The response of ground and bark foraging insectivorous birds across an urban–forest gradient

Landscape and Urban Planning 93 (2009) 142–150

Contents lists available at ScienceDirect

Landscape and Urban Planning journal homepage: www.elsevier.com/locate/landurbplan

The response of ground and bark foraging insectivorous birds across an urban–forest gradient Samuel T. Trollope, John G. White ∗ , Raylene Cooke School of Life and Environmental Sciences, Deakin University, 221 Burwood Highway, Burwood, Victoria 3125, Australia

a r t i c l e

i n f o

Article history: Received 14 January 2009 Received in revised form 20 April 2009 Accepted 29 June 2009 Available online 24 July 2009 Keywords: Habitat fragmentation Connectivity Isolation Roads Landscape

a b s t r a c t This paper assesses the response of four common species of forest dependant insectivorous birds to an urban–forest gradient. The presence or absence was recorded for each species in landscapes that varied in landscape and site level attributes. Landscapes were classified into three categories based on their level of urbanisation. Broad comparisons across the landscapes were used to determine species specific response to increasing levels of urbanisation. Site level attributes were modelled to predict the patch occupancy for each species in each of the landscape types. Two broad trends were identified: the superb fairy wren (Malurus cyaneus) and white-browed scrubwren (Sericornis frontalis) displayed a tolerance to urbanisation and the eastern yellow robin (Eosaltrica australis) and white throated treecreeper (Cormobates leucophaeus) demonstrated a threshold response to urbanisation. The density of roads (−ve) and the extent of tree cover (+ve) in a landscape were highly correlated with the occurrence of urban sensitive species while at the site level the density of roads and density of rivers were the strongest contributors to their presence. The marked differences in the isolation and connectivity of patches where the threshold for urban sensitive species ceases are the likely contributors to their decline and sensitivity to suburban habitats. Conservation and management of urban sensitive species is largely dependant on the way urban development is managed. Of critical importance is careful planning in urban-fringe environments. © 2009 Elsevier B.V. All rights reserved.

1. Introduction Habitat loss and fragmentation caused by anthropogenic influences have been identified as the primary factors responsible for the global decline in biodiversity (Saunders et al., 1991; Garden et al., 2006). Urbanisation is characterised by a suite of anthropogenic processes that dramatically alter the structure and composition of natural ecosystems through the clearing of native vegetation and its transformation into an environment dominated by residential properties, commercial buildings and other impervious structures (such as roads and paved surfaces) (Blair, 1996). Furthermore, remnant vegetation becomes heavily fragmented and isolated within the surrounding urban matrix (Saunders et al., 1991; Smith and Wachob, 2006). Consequently, urban ecology has been a major research focus worldwide, especially given the expected growth of the human population and the subsequent expansion of urban developments (Rebele, 1994). Urban ecology has been approached from a number of different perspectives including the application of habitat island theory (Fernández-Juricic and Jokimäki, 2001; Palmer et al., 2008), long-

∗ Corresponding author. Tel.: +61 3 9251 7625; fax: +61 3 9251 7626. E-mail address: [email protected] (J.G. White). 0169-2046/$ – see front matter © 2009 Elsevier B.V. All rights reserved. doi:10.1016/j.landurbplan.2009.06.013

term temporal studies (e.g. Tait et al., 2005) and comparisons of community composition between urban areas and non-urban areas (e.g. Beck and Heinsohn, 2006). The use of urban gradients to examine community composition between urban and non-urban areas has been popular as the process of urbanisation produces a gradient of environmental change appearing as a dense, highly modified and developed core, surrounded by asymmetrical bands of diminishing development. A set of anthropogenic pressures at varying intensities can be quantified along the gradient and used to study the effects on ecological systems such as community composition and function (McDonnell and Pickett, 1990). The components used to quantify the intensity of urban development vary between each study as the measure, or set of measures, depends on the nature and objectives of the study (Hahs and McDonnell, 2006). Birds have been common taxa to investigate urban systems as ecologically they are highly diverse and occupy a wide range of habitats (Sandström et al., 2006). As urbanisation intensifies, urban bird communities typically experience a decline in species richness and become more vulnerable to the invasion of exotic species which dominate the environment (Clergeau et al., 1998; Jökimäki and Kaisanlahti-Jökimäki, 2003; Fraterrigo and Wiens, 2005; White et al., 2005), usually at the expense of forest dependant species (Crooks et al., 2004; Palmer et al., 2008). This process of ‘biotic homogenisation’ has been observed throughout North America

S.T. Trollope et al. / Landscape and Urban Planning 93 (2009) 142–150

(Blair, 1996; Crooks et al., 2004), Europe (Clergeau et al., 1998; Jökimäki and Kaisanlahti-Jökimäki, 2003), Asia (Lim and Sodhi, 2004; Soh et al., 2006) and Australia (White et al., 2005). One of the most notable impacts of urbanisation has been the disproportionate effect within different feeding guilds. Insectivores have consistently declined and are often the most heavily impacted (Clergeau et al., 1998; Rottenborn, 1999; Lim and Sodhi, 2004; Fraterrigo and Wiens, 2005; White et al., 2005). While few Australian studies have examined this trend more intently in urban landscapes, insights have emerged from research in agricultural landscapes that have documented similar declines in insectivorous birds (Zanette et al., 2000). It has been proposed that fragment size and insect biomass drive the abundance and diversity of insectivorous birds. Major et al. (2001) demonstrated that insectivores displayed a strong preference for remnants larger than 200 ha. Remnant size has also been shown to have a significant relationship with forest dependant insectivores, especially understorey species which displayed the greatest sensitivity (Watson et al., 2002). The trend has therefore been to use broad scale attributes at the landscape and site level to explain aspects of insectivore ecology that may achieve a better understanding as to why they have declined in fragmented systems. This approach has largely been applied in agricultural landscapes where woodland remnants have been fragmented and isolated, however, few studies have used similar approaches in urban environments. This paper therefore aims to determine the response of four ground and bark–trunk foraging insectivorous bird species that are considered common throughout south eastern Australia across a gradient from suburban to forest. The target species are the eastern yellow robin (Eosaltrica australis), superb fairy wren (Malurus cyaneus), white-browed scrubwren (Sericornis frontalis) and the white throated treecreeper (Cormobates leucophaeus). These species forage primarily on or near the ground (Ambrose and Davies, 1989; Cale, 1994; Hodgson et al., 2006) with the exception of the white throated treecreeper which is a bark and trunk forager (Lindenmayer et al., 2007). They are also considered forest dependant species that are unable to utilize the streetscape component of urban environments (White et al., 2005). The use of common species as a model allows for the detection of the target species at a reasonable number of sites, and as such increases the chance of gaining meaningful data. Specifically this paper aims to: 1. Determine the response of ground and bark foraging insectivorous birds across an urban–forest gradient. 2. Determine the landscape and site level components that influence the distribution of ground foraging insectivorous birds. 3. Develop conservation management strategies for insectivorous birds across urban–forest gradients. 2. Methods 2.1. Study area This study encompassed the suburban, urban-fringe and forested areas of greater Melbourne, Victoria, Australia (37◦ 50 S, 44◦ 58 E). In 2006, Melbourne’s population was 3.74 million and has experienced the largest population growth of all Australian capital cities since 2001 (Australian Bureau of Statistics, 2007). Nine 10 km by 10 km study landscapes were selected to reflect a gradient of urbanisation based on the proportion of dense tree cover (Fig. 1). Dense tree cover was derived from 1:25 000 scale GIS mapping of tree cover under license from the Department of Sustainability and Environment (DSE). The layer displays the presence/absence of woody vegetation greater than 2 m in height and defines dense tree cover as having foliage cover greater than 80%.

143

Fig. 1. Study area including location of suburban (dotted boxes), urban-fringe (dashed boxes) and forest landscapes (solid boxes). ! denotes Melbourne’s CBD. Rivers and water bodies are represented in dark grey and the extent of dense tree cover is represented in light grey.

Landscapes were classified as suburban (n = 3), urban-fringe (n = 3) (urban-fringe being the interface between suburban and continuous forest) or forest (n = 3) (Fig. 1). Dense tree cover contributed between 90% and 100% of forested landscapes, 30–40% of urbanfringe landscapes, and <10% of suburban landscapes. Landscapes of this size have been used in other landscape studies of birds (e.g. Radford et al., 2005) as they enable landscape level comparisons of sedentary avifauna but are small enough to be replicated throughout the study area. Ten sampling sites were selected within each landscape (n = 90). All sites were located in remnant woodland patches consisting of dense tree cover greater than two hectares in area and were situated at least 50 m into the patch from the urban edge. To improve spatial independence, sites were also separated from each other by at least one kilometre. 2.2. Surveys All surveys were conducted between April and September of 2007. At each sample site, a 200 m by 200 m grid was established and divided into four sections, each measuring 100 m by 100 m. Surveys were conducted at the centre of each section (n = 4 per site) for the superb fairy wren, eastern yellow robin, white-browed scrubwren and white throated treecreeper. Where patches were too narrow, four surveys were conducted at 100 m intervals along a 400 m transect through the centre of the linear strip. Playback was used to survey for the target species and has been used to detect similar species in other research (e.g. Major et al., 1999). It involves playing bursts of the species call to illicit a territorial or social response. Playback was conducted at a low volume from a portable MP3 player, to minimize the risk of drawing animals from outside the site. All four species are highly responsive to playback. Once a species was detected at a sample site, it was considered ‘present’ and no further surveys were conducted for that species at that site. A species was considered ‘absent’ from a site if it was not detected after four repeat visits. Sites were visited throughout the day as all four target species are known to call all day, however to avoid any bias associated with more active periods of time, each repeat survey was conducted at different times of the day, between dawn and 1700 h. All surveys were conducted during periods of calm weather and by the same observer. Repeat visits were separated by a period of at least seven days.

144

S.T. Trollope et al. / Landscape and Urban Planning 93 (2009) 142–150

of the PATCH measure and includes the total extent of tree cover from a focal patch that is not separated by more than 100 m, with multiple steps to different patches possible (adapted from Bender et al., 2003) (Fig. 2). Road density (ROADDEN) was measured as the total length of roads in meters within 1000 m of the site (adapted from Shukuroglou and McCarthy, 2006). River density (RIVERDEN) was measured as the total length of rivers, streams and shoreline within 1000 m of the focal site. Riparian vegetation is often structurally more complex and supports a greater diversity of bird species, including the presence of rare species (Palmer and Bennett, 2006). A water proximity value was also assigned to each site (DISTWATER) as the distance in meters to the nearest water body. The perimeter to area ratio (PARATIO) was also calculated for each patch.

2.5. Statistical analysis

Fig. 2. Graphic representation of patch (PATCH) and connectivity (CONNECT) measures. Dashed line represents 100 m buffer around focal patch (black). PATCH measure includes sum of focal patch and patches that lie within 100 m (black and dashed patches). CONNECT measure is the total extent of tree cover that is not separated by more than 100 m (black, dashed and dotted patches).

2.3. Landscape level attributes GIS layers at 1:25 000 scales (under license from the DSE and VICMAP) were used to derive landscape level attributes in ArcView 3.3. The total extent of dense tree cover (TREE) was calculated as a percentage of dense tree cover in the landscape. The number of fragments (FRAG) was a measure of the number of dense tree cover patches in each landscape. The density of roads (ROADS) was calculated by summing the length of sealed roads in each landscape. The density of rivers and streams (RIVERS) was measured as the sum of the length of all rivers occurring in each landscape. Altitude range (ALTRANGE) was a measure of the difference in topographical relief occurring in the landscape. 2.4. Site level attributes Ten spatial attributes were quantified for each site. A measure of isolation was calculated as the total amount of dense tree cover within a radius of 500 m (ISO500), 1000 m (ISO1000) and 3000 m (ISO3000) from the centre of each site. This method using ‘buffers’ is recommended by Bender et al. (2003) as the most effective predictor of immigration and has been adapted to suit a variety of studies on different taxon including birds (e.g. Westphal et al., 2003). The size of the buffer is species specific and largely dependant on the species dispersal characteristics. The shortest distance from the sample site to a patch larger than 50 ha of dense tree cover (ISOFRAG) was also calculated as a measure of isolation. Sites located in patches larger than 50 ha were allocated a distance of zero. The area of habitat (PATCH) was a measure of the core area of habitat plus the total area of all patches that fall within 100 m from its edge (Fig. 2). This measure provides an indication of how much habitat a species can easily access (adapted from Bender et al., 2003). The connectivity measure (CONNECT) was an extension

Statistical analysis was performed using SPSS version 14.0. Analysis of Variance (ANOVA) was used to determine whether there were differences between suburban, urban-fringe and forest landscapes for each of the landscape level and site level attributes. Tukeys post hoc tests were used to identify homogeneous subgroups when significant differences were detected in the ANOVAs. Where data was not parametric appropriate transformations were applied (e.g. logarithmic and arc sin). Where the data could not be normalized we used appropriate non-parametric tests (e.g. Kruskal Wallis tests). To determine whether the number of repeat visits was adequate, two-way ANOVAs were used to test the differences between each repeat visit and the number of additional occurrences detected for each species in the three landscape types. At the landscape level, the occurrences for each species were pooled across each landscape and calculated as a percentage based on the number of sites in each landscape (n = 10). One-way ANOVAs were used to determine whether there was a difference in the occurrence of the species in relation to increasing urbanisation. Bivariate correlation was used to detect any relationships between the percentage occurrence of each species in each landscape and the landscape level attributes. To determine the site level attributes that drive the presence or absence of insectivorous birds within a landscape type an information-theoretic approach based on Akaike’s information criterion (AIC) was performed (Burnham and Anderson, 2002). To understand the dynamics occurring in each landscape type and provide subsequent management directions, modelling was performed on each species within each landscape type. Six predictor variables were selected and modelled using logistic regression assuming a binomial distribution for the presence or absence of the species. The variables selected were ROADDEN, ISOFRAG, PARATIO, PATCH, CONNECTA, and RIVERDEN. The variables were selected as they have been shown to affect bird communities in other studies. The density of roads (ROADDEN) was selected as roads have been demonstrated to adversely impact woodland dependant birds by reducing habitat quality (Ortega and Capen, 1999), creating barriers to movements (Laurance et al., 2004) and disturbance from traffic noise (Forman and Deblinger, 2000). An isolation measure (ISOFRAG) was used to see if isolation from a large patch greater than 50 ha would have an influence on dispersal and meta-population function. Perimeter to area ratios (PARATIO) give an indication of the support for patches of various shapes. The area of available habitat (PATCH) was selected to test the value of species area relationships. Connectivity (CONNECT) was selected to test the effect of broader linkages in to the landscape. The density of rivers (RIVERDEN) was selected as a surrogate for riparian habitat, as riparian habitat supports a diversity of birds and may provide an indication of connectivity through the landscape.

S.T. Trollope et al. / Landscape and Urban Planning 93 (2009) 142–150

145

Table 1 Comparison of mean values for landscape level attributes (mean ± std dev) from single factor ANOVAs. Variables are extent of tree cover (TREE); density of roads (ROADS); density of rivers (RIVERS), range in altitude (ALTRANGE), and the number of fragments (FRAG). Suburban TREE (%) ROADS (km) RIVERS (km) ALTRANGE* FRAG * a

2.97 967.72 72.61 96.67 19.33

± ± ± ± ±

Urban-fringe 1.85 106.49 15.17 15.28 6.69

34.55 247.17 241.08 250 38.33

± ± ± ± ±

0.57 85.10 46.44a 45.83 9.45

Forest 95.15 19.15 244.74 666.67 0

± ± ± ± ±

2.14 13.09 40.72 a 237.56 0

F

p

2372.57 117.66 21.513 47.73 24.74

<0.001 <0.001 0.002 <0.001 <0.001

ANOVA results (F and p values) presented from transformed data (log10). Homogenous subsets (Tukeys).

All possible subsets of the six predictor variables were modelled (n = 63). For each model, the AIC, corrected for small sample size (AICC ), and Akaike differences (i ) were calculated. Following Burnham and Anderson (2002), Akaike differences ≤2 have substantial support, while 4–7 have considerable less support and ≥10 have no empirical evidence for support. The respective Akaike weights (ωi ) were also calculated for each model and used to provide additional support. Akaike weights are normalized model likelihoods that sum to 1 and indicate the probability of being the best model. Summing the AIC weights for each model containing a certain variable provides an indication of the importance of that variable. Hierarchal partitioning was also used to help identify the predictor variables that had the strongest independent influence. The resultant model was evaluated using the receiver operating characteristic (ROC) technique which plots the true positive cases against false positive cases. The area under the curve (AUC) produces a value (and standard error) to support the model between 0.5 and 1. Results of 1 indicate a perfect ability of the model to correctly predict between the presence or absence of the target species and results of 0.5 suggest the model has no better support than random predictions. Akaike modelling was performed using R statistical package using algorithms to run the hierarchal partitioning analysis (Walsh and Mac Nally, 2003) and the AICC (Scroggie, unpublished). 3. Results 3.1. Summary of landscape level attributes All landscape level attributes were different between the three landscape types (Table 1). Forest landscapes were dominated by a high proportion of dense tree cover which formed continuous unfragmented habitat. There were fewer sealed roads contributing to the lowest densities within the three landscape types. Forest landscapes had the widest range in altitude as they occurred mostly in high altitude regions. As a result, river densities were also very high as they function as the source for many rivers and streams. On the continuum towards increased urbanisation, urban-fringe landscapes were characterised by higher density of roads, less vegetation cover but the highest mean number of fragments. Suburban landscapes were clearly the most heavily impacted from anthropogenic pressures. Mean road densities were the highest of all landscape types. The mean proportion of dense vegetation cover was the lowest and distributed across fewer fragments than urbanfringe landscapes. Urban landscape also had the least variation in altitude and lowest density of rivers. 3.2. Summary of site level attributes The isolation measures showed distinct differences between each of the landscapes. There were significant differences between the three landscape types for ISO500 (Kruskal Wallis: H = 74.223, df = 2, p < 0.001), ISO1000 (Kruskal Wallis: H = 76.656, df = 2,

p < 0.001) and ISO3000 (Kruskal Wallis: H = 78.684, df = 2, p < 0.001). For each of these attributes, sites in forest landscapes contained the highest mean area of dense tree cover, followed by urban-fringe then suburban sites. This trend was expected given landscapes were selected and classified based on the extent of dense tree cover they contained, however, lower measurements (such as in suburban landscapes) also indicate that the patches that remain are more isolated from each other. The shortest distance to a fragment greater than 50 ha (ISOFRAG) showed significant differences between landscapes (Kruskal Wallis: H = 60.193, df = 2, p < 0.001). All sites in forest landscapes were located in continuous forest and therefore allocated zero values. The distance in urban-fringe landscapes was extremely low (0.35 km ± 0.127 (mean ± 1 std dev)) indicating low proximity isolation compared to sites in suburban landscapes (4.387 km ± 3.930 (mean ± 1 std dev)). The density of roads (ROADDEN) exhibited differences between landscape types (Kruskal Wallis: H = 70.663, df = 2, p < 0.001). Sites in suburban landscapes had the highest density of roads (23.599 km ± 8.936 (mean ± 1 std dev)), followed by urbanfringe (7.744 km ± 5.385 (mean ± 1 std dev)) then forest sites (0.925 km ± 1.336 (mean ± 1 std dev)). River densities (RIVERDEN) were significantly different between the sites in the three landscapes (F = 22.036, df = 2,87, p < 0.001). The highest density occurred in urban-fringe landscapes (mean = 8.198 km ± 2.992 (mean ± 1 std dev)) and was statistically similar (Tukeys: p > 0.05) to the density in forest landscapes (7.427 km ± 2.718 (mean ± 1 std dev)). Sites in suburban landscapes had the lowest density of rivers (3.999 km ± 2.014 (mean ± 1 std dev)) (Tukeys p < 0.05). Measures of connectivity (CONNECT), area of habitat (PATCH) and perimeter to area ratio (PARATIO) were performed only within suburban landscapes. The measures in urban-fringe and forest landscapes turned into continuous tree cover which made calculations for these variables indefinite. Connectivity (CONNECT) of sites in urban landscapes had values of 257.232 ha ± 523.172 (mean ± 1 std dev). The area of available habitat (PATCH) was 156.670 ha ± 459.084 (mean ± 1 std dev), and perimeter to area ratio (PARATIO) of 0.470 km/ha ± 0.172 (mean ± 1 std dev). 3.3. Response of insectivorous birds 3.3.1. Survey effort There was a significant difference in the accumulation of presences of the superb fairy wren, eastern yellow robin and white-browed scrubwren between repeat visits, however there was no significant improvement in the proportion of sites in a landscape that had the species detected beyond the second visit (Tukeys: p > 0.05). Landscape type had a significant effect on the proportion of sites that had the species. There was no interaction between repeat visit and landscape type, suggesting that the sampling regime was adequate and consistent across landscape types (superb fairy wren: Visit F = 5.345, df = 3,24, p = 0.006, Landscape F = 3.682, df = 2,24, p = 0.040, Interaction

146

S.T. Trollope et al. / Landscape and Urban Planning 93 (2009) 142–150

Fig. 3. Proportion of sites supporting the superb fairy wren (a), the white-browed scrubwren (b), the eastern yellow robin (c), and the white throated treecreeper (d) in suburban, urban-fringe and forest landscapes (mean ± 1.96 S.E.).

F = 0.869, df = 6,24, p = 0.869; eastern yellow robin: Visit F = 4.055, df = 3,24, p = 0.018, Landscape F = 28.529, df = 2,24, p < 0.001, Interaction F = 0.230, df = 6,24, p = 0.963; white-browed scrubwren: Visit F = 6.009, df = 3,24, p = 0.003, Landscape F = 28.529, df = 2,24, p < 0.001, Interaction F = 0.230, df = 6,24, p = 0.963). The white throated treecreeper was the only species that repeat sampling was not necessary (F = 0.783, df = 3,24, p = 0.515). After the initial visit, there was no significant improvement in the proportion of sites in a landscape that had the species (Tukeys: p > 0.05). Landscape type had a significant effect on the proportion of sites that had the species (F = 141.647, df = 2,24, p < 0.001) and there was no interaction between repeat visit and landscape type (F = 0.079, df = 6,24, p = 0.998). These results indicate that the number of repeat visits in this study was adequate for detecting the patch occupancy for each of the species in all landscape types. 3.4. Response to landscape level attributes Throughout the entire study area, the white-browed scrubwren occurred in the highest proportion of sites (79%). The eastern yellow robin (68%), superb fairy wren (67%) and white throated treecreeper (57%) were all observed at a sufficient amount of sites to enable landscape scale comparisons.

With the exception of the superb fairy wren, forest landscapes contained the highest mean presence of all species. Comparison of the proportion of patch occupancy for each species among suburban, urban-fringe and forest landscapes revealed two general response patterns: a tolerance to increasing levels of urban development and a threshold to moderate levels of urbanisation. There was no impact on the presence of the superb fairy wren (F = 0.842, df = 2,6, p = 0.476) (Fig. 3a) or the white-browed scrubwren (F = 1.632, df = 2,6, p = 0.272) (Fig. 3b). The mean presence of the white-browed scrubwren showed some decline in response to urbanisation, however, all landscapes were statistically inseparable due to large variances of the data in suburban and urban-fringe landscapes (Tukeys: p > 0.05). Species that displayed a decline over the three landscape types were the eastern yellow robin (F = 14.467, df = 2,6, p = 0.005) and the white throated treecreeper (F = 92.625, df = 2,6, p < 0.001). In both cases, forest and urban-fringe sites were statistically similar (Tukeys: p > 0.05), however, the mean presence of each species was significantly lower in suburban sites (Tukeys: p < 0.05) (Fig. 3c and d). In forest landscapes, the white throated treecreeper and eastern yellow robin were present at an extremely high percentage of sites, means 100% and 96.67% respectively. The white throated treecreeper displayed the most dramatic decline to 3.33% of sites in

S.T. Trollope et al. / Landscape and Urban Planning 93 (2009) 142–150

147

Table 2 Summary of bivariate correlation analysis for superb fairy wren (SFW), the eastern yellow robin (EYR), the white-browed scrubwren (WBS), and the white throated treecreeper (WTT) and landscape level attributes (extent of tree cover (TREE), density of roads (ROADS), the density of rivers (RIVERS), range in altitude (ALTRANGE), and the number of fragments (FRAG)). TREE

ROADS

r SFWa EYRa WBSb WTTa a b

p

−0.092 0.780 0.505 0.823

0.813 0.013 0.166 0.006

RIVERS

r −0.176 −0.902 −0.440 −0.986

ALTRANGE

p

r

p

r

0.651 0.001 0.235 <0.001

0.352 0.789 0.073 0.879

0.352 0.012 0.851 0.002

FRAG p

−0.277 0.651 0.661 0.715

r

0.471 0.058 0.053 0.030

p

0.300 −0.238 −0.523 −0.178

0.433 0.538 0.149 0.646

Pearsons correlation. Spearman rank correlation.

Table 3 Results for the AICc -based model selection for the eastern yellow robin in urban landscapes; table shows maximum log-likelihood function (log(L)), number of predictor variables (K), AICc differences (i ), Akaike weights (ωi ). Model includes site level variables: density of rivers (R), density of roads (Rd), patch size (P), perimeter to area ratio (Pa), connectivity (C), isolation (I). Number

Model

1 2 3 4 5 6 7 8 9

R + Rd + P Rd + Pa R + Rd Rd + P + Pa C + Rd + Pa Rd + P C + R + Rd + P R + Rd + Pa R + Rd + P + Pa

log(L)

K

AICc

i

ωi

−7.4383 −8.9571 −9.2268 −8.0415 −8.2805 −9.6780 −6.8999 −8.5700 −7.2457

4 3 3 4 4 3 5 4 5

24.48 24.84 25.38 25.68 26.16 26.28 26.30 26.74 26.99

0.00 0.36 0.90 1.21 1.68 1.80 1.82 2.26 2.51

0.128 0.107 0.082 0.070 0.055 0.052 0.051 0.041 0.036

suburban landscapes compared to the eastern yellow robin which was present at 43.33% of sites in suburban landscapes. At the landscape level there were no significant correlations between the landscape attributes and the proportion of sites occupied by the superb fairy wren or the white-browed scrubwren (p > 0.05) (Table 2). In contrast, the density of roads proved to have a very strong, negative relationship with the occurrence of the white throated treecreeper (rp = −0.986, df = 8, p < 0.01) and the eastern yellow robin (rp = −0.902, df = 8, p = 0.001). As the density of roads increased with urbanisation, there were subsequent declines in the occurrence of these species. There was a strong positive correlation between the proportion of sites occupied by the white throated treecreeper and the density of rivers in the landscape (rp = −0.879, df = 8, p = 0.002), as was for the eastern yellow robin (rp = −0.789, df = 8, p = 0.012). The white throated treecreeper and eastern yellow robin were also positively correlated with the extent of dense tree cover in the landscape (White throated tree creeper: rp = 0.823, df = 8, p = 0.006; Eastern yellow robin: rp = 0.780, df = 8, p = 0.013) (Table 2).

3.5. Response to site level attributes

across landscapes to model as they occupied a high proportion of sites in each of the landscape types. Similarly, the white throated treecreeper occurred in a high proportion of sites in forest and urban-fringe sites but only at one site in the suburban landscapes. Data was, therefore, inadequate to model. The top 9 models out of a potential 63 produced from the Akaike statistics are displayed in Table 3 and ranked according to their AICc differences ((AICc ) from best to worst. The model best suited to predict the presence of the eastern yellow robin in suburban patches was an interaction between river density, road density and patch area (model number 1). As models with Akaike differences between 0 and 2 have substantial support (Burnham and Anderson, 2002), the subsequent six models are also plausible. All models that have substantial support include the density of roads as a contributing variable (Table 3). Sum of AIC weights also indicates strong support for roads being in any model (Table 4). The hierarchal partitioning analysis indicates only the density of roads to have a significant independent contribution (59.75%) in predicting the occurrence of the eastern yellow robin (Table 4). A logistic regression model was produced from the coefficients (Table 4) for each variable: Y = 16.61394 − 0.69068 (ROADS) + 0.75096 (RIVERS)

Modelling was only performed on the eastern yellow robin in suburban landscapes. There was not enough variance in the patch occupancy of the superb fairy wren and white-browed scrubwren

+ 3.38408 (CONNECT) − 6.77584 (PATCH) − 0.09218 (PARATIO) − 0.04531 (ISOFRAG)

Table 4 Results from AIC analysis. Table displays coefficient for each variable, standard error, z-score, statistical significance value (based on upper 0.95 confidence limit), independent contribution (%) derived from hierarchal portioning analysis and sum of AIC weights. Variable

Coefficient

Standard error

z-Score

Pr(>|z|)

Contribution

Sum of AIC weights

Constant ROADS RIVERS CONNECT PATCH PARATIO ISOFRAG

16.161394 −0.69068 0.75096 3.38408 −6.77584 −0.09218 −0.04531

10.9446 0.4068 0.6370 5.3026 7.3018 17.4774 0.2146

1.518 −1.698 1.179 0.638 −0.928 −0.005 −0.211

0.1290 0.0895 0.2384 0.5233 0.3534 0.9958 0.8328

59.746 20.540 7.927 7.330 3.086 1.371

0.9982 0.5061 0.2992 0.5073 0.4671 0.2127

148

S.T. Trollope et al. / Landscape and Urban Planning 93 (2009) 142–150

To transform the predictors from logit scale to probability scale, the linear predictor (Y) was applied to the following equation: Probability of occurrence = exp(Y )/(1 + exp(Y )) The result from the area under the curve of the ROC plot was 0.964 ± 0.031 which indicates that the model could correctly predict the occurrence of the eastern yellow robin 96% of the time. As such, the model provides useful predictive power. 4. Discussion The patterns that emerged from this study highlighted two distinct responses to increasing levels of urbanisation by four species of common insectivorous birds. Firstly, tolerance to increasing urbanisation; and secondly, sensitivity to increasing urbanisation with a threshold occurring between urban-fringe and suburban areas. The general trends found in this study are consistent with the literature in that some insectivores have displayed a stronger resilience to increasing levels of urban development than others. This varied response is likely to be dependant on species specific aspects of their ecology such as territory size, dispersal requirements, and habitat and resource selection. 4.1. Urban tolerant species Despite the extensive changes to the landscape in suburban environments, the superb fairy wren and white-browed scrubwren still occurred in similar proportions to urban-fringe and forested landscapes. The smaller fragments leave much of the habitat at the influence from edge effects (Young and Mitchell, 1994) and to increased predation rates that have been associated with urbanisation throughout the world (Thorington and Bowman, 2003; Crooks et al., 2004; Jokimäki and Kaisanlahti-Jokimäki, 2005; Garden et al., 2006). While many forest dependant species are unable to persist in these environments, the superb fairy wren and the white-browed scrubwren are able to utilize the compositional and structural modifications of habitat and resources that are commonly associated with urban fragments (Tait et al., 2005). The superb fairy wren has been found to exclusively inhabit forest edges (Berry, 2001). Furthermore, Nias (1986) showed that nest success of the superb fairy wren was increased in blackberry bushes, Rubus fruticosus. Similarly, it has been proposed that the lowered risk of nest failure of the white-browed scrubwren is due to their well hidden dome nests at ground level (Magrath et al., 2000) and although not considered an edge specialist, it has been found to commonly inhabit forest edges (Berry, 2001). In the present study, 47% of patches in urban landscapes were 10 ha or less, which, following Young and Mitchell (1994), are therefore, dominated by edge effects. The superb fairy wren, however, is able to exploit these conditions. Furthermore, territory size and dispersal distances of the superb fairy wren are relatively small. Tidemann (1990) found territory size to vary between 1.3 and 2.4 ha over a four year period. Dispersal distances have also been demonstrated to be small and sex biased towards females with the majority dispersing at least three territories (Cockburn et al., 2003). Although less is known about the white-browed scrubwren, home range sizes have been estimated at 2.03 ha (Ambrose and Davies, 1989). Consequently, despite the heavily fragmented nature and small patch sizes, characteristic of suburban landscapes, these areas still provide adequate resources to support meta-populations of the superb fairy wren and white-browed scrubwren. In summary, insectivorous birds species that are able to tolerate increasing levels of urbanisation tend to have low resource requirements, and are able to exploit or tolerate edge environments.

4.2. Urban sensitive species The species that displayed the strongest sensitivity to urbanisation were the eastern yellow robin and the white throated treecreeper. Rather than displaying a linear response, their occurrence at a high proportion of sites in forest and urban-fringe landscapes indicates that they are able to endure a threshold to urbanisation beyond which they decline rapidly. There are a number of hypotheses relating to their ecology and to the urban matrix which may account for the declining distribution of urban sensitive species. Previous research has attributed the decline of urban sensitive species to isolation (Watson et al., 2005), disrupted dispersal as a result of barriers to movements (Drinnan, 2005), small fragment area (Watson et al., 2001), a reduced resource base in urban fragments (Harper et al., 2005) and increased predation rates (Rottenborn, 1999; Patten and Bolger, 2003). In the present study, the landscape level attribute that was most strongly associated with patch occupancy of both the eastern yellow robin and the white throated treecreeper was the density of roads. The extent of tree cover was also positively correlated with the presence of these species, which indicates that networks of habitat including isolation and connectivity indices may also be important in determining the habitat configuration that supports urban sensitive species. Comparisons of the transition in tree cover between urbanfringe and suburban landscapes would seemingly not result in the disproportionate effect on the urban sensitive species observed in this study. Several other variables are likely to be operating that inhibit their persistence in urban patches. Sites in urban-fringe landscapes are well connected and have low isolation measures, despite the low extent of tree cover in the landscape, which indicates that dispersal is not disrupted. This is supported by Drinnan (2005) who suggested that forest dependant species displayed a threshold to remnants connected by large, good quality corridors. Dispersal has been a common theme in other research. Hodgson et al. (2007) showed that the dispersal of insectivores was impeded by high density housing which suggests that sub-populations in suburban patches may be independent from meta-population functions and completely reliant on the resources provided within the remnant. Species such as the white throated treecreeper, that have relatively large home ranges and large dispersal distances, may be disproportionately affected by the abrupt edges in areas of high density housing compared to other small insectivorous birds such as the superb fairy wren. The smallest patch occupied by white throated treecreeper was 32 ha, however, 92% of occurrences were in patches greater than 500 ha. Furthermore, occupied patches less than this size had low isolation measures (ISOFRAG). Isolation has been attributed to a species ability to disperse (Radford and Bennett, 2004), which is an important ecological function to maintain meta-populations and reduce the potential of local extinction (Hodgson et al., 2007). The significant differences in the isolation measures between urban and urban-fringe landscapes is therefore likely to heavily impact species due to the requirement for large dispersal distances. This has been demonstrated within agricultural landscapes by Coopers and Walters (2002) who showed that the absence of female brown treecreepers in fragmented remnants was attributed to isolation as females were unable to disperse long distances into vacant breeding territories. Furthermore, the sensitivity of this species to fragment area is enhanced in urban landscapes compared to agricultural landscapes (Watson et al., 2001). The dispersal of the white throated treecreeper (which has a similar ecology to the brown treecreeper) may also be disrupted by the spatial configuration of habitat in the landscape and therefore unable to persist in urbanised landscapes where patches of habitat are highly isolated.

S.T. Trollope et al. / Landscape and Urban Planning 93 (2009) 142–150

Analysis of site level attributes in urban landscapes revealed the density of roads as the strongest independent predictor variable for the presence of the eastern yellow robin with lower presence in areas of higher road densities. The density of rivers was also identified as a positive significant determinant of eastern yellow robin presence, however, was not as influential as roads. Surprisingly, habitat variables entered into the regression model, such as area of available habitat (PATCH) and connectivity measures (CONNECT), did not have a significant contribution despite the eastern yellow robin being considered as an area sensitive species (Zanette et al., 2000; Watson et al., 2001). The density of roads had such a strong contribution that it outweighed these predictor variables. In fact the PATCH variable in the model contributed a negative relationship albeit a minor input, which contradicts most previous research that found fragment size to be a strong positive predictor of bird diversity and abundance in urban landscapes (Crooks et al., 2004; Fernández-Juricic, 2004). This finding may be more a reflection of the adjacent land between the patch and the urban matrix that reduces abrupt edges. Maintaining land that has low human disturbance in place of roads around patches of viable habitat, thereby creating soft edges, may result in more favourable habitat for urban sensitive species. The outstanding contribution of roads to the model has several interpretations as it is likely to indicate multiple mechanisms that are operating in urban environments. Roads can have a direct impact on mortality. Ramp et al. (2006) recorded high mortality of honeyeaters on roads, however, insectivores such as the superb fairy wren and white-browed scrubwren were also impacted. In the United States, Forman et al. (2002) showed the diversity of birds to decline within several hundred meters of the road and suggested that roads have their largest impact in suburbanising landscapes, where the road has a greater interaction with natural landscapes. As landscapes become heavily urbanised, this has important implications for the way fringe landscape are managed to maintain biodiversity. Increasing densities of roads have been shown to be highly correlated with increasing densities of housing (Green and Baker, 2003). In addition to the subsequent disrupted dispersal in areas of high density housing, species may also suffer from increased predation rates by domestic animals (Rottenborn, 1999). The contribution of rivers to the model was expected given previous research that has associated riparian systems with an increase in the abundance of individuals and diversity of bird communities (Knopf and Samson, 1994) compared to surrounding ecosystems including habitat that can support rare species (Palmer and Bennett, 2006). Miller et al. (2003) have however, demonstrated that the number of species using riparian habitats declines as the intensity of urbanisation increases in the surrounding area. Maintaining and enhancing riparian vegetation in urban landscapes and also reducing the intensity of urban development, including roads and buildings, on adjacent land is likely to have subsequent benefits for urban sensitive birds (e.g. Miller et al., 2003). These findings are supported by research from the United States that found avian communities in riparian zones to be affected by the proximity of roads and buildings (Rottenborn, 1999). Furthermore, Hennings and Edge (2003) found a similar interaction to the current study between rivers and roads. They recommended that decreasing road density within 100 m of the stream and increasing canopy cover within 450 m of the stream would manage exotic birds and conserve native species. 4.3. Conservation implications Given the decline of insectivorous birds, and in particular ground and bark–trunk foraging species, in human modified landscapes (e.g. Lim and Sodhi, 2004), what can we do to avoid further losses

149

across suburban–forest gradients? It is clear from our results that urban sensitive insectivorous species such as eastern yellow robin and white throated treecreeper are likely to be impacted adversely in the shift between urban-fringe environments and suburban areas. This change appears to be associated with increasing housing and road densities (e.g. Green and Baker, 2003), decreasing natural tree cover and connectivity, and declining quality of riparian habitats (e.g. Miller et al., 2003). We suggest several strategies which may help to mitigate the impacts of urbanisation on ground foraging and bark–trunk foraging insectivores. Within the suburban zone, our focus must be on maintaining and enhancing the quality and extent of what vegetation remains (e.g. Melles et al., 2003; Palmer et al., 2008). This may best be achieved by focusing on riparian systems embedded in the urban zone and developing them as green areas. Restricting development around riparian systems and improving the quality and connectivity of riparian vegetation (Miller et al., 2003) will enhance the opportunities for insectivorous birds. Within the urban-fringe growth areas of cities, we have the capacity to make the most difference to insectivorous avifauna. These areas currently maintain sensitive species, but are at risk from increasing levels of urbanisation. Any conservation strategies that are going to work to reduce the impact of urbanisation in the urban-fringe environment are going to be reliant on strong and clear planning procedures. By defining the urban-fringe area and establishing different planning rules for these areas, cities have the capacity to limit the extent and intensity of urbanisation. Increasing the housing block sizes (Melles et al., 2003), implementing strong vegetation protection rules, and protecting areas of significant vegetation with extremely low density urbanisation buffer zones would together limit the impact of urbanisation on sensitive ground and bark–trunk foraging insectivorous birds. Acknowledgements A thank you to Bronwyn Isaac and Fiona Hogan for their GIS knowledge and advice, Isobelle and Joan Trollope and Sally Robotham for help in the field. My thanks also extend to the Department of Sustainability and Environment, Parks Victoria, and Melbourne Water which were all integral in the completion of this project. This research was completed under permit no. 10004122, and with animal ethics approval (A16/2007). References Ambrose, S.J., Davies, S.J.J.F., 1989. The social organization of the white-browed scrubwren Sericornis frontalis gould (Acanthizidae) in arid, semi-arid and mesic environments of Western Australia. Emu 89, 40–46. Australian Bureau of Statistics, 2007. Regional Population Growth, Australia, 1996 to 2006. Australian Bureau of Statistics, Commonwealth of Australia. Beck, N.R., Heinsohn, R., 2006. Group composition and reproductive success of cooperatively breeding white-winged choughs (Corcorax melanorhamphos) in urban and non-urban habitat. Aust. Ecol. 31, 588–596. Bender, D.J., Tischendorf, L., Fahrig, L., 2003. Using patch isolation metrics to predict animal movement in binary landscapes. Landscape Ecol. 18, 17–39. Berry, L., 2001. Edge effects on the distribution and abundance of birds in a southern Victorian forest. Wildlife Res. 28, 239–245. Blair, R.B., 1996. Land use and avian species diversity along an urban gradient. Ecol. Appl. 6, 506–519. Burnham, K.P., Anderson, D.R., 2002. Model Selection and Multimodel Inference: A Practical Information-Theoretical Approach, 2nd ed. Springer-Verlag, New York. Cale, P., 1994. Temporal changes in the foraging behaviour of insectivorous birds in a sclerophyll forest in Tasmania. Emu 94, 116–126. Clergeau, P., Savard, J-P.L., Mennechez, G., Flardeau, G., 1998. Bird abundance and diversity along an urban-rural gradient: a comparative study between two cities on different continents. Condor 100, 413–425. Cockburn, A., Osmond, H.L., Mulder, R.A., Green, D.J., Double, M.C., 2003. Divorce, dispersal and incest avoidance in the cooperatively breeding superb fairy-wren Malurus cyaneus. J. Anim. Ecol. 72, 189–202. Coopers, C.B., Walters, J.R., 2002. Experimental evidence of disrupted dispersal causing decline of an Australian passerine in fragmented habitat. Conserv. Biol. 16, 471–478.

150

S.T. Trollope et al. / Landscape and Urban Planning 93 (2009) 142–150

Crooks, K.R., Suarez, A.V., Bolger, D.T., 2004. Avian assemblages along a gradient of urbanization in a highly fragmented landscape. Biol. Conserv. 115, 451–462. Drinnan, I.N., 2005. The search for fragmentation thresholds in a southern Sydney suburb. Biol. Conserv. 124, 339–349. Fernández-Juricic, E., 2004. Spatial and temporal analysis of the distribution of forest specialists in an urban-fragmented landscape (Madrid, Spain)—implications for local and regional bird conservation. Landscape Urban Plan. 69, 17–32. Fernández-Juricic, E., Jokimäki, J., 2001. A habitat island approach to conserving birds in urban landscapes: case studies from southern and northern Europe. Biodivers. Conserv. 10, 2023–2043. Forman, R.T.T., Deblinger, R.D., 2000. The ecological road-effect zone of a Massachusetts (U.S.A.) suburban highway. Conserv. Biol. 14, 36–46. Forman, R.T.T., Reineking, B., Hersperger, A.M., 2002. Road traffic and nearby grassland bird patterns in a suburbanizing landscape. Environ. Manage. 29, 782–800. Fraterrigo, J.M., Wiens, J.A., 2005. Bird communities of the Colorado Rocky Mountains along a gradient of exurban development. Landscape Urban Plan. 71, 263–275. Garden, J., McAlpine, C., Peterson, A., Jones, D., Possingham, H., 2006. Review of the ecology of Australian urban fauna: a focus on spatially explicit processes. Aust. Ecol. 31, 126–148. Green, D.M., Baker, M.G., 2003. Urbanization impacts on habitat and bird communities in a Sonoran desert ecosystem. Landscape Urban Plan. 63, 225–239. Hahs, A.K., McDonnell, M.J., 2006. Selecting independent measures to quantify Melbourne’s urban-rural gradient. Landscape Urban Plan. 78, 435–448. Harper, M.J., McCarthy, M.A., van der Ree, R., 2005. The abundance of hollow-bearing trees in urban dry sclerophyll forest and the effect of wind on hollow development. Biol. Conserv. 122, 181–192. Hennings, L.A., Edge, W.D., 2003. Riparian bird community structure in Portland, Oregon: habitat, urbanization, and spatial scale patterns. Condor 105, 288–302. Hodgson, P., French, K., Major, R.E., 2006. Comparison of foraging behaviour of small, urban-sensitive insectivores in continuous woodland and woodland remnants in a suburban landscape. Wildlife Res. 33, 591–603. Hodgson, P., French, K., Major, R.E., 2007. Avian movement across abrupt ecological edges: different responses to housing density in an urban matrix. Landscape Urban Plan. 79, 266–272. Jökimäki, J., Kaisanlahti-Jökimäki, M.-L., 2003. Spatial similarity of urban bird communities: a multiscale approach. J. Biogeogr. 30, 1183–1193. Jokimäki, J., Kaisanlahti-Jokimäki, M.-L., 2005. Evaluation of the ‘safe nesting zone hypothesis’ across an urban gradient: a multi-scale approach. Ecography 28, 59–70. Knopf, F.L., Samson, F.B., 1994. Scale perspectives on avian diversity in western riparian ecosystems. Conserv. Biol. 8, 669–676. Laurance, S.G.W., Stouffer, P.C., Laurance, W.F., 2004. Effects of road clearings on movement patterns of understorey rainforest birds in central Amazonia. Conserv. Biol. 18, 1099–1109. Lim, H.C., Sodhi, N.S., 2004. Responses of avian guilds to urbanization in a tropical city. Landscape Urban Plan. 66, 199–215. Lindenmayer, D.B., Cunningham, R.B., Weekes, A., 2007. A study of the foraging ecology of the white-throated treecreeper (Cormobates leucophaeus). Emu 107, 135–142. Magrath, R.D., Leedman, A.W., Gardner, J.L., Giannasca, A., Nathan, A.C., Yezerinac, S.M., et al., 2000. Life in the slow lane: reproductive life history of the whitebrowed scrubwren, an Australian endemic. Auk 117, 189–479. Major, R.E., Christie, F.J., Gowing, G., 2001. Influence of remnant and landscape attributes on Australian woodland bird communities. Biol. Conserv. 102, 47–66. Major, R.E., Christie, F.J., Gowing, G., Ivison, T.J., 1999. Age structure and density of red-capped robin populations vary with habitat size and shape. J. Appl. Ecol. 36, 901–908. McDonnell, M.J., Pickett, S.T.A., 1990. Ecosystem structure and function along urbanrural gradients: an unexploited opportunity for ecology. Ecology 71, 1232–1237. Melles, S., Glenn, S., Martin, K., 2003. Urban bird diversity and landscape complexity: species–environment associations along a multiscale habitat gradient. Conserv. Ecol. 7, 5. [online] URL: http://www.consecol.org/vol7/iss1/art5. Miller, J.R., Wiens, J.A., Thompson Hobbs, N., Theobald, D.M., 2003. Effects of human settlement on bird communities in lowland riparian areas of Colorado (USA). Ecol. Appl. 13, 1041–1059.

Nias, R.C., 1986. Nest-site characteristics and reproductive success in the superb fairy-wren. Emu 86, 139–144. Ortega, Y.K., Capen, D.E., 1999. Effects of forest roads on habitat quality for oven birds in a forested landscape. Auk 116, 937–946. Palmer, G.C., Bennett, A.F., 2006. Riparian zones provide for distinct bird assemblages in forest mosaics of south-east Australia. Biol. Conserv. 130, 447–457. Palmer, G.C., Fitzsimons, J.A., Antos, M.J., White, J.G., 2008. Determinants of native avian richness in suburban remnant vegetation: implications for conservation planning. Biol. Conserv. 141, 2329–2341. Patten, M.A., Bolger, D.T., 2003. Variation in top-down control of avian reproductive success across a fragmentation gradient. Oikos 101, 479–488. Radford, J.Q., Bennett, A.F., 2004. Thresholds in landscape parameters: occurrence of the white-browed treecreeper Climacteris affinis in Victoria, Australia. Biol. Conserv. 117, 375–391. Radford, J.Q., Bennett, A.F., Cheers, G.J., 2005. Landscape-level thresholds of habitat cover for woodland-dependant birds. Biol. Conserv. 124, 317–337. Ramp, D., Wilson, V.K., Croft, D.B., 2006. Assessing the impacts of roads in peri-urban reserves: road-based fatalities and road usage by wildlife in the Royal National Park. New South Wales, Australia. Biol. Conserv. 129, 348–359. Rebele, F., 1994. Urban ecology and special features of urban ecosystems. Global Ecol. Biogeogr. 4, 173–187. Rottenborn, S.C., 1999. Predicting the impacts of urbanization on riparian bird communities. Biol. Conserv. 88, 289–299. Sandström, U.G., Angelstam, P., Mikusinski, G., 2006. Ecological diversity of birds in relation to the structure of urban green space. Landscape Urban Plan. 77, 39– 53. Saunders, D.A., Hobbs, R.J., Margules, C.R., 1991. Biological consequences of ecosystem fragmentation: a review. Conserv. Biol. 5, 18–32. Shukuroglou, P., McCarthy, M.A., 2006. Modelling the occurrence of rainbow lorikeets (Trichoglossus haematodus) in Melbourne. Aust. Ecol. 31, 240–253. Smith, C.M., Wachob, D.G., 2006. Trends associated with residential development in riparian breeding bird habitat along Snake River in Jackson Hole, WY, USA: implications for conservation planning. Biol. Conserv. 128, 431–446. Soh, M.C.K., Sodhi, N.S., Lim, S.L.H., 2006. High sensitivity of montane bird communities to habitat disturbance in Peninsular Malaysia. Biol. Conserv. 129, 149– 166. Tait, C.J., Daniels, C.B., Hill, R.S., 2005. Changes in species assemblages within the Adelaide metropolitan area, Australia, 1836–2002. Ecol. Appl. 15, 346–539. Tidemann, S.C., 1990. Factors affecting territory establishment, size and use by three coexisting species of fairy-wrens (Malurus). Emu 90, 7–14. Thorington, K.K., Bowman, R., 2003. Predation rate on artificial nests increases with human housing density in suburban habitats. Ecography 26, 188–196. Walsh, C., Mac Nally, R., 2003. The hier.part package, Version 0.5-1. Hierarchal Partitioning. Documentation for R (R. project for statistical computing). [http://cran.r-project.org/]. Watson, J., Freudenberger, D., Paull, D., 2001. An assessment of the focal-species approach for conserving birds in variegated landscapes in southeastern Australia. Conserv. Biol. 15, 1364–1373. Watson, J.E.M., Whittaker, R.J., Dawson, T.P., 2002. Avifaunal responses to habitat fragmentation in the threatened littoral forests of south-eastern Madagascar. J. Biogeogr. 31, 1791–1807. Watson, J.E.M., Whittaker, R.J., Freudenberger, D., 2005. Bird community responses to habitat fragmentation: how consistent are they across landscapes? J. Biogeogr. 32, 1353–1370. Westphal, M.I., Field, S.A., Tyre, A.J., Paton, D., Possingham, H.P., 2003. Effects of landscape pattern on bird species distribution in the Mt. Lofty Ranges, South Australia. Landscape Ecol. 18, 413–426. White, J.G., Antos, M.J., Fitzsimons, J.A., Palmer, G.C., 2005. Non-uniform bird assemblages in urban environments: the influence of streetscape vegetation. Landscape Urban Plan. 71, 123–135. Young, A., Mitchell, N., 1994. Microclimate and vegetation edge effects in a fragmented podocarp-broadleaf forest in New Zealand. Biol. Conserv. 67, 63–72. Zanette, L., Doyle, P., Trémont, S.M., 2000. Food shortage in small fragments: evidence from an area-sensitive passerine. Ecology 81, 1654–1666.