Hansen et al.
Edge effects across ecosystem types
Ecosystem Biomass as a Framework for Predicting Habitat Edge Effects
Running Head: Edge effects across ecosystem types
Key Words: biomass, conservation principles, edge effects, forest interior species, habitat
fragmentation, microclimate
Word Count: 7150
Andrew James Hansen, Ecology Department, Montana State University, Bozeman, MT 597173460
Lisa Baril, Ecology Department, Montana State University, Bozeman, MT 59717-3460
Jennifer Watts, Land Resources and Environmental Sciences Department, Montana State
University, Bozeman, MT 59717-3460
Fletcher Kasmer, Montana State University, Bozeman, MT 59717-3460
Toni Ipolyi, Montana State University, Bozeman, MT 59717-3460
Ross Winton, Entomology Department, Montana State University, Bozeman, MT 59717-3460
Corresponding Author: Andrew Hansen, Ecology Department, 310 Lewis Hall, Montana State
University, Bozeman, MT 59717-3460. hansen@montana.edu
25 February 2008
1
Hansen et al.
Edge effects across ecosystem types
Abstract: Past studies of the consequences of human-induced edge effects on native
biodiversity have had mixed results leading to confusion on if and how to manage to avoid
negative edge effects in different forested ecosystem types. The purpose of this paper is to
evaluate if forest ecosystems differ predictably in response to edge effects based on forest
structure and density. The Biomass Accumulation Hypothesis (Hansen & Rotella 2000) asserts
that edge effects have the highest magnitude of influence in ecosystems that accumulate high
levels of standing aboveground vegetation biomass. We test two predictions of this hypothesis:
1) The dense vegetation in mid to late seral habitats within high-biomass ecosystems buffers
microclimate, resulting in large differences in average microclimate between disturbance patch
edges and forest interiors; 2) In high biomass ecosystems the sharp gradient in vegetation and
microclimate results in finer habitat partitioning by organisms and more forest interior specialists
than is the case in lower biomass ecosystems. These predictions were tested by statistical
analysis of the results of published studies in several of the major forest biomes. We found that
magnitude of edge influence of microclimate was significantly related to forest biomass for light
intensity and relative humidity. Trends for air temperature, soil temperature, vapor pressure
deficit, and soil moisture were as predicted, but not statistically significant. A model including
all microclimate samples and controlling for microclimate variable type was significant. The
percent of species that specialized on forest interiors was significantly related to biomass for
mammals and birds, and nearly significant for beetles. The results suggest that forest
fragmentation is most likely to negatively influence forest species in high biomass ecosystems
such as tropical and temperate rainforests, but may have little influence on forest species in lowbiomass ecosystems such as boreal or subalpine forests. These finding provide a basis for
2
Hansen et al.
Edge effects across ecosystem types
prioritizing the management of habitat fragmentation appropriately across the world’s forest
ecosystems.
3
Hansen et al.
Edge effects across ecosystem types
Introduction
Human expansion has led to fragmentation of many natural ecosystems (Saunders et al.
1991). Habitat fragmentation results in both a reduction in total area of habitat and change in
spatial configuration of remaining habitat patches (Wilcove et al. 1986). As fragmentation
proceeds, changes in habitat patch size and number can lead to increases in abrupt edges between
remaining habitat patches and the expanding matrix. While some native species thrive at habitat
edges, others are adapted to habitat patch interiors and may become extinct in landscapes where
habitat is dominated by edge effects (Noss et al. 2006a).
The vast body of research on the consequences of human-induced habitat edge effects on
native biodiversity, however, has shown conflicting results, (Paton 1994; Murcia 1995; Harper et
al. 2005) leading to confusion concerning management. A major review by Matlack & Litvaitis
(1999) concluded, “The negative repercussions of edge habitats have prompted changes in
forestry practices …. Yet there is considerable variability in edge response among forest sites
and species, which makes it difficult to formulate a consistent edge management policy.” (pg.
222). More recently, Fahrig (2003) concluded that change in spatial configuration of habitat
(including edges), independent of habitat loss, “… has rather weak effects on biodiversity, which
are as likely to be positive as negative.” (pg. 508). She states regarding management, “…
conservation actions that attempt to minimize fragmentation (for a given habitat amount) may
often be ineffectual.” (pg., 508). A caution is offered, however, that that negative edge effects
may be much stronger in tropical than in temperate systems, but, “This prediction remains to be
tested.” (pg 508). Thus, substantial uncertainty remains on which ecosystem types are sensitive
to edge effects and which management strategies are most effective for maintaining native
biodiversity in a given ecosystem.
4
Hansen et al.
Edge effects across ecosystem types
Efforts to explain the variable findings of these edge studies have focused primarily on
local-scale factors; the characteristics of the edges and of the surrounding landscape. These
factors include the age of habitat edges, edge aspect, the combined effects of multiple nearby
edges, fragment size, the structure of the adjoining matrix vegetation, influxes of animals or
plant propagules from the matrix, extreme weather or disturbance events, and land use in the
surrounding landscape (Murcia 1995; Harrison & Bruna 1999; Noss et al. 2006a; Laurance et al.
2007). Such local scale factors can produce striking variability in edge effects within the same
region (Laurance et al. 2007). These local factors may cause difficulty in predicting the nature
and magnitude of edge effects and may also explain some of the conflicting results in the
literature (Harper et al. 2005).
While local variation in edge effects is increasingly well understood, the extent of
variation in edge effects among major ecosystems or biomes is not adequately studied (Murcia
1995). Harper et al. (2005) reviewed studies of vegetative and microclimate patterns across
edges. They suggested that edge effects should be more pronounced in regions with high patch
contrast, infrequent natural disturbance and low natural vegetation heterogeneity, high solar
radiation and low cloudiness, and relatively few pioneer species. None of these hypotheses have
been tested at continental or global scales.
The goal of this paper is to examine one of these hypotheses, that involving patch
contrast as elaborated by the Biomass Accumulation Hypothesis. This hypothesis (Hansen &
Rotella 2000) asserts that edge effects have the highest magnitude of influence in ecosystems
that accumulate high levels of standing aboveground vegetation biomass. We examine how well
the predictions of this hypothesis are supported by published studies from forest ecosystem types
spanning the gradient in global forest biomass accumulation. Our hope is that this paper will
5
Hansen et al.
Edge effects across ecosystem types
prompt additional tests of this and other hypotheses and lead to an improved understanding of
variation globally in the effects of habitat fragmentation. Such knowledge would better allow
land managers to identify and employee the conservation strategies that are likely to be most
effective in their particular ecosystems.
The Biomass Accumulation Hypothesis
The Biomass Accumulation Hypothesis is a logical extension of the considerable body of
work on the role of vegetation structure in edge effects (reviewed by Harper et al. 2005). The
abrupt edge transition comprising human-induced edges in forest systems is typically in
vegetation structure, from patches with lower vegetation height and/or density to forest stands
with higher vegetation height and/or density. Because dense vegetation buffers microclimate
and disturbances, forest patch interiors often have less extreme microclimates and disturbance
regimes than forest edges (e.g., Chen et al.1999). These more moderate interior forest conditions
often support plant and animal species that are uniquely adapted to such conditions (Matlack &
Litvaitis 1999). Creating edges within or near forest interior habitat can reduce this vegetation
buffer allowing more extreme conditions that may be intolerable for forest interior species.
Ecosystem energy is increasingly understood to be a major factor organizing community
diversity, species abundances, and ecosystem processes. Globally, radient energy and primary
productivity are the primary correlates with species richness (Waide et al. 1999, Mittelbach et al.
2001, Gaston 2000, Hawkins et al. 2003). Richness increases with diversity in low energy
systems, possibly because higher energy favors larger population sizes (Wright 1983, Srivastava
and Lawton 1998, Evans et al. 2007)). Richness sometimes decreases with energy in high
energy systems, possibly because it favors competitive dominance by a few species and because
variation in energy and thus species niches are reduced in high energy ecosystems (Rosenzweig
6
Hansen et al.
Edge effects across ecosystem types
and Abramsky 1993, Huston 1994). Ecosystem energy also influences vegetation structure and
disturbance frequency, both of which may bear on edge effects.
The major forest ecosystems of the world differ predictably in vegetation height and
density as determined by forest productivity and disturbance (Perry 1994). High levels of
vegetation structure result from high net primary productivity and/or infrequent loss of
vegetation to disturbance. Net primary productivity is favored by warm temperatures, high solar
radiation, high moisture, and fertile soils (Running et al. 2004). Stand replacing disturbances are
often less frequent in highly productive forests (White & Jentsch 2001). This is because fires are
inhibited by high precipitation and humidity within the forest, deep fertile soils inhibit
windthrow, and healthy, productive trees are generally less susceptible to catastrophic insect and
disease outbreaks. Across the forests of the earth, vegetation structure, expressed as
aboveground biomass of mid to late seral stages, is highest in wet tropical and temperate forests,
intermediate in moist temperate forests, and lowest in dry or cold forests (Perry 1994).
Merging concepts on drivers of edge effects and knowledge of global patterns of forest
productivity and structure, the Biomass Accumulation Hypothesis asserts that edge effects have
the highest magnitude of influence in ecosystems that accumulate high levels of standing
aboveground vegetation biomass (AGB). AGB accumulation refers to the total dry weight of
vegetation present within a forest in mid to late successional stages, typically quantified as tons
per hectare. High AGB forests are often characterized by high canopies, multiple canopy layers,
and high foliage height diversity.
The hypothesis predicts that forest ecosystem types with high AGB accumulation will
have greater contrast in microclimate, decomposition, vegetation structure, and disturbance rates
between edge and forest interior that forest ecosystem types with low AGB accumulation (Fig 1).
7
Hansen et al.
Edge effects across ecosystem types
This steeper gradient in resources and conditions may be more finely partitioned by plants and
animals, leading to a greater percentage of species specializing on forest interior, edge, or
disturbance patch interior conditions (need ref for this) in high compared to low AGB
accumulation forest ecosystem types.
This hypothesis was developed by Hansen and Rotella (2000) to account for differences
in the prevalence of edge and interior specialists between the temperate maritime rainforests and
the cold temperate continental forests in the Pacific and Inland Northwest US. Forests in this
region have broadly similar natural disturbance regimes, similar land use patterns, and broadly
overlapping pools of species. Hence, the influence of AGB accumulation on edge effects can be
examined in this region while controlling for the other hypotheses mentioned above. In the first
test of the Biomass Accumulation Hypothesis, WcWethy et al. (in press) found that more bird
species responded to changes in edge density in more productive west-slope Cascade forests than
less productive east-side Cascade forests and that bird community similarity in the productive
west-slope Cascade forests differed across low and high levels of edge density whereas no such
differentiation occurred in harsh, east-side Cascade forests. These findings lead us to examine
the hypothesis across a greater range of forest ecosystem types.
Objectives
This paper examines the degree to which previously published studies from a wide range
of forest ecosystem types support or refute the Biomass Accumulation Hypothesis. A key
conservation concern with regards to fragmentation is loss of species dependent upon interior
habitats. Consequently we choose as a meaningful measure of community response to
fragmentation the proportion of species in the community statistically associated with forest
8
Hansen et al.
Edge effects across ecosystem types
interiors because these are species that are likely to be lost if fragmentation proceeds. The
hypothesis suggests that degree of contrast in resources and conditions from edge to interior is
the mechanism underlying species responses. Thus, we also examine change in microclimate
from edge to interior.
The predictions tested were:
1.
Contrast in microclimate from forest edge to interior is higher in forest ecosystem types
with higher AGB accumulation than those with lower biomass.
2.
Because of the sharp gradient in vegetation and microclimate from forest interior to edge
in high AGB ecosystems, a greater percentage of species found in forest interiors are
significantly less abundant near forest edges than is the case in lower AGB ecosystems.
The notion that edge effects differ predictably across the world’s forests as a function of
their inherent abilities to accumulate biomass, while simple and intuitive, has not been
previously examined in the peer review literature nor discussed in forest conservation and
management texts. Increased knowledge on this hypothesis and others may eventually
contribute to a framework for prioritizing conservation and management strategies for habitat
fragmentation across the major forest ecosystem types.
Methods
Overview of Methods
We drew on published research on edge effects for forest ecosystem types ranging from
low to high in AGB. The goal was to summarize results on patterns of microclimate and species
distributions across abrupt forest edges. Thus, we focused on studies that quantified response
variables along transects placed perpendicular to forest edges, expressly, newly created edges
9
Hansen et al.
Edge effects across ecosystem types
between nonforest or early successional forest and mid or late-seral forest. This allowed us to
select studies that had similar study designs and allowed a direct test of the predictions.
We used standard literature search engines such as Web of Science to identify published
papers to consider for the study. Search terms such as “edge effects”, “ecotones”, “aboveground
biomass”, “microclimate”, and “species composition” were used. We also identified candidate
studies from the literature cited in published papers. Candidate papers where then scrutinized
relative to the criteria we specified for each of the predictions. The data were analyzed by
regressing the microclimate and interior species edge response variables across edges on AGB of
the forest.
Vegetation AGB
We estimated AGB for the selected studies by drawing on 10 published studies of AGB
from similar forest types (Fig. 2). These biomass studies synthesized results from a total of 59
ecosystems. We eliminated estimates from early seral forests, and non-native forests, which left
53 estimates of AGB in mid to late seral forests. These studies used various methods to estimate
AGB, including allometric, modeling, and remote sensing approaches. The accuracy of the AGB
data was not quantified. We grouped the results of these 53 ecosystems into one of seven biome
types (Olson et al. 2001) and averaged AGB within types to represent AGB levels typical of the
biome.
Prediction 1: Microclimate
Criteria for inclusion of published studies in this analysis were: 1) study designs
compared edge and/or matrix microclimate variables to interior microclimate variables; 2) the
disturbance patch adjacent to the forest had very low AGB and microclimate there approximated
that on ground uninfluenced by vegetation; 3) the mid and late-seral forests studied were in
10
Hansen et al.
Edge effects across ecosystem types
patches large enough to exhibit interior microclimate conditions; 4) the microclimate variables
were measured during the dry season in tropical evergreen forests or during the growing season
in tropical deciduous, temperate and boreal forests; and 4) the microclimate variables were
measured during mid-morning to mid-afternoon; 5) the results among studies were not rendered
incomparable due to edge orientation, season, or other factors. Thirteen studies met these criteria
and were included in the analysis (Table 1). These spanned the gradient in biome types and
AGB levels.
The microclimate variables reported differed among studies. The following variables
were studied frequently enough to include in our comparison: light levels; air temperature; soil
temperature; humidity; vapor pressure deficit; and soil moisture. All variables were measured at
intervals along transects from forest edge and/or matrix to forest interior using either a hand-held
sensor or a semi-permanent microclimate monitoring station situated near the ground or a
maximum of two meters in height. Measurements used were those taken simultaneously or
within two hours of each other along transects.
We extracted from each paper estimates for a given microclimate variable for forest
interior and forest edge. Interior values used were those that did not differ significantly as a
function of distance from edge. We assumed that this indicated that these locations were not
influenced by proximity to edges. Edge or matrix values were averages of those reported. The
distance from edge for interior conditions varied among studies (range: 30 m to 120 m). Exact
values were obtained from tables when available in the publications and estimations from figures
were used otherwise.
We used these data to estimate magnitude of edge influence (MEI). Following Harper et
al (2005), MEI was calculated as:
11
Hansen et al.
Edge effects across ecosystem types
(e-i)/(e+i)
e: value of the parameter at the edge
i: value of the parameter in the interior
MEI ranges between -1 and +1, with negative values indicating edge is lower than interior,
positive values indicating that edge is higher than interior, and a value of 0 indicating no edge
effect.
Prediction 2: Proportion Interior Species
Criteria for inclusion of papers in this analysis were: 1) species abundances were
quantified along forest edge to interior transects; 2) forest edges were relatively recently created
with matrix AGB being low; 3) sampling methods were comparable in sampling interval (spatial
and temporal); 4) the results among studies were not rendered incomparable due to edge
orientation, season, or other factors; and 5) statistical significances of species associations with
forest interiors were reported. Studies near urban or suburban development were excluded to
prevent complications due to species-human interactions. Most published studies we found
involved beetles, birds, and mammals, thus we restricted the analyses to these groups. A total of
20 studies remained after the final selection (Table 2).
Species response to edge was quantified as the proportion of species found in forests that
were significantly more abundant in forest interior than at the forest edge. This measure was
obtained for each study by dividing the total number of species associated statistically with
interior sites by the total number of species included in the statistical analysis of forest species.
MEI based on abundances of individual species was not appropriate because the species present
12
Hansen et al.
Edge effects across ecosystem types
differed between studies. Moreover, measures of total abundance among all species or species
richness are not considered highly relevant to conservation (Noss 2006a).
Statistical Analyses
Statistical inference from research findings across studies is increasingly drawn using
meta-analysis (Gurevitch & Hedges 1999, Osenberg et al. 1999). Meta-analysis requires
information on sample size and sampling variation for each study. Few of the studies we
selected for analysis reported sampling variation. Among the 31 studies included in the analyses,
only 5 reported sampling variance numerically. We concluded that a rigorous meta-analysis is
not possible with the current studies.
These studies do, however, represent the best current opportunity to evaluate the Biomass
Accumulation Hypothesis. If these studies provide support for the hypothesis, new well
designed research is justified. This approach is consistent with Gurevitch and Hedges (1999)
who argue that, “given a body of literature, some information regarding the overall findings is
much better than no information, and that therefore it is desirable to develop methods for data
synthesis of poorly reported data (e.g., where no estimate of sampling variance is published)” (pg
1146). They suggest unweighted standard parametric statistical tests such as ordinary leastsquares regression can sometimes be used and that the assumption of homogeneity of variances
of conventional statistics “does not always seriously compromise the Type I error rates of these
tests” (pg 1146). Sample variance is strongly influenced by sample size. If the sample size is
not biased relative to the magnitude of the predictor variable, regression may provide reliable
results. We examined the sample sizes for studies used in each of our analyses and found they
were either random relative to estimated AGB or were larger in lower AGB forests, which
increases the likelihood of significant relationships in low AGB forests and makes this analysis
13
Hansen et al.
Edge effects across ecosystem types
conservative for testing the hypothesis of greater differences in high AGB forests. We conclude
that use of regression to relate response variables to forest AGB is justified for these analyses.
MEI for each microclimate variable was regressed on AGB. Because sample sizes were
relatively small, we additionally used an analysis of covariance linear model for microclimate,
where microclimate type was the classification variable, MEI was the response variable, and
AGB and microclimate variables were the predictors. The model allowed the slope and intercept
to differ among microclimate variables. The absolute value of MEI was used in this analysis. If
AGB was significant in the model, we considered this as evidence in support of the AGB
Accumulation Hypothesis. Because sample sizes for species responses were higher, we analyzed
each taxonomic group separately. The proportion of interior species specialists was regressed
against AGB with linear models. Results were considered significant at the P<.05 level.
Results
MEI of light intensity increased significantly with AGB (n=13, F=8.65, p<0.01) (Fig 3).
MEI for forests with AGB of less than 200 t/ha ranged from 0.5 to 0.9 and was generally 0.9
to1.0 for forests higher in AGB. MEI for humidity was significantly negatively related to AGB
(n=6, F=27.49, p<0.006). This indicated a more humid environment in forest interiors than in
edges.
The remaining microclimate variables generally had the weakest MEI in low AGB
forests, however the univariate relationships were not statistically significant. VPD (n=5) was
similar to humidity showing moister conditions in forest interiors (Table 1). MEI for air
temperature data (n=7) generally increased with AGB, except for one observation in a low AGB
14
Hansen et al.
Edge effects across ecosystem types
Temperature Broadleaf forest in Hungary that showed a very high MEI. For soil moisture (n=3)
and soil temperature (n=4) there was no apparent relationship between MEI and AGB.
The overall model of microclimate MEI on AGB, controlling for microclimate variable
was significant (n=37, F=79.94, p<.0001). Within this model, AGB was possitively related to
the absolute value of MEI (F=251.02, p<0.0001).
Prediction 2: Interior Species
The percent of forest species specializing on forest interiors exhibited a positive
significant relationship with AGB for mammals (n=6, F=28.93, P<0.006) and birds (n=8,
F=6.57, P<0.043) (Fig. 4). The relationship for beetles was positive, but P-value slightly
exceeded the 0.05 cut-off for statistical significance (n=6, F=6.72, P<0.060). AGB explained
90%, 67%, and 65% of the variation in mammals, birds, and beetles respectively.
Among mammal studies, no forest interior species were found in three studies with forest
AGB below 140 t/ha. Percent interior species was 11-25 for mammals in forests of 312-412 t/ha.
Percent interior bird species increased in forests with AGB of 40 t/ha to about 200 t/ha. Above
this AGB level, the percent interior species remained near 30. The percentage for beetles was 0
in forests below75 t/ha, approximately 18 in forests 78-423 t/ha, and was 50 in one forest with a
AGB of 450 t/ha.
Discussion
The results were supportive of the two predictions of the Biomass Accumulation
Hypothesis. The microclimate analyses were limited by very small samples for four of the five
variables. Even so, there was a significant relationship between MEI and AGB for light and
humidity and the overall effect of AGB on MEI across microclimate variables was significant.
15
Hansen et al.
Edge effects across ecosystem types
These results suggest that the greater amount of vegetation in higher AGB forest ecosystems
more fully buffers the microclimate in forest interiors and creates sharp gradients from interior to
edge. The magnitude of MEI for microclimate in tropical rainforests is known to be sufficient to
have pronounced ecological effects such as tree and plant mortality (Laurance et al. 2002) and
substantially elevated fire frequencies (Cochrane & Laurance 2002; Cochrane 2003).
The proportion of species significantly more abundant in forest interior was also
positively related to AGB for two of the three taxonomic groups we examined. This was
especially the case with mammals for which three studies with AGB below 200 t/ha had no
forest interior specialists. These results are consistent with the prediction of the Biomass
Accumulation Hypothesis that interior species were poorly represented in these low AGB forests
because forest interiors and edges did not differ much in microclimate, vegetation structure, and
other direct edge effects. In support, several studies found significant correlations between
microclimate, vegetation structure, and species abundances along edge to interior gradients
(Didham et al. 1998; Magura et al. 2001).
The trends in percent interior species with AGB were generally similar for the three
taxonomic groups. The results suggest that beetle species may partition the edge-to interior
gradient in lower AGB forests than mammals and birds. The results also suggest that the
proportion of interior bird specialists plateaus at forest AGB levels above about 200 t/ha. It is
likely that differences in body size, home range size, and other aspects of scaling between
taxonomic groups influences the relationship between edge effects and AGB. More rigorous
study and larger sample sizes would be needed to test this hypothesis.
Scope and Limitations
16
Hansen et al.
Edge effects across ecosystem types
We acknowledge several limitations to our treatment of this issue. We choose to limit the
analyses to microclimate, beetles, birds, and mammals in forested systems. Forested ecosystems
were studied because the hypothesis most obviously applies to forests. Conceptually, the
hypothesis should apply to grassland and shrubland systems, but less so than for forests due to
their greater AGB. Moreover, studies of edge effects in nonforest vegetation types are fewer and
estimates of AGB are more difficult to obtain.
The analysis of species specialization was restricted to beetles, birds, and mammals
because too few studies were available for other taxonomic groups. Also, we suspect that edge
effects for tree species composition are more difficult to quantify because of the relatively slow
response of their distribution to changing conditions such as edge creation. Edge effects for
amphibians may also be difficult to assess because these species require various aquatic and
terrestrial habitats at different life stages (Becker et al. 2007).
An assumption of our approach for species distributions across edges was that no forest
interior species had become locally extinct after habitats had become fragmentation but before
the studies were conducted. Local extinction in forest fragments has been documented (Saunders
et al.1991: Robinson 1999). The patch sizes at which extinction occurs is known to vary with
trophic level, home range size, and population abundance, with top-level carnivores requiring the
largest habitat sizes for persistence (Woodroffe & Ginsberg 1998). The species sampled in the
studies we used were relatively small in body size and sufficiently abundant to be detected at
levels adequate for statistical analysis by the multispecies sampling methods used in these
studies. Thus, these species likely had relatively small home ranges. Moreover, all the studies
were done in relatively large forest stands. We conclude that it is unlikely that our results were
influenced by previous local extinctions of forest interior species.
17
Hansen et al.
Edge effects across ecosystem types
The study considered only the magnitude of edge influence and not depth of edge
influence. Depth of edge influence (DEI) is the distance that edge effects penetrate the habitat
(Chen et al. 1999; Harper et al. 2005). This was done to make this initial analysis more tractable.
We speculate that DEI has a unimodal relationship with AGB, reaching a maximum in forests
with intermediate AGB. In forests higher in AGB forests, the dense vegetation should inhibit
depth of penetration of direct and indirect edge effects. In forest with lower AGB, DEI should
diminish as conditions in the forest interior are similar to those in the matrix.
Within the response variables we chose for analysis, sample sizes were relatively small.
This was because of the moderate number of edge studies that have been published and because
we excluded many of the published papers because of incompatible study designs, lack of
rigorous statistical analysis, or because of confounding factors. To best draw inference from the
limited sample, we reported results for both the relationships between AGB and MEI of
individual microclimate variables and across all microclimate variables and controlling for
variable type.
Although the studies included in the analyses were selected based on the stated criteria,
they differed to some extent in site-level factors such as edge age and development, orientation,
and matrix type. We assume that these biases were random relative to the effects of AGB.
Laurance et al. (2007) describes how such local factors can cause considerable variation in edge
effects within a given region. The fact that significant relationships were found in our analyses
despite the variability introduced by differences in the site conditions of studies we drew upon,
suggests that the effect of AGB on edge effects was strong enough to be detected despite the
variability due to confounding factors.
The tropical studies only sampled a small fraction of local diversity in many cases and it is likely
that the species chosen were not a random sub-sample. It is certainly not possible to conclude
18
Hansen et al.
Edge effects across ecosystem types
from a study with 4 species about the effects on a whole community of dozens or even hundreds
of species (in the case of
beetles). It is likely that investigators chose species that are likely to show an edge effect. It
appears that his bias is greater in the tropics where communities were seriously under-sampled.
The analysis should be repeated using only the studies that have a decent number of species
sampled (a minimum of 8 or even 10).
Finally, the studies did not provide adequate information to allow formal meta-analysis (see
Methods), we feel the regression methods used were justified for this analysis.
Despite these limitations, we feel that this analysis is an appropriate first test of the
hypotheses. Given the results of this analysis, the cost of conducting a replicated experiment
across biomes may now be justified.
Review alternative hypotheses
If the edges are a recent man-made phenomenon in a region, one would not expect
edge-specialist species. Perhaps a better hypothesis is that ecosystems with little history of
edges and open habitats should have more species intolerant of the stresses associated with
open habitats. It is not a matter of steepness of gradients but consequence of lacking
adaptation because of no previous exposure. Could we test the disturbance history
alternative hyp? I think it is a good one, having been to suriname. The tropics jump out as
having less large patch creating disturbances of any system I have seen. Is disturbance
history something we could control for in the analysis? I suspect both are happening.
This is a good example where confounding high latitude clear cut edges with low latitude
agricultural field edges is a problem. Boreal forest mammals like moose find excellent forage in
clear cuts, while moose would avoid a cow pasture or soybean field.
19
Hansen et al.
Edge effects across ecosystem types
Similarly not all mammals are alike. The boreal forest has mostly ground dwelling mammals like
moose and beaver, whereas tropical forests have many arboreal mammals, which obviously
depend on trees. Thus there is a latitudinal difference in species guilds that affects edge effects
independent of biomass. Tree dwelling marsupials of the tropical rainforest in Queensland
Australia will not enter a cow pasture, regardless of the tree biomass in the forest. Such
latitudinal differences in species guild composition are an important dimension of the edge effect
question that needs to enter the discussion. Moreover, it implies that the apparent relationship
between biomass and edge effect strength may have little to do with the microclimatic
explanation given here. To meet the scholarship standards of CB, such possible alternative
interpretations need to be at least mentioned.
The other low biomass forest in the bird dataset is boreal. As mentioned before, the clear cut
edges in the boreal forests are very different than temperate forest that are fragmenting due to
agriculture and development. Specifically, as the authors mention in the introduction, edge
effects on birds are frequently due to brood parasitism or predation by small predators. The
boreal forest neither has brood parasites like cow birds nor do small and medium sized predators
concentrate along clear cut edges. In contrasst areas subject to higher human population densities
have abnormally high concentrations of small predators (like domestic cats)
which like to hunt along forest edges. These points are important because in the savanna case the
biomass effect results from a complete lack of "forest interior" habitat in the landscape, and in
the other types of forest the mechanism has more to do with predator and brood parasite behavior
than with forest biomass or micro-climate.
Percent of landscape disturbed and seperateing area effects and patch size effects.
Is another evolution time?
Review well known studies that were not included here
Comparison with Current Knowledge
Previous efforts to develop general theory on the situations where edge effects are most
pronounced have focused largely on site-level factors (Donovan et al. 1997; Laurance et al.
2002). These include: attributes of the habitat such as vertical structure and soil depth; edge
attributes such as age, orientation, and vegetation contrast; and matrix characteristics such
vegetation structure and composition and land use. The susceptibility of major ecosystem types
to edge effects has been little studied. A recent paper by Harper et al. (2005) suggested that the
20
Hansen et al.
Edge effects across ecosystem types
traits of ecosystems that are especially prone to edge effects include: climate (high mean air
temperature and solar radiation, low cloud cover, frequent extreme winds); disturbance
(infrequent stand replacing disturbances); community structure (many early-seral and invasive
species); landscape patterns (low inherent habitat patchiness). Additionally, Hansen & Urban
(1992) suggested that the life history attributes of species in the community vary among
ecosystems and influence direct biotic edge effects.
The Biomass Accumulation Hypothesis integrates several the ecosystem factors
described by Harper et al. (2005) and Hansen & Urban (1992). Forests with high AGB
accumulation tend to have warm temperatures, high solar radiation, periods of low clouds, high
primary productivity, infrequent stand replacing disturbance, and low natural patchiness in
forest/non-forest conditions (Brown & Lugo 1982). Moreover, species in high productivity and
high AGB systems tend to have small home ranges, low dispersal, and habitat specialization.
Hence, biomass accumulation appears to represent a syndrome of ecosystem characteristics that
cause magnitude of edge effects to be pronounced.
Implications
This study is the first to test the Biomass Accumulation Hypothesis. The results support
the hypothesis that biomass accumulation influences the magnitude of one component of
fragmentation, edge effects. Edge effects, in turn, are a component of patch size effects (Turner
et al. 2001; Noss et al. 2006b). Less area within a patch will display habitat interior conditions
when edge effects are pronounced. Consequently, we expect that extinction rates of interior
species in small patches will be higher in high biomass ecosystems.
Our results suggest that habitat fragmentation has the strongest negative effects on
ecosystems with high productivity and biomass accumulation, such as wet tropical and wet
21
Hansen et al.
Edge effects across ecosystem types
temperate forests. Thus, efforts to minimize or mitigate fragmentation are most appropriately
applied to such high biomass ecosystems. It is important that managers in high biomass forests
not be confused by the ambiguous results of edge studies globally and take seriously the
management of habitat configuration within their forests. In ecosystems with low biomass
accumulation such as boreal, dry, or cold forests, conservation strategies to manage edge and
patch effects may be a lower priority. Further work should be directed towards identifying
thresholds in the relationship between forest biomass and edge effects that could be used to more
precisely guide the management of landscape configuration to local biophysical conditions.
Note the value of this, it is the general message that conservation should be tailored to
local conditions.
Page 21 re: cross biome experiments: I think it would be a waste of money. Biomass has a
spurious correlation at best for the data presented. Most likely there is a threshold
biomass from closed canopy forests to open savannas, but other wise biomass seems to have
little explanatory power. Conservationists already have much better arguments for conserving
large contiguous habitats. For example range requirements for large animals and minimum
viable population size. Knowing the minimum patch sizes
needed in particular environmental contexts will do far more for conservation than exploring a
global relationship between biomass and strength of edge effects. As someone that works for a
conservation NGO, I can’t see any way how such a global approximation could be useful in
practice. The exercise proposed is purely academic. I find that even academically it has little
merit, given that it ignores causal mechanisms.
o
Overall, application of the Biomass Accumulation Hypothesis is an example of using
fundamental ecosystem properties as a basis for tailoring conservation to local ecosystem
conditions, a needed next step for conservation biology.
Acknowledgements
22
Hansen et al.
Edge effects across ecosystem types
We thank Diane Debinski and Jiquan Chen for comments on earlier drafts of the
manuscript. Jim Robinson-Cox provided guidance on statistical analyses. We also thank the
authors of the numerous publications that made this study possible.
Literature Cited
Baker, J., K. French, R. J. Whelan. 2002. The edge effect and ecotonal species: Bird
communities across a natural edge in southeastern Australia. Ecology 83:3048–3059.
Becker, C.G., C.R. Fonseca, C.F.B. Haddad, R.F. Batista, P.I. Prado. 2007. Habitat Split and
the Global Decline of Amphibians. Science 318 (5857): 1775-1777.
Berry, L. 2001. Edge effects on the distribution and abundance of birds in a southern Victorian
forest. Wildlife Research 28:239-245.
Brand, L. A., and T. L. George. 2001. Response of passerine birds to forest edge in coast
redwood forest fragments. The Auk 118:678-686.
Brown, S., and A. E. Lugo. 1982. The storage and production of organic matter in tropical
forests and their role in the global carbon cycle. Biotropica 14:161-187.
Brown, S., and A. E. Lugo. 1984. AGB of tropical forests: A new estimate based on forest
volumes. Science 223: 1290-1293.
Brown, S. L.R. Iverson, A. Prasad, and D. Liu. 1993. Geographical distributions of carbon in
biomass and soils in tropical Asian forests. Geocarto International 4:45-59.
Burke, D. M., and E. Nol. 1998. Edge and fragment size effects on the vegetation of deciduous
forests in ontario, Canada. Natural Areas Journal 18:45-53.
23
Hansen et al.
Edge effects across ecosystem types
Cairns, M. A., I. Olmsted, J. Granados, and J. Argaez. 2003. Composition and aboveground tree
AGB of a dry semi-evergreen forest on Mexico’s Yucatan Peninsula. Forest Ecology and
Management 186:125–132.
Chazon, R. L., and N. Fetcher. 1984. Photosynthetic light environments in a lowland tropical
rain forest in Costa Rica. The Journal of Ecology 72:553-564.
Chen, J., J.F. Franklin, and T.A. Spies. 1993. Contrasting microclimates among clearcut, edge
and interior of old growth Douglas-fir forest. Agricultural and Forest Meteorology
63:219-237.
Chen, J., S. C. Saunders, T. R. Crow, R. J. Naiman, K. D. Brosofske, G. D. Mroz, B. L.
Brookshire, and J. F. Franklin. 1999. Microclimate in forest ecosystem and landscape
biology. BioScience 49:288-297.
Cochrane, M.A. and W.F. Laurance. 2002. Fire as a large-scale edge effect in Amazonian
forests. Journal of Tropical Ecology 18:311-325.
Cochrane, M.A. 2003. Fire science for rainforests. Nature 421:913-919.
Didham, R. K., P. M. Hammond, J. H. Lawton, P. Eggleton, and N. E. Stork. 1998. Beetle
species responses to tropical forest fragmentation. Ecological Monographs 68:295-323.
Donovan, T., P. W. Jones, E. M. Annand, and F. R. I. Thompson. 1997. Variation in local-scale
edge effects: Mechanisms and lanscape context. Ecology 78:2064-2075.
Fahrig, L. 2003. Effects of habitat fragmentation on biodiversity. Annu. Rev. Ecol. Evol. Syst.
2003. 34:487–515.
Gehlhausen, S. M., M. W. Schwartz, and C. K. Augspurger. 2000. Vegetation and microclimatic
edge effects in two mixed-mesophytic forest fragments. Plant Ecology 147:21-35.
24
Hansen et al.
Edge effects across ecosystem types
Gerwing, J.J., and D. L. Farias. 2000. Integrating liana abundance and forest structure into an
estimate of total aboveground biomass for and eastern Amazonian forest. Journal of
Tropical Biology 16:327-335.
Ghuman, B. S., and R. Lal. 1987. Effects of partial clearing on microclimate in a humid tropical
forest. Agricultural and Forest Meteorology 40:17-29.
Groom, M. J., G. K. Meffe and C. R. Caroll, editors. 2006. Principles of Conservation Biology.
3rd edition. Sinauer, Sunderland, MA.
Grumbine, R. E. 1994. What is ecosystem managment? Conservation Biology 8:27-38.
Gurevitch, J., and L.V. Hedges. 1999. Statistical issues in ecological meta-analyses. Ecology
80:1142-1149.
Hansen, A. J. and D. L. Urban. 1992. Avian response to landscape pattern: The role of species
life histories. Landscape Ecology 7:163-180.
Hansen, A. J. and J. J. Rotella. 2000. Bird responses to forest fragmentation. Pgs 202-221 in R.L.
Knight, F.W. Smith, S.W. Buskirk, W.H. Romme, and W.L. Baker, (eds.) Forest
Fragmentation in the Southern Rocky Mountains. University of Colorado Press, Boulder,
CO.
Hansson, L. 1994. Vertebrate distributions relative to clear-cut edges in a boreal forest
landscape. Landscape Ecology 9:105-115.
Harper, K. A., S. E. Macdonald, P. J. Burton, J. Chen, K. D. Brosofske, S. C. Saunders, E. S.
Euskirchen, D. Roberts, M. S. Jaiteh, and P. Esseen. 2005. Edge influence on forest
structure and composition in fragmented landscapes. Conservation Biology 19:768-782.
Harrison, S., and E. Bruna. 1999. Habitat fragmentation and large-scale conservation: What do
we know for sure? Ecography 22:225-232.
25
Hansen et al.
Edge effects across ecosystem types
Heliola, J., M. Koivula, and J. Niemela. 2001. Distribution of carabid beetles (coleoptera,
carabidae) across a boreal forest-clearcut ecotone. Conservation Biology 15:370-377.
Heske, E. J. 1995. Mammalian abundances on forest-farm edges versus forest interiors in
southern illinois: Is there an edge effect? Journal of Mammalogy 76:562-568.
Hill, C. 1995. Linear strips of rain forest vegetation as potential dispersal corridors for rain forest
insects. Conservation Biology 9:1559-1566.
Kapos, V. 1989. Effects of isolation on the water status of forest patches in the Brazilian
Amazon. Journal of Tropical Ecology 5:173-185.
King, D. I., C. R. Griffin, and R. M. DeGraaf. 1997. Effect of clearcut borders on distribution
and abundance of forest birds in northern New Hampshire. Wilson Bulletin 109:239-245.
Koivula, M., V. Hyyryläinen, and E. Soininen. 2004. Carabid beetles (coleoptera: Carabidae) at
forest-farmland edges in southern Finland. Journal of Insect Conservation 8:297-309.
Kremsater L, Bunnell FL. 1999. Edge effects: theory, evidence and implications to management
of western North American forests. Pages 117–153 In Forest Fragmentation: Wildlife and
Management Implications, ed. J.A. Rochelle, L.A. Lehmann, J. Wisniewski. Boston, MA.
301 pp.
Kroodsma, R. L. 1982. Edge effect on breeding forest birds along a power-line corridor. The
Journal of Applied Ecology 19:361-370.
Laurance, W. F. 1994. Rain-forest fragmentation and the structure of small mammal
communities in tropical Queensland. Biological Conservation 69:23-32.
Laurance, W. F., T. E. Lovejoy, H. L. Vasconcelos, E. M. Bruna, R. K. Didham, P. C. Stouffer,
C. Gascon, R. O. Bierregaad, S. G. Laurance, and E. Sampaio. 2002. Ecosystem decay of
Amazonian forest fragments: A 22-year investigation. Conservation Biology 16:605-618.
26
Hansen et al.
Edge effects across ecosystem types
Laurance, W.F., H.E.M. Nascimento, S.G. Laurance, A. Andrade, R.M. Ewers, K.E. Harms,
R.C.C. Luizao, J.E. Ribeiro. 2007. Habitat Fragmentation, Variable Edge Effects, and
the Landscape-Divergence Hypothesis. PLoS ONE 2(10): e1017, pgs 1-8.
Lefsky, M. A., W. B. Cohen, D. J. Harding, G. G. Parker, S. A. Acker, and S. T. Gower. 2002.
Lidar remote sensing of above-ground AGB in three biomes. Global Ecology &
Biogeography 11:393–399.
Lehman, S. M., A. Rajaonson, and S. Day. 2006. Lemur responses to edge effects in the vohibola
III classified forest, Madagascar. American Journal of Primatology 68:293-299.
Luken, J. O., and N. Goessling. 1995. Seedling distribution and potential persistence of the
exotic shrub lonicera maackii in fragmented forests. American Midland Naturalist
133:124-130.
Magura, T., B. Tothmeresz, and T. Molnar. 2001. Forest edge and diversity: Carabids along
forest-grassland transects. Biodiversity and Conservation 10:287-300.
Matlack, G. R. 1993. Microenvironment variation within and among forest edge sites in the
eastern united states. Biological Conservation 66:185-194.
Matlack, G. and J. Litvaitis. 1999. Forest Edges. Pages 210-233 In: M.L Hunter, Jr. (ed.).
Maintaining biodiversity in forest ecosystems. Cambridge University Press, Cambridge,
U.K.
McDonald, D., and D. A. Norton. 1992. Light environments in temperate new zealand podocarp
rainforests. New Zealand Journal of Ecology 16:15-22.
Means, J. E., S. A. Acker, D. J. Harding, J. B. Blair, M. A. Lefsky,: W. B. Cohen, M. E. Harmon,
and W. A. McKee. 1999. Use of large-footprint scanning airborne Lidar to estimate
27
Hansen et al.
Edge effects across ecosystem types
forest stand characteristics in the Western Cascades of Oregon. Remote Sensing of the
Environment. 67:298-308.
Messier, C., S. Parent, and Y. Bergeron. 1998. Effects of overstory and understory vegetation on
the understory light environment in mixed boreal forests. Journal of Vegetation Structure
9:511-520.
Murcia, C. 1995. Edge effects in fragmented forests: Implications for conservation. Tree 10:5862.
Myneni, R. B., J. Dong, C. J. Tucker, R. K. Kaufmann, P. E. Kauppi, J. Liski, L. Zhou, V.
Alexeyev, and M. K. Hughes. 2001. A large carbon sink in the woody AGB of Northern
forests. PNAS 98:14784-14789.
Noss, R. F. 1991. Effects of edge and internal patchiness on avian habitat use in an old-growth
Florida hammock. Natural Areas Journal 11:34-47.
Noss, R., B. Csuti, and M. J. Groom. 2006a. Habitat fragmentation. Pages 213-251 in M. J.
Groom, G. K. Meffe and C. R. Caroll, editors. Principles of Conservation Biology. 3rd
edition. Sinauer, Sunderland, MA.
Noss, R. F., J. F. Franklin, W. L. Baker, T. Schoennagel, and P.B. Moyle. 2006b: Managing fireprone forests in the western United States. Frontiers in Ecology and the Environment
4:481–487.
Olson, D. M., E. Dinerstein, E. D. Wikramanayake, et al. 2001. Terrestrial ecoregions of the
world: A new map of life on Earth. BioScience 51:933-938.
Osenberg, C. W., O. Sarnelle, S. D. Cooper, and R. D. Holt. 1999. Resolving ecological
questions through meta-analysis: goals, metrics, and models. Ecology 80:1105–1117.
28
Hansen et al.
Edge effects across ecosystem types
Pardini, R. 2004. Effects of forest fragmentation on small mammals in an Atlantic forest
landscape. Biodiversity and Conservation 13:2567-2586.
Paton, W. C. 1994. The effect of edge of avian nest success: How strong is the evidence?
Conservation Biology 8:17-26.
Penner, M., K. Power, C. Muhairwe, R. Tellier, and Y. Wang. 1997. Canada’s Forest AGB
Resources: Deriving Estimates from Canada’s Forest Inventory. Pacific Forestry Centre,
Canadian Forest Service, Victoria, British Columbia. Information Report BC-X-370
Perry, D. 1994. Forest Ecosystems. Baltimore, Maryland. The Johns Hopkins University Press.
649 pg
Reifsnyder, W. E., G. M. Furnival, and J. L. Horowitz. 1971/1972. Spatial and temporal
distribution of solar radiation beneath forest canopies. Agricultural Meteorology 9:21-37.
Restrepo, C., and N. Gomez. 1998. Responses of understory birds to anthropogenic edges in a
neotropical montane forest. Ecological Applications 8:170-183.
Robinson, W.D. 1999. Long-term changes in the avifauna of Barro Colorado Island, Panama, a
tropical forest isolate. Conservation Biology 13 (1):85–97.
Running, S. W., R. R. Nemani, F. A. Heinsch, M. S. Zhao, M. Reeves, and H. Hashimoto. 2004.
A continuous satellite-derived measurement of global terrestrial primary production.
Bioscience 54: 547-560.
Saunders, D. A., R. J. Hobbs, and C. R. Margules. 1991. Biological consequences of ecosystem
fragmentation: A review. Conservation Biology 5:18-32.
Sekgororoane, G. B., and T. G. Dilworth. 1995. Relative abundance, richness, and diversity of
small mammals at induced forest edges. Canadian Journal of Zoology 73:1432-1437.
29
Hansen et al.
Edge effects across ecosystem types
Strong, A. M., C. A. Dickert, and R. T. Bell. 2002. Ski trail effects on a beetle (coleoptera:
Carabidae, elateridae) community in Vermont. Journal of Insect Conservation 6:149-159.
Tate, K. R., D. J. Giltrap, J. J. Claydon, P. F. Newsome, A. E. Atkinson, M. D. Taylor, R. Lee.
1997. Organic carbon stocks in New Zealand's terrestrial ecosystems. Journal of The
Royal Society of New Zealand 27:315-335.
Turner, M. G., R. H. Gardner, R. V. O’Neill. 2001. Landscape Ecology in Theory and Practice:
Pattern and Process. Springer Verlag, New York.
Turton, S. M, and H. J. Freiburger.1997. Edge and aspect effects on the microclimate of a small
tropical forest remanant on the Atherton Tablelands, northeastern Australia. Pages 45-54
in W.L. Laurance and R.O. Bierrgaard,Jr., editors. Tropical forest remnants: ecology,
managment, and conservation of fragmented communities. University of Chicago Press,
Chicago, Illinois, USA.
Vaillancourt,D. A. 1995. Structural and microclimatic edge effects associated with clear-cutting
in a Rocky Mountain forest. Master's thesis, University of Wyoming, Laramie,
Wyoming.
White, J. D., N. C. Coops, N. A. Scott. 2000. Estimates of New Zealand forest and scrub AGB
from the 3-PG model. Ecological Modelling 131:175–190.
White, P. S., and A. Jentsch. 2001. The search for generality in studies of disturbance and
ecosystem dynamics. Progress in Botany 62:399-450.
Woodroffe, R., and J. R. Ginsberg. 1998. Edge effects and the extinction of populations inside
protected areas. Science 280:2126–2128
Young, A., and N. Mitchell. 1994. Microclimate and vegetation edge effects in a fragmented
podocarp-broadleaf forest in New Zealand. Biological Conservation 67:63-72.
30
Hansen et al.
Edge effects across ecosystem types
Evans, K.L. Newson, S.E., Storch, D. Greenwood, J.D. and Gaston, K.J. 2007. Spatial scale,
abundance and the species-energy relationship in British birds, Journal of Animal
Ecology, 77:2, 395-405
Gaston, K. J. (2000). Global patterns in biodiversity. Nature, 405,220–227
Hawkins, B. A., Porter, E. E., & Diniz-Fahlo, J. A. F. (2003). Productivity and history as
predictors of the latitudinal diversity gradient of terrestrial birds. Ecology, 84, 1608–1623
Huston, M. A. 1994. Biological diversity: the coexistence of species on changing landscapes.
Cambridge University Press, Cambridge, UK.
Mittelbach, G. G., Steiner, C. F., Scheiner, S. M. , Gross, K. L., Reynolds, H. L., Waide, R. B.,
Willig, M. R., Dodson, S. I., & Gough, L. (2001). What is the observed relationship
between species richness and productivity? Ecology, 82:2381-2396
Rosenzweig, M.L, and Abramsky, Z., 1993. How are diversity and productivity related? Pp. 5265 in Ricklefs, R. and D Schluter (eds.) Species diversity in ecological communities:
historical and geographical perspectives. University Chicago Press.
Srivastava, D.S. and J.H. Lawton 1998. Why more productive sites have more species: an
experimental test of theory using tree-hole communities. American Naturalist 152:510529.
Waide, R.B., Willig, M.R., Steiner, C.F., Mittelbach, G., Gough, L., Dodson, S.I., Juday, G.P.,
& Parmeter, R. (1999). The relationship between productivity and species richness.
Annual Review of Ecology and Systematics, 30: 257–300
Wright, D.H. (1983). Species-energy theory – an extension of species-area theory. Oikos 41, 3,
496-506
31
Hansen et al.
Edge effects across ecosystem types
Table 1. Studies of microclimate across forest edges included in the analyses. Biomes are
defined as defined by Olson et al. 2001 except that the only Temperate Coniferous samples
included in the study were Temperature Coniferous Rainforest and are thus termed that. AGB
refers to aboveground standing vegetation. MEI is magnitude of edge influence as defined in
Methods.
Biome
Study
Region
AGB
Variable
MEI
(t/ha)
Boreal
Burke & Nol
Ontario, Canada
63
Light
0.60
Quebec, Canada
63
Light
0.78
Quebec, Canada
63
Light
0.79
Quebec, Canada
63
Light
0.86
Vaillancourt 1995
Wyoming, USA
100
Light
0.51
Temperate
Luken &
Kentucky, USA
104
Light
0.88
Broadleaf
Goessling 1995
Temperate
Reifsnyder et al,
Connecticut, USA 142
Light
0.83
Broadleaf
1971
Temperate
Matlack 1993
Pennsylvania,
Light
0.82
1998
Boreal
Messier et al.
1998
Boreal
Messier et al.
1998
Boreal
Messier et al.
1998
Temperate
Coniferous (subalpine)
180
32
Hansen et al.
Edge effects across ecosystem types
Broadleaf
USA
Subtropical Moist
McDonald &
New Zealand
343
Light
0.95
Broadleaf
Norton 1992
Subtropical Moist
Young &
New Zealand
378
Light
0.86
Broadleaf
Mitchell 1994
Tropical Moist
Kapos 1989
Brazil
400
Light
0.94
Tropical Moist
Ghuman & Lal
Nigeria
412
Light
0.94
Broadleaf
1987
Tropical Moist
Chazdon &
Costa Rica
450
Light
0.97
Broadleaf
Fetcher 1984
Temperate
Magura et al.
Hungary
78
Air temperature
0.10
Broadleaf
2001
Temperate
Gelhausen et al.
Broadleaf
2000
Temperate
Matlack 1993
Broadleaf
Broadleaf
Illinois, USA
100
Turton &
Broadleaf
Frieburger 1997
Subtropical Moist
Young &
Broadleaf
Mitchell 1994
Tropical Moist
Kapos 1989
Air temperature
0.03
(°C)
Pennsylvania,
180
USA
Tropical Moist
Broadleaf
(°C)
Australia
Air temperature
0.05
(°C)
270
Air temperature
0.01
(°C)
New Zealand
378
Air temperature
0.04
(°C)
Brazil
400
Air temperature
0.08
(°C)
33
Hansen et al.
Temperate
Edge effects across ecosystem types
Chen et al. 1993
Washington, USA 687
Coniferous
Air temperature
0.10
(°C)
Rainforest
Boreal
Burke & Nol
Ontario
63
Humidity (%)
0.00
Hungary
78
Humidity (%)
-0.07
Illinois, USA
100
Humidity (%)
-0.06
Pennsylvania,
180
Humidity (%)
-0.04
412
Humidity (%)
-0.26
Humidity (%)
-0.29
180
VPD (mb)
0.17
Australia
270
VPD (mb)
0.50
New Zealand
378
VPD (mb)
0.15
Brazil
400
VPD (mb)
0.68
1998
Temperate
Magura et al.
Broadleaf
2001
Temperate
Gelhausen et al.
Broadleaf
2000
Temperate
Matlack 1993
Broadleaf
USA
Tropical Moist
Ghuman & Lal
Nigeria
Broadleaf
1987
Temperate
Chen et al. 1993
Washington, USA 687
Matlack 1993
Pennsylvania,
Coniferous
Rainforest
Temperate
Broadleaf
USA
Tropical Moist
Turton &
Broadleaf
Frieburger 1997
Subtropical Moist
Young &
Broadleaf
Mitchell 1994
Tropical Moist
Kapos 1989
34
Hansen et al.
Edge effects across ecosystem types
Broadleaf
Boreal
Burke & Nol
Ontario, Canada
63
1998
Temperate
Gelhausen et al.
Broadleaf
2000
Tropical Moist
Kapos 1989
-0.07
(%)
Illinois, USA
100
Soil Moisture
-0.22
(%)
Brazil
400
Broadleaf
Boreal
Soil Moisture
Soil Moisture
-0.14
(%)
Burke & Nol
Ontario
63
1998
Soil
0.07
Temperature
(°C)
Temperate
Magura et al.
Broadleaf
2001
Hungary
78
Soil
0.05
Temperature
(°C)
Tropical Moist
Turton &
Broadleaf
Frieburger 1997
Australia
270
Soil
0.01
Temperature
(°C)
Temperate
Chen et al. 1993
Washington, USA 687
Soil
Coniferous
Temperature
Rainforest
(°C)
0.04
35
Hansen et al.
Edge effects across ecosystem types
Table 2. Studies of animal species composition used in the analyses. AGB refers to
aboveground standing vegetation.
Biome
Study
Region
AGB
Taxonomic
Total
Percent
(t/ha)
Group
Species
Interior
Specialists
Boreal
Heliola et al.
Finland
40 beetle
34
0
Finland
75 beetle
12
0
130 beetle
11
18
78 beetle
17
17
Brazil
423 beetle
32
19
Hill 1995
Australia
450 beetle
4
50
Boreal
Hansson 1994
Sweden
39 Bird
16
0
Temperate
Baker 2001
Australia
100 Bird
27
11
Berry 2001
Victoria,
157 Bird
13
0
2001
Boreal
Koivula et al.
2004
Temperate
Strong et al.
Vermont,
Coniferous
2002
USA
Temperature Magura et al.
Broadleaf
2001
Tropical
Didham et al.
Moist
1998
Hungary
Broadleaf
Tropical
Moist
Broadleaf
Broadleaf
Tropical
36
Hansen et al.
Edge effects across ecosystem types
Intermediate
Australia
Broadleaf
Temperate
Noss 1991
Broadleaf
Florida,
181 Bird
27
15
244 Bird
26
35
266 Bird
7
29
USA
Temperate
Kroosma et al.
Tennessee,
Broadleaf
1982
USA
Temperate
King et al.
New
Broadleaf
1997
Hampshire,
USA
Tropical
Restrepo 1998
Columbia
552 bird
25
32
Temperate
Brand &
California,
600 bird
14
29
Coniferous
George 2001
USA
Boreal
Hansson 1994
Sweden
39 mammal
9
0
Temperate
Sekgororoane
New
84 mammal
9
0
Coniferous
et al. 1995
Brunswick,
137 mammal
11
0
314 mammal
9
11
Moist
Broadleaf
Rainforest
Canada
Temperate
Heske 1995
Broadleaf
Tropical
Illinois,
USA
Pardini 2004
Brazil
Intermediate
37
Hansen et al.
Edge effects across ecosystem types
Broadleaf
Tropical
Laurance 1994
Australia
400 mammal
4
25
Temperate
Lehman et al
Madagascar
412 mammal
6
17
Broadleaf
2006
Moist
Broadleaf
Table 2: The edges in these studies include hard edges like agriculture in Queensland Australia
to forest clear cuts in eastern Canada. The effect on edge effects and species is very different. A
regenerating clear cut provides good habitat with natural forest vegetation whereas dairy pastures
do not. This difference creates a bias because northern
sites tend to involve clear cuts while southern sites tend to involve cattle pastures.
38
Hansen et al.
Edge effects across ecosystem types
Figure Legends
Figure 1. Conceptual model of edge effects in ecosystems with high and biomass accumulation.
Depicted are adjacent early and late seral forest patches. Aboveground vegetation biomass (line
1) increases abruptly between early seral and late seral forest patches, causing a strong gradient
in microclimate (line 2) from forest edge to forest interior, and allowing species (line 3) to
specialize in either forest interior, edge, or early seral habitats resulting in narrow distributions in
abundance of guilds across the edge to interior gradient. In lower biomass ecosystems, the
gradient in biomass is less pronounced, consequently microclimate is less different between early
and late seral patches and species do not specialize highly on interior or edge habitats.
Figure 2. Average aboveground biomass of late seral forest in seven forested ecoregions
(defined in Olson et al. 2001). Data derived from published biomass values (Brown et al. 1993;
Penner et al 1997; Lefsky et al 2002; Myneni 2006; Brown & Lugo 1984; White et al 2000; Tate
et al 1997; Gerwing et al 2000; Means et al. 1999; Cairns et al. 2003). Temperate coniferous
studies were from extremely high biomass systems (California redwoods, Pacific Northwest
rainforest) and is not likely representative of the broader ecoregion.
Figure 3. Magnitude of edge influence (MEI) for microclimate variables across AGB levels.
MEI ranges between -1 and +1, with negative values indicating edge is lower than interior,
positive values indicating that edge is higher than interior, and a value of 0 indicating no edge
effect. VPD is vapor pressure deficit. Data are from the studies in Table 1.
39
Hansen et al.
Edge effects across ecosystem types
Figure 4. Percentage forest interior species for birds, beetles, and mammals across aboveground
biomass levels. Data are from studies in Table 2.
40
Hansen et al.
Edge effects across ecosystem types
Magnitude
Low
High Biomass Ecosystem
2. Microclimate (e.g.,
wind speed)
1. Vegetation biomass
High
3. Species Guild
Abundances
Early Seral Patch
Edge
Later Seral Patch
Magnitude
Low
Low Biomass Ecosystem
2. Microclimate (e.g.,
wind speed)
1. Vegetation biomass
High
3. Species Guild
Abundances
Early Seral Patch
Edge
Later Seral Patch
41
Hansen et al.
Edge effects across ecosystem types
42
Hansen et al.
Edge effects across ecosystem types
y= 0.0006 * AGB + 0.70
2
0.4
R =0.44
0.0
MEI
0.8
Light Intensity
0
100
200
300
400
500
AGB (t/ha)
0.0
Humidity
-0.3
-0.6
MEI
y= 0.0005 * AGB + 0.001
2
R = 0.87
0
100
200
300
400
500
600
700
AGB (t/ha)
43
Hansen et al.
Edge effects across ecosystem types
Percent of Species Specializing on Forest Interiors
60
Beetles
y = 0.0771x + 2.3499
R2 = 0.6457
50
Birds
y = 0.07x - 0.6979
R2 = 0.6782
40
30
Mammals
y = 0.0664x - 5.7805
R2 = 0.8958
20
10
0
-10
0
100
200
300
400
500
600
700
Biomass (t/ha)
44