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Disturbance-based restoration for recovery of pitch pine (Pinus rigida)
in the Thousand Islands Ecosystem: a comparison of prescribed fire and
mechanical disturbance on seedling regeneration.
By
Joshua Frans Van Wieren
A thesis submitted to
the Faculty of Graduate Studies and Research
in partial fulfillment of the requirements for the degree of
Master of Science
Department of Biology
Carleton University
Ottawa, Ontario
January 2014
© 2013, Joshua Frans Van Wieren
ii
Abstract Disturbance plays an important role in maintaining forests worldwide. Many natural
disturbance regimes, especially wildfire, have been disrupted or modified over time,
which can lead to the loss of disturbance adapted forest communities. Determining
historic disturbance patterns and mimicking them can be difficult, and can be further
complicated when disjunct or marginal populations exhibit different patterns than those
at the core. Pinus rigida (pitch pine) is strongly associated with wildfire in the core of its
range, however the association becomes less certain towards the species’ range
margins. I tested the efficiency of two disturbance restoration techniques on increasing
P. rigida seedlings using a Before-After Control-Impact (BACI) design. I compared
prescribed fire with a mechanical treatment and a control at two sites at the northeast
range margin of P. rigida in the Thousand Islands Ecosystem, Canada. I measured
canopy cover, understory cover and depth to mineral soil to control for their effects on
seedling regeneration. Fire had the greatest effect on regenerating P. rigida seedlings
and mechanical treatments were ineffective. My results suggest that the use of
prescribed fire is the best approach to increase P. rigida seedlings in the Thousand
Islands Ecosystem, possibly because these populations are exhibiting phenotypic
plasticity in traits that favour conditions created by fire. Restoration considerations are
discussed including the potential for modified mechanical disturbance treatments where
prescribed fires are not feasible.
iii
Acknowledgements Funding for this project was generously provided by the Parks Canada Agency. I would
like to thank my advisor Andrew Simons for his timely and positive feedback throughout
my thesis and for his patience with me working in spurts as I balanced my career with
my Masters. Thank you to my committee; Naomi Cappuccino and David Currie for their
feedback and positive approach to teaching. A big thank you to Sheldon Lambert, Jeff
Leggo and Harry Szeto at Thousand Islands National Park for providing me with the
opportunity to complete my Masters while continuing my role as a Park Ecologist.
Thank you to Mary Beth Lynch and Pauline Quesnelle, the two best botanists I know,
for their help in identifying the eruption of new species that emerged post treatments!
Thanks to my Thousand Islands National Park fire teammates and Parks Canada Fire
Program staff, especially Derek Bedford, Marie-eve Foisy, Victor Kafka and Raymond
Quenneville, that helped completed these complex fires in settled areas flawlessly.
Thanks to Doug Bickerton for his local expertise and passion for TIE pitch pine
populations. A big thank you to Paul Zorn for always having the time to brainstorm with
me and for his sage guidance throughout my thesis. Thank you to Kristen Zorn and
everybody else that provided assistance and enthusiasm in the field. A special thank
you to my Mother for (as always) expressing interest and her willingness to listen and
provide encouragement. Finally, I owe a big thank you to my wife Pauline for all her
help and encouragement and most of all for all the times we spent talking about
scientific theory, statistical principles and writing techniques, all while working on her
own PhD. Having one of the most well-rounded ecologists I know working back-to-back
with me each weekend was invaluable and enhanced my entire experience!
iv
Table of Contents Abstract ........................................................................................................................................................ ii
Acknowledgements ................................................................................................................................... iii
List of Tables ............................................................................................................................................... v
List of Figures ............................................................................................................................................ vi
1.0 Introduction ........................................................................................................................................... 1
1.1 Disturbance Ecology ............................................................................................................................ 1
1.2 Fire Influences on Forest ..................................................................................................................... 2
1.3 Pinus Fire Adaptations ........................................................................................................................ 2
1.4 Fire Suppression .................................................................................................................................. 4
1.5 Pinus rigida Miller ............................................................................................................................... 5
1.6 Thousand Islands Ecosystem Pitch Pine .............................................................................................. 8
1.7 Restoration Techniques .................................................................................................................... 10
2.0 Methods .............................................................................................................................................. 11
2.1 Study Area ......................................................................................................................................... 11
2.2 Study Design ...................................................................................................................................... 13
2.3 Treatment Types ............................................................................................................................... 14
2.4 Sampling Design ................................................................................................................................ 16
2.5 Variables Measured .......................................................................................................................... 17
2. 6 Statistical Methods .......................................................................................................................... 18
3.0 Results ................................................................................................................................................ 21
3.1 General Responses of Vegetation Community and Soil Depth to Treatments ................................. 21
3.2 Model Selection ................................................................................................................................ 23
4.0 Discussion........................................................................................................................................... 26
4.1 Treatment Effectiveness ................................................................................................................... 26
4.2 Treatment Effects on Competition and Access to Mineral Soil ........................................................ 27
4.3 Possible Explanations of the Positive Effects of fire on Seedling Recruitment ................................ 29
4.4 Possible Phenotypic Responses to Fire ............................................................................................. 30
4.5 Restoration Considerations and Further Studies .............................................................................. 32
5.0 Conclusions ........................................................................................................................................ 37
References ................................................................................................................................................ 39
Appendix .................................................................................................................................................... 46
v
List of Tables 1. Complete list of variables and their measurement units. 2. The model combinations selected against in an MMI framework, analyzed using
a two-factor poisson mixed model ANCOVA. 3. AIC model selection statistics of ANCOVA models. 4. Model-averaged estimates of the variable coefficients and standard error,
calculated using both top models. 5. values for each parameter in the original treatment + depth to mineral soil tests
and post hoc interaction tests, including r squared values for each model.
vi
List of Figures 1. North American distribution of Pinus rigida. 2. Study sites at Georgina Island and Mallorytown Landing. 3. Transect and quadrat placement. 4. Effect of treatments on canopy cover. 5. Effect of treatments on understory cover. 6. Effect of treatments on depth to mineral soil. 7. Change in relative importance of fire compared to depth to mineral soil (soil) for
an ANCOVA model that includes a treatment*soil interaction term versus a model that does not.
8. Pitch pine seedling numbers in 10x10m plots in the three years post treatment. A1. Before and after site photos of the Georgina Island fire. A2. Before and after site photos of the Mallorytown Landing fire.
1
1.0 Introduction
1.1 Disturbance Ecology
Ecological restoration is a key tool used to mitigate the effects of disturbances which
degrade ecosystems (Hobbs and Norton 1996). However, many forest ecosystems are
becoming increasingly imperilled because of a lack of disturbance (Van Sleeuwen
2006). Disturbance is known to influence the development, structure and function of
forests as well as the persistence of many forest-dependent species (Attiwill 1994).
Natural disturbances such as fire, wind, insect attacks, drought and ice storms are
driving forces in shaping many forest ecosystems (Bormann and Likens 1979; Attiwill
1994; Rogers 1996). Maintaining natural patterns and processes, such as disturbance
regimes, is a critical component to preserving the ecological integrity of an ecosystem
(Norton 1992; Grumbine 1994; PCA 2013). Concordantly, it is important to understand
disturbance processes and incorporate them into forest management (Whitmore 1982;
Rogers 1996). However, many disturbance regimes have been suppressed or altered
(Parsons and DeBenedetti 1979; Baker 1992) and in many cases it has become difficult
to determine which disturbance or which regime is required to maintain disturbance
dependent forests (Ne’eman et al. 2004). Hobbs and Norton (1996) suggest that
understanding the processes leading to degradation and decline as well as developing
methods to reverse or ameliorate them are two of the key processes in ecological
restoration. As such, it is imperative that conservation managers understand how to
implement disturbance restoration actions in forests where natural disturbances have
been altered.
2
1.2 Fire Influences on Forest
Many forest ecosystems are wholly or partially dependent on fires (Naveh 1975;
Abrams 1992; Wolf 2004). Wildfire is known to create a patchwork of different
ecological communities across a landscape (Davis et al. 2003). Different ecosystems
are influenced in a variety of ways depending on the local fire regime (Keeley et al.
2011); however, fire generally influences vegetation composition, structure and pattern
by decreasing competition, and preparing seedbeds and soil conditions suitable to
certain species (Van Sleeuwen 2006). Pinus (pine) communities are often more fire
prone than hardwood dominated ecosystems because of low moisture content in their
needles and the high content of flammable organic compounds (Whitney 1986). Fire is
often beneficial for tree regeneration because it provides access to the mineral soil by
removing the duff layer, reduces understory competition by controlling brush and
increases light penetration by killing canopy trees (Van Wagner 1970; Heinselman
1981; Wright and Bailey 1980; Bergeron and Brisson 1990). Pines benefit from these
conditions because many do not grow well in heavy shade and seedlings tend to
survive best on mineral soil and with little or no competition from shrubs and shade-
tolerant trees (Heinselman 1981).
1.3 Pinus Fire Adaptations
Pinus spp. found in fire-dependent ecosystems have developed a wide variety of fire
adaptations. Fire adaptation usually involves either individual resistance (survival of
adult trees) and/or stand resilience (seedling recruitment after the loss of a mature
stand; Keeley and Zedler 1998). Pinus that benefit from lower-severity ground fires
tend to grow taller and shed their lower dead branches thus discouraging ladder fuels
and dangerous crown fires (Keeley et al. 2011). Pinus in ecosystems that experience
3
more intense stand-replacing crown fires often do not shed their lower branches (Keeley
and Zedler 1998) and also retain empty open cones (Ne’eman et al. 2004), both of
which are highly flammable and increase the chances of a high intensity crown fire.
Some have adaptations that help them survive fires such as thick bark and deep rooting
(Heinselman 1981; McRae et al. 1994; Knight 1999). Others have adaptations that
enable adult trees to recover from fire damage, including epicormic sprouting from tree
trunks or branches in damaged areas (Keeley and Zedler 1998). These sprouts can
appear in large densities after intense fires and allow canopies to recover in a matter of
years (Climent et al. 2004). Some Pinus are able to resprout from their root collar as
seedlings (Klaus 1989; Keeley and Zedler 1998) and a few even as adults (Cain and
Shelton 2000; SCBD 2001).
Pinus spp. also exhibit a number of adaptations that improve their chances of
successful regeneration after fire. Cone serotiny is a well-known fire adaptation in
Pinus spp. (Cayford 1970; Vogl 1970; Benzie 1977), whereby cones only open when
they are heated enough to melt the resin on the cone scales allowing seeds to drop
when the conditions are more conducive to regeneration. Some species are known to
increase their reproductive output after fire (Peters and Sala 2008, Haymes and Fox
2012). Thomas and Wein (1985) suggest the delayed seed emergence from the soil
and partial seed retention in tree crowns of jack pine (Pinus banksiana Lamb.)
increases the chances of seedling regeneration if the conditions are poor immediately
after a fire. Larger seed sizes, which are more likely to survive heat shocks, are
exhibited in some Pinus species (Escudero et al. 2000). Furthermore, Escudero et al.
(2000) found that Canary Island pine (Pinus canariensis) seedlings were larger if their
4
cones were heated prior to germination, and Hille and den Ouden (2004) found that
Scots pine (Pinus sylvestris L.) seedlings were significantly taller in recently burnt areas.
Some Pinus seedlings can survive complete defoliation from heat if it occurs before
their terminal buds open (Methven 1971). Moreover, many Pinus species occur in
areas frequented by fires, exhibit fire adaptations and regenerate better after fire,
suggesting fire is a crucial element to their persistence.
1.4 Fire Suppression
Despite the importance of fire to many Pinus species, wildfires have been suppressed in
many forest ecosystems (Thompson, 2000). Human activities and active suppression in
the 19th and 20th centuries have significantly altered many fire regimes with the effects
largely still not understood (Thompson, 2000). Suppression has led to an increase of
shade tolerant species that change light, moisture and soil dynamics (Carleton 2000;
Scheller et al. 2005). Fire suppression also causes fire frequency to decrease until the
fuel loads are well above traditional levels leading to more severe fires than forests are
adapted to, which may cause significant mortality in mature trees (Swezy and Agee
1991; Knight 1999; Van Sleeuwen 2006).
In the continued absence of fire, many pines are negatively affected by increased
canopy and understory competition as well as reduced access to mineral soil.
Competition increases at the understory level as herbaceous and woody species begin
to proliferate and create light and moisture competition for shade-intolerant pines
(Feeney et al. 1998; Parker et al. 2009). Woody competitors such as shrub species or
tree seedlings can reduce light exposure (0’Brien et al. 2007). Canopy competition
creates negative impacts through mortality of shade-intolerant seed trees (Welch et al.
5
2000; Goubitz et al. 2003) and decreased regeneration (O’Brien et al. 2007). Without
fire, forest succession occurs and the litter and duff layers increase quickly (Debano
1991; Arno et al. 1993; Covington and Moore 1994). The tap roots of germinating
seedlings of some pine species are unable to access the mineral soil through thick
layers of litter and duff, which prevents establishment (Little and Moore 1949). As a
result, shallow litter and duff layers are key components to successful germination for
some pine species (Little and Garrett 1990; Waldrop and Brose 1999). Soils with no
leaf litter not only increase seedling establishment, but also provide a more suitable
medium for seedling growth (Hille and den Ouden 2004; Jonsson et al. 2006).
1.5 Pinus rigida Miller
Pinus rigida Miller (pitch pine) is a predominantly fire-adapted coniferous tree found
throughout the eastern United States from Maine to Georgia reaching its northern range
limit in southern Ontario and Quebec in Canada (Gucker 2007; Figure 1). P. rigida is
often a dominant species in pine barrens throughout much of its range, where it can
sometimes be a climax species (Abrams and Orwig 1995). However, it is most often an
early successional species replaced by hardwoods in the absence of fire (Westveld et
al. 1956; Little 1974).
Like many other pines, P. rigida is negatively affected by both canopy and understory
competition and increased depth to mineral soil. Canopy competition can cause
mortality in seed trees and reduce light availability for seedlings (Witzke 1982;
Copenheaver et al. 2000; Welch et al. 2000). Understory competition is also known to
affect P. rigida seedlings by increasing competition, especially light competition (SLINP
1993; Witzke 1996; Gucker 2007). Increased duff and litter layers decrease access to
6
mineral soil and chances for successful regeneration (Bramble and Goddard 1942;
Ledig and Little 1979; Little and Garrett 1990; Srutek et al. 2008). Based on these
preferences it is not surprising that P. rigida has traits characteristic of fire-adapted
species.
Figure 1: North American distribution of Pinus rigida (Little 1971), with northern range including the Thousand Islands Ecosystem inset.
7
P. rigida often occurs in ecosystems with frequent fire (Gucker 2007) and has long been
considered to have strong fire resistance (Starker 1932) and regeneration associated
with fire (Buell and Cantlon 1953; Buchholz and Good 1982). P. rigida develops thick
bark that protects mature trees from fire (Little 1953). Another adaptation is epicormic
sprouting from dormant buds along the main trunk (Ledig and Little 1979). All of the
foliage of a pitch pine may be killed by the heat of a fire and the crown will still produce
new needles (Ledig and Little 1979). Seedlings are also able to recover from fires
through basal buds insulated in or against mineral soil (Little and Somes 1956) or by
initiating a new lead from the bole (Little 1959). Perhaps the most striking fire
adaptation of P. rigida is the presence of serotinous cones throughout the core of the
species’ range (Ledig and Little 1979).
Despite evidence for strong fire dependence in certain parts of P. rigida’s range, in other
parts the species may be less dependent on fire. The serotinous habit in P. rigida is
concentrated towards the center of the species’ range in the New Jersey Pine Plains,
with frequency of serotiny generally decreasing from there in all directions (Ledig and
Fryer 1972). Populations away from the center, including marginal populations such as
those found in Ontario, Canada, have no cone serotiny (Vander Kloet 1981). Fire
appears to be the major selective force determining the patterns of serotiny in P. Rigida
(Frasco and Good 1976; Givnish 1981; but see Ledig and Fryer 1972). If local fire
frequencies drive the evolution of serotiny at a site, then sites with low fire frequencies
will have little to no serotiny.
8
1.6 Thousand Islands Ecosystem Pitch Pine
The Ontario population, found at the northeastern range margin of the species, occurs
within the Thousand Islands Ecosystem (TIE). Most populations found in the TIE occur
on the Frontenac Arch, a narrow portion of Precambrian shield that connects the
Adirondack mountain range in New York State with the Canadian Shield in Canada
(Lynch 2008). Pitch pine in the TIE is found predominantly on rock outcrops and
populations are currently described as over-mature with little to no recruitment
(Ellsworth et al. 2009)
The relationship between TIE pitch pine populations and fire is not currently understood.
Since fire is considered the major selective force on cone serotiny and there is no
serotiny in the TIE, it is possible that fire does not maintain pitch pine in the region.
Although lack of serotiny suggests fire may not strongly influence pitch pine in the TIE,
this is partially contradicted by the presence of other fire adaptations such as thick bark
and epicormic sprouting. These adaptations suggest that fire has played a role in at
least some of the pitch pine stands in the TIE, however it is unclear to what extent fire is
necessary or important to the population. Since it is unknown if TIE pitch pine
populations are the leading edge of expanding populations or relicts from a previous
range contraction (Guries and Ledig 1982), it is possible that phenotypes that respond
favourably to fire have been selected against or that trees will exhibit phenotypic
plasticity after an increase in fire events.
The degree to which fire is important for TIE populations is largely unknown. The strong
fire association with P. rigida in other parts of its range and the fire adaptations
exhibited in the TIE suggest that fire may be important for TIE populations. There is
9
evidence of at least one pitch pine stand in the TIE regenerating after a stand-replacing
fire (Rogeau 2007) and another site demonstrated successful regeneration after a fire
(Srutek et al. 2008). Furthermore, the population has been significantly decreasing
since at least the 1970’s (Lynch 2008), a period in which there was strong fire
suppression in the area (SLINP 1993; Ellsworth et al. 2009). However, while P. rigida
is known to regenerate primarily after fires, it can also be an early successional pioneer
that invades open disturbed sites (SLINP 1993; Jordan et al. 2003). The lack of
serotinous pitch pine in the TIE is a concern when considering the use of fire as a
management tool for pitch pine regeneration (Witzke 1996). Additionally, Vander Kloet
(1981) observed that a fire completely destroyed a pitch pine population in the TIE.
Other authors have found that fire does not appear to play a role in the development of
pitch pine or other plant communities in the TIE (Vander Kloet 1981; Warner and
Marsters1993).
Developing an understanding of which disturbance(s) pitch pine respond to in the TIE is
imperative for conservation managers aiming to maintain the population. Most pitch
pine populations in the TIE are being outcompeted by hardwood species in the canopy
and by shade tolerant seedlings and shrub species in the understory (SLINP 1993;
Donnelly 1996; Lynch 2008). Populations are declining and exhibiting little to no
recruitment (Vander Kloet 1973; Witzke 1982; SLINP 1993; Lynch 2007). These
deteriorating conditions, combined with the fact that most populations in the TIE are too
close to residential areas to allow wildfire to burn free, suggest active management is
required.
10
1.7 Restoration Techniques
Prescribed fire and mechanical restoration approaches, especially canopy thinning and
soil scarification, are widely implemented for pine species (Covington et al. 1997;
Feeney et al. 1998; Karlsson and Orlander 2000; Hille and den Ouden 2004; Béland et
al. 2010). Prescribed fire (Welch et al. 2000) and canopy thinning (Béland et al. 2010)
are tools used to decrease both canopy and understory competition. Prescribed fire
(Heinselman 1981) and soil scarification (Karlsson and Orlander 2000; Béland et al.
2010) are used to reduce or eliminate the litter and duff layers to improve access to
mineral soil. Prescribed fire has been applied extensively to various P. rigida
populations in the United States since the 1930’s (Little and Moore 1949; Little 1964;
Welch et al. 2000). Canopy thinning has also been used, although less frequently than
fire, to both restore P. rigida and reduce fuel loads (Clark and Patterson 2003; APBPC
2010). No mechanical treatments and only one experimental prescribed fire (Srutek et
al. 2008) have been implemented in the TIE. Pitch pine populations in the TIE lack
serotiny and occur in unique forest communities with unique fuel types and micro-
climates (Witzke 1996). Consequently, pitch pine populations in the TIE may respond
differently than core populations do to treatments and warrant regional specific
approaches.
Understanding the most effective restoration technique to promote pitch pine
regeneration is imperative to halt the decline of the species in the TIE. My objective
was to determine what restoration technique will have the greatest effect on increasing
pitch pine seedlings in the TIE; specifically, to test the expectation that prescribed fire
will cause the greatest increase in pitch pine seedlings relative to a mechanical
treatment or control. To this end, I assessed pitch pine seedling recruitment at a
11
prescribed fire plot, a mechanical treatment plot and a control plot at each of two sites in
the TIE, using a Before-After Control-Impact (BACI) design.
2.0 Methods
2.1 Study Area
In order to determine what restoration technique was the most effective at promoting
pitch pine seedling establishment, I compared the results of two different treatments and
a control at two locations (hereafter referred to as “sites”) in the TIE; Georgina Island
(Georgina) and Mallorytown Landing (Mallorytown; Figure 2). Both sites were in similar
ecosites (Lee et al. 1998) to ensure comparable species compositions, tree sizes and
soil conditions. They were characterized by dry rocky ridges interspersed with dips
containing deeper soils. Georgina pitch pine are found in “Dry-Fresh Mixed Woodland
ecosites” and Mallorytown pitch pine stands are found in “Dry-fresh pitch pine
coniferous woodland ecosites” (note: this community is derived from the “Dry-fresh
white pine coniferous woodland ecosite, which was the closest fit in the manual; Lee et
al. 1998). Both sites were conifer dominated, mixed with deciduous species; however,
Mallorytown had a stronger maple (Acer spp.) presence whereas Georgina had a
stronger oak (Quercus spp.) presence. Georgina treatment plot sizes were 80x50m,
50x40m and 60x50m in the fire, mechanical and control plots respectively and
Mallorytown plot sizes were 40x40m, 30x40m and 40x40m in fire, mechanical and
control plots respectively.
Georgina became part of Thousand Islands National Park (TINP) in 1904 and has
remained protected ever since. Pitch pine trees at this site varied in diameter but were
12
all found to be between 88 and 102 years old, which suggests that there was a
disturbance in the early 1900’s that led to the formation of the current pitch pine stand
(Rogeau 2007). Charcoal found on site was determined to have been generated by a
fire in the 1850’s and it is possible that the pitch pines may have originated from a
different fire in the early 1900’s (Rogeau 2007). Mallorytown was used as pasture in the
early 1900’s until as late as the 1940’s and became a part of TINP in 1959 (Leggo,
personal communication) Since then the area has remained undisturbed and
succeeded into a natural state. Although the diameters of the pitch pine at Mallorytown
are similar to those at Georgina, their age is unknown. Although farming was practiced
in the area, the ridge on which the pitch pine occur would have been unsuitable for
crops and used primarily for grazing. As a result, it is likely the pitch pine were present
on the ridge during or prior to farming and they may be as old as the trees on Georgina.
13
Figure 2: Study sites at Georgina Island and Mallorytown Landing, where a prescribed fire, mechanical treatment and control plot were included at both sites.
2.2 Study Design
A Before-After Control-Impact (BACI) design was utilized to test the effect of different
treatments on the number of pitch pine seedlings. BACI designs are used in a wide
variety of impact studies such as mining (Condrey and Gelpi 2010), oil spills (Murphy et
al. 1997), wind farms (Dahl et al. 2012) and urbanization (Price et al. 2012), as well as
in restoration studies (Maccherini and Santi 2012, Boys et al. 2012, Bayne and Nielsen
2011, Dickson et al. 2009). The before- after component of the design involves looking
at environmental data in an area before and after an impact or treatment occurs. These
designs are not controlled experiments and do not control for natural changes in the
environment. However, the inclusion of a non-impacted or untreated control site allows
a test of the impact (in the case of my study; two impacts) while controlling for any
14
natural change that may have occurred (Stewart-Oaten et al. 1986; Smith 2002) and
better control for both spatial and temporal variation (Parker and Wiens 2005). In my
study, one prescribed fire treatment, one mechanical treatment and one control plot
were included at each site. Data were collected in all plots within one year before the
treatment and one year following the treatment.
Many BACI studies only include one or two study sites because impacts are not
planned, or treatments can only be applied in a few locations (due to logistical or
resource constraints; Smith 2002). Similarly, my study only involved two sites because
prescribed fires are expensive and logistically difficult to implement and because P.
rigida is a very rare tree with few stands in Canada (Vander Kloet 1973; Lynch 2008).
The fact that the control plots are in the same ecological communities and located
spatially close to the treatments provides support to that assumption. Additionally, my
use of environmental measures as covariates also lessens the sensitivity to this
assumption (Parker and Wiens 2005).
2.3 Treatment Types
Prescribed fires were hand ignited using drip torches in an “S” pattern across the entire
burn plot. Fires were ignited using prescriptions outlined by a Parks Canada Fire
Behaviour Analyst in part using the Field Guide to the Canadian Forest Fire Behaviour
Prediction System (FBP; Taylor et al. 1997). The prescription for Mallorytown was
slightly more moderate as a precaution for the presence of residential housing within
300m of the prescribed fire. Some canopy thinning took place at Mallorytown to
increase the fuel load to a more comparable level to that found at Georgina. This was
determined using the fuel load classifications outlined in the FBP and by
15
recommendations from a Parks Canada Fire Behaviour Analyst to ensure complete
burn coverage of the treatment plot. Ignition involved lighting the entire treatment area
and allowing the fire to self-extinguish where safely possible. The Georgina fire was
ignited in August of 2009 and Mallorytown was ignited in August of 2011. Although the
treatment areas were quite small, it is likely that a wildfire in the TIE would rarely be
larger than the patch of homogeneous fuel type it is burning and would be limited by the
lack of continuous surface fuel. Thus, it is not unusual for fire to be in the range of only
30x30m to 70x70m in size in the TIE (Rogeau 2007).
Mechanical treatments involved removing 85% of all competing canopy trees including
all size ranges down to trees 1m in height, while leaving all pitch pines standing.
Eighty-five percent was an estimate of the amount of canopy cover that might be
removed in a fire situation and also based on Barden and Woods (1976) who found that
fires that removed 85% of the basal area led to an increase in pitch pine regeneration.
The majority of trees were removed using chainsaws, however some large white pines
(Pinus strobus) were girdled and left standing as snags to provide wildlife habitat.
Shrubs and small trees less than 1m in height were cut as close to the base of the trunk
as possible using a Stihl KM 90R motor with a Stihl FS-KM metal blade attachment. All
woody debris from tree and shrub reductions were removed from the sites or dragged
into large piles to minimise the impact on the study site. The soil was then exposed by
blowing most debris from the surface using a Stihl KW-KM power sweep tool. Finally,
the entire site was scarified using a Stihl BF-KM soil cultivator to increase access to
mineral soil and attempt to remove remaining competing herbaceous and woody
species.
16
2.4 Sampling Design
All variables were measured in 2x2m quadrats placed every 10m along two parallel
transects in both treatments and the control at both sites within one year before and
after the treatments (Figure 3). On Georgina there were 10 2x2m quadrats in each
treatment and the control (transect length of 40m); at Mallorytown there were 8, 8, and 4
2x2m quadrats (transect length 30m, 30m and 20m respectively) in the fire, control and
mechanical plots respectively. There were only eight quadrats in the fire and control
plots at Mallorytown compared to 10 at Georgina due to the slightly smaller size of
Mallorytown. I was only able to collect data at four mechanical quadrats in Mallorytown
because some of the original quadrats were compromised after the mechanical
treatments were completed. As a result, the total sample size was 18 for the fire and
control and 14 for the mechanical. It is important to note that my study design assumes
independence between each of these quadrats. Ideally all the quadrats along a
transect or both transects at a site would have been averaged and used as individual
sample units. However, that would have required having more pitch pine stands than
were available and implementing more fire and mechanical treatments than were
operationally feasible. Quadrats were located along transects rather than being
randomly placed because a) the sites were small enough that these transects traversed
the majority of the site and b) they increased repeatability and decreased error in
subsequent surveys.
17
Figure 3: Transect and quadrat placement, replicated in each plot on Georgina Island (Mallorytown plots were smaller and consequently had shorter transects and fewer quadrats).
2.5 Variables Measured
The response variable and three covariates were measured in each 2x2m quadrat.
The response variable was the number of pitch pine seedlings and the covariates were
canopy cover, understory cover and depth to mineral soil.
To determine understory cover, the percent area covered in the quadrat by all
herbaceous plants and any woody plant less than 4cm in diameter at breast height
(DBH) were included. All plants were identified to species save grasses and sedges,
which were grouped together. The percentage of each species was then combined to
determine an overall percent cover. Percent cover exceeded 100% if plant cover was
thick and layered. For example, a grass species may cover 80% of the quadrat and
then a fern species may cover 30% of the quadrat above the grass, leading to 110%
18
total cover. Quadrats were surveyed in mid-May for spring ephemeral species and from
July – August to capture everything else.
To determine percent canopy cover, I stood at the center of each 2x2m quadrat and
estimated what percentage of the canopy was closed. I considered “closed canopy” to
be any area where the sky was obstructed. A quadrat with 80% canopy cover would
have only 20% of the sky visible from its centroid.
To determine the depth to mineral soil, I measured the distance between the forest floor
and mineral soil. The start of mineral soil was defined as the top of the A horizon (Lee
et al. 1998). Since soil depths can vary even within a site due to rocky outcrops and
dips and rises in the terrain, depth to mineral soil was measured in each of the 2x2m
quadrats. This was done using a soil auger to extract a soil core that was used to
measure the distance between the forest floor and where the mineral soil begins. The
Ecological Land Classification for Southern Ontario field guide (Lee et al. 1998) was
followed to identify different soil horizons.
2. 6 Statistical Methods
To evaluate the relative importance of treatment (fire and mechanical) on pitch pine
seedling establishment, I included three covariates (canopy cover, understory cover and
depth to mineral soil; Table 1) and compared 15 models in a multi-model inference
framework (MMI; Table 2). I analyzed my data using a two-factor poisson mixed model
analysis of covariance (ANCOVA) using R version 3.0.2. An ANCOVA was appropriate
because my response variable was continuous and my explanatory variables were both
continuous and categorical (Crawley 2007). Since each covariate is known to influence
pitch pine regeneration, an ANCOVA was ideal because it allowed me to test the effect
19
of both treatments on the response variable, while controlling for the effect of the
covariates (Quinn and Keough 2002). To facilitate the BACI design, time (before and
after) was included in each model as a categorical factor variable. As a result, each
model assesses the differences among treatments in their effect on the change in the
response variable from the before to after values.
Table 1: Complete list of variables and their measurement units.
Variable Type of variable Measurement
Response Continuous Number of pitch pine seedlings
Fixed factor Categorical Time
Fixed factor Categorical Treatment type
Covariate Continuous % Canopy cover
Covariate Continuous % Understory cover
Covariate Continuous Cm to mineral soil
Random factor Categorical Site
I included site as a random effect in the ANCOVA to control for any differences between
the two sites that might confound my results. This enabled me to test the more general
hypothesis about pitch pine stands in the TIE rather than a hypothesis about the two
sites in my study (Zuur et al. 2009). This is especially important for my BACI design
since I had only two sites to work with. With only two sites in my study, the potential
impact of confounding effects due to unmeasured site differences increased. Including
site as a random variable is further supported because it was a) not something I was
explicitly testing for and b) it was something I expected to influence the variance of the
data not the mean (Quinn and Keough 2002).
I ranked models in the MMI framework based on their Akaike Information Criterion (AIC)
values (i.e. AIC <2.0) and calculated the associated model weights (wi; Burnham and
20
Anderson 2002). To determine which variable(s) were most strongly supported in
determining pitch pine seedling establishment, I calculated model-averaged estimates
of the coefficients for each of the variables in the top models. One of the advantages of
this approach is that it allowed me to measure and reflect model selection uncertainty.
That advantage was particularly important in my study, due to my study’s small sample
size. Using a global model with small sample size may lead to low statistical power
because the model may be too complex for the available degrees of freedom to support
and often results in problems with overinterpreting limited data. The use of AIC allows
assessment of model selection uncertainty and the objective determination of which
model, with which combination of variables, to base conclusions on. A limitation of the
design is that if more than one model is selected on the basis of strong AIC values,
effects exclusive to different models may in fact be driven by correlation with effects not
included in each model. Under these circumstances, an additional post-hoc ANOVA
can partition the competing effects and their interaction.
Table 2: The model combinations selected against in a MMI framework, analyzed using a two-factor poisson mixed model ANCOVA where T=treatment, C=canopy cover, U=understory cover and S=depth to mineral soil.
T+C+U+S T+C+U T+C+S T+U+S T+C T+U T+S C+U+S C+U C+S U+S T C U S
21
3.0 Results
3.1 General Responses of Vegetation Community and Soil Depth to Treatments
There was a variable response by the covariates known to influence P. rigida
regeneration one year after the treatments. Percent canopy cover significantly
decreased following both the fire (df=95, p=<0.0001) and mechanical treatments (df=95,
p=<0.0001; Figure 4). Percent understory cover was not significantly affected by either
the fire (df=95, p=0.362) or mechanical (df=95, p=0.093) treatments (Figure 5). Finally,
depth to mineral soil was significantly decreased in the fire treatment (df=95, p=0.013)
but not the mechanical treatment (df=95, p=0.149; Figure 6).
Figure 4: Canopy cover in A (control), B (fire treatment) and C (mechanical treatment) before and after treatments. ***=p<0.001 using ANCOVA.
22
Figure 5: Understory cover in A (control), B (fire treatment) and C (mechanical treatment) before and after treatments.
Figure 6: Depth to mineral soil in A (control), B (fire treatment) and C (mechanical treatment) before and after treatments. *=p<0.05 using ANCOVA.
23
3.2 Model Selection
The treatment (fire and mechanical) and depth to mineral soil models had the greatest
support in determining an increase in pitch pine regeneration in the initial ANCOVA
analysis (Table 3). Treatment had an Akaike weight (wi) of 0.509 and depth to mineral
soil was 0.331, combined accounting for 84% of the total wi. All other models, including
any with canopy and understory cover included were >4AIC from the top model. The
model-averaged partial regression coefficients were 0.202, 0.065 and -0.012 for the fire
treatment, mechanical treatment and depth to mineral soil respectively (where both
treatments and a decrease in the depth to mineral soil had a positive effect on pitch pine
seedling numbers; Table 4). Fire and depth to mineral soil were the only two variables
whose standard error did not overlap with 0.
Table 3: AIC model selection statistics of ANCOVA models where: T=treatment, S=depth to mineral soil, C=canopy cover and U=understory cover. Response variable is number of pitch pine seedlings.
Model AIC i wi
T 166.769 0.000 0.509
S 167.631 0.861 0.331
C 170.772 4.003 0.069
TS 171.525 4.756 0.047
CS 172.192 5.423 0.034
TC 175.365 8.596 0.007
U 178.768 11.998 0.001
TU 179.178 12.409 0.001
TCS 179.588 12.818 0.001
US 180.315 13.546 0.001
CU 183.569 16.800 0.000
TUS 183.872 17.103 0.000
CUS 184.556 17.787 0.000
TCU 187.329 20.560 0.000
TCUS 191.501 24.731 0.000
24
Table 4: Model-averaged estimates of the variable coefficients and standard error, calculated using both top models.
Parameter SE df p-value
Fire 0.202 0.072 95 0.006
Mechanical 0.065 0.077 95 0.401
Depth to Mineral Soil -0.012 0.004 96 0.006
Since both the treatment and depth to mineral soil models demonstrated good
predictive ability in determining pitch pine seedling regeneration in the initial analysis, a
post-hoc test was completed to test if there was an interaction effect between the two
models. In the post-hoc interaction test I found there was an interaction effect between
treatment and depth to mineral soil. The model containing treatment and depth to
mineral soil as well as the interaction between the two had the highest r2 value (Table
5). Only the fire treatment has a regression coefficient that does not overlap with zero
in this model. The interaction effect between fire and soil seems to potentially confound
the relative importance of both parameters in determining pitch pine seedling
regeneration. When the interaction is not controlled for in the model, the regression
coefficients are fairly close (see hash line in Figure 7). However, when the interaction is
included in the model, the regression coefficients for both fire and soil deviate from each
other and increase from their original values (see solid line in Figure 7).
25
Table 5: values for each parameter in the original treatment + depth to mineral soil tests and post hoc interaction tests, where F=fire treatment, M=mechanical treatment, T= treatment, S = depth to mineral soil and “:” represents an interaction test. r squared values are provided as indicators of the amount of variation explained by each model.
Model Parameter r2 SE df p-value
S+T F 0.269 0.191 0.12 94 0.028
M 0.143 0.126 94 0.262
S -0.024 0.011 94 0.033
S+T+S:T F 1.16 0.318 0.322 92 0.001
M 0.171 0.305 92 0.576
S -0.001 0.026 92 0.98
S:F -0.125 0.037 92 0.001
S:M -0.006 0.03 92 0.848
S:T S:F -0.038 0.174 0.019 94 0.049
S:M -0.026 0.011 94 0.015
Figure 7: Change in relative importance of fire compared to depth to mineral soil (soil) for an ANCOVA model that includes a treatment*soil interaction term versus a model that does not. refers to the partial regression parameter for each ANCOVA model.
26
4.0 Discussion
4.1 Treatment Effectiveness
The results of my study support my prediction that prescribed fire would cause the
greatest increase in pitch pine seedlings compared to the mechanical treatment or
control. In the initial model selection process the treatment model had the greatest
predictive ability on increasing pitch pine seedlings. Within the treatment model, the fire
treatment regression coefficient was three times that of the mechanical treatment.
Since both regression coefficients are measured on the same scale, I can infer that the
fire treatment is expected to produce three times more pitch pine seedlings than the
mechanical treatment. It was further demonstrated that the fire treatment was more
effective than the mechanical treatment, when the interaction between depth to mineral
soil and treatment was assessed in the post-hoc test. In addition to the fire treatment
having the greatest support in the model selection process, it is also important to note
the consistency with which fire had a positive effect on pitch pine regeneration.
Regardless of which variables were included, fire was consistently positively associated
with pitch pine regeneration. Although the efficacy of fire to increase pitch pine
regeneration is well supported in parts of its range (Little and Moore 1949; Buchholz
and Good 1982; Groeschl et al. 1993; Welch et al. 2000), this study represents only the
second and third prescribed fires for P. rigida in Canada and is the first study to
determine that fire is more effective than a mechanical disturbance technique.
Moreover, my results suggest that fire may be more effective than mechanical
disturbance at increasing P. rigida regeneration in ways other than altering habitat
conditions such as canopy / understory cover and depth to mineral soil.
27
The mechanical treatment was ineffective at promoting pitch pine regeneration. There
are few published studies that compare pitch pine regeneration after prescribed fire with
a canopy thinning approach. Furthermore, no mechanical treatments of any kind have
been attempted to increase pitch pine regeneration in the TIE. Thinning approaches
are frequently used to reduce fuel loads in P. rigida stands elsewhere in the species’
range (Clark and Patterson 2003). Additionally, thinning in parts of P. rigida’s range has
led to large, sometimes over-abundant, increases in regeneration (Patterson, personal
communication). However, these mechanical treatments occurred in different
communities than pitch pine in the TIE and the canopy thinning involved removing pitch
pine canopy, as opposed to removing competing canopy trees such as in this study.
Whereas thinning has been effective in increasing P. rigida regeneration in other parts
of the species range, I found it to be ineffective in the TIE.
4.2 Treatment Effects on Competition and Access to Mineral Soil
The fire and mechanical treatments had a similar effect on canopy and understory
cover. As expected, both the mechanical and fire treatment significantly decreased
canopy cover (see fire treatment photos in Figure A1 and A2). Thus there was an
increase in light penetration from the canopy cover reaching the understory. This is
consistent with other studies that found both fire and mechanical thinning decreased
canopy cover (Fulé et al. 2012). What was somewhat unexpected was the lack of effect
both treatments had on decreasing the percent of understory cover. Although non-
significant, the results suggested even a slight increase in understory cover in the fire
treatment (Figure A1 and A2). There was a window after the treatments were
implemented where understory cover was significantly reduced, which could provide an
opportunity for pitch pine seedlings to become established (see fire treatment photos in
28
Figure A1 and A2). However, within one year both herbaceous and shrub species
emerged from existing seedbanks or rhizomes and also likely arrived via seed dispersal
to replace the percentage of understory cover removed by the treatments. Understory
species richness increased remarkably from 28 to 73, 25 to 55 and 35 to 37 species
after the fire treatment, mechanical treatment and control respectively. Moreover, while
the percent understory cover remained relatively constant in both treatments, the
community composition was considerably different with 49 and 35 new species found
after the fire and mechanical treatments that were not present before.
In contrast to the similar effect both treatments had on canopy and understory cover,
depth to mineral soil was effectively decreased by the fire treatment but not the
mechanical treatment. In many locations fire smouldered and burnt through the duff
and litter layers exposing bare mineral soil, ideal for P. rigida seedling germination and
growth (Little and Moore 1952). The mechanical treatment scarified the soil and in
places decreased the depth to mineral soil, but overall was ineffective at increasing
access to mineral soil for pitch pine seedlings. This is possibly because the treatment
did not remove the litter or duff layers, rather mixed them in with some mineral soil tilled
up from underneath. This was the only variable that fire significantly improved that the
mechanical treatment did not. It is possible that this variable may have been
responsible for the fire treatment effectively promoting pitch pine regeneration better
than the mechanical treatment. Considering the test that included the interaction
between treatment and depth to mineral soil had the highest r2 value, fire and depth to
mineral soil may be an important combination to increase pitch pine regeneration.
However, considering the standard error is very large for the depth to mineral soil
29
regression coefficient in this model it is uncertain to what degree this variable is
influencing pitch pine regeneration. As a result, it is also possible that fire could be
modifying the importance of depth to mineral soil to pitch pine regeneration and that
something else about fire is driving improved pitch pine regeneration in the fire
treatments.
4.3 Possible Explanations of the Positive Effects of fire on Seedling Recruitment
The post fire treatment soil chemistry may have improved conditions for pitch pine
generation more effectively than did the mechanical treatment. Fires have been
documented to change a variety of soil properties including physical, physio-chemical,
mineralogical, chemical and biological (Certini 2005). There are also examples of
thinning treatments influencing soil properties in P. rigida stands (Hwang and Son 2006;
Geng et al. 2012). However, there is evidence that fire treatments create favourable
soil conditions for increasing P. rigida recruitment. Groeschl et al. (1993) found that fire
led to significant reductions in nutrient content and an increase in P. rigida recruitment.
They hypothesized that fire degrades site quality and sets back site succession, which
favours P. rigida. Other studies have found that P. rigida seedlings grew significantly
better in the absence of leaf litter (Jonsson et al. 2006) or that abundant leaf litter
reduced seedling growth (Garnett et al. 2004). This may have led to increased seedling
growth in the fire treatments, since fire burns off leaf litter whereas the mechanical
treatments simply tilled existing leaf litter into the soil. Moreover, fire may have created
conditions more conducive to pitch pine seedling establishment and growth and
unfavourable to competing species, than the mechanical treatment.
30
Another possibility is that fire actually promoted a response from mature pitch pine trees
that increased reproductive output and / or efficiency. Some studies have found that
other Pinus species increase cone output after fire (Haymes and Fox 2012), thinning
(González-Ochoa et al. 2004) and after combined fire / thinning treatments (De Las
Heras et al. 2007; Peters and Sala 2008). In the present study on P. rigida, the
maximum number of cones would have been determined prior to the treatments in the
form of fully developed cones (already developed before the treatment) or fertilized
female strobili (which develop into cones the year following the treatment). However,
Peters and Sala (2008) found that there were a higher number of filled seeds per cone
in ponderosa pine after fire compared with after thinning treatments. Other studies have
found that Pinus seedlings had higher initial growth rates after cones were heated prior
to germination (Escudero et al. 2000), or in plots that were burned compared to either a
control site or sites that only had soil scarification (Hille and den Ouden 2004).
Considering understory competition returned to similar pre-treatment levels, it is
possible that smaller seedlings may have been outcompeted and experienced higher
mortality in the mechanical plots. If, in the present study, seed trees in the fire
treatment released a greater number of seeds and / or had seedlings that grew larger,
this could at least partially explain the difference in recruitment between treatments.
4.4 Possible Phenotypic Responses to Fire
My results provide an example of the importance of fire in a population at its range
margin that has experienced lower recent fire frequency and that exhibits fewer fire-
adapted traits than populations in the core. This suggests that it is possible that
populations occurring in areas of lower fire frequency, which originated in areas of high
fire frequency, may respond favourably or even exhibit phenotypic plasticity that
31
provides them with an advantage when a fire does occur. If increased regeneration in
the fire treatment was due to improved reproductive response by pitch pine (increased
filled seeds per cone, increased germination rates, increased seedling growth), TIE
populations may be exhibiting some degree of adaptive phenotypic plasticity.
Cone serotiny provides an opportunity to investigate this possibility. Since fire is
believed to be the major selective force determining the gradient of cone serotiny in P.
rigida and recent fire appears to be less frequent in populations at the range margin, it is
not surprising that populations such as those found in the TIE are not serotinous. It is
not known if the absence of strict serotiny in pitch pine in the TIE is due to selection
against serotiny, or whether this trait persists in the population but the trait is not
expressed in the absence of frequent fire. In fact, even within the high fire frequency
core of the species, there are populations that include many individuals without
serotinous cones. It has been observed that fewer trees exhibit serotiny in non-burnt
clearings, compared to undisturbed adjacent plains which experience fire (Givnish 1981;
Jordan et al. 2003). Indeed, in the absence of frequent fire, many populations in the TIE
may have been colonized by seeds from non-serotinous cones moving into recently
disturbed land. However, it is unknown if trees with non-serotinous cones produce
some serotinous offspring and there is still little known about the genetics of these traits
(Givnish 1981; Jordan et al. 2003). This is not to say that pitch pine in the fire
treatments will now exhibit serotinous cones. Rather I am suggesting that it is possible
that they may have exhibited other fire adapted traits beneficial to establishing seedlings
that were triggered by the fire. If so, it is possible that disjunct populations removed
from regular fire events may retain a level of plasticity that enables them to take
32
advantage of the conditions created when fire returns. These explanations are of
course speculative, and would be worthwhile subjects of future study.
4.5 Restoration Considerations and Further Studies
To further investigate the explanations for the greater effectiveness of fire at increasing
regeneration than mechanical treatments, additional studies are recommended. Soil
chemistry before and after fire and mechanical treatments should be tested to
determine if it is influencing regeneration. If soil chemistry is a key element contributing
to increased regeneration, it would limit the ability of mechanical restoration to increase
natural recruitment.
The possibility that TIE populations of pitch pine increase their reproductive effort and
success after fire but not following mechanical treatments warrants further study. If
confirmed, it would provide a useful insight for conservation managers in the TIE to
improve local pitch pine restoration efforts. It would also be important information for
use in the management of other P. rigida populations outside the high fire frequency
core and for other species found in similar situations worldwide. Studies should focus
on adaptations that promote reproductive effort and success exhibited in other Pinus
species, as discussed (increased serotiny, cone production, seeds per cone,
germination success and seedling growth).
It is important to recognise that my study only included treatment years, and
observations taken during the first year immediately following each treatment. As a
result, the focus is on which treatment created conditions suitable for initial seed
germination and early seedling survival. Although successful regeneration in the first
year after the treatment is likely a good indication that the conditions created are
33
suitable to regenerating the stand, additional years of data collection would be
beneficial. At the Georgina site, seedling numbers have been recorded for an additional
two years beyond the initial year after the treatments in three 10x10m plots per
treatment. Although this represents a small sample size, pitch pine seedlings increased
each year after the fire treatment while not increasing in the mechanical or control
(Figure 8). This implies that, additional years would further support the results of this
study since conditions in the fire treatments clearly created suitable conditions for
recruitment and produced significant regeneration, while mechanical treatments
demonstrated very low recruitment.
Figure 8: Pitch pine seedling numbers in 10x10m plots in the three years post treatment.
Perhaps the strongest indication that fire treatments will continue to be more effective at
regenerating pitch pine compared to the mechanical treatment is that competition may
remain in-check for longer in the fire treatment. Although competing hardwood species
did sprout from root masses of trees in both treatment types, it was considerably more
34
noticeable in the mechanical treatments. I observed limited sprouting in the fire
treatments, where it appears the only hardwoods that were able to sprout were in small
pockets that did not burn very intensely. Overall the majority of hardwoods such as
Quercus rubra, Acer saccharum, Ostrya virginiana, Carya ovata and shrubs such as
Amelanchier arborea and especially Vaccinium spp., exhibited little resprouting in fire
treatments. In contrast, the same species were observed sprouting prolifically the year
after in the mechanical treatments. Rigorous sprouting from hardwoods will increase
understory cover that is significant competition for young shade intolerant seedlings
(Gucker 2007) and eventually, canopy competition for those seedlings that do persist
into trees (Copenheaver et al. 2000). Concordantly, it is likely that the mechanical
treatments will facilitate more hostile conditions for young pitch pines in years following
the treatment than prescribed fires.
Even though mechanical treatments were not effective in promoting pitch pine
regeneration and may facilitate greater competition for young seedlings, it is important
to consider if mechanical treatments could be improved, given that fire treatments are
not always possible. Where the application of prescribed fire is not practical,
mechanical treatments are needed to replicate wild or prescribed fire (Jordan et al.
2003). There are numerous cases where prescribed fire may not be possible, including
proximity to residential areas, private ownership, lack of financial resources or lack of
local fire expertise. In these cases, mechanical approaches may be the only option to
restore pitch pine stands if there is continuing adult pitch pine mortality with no
recruitment. Although mechanical restoration plots were not effective in promoting
regeneration, some seedlings were observed. Considering virtually no regeneration is
35
observed naturally in the TIE, this suggests that mechanical treatments may have some
potential as a restoration approach.
To improve the likelihood of mechanical treatment success, a few options should be
considered. One option that may make mechanical treatments effective is post
treatment seedling plantings. Canopy and understory cover were similarly affected in
both treatments (Figures 4 and 5), yet seedlings germinated and survived in the fire
treatment. It is possible then, that mechanical treatments are unable to provide
conditions suitable to seed germination, young seedling survival or lack seed input.
Consequently, planted seedlings could by-pass any seed germination difficulties or
seed input deficiencies and grow in similar competition conditions to natural recruitment
in the prescribed fire sites. Roughly 100 seedlings planted in two mechanical
treatments in the TIE have demonstrated a high survivorship over a two year post-
treatment period (Van Wieren unpublished). Because thinned hardwoods will likely
necessary. This approach may only work if the limiting factors in the mechanical plot
can be explained by lack seed input, germination or reduced early (<1 year) seedling
growth and not by other factors limiting seedling survival. However, the fact that P.
rigida can be an early pioneer species and have successfully established in non-fire
sites (Jordan et al. 2003), suggests that an investigation of the success of planting pitch
pine seedlings in mechanical restoration plots would be worthwhile. If natural
recruitment is a goal in mechanical restoration sites, experimenting with additional soil
scarification techniques may be beneficial. The approach used to increase access to
mineral soil in this study proved largely ineffective. Mechanical treatments that include
removing the duff layer may improve natural generation in some cases. As discussed in
36
the planting option, continued mechanical thinning would likely be necessary to avoid
seedlings getting outcompeted in subsequent years.
Although determining the fire regime in TIE and other marginal populations of P. rigida
may be difficult (Rogeau 2007), understanding the historical disturbance regime is
important to help guide land management (Cissel et al. 1999). Disturbed ecosystems
are known to have thresholds, which once crossed result in a substantial increase in the
amount of restoration required (Hobbs and Norton 1996; Hobbs and Harris 2001). In
this case it is possible that the natural disturbance cycle was disrupted for so long that it
passed a threshold and fires may be more severe than the forest has historically
experienced. When fire cycles are disrupted through fire suppression, duff layers and
fuel loads increase and fires tend to be more severe and can destroy many adult trees
(Van Sleeuwen 2006). This can be significant for P. rigida, since more intense fires
may cause extreme smoldering which can disrupt basal sprouting (Windisch 1999).
Moreover, since P. rigida is known to lose some of its fire adaptations as it ages
(Windisch 1999), increased periods between fires may reduce the ability of P. rigida
stands to respond favourably to fire. In three 10x10m plots at the Georgina site, 80%
(n=29) of the adult trees (DBH > 4cm) were killed within one year of the fire and 93%
had died two years after the fire. Even though remaining seed trees generated
successful recruitment, it is possible that with lower adult tree mortality rates,
regeneration may have been even better. However, Srutek et al. (2008) found that a
less intense spring fire in the TIE was ineffective at opening up understory and canopy
conditions. Thus, there appears to be a trade-off between treating sites with prescribed
fires severe enough to destroy shade tolerant hardwoods and the root systems of
37
competing shrubs, while retaining some pitch pine seed trees. Conservation managers
should strive to determine the ideal fire frequency to achieve optimum seedling
recruitment.
5.0 Conclusions I found that prescribed fire was more effective than mechanical disturbance at
increasing P. rigida seedling regeneration at the species’ extreme northeast range
margin. I also found that both fire and mechanical disturbance similarly affected canopy
cover and understory cover, and that while only fire decreased depth to mineral soil,
that fire modified the importance of depth to mineral soil on pitch pine regeneration. My
results imply that fire has a significant effect on pitch pine seedling regeneration beyond
a reduction in canopy cover and possibly beyond or in conjunction with depth to mineral
soil. P. rigida at the core of its range exhibits strong fire adaptations that increase
seedling regeneration after fires, whereas TIE populations exhibit fewer adaptations.
Consequently, the effectiveness of fire to increase seedling regeneration compared to
mechanical disturbance demonstrated in my study suggests it is possible that pitch pine
in the TIE have retained fire adapted traits beneficial to establishing seedlings that are
triggered by fire events. This further underscores the importance of researching and
understanding disturbance regimes before conducting wide-scale restoration of a
species or population. My results suggest that prescribed fire should be the primary
conservation management tool to restore declining pitch pine populations in TIE (and
potentially at other locations at the edge of its range distribution). Where prescribed fire
is not feasible, I recommend that additional research to determine why mechanical
38
treatments are failing should be considered and mechanical treatments should be
modified based on the results.
39
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Appendix
Figure A1: From top to bottom, Georgina Island prescribed fire treatment one year before the fire, one day after the fire and one year after the fire.
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Figure A2: From top to bottom, Mallorytown Landing prescribed fire treatment one year before the fire, two and half months after the fire and one year after the fire.