Effects of patch size and basal area on avian taxonomic and functional diversity in pine forests: Implication for the influence of habitat quality on the species–area relationship

Relationships between avian diversity and habitat area are assumed to be positive; however, often little attention has given to how these relationships can be influenced by the habitat structure or quality. In addition, other components of biodiversity, such as functional diversity, are often overlooked in assessing habitat patch value. In the Sandhills Ecoregion of Georgia, USA, we investigated the relationship between avian species richness and functional diversity, forest basal area, and patch size in pine forests using basal area as a surrogate for overstory structure which in turn impacts vegetation structure and determines habitat quality within a patch. We conducted bird surveys in planted mature pine stands, during breeding season of 2011. We used three classes of stand basal area (BA): OS, overstocked (BA ≥ 23 m²/ha); FS, fully/densely stocked (13.8 m²/ha ≤ BA < 23 m²/ha); and MS, moderately stocked (2.3 m²/ha ≤ BA < 13.8 m²/ha). MS patches showed more structural diversity due to higher herbaceous vegetation cover than other two pine stocking classes of patches. Total species richness and functional richness increased with the size of MS patches, whereas functional divergence decreased with the size of OS patches (p < 0.05). Functional richness tended to be lower than expected as the size of OS patches increased. Greater richness of pine–grassland species was also found at MS patches. Percent cover of MS patches within a landscape influenced positively the richness of pine–grassland species (p < 0.05). Our results suggest that (a) avian species–habitat area relationship can be affected by habitat quality (structural diversity) and varies depending on diversity indices considered, and (b) it is important to maintain moderate or low levels of pine basal area and to preserve large‐sized patches of the level of basal area to enhance both taxonomic and functional diversity in managed pine forests.     

Developing landscape habitat models for rare amphibians with small geographic ranges: a case study of Siskiyou Mountains salamanders in the western USA

To advance the development of conservation planning for rare species with small geographic ranges, we determined habitat associations of Siskiyou Mountains salamanders (Plethodon stormi) and developed habitat suitability models at fine (10 ha), medium (40 ha), and broad (202 ha) spatial scales using available Geographic Information Systems data and logistic regression analysis with an information theoretic approach. Across spatial scales, there was very little support for models with structural habitat features, such as tree canopy cover and conifer diameter. Model-averaged 95% confidence intervals for regression coefficients and associated odds ratios indicated that the occurrence of Siskiyou Mountains salamanders was positively associated with rocky soils and Pacific madrone (Abutus menziesii) and negatively associated with elevation and white fir (Abies concolor); these associations were consistent across 3 spatial scales. The occurrence of this species also was positively associated with hardwood density at the medium spatial scale. Odds ratios projected that a 10% decrease in white fir abundance would increase the odds of salamander occurrence 3.02–4.47 times, depending on spatial scale. We selected the model with rocky soils, white fir, and Oregon white oak (Quercus garryana) as the best model across 3 spatial scales and created habitat suitability maps for Siskiyou Mountains salamanders by projecting habitat suitability scores across the landscape. Our habitat suitability models and maps are applicable to selection of priority conservation areas for Siskiyou Mountains salamanders, and our approach can be easily adapted to conservation of other rare species in any geographical location.     

Pond-Breeding Amphibian Species Richness and Habitat Selection in a Beaver-Modified Landscape

ABSTRACT Beaver (Castor canadensis) activity creates wetland habitats with varying hydroperiods important in maintaining habitat diversity for pond-breeding amphibians with significantly different breeding habitat requirements. We documented pond-breeding amphibian assemblages in 71 freshwater wetlands in Acadia National Park, Maine, USA. Using 15 variables describing local pond conditions and wetland landscape characteristics, we developed a priori models to predict sites with high amphibian species richness and used model selection with Akaike's Information Criterion to judge the strength of evidence supporting each model. We developed single-species models to predict wood frog (Rana sylvatica), bullfrog (R. catesbeiana), and pickerel frog (R. palustris) breeding site selection. Sites with high species richness were best predicted by 1) connectivity of wetlands in the landscape through stream corridors and 2) wetland modification by beaver. Wood frog breeding habitat was best predicted by temporary hydroperiod, lack of fish, and absence of current beaver activity. Wood frog breeding was present in abandoned beaver wetlands nearly as often as in nonbeaver wetlands. Bullfrog breeding was limited to active beaver wetlands with fish and permanent water. Pickerel frog breeding sites were best predicted by connectivity through stream corridors within the landscape. As beavers have recolonized areas of their former range in North America, they have increased the number and diversity of available breeding sites in the landscape for pond-breeding amphibians. The resulting mosaic of active and abandoned beaver wetlands both supports rich amphibian assemblages and provides suitable breeding habitat for species with differing habitat requirements. Land managers should consider the potential benefits of minimal management of beavers in promoting and conserving amphibian and wetland diversity at a landscape scale.     

Guild-specific responses of avian species richness to LiDAR-derived habitat heterogeneity

Ecological niche theory implies that more heterogeneous habitats have the potential to support greater biodiversity. Positive heterogeneity-diversity relationships have been found for most studies investigating animal taxa, although negative relationships also occur and the scale dependence of heterogeneity-diversity relationships is little known. We investigated multi-scale, heterogeneity-diversity relationships for bird communities in a semi-arid riparian landscape, using airborne LiDAR data to derive key measures of structural habitat complexity. Habitat heterogeneity-diversity relationships were generally positive, although the overall strength of relationships varied across avian life history guilds (R² range: 0.03–0.41). Best predicted were the species richness indices of cavity nesters, habitat generalists, woodland specialists, and foliage foragers. Heterogeneity-diversity relationships were also strongly scale-dependent, with strongest associations at the 200-m scale (4 ha) and weakest associations at the 50-m scale (0.25 ha). Our results underscore the value of LiDAR data for fine-grained quantification of habitat structure, as well as the need for biodiversity studies to incorporate variation among life-history guilds and to simultaneously consider multiple guild functional types (e.g. nesting, foraging, habitat). Results suggest that certain life-history guilds (foliage foragers, cavity nesters, woodland specialists) are more susceptible than others (ground foragers, ground nesters, low nesters) to experiencing declines in local species richness if functional elements of habitat heterogeneity are lost. Positive heterogeneity-diversity relationships imply that riparian conservation efforts need to not only provide high-quality riparian habitat locally, but also to provide habitat heterogeneity across multiple scales.     

Evaluating the ability of regional models to predict local avian abundance

Spatial modeling over broad scales can potentially direct conservation efforts to areas with high species-specific abundances. We examined the performance of regional models for predicting bird abundance at spatial scales typically addressed in conservation planning. Specifically, we used point count data on wood thrush (Hylocichla mustelina) and blue-winged warbler (Vermivora cyanoptera) from 2 time periods (1995–1998 and 2006–2007) to evaluate the ability of regional models derived via Bayesian hierarchical techniques to predict bird abundance. We developed models for each species within Bird Conservation Region (BCR) 23 in the upper midwestern United States at 800-ha, 8,000-ha, and approximately 80,000-ha scales. We obtained count data from the Breeding Bird Survey and land cover data from the National Land Cover Dataset (1992). We evaluated predictions from the best models, as defined by an information-theoretic criterion, using point count data collected within an ecological subregion of BCR 23 at 131 count stations in the 1990s and again in 2006–2007. Competing (Deviance Information Criteria <5) blue-winged warbler models accounted for 67% of the variability and suggested positive associations with forest edge and proportion of forest at the 8,000-ha scale, and negative associations with forest patch area (800 ha) and wetness (800 ha and 80,000 ha). The regional model performed best for blue-winged warbler predicted abundances from point counts conducted in Iowa during 1995–1996 (r_s = 0.57; P = 0.14), the survey period that most closely aligned with the time period of data used for regional model construction. Wood thrush models exhibited positive correlations with point count data for all survey areas and years combined (r_s = 0.58, P ≤ 0.001). In comparison, blue-winged warbler models performed worse as time increased between the point count surveys and vintage of the model building data (r_s = 0.03, P = 0.92 for Iowa and r_s = 0.13, P = 0.51 for all areas, 2006–2007), likely related to the ephemeral nature of their preferred early successional habitat. Species abundance and sensitivity to changing habitat conditions seems to be an important factor in determining the predictive ability of regional models. Hierarchical models can be a useful tool for concentrating efforts at the scale of management units and should be one of many tools used by land managers, but we caution that the utility of such models may decrease over time for species preferring relatively ephemeral habitats if model inputs are not updated accordingly. © 2012 The Wildlife Society.     

Occurrence of lemurs in landscapes and their species-specific scale responses to habitat loss

Studies on the impact of habitat loss on species occurrence consistently find that the amount of habitat (measured as patch area) is a major determinant of species occurrence at a patch-level. However, patch-level research may fail to detect important patterns and processes only observable at a landscape-level. A landscape-level approach that incorporates species-specific scale responses is needed to better understand what drives species occurrence. Our aim was to determine the landscape-level scale of effect of habitat amount on the occurrence of three species of nocturnal lemurs (Cheirogaleus medius, Microcebus murinus, and M. ravelobensis). We surveyed line transects to determine the occurrence of three lemur species within a fragmented landscape of deciduous dry forest and anthropogenic grassland in northwestern Madagascar. To determine the scale of effect of habitat loss on lemur occurrence, we compared logistic regression models of occurrence against habitat amount among eight different landscape scales using Akaike's Information Criterion values. We found differing scale responses among the lemurs in our study. Occurrence of C. medius responded to habitat amount at scales between 0.5–4 ha, M. murinus at scales between 1 and 4 ha and M. ravelobensis at scales between 0.125 and 4 ha. We suggest that the scale of effect for C. medius is mediated by their ability to hibernate. A relatively lower scale-response for Microcebus spp. likely reflect their omnivorous diet, small habitat requirements, and limited dispersal ability. Differences in scale responses between M. murinus and M. ravelobensis are likely a result of differing dispersal ability and responses to edge effects between these species. Our study is among the first on lemurs to show the value of a landscape-level approach when assessing the effects of habitat loss on species occurrence.     

Effects of ecogeographic variables on genetic variation in montane mammals: implications for conservation in a global warming scenario

Aim Evolutionary theory predicts that levels of genetic variation in island populations will be positively correlated with island area and negatively correlated with island isolation. These patterns have been empirically established for oceanic islands, but little is known about the determinants of variation on habitat islands. The goals of this study were twofold. Our first aim was to test whether published patterns of genetic variation in mammals occurring on montane habitat islands in the American Southwest conformed to expectations based on evolutionary theory. The second aim of this research was to develop simple heuristic models to predict changes in genetic variation that may occur in these populations as a result of reductions in available mountaintop habitat in response to global warming. Location Habitat islands of conifer forest on mountaintops in the American Southwest. Methods Relationships between island area and isolation with measures of allozyme variation in four species of small mammal, namely the least chipmunk (Tamias minimus), Colorado chipmunk (Tamias quadrivittatus), red squirrel (Tamiasciurus hudsonicus), and Mexican woodrat (Neotoma mexicana), were determined using correlation and regression techniques. Significant relationships between island area and genetic variation were used to develop three distinct statistical models with which to predict changes in genetic variation following reduction in insular habitat area arising from global warming. Results Patterns of genetic variation in each species conformed to evolutionary predictions. In general, island area was the most important determinant of heterozygosity, while island isolation was the most important determinant of polymorphism and allelic diversity. The heuristic models predicted widespread reductions in genetic variation, the extent of which depended on the population and model considered. Main conclusions The results support a generalized pattern of genetic variation for any species with an insular distribution, with reduced variation in smaller, more isolated populations. We predict widespread reductions in genetic variation in isolated populations of montane small mammals in the American Southwest as a result of global warming. We conclude that climate‐induced reductions in the various dimensions of genetic variation may increase the probability of population extinction in both the short and long term.     

The effect of woodland area on avian community composition in a fragmented southern UK landscape and associated management recommendations

ABSTRACT

Capsule: Smaller woodlands not only support fewer species but also show different avian community composition due to loss of woodland interior and an increase in edge habitat.

Aims: To use observed community composition changes, rather than traditional total species richness-area relationships, to make area-specific management recommendations for optimizing woodland habitat for avian communities in fragmented landscapes.

Methods: 17 woodlands were selected in Oxfordshire, UK, with areas between 0.2 and 120 ha. Three dawn area searches were conducted in each woodland between 1st April and 28th May 2016 to record encounter rates for each species. The impact of internal habitat variation on woodland comparability was assessed using habitat surveys.

Results: Woodlands with area less than 3.6 ha showed a significant positive relationship between total avian species richness and woodland area. Woodlands with area over 3.6 ha were all consistent with a mean (± se) total richness of 25.4?±?0.6 species, however the number of woodland specialists continued to increase with woodland area. Woodland generalists dominated the total encounter rate across the area range, however the fractional contribution of woodland specialists showed a significant positive correlation with woodland area, while the fractional contribution of non-woodland species significantly decreased. Non-woodland species numbers peaked in mid-sized woodlands with enhanced habitat heterogeneity.

Conclusions: Community composition analysis enabled more targeted recommendations than total species richness analysis, specifically: large woodlands (over 25?ha) in southern UK should focus conservation efforts on providing the specific internal habitats required by woodland specialists; medium-sized woodlands (between approximately 4 and 25?ha) should focus on promoting internal habitat variety, which can benefit both woodland species and non-woodland species of conservation concern in the surrounding landscape; small woodlands (under 4?ha) should focus on providing nesting opportunities for non-woodland species and on improving connectivity to maximize habitat for woodland generalists and facilitate movement of woodland specialists.     

Newer Classification and Regression Tree Techniques: Bagging and Random Forests for Ecological Prediction

The task of modeling the distribution of a large number of tree species under future climate scenarios presents unique challenges. First, the model must be robust enough to handle climate data outside the current range without producing unacceptable instability in the output. In addition, the technique should have automatic search mechanisms built in to select the most appropriate values for input model parameters for each species so that minimal effort is required when these parameters are fine-tuned for individual tree species. We evaluated four statistical models—Regression Tree Analysis (RTA), Bagging Trees (BT), Random Forests (RF), and Multivariate Adaptive Regression Splines (MARS)—for predictive vegetation mapping under current and future climate scenarios according to the Canadian Climate Centre global circulation model. To test, we applied these techniques to four tree species common in the eastern United States: loblolly pine (Pinus taeda), sugar maple (Acer saccharum), American beech (Fagus grandifolia), and white oak (Quercus alba). When the four techniques were assessed with Kappa and fuzzy Kappa statistics, RF and BT were superior in reproducing current importance value (a measure of basal area in addition to abundance) distributions for the four tree species, as derived from approximately 100,000 USDA Forest Service’s Forest Inventory and Analysis plots. Future estimates of suitable habitat after climate change were visually more reasonable with BT and RF, with slightly better performance by RF as assessed by Kappa statistics, correlation estimates, and spatial distribution of importance values. Although RTA did not perform as well as BT and RF, it provided interpretive models for species whose distributions were captured well by our current set of predictors. MARS was adequate for predicting current distributions but unacceptable for future climate. We consider RTA, BT, and RF modeling approaches, especially when used together to take advantage of their individual strengths, to be robust for predictive mapping and recommend their inclusion in the ecological toolbox.     

Testing alternative models for the conservation of koalas in fragmented rural–urban landscapes

Abstract Predicting the various responses of different species to changes in landscape structure is a formidable challenge to landscape ecology. Based on expert knowledge and landscape ecological theory, we develop five competing a priori models for predicting the presence/absence of the Koala (Phascolarctos cinereus) in Noosa Shire, south‐east Queensland (Australia). A priori predictions were nested within three levels of ecological organization: in situ (site level) habitat (<1 ha), patch level (100 ha) and landscape level (100–1000 ha). To test the models, Koala surveys and habitat surveys (n = 245) were conducted across the habitat mosaic. After taking into account tree species preferences, the patch and landscape context, and the neighbourhood effect of adjacent present sites, we applied logistic regression and hierarchical partitioning analyses to rank the alternative models and the explanatory variables. The strongest support was for a multilevel model, with Koala presence best predicted by the proportion of the landscape occupied by high quality habitat, the neighbourhood effect, the mean nearest neighbour distance between forest patches, the density of forest patches and the density of sealed roads. When tested against independent data (n = 105) using a receiver operator characteristic curve, the multilevel model performed moderately well. The study is consistent with recent assertions that habitat loss is the major driver of population decline, however, landscape configuration and roads have an important effect that needs to be incorporated into Koala conservation strategies.     

Distinguishing area and habitat heterogeneity effects on species richness: Birds in Victorian buloke remnants

Abstract Resolving whether area per se or habitat heterogeneity has the greater influence in controlling species richness remains a controversial yet important question. Here we show that avian species richness of same-sized transects (1 ha) is independent of the remnant area (of buloke woodland) within which a transect is positioned. We also show that avi-faunal similarity of pairs of transects randomly placed within the largest remnants (≥ 48 ha) is not consistently related to either proximity (i. e. being within the same remnant) nor to physiognomic characteristics of the transects. We believe that much of the controversy over area/habitat heterogeneity effects is probably related to scalar issues and propose a protocol by which some resolution of the question might be reached. The protocol involves ‘zoom’ sampling in which successively larger transect sizes are used, and measures of faunal richness and habitat heterogeneity are made at these different grains of resolution. One of our intentions is to stimulate discussion on how heterogeneity might be measured when grains increase from typical transect sizes (ca 1 ha) up to much larger grains (ca 128 ha).     

Relative accuracy of spatial predictive models for lynx Lynx canadensis derived using logistic regression-AIC,multiple criteria evaluation and Bayesian approaches

We compared probability surfaces derived using one set of environmental variables in three Geographic Information Systems (GIS) -based approaches: logistic regression and Akaike's Information Criterion (AIC),Multiple Criteria Evaluation (MCE),and Bayesian Analysis (specifically Dempster-Shafer theory). We used lynx Lynx canadensis as our focal species,and developed our environment relationship model using track data collected in Banff National Park,Alberta,Canada,during winters from 1997 to 2000. The accuracy of the three spatial models were compared using a contingency table method. We determined the percentage of cases in which both presence and absence points were correctly classified (overall accuracy),the failure to predict a species where it occurred (omission error) and the prediction of presence where there was absence (commission error). Our overall accuracy showed the logistic regression approach was the most accurate (74.51% ). The multiple criteria evaluation was intermediate (39.22%),while the Dempster-Shafer (D-S) theory model was the poorest (29.90%). However,omission and commission error tell us a different story: logistic regression had the lowest commission error,while D-S theory produced the lowest omission error. Our results provide evidence that habitat modellers should evaluate all three error measures when ascribing confidence in their model. We suggest that for our study area at least,the logistic regression model is optimal. However,where sample size is small or the species is very rare,it may also be useful to explore and/or use a more ecologically cautious modelling approach (e.g. Dempster-Shafer) that would over-predict,protect more sites,and thereby minimize the risk of missing critical habitat in conservation plans.     

Coexistence of protected avian predators: does a recovering population of White-tailed Eagle threaten to exclude other avian predators?

The processes of competition and predation determine the degree to which species can coexist; the importance of competition in particular has been emphasized at high trophic levels. Competition exclusion will occur when habitat overlap between sympatric species is high. In this study, we investigated nesting habitat overlap between internationally protected diurnal tree-nesting avian predators of central Europe, namely, White-tailed Eagle (Haliaeetus albicilla), Lesser Spotted Eagle (Aquila pomarina), Black Stork (Ciconia nigra), and Osprey (Pandion haliaetus). We found significantly different nesting habitats among the study species and suggest that this could be a consequence of the resource-based segregation, but not a consequence of asymmetrical interspecific competition. The results also show that habitat of the recovering populations of White-tailed Eagle overlapped with the habitat used by the Lesser Spotted Eagle, Black Stork, and Osprey to varying extents with a niche overlap values being below the competition exclusion threshold. Nevertheless, we suggest that competition by White-tailed Eagle at a population level may limit Osprey, though not Lesser Spotted Eagle or Black Stork.     

Land use and climate influences on waterbirds in the Prairie Potholes

Aim We examined the influences of regional climate and land‐use variables on mallard (Anas platyrhynchos), blue‐winged teal (Anas discors), ruddy duck (Oxyura jamaicensis) and pied‐billed grebe (Podilymbus podiceps) abundances to inform conservation planning in the Prairie Pothole Region of the United States. Location The US portion of Bird Conservation Region 11 (US‐BCR11, the Prairie Potholes), which encompasses six states within the United States: Montana, North Dakota, South Dakota, Nebraska, Minnesota and Iowa. Methods We used data from the North American Breeding Bird Survey (NABBS), the National Land Cover Data Set, and the National Climatic Data Center to model the effects of environmental variables on waterbird abundance. We evaluated land‐use covariates at three logarithmically related spatial scales (1000, 10,000 and 100,000 ha), and constructed hierarchical spatial count models a priori using information from published habitat associations. Model fitting was performed using a hierarchical modelling approach within a Bayesian framework. Results Models with the same variables expressed at different scales were often in the best model subset, indicating that the influence of spatial scale was small. Both land‐use and climate variables contributed strongly to predicting waterbird abundance in US‐BCR11. The strongest positive influences on waterbird abundance were the percentage of wetland area across all three spatial scales, herbaceous vegetation and precipitation variables. Other variables that we included in our models did not appear to influence waterbirds in this study. Main conclusions Understanding the relationships of waterbird abundance to climate and land use may allow us to make predictions of future distribution and abundance as environmental factors change. Additionally, results from this study can suggest locations where conservation and management efforts should be focused.     

Biogenic habitat creation affects biomass–diversity relationships in plant communities

Biogenic habitat creation refers to the ability of some organisms to create, maintain or destroy habitats. These habitat changes affect species diversity of natural communities, but it remains to be elucidated if this process also affects the link between ecosystem functions and species diversity. Based on the widely accepted positive relationships between ecosystem functions and species diversity, we hypothesize that these relationships should be different in biogenically created habitat patches as compared to unmodified habitat patches. We tested this hypothesis by assessing the effects of a high-Andean cushion plant, Azorella madreporica, which creates habitat patches with different environmental conditions than in the surrounding open areas with reduced vegetation cover. We used observational and experimental approaches to compare the plant biomass–species richness relationships between habitat patches created by A. madreporica cushions and the surrounding habitat without cushion plants. The observational assessment of these relationships was conducted by counting and collecting plant species within and outside cushion patches. In the experiment, species richness was manipulated within and outside cushion patches. The cushion plant itself was not included in these approaches because we were interested in measuring its effects. Results of both approaches indicated that, for a given level of species richness, plant biomass within cushions was higher than in the surrounding open areas. Furthermore, both approaches indicated that the shape of plant biomass–species richness curves differed between these habitat types. These findings suggest that habitat modifications performed by A. madreporica cushions would be positively affecting the relationships between ecosystem functions and species diversity.     

Ecological traits modulate bird species responses to forest fragmentation in an Amazonian anthropogenic archipelago

Aim

We assessed patterns of avian species loss and the role of morpho‐ecological traits in explaining species vulnerability to forest fragmentation in an anthropogenic island system. We also contrasted observed and detectability‐corrected estimates of island occupancy, which are often used to infer species vulnerability.

Location

Tucuruí Hydroelectric Reservoir, eastern Brazilian Amazonia.

Methods

We surveyed forest birds within 36 islands (3.4–2,551.5 ha) after 22 years of post‐isolation history. We applied species–area relationships to assess differential patterns of species loss among three data sets: all species, forest specialists and habitat generalists. After controlling for phylogenetic non‐independence, we used observed and detectability‐corrected estimates of island occupancy separately to build competing models as a function of species traits. The magnitude of the difference between these estimates of island occupancy was contrasted against species detectability.

Results

The rate of species loss as a function of island area reduction was higher for forest specialists than for habitat generalists. Accounting for the area effect, forest fragmentation did not affect the overall number of species regardless of the data set. Only the interactive model including natural abundance, habitat breadth and geographic range size was strongly supported for both estimates of island occupancy. For 30 species with detection probabilities below 30%, detectability‐corrected estimates were at least tenfold higher than those observed. Conversely, differences between estimates were negligible or non‐existent for all 31 species with detection probabilities exceeding 45.5%.

Main conclusions

Predicted decay of avian species richness induced by forest loss is affected by the degree of habitat specialisation of the species under consideration, and may be unrelated to forest fragmentation per se. Natural abundance was the main predictor of species island occupancy, although habitat breadth and geographic range size also played a role. We caution against using occupancy models for low‐detectability species, because overestimates of island occupancy reduce the power of species‐level predictions of vulnerability.

     

Species‐area relationships of lemurs in a fragmented landscape in Madagascar

We used species‐area relationships (SARs) to investigate the effects of habitat loss on lemur biogeography. We measured species richness via visual surveys on line transects within 42 fragments of dry deciduous forest at the Ambanjabe field site in Ankarafantsika National Park, Madagascar. We measured human disturbance and habitat characteristics within 38 of the 42 fragments. We measured the distance between each fragment and the nearest settlement, continuous forest, and nearest neighboring fragment. We fit 10 candidate SAR models to the data using nonlinear least squares regression and compared them using Akaike's Information Criterion (AIC). To determine how habitat characteristics, as well as area, influenced species richness, we ran a hierarchical partitioning procedure to select which variables to include in generalized additive models (GAMs) and compared them using AIC. Contrary to expectations, we found that lemurs form convex SARs, without a “small island effect”, and with the power model being the most likely SAR model. Although we found that four variables (area, survey effort, and total human disturbance, and mean tree height) independently contributed greater than 10% of the variation in lemur species richness, only area was included in the most likely model. We suggest that the power model was the most likely SAR model and our inability to detect a “small island effect” are the result of Microcebus spp. being edge tolerant and capable of dispersing through matrix, scale issues in the study design, and low γ‐diversity in the landscape. However, more study is needed to determine what role human disturbance plays in influencing species richness in lemurs.     

Modelling of landscape variables at multiple extents to predict fine sediments and suitable habitat for Tubifex tubifex in a stream system

1. Aggregations of fine sediments are a suitable proxy for the presence and abundance of Tubifex tubifex, one of the obligate hosts in the parasitic life cycle that causes salmonid whirling disease (Myxobolus cerebralis). 2. To determine and evaluate practical approaches to predict fine sediments (<2 mm diameter) that could support Tubifex spp. aggregations, we measured habitat features in a catchment with field measures and metrics derived from digital data sets and geospatial tools at three different spatial extents (m²) within a hierarchical structure. 3. We used linear mixed models to test plausible candidate models that best explained the presence of fine sediments measured in stream surveys with metrics from several spatial extents. 4. The percent slow water habitat measured at the finest extent provided the best model to predict the likely presence of fine sediments. The most influential models to predict fine sediments using landscape metrics measured at broader extents included variables that measure the percentage land cover in conifer or agriculture, specifically, decreases in conifer cover and increases in agriculture. 5. The overall best‐fitting model of the presence of fine sediments in a stream reach combined variables measured and operating at different spatial extents. 6. Landscape features modelled within a hierarchical framework may be useful tools to evaluate and prioritise areas with fine sediments that may be at risk of infection by Myxobolus cerebralis.     

Habitat Use of Sympatric Rattlesnake Species Within the Gulf Coastal Plain

Abstract: The eastern diamondback rattlesnake (Crotalus adamanteus) and timber rattlesnake (Crotalus horridus) are sympatric throughout most of southern Georgia, USA. We used rattlesnake sightings to quantify and compare habitat use by these 2 species in the Gulf Coastal Plain. At the largest scale examined, univariate statistics and logistic regression models indicated that eastern diamondback rattlesnakes were associated with roads but not with any of the specific habitat types we examined. In contrast, timber rattlesnakes were closely associated with hardwood habitat and riverine systems but not with roads and edges. To effectively conserve and manage both species in the Southeast, a habitat matrix of large intact patches of both hardwood and pine (Pinus spp.) forest may be necessary.     

Greater Sage-Grouse Nesting Habitat: The Importance of Managing at Multiple Scales

Abstract: Considering habitat selection at multiple scales is essential to fully understand habitat requirements and management needs for wildlife species of concern. We used a hierarchical information-theoretic approach and variance decomposition techniques to analyze habitat selection using local-scale habitat variables measured in the field and landscape-scale variables derived with a Geographic Information System (GIS) for nesting greater sage-grouse (Centrocercus urophasianus) in the Powder River Basin (PRB), Montana and Wyoming, USA, 2003–2007. We investigated relationships between habitat features that can and cannot be mapped in a GIS to provide insights into interpretation of landscape-scale—only GIS models. We produced models of habitat selection at both local and landscape scales and across scales, yet multiscale models had overwhelming statistical and biological support. Variance decomposition showed that local-scale measures explained the most pure variation (50%) in sage-grouse nesting-habitat selection. Landscape-scale features explained 20% of pure variation and shared 30% with local-scale features. Both local- and landscape-scale habitat features are important in sage-grouse nesting-habitat selection because each scale explained both pure and shared variation. Our landscape-scale model was accurate in predicting priority landscapes where sage-grouse nests would occur and is, therefore, useful in providing landscape context for management decisions. It accurately predicted locations of independent sage-grouse nests (validation R² = 0.99) and showed good discriminatory ability with >90% of nests located within only 40% of the study area. Our landscape-scale model also accurately predicted independent lek locations. We estimated twice the amount of predicted nesting habitat within 3 km of leks compared to random locations in the PRB. Likewise we estimated 1.8 times more predicted nesting habitat within 10 km of leks compared to random locations. These results support predictions of the hotspot theory of lek placement. Local-scale habitat variables that cannot currently be mapped in a GIS strongly influence sage-grouse nest-site selection, but only within priority nesting habitats defined at the landscape scale. Our results indicate that habitat treatments for nesting sage-grouse applied in areas with an unsuitable landscape context are unlikely to achieve desired conservation results.