Effect of fragmentation, habitat loss and within-patch habitat characteristics on ant assemblages in semi-arid woodlands of eastern Australia

The reliability of ants as bioindicators of ecosystem condition is dependent on the consistency of their response to localised habitat characteristics, which may be modified by larger-scale effects of habitat fragmentation and loss. We assessed the relative contribution of habitat fragmentation, habitat loss and within-patch habitat characteristics in determining ant assemblages in semi-arid woodland in Queensland, Australia. Species and functional group abundance were recorded using pitfall traps across 20 woodland patches in landscapes that exhibited a range of fragmentation states. Of fragmentation measures, changes in patch area and patch edge contrast exerted the greatest influence on species assemblages, after accounting for differences in habitat loss. However, 35% of fragmentation effects on species were confounded by the effects of habitat characteristics and habitat loss. Within-patch habitat characteristics explained more than twice the amount of species variation attributable to fragmentation and four times the variation explained by habitat loss. The study indicates that within-patch habitat characteristics are the predominant drivers of ant composition. We suggest that caution should be exercised in interpreting the independent effects of habitat fragmentation and loss on ant assemblages without jointly considering localised habitat attributes and associated joint effects. The State of Queensland's right to retain a non-exclusive, royalty free license in and to any copyright is acknowledged.     

Accessible habitat: an improved measure of the effects of habitat loss and roads on wildlife populations

Habitat loss is known to be the main cause of the current global decline in biodiversity, and roads are thought to affect the persistence of many species by restricting movement between habitat patches. However, measuring the effects of roads and habitat loss separately means that the configuration of habitat relative to roads is not considered. We present a new measure of the combined effects of roads and habitat amount: accessible habitat. We define accessible habitat as the amount of habitat that can be reached from a focal habitat patch without crossing a road, and make available a GIS tool to calculate accessible habitat. We hypothesize that accessible habitat will be the best predictor of the effects of habitat loss and roads for any species for which roads are a major barrier to movement. We conducted a case study of the utility of the accessible habitat concept using a data set of anuran species richness from 27 ponds near a motorway. We defined habitat as forest in this example. We found that accessible habitat was not only a better predictor of species richness than total habitat in the landscape or distance to the motorway, but also that by failing to consider accessible habitat we would have incorrectly concluded that there was no effect of habitat amount on species richness.     

Accessible habitat delineated by a highway predicts landscape-scale effects of habitat loss in an amphibian community

Context

Habitat loss and habitat fragmentation negatively affect amphibian populations. Roads impact amphibian species through barrier effects and traffic mortality. The landscape variable ‘accessible habitat’ considers the combined effects of habitat loss and roads on populations.

Objectives

The aim was to test whether accessible habitat was a better predictor of amphibian species richness than separate measures of road effects and habitat loss. I assessed how accessible habitat and local habitat variables determine species richness and community composition.

Methods

Frog and tadpole surveys were conducted at 52 wetlands in a peri-urban area of eastern Australia. Accessible habitat was delineated using a highway. Regressions were used to examine relationships between species richness and eleven landscape and local habitat variables. Redundancy analysis was used to examine relationships between community composition and accessible habitat and local habitat variables.

Results

Best-ranked models of species richness included both landscape and local habitat variables. There were positive relationships between species richness and accessible habitat and distance to the highway, and uncertain relationships with proportion cover of native vegetation and road density. There were negative relationships between species richness and concreted wetlands and wetland electrical conductivity. Four species were positively associated with accessible habitat, whereas all species were negatively associated with wetland type.

Conclusions

Barrier effects caused by the highway and habitat loss have negatively affected the amphibian community. Local habitat variables had strong relationships with species richness and community composition, highlighting the importance of both availability and quality of habitat for amphibian conservation near major roads.

     

Measuring habitat availability for dispersing animals

Understanding dispersal is central to ecology and evolution. To integrate habitat selection and dispersal it is important to compare habitat used for movement to those available in the landscape, i.e. found in an area that an animal could access in a given time period. Here, we explore ways of determining available habitat for dispersing individuals, illustrated by recent studies on habitat selection of dispersers.     

The use of native vegetation as a proxy for habitat may overestimate habitat availability in fragmented landscapes

Context

Native vegetation is often used as a proxy for habitat to estimate habitat availability in landscapes. This approach may lead to incorrect estimates of the impacts of habitat loss and fragmentation on species, which have not been thoroughly quantified so far.

Objectives

We quantified to what extent the loss of native vegetation reflect actual habitat loss by native species in landscapes. We tested the hypothesis that habitat availability declines at greater rates than native vegetation and thus is overestimated when it is quantified on the basis of native vegetation.

Methods

Using simulations, we quantified how the loss of native vegetation in artificial and real landscapes affects habitat availability for species with different habitat requirements. We contrasted a generalist species, which uses all native vegetation, with 10 habitat-specialist species classified into three categories (interior, patchy and riparian species).

Results

Habitat availability generally declined at greater rates than native vegetation for all specialist species. This pattern was apparent for different specialist species in a broad range of landscape types. Interior species always lost habitat availability more rapidly than the generalist species. Most riparian species lost habitat availability more rapidly than the generalist species. Responses of patchy species were more complex, depending on their dispersal abilities and landscape structure.

Conclusions

Habitat availability is likely to be overestimated when native vegetation is used as proxy for habitat, because habitat availability will generally decline at greater rates than native vegetation. Therefore, a species-centered approach should be adopted when estimating habitat availability in landscapes.

     

Connectivity change in habitat networks

Habitat management is essential for safeguarding important flora and fauna. Further, habitat connectivity is a crucial component for maintaining biodiversity given that it is known to have implications for species persistence. However, damage to habitat due to natural and human induced hazards can alter spatial relationships between habitats, potentially impacting biodiversity. Therefore, the susceptibility of spatial relationships to patch loss and associated connectivity degradation is obviously an important factor in maintaining existing or planned habitat networks. Identifying patches vital to connectivity is critical both for effectively prioritizing protection (e.g., enhancing habitat connectivity) and establishing disaster mitigation measures (e.g., stemming the spread of habitat loss). This paper presents a methodology for characterizing connectivity associated with habitat networks. Methods for evaluating habitat network connectivity change are formalized. Examples are presented to facilitate analysis of connectivity in the management of biodiversity.

Effects of spatial habitat heterogeneity on habitat selection and annual fecundity for a migratory forest songbird

Understanding how spatial habitat patterns influence abundance and dynamics of animal populations is a primary goal in landscape ecology. We used an information-theoretic approach to investigate the association between habitat patterns at multiple spatial scales and demographic patterns for black-throated blue warblers (Dendroica caerulescens) at 20 study sites in west-central Vermont, USA from 2002 to 2005. Sites were characterized by: (1) territory-scale shrub density, (2) patch-scale shrub density occurring within 25 ha of territories, and (3) landscape-scale habitat patterns occurring within 5 km radius extents of territories. We considered multiple population parameters including abundance, age ratios, and annual fecundity. Territory-scale shrub density was most important for determining abundance and age ratios, but landscape-scale habitat structure strongly influenced reproductive output. Sites with higher territory-scale shrub density had higher abundance, and were more likely to be occupied by older, more experienced individuals compared to sites with lower shrub density. However, annual fecundity was higher on sites located in contiguously forested landscapes where shrub density was lower than the fragmented sites. Further, effects of habitat pattern at one spatial scale depended on habitat conditions at different scales. For example, abundance increased with increasing territory-scale shrub density, but this effect was much stronger in fragmented landscapes than in contiguously forested landscapes. These results suggest that habitat pattern at different spatial scales affect demographic parameters in different ways, and that effects of habitat patterns at one spatial scale depends on habitat conditions at other scales.     

Implications of rescaling rules for multi-scaled habitat models

Recent work in landscape ecology suggests that organisms use environmental cues at a variety of scales to select habitat. As a result, habitat studies that evaluate environmental conditions at multiple spatial scales have become increasingly common. We examined whether the way in which data are rescaled influences inferred relationships between organisms and habitat features. Using a habitat model developed at fine scales, we systematically rescaled habitat (canopy density, slope, and cover type) and distribution maps according to a variety of different rescaling rules, including spatial averaging, thresholding, presence/absence, and majority. We found that the spatial autocorrelation of habitat data interacts with rescaling rules to alter the correspondence between species presence and habitat across scale. Different rules lead to substantially divergent and sometimes opposite correlations among the species and habitat features on the landscape. Such differences in interpretation due to variation in methodology can lead to very different interpretations of a species habitat requirements and thus have important implications for both ecology and conservation.     

Separating the effects of habitat area,fragmentation and matrix resistance on genetic differentiation in complex landscapes

Little is known about how variation in landscape mosaics affects genetic differentiation. The goal of this paper is to quantify the relative importance of habitat area and configuration, as well as the contrast in resistance between habitat and non-habitat, on genetic differentiation. We hypothesized that habitat configuration would be more influential than habitat area in influencing genetic differentiation. Population size is positively related to habitat area, and therefore habitat area should affect genetic drift, but not gene flow. In contrast, differential rates and patterns of gene flow across a landscape should be related to habitat configuration. Using spatially explicit, individual-based simulation modeling, we found that habitat configuration had stronger relationships with genetic differentiation than did habitat area, but there was a high degree of confounding between the effects of habitat area and configuration. We evaluated the predictive ability of six widely used landscape metrics and found that patch cohesion and correlation length of habitat are among the strongest individual predictors of genetic differentiation. Correlation length, patch density and clumpy are the most parsimonious set of variables to predict the magnitude of genetic differentiation in complex landscapes.     

A proximity-based approach to assessing habitat

Planning for either a single species, multiple species, or ecosystems is greatly dependent on spatial interactions in the landscape. Problems exist for evaluating wildlife habitat changes over large ranges of space and time. This paper illustrates the use of Geographic Information Systems (GIS) to evaluate habitat for a single species, ruffed grouse (Bonasa umbellus), following a time series of forest harvests. A habitat suitability model for ruffed grouse is utilized on a two-township study area in north-central Minnesota to assess the habitat suitability changes over time using an even-aged area-control harvesting plan. The results are presented as a habitat quality change map and a contingency table, representing the movement of habitat class areas between time periods resulting from the proposed harvesting. We developed a neighborhood definition to allow for spatially varying habitat values. This work illustrates the ability to look ahead and around in estimating the impact on wildlife habitat resulting from alternative future management activities.Now with the U.S. Forest Service, Sitka, AK 99835.     

A mathematical partitioning of the effects of habitat loss and habitat degradation on species abundance

Context

Worldwide, anthropogenic habitat loss and degradation have led to substantial biodiversity declines. Preserving biodiversity requires an understanding of how habitat loss and degradation interact to impact species populations, and how land-use decisions can limit these losses.

Objectives

We present a mathematical partitioning of changes in landscape-level population abundance in response to land-use change using a modified version of the Price equation from evolutionary biology.

Methods

The Price equation partitions changes in species abundance into multiple drivers related to habitat loss, habitat degradation, and their interaction. We describe its development and exemplify its applicability using simulated data.

Results

Applying the Price equation to simulated data reveals the roles of habitat loss, habitat degradation, and their interaction in driving population change in patchy landscapes undergoing complex land-use change processes.

Conclusions

The Price equation is a theoretical tool that may enhance our understanding of the effects of land-use change on populations by accounting for the specific processes by which land-use change operates across landscapes.

     

Multi-level,multi-scale habitat selection by a wide-ranging,federally threatened snake

Context

Although multi-scale approaches are commonly used to assess wildlife-habitat relationships, few studies have examined selection at multiple spatial scales within different hierarchical levels/orders of selection [sensu Johnson’s (1980) orders of selection]. Failure to account for multi-scale relationships within a single level of selection may lead to misleading inferences and predictions.

Objectives

We examined habitat selection of the federally threatened eastern indigo snake (Drymarchon couperi) in peninsular Florida at the level of the home range (Level II selection) and individual telemetry location (Level III selection) to identify influential habitat covariates and predict relative probability of selection.

Methods

Within each level, we identified the characteristic scale for each habitat covariate to create multi-scale resource selection functions. We used home range selection functions to model Level II selection and paired logistic regression to model Level III selection.

Results

At both levels, EIS selected undeveloped upland land covers and habitat edges while avoiding urban land covers. Selection was generally strongest at the finest scales with the exception of Level II urban edge which was avoided at a broad scale indicating avoidance of urbanized land covers rather than urban edge per se.

Conclusions

Our study illustrates how characteristic scales may vary within a single level of selection and demonstrates the utility of multi-level, scale-optimized habitat selection analyses. We emphasize the importance of maintaining large mosaics of natural habitats for eastern indigo snake conservation.

     

Thresholds in seascape connectivity: influence of mobility, habitat distribution, and current strength on fish movement

Assessing connectivity of the marine environment is a fundamental challenge for marine conservation and planning, yet conceptual development in habitat connectivity has been based on terrestrial examples rather than marine ecosystems. Here, we explore differences in marine environments that could affect localized movement of marine organisms and demonstrate the importance of incorporating them into seascape models. We link a fish-based cost surface model to simulated seascapes to test hypotheses about the effects of fish mobility, water current strength, and their interactions on functional connectivity of a seascape. Our models predict that sedentary fish should be more sensitive to habitat change than more mobile fish. Furthermore, highly mobile fish should be more sensitive to water currents than habitat change. In our models, the cost of swimming against a current (of any strength) exceeded its benefits, resulting in overall decreases in connectivity with increasing current strengths. We further hypothesized that thresholds in functional connectivity will be affected by both fish mobility and water current strength. Connectivity thresholds in the models occurred when 10–50 % of benthic habitat was favourable; below these thresholds there was a rapid increase in path cost. Thresholds were influenced by the interaction of relative habitat costs (simulated fish mobility) and habitat fragmentation: thresholds for less mobile fish (higher relative cost) were reached at lower habitat abundance when habitat was fragmented, while thresholds for mobile fish were less affected by fragmentation. Our approach suggests mobility and water current are useful indicators of connectivity in marine environments and should be incorporated in seascape models.     

Grain-dependent functional responses in habitat selection

Context

Spatial scale is an important consideration for understanding how animals select habitat, and multi-scalar designs in resource selection studies have become increasingly common. Despite this, examination of functional responses in habitat selection at multiple scales is rare. The perceptual range of an animal changes as a function of vegetation association, suggesting that use, selection and functional responses may all be habitat- and scale-dependent.

Objectives

Our objective was to determine how varying grain size affects our interpretation of functional response in habitat selection and to elucidate scalar and landscape effects on habitat selection.

Methods

We quantified the functional response of GPS-collared, female white-tailed deer (Odocoileus virginianus, n = 18) in Riding Mountain National Park, Canada, to different habitat types. Functional responses were quantified at multiple spatial scales by regressing proportion of habitat used against proportion of habitat available at different buffer radii (ranging from 75–1000 m radius) surrounding used (telemetry) locations and available points within the individual’s seasonal home range. We examined how functional responses changed as a function of grain by plotting grain size against the slope of the functional response.

Results

We detected functional responses in most habitat types. As expected, functional responses tended to converge towards 1 (use proportional to availability) at large buffer sizes; however, the relationship between scale and functional response was typically non-linear and depended on habitat type.

Conclusions

We conclude that a multi-scalar approach to modelling animal functional responses in habitat selection is important for understanding patterns in animal behaviour and resource use.

     

An integration of habitat evaluation,individual based modeling,and graph theory for a potential black bear population recovery in southeastern Texas,USA

Population recovery is difficult for species that require large contiguous areas of habitat, particularly within areas of heterogeneous land ownerships. Ecologically, potential for recovery success requires assessment of quantity, quality, and distribution of available habitat. Our objective was to evaluate habitat for a possible Louisiana black bear recovery in southeastern Texas. First, we categorized land cover and identified remote areas of highly suitable habitat. Next, we used the individual based simulation model J-walk to estimate ability of female black bears to move among remote habitat patches. Then, we applied graph theory to J-walk output to evaluate overall connectivity of remote habitat. An estimated 225,626 ha of remote habitat were identified in 901 patches, most of which was located within the eastern half of the study area. Network analysis showed specific areas where targeted conservation efforts may help black bear population expansion throughout the study region. Ultimately, enough habitat area exists to sustain a black bear population and it is best connected among public and private lands largely within the eastern half of the study area. Habitat evaluation will need to be revisited if black bears establish themselves locally and actual habitat use data become available. Regardless, our analysis demonstrates an important first step that may be incorporated into a larger adaptive management framework, updated, and replicated as more-detailed habitat suitability and land use data are available.     

Modeling habitat dynamics accounting for possible misclassification

Land cover data are widely used in ecology as land cover change is a major component of changes affecting ecological systems. Landscape change estimates are characterized by classification errors. Researchers have used error matrices to adjust estimates of areal extent, but estimation of land cover change is more difficult and more challenging, with error in classification being confused with change. We modeled land cover dynamics for a discrete set of habitat states. The approach accounts for state uncertainty to produce unbiased estimates of habitat transition probabilities using ground information to inform error rates. We consider the case when true and observed habitat states are available for the same geographic unit (pixel) and when true and observed states are obtained at one level of resolution, but transition probabilities estimated at a different level of resolution (aggregations of pixels). Simulation results showed a strong bias when estimating transition probabilities if misclassification was not accounted for. Scaling-up does not necessarily decrease the bias and can even increase it. Analyses of land cover data in the Southeast region of the USA showed that land change patterns appeared distorted if misclassification was not accounted for: rate of habitat turnover was artificially increased and habitat composition appeared more homogeneous. Not properly accounting for land cover misclassification can produce misleading inferences about habitat state and dynamics and also misleading predictions about species distributions based on habitat. Our models that explicitly account for state uncertainty should be useful in obtaining more accurate inferences about change from data that include errors.     

The concept of habitat specificity revisited

Habitat specificity indices reflect richness (α) and/or distinctiveness (β) components of diversity. The latter may be defined by α and γ (landscape) diversity in two alternative ways: multiplicatively () and additively (). We demonstrate that the original habitat specificity concept of Wagner and Edwards (Landscape Ecol 16:121–131, 2001) consists of three independent components: core habitat specificity (uniqueness of the species composition), patch area and patch species richness. We describe habitat specificity as a family of indices that may include either area or richness components, or none or both, and open for use of different types of mean in calculation of core habitat specificity. Core habitat specificity is a beta diversity measure: the effective number of completely distinct communities in the landscape. Habitat specificity weighted by species number is a gamma diversity measure: the effective number of species that a patch contributes to landscape richness. We compared 12 habitat specificity indices by theoretical reasoning and by use of field data (vascular plant species in SE Norwegian agricultural landscapes). Habitat specificity indices are strongly influenced by weights for patch area and patch species richness, and the relative contribution of rare vs. common species (type of mean). The relevance of properties emphasized by each habitat specificity index for evaluation of patches in a biodiversity context is discussed. Core habitat specificity is emphasized as an ecologically interpretable measure that specifically addresses patch uniqueness while habitat specificity weighted by species number combines species richness and species composition in ways relevant for conservation biological assessment. Electronic supplementary material  The online version of this article (doi:) contains supplementary material, which is available to authorized users.     

Impact of land use compactness on the habitat services from green infrastructure in Wuhan,China

As an important carrier of biodiversity, green infrastructure (GI) is significantly affected by changes in urban land use in the process of urbanization. In this study, habitat services from GI were used to represent biodiversity support services, and geographic information system (GIS), remote sensing and statistical analysis were combined to analyze the changes in urban land use compactness and GI habitat services in Wuhan in 2005, 2013 and 2018. Seven indices for land use compactness mainly covering three aspects (land use morphology, land use intensity and land function layout) were selected to explore the correlation and regression relationships between urban land use compactness and habitat services on a grid scale. The results show that: i) The urban land use in Wuhan presents a compact development trend except for the degree of integration; and habitat services decrease along with increasing land use compactness. ii) Relative to land use morphology and land function layout, land use intensity is a more prominent factor affecting habitat services, with construction land density and residential land density always being significant indicators for the habitat pattern. iii) Urban areas with different degrees of land use compactness tend to have different indices that affect the habitat services. Therefore, differential urban development strategies should be formulated based on the regional characteristics of land use compactness levels, so as to coordinate urban compact land use and biodiversity conservation.     

Landscape and habitat filters jointly drive richness and abundance of specialist plants in terrestrial habitat islands

Context

Landscape and habitat filters are major drivers of biodiversity of small habitat islands by influencing dispersal and extinction events in plant metapopulations.

Objectives

We assessed the effects of landscape and habitat filters on the species richness, abundance and trait composition of grassland specialist and generalist plants in small habitat islands. We studied traits related to functional spatial connectivity (dispersal ability by wind and animals) and temporal connectivity (clonality and seed bank persistence) using model selection.

Methods

We sampled herbaceous plants, landscape (local and regional isolation) and habitat filters (inclination, woody encroachment and disturbance) in 82 grassland islands in Hungary.

Results

Isolation decreased the abundance of good disperser specialist plants due to the lack of directional vectors transferring seeds between suitable habitat patches. Clonality was an effective strategy, but persistent seed bank did not support the survival of specialist plants in isolated habitats. Generalist plants were unaffected by landscape filters due to their wide habitat breadth and high propagule availability. Clonal specialist plants could cope with increasing woody encroachment due to their high resistance against environmental changes; however, they could not cope with intensive disturbance. Steep slopes providing environmental heterogeneity had an overall positive effect on species richness.

Conclusions

Specialist plants were influenced by the interplay of landscape filters influencing their abundance and habitat filters affecting species richness. Landscape filtering by isolation influenced the abundance of specialist plants by regulating seed dispersal. Habitat filters sorted species that could establish and persist at a site by influencing microsite availability and quality.