Vol.1, No.2, 9-23 (2011)
http://dx.doi.org/10.4236/oje.2011.12002
Open Journal of Ecolog y
Bush, bugs, and birds; interdependency in a farming
landscape
Philippe James Thomas1*, Pamela Martin2, Céline Boutin1
1National Wildlife Research Centre, Science & Technology Branch, Ottawa, Ontario, Canada;
*Corresponding Author:
2Science & Technology Branch, Environment Canada, Burlington, Ontario, Canada;
Received 9 June 2011; revised 3 July 2011; accepted 15 July 2011.
ABSTRACT
Changes in farming practices over the second
half of the twentieth century greatly reduced the
extent of natural areas remaining within agri-
cultural landscapes. Field margins and hedge-
rows have recently been recognized as impor-
tant habitat in maintaining wildlife diversity and
proper ecosystem functioning. Ecotones, de-
fined as the transitionary area of vegetation be-
tween w oody plant species and the arable crop,
are an especially important landscape element
for birds and arthropods. In this manu- script,
we aimed to evaluate which hedgerow attribute
was best at predicting avian densities in a con-
ventional and organic farming landscape. Fur-
thermore, we wished to investigate if these
same hedgerow attributes could explain arthr-
opod family density, richness and diversity, and
how these were correlated to avian densities.
An information theory-based multimodel infer-
ence method was used to identify which factors
influenced variability in avian densities. Al-
though not always significant, avian densities
increased with arthropod richness at our study
sites. Ecotone width is the best predictor of
avian densities and arthropod richness while
percent gap is the most important factor if a
manager wishes to increase avian diversity (H’)
in hedgerow habitats. Increasing ecotone width
benefits both avian densities and arthropod
richness that in turn further increases bird
numbers in our farming landscape.
Keywords: Abundance; AIC, Arthropod; Avian;
Diversity; Ecotone; Farming Landscape;
Management; Rich ness
1. INTRODUCTION
Over the last decades, field margins and hedgerow
habitats have been recognized as being important in
maintaining plant and wildlife diversity [1,2]; particu-
larly for birds. With the distinct shift in agricultural
practices that has occurred in both Europe and North
America, away from subsistence farming and towards
large-scale industrial farming [3,4], adjacent hedgerows
and marginal areas have been reduced or eliminated [5].
In Europe where agricultural intensification is marked,
hedgerows comprise one of the most important surviv-
ing semi-natural habitats for avian species [2]. Manag-
ing hedgerow habitats on farmland property is a com-
mon way to enhance local bird populations, general
biodiversity and consequently, ecosystem functioning
[6]. In such circumstances, understanding the relative
importance of the different hedgerow structural attrib-
utes is imperative if we are to implement successful
and cost effective mitigation strategies aimed at in-
creasing, or at least conserving the wildlife diversity
we have left.
Another key impact of changing and intensifying
farming practices on bird populations in North America
has been a reduction in available food resources across
the farmed landscape [7]. Decreasing food resources is
responsible for the decline of a wide range of species
[7]. Consequently, increasing the availability of food is
a common mitigation strategy to promote population
growth [8]. An important component of Agri-Environ-
ment Schemes (AES), implemented in Europe to en-
courage farmers to manage remaining semi-natural
habitat in a sustainable fashion, involves conserving
and creating invertebrate-rich foraging habitat for birds
during the breeding season. Arthropods are especially
important for biodiversity. They form an important part
of the diet of many birds, especially young nestlings.
Predatory invertebrates also have an important function

P. J. Thomas et al. / Open Journal of Ecology 1 (2011) 9-23 10
in agricultural pest management. Uncropped field mar-
gins (or hedgerow habitats) support high invertebrate
populations. As a result, their creation and maintenance
is a key recommendation of AES [9].
Hedgerows and field margins are excellent at pro-
viding birds with appropriate nesting, roosting and
foraging habitats [2,6]. Not only do they fulfill these
essential functions, but they also provide cover for lo-
cal movements and can facilitate longer distance travels
through different landscapes [2,10,11]. However, the
value of these hedgerows to different bird species de-
pends on a number of different factors such as hedge-
row height, width, length, ditch dimensions, number of
snags or number of trees [2,12]. A number of these
factors are species or guild-specific [12]. Therefore, the
task becomes daunting when a landowner wishes to
manage his hedgerows without prior bird identification
knowledge or a strong understanding of avian ecology
and habitat requirements.
The purpose of our study was to evaluate which
hedgerow attribute was best at predicting avian densi-
ties in a conventional and organic farming landscape.
Furthermore, we wished to investigate if these same
hedgerow attributes could explain arthropod family
density, richness and diversity, and how these were
correlated to avian densities. Our results would then allow
us to provide landowners with a simple, stand-alone
hedgerow management strategy that could help in-
crease avian diversity through improved habitat and
food resource management. An information theory-bas-
ed multimodel inference method was used to identify
which factors best explained avian density variance at
organic and conventional farming sites. We hypothe-
sized that similar to other studies, bird densities will be
higher on organic farms since these typically have
greater and higher quality hedgerow habitat. Larger
hedgerows (in length, width and height) should also be
capable of accommodating larger avian populations.
2. METHODS
2.1. Study Area
The study area was situated in the Great Lakes – St.
Lawrence River corridor. It was originally vegetated
with mixed deciduous forest and woodland, characteris-
tic of the Lower Great Lakes/St. Lawrence Plain. It is
now one of the most intensively cultivated and inhabited
parts of Canada. Narrow hedgerows often represent the
only remaining natural habitat in a largely agricultural
landscape, and could therefore be of particular ecologi-
cal importance and mirror the trends we are seeing in
Europe. Woodlots and woody hedgerows remain com-
mon in farmland across much of Peterborough and Vic-
toria counties in southern Ontario (Figure 1). In addition,
this region features an unusually high prevalence of or-
ganic farms; an ideal situation in which we can include
farm management practice when modeling bird commu-
nities in an agricultural environment.
An equal number of hedgerows situated on organic
and conventional farms were chosen within a 60 kilome-
tre span around Peterborough, Ontario (44.25 N, 78.49
W; Figure 1). Organic farms were selected only if certi-
fied by an official certification body and did not use
synthetic fertilizers, pesticides, growth regulators, anti-
biotics, hormones or other additives, or genetically
modified stock. They had been certified for at least three
years. Hedgerows of conventional farms were selected to
match those of organic farms as closely as possible in
terms of location, hedgerow structure, and crop type. In
1999, eight organic and eight conventional sites were
surveyed. In 2000, six organic and six conventional sites
were surveyed. Two conventional farm hedgerows were
surveyed in both years, all others only in one. The 1999
duplicate hedgerows (n = 2) were subsequently dropped
from the analysis to prevent these sites from having an
undue influence on the results.
2.2. A vian Surveys
Bird surveys were conducted three times in the spring
of 1999 and 2000. Spring counts were used as opposed to
fall counts as breeding birds are thought to be most influ-
enced by arthropod abundance in the spring. The inverte-
brate-rich food resource helps ensure nestling growth and
productivity [6]. Data were collected from the last week
of May to the first week of July. Counts began at official
dawn and concluded no later than 10:15 h, and were
restricted to mornings with no precipitation and winds
under 11 km/h, in accordance with the guidelines estab-
lished by Ralph et al. [13]. The number of birds of each
Canada
Ontario
*Ottawa
Peterborough
Canada
Ontario
*Ottawa
Peterborough
Canada
Ontario
*Ottawa
Peterborough
Figure 1. Map of Peterborough, Ontario, Canada. Study area is
represented by square box east of Peterborough.

P. J. Thomas et al. / Open Journal of Ecology 1 (2011) 9-23 11
species seen or heard was recorded in all visits. At each
site, one hedgerow was selected for study. Five-minute
surveys were conducted on three or four 50 m linear
transects along the length of each hedgerow (depending
on hedgerow length), taking care to avoid double-count-
ing birds.
A single field adjacent to the hedgerow was surveyed
at each site. Birds were surveyed at four locations
around the perimeter. Semi-circular point counts [19] of
100 m radius were performed over five minutes. Birds
observed within 5 m of the edge of the cultivated portion
of the field were recorded as being in the field margin,
while others, including those engaged in aerial foraging
over the field, were recorded as being in the field interior
(Figure 2).
2.3. Hedgerow Characterization
A literature search was performed in order to identify
which structural attributes could influence the presence
or absence of birds in field margins and woody hedge-
rows. Hedge characteristics including height (m), length
(m), width (m), ditch presence or absence (1,0), percent
gaps (%), ecotone width (m) and number of trees with a
diameter at breast height (DBH) > 15 cm were identified
as being ecologically important factors [2,12]. These
seven hedgerow metrics were measured in the field. The
final list of factors included in our multivariate analysis
combined all hedgerow metrics measured and farm type
(conventional or organic; binomially coded as 0 or 1
respectively).
2.4. Arthropod Characterization
The same hedgerow parameters that were used for the
avian multivariate analysis were also used to see if any
had a significant influence on total arthropod abundance,
richness and diversity. However, ditch presence or ab-
Figure 2. Schematic diagram (not to scale) summarizing the
bird surveys conducted at each site.
sence was dropped from the analysis because in some
instances (for example: pitfall traps), ditches were not
present at all (all 0 values) so the over dispersed distri-
bution muddied the results. Arthropod species were col-
lected using several techniques. The methodology has
already been reported in Boutin et al. [14] for sticky
traps and sweep nets. Moth survey methodology has
already been reported in Boutin et al. [15]. Arthropod
sampling was conducted during the last two weeks of
June 1999 and 2000 for sticky traps, sweep nets and pit-
fall traps. Moth surveys were sampled from early June to
the end of September 2001. Cereal crops were still green
and succulent during this period allowing us to sample
arthropods when food resources were abundant and fresh.
Because of every technique’s inherent bias in sampling
and because of unequal sample size between each sam-
pling technique (different number of sites were sur-
veyed), arthropods were analysed independently from
one another (ie-sticky trap arthropods were analysed
independently from pitfall traps …).
Sticky traps.—A total of 240 sticky traps (10 per site)
were placed for six days in June 1999 (19 - 24 June 1999)
and five days in June 2000 (25 - 30 June 2000). A total
of 24 sites were surveyed (12 conventional farms, 12
organic farms). Five equidistant points were sampled at
each site (ecotone and centre of woody hedgerow, and
50m in field interior). Sticky traps consisted of yellow,
water resistant cards (10 × 15 cm) staked 1.5 m above
ground level. Arthropods were collected and stored in
alcohol to be later identified to the family level.
Sweep nets.—220 sweep net surveys were conducted
at 22 sites (10 conventional farms, 12 organic farms)
during three days in 1999 (21 - 23 June 1999) and two
days in 2000 (1 - 2 July 2000). Sweep net sampling was
conducted in five, 5m swathes in between sticky traps in
hedgerows and field interior. All arthropods were identi-
fied to the level of family.
Moth surveys.—Sixteen sites (8 conventional farms, 8
organic farms) were surveyed using 2 light traps per site.
A field trap was located 50m from the hedgerow site in
the middle of the crop. Moths were sampled overnight
from June 2001 to September 2001. Each site had a total
sampling effort of 6 trap nights over the season. Each
trap consisted of a 20 L bucket with a funnel fixed in the
mouth and a 1/8 strip of Vapona® (Dichlorvos) in the
bottom. A fluorescent ultraviolet black light was
mounted to the top of the bucket. Samples were col-
lected early in the morning, stored in alcohol and identi-
fied to both the family and species level.
Pitfall traps.—We surveyed arthropods in hedges and
fields using pitfall traps at 10 sites (5 conventional farms,
5 organic farms). Trapping was conducted during the last
week of June 2000, when the wheat crop was green and

P. J. Thomas et al. / Open Journal of Ecology 1 (2011) 9-23 12
immature. At each location, five equidistant sampling
sites were selected along the length of the chosen
hedgerow. Hedge sites were located as close as possible
to the centre of the width of the hedge and field interior
sites were 25 m into the field from the edge of the
hedgerow. At each of these sampling sites, we positioned
a pitfall trap.
Pitfall traps consisted of a one litre plastic container
filled with 500 ml of water and 10 ml of Photoflo, a
photographic cleanser added to reduce surface tension of
the water in the trap. Traps were dug into the soil such
that the lip of the trap was at the surface of the soil; traps
remained open for three days and were collected at that
time. Following collection, arthropod specimens were
labelled in plastic bags and frozen pending identification.
Specimens were identified to the family level.
Common sticky trap, sweep net, moth survey and pit-
fall trapping sites were matched to avian survey sites for
analysis after pooling the data by sampling technique.
2.5. Data Analysis
Bird counts were summed at each site (field, margin
and woody hedgerow), our three spring censuses were
averaged and density was expressed as the number of
birds per hectare (no. birds/ha). T-tests were used to
evaluate differences between conventional and organic
farming sites. Because of a high degree of variation in
bird densities, significance was set at α = 0.1 level. Kol-
mogorov-Smirnov tests and Kernel density plots were
used to confirm the normality of the data. If a Folded
F-test indicated a significant difference in the two vari-
ances, the Satterthwaite method was used to compute the
p-value. If variances were found to be homogenous, the
pooled t statistic was used.
Furthermore, since bird densities were derived from
count data, generalized linear models were employed.
Depending on the distribution of the count data, one can
fit either Negative Binomial Regression Models (NBRM)
or Poisson Regression Models (PRM). PRM models are
however not recommended as they do not take into ac-
count over-dispersion of the data, or in our case, the ex-
tremely high frequency of zero counts [20]. Since
NBRM models tend to under-predict the occurrence of
zero counts, we opted for a zero-inflated version of the
Poisson model (ZIP) to accurately account for the high
frequency of zero counts. The presence of colinearirty
was investigated using variance inflation factors (VIF)
and was found to be non-existent. All statistics were
completed using SAS version 9.2 TS Level 2M0.
Models.—All possible subset of models were tested
for the eight hedgerow factors. By using the information
theoretic model comparison (ITMC) technique, an
Akaike’s Information Criterion (AIC) value for each
model was calculated from the log likelihoods obtained
from fitting the ZIP regressions. In lieu of using the
standard AIC, we used the small-sample bias correction
form (AICc) which has been shown to converge to the
standard AIC value as you increase sample size [21].
The formula to calculate AICc is:
c
K1
AIC2LL2K2K nK1


 




(1)
where: LL = log likelihood, K = # of parameters and n =
sample size.
Since the actual AICc value is less important than the
change in the AICc value between different models, the
difference, or Δi, between the best model (lowest AICc
value) and model i was calculated. The “best” model
will have a delta AICc equal to 0 [21]. This value repre-
sents the information lost if modeli was used instead of
the “best” model. Anderson et al. [17] stipulate that as a
general rule of thumb, if Δi < 2, the models compared
are too similar to be ranked by the AICc value (or Δi) and
the most parsimonious model should be selected. How-
ever, Guthery et al. [18] cautioned that from a biological
standpoint, especially in the field of conservation biol-
ogy, being able to statistically unravel the “best” model
is not the most important result. It is the model’s predic-
tive ability that will determine how it will hold up
against what is happening in “real world” situations.
Thus, it is necessary to cross-validate the models, and
also consider parsimonious models against a stronger
model that includes additional variables. In our situation,
we investigated the top three models ranked according to
their ΔAICc values regardless of whether its ΔAICc ex-
ceeded the 2.0 cut off.
2.6. Diversity Index
Shannon-Diversity index were calculated for every
conventional and organic site using the total number of
birds detected in fields, margins and hedgerows (pooled
species density). Similar to the above AIC analysis,
Shannon-Diversity indexes were analyzed to uncover
which structural hedgerow metric accounted for most of
the variance in the dataset. An identical diversity index
analysis was conducted for pooled sticky trap, pitfall
trap, sweep net and moth survey arthropods independ-
ently but using family level information.
3. RESULTS
3.1. Organic and Conventional Farming
Avian Densities
When considering avian species density (no. birds/ha)
at conventional and organic farms calculated for the

P. J. Thomas et al. / Open Journal of Ecology 1 (2011) 9-23 13
Organic
study period (n = 58 species total), a two-sample t-test
revealed that mean densities are significantly greater on
organic farms (2.79 ± 0.25; x¯ ± SE) when compared to
conventional farms (2.1 ± 0.21; x¯ ± SE) at the α = 0.1
level (two-sample t(24) = –2.04, p = 0.05). It was also
found that average number of different species per site
was higher on organic (20.43 ± 1.2; x¯ ± SE) when
compared to conventional (15.42 ± 1.01; x¯ ± SE) farms
(t(24) = –3.09, p = 0.005).
Table 1 presents the results of a Kruskal-Wallis test
on mean avian densities at conventional (n = 12) and
organic (n = 14) farms. Out of the 58 tested avian spe-
cies, 8 were found to be present in greater numbers on
organic farms at the 0.1 significance level (Table 1).
American goldfinch (Spinus tristis; p = 0.03), Baltimore
oriole (Icterus galbula; p = 0.03) and tree swallows
(Tachycineta bicolor; p = 0.08) were at least twice as
abundant on organic farms. Black-capped chickadee
(Poecile atricapillus; p = 0.001), brown thrush (Toxosto-
ma rufum; p = 0.06) and rose-breasted grosbeak (Pheuc-
ticus ludovicianus; p = 0.04) were at least 5 times more
abundant on organic farms. Finally, blue-winged warbler
(Vermivora pinus; p = 0.09) and house sparrow (Passer
domesticus; p = 0.05) were only detected on organic
farms.
Even if only 14% of the birds were significantly pre-
sent in greater densities at organic sites, the general trend
tends to show a higher abundance of birds on organic
farms when compared to their conventional counterparts
(69% [40/58] of bird species were more abundant on
organic farms).
Table 1. Table showing average avian density (no. birds/ha) at conventional (n = 12) and organic (n = 14) hedgerow, field margin and
field habitats near Peterborough, Ontario, Canada. Mean ± standard deviation as well as the p values from a Kruskall-Wallis test are
presented. N/A indicates that no birds were detected. Shaded p values are significant at the α = 0.1 level.
English Name Scientific Name Conventional
x¯ ± SD x¯ ± SD p
American crow Corvus brachyrhynchos 0.03 ± 0.004 0.05 ± 0.006 0.89
American goldfinch Spinus tristis 0.07 ± 0.006 0.15 ± 0.006 0.03
American kestrel Falco sparverius 0.004 ± 0.0001 N/A 0.28
American robin Turdus migratorius 0.18 ± 0.01 0.22 ± 0.01 0.48
Baltimore oriole Icterus galbula 0.02 ± 0.002 0.05 ± 0.004 0.03
Barn swallow Hirundo rustica 0.13 ± 0.009 0.09 ± 0.007 0.53
Bahama swallow Tachycineta cyaneoviridis 0.02 ± 0.002 0.02 ± 0.003 0.95
Black-capped chickadee Poecile atricapillus 0.02 ± 0.002 0.14 ± 0.01 0.001
Brown-headed cowbird Molothrus ater 0.03 ± 0.003 0.03 ± 0.004 0.84
Blue jay Cyanocitta cristata 0.09 ± 0.008 0.05 ± 0.007 0.19
Bobolink Dolichonyx oryzivorus 0.01 ± 0.002 0.007 ± 0.001 0.70
Brown thrush Toxostoma rufum 0.004 ± 0.002 0.02 ± 0.003 0.06
Blue-winged warbler Vermivora pinus N/A 0.02 ± 0.002 0.09
Cedar waxwing Bombycilla cedrorum 0.11 ± 0.01 0.18 ± 0.02 0.27
Chipping sparrow Spizella passerina 0.09 ± 0.01 0.04 ± 0.004 0.38
Cliff swallow Petrochelidon pyrrhonota N/A 0.002 ± 0.0005 0.36
Common grackle Quiscalus quiscula 0.03 ± 0.004 0.05 ± 0.007 0.79
Common yellowthroat Geothlypis trichas 0.004 ± 0.0001 0.01 ± 0.0009 0.58
Chestnut-sided warbler Dendroica pensylvanica 0.01 ± 0.0001 0.002 ± 0.0001 0.87
Downy woodpecker Picoides pubescens 0.02 ± 0.002 0.02 ± 0.002 0.76
Eastern bluebird Sialia sialis N/A 0.02 ± 0.008 0.18
Eastern kingbird Tyrannus tyrannus 0.08 ± 0.005 0.06 ± 0.004 0.55
Eastern meadowlark Sturnella magna 0.004 ± 0.001 0.002 ± 0.0006 0.87
Eastern phoebe Sayornis phoebe 0.006 ± 0.001 0.01 ± 0.00 0.53
Eastern wood-pewee Contopus virens 0.01 ± 0.003 N/A 0.12
European starling Sturnus vulgaris 0.09 ± 0.01 0.10 ± 0.01 0.98
Great crested flycatcher Myiarchus crinitus 0.008 ± 0.002 0.02 ± 0.003 0.46
Gray catbird Dumetella carolinensis 0.03 ± 0.004 0.03 ± 0.002 0.59
Grasshopper sparrow Ammodramus savannarum N/A 0.002 ± 0.0001 0.36
Hairy woodpecker Picoides villosus 0.004 ± 0.001 0.004 ± 0.0009 0.91
Horned lark Eremophila alpestris 0.01 ± 0.0082 0.04 ± 0.008 0.55

P. J. Thomas et al. / Open Journal of Ecology 1 (2011) 9-23 14
House sparrow Passer domesticus N/A 0.01 ± 0.002 0.05
House wren Troglodytes aedon 0.01 ± 0.003 0.02 ± 0.002 0.58
Indigo bunting Passerina cyanea 0.10 ± 0.01 0.08 ± 0.007 0.73
Killdeer Charadrius vociferus 0.009 ± 0.002 0.03 ± 0.005 0.18
Least flycatcher Empidonax minimus N/A 0.006 ± 0.001 0.18
Mourning dove Zenaida macroura 0.03 ± 0.009 0.08 ± 0.02 0.23
Mourning warbler Oporornis philadelphia 0.004 ± 0.0001 N/A 0.12
Northern cardinal Cardinalis cardinalis 0.002 ± 0.0006 0.02 ± 0.002 0.17
Northern flicker Colaptes auratus 0.02 ± 0.003 0.03 ± 0.003 0.60
Pine warbler Dendroica pinus N/A 0.002 ± 0.001 0.36
Purple martin Progne subis 0.009 ± 0.0001 N/A 0.28
Rose-breasted grosbeak Pheucticus ludovicianus 0.002 ± 0.0006 0.09 ± 0.02 0.04
Red-eyed vireo Vireo olivaceus 0.02 ± 0.003 0.03 ± 0.002 0.33
Red-headed woodpecker Melanerpes erythrocephalus N/A 0.006 ± 0.0001 0.36
Rock pigeon Columba livia N/A 0.004 ± 0.0009 0.36
Red-tailed hawk Buteo jamaicensis 0.002 ± 0.0006 0.004 ± 0.0009 0.96
Red-winged blackbird Agelaius phoeniceus 0.17 ± 0.02 0.14 ± 0.02 0.63
Savannah sparrow Passerculus sandwichensis 0.20 ± 0.02 0.25 ± 0.02 0.23
Scarlet tanager Piranga olivacea 0.002 ± 0.0001 N/A 0.28
Song sparrow Melospiza melodia 0.26 ± 0.02 0.28 ± 0.01 0.66
Tree swallow Tachycineta bicolor 0.04 ± 0.004 0.11 ± 0.01 0.08
Turkey vulture Cathartes aura 0.01 ± 0.002 0.004 ± 0.0008 0.43
Vesper sparrow Pooecetes gramineus 0.12 ± 0.007 0.15 ± 0.01 0.86
Warbling vireo Vireo gilvus 0.006 ± 0.0001 N/A 0.28
White-breasted nuthatch Sitta carolinensis N/A 0.02 ± 0.0001 0.36
Wild turkey Meleagris gallopavo N/A 0.002 ± 0.0001 0.36
Yellow warbler Dendroica petechia 0.02 ± 0.005 0.02 ± 0.003 0.26
3.2. A vian Density Models
An AIC predicting avian density (no. birds/ha) from a
combination of hedge length (m), hedge width (m),
hedge height (m), no. trees > 15 cm DBH, percent gaps
(%), farm type, ditch presence or absence (1, 0) and
ecotone width (m) revealed that ecotone width (m) alone
best accounted for the majority of the variance in our
avian density dataset (Table 2). This model was ranked
4th using the ΔAICc value, but ranked first because of its
parsimony (see Data Analysis subsection of the Meth-
ods), ie- it had the fewest number of parameters in the
model while having a ΔAICc < 2. The R2 for the best
model is equal to 0.24.
A closer look at ecotone width data revealed
non-normality and data transformations failed to help
meet this assumption. Therefore, a Kruskal-Wallis test
was used to determine if ecotone width differed at or-
ganic and conventional sites. Organic farms (1.91 ± 0.15;
x¯ ± SE) had significantly higher ecotone width than
conventional farms (1.5 ± 0.08; x¯ ± SE) at the α = 0.1
level (Chi-square = 2.73, df = 1, p = 0.09).
Because farm type did not enter our best AIC model,
regressing avian density (no. birds/ha) as a function of
ecotone width (m) was conducted on the pooled conven-
tional and organic sites; it revealed a significant rela-
tionship (F(1,24) = 7.64, p = 0.01). As ecotone width in-
creases, avian density increases (Figure 3).
3.3. Organic and Conventional Farming
Avian Diversity
Mean Shannon-Wiener Index (H’) was calculated at
organic and conventional farming sites. A two-sample
t-test on H’ revealed that organic farming avian Shannon
index was significantly higher (2.56 ± 0.07; x¯ ± SE)
than conventional farming sites (2.36 ± 0.06; x¯ ± SE) at
the α = 0.1 level (two-sample t(24) = –1.89, p = 0.07).
3.4. A vian Diversity Models
Identical to the above avian density analysis, an AIC
was used to uncover which hedgerow parameter best
explained the variance present in our H’ results. An AIC
predicting Shannon-Wiener index (H’) revealed that the
parsimonious model combining ecotone width (m), per-
cent gap (%) and farm type best accounted for the ma-
jority of the variance in our avian diversity dataset (Ta-
ble 3). This model was ranked 5th using the ΔAICc value,
but ranked first because of its parsimony. This model
had a ΔAICc < 2 and an R2 = 0.47.
A
n ANOVA of our parsimonious H’ model [H’=

P. J. Thomas et al. / Open Journal of Ecology 1 (2011) 9-23 15
Table 2. Summary AICc statistics for top five candidate regression models from all possible combinations of 8 hedgerow factors.
Models predict avian density (no birds/ha) at conventional (n = 12) and organic (n = 14) farming sites (within a radius of 1000 m) in
Peterborough, Ontario. Models are presented from lowest Δ AICc value to highest Δ AICc value. There are a total of 1710 observa-
tions (n) in each model. Ranked model represents the best model as advised by Guthery et al. [18]. RSS represents the residual sum
of squares, or the discrepancy between the data and the estimated model; the smaller the RSS, the better the fit.
Model # Hedge length (m) Hedge width (m) Hedge height (m) # trees >15cm DBH Percent gaps (%) Farm type Ditch length (m) Ecotone width (m)
AICc ΔAICcRSS R2 Ranked
Model
1    –10.30 0 12.86 0.36 4
2   –10.21 0.09 13.94 0.31 2
3
   –10.08 0.22 12.97 0.36 5
4  –9.78 0.52 15.31 0.24 1
5   –9.53 0.77 14.31 0.29 3
Ecotone width
(
m
)
Avian densit
y
(
no. birds/ha
)
Figure 3. Regression of avian density (no. birds/ha) as a function of ecotone width (m) at conventional (n = 12) and organic (n = 14)
sites. An ANOVA revealed a significant relationship (F(1,24) = 7.64, p = 0.01) with an R2 = 0.25.
0.15 (farm type) - 0.01(percent gap) + 0.09(ecotone
width) + 2.24] reveals significance (F(3,22) = 6.49, p =
0.003). However, only percent gap is significantly dif-
ferent than zero (t(1) = –3.36, p = 0.003). Even if farm
type entered our best model, the above ANOVA revealed
that it was not a significant predictor when considered
alone. Therefore, H’ was regressed as a function of per-
cent gaps (%) only. The regression revealed a significant
negative relationship (F(1,24) = 10.11, p = 0.004) with an
R2 = 0.3. As one increases the percent gap in a hedgerow,
avian diversity decreases (Figure 4).
3.5. Birds and Bugs
Unique in our study, it was interesting to calculate if
arthropod abundance, richness or diversity influenced
avian densities. Linear regressions of avian densities as a
function of arthropod abundance, richness and diversity
revealed that arthropods collected by pitfall traps were

P. J. Thomas et al. / Open Journal of Ecology 1 (2011) 9-23 16
Table 3. Summary AICc statistics for top five candidate regression models from all possible combinations of 8 hedgerow factors.
Models predict Shannon-Wiener index (H’) at conventional (n = 12) and organic (n = 14) farming sites (within a radius of 1000 m) in
Peterborough, Ontario. Models are presented from lowest Δ AICc value to highest Δ AICc value. There are a total of 1710 observa-
tions (n) in each model. Ranked model represents the best model as advised by Guthery et al. [18]. RSS represents the residual sum
of squares, or the discrepancy between the data and the estimated model; the smaller the RSS, the better the fit.
Model #
Hedge length (m)
Hedge width (m)
Hedge height (m)
# trees >15cm
DBH
Percent gaps (%)
Farm type
Ditch length (m)
Ecotone width (m)
AICc ΔAICc RSS R2 Ranked
Model
1      -77.47 0 0.83 0.58 4
2     -76.88 0.59 0.92 0.53 2
3       -76.02 1.45 0.82 0.58 5
4
    -75.88 1.59 0.96 0.51 3
5    -75.68 1.79 1.04 0.47 1
% gap
H’
Figure 4. Regression of Shannon-Wiener Index (H’) as a function of percent gap (%) at conventional (n = 12) and organic (n = 14)
sites. An ANOVA revealed a significant relationship (F(1,24) = 10.11, p = 0.004) with an R2 = 0.3.
Table 4. Linear regressions of avian densities as a function of arthropod abundance, richness and diversity for arthropods sampled by
sticky trap, pitfall trap, sweep netting and moth surveys. Both family and species of moths were tested to contrast the difference be-
tween family and species level results. (+) indicates a positive trend; (–) indicates a negative trend. Shaded p values are significant at
the 0.1 significance level.
Abundance Richness Diversity Arthropods sampled
by: DF F P DF F P DF F P
Sticky Trap 1/22 0.37 0.55 (+) 1/22 1.04 0.32 (+) 1/22 1.35 0.26 (–)
Pitfall Trap 1/8 1.95 0.2 (+) 1/8 7.35 0.03 (+) 1/8 6.04 0.04 (+)
Sweep netting 1/20 3.72 0.07 (+) 1/20 0.18 0.67 (+) 1/20 2.87 0.11 (–)
Moth family 1/14 1.37 0.26 (–) 1/14 0.13 0.73 (+) 1/14 0.11 0.75 (+)
Moth species - - - 1/14 4.01 0.07 (+) 1/14 0.41 0.53 (–)

P. J. Thomas et al. / Open Journal of Ecology 1 (2011) 9-23 17
most important to avian densities (Table 4). Furthermore,
arthropod richness had the strongest p-values, was sig-
nificant at the family level for pitfall traps, and at the
species level for moths and was the only measure that
consistently showed a positive trend (albeit, not always
significant). Therefore, given the results, arthropod
richness is selected as the strongest predictor of avian
densities.
Table 5 presents the results of a comparison of ar-
thropod family richness at conventional and organic
farming sites for those sampled by sticky trap, pitfall
trap, sweep netting and moth surveys. In no instance did
the richness at conventional and organic sites differ.
3.6. Arthropod Richness Models
Similar to the avian models, an AIC predicting sticky
trap, pitfall trap, sweep netting and moth survey arthro-
pod richness (total no. families) from a combination of
hedge length (m), hedge width (m), hedge height (m), no.
trees > 15 cm DBH, percent gaps (%), farm type, and
ecotone width (m) revealed that the only significant
model was for sweep netting insects (Table 6). The top
parsimonious sweep netting model combined 2 parame-
ters, hedge length (m) and ecotone width (m). This
model was ranked 1st using the ΔAICc value and was
also the most parsimonious model.
An ANOVA of our parsimonious sweep netting ar-
thropod richness model [sweep family richness = –0.09
(hedge length) + 2.39 (ecotone width) + 37.65] reveals
significance (F(2,19) = 4.17, p = 0.03) at the α = 0.1 level.
The R2 value of the model is 0.31. Both factors were
significant in the model (with p = 0.04) so they were
graphed as a function of each other’s residuals to illus-
trate the relationship.
Regressing pooled arthropod richness residuals as a
function of ecotone width (m) on the pooled conven-
tional and organic sites revealed a significant and posi-
tive relationship. As ecotone width increases, sweep net-
ting arthropod richness increases (Figure 5a). On the
other hand, as hedgerow length increases, sweep netting
arthropod richness decreases (Figure 5b). Both R2 val-
ues were equal at roughly 0.2.
4. DISCUSSION
Our best models revealed some important factors in
understanding the dynamic links between habitat, ar-
thropod richness and avian density and diversity in an
organic and conventional farming landscape. High ar-
thropod family richness translates in higher avian densi-
ties. Ecotone width is the best predictor of avian densi-
ties and is an important factor influencing arthropod
richness at conventional and organic farming sites while
percent gap in hedgerows is the most important predictor
of avian diversity (H’).
4.1. On Defining Ecotones
In our study, we have used the term “ecotone” to de-
Table 5. Species richness comparisons for arthropods sampled by sticky traps, pitfall traps, sweep netting and moth surveys. Mean ±
standard error as well as the statistical results of a T-test is presented.
Conventional Organic
Arthropods sampled by: Mean ± SE Mean ± SE DF t P
Sticky Trap 32.82 ± 1.72 32.31 ± 1.56 22 0.22 0.83
Pitfall Trap 15.2 ± 2.35 16.0 ± 2.77 8 –0.22 0.83
Sweep netting 23.0 ± 1.19 24.67 ± 1.6 20 –0.81 0.43
Moth Surveys 8.13 ± 0.35 8.5 ± 0.63 14 –0.52 0.61
Table 6. Multiple regression results of arthropod richness as a function of habitat parameters selected by AIC (only top models were
tested for every sampling technique). Shaded p value is significant.
AIC Model Parameter
Arthropods sampled by:
Hedge length (m) Hedge width (m) Hedge height (m) # trees >15cm DBH Percent gaps (%) Farm type Ecotone width (m)
DF F Pr > F R2
Sticky Trap  1/22 0.53 0.48 0.02
Pitfall Trap        7/2 6.44 0.14 0.96
Sweep netting
  2/19 4.17 0.03 0.31
Moth Surveys  1/14 1.63 0.22 0.1

P. J. Thomas et al. / Open Journal of Ecology 1 (2011) 9-23 18
fine the transitionary area of vegetation between woody
plant species (characteristic of the centre of the hedge-
row) and the arable crop. Ecotone is therefore consid-
ered a synonym of the popularly used term “field mar-
gin”.
We have decided to stray from using “field margin” as
we felt “ecotone” was more appropriate. The definition
of ecotone includes certain ecological processes and
assumptions that are otherwise missed when character-
ising edge habitat as “field margin”. According to the
Encyclopaedia Britannica, “ecotone” is defined as the
“area of vegetation between two different plant commu-
nities, such as forest and grassland. It has some of the
characteristics of each bordering community and often
contains species not found in the overlapping communi-
ties” [22].
Our data supports this definition as a higher density
and diversity of organisms (arthropods and birds) were
present with increasingly large ecotone width. Even if
the popular use of the term “ecotone” usually applies to
the area of vegetation transition on a larger geographical
scale, we felt it was as valid to use it at the smaller spa-
tial scale our research was concerned with.
4.2. Importance of Ecotones to Bird
Abundance
Many of the breeding avian species observed used
hedgerows for nesting, while foraging along ecotones.
Very few used crop fields. In fact, a study by Douglas et
al. [6] discussed the importance of maintaining and im-
proving ecotones as foraging habitat for farmland birds.
Others [23,24] stress the importance of maintaining nar-
row habitat strips along the perimeter of agricultural
areas in order to maintain a high abundance of bird spe-
cies. To further improve avian densities in hedgerow
habitat, in Europe, some farms have provided pesticide
exclusion strips around the perimeter of fields, resulting
in a noticeable increase in wildlife numbers with only a
negligible decrease in arable area [25,26]. Twenty-six of
44 European countries have instituted agri-environment
schemes that provide farmers with financial compensa-
tion for loss of income associated with efforts to ecol-
ogically improve their land [29]. As studies on the use of
hedgerow and ecotone habitat by birds at conventional
and organic farms have shown similar results across re-
gions, it is expected that such measures would also be
beneficial in North America.
Conover et al. [16] found that bird abundance was up
to 2 times greater in wider ecotones. Our study supports
his findings. Similar to our results, he also found that
bird diversity was not as influenced by ecotone width.
Common with the recommendations brought forward by
our findings, the authors recommend implementing
wider field borders (or ecotones) that contribute substan-
tially to grassland bird conservation measures in agri-
cultural landscapes.
The importance of ecotones cannot be understated.
These field borders benefit avian populations year-round
by providing nesting, foraging, roosting and movement
corridors for many species [30-32]. Wider herbaceous
ecotones adjacent to woody hedgerows further enhance
avian benefits where bird abundance are typically ele-
vated such as was the case at our avian-rich Peterbor-
ough sites. Ecotone width is a particularly important
factor as it most likely mitigates the vulnerability of cer-
tain avian species to edge effects [33,34]. Wider
ecotones also provide habitat farther from wooded areas
which can benefit grassland birds that select for edges
and those that avoid this habitat type [35].
We have presented evidence that there exist differ-
ences in avian densities and richness at conventional and
organic farms supporting findings presented by Shuttler
et al. [27]. Since ecotone width was also significantly
higher on organic farms, we found convincing support
that greater avian densities might not be correlated to
agricultural management as much as ecotone width. In
fact, agricultural management did not enter our best
model and this could be attributed to the nature of the
landscape.
In a paper published by Chamberlain et al. [28], the
authors found that on average, 25% more birds were
found on organic farms but that only some individual
species were significantly more abundant. In a North
American context, especially at our study area (Peter-
borough, Ontario), few recently established (3 - 8 years
old) organic farms were interspersed amongst
well-established conventional farms. As a result, organi-
cally managed farmland differed only marginally from
their conventional counterparts. Thus, if habitat is the
limiting avian density factor, then one would not expect
significantly different bird densities in conventional and
organic hedgerow and ecotone habitats. A similar situa-
tion was observed with arable weeds [36] and butterflies
[37]. The outcome of these studies varied according to
the landscape on a broader context. The differences in
biodiversity between organic and conventional farmland
were greater in more homogeneous landscapes. Organic
farm management may recreate some of this heterogene-
ity in the more intensively farmed (ie- more homogenous)
areas [37] and would therefore favour and increase bio-
diversity in organically managed farmland. Therefore, as
a result of the already heterogeneous landscape, agricul-
tural management was not an important predictor of
vian densities, but finer habi at features such as ecotone at

P. J. Thomas et al. / Open Journal of Ecology 1 (2011) 9-23 19
R
2
= 0.1863
-10
-8
-6
-4
-2
0
2
4
6
8
10
12
0 0.51 1.52 2.533.54 4.5
Ecotone Wi dth (m)
Residuals
A
(a)
R
2
= 0.19 71
-10
-8
-6
-4
-2
0
2
4
6
8
050100 150200 250 300
Hedgerow Length (m )
Residuals
B
(b)
Figure 5. Partial regressions of the residuals of a multiple regression of arthropod family richness as a function of ecotone width (A)
and hedgerow length (B). An ANOVA revealed a significant relationship (F(2,19) = 4.17, p = 0.03) at the α = 0.1 level. The R2 value of
the full model is 0.31. Both factors were significant in the model (with p = 0.04).
width were found to be of greater importance.
4.3. Importance of Ecotones to Arthropod
Richness
Arthropods represent a key functional component of
agricultural ecosystems [38]. Their importance as pests,
food resources for birds and their own innate conserva-
tion value have been documented in the past [41,42,43].
Key ecosystem functions such as nutrient cycling, bio-
control and pollination would be hindered by a decrease
or absence of arthropods in agricultural ecosystems [41].
An important cause of decline of arthropod populations

P. J. Thomas et al. / Open Journal of Ecology 1 (2011) 9-23 20
in hedgerow and ecotone habitats involves structural
changes in the plant community as a whole through cut-
ting, grazing, fertilizer and pesticide applications [42].
A study by Woodcock et al. [44] found that ecotones
receiving either no management or minimal cutting sup-
ported greater abundances and species richness of bee-
tles. Subtle modifications of conventional management
practices (such as discontinuing the use of NPK fertiliz-
ers and maintaining grazing) were also shown to be
beneficial to beetle populations [44]. Others such as
Merckx et al. [48] found that wider ecotones positively
affected abundance of mobile arthropod species such as
moths. Clearly, floristic and structural attributes of
ecotones influence arthropod abundance and should be
managed accordingly to sustain proper ecosystem func-
tioning.
Wider ecotones in arable landscapes affect groups of
arthropods in different ways. Unfortunately, these rela-
tionships are often complex and should be considered
individually (in different arthropod species, or groups of
species such as families). However, wider margin habitat
increases the abundance of certain insects and changes
the species composition in the ecotone itself [45,46].
Few studies have attempted to investigate the effects of
ecotone width on invertebrate density and diversity.
Wider margins may support higher plant diversity [47]
which in turn favours particular groups of arthropods
who feed on nectar sources for-example [48]. It could
also be that wider margins with increased floral diversity
provides better quality breeding habitat for arthropods
whose larvae are phytophageous [48]. The greater area
resulting from wider ecotones could even act as a buffer
against agrochemical drift that negatively impacts in-
sects.
4.4. Hedgerow Length and Gaps
Similar to our results, Conover et al. [16] detected no
effect of ecotone width on avian diversity during their
study. The authors speculated that the lack of a positive
relationship between border width and avian diversity
was most likely influenced by the scarcity of non-crop
habitat at the landscape scale. In the context of our study
area, non-crop habitats were diverse and represented the
majority of the landscape cover. As a consequence, birds
in both conventional and organic farming sites were di-
verse (with high H’ values over 2).
Our best model revealed that percentage hedgerow
gap was the best predictor of avian diversity (H’) at our
26 farming sites. Therefore, our results support the the-
ory that increasing hedgerow fragmentation (or gaps) in
a dominantly forested landscape decreases avian diver-
sity. This decrease could be due to an increase in nest
predators such as raccoons (Procyon lotor) or brood
parasitism by species such as the cowbird [49]. With
increasing hedgerow gaps, avian diversity decreases
through increased nest predation and brood parasitism;
unlike the trend reported by Bowen et al. [50] where the
creation of small canopy gaps increased local bird spe-
cies richness.
It was surprising that longer hedgerows supported
lower arthropod richness. This could be due to a diluting
effect but the interpretation is still subject to criticism. In
fact, Ricci et al. [40] documented that hedgerow length
was not a significant predictor of moth abundance in an
agricultural landscape and the trend was opposite with
each sampling year. It is mentioned that this erratic result
could be due to insecticide treatments that affect the
presence or absence of enemies and/or the fact that
longer hedgerows support a greater number of natural
insect enemies such as parasitoids or predators. Our
study lacks the data to support such claims.
4.5. Bugs and Birds
We have documented 8 avian species that were pre-
sent in higher densities at organic farms (see results).
These bird species were for the most part, insectivores
and seed eaters that favour forested, early successional
and ecotone areas of the landscape [50]. Contrary to re-
sults presented by Parish et al. [12], the abundance of the
majority of our avian species was not strongly influ-
enced by hedgerow height, width and length. However,
similar to his findings, ecotone width was important for
the smaller insectivores and seed eating birds, or the 8
species present in higher densities on organic farms.
Furthermore, the presence of wider ecotones altered
bird use of row-crop fields in a study by Conover et al.
[32]. The authors observed increased sparrow (Ember-
izidae) abundance in agricultural fields near wide
ecotones. This was most likely a result from enhanced
waste grain foraging opportunities. Similar to their study,
house sparrows were more abundant in organically
managed farmland with wider ecotones.
The positive impacts of higher arthropod richness on
bird populations favouring ecotones have been docu-
mented by others such as Douglas et al. [6]. Indeed,
maintaining high arthropod-rich ecotones is a core com-
ponent of Agri-Environment Schemes. It has been stipu-
lated that their value is limited in late summer [6], but
the benefits to foraging birds during the breeding season
is crucial to the birds’ reproductive success and ensures
healthy ecosystem functioning in the long run.
In general, agricultural management options that
promote floral diversity will automatically stimulate
arthropod diversity [51]. A rich variety of Angiospermae
provides larval foodstuffs and structural diversity that
benefits a wide range of invertebrates [51]. Insects that

P. J. Thomas et al. / Open Journal of Ecology 1 (2011) 9-23 21
thrive on wildflowers and naturally regenerated vegeta-
tion will enhance the reproductive success of the many
birds that prey on these arthropods. Encouraging a di-
verse insect fauna will not automatically address the
food requirements of all farmland birds, but it at least
provides a strategic angle that could be used to mitigate
the decline of many aerial insectivores that frequent ar-
able land.
Favouring a higher richness of arthropods through
ecotone management may increase the abundance and
distribution of avian species who select for arthro-
pod-rich habitats as a source of food [45]. At the field
scale during the summer months (or the breeding season),
many bird species nest at the base of woody hedgerows
and will forage in nearby ecotonal areas. By increasing
arthropod richness (and abundance) in margin areas (or
ecotones), one should increase reproductive success by
allowing an insectivorous bird to successfully forage for
bugs, using the least amount of energy. Arthropod-rich
ecotones thus provide more “bang for your buck”.
4.6. Study Limitations
Although we have documented some interesting
trends and some strong significant results, our study is
not without any limitations. First, it would have been
appropriate to sample pitfall traps, sticky traps, sweep
net surveys and moth surveys at every single avian site
in order to increase our sample size and subsequent
power. A carefully tailored multi-year study would have
helped reduce some of the variability in the dataset. Also,
identifying all arthropods to species level would have
helped keep the sample size high and would have in-
creased our statistical strength. For-example, 313 known
moth species were part of our dataset. Rolling the infor-
mation up to family level reduced our sample size to
only 12. Clearly, in Table 4, this reduction explains why
the p-value drops from 0.73 when moth family richness
is calculated as opposed to moth species richness where
the p-value becomes an impressive 0.07. Identifying all
our arthropods to species level would have most likely
helped us in uncovering stronger relationships.
4.7. Implications for Management
Common to the recommendations of Vickery et al.
[51], we continue to stress the importance of creating,
maintaining and improving ecotones (field margins) as a
cost-effective way of providing ample resources to dif-
ferent taxa at every trophic level. Field margins should
be managed with adjacent woody hedgerows in a way to
create a heterogeneous habitat structure capable of sup-
porting a wide range of needs in different species such as
nesting opportunities (for birds), refuge and food supply
(for arthropods). Increasing ecotone width and keeping
woody hedgerow habitats as gapless as possible is a
good strategy to ensure proper agroecosystem health and
functioning.
Our findings are important in that they further our
knowledge on the relationships amongst different trophic
levels in two different ecotone management systems
(organic and conventional farming). In our case, agri-
cultural management did not have a strong effect on
these relationships but finer habitat attributes (such as
ecotone width and percent hedgerow gap) clearly influ-
enced prey-predator dynamics.
5. ACKNOWLEDGEMENTS
We would like to thank all the landowners who permitted access to
their properties and provided information about their farming practices.
J. Duffe and A. Baril conducted the GIS analysis of landscape habitat
variables. M. Gaubehr, D. Kirk and K. Lindsay conducted preliminary
statistical analysis and provided valuable advice. This research was
funded by Environment Canada.
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