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The Balance between Positive and Negative Plant Interactions and Its Relationship toEnvironmental Gradients: A ModelAuthor(s): Rob W. Brooker and Terry V. CallaghanReviewed work(s):Source: Oikos, Vol. 81, No. 1 (Feb., 1998), pp. 196-207Published by: Blackwell Publishing on behalf of Nordic Society OikosStable URL: http://www.jstor.org/stable/3546481 .Accessed: 18/05/2012 11:35

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FORUM FORUM

FORUM

FORUM is intended for new ideas or new ways of interpreting existing information. It provides a chance for suggesting hypotheses and for challenging current thinking on ecological issues. A lighter prose, designed to attract readers, will be permitted. Formal research reports, albeit short, will not be accepted, and all contributions should be concise with a relatively short list of references. A summary is not required.

The balance between positive and negative plant interactions and its relationship to environmental gradients: a model

Rob W. Brooker and Terry V. Callaghan, Sheffield Centre for Arctic Ecology, Dept of Animal and Plant Sciences, Univ. of Sheffield, 26 Taptonville Road, Sheffield, UK S10 5BR (bop95rwb@sheffield.ac.uk).

Positive, beneficial interactions between individuals within plant communities have been observed in nature and recorded in a wide variety of ecological experiments. However, the existence of such interactions has been, and continues to be, largely ignored by most ecological researchers. We present here a new model that combines current ecological theory on plant competition, and its relationship to environmental severity, with evidence from a range of studies that show positive plant interactions in the field. The model describes a hypothetical relationship between the intensity of positive (e.g. mutualistic) and negative (e.g. competitive) interactions between members of a plant commu- nity, and the severity of the external environment. It also provides an explanation for the past and current neglect of positive plant interactions, and for the conflicting results from plant community manipulation experiments examining such phe- nomena. Potential directions for future research into positive plant interactions are proposed.

The existence and importance of positive and beneficial interactions within certain plant communities have re- cently been highlighted by a number of authors (Callaghan and Emanuelsson 1985, Fowler 1986, Hunter and Aarssen 1988, Bertness and Hacker 1994, Bertness and Callaway 1995). They state that this sub- ject, a basic tenet of plant ecological theory during its initial development at the start of this century, has suffered neglect during the last 20 to 30 years. Recently the study of ecological interactions between plants has been dominated by competition, a bias which possibly stems in part from the concentration of ecological research in competition-rich temperate ecosystems within easy reach of most experimenters (Callaghan and Emanuelsson 1985, Bertness and Callaway 1995), coupled with strong arguments concerning the primacy of competition as a driving force in ecological processes (e.g. Connell and Slatyer 1977).

Despite this apparent neglect, positive plant interac- tions are again starting to be addressed with the same quantitative approach that competition has already been afforded (Aarssen and Epp 1990). Perhaps the

ongoing and apparently insoluble debates surrounding certain aspects of competition, and its relationship to productivity and diversity, have made researchers more willing to examine what may originally have seemed unorthodox hypotheses. However, regardless of the emergence of new evidence to support the call for increased recognition of positive plant interactions within ecology, "the general importance of positive interactions to community diversity, structure and pro- ductivity is rarely acknowledged" (Bertness and Callaway 1995), and they "are largely ignored in cur- rent models of natural community organisation" (Bert- ness and Hacker 1994).

In this article we discuss certain unifying aspects of the evidence produced for the occurrence of positive plant interactions. Secondly we suggest a novel link between positive plant interactions and existing ecologi- cal theory. Finally we suggest potential directions for research into positive interactions within plant commu- nities.

Before proceeding it is necessary to set limitations upon the scope of this article. "Positive plant interac- tions" as it is used here, relates (unless otherwise stated) only to those interactions occurring between physiolog- ically separate unitary plants. They can be either inter- or intraspecific interactions and in all cases at least one of the interacting individuals benefits, this benefit being reflected in an increase in a recognised measure of plant performance, for example biomass or reproductive out- put. The other individual either remains unaltered by, or benefits from, the interaction. The interaction can be defined as either a mutualism (the interaction being obligatory) or a commensalism (the interaction being beneficial to one individual, the other remaining unaf- fected) (sensu Odum 1968). A number of positive inter- actions between plants can occur through physiological connections, for example via the connections between the ramets of clonal plants, root grafts between trees or mycorrhizal connections between grassland species

OIKOS 81:1 (1998) 196

Table 1. Evidence for positive interactions taken from ecological literature. The table shows the author(s) of the work, the environment of the community involved, the stress or

disturbance variable impacting upon plants within those environments, the species involved in the positive plant interaction i.e. species 1 and species 2 (in some cases of simple density-dependent survival these can be the same species), and the form and mechanism of their positive interaction.

Authors Environment Stress/disturbance Species 1 Species 2 Interaction and mechanism variable

Bertness and Hacker High salt marsh intertidal High soil salinity due to Juncus gerardi Iva frutescens (marsh Juncus shading limiting evaporative soil . I I -__wte los,an tneeioe siinty ul-up.

Bertness and Shumway (1993)

Carlsson and Callaghan (1991)

Fowler (1986)

Grindey (1975)

Heilbronn and Walton (1984)

Jonasson (1992)

Mailette (1988)

Okland and 0kland (1996)

Low salt marsh intertidal zone

Arctic mountain fellfield

Arid desert

Limestone scree

Subantarctic fellfield scree slopes

Arctic shrub tundra

Arctic shrub tundra

evaporative salt concentration

High soil salinity due to evaporative salt concentration

Extreme cold, and nutrient impoverished soil

Extremes of temperature, low water supply and grazing

Low soil nutrient and moisture availability

Frost-heaving scree slope movement

Low temperatures and limited soil nutrient availability

Herbivory, disease, low temperatures, and low soil nutrient availability

Arctic boreal spruce forest Low light and water understorey availability

Spartina patens

Cassiope tetragona and Empetrum hermaphroditum

elder)

Juncus gerardi

Carex bigelowii

Desert shrubs Carnegia gigantea (species unspecified) (sagauro cactus)

Bryophyte species (unspecified)

Phleum alpinum

Betula nana

Vaccinium uliginosum, V. angustifolium and V. myrtilloides

Hylocomium splendens

Hieracium pilosella

Deschampsia antarctica, Festuca contracta and Acaena tenera

Vaccinium myrtilus

Vacccinium uliginosum, V. angustifolium and V. myrtilloides

Hylocomium splendens

water loss, and therelore salinity bulld-up. Enables Iva to have a lower distribution down the marsh.

Spartina shading limiting evaporative soil water loss, and therefore salinity build-up. Enables Juncus to have a lower distribution down the march.

Carex has enhanced growth in the vicinity of the dwarf shrubs, possibly through the provision of shelter and their action as snow and litter traps, providing warmer wetter and richer growing conditions.

Young Carnegia plants growing beneath shrubs exist in a more stable insulated microclimate, and are also protected from grazing defoliation.

Increased germination and growth of Hieracium seedlings within the moss dominated areas, possibly the result of improved water retention by the mosses.

High densities of Phleum roots provide stable islands for colonisation by the benefactees, with a reduction of scree movement and root damage.

Decreased abundance of Vaccinium following Betula removal. No mechanism postulated.

Close proximity to dominant Vaccinium Species in zones outside of optimum range produces increased growth in non- dominant Vaccinium species, possibly through protection from herbivory, disease or via improved microclimatic conditions

Increased Hylocomium density increases the mean size of mature moss segements; attributed to enhanced moisture conditions.

0

0

(1994) zone

:w^~~ ~~(Hunter and Aarssen 1988). Although these interactions 7

' - ? are not the primary focus of this article, their occur- - ar e &? O rence should be acknowledged.

t -o o '.

= 4

?E fi?o =O _. D 0 Evidence and mechanisms

e E E._ = :cx . = U The formulation of widely applicable rules of ecology ? : ' ,= ^ H , ~ ~ depends upon the existence and observation of wide-

:o os; X | o 3 g ? E spread reoccurring patterns within ecosystems and eco- 5 e)^ i| B Ur *? 3^ ^ logical interactions. We have tried to identify such

e ~

. e

.> X e .= ? v patterns from some of the recent evidence demonstrat- S O , t t

U e E ing the occurrence of positive plant interactions (Table

Q . s o oc ; o ~o 2o 1). There appear to be two common features linking i t) ? E - C E Y % a - these studies.

1) The interacting species occur within relatively (N x Qsevere environments such as polar tundra (Heil-

a*| ~ ~~, *|f,2~ ;bronn and Walton 1984, Carlsson and Callaghan v E ? ,, 1991, Shevtsova et al. 1995), saline marshes (Bert-

<,~-^ c~.s~ ~ness and Shumway 1993, Bertness and Hacker |4t ~ 1-b4"~ i1994, Bertness and Callaway 1995) or arid desert F?^ ~ c?;q~ ^~ >ecosystems (Fowler 1986).

2) The environmental factor constraining plant growth or survival is one that can be alleviated by

P,, - ~ the physical presence of another plant. The posi-

' i ? tive interaction does not occur through the ex- e E .1 change of resources but through an amelioration

~*_?~t ^,3tof the conditions of the external environment og^ ~ gQ~a~ -?~ >(Hunter and Aarsson 1988). As a result of this the

strength of the interaction is often density depen- 'o 3 dent (Callaghan and Emanuelsson 1985), for ex-

,-o O ample increased plant density can lead to

cl ct >, ct f <l et ;^ eI

increased litter accumulation (Wilson and Keddy |t ^e 1986), improved water status (Okland and 0kland

e' .E - 1996), increased soil stability (Heilbronn and Wal-

|) 8< ' . 5 ton 1984) or decreased evaporative water loss sol^~ E c^ O~ eg~ ;(Bertness and Hacker 1994). They are therefore

. ., - o . not dependent upon physical connections between ,; = ~ m the interacting individuals, but rather act through

feedbacks on the external environment. The influ- ence of this second factor may be important in

ct~~^~~~= ~understanding why positive interactions are not

Xr^~~ eg~~~~ |evident in all plant-plant interactions in severe v + :< environments, i.e. in some situations the con-

Ocl yle< ES straining factor is not one that can be alleviated * 0|? *- || through the physical presence of another plant.

.a^o;~~ . Environmental severity is taken here as being a combi- .,. *-C nation of both stress and disturbance (sensu Grime

1979). Stress includes those phenomena restricting pho- ,~^~~~~~, ~tosynthetic production, for example limited supply of

0o ;>,^ resources such as light, water and soil nutrients, but can .t ^~ ~ also include environmental factors such as extremes of

~ ' ee ^i temperature that can directly limit photosynthesis. Dis-

^ ~ ~~Q a,t^~ S~ 4turbance phenomena, for example grazing or soil ero- o = = sion, cause partial or total destruction of the plant

-S : > ,- ? o biomass. The occurrence of stress is often a continuous - ~ ~ 3 , 3 process whereas disturbance is mainly episodic.

198 OIKOS 81:1 (1998)

Since much of the evidence for positive plant interac- tions (Table 1) comes from extreme environments, does this mean that as community organising processes they do not occur in less stressful, more productive environ- ments? This is unlikely; we can easily conceive that in any ecosystem there will be situations where the physi- cal presence of one plant will be beneficial to another plant within its vicinity. For example, increased stand density may provide protection against wind damage in forestry plantations (Foster 1988) or leguminous species may cause nitrogen enrichment of soils (Barnes and Archer 1996), leading to increased foliage densities and decreasing evaporative water loss from the soil. Why then are positive interactions not commonly observed?

We propose that experiments undertaken in less severe environments have found little evidence of posi- tive plant interactions because, although such interac- tions occur, they are masked by the relatively greater impact of competition for resources within such envi- ronments. In addition there appears to be an active relationship between the severity of the external envi- ronment and the overall direction, either positive (beneficial) or negative (detrimental), of plant-plant interactions.

We have defined environmental severity as a combi- nation of both stress and disturbance. Although there seems to be a consensus concerning the relationship between the level of competition and disturbance, that between competition and stress is still contentious (Tay- lor et al. 1990). The aim of this paper is not to summarise this debate or attempt to find a solution to it. Therefore in the following discussion we will primar- ily examine the relationships between positive and negative plant-plant interactions and gradients of dis- turbance. Once we have outlined our model using dis- turbance as our independent environmental factor, we shall briefly examine the relationship between competi- tion (and positive interactions) and stress.

Positive and negative interactions, and gradients of disturbance When examining the relationship of competition or positive interactions to any factor such as stress or disturbance, possible confusion may ensue as a result of not specifying whether one is dealing with the intensity or importance of competition (Welden and Slauson 1986). Competition intensity is the absolute degree of reduction of a plant's success via the presence of its neighbour. Competition importance is "the relative de-

gree to which competition contributes to the overall decrease in growth rate, metabolism, fecundity, sur- vival or fitness of that organism below its optimal condition". The intensity and the importance of compe- tition "need not be correlated" (Welden and Slauson 1986).

Competition intensity will affect growth parameters such as biomass. However, the only measure of the importance of competition is its impact upon the fitness of a plant, which will be measurable as its reproductive output. Therefore, when we discuss the outcome of the interaction between two individuals and the relative importance of competition and positive interactions in causing that outcome, we would measure it as some function of the fitness and reproductive output of the individuals.

As mentioned, there currently appears to be a con- sensus in plant ecology that with increasing levels of disturbance both the intensity and importance of com- petition as a community structuring process and selec- tive force are reduced (Taylor et al. 1990). Evidence from experimentation (Table 1) suggests that, just as the importance and intensity of competition seem to decrease with increased disturbance, so positive interac- tions seem to become more important and intense. Why should this relationship occur? A number of factors may interact to produce this relationship:

1) As stated, the importance of competition is re- duced by increased environmental severity.

2) In certain extreme conditions disturbance within the environment is the primary factor limiting the growth, development and fitness of vegetation (Porsild 1951, Billings 1978, 1987, Callaghan 1987, Callaghan and Jonasson 1995). Positive in- teractions can act through the amelioration of disturbance (although it should be pointed out that they might also act through the amelioration of stress, Table 1). Therefore they may have a greater impact in harsh conditions, since the fac- tor which they alleviate also has an enhanced impact on plant development and survival. For example facilitation, a well-known example of a positive plant interaction, "appears to be impor- tant only in severe environments ... and primarily in the stages of colonisation and early community development" and, as the productivity and biomass of the community increases, with a con- comitant decrease in disturbance levels through the ameliatory effect of the physical presence of plants (e.g. in stabilising scree slopes or providing increased protection against herbivory) competi- tive interactions "become progressively more im- portant" (Walker and Chapin 1987).

3) The results of species interactions observed by researchers conducting community manipulations are the final outcome of a balance between posi- tive (mutualistic or protocooperative) and nega- tive (e.g. competitive) interactions. Any plants in close proximity are likely to use the same re- sources to a certain extent, and may inflict re- source limitations upon one another (Grime 1987) so that, since amelioration of physical severity seems to depend upon close proximity, "plants

OIKOS 81:1 (1998) 199

100

00

I -

O o

80

60

40

20

0 Distance through

space or time

100 ftf I%% 50 ftf . -20 _

-40 - - . . - p

D -- O0

-60

-80 -

-100 -

Fig. 1. Hypothetical relationship between the importance of P (positive plant interactions) and N (negative plant interactions), and the observable outcome of community manipulation experiments (O), to a gradient of decreasing disturbance (D) through space or time (x-axis) used in the production of plant-plant interaction surfaces (Figs 2 and 4). All values are in arbitrary units, showing the relative size of each factor as used in the model (see Appendix 1).

that benefit from their neighbors ... are likely also to compete with them" (Hunter and Aarssen 1988).

We can combine these points in an attempt to explain the apparent relationship of positive plant interactions, competition and severity of disturbance. The resulting hypothesis holds that under conditions of high distur- bance the importance of positive interactions is greatly enhanced. At the same time the importance of competi- tion as a force is greatly diminished due to the relatively greater impact of disturbance on plant survival and

reproduction, as outlined above. Since the outcome of

any plant-plant interaction is the sum total of the

impact of these two opposing forces, the outcome of

plant-plant interactions under extremely disturbed envi- ronmental conditions is more likely to be a positive relationship.

We propose that community manipulation experi- ments are more likely to reveal positive plant-plant interactions in highly disturbed environments, manifest-

ing as positive density-dependent effects on the fitness of individuals. As disturbance within the environment is reduced, either through time or space, competition becomes more important and in parallel positive interac- tions become less important, so that competition be- comes the dominant selective force in plant-plant interactions. Because we observe only the final outcome of this balance, in temperate ecosystems competition may be the only force apparent within plant communi- ties. Also, because certain abiotic environmental distur- bances are episodic, the chance of detecting positive interactions depends to some extent on the duration of observations.

A simple model

It is possible to construct an extremely simple model to illustrate this hypothesis. Let us consider the observable outcome of an hypothetical plant community manipula- tion experiment within a monoculture stand of constant

density. Since the observable outcome of any community manipulation is the result of a number of positive and

negative interactions we can express it as:

O=P+N

where O is the observable outcome in terms of the net direction of the interaction, P the importance of positive plant-plant interactions (e.g. mutualism and facilita- tion) and N the importance of negative plant-plant interactions (e.g. competition or allelopathy). Values of P are given a positive sign, and values of N are given a

negative sign, reflecting their opposing actions. P and N, for simplicity, are considered as being directly propor- tional to the level of disturbance, P being positively correlated with disturbance, and N negatively correlated with disturbance.

Let us first examine the relationship between 0, P and N within this monoculture along a gradient of decreasing disturbance (Fig. 1). As proposed by our model, as environmental severity decreases the value of O tends to decrease, the outcome of the relationship between individuals becoming progressively more nega- tive. When O is above the x-axis (i.e. O > 0), the net observable interaction between individuals is positive, and when it is below the x-axis (i.e. 0 < 0) the net

OIKOS 81:1 (1998)

r~~~~~

to oft

".% %*. ft

* . asf % .

4f a % ftf %% ft

At * r~~~~~~~t* .

r~~~~~~~f C r~~~~~I%4p

200

0 a

0

C) 0

4)

-0 co~ t

100

*50-100

*0-50

*-50-0 -100-50

*-150-100

*-200-150

time(t)

space(s) 100

Fig. 2. Three-dimensional plot of observable plant-plant interaction outcome (O) against gradients of disturbance through time (t) and space (s) as illustrated in Fig. 1. All areas where O > 0 indicate zones of net positive plant-plant interaction. All areas where O < 0 indicate zones of net negative plant-plant interaction (e.g. competition). All values are in arbitrary units.

observable interaction between individuals is a negative one.

Levels of disturbance may vary either through time or space. Through time they may vary either cyclically (e.g. in a seasonally variable pattern, as in the case of periglacial soil movement processes in alpine or arctic regions), episodically at random (e.g. as a result of chaotic weather features such as extreme storms), or with a monodirectional trend (e.g. decreasing in inten- sity during the course of succession). Examples of spa- tial gradients of disturbance exist in a multitude of situations, for example from the edge to the centre of a scree slope. So the gradient of disturbance severity described above (Fig. 1) could be either a spatial or temporal one (hence the x-axis is defined as distance through either space or time). It is possible that the two types of gradient may interact. For example what may be a beneficially high density of individuals on a mov- ing alpine solifluction lobe during the winter may be the cause of competition for water during a dry summer period. We can combine these gradients of disturbance to show the interactions of space and time in altering the balance of positive and negative interactions within our hypothetical plant community. Now the observable outcome (O) of the interactions within our monocul- ture stand is expressed as:

o = N,+ P + N,+ P,

where N and P are the importance of negative or positive interactions at a particular point in time (t) or space (s). Using hypothetical data sets (Appendix 1) that illustrate the relative levels of N and P under different levels of disturbance (D) as proposed by the model, this equation will produce plant-plant interac- tion surfaces, the three axes of each graph being the position in space, the position in time and the observ- able outcome of the interaction. The position of a point upon this surface relative to the x-axis indicates whether the observable outcome (O) will tend to be a positive or negative interaction.

Using this equation we will now examine two hypo- thetical interactions between patterns of disturbance within space and time. In both examples the relation- ship of P and N to the gradient of disturbance through space will be that indicated in Fig. 1.

Example 1: Successional progression The relationship of P and N to changes in disturbance through time in this example is also that shown in Fig. 1. As disturbance levels decrease with successional pro- gression through time, so the importance of P also decreases, but the importance of N increases (i.e. N

OIKOS 81:1 (1998) 201

100

80 80

g w

I 8 40

|t 20 . -4 **? 'IO

i ? _30 0 S|I I I S Distance through time a > ^' 50 a 100

v , -20 - ^ o i \ r

_g -40 -

| -60- ---N -----D

-80 - -100_ -100 - N

Fig. 3. Hypothetical relationship between the importance of P (positive plant interactions) and N (negative plant interactions) to cyclically fluctuating levels of disturbance (D) through time (x-axis) used in the production of the plant-plant interaction surface shown in Fig. 4. The relationship between N, P and D, although based upon the predictions of the model, is purely illustrative. All values are in arbitrary units (see Appendix 1 for data set).

becomes progressively more negative). The subsequent interaction surface (Fig. 2) indicates the trend from positive to negative interactions through time, a rela- tionship that would perhaps be expected during succes- sion. Once the conditions of the environment are sufficiently ameliorated, for example through the action of facilitatory mechanisms or geological processes such as weathering, then plant-plant interactions tend to become more competitive. The shape of the interaction surface also indicates that in stable environments, even at the initiation of succession, competition may occur.

Example 2: Cyclical patterns In this example P and N have a cyclical relationship to disturbance through time (Fig. 3). At either end of the time axis there are high levels of disturbance. This pattern of disturbance could be caused by a seasonally active disturbance factor such as winter-time ice crystal abrasion of exposed plant tissue, or solifluction activity in alpine or arctic environments. In the middle of the time axis the conditions are less severe, as would per- haps be the case during the summer period. The inter- action surface (Fig. 4) illustrates the subsequent trend of plant-plant interactions toward competition during the mild period, and the increased importance of posi- tive interactions, perhaps through the provision of shel- ter and protection from ice-crystal abrasion, during more disturbed periods. In a harsher environment the interactions cycle between positive and negative observ- able outcomes, whereas in the more clement environ-

ment the interactions are always competitive, although the force of this negative interaction varies.

This model, as stated previously, is extremely crude, a number of factors having been excluded from it in the

quest for simplicity. For example, it assumes that the relationship of disturbance through space is constant

through time, and that the relationships of N and P to disturbance run in parallel. However, this need not necessarily be the case. A more complex relationship of N and P to disturbance in space and time can be introduced by altering the data sets, possibly using data from field experimentation, and will simply produce a more complex interaction surface.

One interesting feature of this model is that the observable outcome of a manipulation is variable

through time, and the net outcome will be the sum of O for the entire period of a plant's life. Short-term studies of plant-plant interactions may fail to find positive plant interactions either because they are being masked by competitive interactions, or because they are not occurring during the period of the manipulation. This latter explanation may result from the periodic nature of the disturbance factor and the associated periodicity of the positive interactions. For example the benefits of high stand density in forestry plantations are only obvious during occasional short periods of intense wind (Everham and Brokaw 1996). When these factors are combined with the tendency for research to be focused within temperate, easily accessible, productive ecosys-

202 OIKOS 81:1 (1998)

0

0

0

Cd

a, o O 0 I1. ?

100

50-100

*0-50

m-50-0 1-100-50

-150-100

*-200-150

time(t)

space(s) 100

Fig. 4. Three-dimensional plot of observable plant-plant interaction outcome (O) against gradients of environmental severity through time (t) (Fig. 3) and space (s) (Fig. 1). All areas O > 0 indicate zones of net positive plant-plant interaction. All areas O < 0 indicate zones of net negative plant-plant interaction (e.g. competition). All values are in arbitrary units.

tems, the bias toward the study of competition is per- haps not surprising, and could lead to the subsequent neglect of positive interactions as discussed in the in- troduction.

Competition and stress

Although we have so far limited our discussion to an examination of the impact of disturbance on the bal- ance between positive and negative interactions, it is important to consider at some point the effect of stress. From experimental evidence (Table 1) we can see that positive plant interactions can occur through the ame- lioration of factors that are classified as stress vari- ables, for example water or nutrient shortage. In addition stress, when combined with disturbance (often as "environmental severity"), can have severe impacts on plant growth, development and reproduction (Walker and Chapin 1987). The inclusion of a stress variable in this model, or indeed any variable influenc- ing the importance of competition or positive plant interactions, presents no problems. However, there is some debate as to the exact nature of the relationship between the level of stress and the intensity and impor- tance of competition. The opposing opinions of two of the debate's main protagonists are outlined below.

1) The Taylor et al. hypothesis The first of the two main hypotheses is that put for- ward by Taylor et al. (1990). They propose that the level of competition within a community is not directly related to the productivity of that community, or the level of stress within the environment. For example, plant species within extremely unproductive, stressful environments will not consistently be subject to lower levels of competition than those in more productive environments. Rather the levels of competition within a particular environment are related to the distance of the actual productivity of that environment from its theo- retical maximum carrying capacity, K (MacArthur and Wilson 1967), which is itself a consequence of the intensity and frequency of disturbance events. The closer a community of plants is to its carrying capacity, the more intense the competition for a given level of limiting resource, irrespective of the level of stress within that environment. From this model one can predict that in stressed environments, competition be- tween individuals can be as intense as in more produc- tive environments and possibly "the main organising force in the scanty vegetation" (Oksanen 1982).

2) The Grime et al. hypothesis The opposing view is that put forward by Grime and co-workers (Grime 1974, 1977, 1979, 1987). It states

OIKOS 81:1 (1998) 203

that the relative importance of competition as a com-

munity structuring process is inversely proportional to the levels of stress (or disturbance) within an environ- ment. Therefore as the levels of stress increase, selective forces within the environment are more strongly related to survival within the severe conditions than they are to "winning" competitive interactions with other plants.

Both hypotheses are supported by a variety of empir- ical, experimental data (Wijk 1986, Campbell and Grime 1992, Goldberg and Barton 1992, Wilson and Tilman 1993, Bonser and Reader 1995). The aim here is not to attempt a reconciliation of these two theories. It seems reasonable to predict that for a given level of resource supply and demand the intensity of competi- tion should remain constant. However, resource supply is not the only component of stress. Other factors, not

directly related to competitive interactions for re- sources, may limit growth and competition, and thus also reproductive output and fitness. For the most part along a gradient of increasing stress, although the absolute intensity of competition will follow the pattern outlined by Taylor et al. (1990), the importance of

competition is probably reduced, as predicted by Grime, since in very stressed environments the abiotic conditions have a much greater selective impact. As stated by Welden and Slauson (1986) "members of two species living together in a very stressful habitat may require many of the same resource items, and thus compete intensely. At the same time their growth rates, survival or reproductive success may be determined almost entirely by their abilities to cope with or escape abiotic stress, defoliation by herbivores, [or] other forms of disturbance,... thus rendering competition unimportant". In addition, increased stress may act to alter the intensity of competition by reducing resource demand. In particularly severe environments it is doubtful that competition can play much of a role either as a community-structuring force altering plant biomass or growth rate (competition intensity) or its reproductive success (competition importance). It is also worth considering the position of vegetative prolif- eration in this scheme, since the intensity of competi- tion will impact upon growth rates, which will have a direct influence on the fitness of clonal species. Separa- tion of competition intensity and importance may therefore not be as straightforward as is suggested by the scheme of Welden and Slauson.

Positive plant interactions and current research It is important to reiterate that, irrespective of the debate concerning the links between competition, stress and disturbance, our model still illustrates a number of important points, and can provide us with some inter- esting explanatory hypotheses concerning certain eco- logical conundra, having ramifications in several fields

of plant community ecology (and possibly other areas of ecology).

The model emphasises the need to consider the bal- ance between opposing forces in producing observable

experimental outcomes. DiTommaso and Aarssen

(1991) have suggested a similar counter-balancing rela- tionship of competition and "beneficence" between

plants in determining the overall outcome of plant- plant interactions. However, ecological research may often oversimplify interactions by ignoring such bal- ances, and also their long-term nature. It is only through long-term studies that we will be able to get a true indication of the outcome of the interactions be- tween plant species. This may explain certain paradoxi- cal results such as the apparent coexistence of species that would at first appear to be strongly competitive. If there is a sufficiently severe period then this may make the overall balance of interactions between the two species positive, and thus promote coexistence, or at least prevent the competitive dominance of one species.

An inherent aspect of this model is the ability of plants to modify their environments. Wilson and Ag- new (1992) also considered such environmental feed- backs acting as the basis of positive feedback switches, possibly leading to the divergence of the form of neigh- bouring communities in a way that could either not be explained by an external, environmental phenomenon, or that enhanced the divergence of community compo- sitions initiated by such phenomena. However, they did not consider the interactions between species in the communities where these feedbacks were operating. Many of the switches that they discuss could be the basis for positive plant interactions, for example the entrapment of soil by roots, or the increased supply of water from occult precipitation collected by vegetation. Both of these interactions may benefit the individuals involved, with increased densities of plants being bene- ficial either by accumulating more soil within the root system or by capturing more air-borne moisture. Posi- tive interactions, especially in the initial stages of com- munity development, could have important conse- quences not only for the speed or mechanism of succes- sion (Connell and Slatyer 1977), but also for its direc- tion.

The selective impact of positive plant interactions Our model predicts that positive plant interactions oc- cur in the majority of ecosystems, and may be involved in many ecosystem processes. Therefore, further re- search on the mechanisms and effects of positive plant interactions may be essential for a thorough under- standing of the factors involved in the structuring of plant communities. One potential direction for research into positive plant interactions is that of investigating

OIKOS 81:1 (1998) 204

their evolutionary impact. If they are of consequence in effecting the mortality or fecundity of plants in extreme conditions, then we can infer that they will have some selective impact on plant traits. Can we hypothesise in what way this force will have selected for plant charac- teristics? A number of possible traits that could en- hance positive plant interactions are outlined below.

I) Decreased dispersal distance of seeds Increased offspring density near to parent plants may bring density-dependent advantages such as increased seedling survival (Walton 1922, Table 1). Vivipary may be one adaptation to this selective force, since not only will it increase the survival probabilities of offspring through increased maternal investment in large propag- ules (Billings and Mooney 1968, Callaghan and Emanuelsson 1985), but it will also act to increase the density of conspecifics around the parent plant by limiting propagule dispersal distances.

2) Compact morphology of plants This adaptation could increase the density of plant foliage or biomass within a given space and so enhance positive density-dependent effects. Such a situation may be the cause of the compact form of moss cush- ions (Callaghan and Emanuelsson 1985).

3) Limited response to improved environmental condi- tions A large response to improved environmental condi- tions would perhaps indicate competitive tendencies and plastic morphology. Plants that had undergone selection for reduced competition would less readily respond to improved growing conditions. This would

produce extremely determinate growth in plant species from extreme environments, as has been shown to be the case for certain species of cushion plant (Spomer 1964, 1979).

4) Increased tendency for mycorrhizal associations between plants within a community Seedlings can utilise mycorrhizal connections with ma- ture plants as a means of obtaining resources from parent plants within a community (Hunter and Aarssen 1988). Increased susceptibility to mycorrhizal infection would increase the chances of this positive interaction occurring. Many of the dominant species from arctic tundra ecosystems, such as dwarf shrubs, have been shown to be mycorrhizal (Michelsen et al. 1995), and the potential enhancement of positive inter- actions may be one subsequent benefit.

5) Increased tendency for clonality Clonality can be viewed as a more advanced form of positive plant interaction. Ramets within a clone are analogous to individuals within a population (Callaghan 1988). The benefits of the physiological

connections that can exist between these individuals are numerous. The connections enable resource ex- change between individual ramets (Salzmann and Parker 1985, Stuefer et al. 1994), and tighter regulation of the ramet populations' growth pattern in order to make optimum use of heterogenous environments (J6nsd6ttir and Callaghan 1988). The positive interac- tions occurring between the units of clonal plants can

improve the conditions of both their internal and exter- nal environments, and so they may be considered as more advanced than those that occur between unitary plants and alter only the external environment. En- hanced ability for positive interactions may be related to the increased occurrence of clonal species within extreme environments (Callaghan and Collins 1981).

Many of these traits are characteristic of species from arctic ecosystems. As well as the occurrence of species with such traits, the Arctic is particularly suited to research into positive plant interactions for a number of reasons. Arctic environments contain a wide variety of stress or disturbance factors such as low tempera- ture, limited nutrient supply, intense ice-crystal abra- sion and destructive soil movement processes such as frost heaving. The severity of the physical environment produces the primary limitation on plant growth (Por- sild 1951, Billings and Mooney 1968, Savile 1972, Billings 1978, 1987, Callaghan 1987, Callaghan and Jonasson 1995), thus increasing the potential for posi- tive interactions to occur, and to be significantly beneficial to those species involved. According to our

hypothesis, the combination of these factors within arctic environments would also increase the probability of positive interactions being observed, and thus being possibly subjected to experimentation. Arctic ecosys- tems could therefore prove extremely fruitful in any future experimentation on positive plant interactions, such as the examination of possible adaptations.

However, in any extreme environment a primary problem with the search for adaptations that enhance positive plant interactions is that of separating this form of adaptation from that designed to exploit the very localised areas of improved microclimate and re- source availability that can occur in extreme environ- ments. Localised improvement of conditions, for

example increased temperature or nutrient availability, can be caused either by the beneficial impact of plants upon the environment (Table 1), or by the features of small scale landscape topography (Crawford and Ab- bott 1994). The impact of both factors, biotic and

geographic, will be similar, with similar adaptations producing aggregations of individuals. It may be the case that we already have evidence of the evolutionary impact of positive plant-plant interactions, but have never examined it in the light of this possible interpre- tation.

OIKOS 81:1 (1998) 205

Conclusions

Consideration of positive plant-plant interactions may be a key step in obtaining a firm understanding of the dynamics of plant communities. Without further re- search to establish the importance of such interactions for ecosystem function, under a range of environmental conditions and over prolonged periods of time, we will never truly be able to say that we understand how plant communities operate. We should at least be certain that positive plant interactions are unimportant in a particu- lar ecosystem or environment before we banish them from our interpretation of experimental results. We believe that the simple model that we have presented here may act as a focal point for future research into positive plant interactions, and may help to integrate this developing branch of plant ecology with existing ecological theory. We also hope that it will further stimulate interest in this neglected branch of plant ecology.

Acknowledgements - The authors would like to thank Phil Grime for his discussions and encouragement during the devel- opment of many of the ideas within this paper, and Phil Grime, Sven Jonasson and Lonnie Aarssen for their useful comments concerning the manuscript.

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Appendix 1

All figures were produced using Microsoft Excel (ver. 5.0). Data sets have no scale, the values being purely arbitrary and illustrative, indicating the relative importance of the different factors.

Data set for Fig. 1

Distance through P N D time or space

0 50 0 100 10 45 -10 90 20 40 -20 80 30 35 -30 70 40 30 -40 60 50 25 -50 50 60 20 -60 40 70 15 -70 30 80 10 -80 20 90 5 -90 10

100 0 -100 0

Data set for Fig. 3

Distance through time P N D

0 50 0 100 10 45 -10 90 20 30 -30 70 30 15 -70 30 40 5 -90 10 50 0 -100 0 60 5 -90 10 70 15 -70 30 80 30 -30 70 90 45 -10 90

100 50 0 100

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