to particular habitat type(s). In the

UK, these two species are encountered only where sufficient areas of suitable (heathland) habitat, such as old

meadows or sand dunes, remain (Williams 1988).

The concept of abundance and its connection with that of rarity has to be understood at the level

of a habitat patch (Williams 1988). Common species are often more abundant than rare species, even in those

habitat types preferred by the latter. This has been explained by the marginal mosaic model and the abundance

of resources. In some cases rare species can be locally abundant as well, such as B. distinguendus on clover

fields in Finland (Teräs 1976a). Likewise, B. ruderarius can reach high densities on traditionally managed

meadows (Söderman & Leinonen 2003). According to the marginal mosaic model, more resources are available

in these habitats, than in the surrounding matrix, which is why rare species can persist there even at the edges of

their distribution (but see Sagarin et al. 2006). An interaction of the species climatic niche and food plant

reductions has indeed been used to explain which species have declined, where they have declined and how they

have declined in the UK. Williams et al. (2007) suggest that declining species have narrower climatic niches. In

Ireland, late-emerging bumblebees (B. distinguendus, B. ruderarius, B. sylvarum and B. muscorum) are in

decline and there is a clear westward shift in the ranges of these species (Fitzpatrick et al. 2007). Remaining

populations are found in a wide range of habitat types, as long as they have been left outside modern agriculture.

The authors further suggest that moving from hay to silage production has led to a lower flower availability in

late summer, which has been harmful for bumblebee populations in general. Of course, the species may react

differently in different countries. In Ireland, even B. lapidarius is declining and seems to avoid city areas,

whereas in Finland this species is one of the most ´urban´ species of bumblebees (Bäckman 1996).

Bumblebees in general are less demanding in relation to the habitat type than are solitary bees,

whose distribution is controlled by the fact that they typically collect pollen from just one or a few plant species

(Pekkarinen & Teräs 1998, Söderman 1999). According to Banaszak & Cierzniak (2000), B. lapidarius and B.

20

pascuorum are typical species in small forest islands surrounded by cultivated fields. Söderman & Leinonen

(2003) suggest that B. soroeensis builds its nest at road sides and forages on different types of meadows,

whereas B. pratorum is frequently recorded at forest margins and openings, but avoids large areas of forest and

urban areas. This species is said to be particularly abundant in those habitats, in which willows are abundant. In

this thesis, the bumblebee species are divided into forest species, open landscape species and generalists,

according to Bäckman & Tiainen (2002). Again, the same species may clearly behave differently in different

countries. Banaszak (1983) regards B. lucorum as a forest species, since in Poland this species prefers areas with

a high percentage of forests in the landscape, those of the pine-oak type in particular. In the case of B. lucorum

the picture is further complicated by the fact, that some authors fail to mention, whether they are discussing the

B. lucorum species complex as a whole or just one of its species. In Finland, B. lucorum is regarded as a typical

countryside species, B. magnus is known to prefer old-growth forests and B. cryptarum is most commonly

recorded in such forest habitats, where the coverages of bilberry and heather (Calluna vulgaris) are high

(Söderman & Leinonen 2003). In this thesis, the B. lucorum complex is treated as one (generalist) species.

2.4.1.5. Agricultural landscapes in Finland

Together with the Mediterranean countries and Austria, Scandinavian croplands have the highest ecosystem

quality values found in Europe (Reidsma et al. 2006). Some of our farm types, however, have little to offer in

terms of species diversity. In the newer member states of the EU, agriculture is still less intensive and, as a

consequence, associated farmland biodiversity is higher in general (discussion with Irina Herzon). The major

trends in the areas grown with different crops in Finland during the past decades are shown in Fig. 3. While the

area of spring cereal fields has increased considerably, the area of grasslands has decreased. The statistics on

grasslands include pastures and clover grassland fields, the latter being especially beneficial for bumblebees

(Klejin & Raemakers 2008). Red clover fields within the flight-range from the nests of B. muscorum have been

shown to be essential in terms of the colony growth in this species (Diekötter et al. 2006). Unfortunately, most

land use scenarios indicate even further decreases of pasture area in Europe (Rounsevell et al. 2005, Busch

2006).

Meadows and natural pastures are among the most diverse of all Europan ecosystems

(Alanen 1996). It is estimated that traditional agriculture with natural pastures and mowing has had positive

effects on about 30 to 40% of plant species in our flora. Unfortunately, there are now only about 20 000 hectares

of these traditional agricultural biotopes remaining in Finland, an area which is only about 1% of the 1 610 000

hectares in the late 1800´s (Vainio et al. 2001). The vegetation of these habitat types typically needs continuous

or periodical disturbances in the form of mowing or grazing, in order to maintain their high plant and insect

diversities. Management is especially beneficial for solitary bees and rare bumblebees, but benefits common

species as well. Carvell (2002) found a negative correlation between the densities of B. lucorum and B.

lapidarius and vegetation height. The correct timing and intensity of management is of paramount

importantance, since early mowing and intensive grazing can destroy food plants. According to Banaszak

(1992), a major threat to bumblebees in Poland is too intensive sheep grazing. Cattle grazing is more beneficial

for the bumblebees, leaving parts of the vegetation higher and thus conserving nectar and pollen sources.

21

1920 1940 1960 1980 20000

15 000

5 000

10 000

Muu

Heinä, nurmi, laidun

Kevätvilja

SyysviljaViherkesantoAvokesantoP

elto

ala

(km

2 )

Figure 3. Field areas of different crops and set-asides in Finland, between the years of 1920-2003 (data: Juha Tiainen.)

Field margins are important bumblebee foraging and nesting habitats. As a consequence of subsurface draining,

the amount of field margins has decreased drastically in our agricultural landscapes (Tiainen et al. 2004). The

percentage of subsurface-drained out of the total area of cultivated fields increased from 10 % in the year of

1959 to 70 % in the year of 1995. In this situation, road verges have become increasigly important foraging

areas for bumblebees, although road construction may result in the loss of potential nesting sites (Bhattacharya

et al. 2003). They comprise a major fraction of the area of semi-natural vegetation in modern agricultural

landscapes. In SE Norway, for instance, the percentage of unploughed open land rarely exceeds 15 % (Bratli et

al. 2006). But not only has the amount of field margins, but also the quality of the remaining ones decreased.

Pesticides can kill bumblebees either on the fields themselves or when these substances drift to field margins. In

addition, weed control substances can affect the bumblebees indirectly by depleting the source of suitable food

plants (Dover et al. 1990). Furthermore, the extensive use of fertilizers has led to the development of eutrophic

vegetation on field margins and in ditches. Our field margins are now mainly dominated by tall, nitrogen-

favoring species, such as Elymus repens and Urtica dioica (Kuussaari et al. 2008). In main ditches shrubs, such

as willows (Salix), have become more common, which has led to even further decreases in the area of open field

margins. Benefiters of this development include some bird species, such as the whitethroat (Sylvia communis),

the red-backed shrike (Lanius collurio), the thrush nightingale (Luscinia luscinia) and the common rosefinch

fallow (unsown)

spring cereal

winter cerealset-aside (sown)

other

grassland crops

km2

year

22

(Carpodacus erythrinus) (Väisänen et al. 1998). As a consequence, there are now less flowering plants of value

to bumblebees, such as clovers (Trifolium) or vetches (Vicia) on these field margins (Kleijn & Snoeijing 1997,

Kleijn & Verbeek 2000). In the study of Tarmi et al. (2002), V. sepium was recorded on 46 % of the studied

plots in the Uusimaa province, but the coverages were very small (median < 1 %).

2.4.2. Climate change

During the past century, the mean annual temperature has increased by 0.7 oC in Finland. As a consequence, the

start of the growing season has become 2-2.8 days earlier per decade in the years of 1965-2007. The largest

increase in temperature has occurred in the spring months, the flight period of overwintered bumblebee queens

(Kaukoranta & Hakala 2008). In the whole of Europe, the average advance of spring and summer has been 2.5

days per decade, according to a meta-analysis by Menzel et al. (2006), during the years of 1971-2000. This

trend can have positive implications for agriculture in the form of increased crop productivity (Ewert et al.

2005), but there are downsides as well. In Finland, the rising temperature may cause problems since most of our

crop varieties are adapted to low temperature and long days during the growing season (Peltonen-Sainio 2009).

Furthermore, pollination and other ecosystem services may suffer through direct and indirect effects on useful

organisms. In the context of this study, it will be important to detect any modifications in the interaction

between overwintered bumblebee queens and their spring-flowering food plants.

Actual extinctions (Thomas et al. 2004) as well as temperature related range shifts (Root et al. 2003)

have been reported in a wide variety of organisms (but see Sagarin 2001). In butterflies these shifts have been

extremely fast (Pöyry et al. 2009). The eleven distribution clusters of bumblebees in Fennoscandia follow fairly

closely to the bioclimatic vegetation zones, which are in turn strongly correlated with the effective temperature

sum (ETS) during the vegetative period (Pekkarinen & Teräs 1993). This could mean that changes are to occur

in our bumblebee communities, in case warming continues. In Great Britain, some species are already spreading

northwards due to the warming climate and may be replacing locally native species in the mountainous areas

(Goulson & Williams 2001, McDonald 2001).

Interacting species may react differently to the rising temperature, which uncouples their occurrence in

the environment. Major selection pressures are likely to occur in this context, but the exact nature of the

evolutionary responses remains to be seen (Bertin 2008). Furthermore, Visser & Both (2005) point out that

positive records of mistimings may be more frequently published than negative ones. A well known example of

a clear timing mismatch comes from the pied flycatcher (Ficendula hypoleuca). In the Netherlands, a mistiming

of food availability (peak caterpillar abundance) and the arrival time of this bird from its wintering areas has

been reported by Both et al. (2006). Higher spring temperatures in Central Europe have facilitated the migration

of the first-arriving individuals, uncoupling arrival and breeding dates (Ahola et al. 2004). Examples from

insects include mainly moths and butterflies. Schweiger et al. (2008) modelled the potential spatial mismatch of

a monophagous butterfly and its larval food plant, whereas Visser & Holleman (2001) pointed out to the poor

synchrony of the winter moth (Operophtera brumata) and its larval food plant, the oak (Quercus robur), in

recent warm springs. A contrasting example is the sycamore-sycamore aphid –system, in which

23

synchronization is achieved, even though the temperature tracking mechanisms of the plant and the insect are

slightly different (Dixon 2003).

2.4.2.1. Implications for plant flowering

Plants use integrated information from multiple environmental cues to coordinate their growth and development

with favorable seasonal conditions. Light signals, perceived via the photoreceptors, are especially important in

this process (Franklin & Whitelam 2004) and the onset of flowering in most species is cued by photoperiodism.

Several studies indicate earlier plant flowering during the past decades. As the annual photoperiodic cycle has

not changed during this time, it must be assumed, that alterations of temperature (Abu-Asab et al. 2001) and

precipitation (Peñuelas et al. 2004) patterns are causing the trend. However, excessive heat can mean drier soils,

which in turn can mean less and/or later flowering in some cases (Aerts et al. 2004). The picture is further

complicated by the fact that an elevated CO2 level of the atmosphere may alter plant phenology directly, even

when the warming effect of this gas is not taken into account (Ward & Strain 1999). Large interspecific

differences in these kinds of responses will affect both the structure of plant communities and the gene flow

between species as climate warms (Fitter & Fitter 2002).

Indeed, the break of dormancy seems to be triggered by temperature (Salisbury & Ross 1992).

Ahas & Aasa (2001) distinguished three seasonally different landscape types in Estonia and pointed out, that in

an early year the phenological phases move very fast from the South to the North (mean value of the rate being

3 to 6 days per 100 km). The pattern of distribution of phenological phases in Finland was analyzed in a study

of a phenological time series (Lappalainen 1994). The onset of bird cherry (Prunus padus) pollination was

strongly influenced by lakes in early springs and that of the birches (Betula) very strongly by the Baltic Sea.

Flowering is sensitive to the temperature of the previous month especially in spring-flowering species (Aerts et

al. 2006). However, warm and dry summers are typically associated with earlier flowering the following spring

(Doi et al. 2008). Therefore, instead of using monthly or annual trends, the period during which climatic

variables are best related to phenological events, should be sought for (Badeck et al. 2004). In a phenological

time-series of over 700 years, the full-flowering dates of a cherry tree (Prunus jamasakura) were closely related

to the March mean temperature (Aono & Kazui 2008). A corresponding Finnish study, in which phenological

observations over five decades were used, indicated that the date of flowering can be estimated by using the

ETS (Effective Temerature Sum) as a predictor. Spring-flowering species in the study included Salix caprea,

Ribes rubrum, Anemone nemorosa, Tussilago farfara and Caltha palustris. In the case of the species flowering

in May, the estimate had an accuracy of 3-7 days and in earlier flowering species of 7-14 days. The authors

point out, that in case climate warming proceeds as to date, bud burst in the studied species can be expected to

advance by 4 days per each 1 oC of warming (Heikinheimo & Lappalainen 1997).

In a study on the flowering times of herbarium specimens in Boston, USA, the plants flowered

eight days earlier in the years of 1980-2002 than in 1900-1920 (Primack et al. 2004). An analysis of another

American data set from Washington DC showed, that the first-flowering dates of 100 plant species (such as

Acer, Anemone, Corydalis, Tussilago and Vaccinium) have advanced significantly by 2.4 days during the past

three decades. The trend became even more clear, when species with later first-flowering dates were excluded.

24

The advance corresponded with the 1.2 oC increase in the minimum temperature of the months through

December and May during the study period, so that the average flowering time (in Julian date) showed a

negative correlation with this parameter (Abu-Asab et al. 2001). Yet another data set from the North-Eastern

USA shows an advance of 2 to 8 days in the spring phenology of three horticultural woody perennials, a trend

which corresponds with the general warming pattern during the past several decades (Wolfe et al. 2005).

Similar trends have been reported in Europe by various authors. In Estonia, the early spring

phases of Corylus avellana and Tussilago farfara have become 10 to 20 days earlier during the past five

decades, giving a rate of phenological change of -0.3 to -0.4 days per year. Corylus pollen seasons appear to be

particularly responsive to temperature (Emberlin et al. 2007), while Malus x domestica shows a slightly slower

rate of change (-0.1 to -0.3 days per year) according to Ahas et al. (2002). Fitter & Fitter (2002) compared the

average flowering dates of more than 300 British plant species in the years of 1991-2000 and 1954-1990. All

species pooled together, the advance of flowering was 4.5 days during the past decade. 16 % of the species

flowered significantly earlier and 3 % significantly later than previously. In the former case, the average

advancement was 15 days in a decade. Annuals were more likely to flower early than congeneric perennials, and

insect-pollinated species more so than wind-pollinated ones, an important observation in the context of this

study. The most extreme change was detected in the mainly bumblebee-pollinated Lamium album. This species

used to flower, on the average, on the 18th of March, but during the 1990´s the first flowering date had shifted to

the 23rd of January. In Germany, the phenological phases (such as first flowers open´) of 78 agricultural and

horticultural varieties (e.g. red currant and apple) have become earlier during the years of 1951-2004, with a

mean advance of 1.1-1.3 days per decade (Estrella et al. 2007). Some authors report minor shifts only.

According to Scheifinger et al. (2003) the last frost events of each season have indeed become earlier during the

years of 1951-1997, but the beginning of plant flowering has been largely unaffected by this trend. The species

in the study included such early-flowering species as Tussilago farfara and Taraxacum officinale.

2.4.2.2. The plant-pollinator timing mismatch

It is evident that suitable yardsticks are needed when inferring shifts in (spring) phenology along the different

steps of the food-chain. Not only may the timing of peak food availability change, but also may the width of the

optimal period alter (Visser & Both 2005). In the case of plants and their pollinators, studies on the duration of

flowering and the actual period of sufficient nectar and/or pollen production would cast light on the issue.

Nectar secretion and the quality of the produced nectar, such as its amino acid content, may be sensitive to

rising spring temperature and/or elevated CO2 concentration of the atmosphere (Rusterholz & Erhardt 1998).

When it comes to pollinating insects, the flight periods of butterflies seem to be becoming earlier

in the Northern Hemisphere. In California, the average first spring flight of 23 butterfly species has advanced to

an earlier date over the past 31 years (Forister & Shapiro 2003) and this peak appearance period has advanced in

the UK and the Mediterranean as well (Roy & Sparks 2000, Stefanescu et al. 2003). Gordo & Sanz (2006)

studied the spring phenology of the small white (Pieris rapae) and the honey bee in Spain, during the years of

1952-2004. The appearance time of both species was negatively related to the mean temperature in February to

April, and an earlier appearance was observed since the 1970 s.

25

Studies discussing the actual plant-pollinator mismatch have been rather few. Doi et al. (2008)

report a phenological mismatch in the case of four Prunus species and their potential pollinator, the Small

White, from Japan. The flowering of the trees is best predicted by a time window of 30 to 40 days prior to

flowering, whereas 15 days prior to appearance are relevant in the case of the butterfly. During the ´Prunus

time-window , temperatures have increased during the past few decades, whereas no clear trend is visible during

the ´butterfly time-window . As a result, flowering is occurring earlier than before, whereas the butterflies are

actually emerging later than before. Furthermore, not only has the date of bud burst advanced, but also has the

flowering rate of Prunus accelerated in the later stages of flowering.

Bees utilize the maximum daily temperature as a cue to end their hibernation, whereas spring

ephemerals use a combination of spring temperature and snowmelt as a cue to begin flowering. As a

consequence, spring ephemerals are not properly pollinated in warm springs with sudden snowmelt, because the

bees are still in hibernation (Doi et al. 2008). In some cases, lower snowfall due to warming may actually lead to

later flowering, due to the fact that without the protective cover plants will experience lower temperatures

during the winter, especially at high elevations and northern latitudes. In two arctic bog species, Andromeda

polifolia and Rubus chamaemorus, earlier flowering is induced by increased winter snow cover and spring

warming (Aerts et al. 2004). Furthermore, overwintering bumblebee queens may suffer as a consequence of

decreased snowpack (Inoye & McGuire 1991). Kudo et al. (2004) detected a mismatch in the flowering of

Corydalis ambigua and the emergence of its legitimate pollinator, the long-tongued bumblebee B. hypnorum

koropokkurus. Other species may rob the flower by biting a hole in its corolla tube, in which case pollination

does not occur. The study was carried out in the spring of 2002, the warmest spring during the last 40 years in

Japan. Indeed, extreme weather events such as these are likely to become more frequent as warming proceeds

(Memmott et al. 2007). Most spring-ephemeral plants bloomed 7 to 17 days earlier than usual. The seed set of

C. ambigua decreased drastically in every population and at low altitude study sites in particular, where least

bumblebees were observed at the time of the flowering.

It remains to be seen how widespread these kind of mismatches will be in the future and to what

extent interactors will be able to adapt. Further desynchronization of flowering times may follow in the case of

competition (Bertin 2008). It appears, however, that even without the climate change, the flowering phenology

of some plants, such as various woodland herbs, may not be very finely tuned to the temperature regime and

pollinator activity. In the study of Schemske et al. (1978), individual plants blooming during the flowering peak

of the species in question often had low seed production and pollination-limitation was observed. Most

importantly, long-term monitoring is needed in order to understand the pollination system of a particular species

in relation to climate variability and change. Wall et al. (2003) studied the flowering phenology of a spring-

flowering climber (Clematis socialis), a species which usually flowers in mid-April. In the year of 1996,

unusually cool temperatures in February and March delayed the peak of flowering until late April and early

May. The following year, warm conditions in March resulted in an earlier peak, occurring in early April. This

climatic variability was reflected in which bee species played the role of the most important pollinator. The

solitary bee Anthophora ursine played this role in the year of 1996 and the queens of the bumblebee B.

pennsylvanicus in 1997. This pattern again highlights the need to conserve a diverse pollinator community.

26

3. STUDY OBJECTIVES

The objective of this study was to estimate the suitability of an intensively cultivated agricultural landscape for

the overwintered bumblebee queens, when starting their colonies. By using a field data set, answers to the

following questions were sought for:

I will discuss these questions in the framework of the various factors, which may affect the possibilities of

colony initiation and growth (Fig. 4) and consequently will make an effort to answer the question:

Figure 4. Overview of the factors which regulate the possibilities of nest initiation and colony growth in bumblebees, asreviewed in this thesis.

habitatalteration

- changes in theavailability of foodplants and nesting

places

changes inrodent

populations- numbers of

suitable nestingcavities

contemporaryweather

conditions-opportunities for

foraging

competition fornesting placesand food plants

spread ofBombusterrestris

-competition withnative species

parasites anddiseases

climate change- diapause lengthin bumblebees- nectar secretionin plants- timingmismatches

possibilitiesof colonyinitiation

and growth

How is the interplay between queen phenology and food plant availability in this landscape?

What are the densities in the different habitat types and how do they fluctuate during the spring?

Which other properties of the line-transects are important for high queen densities?

What kind of mitigation strategies can be targeted at the starting stage of bumblebee colonies?

27

4. MATERIALS AND METHODS

"The recent discussion on the future of plant–pollinator interactions clearly reveals that understanding thespatio-temporal dynamics of floral resources at the landscape scale is a precondition for the discriminationbetween causes and effects. In many cases, plant–pollinator interactions can only be studied under fieldconditions because confined pollinator movement and missing context of floral resources prevent realisticresults in laboratory experiments." (Frankl et al. 2005)

4.1. Study area

The data were collected in the spring of 2000 between 25th of April and 2nd of June. The study area (Fig. 5),

situated in Lammi, southern Finland (61o 05’N, 24 o 00’E) consisted of ten large (from 95.2 to 240.3 hectares)

areas of farmland, which in turn consisted of various landscape elements, such as cultivated fields, small patches

of forest and field margins. These individual study areas were separated from each other by main roads, lakes

and forest belts, and had different landscape structures and main types of agricultural production (Bäckman &

Tiainen 2002).

Hauhiala E

Hampaanmaa

Ruosuo

Pääjärvi

Pappila

biologinen asema

Jahkola

Vanha-Kartano

Porkkala

Parikkala

Ormajärvi

Kivismäki

Ylänäinen2 km

Hauhiala P

Figure 5. Map of the study area, cross = Lammi church.

Porkkala

Parikkala

Kivismäki

Jahkola

Hauhiala N

Ylänäinen

Ruosuo

Pappila

Hauhiala S

Vanha-Kartano

Hampaanmaa

biological station

Lake Ormajärvi

Lake Pääjärvi

28

4.2. Weather conditions

It was fairly warm and precipitation was low during the study spring (Fig. 6). At the end of April it was warmer

than usual in southern Finland (at Lammi 21.0 oC was reached on 20th April), although the nights were still cold

(Ilmatieteen laitos 2004a). In mid-May there was a long warm period (at Lammi maximum 23.1 oC on 10th May)

and night-frosts were rarer than usual (at Lammi minimum -8.0 oC on 2nd May). The mean temperature of May

was normal, but due to the unusually warm individual days in April and May, the growing season advanced

rapidly. It was 10 days earlier than usual at the beginning of June (Ilmatieteen laitos 2004b,c). Growing season

is the period, during which daily mean temperatures remain continuously above 5 oC.

Early April was rainier than usual due to the two low-pressure areas moving over southern

Finland. From late April until late May the precipitation was low, however, and during my field period the daily

amount exceeded 2 mm only on three days: 25th May (3.1 mm), 26th May(11.6 mm) and 2nd June (2.7 mm)

(Ilmatieteen laitos 2004 a,b). On 25th May and 26th May planned counts could not be carried out. In early June a

colder and rainier period begun. The average temperature of the whole month was lower than usual and the

typical summer showers came earlier than normal in the year of 2000 (Ilmatieteen laitos 2004c).

2.4 12.4 22.4 2.5 12.5 22.5 1.6

-10

0

10

20

30

Co

daily max.daily min.normal max.normal min.

0

10

20

30

40

50

study period

mm

precipitation

Figure 6. Weather conditions (daily maximum/ minimum temperature and precipitation) during the study spring (from 25th

April to 2nd June 2000); normal max. and normal min. are the long-term averages over ten years (data: Lammi biologicalstation).

29

4.3. Data collection

Westphal et al. (2008) compared the performance of six sampling methods in describing bee communities

(observation plots, pan traps, standardized and variable transect walks as well as trap nests with reed internodes

or paper tubes). The pan trap method, a method which avoids collector bias, produced the highest sample

coverage and was the best indicator of total species richness. The line-transect method (Banaszak 1980, Teräs

1983, Dicks et al. 2002) is, however, still the best available method for studying plant-pollinator interactions. It

is an effective method for assessing insect communities across habitats and seasons (Potts et al. 2005).

4.3.1. Line-transects

I carried out the bumblebee counts three times in six and four times in four of the study areas (Table 1). The

counts were made between 9.00 a.m. and 18.00 p.m. in good weather conditions, while walking slowly along

inventory routes. The routes were divided into line-transects according to habitat type.

Table 1. Study dates during each of the four counts. Starting time varied in order to avoid systematic error: a.m. = in themorning, p.m. = in the afternoon. Ylänäinen was counted starting at alternating ends of the counting route, due to the factthat one whole day was needed to count this area during each count. Hauhiala was counted in two parts (southern part:Hauhiala S and northern part: Hauhiala N).

Study area 1. count 2. count 3. count 4. count

Jahkola 25.4. a.m. 9.5. p.m. - 28.5. a.m.

Pappila 26.4. a.m. 7.5. p.m. 17.5. a.m. 28.5. p.m.

Hampaanmaa 26.4. p.m. 7.5. a.m. 17.5. p.m. 27.5. a.m.

Ylänäinen 27.4. a.m. 8.5. a.m. 18.5. a.m. 31.5. a.m.

Hauhiala S 28.4. a.m. 9.5. a.m. - 30.5. p.m.

Hauhiala N 4.5. a.m. - 15.5. p.m. 30.5. a.m.

Ruosuo 4.5. p.m. - 15.5. a.m. 2.6. p.m.

Kivismäki 5.5. p.m. - 16.5. a.m. 2.6. a.m.

Vanha-Kartano 6.5. a.m. - 16.5. p.m. 31.5. p.m.

Porkkala 3.5. p.m. 10.5. a.m. 21.5. a.m. 1.6. p.m.

Parikkala 3.5. a.m. 10.5. p.m. - 1.6. a.m.

The placement of the routes varied between the counts (Appendix 1), which is due to the fact that the location of

the flowering forage patches was not known beforehand. For example, grassland fields did not have any

flowering plants in early May and therefore no transects were placed on them during the first two counts.

Indeed, Westphal et al. (2008) conclude, that variable transect walks produce a higher sample coverage (%) and

a number of detected species than standardized walks. The downside of this method is, that the pollinator

community on the same exact transect can not be compared between different counts.

30

In various previous studies on bumblebee densities (Teräs 1983, Fussel & Corbet 1991, Lagerlöf

et al. 1992, Dramstad & Fry 1995, Bäckman & Tiainen 2002), two meter wide transects have been used. In this

study the width was chosen to be five meters, since the queens are larger and therefore easier to identify than

workers. Only on grassland fields was the width two meters, due to the high bumblebee densities and the

presence of workers. This does not introduce bias in data interpretation, since bumblebee density typically

grows in parallel with patch size (Heard et al. 2007). The length of the transects varied between 40 and 350

meters.

The habitat types were:

forest boundary between a forest and a field (FOF)

forest boundary between a forest and a road (FOR)

grassland field (field sown with grass and/or clover seed, either to be mown or used as pasture) (GFI)

garden (GAR)

field margin between two fields (FMF)

field margin between a field and a road (FMR)

streamside/riparian corridor (or other moist area with tall shrubs and trees) (RIP)

ruderal patch (semi-natural vegetation, such as barn surroundings or a small meadow) (RUD)

The main compass direction (South/West/North/East) of forest margins was noted in the field and so was the

type of the ruderal patches (shrubby/open, the latter with no shrubs or trees). In the case of the field margins

(FMF, Fig. 7 and FMR, Fig. 8), their width with an accuracy of 0.5 meters (of both the margin itself and the

ditch, if present) and the ditch type were checked from large-scale digital maps, based on the interpretation of

orthophotographs (1:5000). The ditch types were: main ditch, which runs directly to rivers and lakes and other

ditch, which runs into main ditches. There were also field margins with no ditch adjacent to them (so-called

temporary field margins). The field margins (total width) of main ditches were in general wider than the other

two types: their mean width was 7.8 meters, whereas the other ditches were 4.5 meters and the temporary

margins 2.9 meters wide on the average.

31

ojaluiska (kosteaa, monivuotistakasvillisuutta)

B

C

A

muokattu reunus (yksivuotista,avointa kasvillisuutta)

tasainen osa (monivuotistakasvillisuutta)

viljelykasvi

Figure 7. The structure of the field margin area between two fields. The area, from which the bumblebees were counted inthis study (A) and in the study of Bäckman & Tiainen (2002) (B). In field margin vegetation studies, the plants are ususallyinventoried in the flat part only (C) (see Tarmi & Helenius 2000, Tarmi et al. 2002).

luiska

tie tasainen osaviljelykasvi

oja

valtatie

luiska

oja

viljelykasvi

Figure 8. The structure of the field margin area between a field and road (upper panel) or a main road (lower panel).

ditch

crop

flat part(perennial vegetation) tilled margin

(open; annual vegetation)

slope(moist; perennial vegetation)

croproad flat part

slope

ditch

main road

slope

ditch

crop

32

4.3.2. Bumblebee and food plant records

The nomenclature of the bumblebees follows Pekkarinen & Teräs (1977). The caste (queen or worker) based on

the individual’s size and behaviour (foraging or searching for a nesting site) were recorded. Some individuals

were caught to be identified later at the biological station. Cuckoo bumblebees were identified as a group as

well as were those individuals belonging to the B. lucorum species complex (referred to as B. lucorum from

now) (Fig. 9). The former is due to the difficulty in telling two common species (P. bohemicus and P. sylvestris)

apart.

The food plants of foraging bumblebees were identified at the species or genus (Salix and

Taraxacum) level according to Hämet-Ahti et al. (1998). Occasionally binoculars had to be used in order to

count bumblebees foraging in high willows (Salix) or Norway maples (Acer platanoides) and to identify them to

species. In some occasions it was only possible to estimate the total number of Bombus and Psithyrus in these

trees. During the study period flowering shrubs and trees were drawn on a large-scale map so that the area on

the map equalled the coverage (m2) of the flowering canopy in the field. In addition, the coverage of flowers

(%) of Taraxacum and the bulbous corydalis (Corydalis solida) was estimated for each line-transect. It would

have been even better to collect this data on all flowering species, since pollinator visitation rate in relation to

flower abundance can not be compared, if the data is unavailable. For example the cow parsley (Anthriscus

sylvestris) is a common plant flowering on field margins in late May and early June. The plant is, however,

rarely visited by bumblebees.

Figure 9. A queen belonging to the B. lucorum species complex, foraging on Salix. Photo: Eeva-Liisa Alanen.

33

4.4. Data analysis

4.4.1. Rarefaction

I performed a rarefaction analysis of the data, using the WWW Rarefaction software, situated at:

www.biodiversity.org.uk/scripts/palaeo/datasys/rare.pl. This was done in order to evaluate, whether the sample

sizes were sufficient to describe the bumblebee communities of the study areas. The calculations were made

both for the separate study areas and the combined data sets. The expected number of species E(Sn) for different

sample sizes and the 95 % confidence intervals for the combined data sets were calculated.

4.4.2. Flower visits

I calculated the Shannon´s diversity index (H´) and evenness index (J´) (Hutcheson 1970) both for the plants

and for the bumblebees, using the BIODIV software (Baev & Penev 1991). This was done in order to get an

impression of the potential of the food plants in supporting bumblebee diversity as well as the potential of the

different bumblebee species as pollinators of the early-flowering plant species. It must be noted, however, that

the values of these indices are highly sensitive to the number of records. As regards to the bumblebee records,

Psithyrus was included as one species. Evenness indices were only calculated for species with more than 10

observations (Teräs 1985).

The formulae used were:

H´ = - pi ln pi

J = H /ln S.

For the plants the terms in the indices were:

pi = the proportion of visits paid by the ith bumblebee species

S = the total number of bumblebee species visiting the plant species

For the bumblebees the terms were:

pi = the proportion of visits paid to the ith plant species

S = the total number of plant species visited by the bumblebee species.

4.4.3. Bumblebee densities

Bumblebee densities (individuals/hectare) were calculated for each line-transect and count ([number of

bumblebees/transect length x width]/10 000). Both the total densities, the densities of foraging and nest-seeking

queens and the densities of each species were calculated. Species were further divided into ecological species

34

groups (open landscape species/forest species/generalists) according to Bäckman & Tiainen (2002) and the

corresponding densities were then calculated.

Bumblebee densities in different habitats were compared by ANOVA and a t-test was performed

for ruderal patches. Before performing the analyses, the bumblebee densities were log10 -transformed. Stepwise

linear regression analysis was performed for the bumblebee densities and the availability of food plants (m2 or

%). This analysis was carried out, in addition, for the bumblebee densities on field margin transects, using the

´width´ as an explaining variable in three different manners: 1) the width of the field margin itself, on which the

transect was placed, 2) the width of the ditch adjacent to it and 3) the width of the total area, including the

former two and the field margin on the other side of the ditch. A level of significance of P < 0.05 was used. The

analyses were performed using the SPSSTM –package (version 11.0).

4.4.4. Landscape structure of the study areas

In order to describe the structure of the study ares, the following landscape indices were calculated using

ArcViewTM and its FragstatsTM (McGarigal & Marks 1994) program (Patch AnalystTM extension).

total landscape area (TLA, ha)

class area (CA, ha)

mean patch size (MPS, ha)

patch size standard deviation (PSSD)

number of patches (NumP)

edge density (ED, m/ha)

landscape level diversity (Shannon´s diversity index, SDI)

landscape level evenness (Shannon´s evennes index, SEI)

The patch classes used by Bäckman & Tiainen (2002) were changed in some cases and the number of the

classes reduced, in order to achieve a better correspondence with the real situation of the study spring. Finally,

there were 15 element classes (Appendix 5). In the original maps, the cultivated fields were classified according

to crop, which would have been out of date information for the purpose of this analysis. Since the placement of

grassland fields and permanent set-asides varies relatively little from one year to another, their share of farmland

in each of the study areas was counted. Kendall correlation coefficients (rK) were then calculated, in order to

detect any correlations between bumblebee densities and the landscape structure of the study areas during each

count.

35

5. RESULTS

5.1. Bumblebee phenology

I recorded 11 species of bumblebees (Table 2) and two species of cuckoo bumblebees. The total number of

individuals was 3711, of which 3526 were queens and 185 workers. 189 of the queens were nest-seeking

individuals. Out of all individuals, 3371 bumblebees were identified at the species level, 181 as cuckoo

bumblebees and 159 remained unidentified. Most of the unidentified individuals were recorded during the

second and third counts, and most of these individuals were observed foraging on the maple (93 individuals)

and on the willows (66 individuals). During the last count, after the flowering of both of these plants had ended,

none of the individuals remained unidentified. 67.3 % of the identified bumblebees belonged to the B. lucorum

species complex. As regards to cuckoo bumblebees, one P. rupestris was identified in the field, foraging on the

apple on the 31st of May and four samples were later identified as P. bohemicus individuals.

Table 2. The recorded bumblebee species and some details of their ecology: a) abbreviations of species’ names used in thisstudy, b) scientific names, c) ecological species groups: o = open landscape species, f = forest species, g = generalist,according to Bäckman & Tiainen (2002) (Psithyrus = forest species), d) the timing of emergence from hibernationaccording to Pekkarinen & Teräs (1977) and the first observation dates of e) foraging queens, f) nest-seeking queens and g)workers in this study, h) the size of the colony according to Løken (1973), i) nest placement according to Söderman et al.(1997) (holes = nest below the ground in a hole, surface = nest above the ground, for example among grass tussocks,holes/surface = nest placement varies according to the local conditions), j) classification into short-, medium- and long-tongued species and k) the actual proboscis (prementum + glossa) length (mm) of queens according to Pekkarinen in Teräs(1985).

a b c d e f g h i j k

DI Bombus distinguendus o late May 1.6. - - - holes long 11.18

HO Bombus hortorum o early May 5.5. 2.6. 2.6. large varies long 14.60

HY Bombus hypnorum f late April 25.4. 26.4. 17.5. large varies short 9.17

JO Bombus jonellus f early May 7.5. - - small holes short 7.94

LA Bombus lapidarius o late April 25.4. 25.4. 30.5. large varies medium 10.85

LU Bombus lucorum -complex * g late April 25.4. 25.4. 28.5. large holes short 8.47

PA Bombus pascuorum g early May 26.4. 26.4. 2.6. varies varies medium 10.62

PR Bombus pratorum f late April 26.4. 26.4. 21.5. small varies short 9.29

RU Bombus ruderarius o early May 25.4. 18.5. - small surface medium 10.11

SO Bombus soroeensis f late May 15.5. - - small holes short 8.97

VE Bombus veteranus o early May 31.5. - - small surface medium 9.44

* referred to as B. lucorum in the text; includes B. lucorum, B. magnus and B. cryptarum.

36

I recorded both foraging and nest-seeking queens during each count (Fig. 10), but the percentage of nest-seekers

was at its highest at the third count (7.2 %). During the other counts the percentages were, in order, 6.7 %, 3.7 %

and 4.4 %. Workers were encountered at the third (5 individuals) and fourth (180 individuals) counts. The

percentages were 0.6 % and 20.5 % respectively. The species, which I recorded already during the first study

day (25th April), included B. hypnorum, B. lucorum, B. lapidarius and B. ruderarius, whereas B. distinguendus

and B. veteranus were only recorded during the last three days of the study (31st May, 1st June and 2nd June). The

three individuals of B. jonellus were recorded during the second and third counts.

1. count 2. count 3. count 4. count0

400

800

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food Q nest Q workers

Figure 10. The abundance of foraging queens (food Q), nest-seeking queens (nest Q) and workers duringeach count.

591

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LU LA HY PA PR SO HO RU VE DI JO B P0

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4. count (n = 880, 10 species)

Figure 11. The percentages of the different bumblebee species during each count (n = total number of individuals duringthe count). For the species abbreviations, see Table 2.

37

Nest-seeking queens were recorded in seven out of 11 species of bumblebees. Workers of these same species,

with the exception of B. ruderarius, were recorded as well. The queens of Psithyrus started both foraging and

seeking for their hosts’ nests on the 7th of May and were at their most abundant during the third count (12.1 %).

The number of species recorded during each count increased from seven to ten species during the

study period (Fig. 11). As late-emerging species started emerging, the percentage of the most abundant species,

B. lucorum, started diminishing towards the end of May. The percentage of B. lucorum was 74.7 %, 70.1 %,

52.6 % and 44.8 % during each count. B. hypnorum, another early-emerging species, showed a slightly different

pattern. During the first and last counts its percentage was around 10 %, while during the second and third

counts the species was less abundant (6.3 % and 4.0 % respectively). The percentage of B. lapidarius, yet

another early-emerging species, increased towards the end of the study period. The abundance of B. rupestris

started growing only until the end of the study period, although the first individual of this species was recorded

already on the 25th of April.

5.2. Comparison of study areas

5.2.1. Differences in bumblebee records between study areas

The total of species was at its lowest in Hauhiala South and at its highest in Kivismäki, Porkkala and Parikkala.

Ylänäinen had by far the most individuals, being the largest of the study areas and Porkkala, the smallest of the

areas, the least (Appendix 2, Table 3).

According to the rarefaction, the expected number of species, with the same sample size, varied

between the study areas during the different counts (Fig. 12). This is because the growth of the species number

with increasing sample size ceased faster in some areas than others. In Ruosuo, for example, the number of

species did not grow considerably with sample sizes larger than 40 individuals during the first count. As another

example, the expected number of species in Porkkala grew slowest during the first, but fastest during the other

counts. In some areas the observed number of species was either smaller or larger than expected, when looking

at the combined data sets (Fig. 13). During the last count, for example, the number of species was higher than

expected in Porkkala and lower than expected in Hampaanmaa and Pappila.

The mean total density of bumblebee queens, counted over all transects, was 29.5 individuals per

hectare during the first count and 67.5 ind./ha, 39.9 ind./ha and 40.0 ind./ha, in order, during the other counts.

The mean total densities in the different study areas are presented in Fig. 14. Since the number of transects in

the different habitat types varied between the study areas (Table 4), I will not further discuss these densities.

38

0 20 40 60 80 100 120 140 160 180 2001

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Pappila

Figure 12. E(Sn) for the separate study areas.

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E(S n)

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n)

Figure 13. E(Sn) and 95 % confidence intervals for the combined data sets.

39

Table 3. Species richness (sp) and abundance (ind) of bumblebees in the different study areas (Psithyrus = one species).

Jahk Papp Hamp Ylän HauS HauN Ruos Kivi Vanh Pork PariI (sp) 4 4 5 5 5 5 5 6 4 2 4(ind) 17 30 49 50 46 89 78 140 77 27 172II (sp) 7 7 6 7 6 - - - - 7 7… 113 129 102 381 219 - - - - 30 151III … - 8 8 8 - 9 5 8 6 6 -… - 124 100 175 - 62 43 200 38 30 -IV … 8 8 7 10 7 8 8 9 8 11 10… 88 146 92 169 43 73 61 44 51 49 64Total 9 9 9 10 7 9 8 11 10 11 11

218 429 343 775 308 224 182 384 166 136 387

1 2 3 40

15

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90 JahkolaPappilaHampaanmaaYl n inenHauhiala SHauhiala NRuosuoKivism kiVanha-KartanoPorkkalaParikkala

indi

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count

Figure 14. The mean total densities of bumblebee queens (individuals/hectare) in each of the study areas, during eachcount. Unidentified individuals are also included in the densities. During the second count the mean density in Hauhiala Swas 194.0 ind./ha (not included in the figure).

Table 4. The habitat types, in which most and least of the transects (by length, m), were counted during each of the fourcounts (I-IV).

Study area I II III IVmost least most least most least most least

Jahkola FMR RIP FMR RIP - - FMR RIPPappila FOF RIP FOF GAR FOF RIP FOF RIPHampaanmaa FOF GAR FOF GAR FOF GAR FOF GARYlänäinen FOF FOR FOF FOR FOF FOR FOF FORHauhiala S FOF FMR FOF FMR - - FOF GFIHauhiala N FMR RIP FMR RIP FMR RIP FMR RIPRuosuo FOF GAR - - FMF GAR FMF GARKivismäki FMF RIP - - FMF GFI FMF GFIVanha-Kartano FMF RUD - - FMF GAR FMF GARPorkkala FMR RUD FMR RUD FMR GAR FMR GARParikkala FMR RUD FMR RUD - - FMR RIP

40

5.2.2. Influence of the landscape structure on bumblebee densities

The results of the landscape analysis are presented in Appendix 5. The largest of the study areas was Vanha-

Kartano (TLA = 240.3 ha), where the total area of agricultural land was at its largest (CA1 = 170.2 ha) and so

was the number of agricultural fields at its highest (NumP1 = 105). In two of the study areas, Hampaanmaa and

Ylänäinen, there were more permanent set-asides and grassland fields, than cereal or oil crop fields (62.3 %,

CAn = 43.2 in the former case, and 61.3 %, CAn = 54.4 ha in the latter). The least of these were found in

Porkkala (5.0 %, CAn = 3.4 ha).

However, the pattern of land-use in an area is better described by the edge density, rather

than the number of patches in a certain class, since the latter depends directly on the size of the area in question.

Based on the edge density of forest patches, the most forest-dominated study of the study areas were Pappila

(ED2 = 93.4 m/ha) and Hampaanmaa (ED2 = 81.0 m/ha). In contrast, the least forested areas were Kivismäki

(ED2 = 26.7 m/ha) and Ruosuo (ED2 = 29.9 m/ha). Furthermore, the most inhabited areas, based on the edge

density of both gardens and buildings, were Hauhiala (ED5 = 99.9 m/ha and ED6 = 37.4 m/ha) and Ylänäinen

(ED5 = 80.2 m/ha and ED6 = 31.1 m/ha) while Jahkola (ED5 = 30.4 m/ha ja ED6 = 11.5 m/ha) and Porkkala

(ED5 = 41.8 m/ha and ED6 = 17.3 m/ha) were the least.

At the level of the total study areas, the edge density of all patches was highest in Parikkala

EDtotal = 1620.5 m/ha) and lowest in Kivismäki (EDtotal = 1170.6 m/ha), meaning that Parikkala was the most

small-scaled of the study areas and Kivismäki the least. The mean patch size (MPS) was at its highest (0.27 ha)

in Kivismäki and lowest (0.15 ha) in Hauhiala, whereas the patch size standard deviation (PSSD) was highest in

Hampaanmaa (1.00 ha) and lowest in (0.58 ha) Hauhiala. The landscape level diversity index was highest in

Pappila (SDI = 2.04) and smallest in Jahkola (P = 1.74), whereas the evenness index was highest in Pappila,

Hampaanmaa and Hauhiala (SEI = 0.75) and smallest in Parikkala (SEI = 0.62).

According to the calculated correlation coefficients, the correlation between bumblebee

density and the landscape structure was weak in general. The density of B. hypnorum positively correlated with

the edge density of gardens during the first count (rK = 0.422, P = 0.045) and the density of forest species

positively correlated with the edge density of forests with during the fourth count (rK = 0.467, P = 0.030) (Fig.

15). Total bumblebee density showed a negative correlation with the mean patch size (MPS) during the second

(rK = – 0.586, P = 0.034) and fourth (rK = – 0.584, P = 0.010) counts. Furthermore, the density of open

landscape species showed a negative correlation with the edge density of forests during the second count (rK = –

0.524, P = 0.049). There were no significant correlations of the dependent variables with the landscape level

diversity or evenness indices.

41

20 40 60 80 100 120

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EDforestsIV rK = 0.467, P = 0.030

Figure 15. Bumblebee density in each of the study areas in relation to landscape indices. Left panel: B. hypnorum againstthe edge density of gardens (ED5 in Appendix 5) during the first count and right panel: forest species against the edgedensity of forests (ED2) during the last count.

5.3. Food plants

5.3.1. Flower visits

The plant species that were visited by the bumblebees belonged to 28 species or genera (Salix and Taraxacum)

(Appendix 3). They were all perennial plants, with one exception, the Red Deadnettle (Lamium purpureum). At

the first count bumblebees visited five, at the second count nine, at the third count 16 and at the fourth count 17

plant species or genera. B. ruderarius had the widest selection of food plants (H´= 1.85; J´= 0.95) and B.

soroeensis the narrowest (H´= 0.25; J´= 0.35). The highest evenness index was that of the unidentified

individuals (J´= 0.98).

Salix, Taraxacum and A. platanoides were the most frequently visited food plants. Taraxacum

had the highest values of both diversity of bumblebees (H´= 1.62) and evenness among the number of visits by

the different species (J´= 0.68). The visits to A. platanoides were clearly dominated by B. lucorum (H´= 0.36;

J´= 0.20). It was the most abundant species visiting Salix as well (J´= 0.43), but in addition nearly all the other

recorded bumblebee species visited this species (H´= 0.95). After Taraxacum, the most frequently visited

herbaceous plant species was Corydalis solida (H´ = 1.40; J´ = 0.87). The flowering of the bush vetch (Vicia

sepium) was at only at its starting phase during the last count, but the plant was already visited by several

species of bumblebees (H´ = 1.17). The visits were clearly dominated by B. pascuorum (J´ = 0.65). The most

frequently visited woody plant, other than Salix and A. platanoides, was the red currant Ribes rubrum. The visits

were dominated by B. lapidarius (H´ = 1.10; J´ = 0.57). At the end of the study period the ornamental Siberian

42

peashrub Caragana arborescens started flowering in gardens and it was visited by several species (H´= 1.45),

but especially by B. lapidarius (J´= 0.66).

5.3.2. Bumblebee density in relation to flower abundance

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Taraxacum (%) on transect (4. count; n = 385)

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Figure 16. Bumblebee density in relation to the abundance of a major food plant during each count: Salix (1. count,transects with a coverage of > 0 m2 included), A. platanoides (2. count, coverage > 0 m2) and Taraxacum (3. and 4. count,coverage 0.5 %). Notice the different scale of the x-axis during the different counts.

The results of the regression analysis for bumblebee densities and food plants shows, that the plant best

explaining most of the variation in bumblebee densities varied between the counts (Fig. 16, Table 5). The

explanatory power (R2) of the models was highest during the last count, in which case the model including the

coverage of flowering Taraxacum on the transect explained 39 % of the variation in the mean total densities of

bumblebee queens. Adding M. domestica improved this explanatory power to 42 % and adding Salix further

improved it to 45 %.

At the first count the total density of the queens was best explained by a model including the total

area covered by flowering willows, but the explanatory power was small (R2 = 0.095). At the second count, A.

platanoides explained the density better than willows did (R2 = 0.047), but adding willows to the model did

slightly improve its explanatory power (R2 = 0.090). At the third count the coverage of Taraxacum gave an

43

explanatory power of R2 = 0.103. Adding A. platanoides to the model improved this to R2 = 0.214 and adding R.

rubrum further to R2 = 0.270. The regression of the latter was negative (ß = – 1.161), while all the other

coefficients in all the models were positive. The coefficient for Taraxacum in the simple model (model 1)

during the fourth count was the highest of all, while the second highest was that of Taraxacum in model 1,

during the fourth count (ß = 0.624) and the smallest (ß = 0.175) that of M. domestica in model 3, also during the

fourth count. According to the analyses, the constant term was necessary in all the models (P < 0.001).

Table 5. The results of step-wise linear regression analyses, in which the density of bumblebee queens (log10- transformed)acted as a response variable and the coverage of major food plants (% or m2) as explaining variables.

count model variable coefficient t P

I model 1 constant (a) 1.582 40.368 < 0.001n = 163, F = 16.827, P= 0.000, R2 = 0.095 SALIX (ß) 0.308 4.102 < 0.001

II model 1 constant 1.831 39.187 < 0.001n = 136, F = 6.659, P = 0.011, R2 = 0.047 A. PLATANOIDES 0.218 2.580 0.011

model 2 constant 1.761 32.844 < 0.001n = 136, F = 6.599, P = 0.002, R2 = 0.090 A. PLATANOIDES 0.238 2.867 0.005

SALIX 0.208 2.506 0.013

III model 1 constant 1.535 34.833 < 0.001n = 167, F = 18.848, P = 0.000, R2 = 0.103 TARAXACUM 0.320 4.341 < 0.001

model 2 constant 1.473 33.979 < 0.001n = 167, F = 22.328, P = 0.000, R2 = 0.214 TARAXACUM 0.371 5.303 < 0.001

A. PLATANOIDES 0.338 4.823 < 0.001

model 3 constant 1.452 34.317 < 0.001n = 167, F = 20.057, P = 0.000, R2 = 0.270 TARAXACUM 0.382 5.635 < 0.001

A. PLATANOIDES 0.330 4.871 < 0.001R. RUBRUM 0.236 3.523 0.001

IV model 1 constant 1.323 35.799 < 0.001n = 191, F = 120.480, P = 0.000, R2 = 0.389 TARAXACUM 0.624 10.976 < 0.001

model 2 constant 1.311 36.195 < 0.001n = 191, F = 68.834, P = 0.000, R2 = 0.423 TARAXACUM 0.621 11.210 < 0.001

M. DOMESTICA 0.183 3.299 0.001

model 3 constant 1.351 35.445 < 0.001n = 191, F = 50.503, P = 0.000, R2 = 0.448 TARAXACUM 0.591 10.673 < 0.001

M. DOMESTICA 0.175 3.221 0.002SALIX -1.161 -2.901 0.004

44

5.4. Role of habitat properties

5.4.1. Habitat type

5.4.1.1. Foraging and nest-seeking queens

During the first count the area covered by flowering willows was highest in riparian corridors, whereas there

were no flowering willows in gardens. During the second count the area covered by flowering A. platanoides

was highest in gardens, whereas the areas were small in all the other habitat types, and on the field margins

between two fields there were no maples. During the last two counts the coverage of Taraxacum was by far at

its highest on grassland fields. Therefore, the density of foraging queens was always at its highest in those

habitat types, in which the most important foods plants during that particular count were at their peaks of

flowering. During the second count, both the willows and the maple played an important role in attracting the

bumblebees. Furthermore, gardens supported relatively high densities of queens even during the other counts,

but during the third one in particular (Fig. 17).

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Taraxacum (%) in habitat type (3. count; r = 0.948 **)

indi

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Taraxacum (%) in habitat type (4. count; r = 0.974 **)

Figure 17. Density of foraging bumblebee queens in each habitat type (see page 30) and the corresponding coverage of animportant food plant during that count. Notice the different scale of the x- and y-axises during the different counts.

45

During the first and second counts the highest densities of foraging queens were counted in riparian corridors

and at the third and fourth counts on grassland fields (Fig. 18). The density of nest-seeking queens was highest

in gardens during the first and last counts, and it was proportionally higher at forest margins, than the density of

foraging individuals. Furthermore, it was higher in boundaries between a forest and a field than those between a

forest and a road. The mean total density of the queens differed significantly (P < 0.05) between the different

habitat types during each count (Table 6).

11823

7 102

126

20

38

8615

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64

89

19

31

9826

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35114

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102 137 12

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FOF FOR GFI GAR FMF FMR RIP RUD0

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FOF FOR GFI GAR FMF FMR RIP RUD0

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FOF FOR GFI GAR FMF FMR RIP RUD0

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nest-seeking queens foraging queens

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4. count (n = 486)

Figure 18. The mean densities of bumblebee queens in the eight habitat types (see page 30), divided into foraging and nest-seeking individuals. The number of transects in each of the habitat types is presented on top of the bars. Notice the different scaleof the y-axis during the different counts. The STD errors are for the total densities.

Table 6. The results of one-way ANOVA for the comparison of the total densities of bumblebee queens in the differenthabitat types. Column source: ´between´ = variation between habitat types, and ´inside´ = variation inside habitat types.

count source SS df MS F P

I between 2221288.2 6 36881.4 7.575 < 0.001inside 2078907.1 427 4868.6

II between 3191085.0 6 531847.5 27.013 < 0.001

inside 6004911.2 305 19688.2

III between 1135665.4 7 162237.9 24.965 < 0.001

inside 2384945.7 367 6498.5

III between 1624945.9 7 232135.1 67.502 < 0.001

inside 1643813.4 478 3438.9

46

5.4.1.2. Ecological species groups

The number of species was at its highest in the same habitat type, as was the number of individuals during each

of the four counts.The densities of the three ecological species groups seemed to vary among habitat types (Fig.

19), although I did not test this statistically due to the small sample sizes. The open landscape species were

especially abundant in gardens and this reflects mainly the occurrence of B. lapidarius, since the densities of the

other open landscape species were very small. The highest individual density of another open landscape species

was that of B. veteranus (3.4 individuals/hectare) during the fourth count on grassland fields.

When it comes to generalists, during the first two counts the densities of B. pascuorum were

relatively small and the total densities reflect mainly the densities of B. lucorum. At the third count, 22.3 % of

the generalists on grassland fields were B. pascuorum. At the fourth count this percentage had dropped to 11.8

%, while in B. lucorum 28.4 % of the individuals on the grassland fields were workers. The density of B.

lucorum workers in this case was 40.5 individuals/hectare and that of queens 124.9 individuals/hectare.

The densities of forest species reflect mainly the occurrence of B. hypnorum, but during the last

two counts also that of Psithyrus. The densities of the latter were at their highest during the third count, in which

case they were clearly at their highest on grassland fields. At the same time the densities of B. lucorum, the

likely host species of most individuals, were at their highest in gardens. The third most abundant forest species

was B. pascuorum, whose densities remained rather small during the whole study period.

0.64

0.4

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Figure 19. The mean densities of all bumblebees (including workers) in the different habitat types (see page 30) duringeach count, divided into ecological species groups (see Table 2). The numbers on top of the bars represent the meannumber of species in the habitat type. The numbers of transects are as in Fig. 18.

47

5.4.2. Ditch type

The main ditch was the ditch type attracting most of the queens during the first two counts, while the temporary

field margins attracted more queens during the last two counts (Fig. 20). The mean total density of the queens

differed significantly between the different ditch types during the whole study period, with the exception of the

third count (Table 7).

45

115

68

29

84 40

34

84

56

43 119

77

1 2 30

15

30

45

60

75

90

1 = main ditch2 = other ditch3 = temporary field margin

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1. count (n = 228)

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2. count (n = 153)

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3. count (n = 174)

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4. count (n = 239)

Figure 20. The mean densities of bumblebee queens in the different ditch types (n = 228 etc.: the number of field margintransects during each count, number of transects per ditch type is presented on top of the bars). Notice the different scale ofthe y-axis during the different counts.

Table 7. The results of one-way ANOVA for the comparison of total densities of bumblebee queens in the three ditch typesduring each count. Column source: ´between´ = variation between the ditch types, ´inside´ = inside the ditch types.

count source SS df MS F PI between 91638.1 2 45819.0 10.576 < 0.001

inside 974823.5 225 4332.5II between 223176.4 2 111588.2 11.870 < 0.001

inside 1410168 150 9401.1III between 3579.7 2 1789.8 2.302 0.103

inside 132926.1 171 777.3III between 4672.7 2 2336.4 5.020 0.007

inside 109831.4 236 465.4

48

5.4.3. Field margin width

The only explanatory field margin variable, which significantly related to the bumblebee queen densities, was

the width of the total field margin area (see chapter 4.4.3.) during the fourth count (Fig. 21, Table 8). The

correlation was negative and weak (R2 = 0.186).

0 2 4 6 8 10 12 140

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field margin area width (m), 4. count (n = 239)

Figure 21. Bumblebee queen density during the fourth count, according to the width of the field margin area (m) (n =number of field margin transects). The outlying point represents an exceptionally high density on one field margin inHampaanmaa (186.1 ind./ha). When leaving out this record, the explanatory power of the model was further weakened (n =83, F = 17.604, P = 0.000, R2 = 0.179), but the statistical significance of the dependence was, however, maintained (ß = –0.423, t = – 4.196, P = 0.000). The constant termn was still necessary in the model (a = 1.530, t = 28.461, P = 0.000).

Table 8. An example result of a regression analysis, in which the density of bumblebee queens (log10- transformed) acted asa response variable and the field margin area width as an explaning variable.

model variable coefficient t Pconstant (a) 1.553 27.970 < 0.001

n = 84, F = 18.709, P = 0.000, R2 = 0.186 width of field margin area (ß) -0.431 -4.325 < 0.001

5.4.4. Rureral patch type

The total densities of bumblebee queens were higher on shrubby than on open ruderal patches during the first

two counts, while during last two counts an opposite pattern emerged. Indeed, during the first count no

bumblebees were observed on the open patches (Fig. 22). According to the t-test, the difference was significant

during the first two, but not during the last two counts (Table 9).

5.4.5. Forest margin direction

During the first count, bumblebee density was highest at West-facing forest margins (Fig. 23). During this

count, the mean total density of the queens differed significantly between the different compass directions of the

forest margin (Table 10).

49

138

14 17

2523

20 24

1. count 2. count 3. count 4. count0

20

40

60

80

100

120in

divi

dual

s/he

ctar

eruderal patch type

open shrubby

Figure 22. The mean densities of bumblebee queens on open and shrubby ruderal patches during each count. The numberson top of the bars represent the number of transects in the two patch types.

Table 9. The results of a t-test (two independent samples) for total bumblebee densities and the ruderal patch type. Theresults of the Levene´s test were taken into account, when choosing the correct value of t.

count Levene´s test t df PI P = 0.007 unequal variances -3.352 24.000 0.003II P = 0.009 unequal variances -2.993 23.797 0.006III P = 0.113 equal variances 1.458 32 0.155IV P = 0.289 equal variances 1.551 39 0.129

32

33

43

33

North East South West0

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1. count (n = 141)

Figure 23. The mean densities of bumblebee queens at forest margins facing to different compass directions during the firstcount (n = 141: the number of forest margin transects, habitat types FOF ja FOR).

Table 10. The results of one-way ANOVA for the comparison of total densities of bumblebee queens at forest marginsfacing to the different compass directions during the first count. Column source: ´between´ = variation between thedirections, ´inside´ = inside the directions.

source SS df MS F Pbetween 9967.6 3 3322.5 4.639 0.004inside 98125.3 137 716.2

50

6. DISCUSSION

6.1. Ecological significance of findings

6.1.1. The interplay between queen phenology and food plant availability

As shown in this study, willows are the most important food plants of (early-emerging) bumblebee queens in

late April and May. They offer large amounts of both nectar, which the queens drink up in order to gain energy

and pollen, which is essential for the development of their ovaries (Pekkarinen & Teräs 1977, Teräs 1985,

Edwards 1996, Svensson 2002). Short-tongued bumblebees visit both sexes of the dioecious willows, while

medium- and long-tongued species prefer male plants. Female plants secrete more nectar than the male

individuals do (Elmqvist et al. 1988). The tree-like Salix caprea is among the earliest flowering willow species

(Hämet-Ahti et al. 1998). It can be assumed that those high individuals, from which I was unable to identify

some bumblebees to the species level, belonged to this species. According to Svensson (2002), high S. caprea

individuals at forest edges are very important for the bumblebee queens as their first source of spring forage. In

its entirety, the flowering of willows spanned over my whole field period. Indeed, different willow species

manifest notably different flowering times, which may be attributed to the competition for pollinators (Heinrich

1976, Bronstein 1995).

The diversity index of the willows was rather high (H´= 0.95), but the evenness index was low

(J´= 0.43). This is due to the fact that the majority of the bumblebees belonged to the early-emerging B. lucorum

complex, this complex accounting for 72.7 % of all flower visits. All the other species, which emerge by-mid

May according to Pekkarinen & Teräs (1977) visited the willows as well, with the exception of B. veteranus. I

recorded the first queen of this species later than expected, on the 31st of May. The peak of Salix flowering

occurred during the first, and in particular during the second count, when B. lucorum was super-abudant. The

total densities of B. lucorum reached their peak during the second count, whereas in the case of B. lapidarius

this occurred during the third count (Appendix 4, Table 11). I assume that the densities of the later emerging

species would have continued growing as well, had I continued the field period further into the month of June.

For example, B. soroeensis was only the sixth most abundant bumblebee species in this study, whereas in the

late summer results of Bäckman & Tiainen (2002) carried out in the same study areas, it was the second most

abundant species after B. lucorum. B. hypnorum, another early-emerging species, paid 8.2 % of the visits to

Salix. This species was at its most abundant, in comparison with the other species, during the first count and the

percentage returned close to 10 % by the last count. The colonies of B. hypnorum and those of B. pratorum

develop fast and workers are therefore recorded earlier in the season, than in other early-emerging species

(Teräs 1985, Goodwin 1995). Indeed, 21.4 % of the B. hypnorum individuals recorded in this study were

workers. These trends are also apparent, when looking at the mean densities of each species during the different

counts (Table 11).

In forests, several plants such as Anemone and Hepatica, Pulmonaria obscura, Corydalis and

Lathyrus vernus flower before the leaves of the canopy trees bud (Banaszak 1980, Teräs 1985, Banaszak &

Cierzniak 2000). In this study, a total of 24 individuals visited Corydalis solida at forest margins and in gardens.

51

In contrast, only five queens visited the wood anemone (Anemone nemorosa), although this species was much

more abundant and common in my study areas (pers. obs., coverage not recorded). Anemones and hepaticas

produce no nectar and only minor amounts of pollen. Indeed, A. nemorosa is mainly pollinated by flies, which

have lower energy requirements than bumblebees (Teräs 1985). In the study of Macior (1968), the earliest

queens made occasional brief visits to Hepatica americana without foraging. Other early-flowering plants,

which received only occasional visits in my study included Tussilago farfara, Lamium purpureum and Caltha

palustris. The latter was only visited by one Psithyrus queen in the study of Teräs (1985).

Table 11. The mean density of each bumblebee species during the four different counts.

Species I II III IV total (mean)

B. lucorum 20.9 49.4 21.4 17.8 27.38B. lapidarius 2.1 4.5 6.8 5.9 4.83

B. hypnorum 3.3 5.0 1.9 3.6 3.45

B. pascuorum 1.3 4.8 2.8 4.9 3.45

Psithyrus sp. - 1.5 5.8 2.2 3.17

B. pratorum 0.8 1.9 0.7 1.8 1.30

B. soroeensis - - 0.3 1.0 0.65

B. hortorum 0.1 0.1 0.4 0.5 0.28

B. veteranus - - - 0.3 0.30

B. distinguendus - - - 0.2 0.20

B. ruderarius < 0.1 0.2 0.1 0.4 0.20

B. jonellus - 0.2 0.1 - 0.15

In mid-May the maples flowering in forest boundaries and gardens attracted large numbers of

bumblebees, the visits being clearly dominated by B. lucorum. 73.1 % of the flower visits were made by this

species complex. In addition, 21.2 % of the visits were made by unidentified individuals, which presumably

included mainly B. lucorum. Therefore this tree can support the nest establishment and colony growth period of

a common and abundant species, which in turn is important in the context of pollination services later in the

season. However, it has little to offer to bumblebee diversity in general, since its flower is unsuitable for long-

tongued species. Furthermore, the maple flowers relatively early in the season, making it a temporarily isolated

forage plant from the later emerging species.

Dandelions are the most important food plants once the flowering of willows has ended (Teräs

1985). In this study, Taraxacum was visited by all but one species, B. jonellus. This species is clearly associated

with forests. Dandelions had high values of both diversity and evenness, that is several species visited them and

the percentages of the different species of bumblebees were rather close to each other. In fact, the values of

these indices for Taraxacum were highest in comparison with any other plant species. However, the nutritional

content of dandelion pollen may actually not be optimal for the newly founded bumblebee colonies. Pollen

types are known to vary in their chemical composition, some of them completely lacking essential amino acids.

52

Honey bees are known to perform badly, if fed only with Taraxacum pollen (Roulston & Cane 2000) and some

experiments point to similar problems in bumblebees. In the study of Génissel et al. (2002), queenless micro-

colonies of B. terrestris were fed with Salix, Taraxacum and Prunus pollen. The latter was highest in protein

content, with 27.5 % of protein. Taraxacum diet resulted in the longest egg-laying delays and highest oophagy

(egg-eating) rate and Prunus the lowest. No males emerged from colonies fed with Taraxacum pollen. It might

therefore be surprising, that Prunus seems to be largely ignored by foraging bumblebees under field conditions.

In this study, only two individuals were observed visiting Prunus padus.

During the latter part of the field period, the queens visited Ribes rubrum and Caragana

arborescens in relatively high numbers. The latter is evidently a valuable food plant for queens initiating nest

building (Teräs 1985) and in my study it was visited by several species (H´= 1.45), but especially by B.

lapidarius (J´= 0.66). Its flower has a deep corolla tube, but can be robbed by short-tongued bumblebees. The

array of visited plant species grew towards the end of the study period. In fact, 60.7 % of the plants (17 out of

28) were only visited during the third and/or fourth counts. As regards to the tongue-length, the medium-

tongued (mean H´= 1.475) and long-tongued (mean H´= 1.290) bumblebee species had a wider selection of food

plants than the short-tongued ones (mean H´= 0.938). The former two groups visited seven such plant species

which were not visited by the latter, for example the red campion (Silene dioica). According to Harder (1985),

bees with long glossae tend to feed from a larger number of plant species and their use of a particular species is

less predictable, that is they manifest lower flower constancy. In this study only one B. hortorum individual

visited the German catchfly (Lychnis viscaria), which was only flowering on two of the transects (pers. obs.,

coverage not recorded). Indeed, this species is often seen visiting rare plant species (Teräs 1985). Furthermore,

long-tongued species more often visit small groups and short-tongued species large groups of flowering

individuals of the same plant species (Sowig 1989).

According to Sowig (1989), the dominance of short-tongued bumblebee species in

agroecosystems is a phenomenom caused by the intensification of agriculture. In the study of Heard et al.

(2007), the density of long-tongued species decreased in concert with the increasing proportion of arable land in

the surrounding landscape. Furthermore, short-tongued species might be able to find rewarding foraging sites

more readily than the long-tongued ones (Teräs 1985), due to the species-specific differences in the

communication and recruitment systems (Dornhaus & Chittka 2001). In the UK, B. hortorum is the only long-

tongued species which is still common and abundant in agricultural landscapes (Goulson 2003). One reason

behind this can be, that the intensification of agriculture has negatively affected vetches (Vicia) and other

bumblebee plants with deep corolla tubes (Fussell & Corbet 1992a). In late May and early June vetches are

important food plants both for the queens and their first workers (Teräs 1985). In conclusion, the early-emerging

and mostly short-tongued species of bumblebees have only a limited array of food plants available. These are,

however, plants which seem to be abundant in our agricultural landscapes, such as Salix and Acer platanoides.

6.1.2. Densities in the different habitat types and their fluctuation during the spring

Williams & Kremen (2007) have been developing a landscape model, in which landscape grids in a GIS

systems are given different values, depending on the forage availability for solitary bees during the different

53

times of the season (the ´foraging landscape , see also Wu & Hobbs 2002). The landscape honey potential has

also been used as a tool for beekeepers in Brazil (Simões et al. 2005). Frankl et al. (2005) used a same kind of

approach. In their data base, management activities (such as crop harvest, mowing and grazing) were recorded

as precisely as possible.

The landscape model of Frankl et al. (2005) was based on the assumption, that the flower cover

of a plant species is related to the area, which is covered by the aboveground biomass of the species. Three

different landscape types (a conservation area, a pasture-dominated landscape and an area of intensive arable

production) differed distinctly in their floral resource levels during the different stages of the season. For

example, woodland with Salix and fields with Brassica napus provided mass-flowering, but only during short

periods of time. The tracksides and meadows, in contrast, were a source of low level, but continuous resources.

In the pasture-dominated study area mass supplies of grassland species (e.g. Taraxacum) presented additional

high supplies in the spring, but mowing soon reduced its resource levels. Furthermore, only small proportions of

linear landscape elements (tracksides, ditches and river shores) were present in this landscapes. The authors

concluded that agricultural practices have effects on the temporal supply of floral resources, but that the floral

resource levels of intensively cultivated landscapes are already strongly reduced by the general low species

richness of entomophilous plants.

My study reveals a snapshot of such a landscape, in the case of overwintered bumblebee queens.

In my study landscape, the forage value of the riparian corridors and main ditches is high during the early

season, but drops immediately, after the flowering of willows has ended. At this point the queens switch to

grassland fields, where high densities are observed during the flowering of dandelions. Interestingly, the gardens

supported relatively high total bumblebee densities during the whole study period, which can be partly, but not

probably not completely explained by the flowering of A. platanoides. Goulson et al. (2002) placed colonies of

B. terrestris in suburban gardens, on conventional farms and on farmland with conservation measures. The nests

in gardens gained weight more quickly and reached a larger size due to a continuous source of forage plants. On

the other hand, these nests were heavily attacked by the wax moth (Aphomia sociella).

Here it is easy to see, how a survey on a single date could give misleading information on the

value of a habitat type as a foraging patch throughout the whole season. In the study of Dramstad & Fry (1995),

a ditch bank offered very few food plants during the spring. During the flowering period of vetches (Vicia) this

site manifested high forage availability, however, and the bumblebees showed a preference for V. sepium and V.

cracca when foraging on the patch. After Vicia flowering had ended, the forage value of the bank dropped again

to a low level. However, this same bank can serve as a nesting site as well, as the authors point out. A further

issue, which is beyond the scope of this study, is the value of any habitat patch in terms of colony fitness. In the

study of Hatfield & Lebuhn (2007), wet montane meadows had fewer floral resources in early summer than

drier meadows, but later in the season the opposite was true. This pattern correlated with bumblebee densities,

which may be due to the wet meadows supporting either higher densities of colonies or larger colonies, a crucial

distinction in terms of the effective population sizes of species. In general, bumblebees can usually be counted

only at sites containing forage, and it is difficult to sample the landscape representatively when forage patches

are unevenly distributed. In addition, even if it were possible to use counts of foraging bees to estimate the

54

number of nests from which they had come, knowledge of the foraging range is required to estimate the area

over which the nests are distributed and thus calculate the nest density (Osborne et al. 2008).

Bumblebee densities are known to be highly variable both within and between seasons. Not all of

this variation can be explained by the spatial arrangement of the flowering food plants or nests nor the

prevailing weather conditions (Banaszak 1983). Instead the issue requires a more comprehensive framework of

the factors, that can affect the different parts of the bumblebee colony cycle (see Fig. 4). Certainly such factors

as the stage of colony development and time of the day should be taken into account, when presenting any

information on the densities. Furthermore, it is important to include the information, whether a one count

density or a mean density of the whole season or possibly of various seasons is being presented (Teräs 1983).

The first peak in the densities of bumblebees is normally observed in May, when the densities of foraging

overwintered queens are at their highest (Banaszak & Cierzniak 2000) (Table 12). In (early) June most queens

stay inside their newly founded colonies, while workers are still scarce. Therefore the densities are low during

this period. The highest peak in the densities is usually observed in late July, due to the high numbers of

workers at the strongest time of the colonies. Again, due to the differential natural speeds of colony growth in

each species, this peak occurs at slightly different times of the season (Goodwin 1995). The workers of B.

hortorum, B. hypnorum, B. jonellus and B. pratorum are at their most abundant earlier than those of B. lucorum,

B. lapidarius, B. pascuorum and B. veteranus (Teräs 1985).

Table 12. Bumblebee densities (ind./ha) during the season according to some previous studies, spanning from theemergence of overwintered queens to the strongest time of the colonies. The caste (Q = queens, W = worker) is mentioned,if the data in the original paper contains individuals from only one caste.

time period ind./ha bumblebee species habitat type reference

late April ca. 5.0 B. lapidarius (Q) forest islands Banaszak & Cierzniak 2000*)early May 22.0 all species present (Q) urban green space Bäckman 1996

half May ca. 7.0 B. pascuorum (Q) forest islands Banaszak & Cierzniak 2000 *)

half May 74.5 B. lucorum (complex) pine-oak forest Banaszak 1983

late May 7 all species present (Q) urban green space Bäckman 1996

late May 7 all species present (W) urban green space Bäckman 1996

half June 31 all species present (W) urban green space Bäckman 1996

half July 69.1 B. pascuorum oak forest Banaszak 1983

half July 3105 B. lapidarius sunflower field Banaszak 1983

half July 1325 B. lapidarius red clover field Banaszak 1983

half July 221.5 all species present Lupinus field Banaszak 1983

late July 252 all species present (W) urban green space Bäckman 1996

late July 137 B. lucorum (complex) field margins Bäckman & Tiainen 2002

late July 45 B. lapidarius field margins Bäckman & Tiainen 2002

*) The given density is estimated from a curve presented in the original paper.

In some habitat types, such as sunflower and red clover fields, the late season densities can reach

thousands of indivuals per hectare (Teräs 1976b, Banaszak 1983), during the mass-flowering of these crops. The

55

average densities in other types of habitats are usually much lower, however. In the field margin study of

Bäckman & Tiainen (2002), the densities were in the magnitude of tens per hectare, depending on the species.

In years with poor weather conditions bumblebee colonies may fail to grow and low densities are observed even

during late season. The sufficient number of dry days, in terms of pollen collection, may be an important factor

determining the success of the colonies (Peat & Goulson 2005). When estimated in the same location, the

difference in the densities between subsequent years may even be 100-fold. In the study of Teräs (1983), local

late July densities were in the magnitude of 100 individuals/hectare in the year of 1973. The year of 1974, with

its high late summer rainfall, manifested growing densities until late June, but low densities were observed in

July and August. Presumably rather few of the colonies managed to reproduce in this case and therefore the

densities of overwintered queens would have been low the following spring, in the year of 1975.

The densities of overwintered bumblebee queens have been rarely studied. In the present study,

the mean total density of queens was 29.5 individuals/hectare during the first count, 67.5 ind./ha during the

second count, 39.9 ind./ha during the third count and 31.0 ind./ha during the fourth count. These figures

correspond fairly closely with the estimated spring densities of the honey bee. In total there are about 50 000

honey bee colonies in Finland, which means that in the spring there are about one milliard bees in the country as

a whole. This in turn corresponds to about 30 individuals/hectare, while in the proximity of the colony this

density can reach 45 individuals/hectare (discussion with Ari Seppälä, Finnish Beekeepers´Association). The

highest recorded individual bumblebee density in this study was that of B. lucorum on one streamside transect

during the second count (341.5 ind./ha) and the second highest on one grassland field transect during the fourth

count (165.5 ind./ha). The queen densities recorded in this study were higher in general, than those recorded by

Bäckman (1996) in the urban green areas of Helsinki in late May. In contrast, in comparison with some Polish

studies, the densities recorded in this study were somewhat smaller. In the present study the mean density of B.

lapidarius was 0.8 ind./ha at forest edges between a forest and a field during the first count. Banaszak &

Cierzniak (2000) recorded a mean density of 5 ind./ha in forest islands in late April. Similarly, the mean density

of B. lucorum was 37.5 ind./ha at forest edges during the second count, whereas Banaszak (1983) recorded 74.5

ind./ha in a pine-oak forest in May. This difference may be explained, in addition to the effect of the study

latitude, by the stronger flowering of such plants as V. myrtillus inside the forest islands than at the edges of the

forests (but see chapter 6.1.3. ).

In recent years, at least in the springs of 2007 and 2008, very low bumblebee densities were

reported in Finland and in some other European countries (Sweden, discussion with Anna Persson). It remains

open to discussion, however, as how much fluctuation in bumblebee densities from one season to another can be

seen as ´normal . In the year of 2007 the queen, as well as late season worker densities were regarded as

exceptionally low (discussion with Ari Seppälä & Ilkka Teräs). Even the Finnish beekeepers noticed only a few

bumblebees and wasps when feeding their bee colonies with sugar solution in the fall of 2007. In ´normal´

years, when this winter food is given to the honey bees, other insects are attracted in high numbers. Densities

remainded low in the spring of 2008, but apparently the few queens succeeded in founding colonies, since high

worker densities were observed in late summer. In comparison with these two years, the spring of 2000 can be

seen as a ´good´ spring in terms of queen densities. In the year of 2009, both spring and late summer densities

were high (Eeva-Liisa Alanen, unpublished data).

56

6.1.3. Other properties of the line-transects important for high queen densities

Typically, the ability of a simple equation to capture the variation in bumblebee densities changes during the

season. Multivariate regression was used in the study of Bowers (1985) to account for the observed bee

densities in subalpine meadows. Each week the equation accounted for between 38 to 98 % of the variation in

the densities of two study species. Most variation was consistently accounted by the temperature or time of the

day, whereas meadow size and elevation played a significant role in early summer only. Later in the season, the

meadow floristics (forage availability), increasingly contributed to the densities of both species. In the late

season study of Bäckman & Tiainen (2002), the abundance and flowering phenology of a limited number of

plant species (Trifolium medium in particilar) were the most important factors explaining bumblebee visits in

field margins. Furthermore, Croxton et al. (2002) showed that bumblebee abundance was significantly higher

within the green lane habitat (= trackway, which is bounded on both sides by hedgerows) than on field margins,

and this abundance was directly related to the abundance of flowers in the habitat. This strong interplay between

the habitat type and forage availability was obvious in my early season stydy as well, food plant availability

strongly affecting bumblebee densities. For example during the fourth count, there was a rather strong

correlation between bumblebee densities and the coverage of Taraxacum on a transect. At this time the

grassland fields manifested their importance and later in the season some of these same fields would have

probably been good foraging areas due to red clover flowering. Kohler et al. (2007) found a corresponding

result in terms of honey bee abundance, using Spearman´s rank coefficient´s (q = 0.42, P = 0.006). Later in the

season the white clover (Trifolium repens) gave a similar result (q = 0.41, P = 0.007). In the same study, both of

the plants showed a significantly higher cover on conventionally managed fields, than on those with

management agreements in an agri-environmental scheme.

Heard et al. (2007) detected a strong positive correlation between the mean estimated number of

flowers of all bumblebee forage plant species and the mean total number of bumblebees per patch. In the study

of Kleijn & van Langevelde (2006), bee abundance was related to the number of inflorescences of bee plants. In

the case of species richness, flower abundance had a positive effect only in those landscapes with few semi-

natural habitats. The authors suggested that this may be due to the concentration of foragers on the few

resource-rich patches in the landscape. Indeed, Westphal et al. (2003, 2006) demonstrated a strong positive

correlation between mass-flowering crops and bumblebee densities, indicating that bumblebees can exploit mass

resources over large distances. This is exactly, what I assume to be occurring also in the case of the

overwintered bumblebee queens and willows. As a corresponding example from the tropics, giant honeybees

(Apis dorsata) (Itioka et al. 2001) and carpenter bees (Xylocopa sonorina) (Appanah 1993) migrate to the site of

the mass- flowering trees. Without these trees, stingless bees are forced to forage from scattered subsets of

flower patches spread out over a large foraging range (Eltz et al. 2001). Furthermore Itioka et al. (2001) showed

that honey bee populations increase rapidly in response to mass-flowering.

Based on the volume of the canopy, the biggest S. caprea attract the highest numbers of queens

(Svensson 2002). Queens are particularly attracted to such areas, where the total volume of all willows exceeds

1000 m3/ha, which corresponds to about 2 % of the total maximum foraging area (of ca. 28 ha) of bumblebees

(Svensson 2002). In this study, the crown volumes of the willows were not estimated. Indeed, had I made an

57

effort to do this, would the explanatory power of the models probably been improved. According to the

estimates of the flowering areas, the riparian corridors and and the main ditches were the habitat types providing

the most abundant supply of forage from willows. In an even more intensively cultivated landscape with fewer

forage patches, also those small willows growing on the more open field margins, that is margins of other

ditches and temporary field margins, could be of major importance. In such areas where crown volumes are

small, willows having a mean crown volume of less than 10 m3, competition for nectar and pollen can become a

significant factor in shaping pollinator communities. The same is true for such areas, where the total crown

volume per hectare is less than 100 m3 (Svensson 2002).

The effect of willows was apparent also,when comparing the transects according to their other

properties, than the habitat type itself. The mean area of flowering Salix was 211.3 m2 in main ditches, 94.7 m2

in other ditches and 17.7 m2 on temporary field margins during the second count, the density of bumblebees

reflecting this pattern. Although the main ditches were wider on average than the other ditches, the width per se

did not seem to affect the bumblebee densities until the fourth count, and even in this case was the correlation

negative. The eutrophic vegetation of main ditches being unsuitable for other bumblebee plants than willows,

these habitats have little to offer in terms of foraging possibilities after the flowering of willows has ended. Even

later in the season the width of field margin has been, however, shown to positively affect the density, but not

the species number of bumblebees (Bäckman & Tiainen 2002). The pattern of Taraxacum and Salix flowering

and the corresponding high bumblebee densities was obvious on the ruderal patches as well. On the open

ruderal patches there were no flowering willows, which was the definition of this patch type in the first place.

On the shrubby patches the mean area of flowering willows was 43.7 m2 during the first and 37.7 m2 during the

second count. The pattern in the dandelions was the opposite. During the third count their coverages were 1.6 %

on shrubby and 5.6 % on open patches and during the fourth count the corresponding percentages were 4.1 %

and 8.9 %.

When it comes to the forest edges, the largest area covered by flowering willows was recorded at

the North-facing margins (62.9 m2). The flowering times of plants are known to vary both between and within

species (Heinrich 1976) and in shady forest habitats the onset of flowering is postponed. At the West- facing

margins, where the highest queen density was recorded during the first count, the mean area of flowering

willows was actually slightly smaller (59.4 m2). In the case of the other two compass directions, the areas were

smaller still (East: 31.9 m2 and South: 17.5 m2). The result can probably be explained, in conjunction with

flowering phenology, by the preference of the queens for warmer habitats per se. Calabuig (2000) studied the

same question by placing yellow traps into forest margins facing into different directions. The number of

trapped bumblebee queens was highest at South-facing margins and lower in the other compass directions (East,

West and North, in order). According to Banaszak & Cierzniak (2000), forest islands not only provide willows,

but other valuable sources of nectar and pollen, as well as nesting sites. Even forest plants thrive better in the

more beneficial light conditions of this ecotone habitat. This is why higher densities of bees are often recorded

at the edge rather than inside the forest island itself. Forest islands can be seen as important aesthetic elements

as well, both the ecological and aesthetic value depending on such factors, as the disturbance rate and the shape

of the island (Hietala-Koivu et al. 2004).

58

6.1.4. Mitigation strategies targeted at the starting stage of bumblebee colonies

"With regard to pollination services and food yield stability, we need to… determine the degree to which intercropping,hedgerows, and other farm management practices can maintain pollinators by providing increased nesting or foragingsites... encourage modern crop breeders to consider the floral attributes of interest to pollinators — color, scent, amount ofnectar and pollen, self-incompatibility, and floral morphology — when selecting new horticultural varieties." (Allen-Wardell et al. 1999)

The amount of suitable nesting sites may well be the most important factor limiting the number of bumblebee

colonies in any particular area. However, pollination problems may occur at low queen densities. This means

that even those individuals, which will not succeed in colony initiation, may add to the fuctional diversity of a

landscape. Therefore any measures targeted at the later stages of the colony cycle will have beneficial

consequences extending into the following spring, in case these measures will lead to the production of new

queens from the colonies.

Bumblebee populations could be supported by artificially adding nests to the field, in the vicinity

of such crops and forest berries in particular, which benefit from bumblebee pollination (Pekkarinen & Teräs

1977, Delaplane & Mayer 2000). A colony can be taken from the field and transported to the desired location,

whereas empty boxes are not easily accepted by bumblebee queens. In a recent experiment, in which

commercial hives of B. terrestris were used, significant local yield increases in bilberry were detected (Kauko

Salo, unpublished data). These kinds of colonies are bred around the year and can then be placed into the

desired location. This kind of interventional approach should, however, be seen only as a last resort in case of

serious pollination problems (Dixon 2009). More important measures are habitat management and the ensuring

of food plant availability in particular. As suggested by Banaszak (1992), two main factors are important in the

effort of maintaining diverse native bee communities in agricultural landscapes. First, the proportion of

farmland should not exceed ¾ in the landscape and second, extensive areas of nutritive plants, such as the

oilseed rape, should be cultivated in it. As it is, my study landscape still seemed to support a relatively diverse

bumblebee community, with 11 observed species. This can presumbably be generalized into most similar

landscapes in southern Finland. In a corresponding Dutch study, in which landscapes with contrasting amounts

of semi-natural habitats and linear landscape elements were compared, only four bumble bee species were

recorded (Kleijn & van Langevelde 2006).

Reintegration of certain native plant species into agricultural landscapes would greatly benefit

bumblebees as well as other pollinators (Isaacs et al. 2009). One option to achieve this is through the agri-

environment schemes. However, a recent review by Kuussaari et al. (2008) indicated, that these schemes are

currently inefficient in terms of protecting or enhancing biodiversity on conventional farmland, although some

useful and effective special measures targeted at traditionally managed biotopes do exist. In the Netherlands,

biodiversity has been slightly enhanced by the management agreements, although their effectiviness is poor in

general. Although bee diversity has been slightly enhanced by the number of management agreements, it seems

to be more strongly related to the presence of woodland and shrubland edges in the landscape (Kleijn et al.

2004). These management agreements may even have unexpected negative consequences, for example in the

59

case of meadow birds (Kleijn et al. 2001). A further problem in the case of bumblebees is the lack of adequate

monitoring data including habitat and food plant relations.

However, some new measures have and are being developed. Set-asides can be valuable habitats

in terms of both foraging and nesting, depending on their duration and method of establishment. Currently there

is no obligation to set-aside according to the CAP regulations, but instead of using this measure to prevent

overproduction of food, it can be developed as a measure to enhance biodiversity. Another promising option is

that of creating strips of suitable foraging habitat, either inside or at the edges of agricultural fields, by planting

a seed mixture of valuable nectar and pollen plants. In the study of Pywell et al. (2006), the abundance of long-

tongued bumblebees per field margin was explained by the number of these types of pollen and nectar

agreements in a 10 x 10 km square, together with flower abundance. Comparisons of sown and unsown belt

treatments have shown, that the ´grass and wildflower mixture´ typically supports the highest bumblebee

densities. An unsown belt is readily colonized by the Creeping Thistle (Cirsium arvense). This species offers an

ample nectar source during the second year after strip establishment, but at the same time prevents the growth of

other valuable forage plants. Furthermore, it presents a serious weed problem. The best solution both

agronomically and ecologically would therefore be to sow with competitive, perennial species suitable for long-

tongued bumblebee species (Pywell et al. 2005, Carvell et al. 2007).

Including early-flowering species in the seed mixtures used on set-asides and sown strips would

benefit the overwintered queens and their first workers. Carvell et al. (2006) recommend S. cinerea to be

included in wildlife seed mixtures and other restoration schemes in agricultural landscapes, together with such

species as Lamium album and Vicia cracca. This is because many native forage plants of bumblebees have

widely declined in the UK between the years of 1978-1998. These species include some plants, which are

important during the colony initiation stage of bumblebees, such as Salix cinerea. The lack of willows in

Finnish agricultural landscapes is usually not a problem though, rather the opposite. It is obligatory according to

the CAP regulations to remove shrubs from field margins, but not all farmers do this often enough. This leads to

a decrease in the area of open, meadow-like field margins (discussion with Irina Herzon). V. cracca, however,

together with the earlier flowering V. sepium would be highly recommendable in Finland as well. Early June,

which is the flight period of late-emerging bumblebee queens, such as the declining B. distinguendus, appears to

be a period with few flowering plants. V. sepium could therefore be used as a bridging species as well, a species

which provides resources over a resource-limited time (Dixon 2009). Other species to consider in mitigation

strategies are framework species, which provide a major nectar or pollen source and magnet species, which are

plants with attractive flowers associated with species with less attractive flowers. Based on the results of this

study, A. platanoides is one such framework species, at least in the case of B. lucorum. In very simple

landscapes, however, the importance of willows can become obvious. For example in the Netherlands there are

practically no shrubby field margins or forest boundaries, and therefore very few willows. Later, there is

apparently an ample supply of dandelions almost everywhere, but few bumblebees are foraging on these (pers.

obs.). I assume that in these kinds of cases certain floral resources can be under-utilized by pollinators, due to an

earlier gap in the availability of food plants.

Willows can offer other ecological and agronomical benefits as well, such as offering protection

from wind around fruit orchads (Gliessman 1997). These windbreaks can in turn support pollination services in

60

at least two different ways. First, less wind means better flying conditions for pollinating insects and thus a

better pollination result. Second, the windbreaks as well as different kinds of buffer plantings and hedgerows

can offer forage for the pollinators. These alternative foraging habitats are especially important, if the crop being

protected requires insect pollination, since any particular crop flowers only during a limited period of time

(Vaughan et al. 2004). In the case of bumblebee queens, creating favourable conditions in apple orchads is an

important task. The value of bumblebee queens in apple production is high especially in those years when honey

bee colonies are unavailable for one reason or another. Large monocultures may, however, need additional

honey bee colonies, even in years when bumblebees are abundant. Even in Finland the size of apple plantations

is increasing and good yields are not achieved in the middle of the plantation, without the help of the honey bee.

The same is true for plantations e.g. on small islands, which offer little bumblebee nesting and foraging habitats

(discussion in the pollination seminar of the Finnish Beekeepers´ Association and the Finnish Fruit and Berry

Growers´ Association, 18th of April 2009, Salo, Finland).

In considering the choice of crop varieties, the requirements of bumblebees can be taken into

account as well. Biodiversity and other environmental benefits of energy crop cultivation using Salix, such as

reduced carbon dioxide emissions from the soil and protection against wind erosion, are discussed by Börjesson

(1999). Most commonly the cultivated species is S. viminalis. By taking more species or different clones of the

same species into production, the flowering times could be spanned over longer periods of time. Care should be

taken to plant both male and female plants. In addition, on large cultivations the harvesting should be done in

parts, since the first spring after the harvest the willows will not flower. Flowering is typically strongest at field

edges and therefore should the division of large plantations into smaller plots be encouraged (Reddersen 2001).

6.2. Methodological issues

It is unfortunate, that the counted lenghts in each of the habitat types varied considerably and were rather small

in some of them. Furthermore, using such analysis methods as the (Generalized) Linear Mixed Models

(GLMMs/GLMs) would have probably been a fruitful approach, instead of analyzing the bumblebee densities

separately according to each property of the line-transects.

6.2.1. Landscape analysis and the comparison of study areas

Heterogeneity (high values of SDI and SEI) promotes biodiversity in agricultural landscapes (Weibull et al.

2000, Tscharntke et al. 2005, Rundlöf & Smith 2006). In my study, no effects of these indices were detected.

However, the negative correlation of bumblebee densities and MPS during the second and fourth counts could

indeed be seen as an indication of a small-scaled landscape being more suitable for bumblebees, than a large-

scaled one. The mean density of B. hypnorum and the edge density (ED) of gardens correlated during the first

count. This species is regarded as a forest species, which has adapted to living close to human settlements

(Söderman & Leinonen 2003) and often nests in bird nest-boxes and inside building walls (Pekkarinen & Teräs

1977). Furthermore, there was a positive correlation of the density of forest species and the edge density of

forests during the fourth count, and a negative correlation of the density of open landscape species and the edge

61

density of forests during the second count. A higher or lower than expected number of species is indicative of a

separate bumblebee community in the area in question (Bäckman & Tiainen 2002). Therefore, distinctive

communities would exist in Porkkala, Parikkala, Hauhiala N, Pappila and Hampaanmaa according to the results

of this study. However, these were manifested only during one count each, except in Porkkala, where a separate

community appeared on three different counts. The results of the fourth count for Pappila are consistent with

those of Bäckman & Tiainen (2002) who recorded a separate community of bumblebees in this area in their late

season study.

The biological meaning of my landscape analyses remains questionable, however, due to their

scale. In a study made in Costa Rica, stingless bee abundance and species richness did not significantly correlate

with plant richness nor pasture management. Instead, bee communities were strikingly different at forest edges

as compared to deforested countryside only a few hundred meters from the forest (Brosi et al. 2007). A similar

approach would have probably been fruitful for testing the landscape-type preferences of the queens in my data

set as well. For example, would the density of a forest´ species on a line-transect depend on the percentage of

forests in a buffer zone around that transect? Several buffer zones can be created in a GIS system, spanning

from meters to kilometers. Or, which landscape elements would be important for the occurrence of the rare

species in the data? Diekötter et al. (2006) studied the regional distribution pattern of B. muscorum in an

agricultural landscape of central Germany, by analyzing grid-based observation records in GIS. Several

landscape variables were combined in ecologically meaningful groups prior to analysis to prevent problems in

convergence. A negative effect of the number of trees and a positive one of the proportion of arable land in the

grid was detected, the latter observation supporting the prevailing view that the species has a preference for

open landscapes. Further important landscape elements were ditches, clover grassland fields and fallow. The

authors point out that analyzing bumblebee abundance or diversity simply in relation to landscape structure

ignores the species-specific differences in foraging ranges, which indeed determine the amount of available

resources for any given colony in the field.

Furthermore, the interpretation of the rarefaction results is complicated by the different

emergence times of the bumblebee species. In this context it is unfortunate, that the study period was not

extended further into the month of June. The sample size is sufficient to describe the species diversity of an

area, when the rarefaction curve levels off before reaching the actual number of recorded individuals. This was

the case in Ruosuo, meaning that the the bumblebee community of this area was successfully described.

However, weather conditions during the different study dates, for example, may have played a large role in

these results. Furthermore, the availability of food plants varied between the areas and the growth speed of

E(Sn) can presumably be attributed to the presence of flowering willows and later that of dandelions in an area.

The late-emerging species B. distinguendus and B. veteranus were only recorded in those areas, where the last

count was made during the last three days of the field period. It is therefore not known, whether these species

would have also occurred in Jahkola, Pappila, Hampaanmaa and Hauhiala. But there is a trade-off, when

considering this issue. Indeed, the queen densities of the late-emerging species probably reached their maximum

levels only after my field period had ended. The main objective of this study was, however, to get a picture of

the total densities of those queens, which form the population of potential nest founders. Sampling later in the

spring would have probably led to the encountering of large numbers of such early-emerging queens (B.

62

lucorum in particular), which are infested by S. bombi. These kinds of individuals do not initiate colonies and as

a consequence, do not contribute to the pollination services in the lanscape later in the season.

6.2.2. Future research needs

Follow-up studies on spring phenology, both of the overwintered bumblebee queens and their food

plants. Combining controlled experiments with the study of natural phenological variation at the

landscape and even larger scales seems a promising research direction (Price & Waser 1998).

The spread of early-flowering invasive plants and their pollination systems. Macior (1968) suggests,

that introduced species (Berberis, Lonicera, Pyrus malus and Taraxacum) may compete with native

plants in attracting bumblebee queens.

The role of parasities and diseases in the population dynamics of bumblebees. They have the potential

of having population level consequences, which have been rarely addressed to date.

Bumblebee colony qrowth parametes in relation to environmental quality. In the study of Giralt et al.

(2008), bird breeding parameters were related to habitat composition and food supply at the territory

level. Fledgling success of early breeders was related to the presence of natural (shrubland) and semi-

natural (fallow) habitats in the predominantly agricultural matrix. In the study of Jepsen et al. (2005), a

spatially explicit simulation model was built, in which the characteristics of the model species (=

´behavioural states ) were captured in impact indices of weather and farming decisions.

The optimization of the landscape pattern, one of the current key priorities in landscape ecological

research, connects closely with the concept of the ´flowering landscape´ in the case of pollinating

insects (Wu & Hobbs 2002, Frankl et al. 2005, Williams & Kremen 2007). There are many difficulties

with assessing the level of available floral resources, but progress should be possible (Williams et al.

2007).

The spread of B. terrestris in Finland in relation to global warming. B. terrestris can be highly invasive

to natural vegetation (Hingston 2006). In the study of Inari et al. (2005), bumblebees were collected at

the distances of 1, 2, 4, and 6 km from a large greenhouse. The peak catch of B. terrestris queens

occurred in early June, suggesting that they had successfully hibernated in the field. The distributions of

B. terrestris and the native B. ardens were mutually exclusive, while the native B. hypocrita appeared at

all sites. Furthermore, the pollination of native plants may be jeopardized by the invasion of the very

short-tongued B. terrestris (Kenta et al. 2007).

63

Long-term monitoring of bumblebee populations, in particular in areas of high pollination needs, such

as apple plantations.

Studying nectar quality and secretion rates in the field, over different habitat types and climatic

conditions, using the methods introduced by Corbet (2003) and Potts et al. (2006). Again, this is

important in the context of climate change in particular.

Developing methods to estimate the ´pollination potential´ of landscapes. Evaluation based on different

landscape parameters (Duelli 1997) should be the most effective way of doing this.

ACKNOWLEDGEMENTS

This stydy was financially supported by Jenny and Antti Wihuri Foundation, which is gratefully acknowledged.

64

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Appendix 1. The total counted lengths (m) in each of the study areas according to habitat type and count. The habitat types were:forest boundary between a forest and a field (FOF), forest boundary between a forest and a road (FOR), grassland field (GFI),garden (GAR), field margin between two fields (FMF), field margin between a field and a road (FMR), streamside (ripariancorridor) (RIP) and ruderal patch (RUD).

Study area count FOF FOR GFI GAR FMF FMR RIP RUD total

Jahkola I 590 - - - 2220 2369 57 - 5236II 781 - - - 2507 2725 57 - 6070IV 590 - 650 - 2014 2724 57 86 6121

Pappila I 2807 - - - 1508 1780 106 144 6345II 2807 184 - 53 1295 1780 106 144 6369III 2787 184 888 312 1508 1721 106 234 7740IV 2475 184 1705 312 1140 1721 106 234 7877

Hampaanmaa I 1862 709 - 134 1072 1647 250 517 6191II 2022 776 - 134 1158 1797 302 683 6872III 2003 709 287 175 1158 1943 209 683 7167IV 2163 709 562 175 1158 2048 - 683 7498

Ylänäinen I 2616 358 - 177 1632 1905 570 482 7740II 3184 410 - 665 1632 2211 703 623 9428III 3067 410 898 740 1632 1952 390 980 10069IV 2869 358 1079 740 1632 1773 390 894 9735

Hauhiala S I 1152 - - - 440 292 278 487 2649II 1152 - - - 440 155 344 349 2440IV 872 - 255 - 440 292 177 640 2676

Hauhiala N I 946 359 - - 650 1135 150 258 3498III 946 359 147 - 650 1135 100 258 3595IV 680 359 869 - 650 1245 100 258 4161

Ruosuo I 1599 185 - 141 1518 828 - - 4271III 1040 252 - 185 1518 1126 - - 4121IV 1040 252 - 185 1518 1126 - - 4121

Kivismäki I 2309 549 - 97 2382 1505 65 375 7282III 2309 549 89 225 2382 1505 - 375 7434IV 2309 589 89 225 2382 1505 - 335 7434

Vanha-Kartano I 796 - - - 1826 798 418 191 4029III 796 - - 102 1826 798 418 191 4131IV 796 - 295 102 1826 798 418 191 4426

Porkkala I 1000 612 - - 842 1824 - 487 4765II 1000 612 - - 842 1824 - 487 4765III 1000 612 - 161 1005 1824 - 487 5089IV 1000 612 - 161 1005 1824 - 437 5039

Parikkala I 419 - - - 1050 3467 236 219 5391II 753 - - - 1050 3216 236 219 5474IV 753 - 721 - 1099 3326 92 219 6210

79

Appendix 2. The total numbers of bumblebees in each of the study areas during the different counts.

Study area DI HO HY JO LA LU PA PR RU SO VE B P TotalJahk. I 1 2 13 1 17

II 1 5 6 84 7 2 8 113

IV 2 7 10 53 6 4 1 5 88

Papp. I 2 3 24 1 30II 7 2 12 92 10 2 17 4 146

III 2 6 32 44 7 5 2 26 124

IV 1 12 8 95 15 7 2 6 146

Hamp. I 8 2 30 8 1 49II 13 1 78 7 2 1 3 105

III 2 6 13 42 14 2 1 20 100

IV 8 7 37 20 7 5 8 92

Ylän. I 7 8 31 2 2 50II 24 35 285 25 8 1 40 3 421

III 1 4 42 97 13 1 1 16 16 191

IV 1 1 17 48 55 22 6 6 4 9 169

HauS I 8 5 25 6 2 3 49II 5 5 188 12 6 11 3 230

IV 3 12 13 8 2 3 2 43

HauN I 16 4 62 5 2 3 92III 1 5 5 32 5 1 1 1 5 11 67

IV 1 10 8 39 5 3 4 3 73

Ruos. I 11 7 48 6 6 78III 2 2 26 2 11 43

IV 10 8 20 8 5 1 1 8 61

Kivi. I 2 14 14 106 2 2 2 142III 2 4 1 9 168 3 2 47 11 247

IV 2 5 2 3 15 8 1 1 7 44

Vanh. I 7 4 64 2 77III 1 2 6 23 2 4 38

IV 6 17 21 3 1 1 1 1 51

Pork. I 26 1 5 32II 1 6 5 11 4 2 1 30

III 5 7 10 3 2 3 30

IV 1 2 2 8 14 7 5 1 4 1 4 49

Pari. I 6 3 162 1 3 175II 1 16 13 103 7 7 4 4 155

IV 1 4 7 32 7 3 1 1 5 3 64

Total 5 26 271 3 381 2268 259 104 15 30 9 159 181 3711

80

Appendix 3. Flower visits of bumblebees (workers in parenthesis). The counts, during which each plant species was visited,are marked as indices 1-4. Abbreviations of plant species: Ace pla = Acer platanoides, Ane nem = Anemone nemorosa, Aquvul = Aquilegia vulgaris, Bar vul = Barbarea vulgaris, Ber cra = Bergenia crassifolia, Cal pal = Caltha palustris, Car arb =Caragana arborescens, Cor sol = Corydalis solida, Geu riv = Geum rivale, Gle hed = Glechoma hederacea, Lam alb =Lamium album, Lam pur = Lamium purpureum, Lon xyl = Lonicera xylosteum, Lyc vis = Lychnis viscaria, Mal dom =Malus x domestica, Pru pad = Prunus padus, Rib alp = Ribes alpinum, Rib nig = R. nigrum, Rib rub = R. rubrum -group,Rib uva = R. uva-crispa, Sal sp. = Salix sp., Sam rac = Sambucus racemosa, Sil dio = Silene dioica, Tar sp. = Taraxacumsp., Tus far = Tussilago farfara, Vac myr = Vaccinium myrtillus, Vic cra = Vicia cracca, Vic sep = Vicia sepium

H’ J’ DI HO HY JO LA LU PA PR RU SO VE B P total

Ace pla 1. 2. 3 0.36 0.20 5 7 320 2 1 93 10 438

Ane nem 1. 3 1.06 2 1 2 5

Aqu vul 4 1 1

Bar vul 3 0.69 1 1 2

Ber cra 2. 3. 4 0.64 2 1 3

Cal pal 2. 3 1.10 1 1 1 3

Car arb 4 1.45 0.66 1 1 2(1)

25 4(2)

6 2 1 1 43(3)

Cor sol 1. 3 1.4 0.87 1 6 9 6 2 24

Geu riv 4 1.03 0.75 1 7 2 1 11

Gle hed 4 1 1

Lam alb 4 0.69 1 1 2

Lam pur 2 1 1

Lon xyl 4 0.56 1(1)

3(2)

4(3)

Lyc vis 4 1 1

Mal dom 3. 4 1.32 0.74 1 2 13(2)

2 2 2 22(2)

Pru pad 3 0.69 1 1 2

Rib alp 2. 3 1.07 1 5 1 1 8

Rib nig 3. 4 1.24 0.90 3(1)

5 2 1 11(1)

Rib rub 2. 3. 4 1.10 0.57 21(3)

1 4 64 2 7 1 100(3)

Rib uva 3 0.69 1 1 2

Sal spp. 1. 2. 3. 4 0.95 0.43 6 145 2 97 1286 84 47 3 66 34 1770

Sam rac 3 0.69 1 1 2

Sil dio 4 1.04 1 2 1 4

Tar spp. 2. 3. 4 1.62 0.68 3 11(1)

75(52)

178(3)

483(108)

102(5)

31(4)

2 28 5 106 1024(173)

Tus far 1. 2 1.49 3 2 1 1 1 8

Vac myr 3. 4 0.45 1 5 6

Vic cra 4 1 1

Vic sep 4 1.17 0.65 1 1 1 15 3 2 23

nest-seekers 2 14 54 73 16 5 2 23 189

total 5 26(1)

271(58)

3 381(3)

2268(112)

259(5)

104(6)

15 30 9 159 181 3711(185)

H’ 0.95 1.63 1.18 0.64 1.26 1.14 1.64 1.48 1.85 0.25 1.15 0.68 1.02 I)

J’ 0.74 0.48 0.51 0.43 0.56 0.60 0.95 0.35 0.98 0.44 0.41

81

Appendix 4. The mean densities (individuals/hectare) of different bumblebee species during each count, according tohabitat type. Both the queens and the workers are included.

count species FOF FOR GFI GAR FMF FMR RIP RUD total

I HO 0.2 0.0 - 0.0 0.0 0.0 1.5 0.0 0.1HY 2.3 1.4 - 0.0 4.6 2.3 14.6 2.2 3.3LA 0.8 0.0 - 17.4 3.0 0.7 5.2 4.8 2.1LU 9.7 3.0 - 24.0 32.2 12.2 74.0 36.5 20.9PA 1.4 1.5 - 0.0 0.7 0.0 13.4 0.3 1.3PR 1.2 0.0 - 2.9 1.4 0.1 1.0 0.3 0.8RU 0.0 0.0 - 0.0 0.0 0.1 0.0 0.0 0.0B 0.4 0.0 - 0.0 0.2 0.8 0.0 7.4 1.0

II HO 0.0 0.0 - 0.0 0.4 0.1 0.0 0.0 0.1HY 4.4 4.1 - 5.6 2.0 0.4 42.4 3.1 5.0JO 0.0 0.0 - 9.5 0.0 0.0 0.0 0.0 0.2LA 2.6 0.7 - 29.4 5.9 1.3 14.9 4.8 4.5LU 30.6 6.9 - 143.2 48.8 5.8 341.5 45.3 49.4PA 4.1 0.9 - 11.3 4.7 0.7 22.8 7.4 4.8PR 0.7 0.9 - 4.7 1.1 1.2 14.9 0.6 1.9RU 0.0 0.0 - 0.0 0.3 0.0 1.7 0.0 0.2B 3.1 0.0 - 76.1 0.5 0.1 48.9 0.0 5.9P 0.5 0.0 - 0.0 3.4 0.2 2.7 4.3 1.5

III HO 0.3 0.0 2.7 0.6 0.0 0.2 0.0 1.4 0.4HY 1.8 2.5 1.6 15.1 0.7 0.6 1.1 0.4 1.9JO 0.0 0.0 0.0 1.2 0.0 0.0 0.0 0.0 0.1LA 1.6 1.1 86.8 20.8 1.1 4.2 0.0 9.2 6.8LU 22.1 33.3 87.5 103.6 6.9 6.8 0.0 16.7 21.4PA 1.4 0.0 25.2 6.3 1.5 2.4 0.0 3.0 2.8PR 1.6 0.5 0.0 4.8 0.0 0.0 0.0 0.0 0.7RU 0.2 0.0 0.0 0.0 0.0 0.0 0.0 0.6 0.1SO 0.0 0.0 4.2 0.6 0.0 0.3 0.0 0.0 0.3B 8.2 5.3 0.0 7.1 0.0 0.0 0.0 0.0 2.9P 2.5 6.0 60.6 16.9 3.6 2.5 1.1 3.7 5.8

IV DI 0.0 0.0 0.7 2.0 0.3 0.0 0.0 0.0 0.2HO 0.2 1.9 3.1 2.0 0.0 0.2 0.0 0.7 0.5HY 1.6 1.8 24.2 10.0 0.3 1.9 5.4 3.7 3.6LA 0.6 0.0 42.8 23.4 1.1 3.2 0.7 7.8 5.9LU 1.9 8.0 165.5 26.0 4.0 7.6 0.0 15.2 17.8PA 2.8 4.4 22.2 17.4 2.3 2.3 0.0 7.1 4.9PR 0.6 0.0 15.6 9.4 0.1 0.4 0.0 0.8 1.8RU 0.0 0.0 1.1 2.4 0.3 0.3 0.0 0.8 0.4SO 0.0 0.2 6.8 1.9 0.2 0.3 0.0 4.2 1.0VE 0.1 0.0 3.4 0.0 0.3 0.1 0.0 0.0 0.3P 1.4 5.4 7.4 4.4 1.0 1.5 2.5 2.7 2.2

82

Appendix 5. The landscape structure of the study areas (total = indices counted for the whole study areas). Abbreviations ofthe indices: TLA = total landscape area (ha), CA = area of cultivated fields (ha), MPS = mean patch size (ha), PSSD =patch size standard deviation (ha), NumP = number of patches (in each class), ED = edge density (m/ha), SDI = landscapelevel diversity index and SEI = landscape leves evenness index for the study areas. In the formulas of diversity andevenness (Shannon-Weaver): pi = the contribution of the area of each patch class to the total area of the study area, S =number of patch classes in that study area. Patch classes: 1 = cultivated fields (c = cereal or oil crops in the year of year1996, g = grassland fields and permanent set-asides in the year of 1996), 2 = forest patches, 3 = small groups of trees orshrubs and planted allies of trees, 4 = old (forested) gardens, 5 = used gardens with open vegetation, 6 = buildings, 7 =surroundings of haystacks, collapsed haystacks, piles of stones and other open uncultivated patches of farmland, 8 =meadows and natural pastures, 9 = forested fields, 10 = clearings in the forest, young areas of forest, openings aroundelectrical lines (in the forest) and gravel pits, 11 = field margins, 12 = streamsides (riparian corridors), including artificialponds, 13 = ditches, 14 = main roads and 15 = other roads.

Jahk. Papp. Hamp. Ylän. Hauh. Ruos. Kivi. Vanh. Pork. Pari.TLA 95.2 124.6 120.5 128.8 136.0 98.0 128.5 240.3 92.9 175.4

CA1 66.9 66.4 69.3 88.8 92.8 74.6 99.4 170.2 67.3 126.1CAc 41.6 39.0 26.1 34.4 65.7 57.6 80.5 128.7 63.9 97.9CAg 25.3 27.4 43.2 54.4 27.2 17.0 18.9 41.6 3.4 28.2

MPStotal 0.21 0.20 0.22 0.17 0.15 0.23 0.27 0.19 0.20 0.16

PSSDtotal 0.84 0.77 1.00 0.63 0.58 0.74 0.93 0.90 0.70 0.59

NumPtotal 456 609 555 775 889 435 481 1249 461 1099NumP1 40 48 47 61 75 43 55 105 46 100NumP2 5 8 9 10 14 5 6 20 11 11NumP3 42 23 16 46 54 19 22 46 24 106NumP4 1 6 10 11 13 11 7 6 3 9NumP5 7 14 18 17 21 13 6 31 6 24NumP6 27 62 68 86 106 50 46 129 34 90NumP7 8 21 14 29 52 8 9 30 13 21NumP8 2 10 2 7 8 1 5 13 7 5NumP9 - 1 3 2 - 1 - - 6 3NumP10 1 1 3 6 - 2 - 4 1 1NumP11 245 308 285 418 343 220 268 684 249 589NumP12 2 2 1 5 2 3 3 5 - 3NumP13 61 62 35 41 49 29 37 131 44 98NumP14 1 1 1 1 1 3 1 1 1 1NumP15 14 42 43 35 60 27 16 44 22 39

EDtotal 1262.4 1260.0 1027.0 1362.7 1417.6 1215.9 1170.6 1321.6 1323.1 1620.5ED1 242.6 208.9 193.6 280.5 299.6 266.4 257.0 249.6 257.8 368.1ED2 47.7 93.4 81.0 38.6 51.0 29.9 26.7 67.7 63.4 46.3ED3 29.9 16.2 12.5 29.8 37.1 13.2 13.4 14.6 15.9 25.5ED4 8.7 11.0 16.3 20.8 26.4 13.2 15.6 8.5 13.0 11.8ED5 30.4 75.5 63.4 80.2 99.9 58.9 60.6 65.9 41.8 51.2ED6 11.5 25.7 23.6 31.1 37.4 21.0 22.1 24.1 17.3 19.9ED7 7.3 14.7 8.8 12.1 34.9 9.8 7.4 13.2 12.7 10.1ED8 2.2 24.5 1.9 19.7 6.7 2.3 6.8 11.7 11.9 5.3ED9 - 1.8 9.5 4.5 - 2.2 - - - 6.3ED10 5.9 5.3 11.3 8.1 - 2.5 - 4.1 2.1 4.3ED11 543.3 444.8 361.3 526.6 549.3 478.6 471.8 548.8 534.6 698.4ED12 19.9 32.7 8.9 62.1 16.4 43.8 15.7 26.6 - 4.6ED13 213.8 158.1 74.8 98.7 96.9 103.0 131.9 186.1 179.7 254.4ED14 67.1 46.2 51.5 61.1 48.7 55.7 72.3 49.8 39.2 36.3ED15 32.1 101.2 108.5 88.7 113.3 96.4 69.4 56.7 133.6 77.9

SDI 1.74 2.04 2.03 1.99 1.94 1.90 1.83 1.85 1.80 1.69SEI 0.66 0.75 0.75 0.74 0.75 0.70 0.71 0.70 0.70 0.62