Estimating landscape resistance from habitat suitability: effects of data source and nonlinearities

Context

Conservation corridors must facilitate long-distance dispersal movements to promote gene flow, prevent inbreeding, and allow animals to shift ranges with climate change. Least-cost models are used to identify areas that support long-distance movement. These models rely on estimates of landscape resistance, which are typically derived from habitat suitability.

Objectives

We examine two key steps in estimating resistance from habitat suitability: choosing a procedure to estimate habitat suitability, and choosing a transformation function to translate habitat suitability into resistance.

Methods

We used linear and nonlinear functions to convert three types of habitat suitability estimates (from expert opinion, resource selection functions, and step selection functions) into resistances for elk (Cervus canadensis) and desert bighorn sheep (Ovis canadensis nelsoni). We evaluated the resulting resistance maps on an independent set of observed long-distance, prospecting movements.

Results

A negative exponential function best described the relationship between resistance values and habitat suitability for desert bighorn sheep indicating long-distance movers readily travel through moderately-suitable areas and avoid only the least suitable habitat. For desert bighorn sheep, all three suitability estimates performed better than chance, and resource and step selection functions outperformed expert opinion. For elk, all three suitability estimates performed the same as chance.

Conclusions

When designing corridors to facilitate long-distance movements of mobile animals, we recommend transforming habitat suitability into resistance with a negative exponential function. Use of an exponential transformation means that larger fractions of the landscape offer low resistance, allowing greater flexibility in where a corridor is located.

     

Prioritization of habitat patches for landscape connectivity conservation differs between least-cost and resistance distances

Context

Methods quantifying habitat patch importance for maintaining habitat network connectivity have been emphasized in helping to prioritize conservation actions. Functional connectivity is accepted as depending on landscape resistance, and several measures of functional inter-patch distance have been designed. However, how the inter-patch distance, i.e., based on least-cost path or multiple paths, influences the identification of key habitat patches has not been explored.

Objectives

We compared the prioritization of habitat patches according to least-cost distance (LCD) and resistance distance (RD), using common binary and probabilistic connectivity metrics.

Methods

Our comparison was based on a generic functional group of forest mammals with different dispersal distances, and was applied to two landscapes differing in their spatial extent and fragmentation level.

Results

We found that habitat patch prioritization did not depend on distance type when considering the role of patch as contributing to dispersal fluxes. However, the role of patch as a connector facilitating dispersal might be overestimated by LCD-based indices compared with RD for short- and medium-distance dispersal. In particular, when prioritization was based on dispersal probability, the consideration of alternatives routes identified the connectors that probably provided functional connectivity for species in the long term. However, the use of LCD might help identify landscape areas that need critical restoration to improve individual dispersal.

Conclusions

Our results provide new insights about the way that inter-patch distance is viewed changes the evaluation of functional connectivity. Accordingly, prioritization methods should be carefully selected according to assumptions about population functioning and conservation aims.

     

Characterising landscape connectivity for conservation planning using a dispersal guild approach

Context

Land use changes have modified the extent and structure of native vegetation, resulting in fragmentation of native species habitat. Connectivity is increasingly seen as a requirement for effective conservation in these landscapes, but the question remains: ‘connectivity for which species?’.

Objective

The aim of this study was to develop and then apply a rapid, expert-based, dispersal guild approach where species are grouped on similar fine-scale dispersal behaviour (such as between scattered trees) and habitat characteristics.

Methods

Dispersal guilds were identified using clustering techniques to compare dispersal and habitat parameters elicited from experts. We modelled least-cost paths and corridors between patches and individual movement probabilities within these corridors for each of the dispersal guilds using Circuitscape. We demonstrate our approach with a case study in the Tasmanian Northern Midlands, Australia.

Results

The dispersal guild approach grouped the 12 species into five dispersal guilds. The connectivity modelling of those five guilds found that broadly dispersing species in this landscape, such as medium-sized carnivorous mammals, were unaffected by fragmentation while from the perspective of the three dispersal guilds made up of smaller mammals, the landscape appeared highly fragmented.

Conclusions

Our approach yields biologically defensible outputs that are broadly applicable, particularly for conservation planning where data and resources are limited. It is a useful first step in multi-species conservation planning which aims to identify those species most in need of conservation efforts.

     

A multi-method approach to delineate and validate migratory corridors

Context

Managers are faced with numerous methods for delineating wildlife movement corridors, and often must make decisions with limited data. Delineated corridors should be robust to different data and models.

Objectives

We present a multi-method approach for delineating and validating wildlife corridors using multiple data sources, which can be used conserve landscape connectivity. We used this approach to delineate and validate migration corridors for wildebeest (Connochaetes taurinus) in the Tarangire Ecosystem of northern Tanzania.

Methods

We used two types of locational data (distance sampling detections and GPS collar locations), and three modeling methods (negative binomial regression, logistic regression, and Maxent), to generate resource selection functions (RSFs) and define resistance surfaces. We compared two corridor detection algorithms (cost-distance and circuit theory), to delineate corridors. We validated corridors by comparing random and wildebeest locations that fell within corridors, and cross-validated by data type.

Results

Both data types produced similar RSFs. Wildebeest consistently selected migration habitat in flatter terrain farther from human settlements. Validation indicated three of the combinations of data type, modeling, and corridor detection algorithms (detection data with Maxent modeling, GPS collar data with logistic regression modeling, and GPS collar data with Maxent modeling, all using cost-distance) far outperformed the other seven. We merged the predictive corridors from these three data-method combinations to reveal habitat with highest probability of use.

Conclusions

The use of multiple methods ensures that planning is able to prioritize conservation of migration corridors based on all available information.

     

Assessing differences in connectivity based on habitat versus movement models for brown bears in the Carpathians

Context

Connectivity assessments typically rely on resistance surfaces derived from habitat models, assuming that higher-quality habitat facilitates movement. This assumption remains largely untested though, and it is unlikely that the same environmental factors determine both animal movements and habitat selection, potentially biasing connectivity assessments.

Objectives

We evaluated how much connectivity assessments differ when based on resistance surfaces from habitat versus movement models. In addition, we tested how sensitive connectivity assessments are with respect to the parameterization of the movement models.

Methods

We parameterized maximum entropy models to predict habitat suitability, and step selection functions to derive movement models for brown bear (Ursus arctos) in the northeastern Carpathians. We compared spatial patterns and distributions of resistance values derived from those models, and locations and characteristics of potential movement corridors.

Results

Brown bears preferred areas with high forest cover, close to forest edges, high topographic complexity, and with low human pressure in both habitat and movement models. However, resistance surfaces derived from the habitat models based on predictors measured at broad and medium scales tended to underestimate connectivity, as they predicted substantially higher resistance values for most of the study area, including corridors.

Conclusions

Our findings highlighted that connectivity assessments should be based on movement information if available, rather than generic habitat models. However, the parameterization of movement models is important, because the type of movement events considered, and the sampling method of environmental covariates can greatly affect connectivity assessments, and hence the predicted corridors.

     

Using multiple metrics to estimate seasonal landscape connectivity for Blanding’s turtles (<Emphasis Type="Italic">Emydoidea blandingii</Emphasis>) in a fragmented landscape

Context

Landscapes and animal behavior can exhibit temporal variability and connectivity estimates should consider this phenomenon. In many species, timing of activities such as nesting, mate searching, and hibernation occurs during distinct periods in which movement events may differ, along with physical characteristics of the surrounding landscape.

Objectives

We estimate movement, landscape conductance, and patch importance for a turtle species across two seasonal activity periods (spring, late summer) in a fragmented agricultural region. Three connectivity approaches are compared to identify their advantages and disadvantages.

Methods

A least-cost distance model, circuit-based approach, and patch-based index were used to collectively describe the potential functional connectivity of Blanding’s turtle (Emydoidea blandingii) across a multi-temporal scale in an agricultural region of south western Ontario.

Results

Connectivity decreased further into the active season exhibited through lower conductance of the landscape and fewer pathways, while the importance of habitat nodes shifted due to temporal variability in the number and distribution of nodes. Models provided different yet complimentary information, with least-cost models overestimating discrete pathways yet providing a secondary measure of landscape barriers. The circuit-based model estimated corridors of least resistance providing an overall characterization of the landscape, while patch-based indices provided key information on the importance of individual habitat patches.

Conclusion

Findings highlight the importance of including a temporal aspect in connectivity modelling as results demonstrate a change in functional connectivity over time. We also recommend employing multiple connectivity metrics to capture variation in movement behavior.

     

A multi-scale assessment of population connectivity in African lions (<Emphasis Type="Italic">Panthera leo)</Emphasis> in response to landscape change

Context

Habitat loss and fragmentation are among the major drivers of population declines and extinction, particularly in large carnivores. Connectivity models provide practical tools for assessing fragmentation effects and developing mitigation or conservation responses. To be useful to conservation practitioners, connectivity models need to incorporate multiple scales and include realistic scenarios based on potential changes to habitat and anthropogenic pressures. This will help to prioritize conservation efforts in a changing landscape.

Objectives

The goal of our paper was to evaluate differences in population connectivity for lions (Panthera leo) across the Kavango-Zambezi Trans-frontier Conservation Area (KAZA) under different landscape change scenarios and a range of dispersal distances.

Methods

We used an empirically optimized resistance surface, based on analysis of movement pathways of dispersing lions in southern Africa to calculate resistant kernel connectivity. We assessed changes in connectivity across nine landscape change scenarios, under each of which we explored the behavior of lions with eight different dispersal abilities.

Results

Our results demonstrate that reductions in the extent of the protected area network and/or fencing protected areas will result in large declines in the extent of population connectivity, across all modeled dispersal abilities. Creation of corridors or erection of fences strategically placed to funnel dispersers between protected areas increased overall connectivity of the population.

Conclusions

Our results strongly suggest that the most effective means of maintaining long-term population connectivity of lions in the KAZA region involves retaining the current protected area network, augmented with protected corridors or strategic fencing to direct dispersing individuals towards suitable habitat and away from potential conflict areas.

     

Enhancing connectivity in agroecosystems: focus on the best existing corridors or on new pathways?

Context

Restoring or establishing corridors between residual forest patches is one of the most adopted strategies for the conservation of animal populations and ecosystem processes in fragmented landscapes.

Objectives

This study aimed to assess whether it is more effective to focus restoration actions on existing corridors or to establish habitats in other strategic areas that can create new dispersal pathways to enhance connectivity.

Methods

We considered a real agroecosystem in northern Italy, based our analyses on graph-theory and habitat availability metrics, and focused on the Hazel Dormouse as the target species. We compared the connectivity increase resulting from (i) the simulated restoration of existing priority corridors, i.e., those with significant presence of forest but in which restoration actions would still result in considerable connectivity gains, or (ii) the simulated plantation of 30 hedgerows along new priority pathways, i.e., those areas with no current forest cover in which habitat creation would be more beneficial for connectivity.

Results

Implementing new priority pathways resulted in substantially larger connectivity gains (+?38%) than when restoration efforts were concentrated in improving already existing corridors (+?11%).

Conclusions

Establishing hedgerows along new pathways allowed enhancing the complementary and functionality of the full set of landscape corridors and proved more efficient than just strengthening the areas where dispersal flows were already concentrated. We demonstrated the importance of analytical procedures able to compare the effectiveness of different management strategies for enhancing connectivity. Our approach may be applied to multiple species sensitive to fragmentation in other heterogeneous landscapes and geographical contexts.

     

Integrating a generic focal species,metapopulation capacity,and connectivity to identify opportunities to link fragmented habitat

Context

A challenge devising revegetation strategies in fragmented landscapes is conserving for the widest spectrum of biodiversity. Habitat network reconstruction should improve landscape capacity to maintain species populations. However, the location of revegetation often fails to account for species occurrence and dispersal processes operating across spatial scales.

Objectives

Our objective was to integrate metapopulation theory with estimates of landscape capacity and dispersal pathways to highlight connectivity gaps. Maintenance of populations could thereby be facilitated through reconnecting habitat networks across regional and broader scales, with assumed benefit for the dispersal needs of less sensitive species.

Methods

Predicted occupancy and metapopulation capacity were calculated for a generic focal species derived from fragmentation-sensitive woodland birds, mammals and reptiles. A metapopulation connectivity analysis predicted regional dispersal links to identify likely routes through which individuals may move to contribute to the viability of the population. We used the revegetation programmes of the Brigalow–Nandewar Biolinks project, eastern New South Wales, Australia, to demonstrate our approach.

Results

Landscape capacity of the current landscape varied across the region. Low-value links between populations provided greatest opportunities for revegetation and improved landscape capacity. Where regional connectivity did not indicate a pathway between populations, broader scale connectivity provided guidance for revegetation.

Conclusions

The metapopulation-based model, coupled with a habitat dispersal network analysis, provided a platform to inform revegetation locations and better support biodiversity. Our approach has application for directing on-ground action to support viable populations, assess the impact of revegetation schemes or monitor the progress of staged implementations.

     

How do field margins contribute to the functional connectivity of insect-pollinated plants?

Context

Habitat fragmentation generates a loss of functional connectivity detrimental to the persistence of biodiversity. The French agricultural intensification initiated in the 1950s has caused a decline in field margins.

Objectives

As field margins may facilitate species dispersal while providing socio-economic benefits, it is of interest to assess their contribution to the functional connectivity of insect-pollinated plants in agro-ecosystems. This will help develop appropriate management strategies mitigating fragmentation.

Methods

We addressed this issue by studying the links between landscape structure and the patterns of abundance and pollen dispersal (using fluorescent dye particles) for two contrasted insect-pollinated plants occurring in field margins (Crepis sancta and Euphorbia serrata). We investigated the influence of field margins quality and of the surrounding matrix on pollen dispersal and compared the relevance of the least-cost algorithm with a straight-line approach to depict pollinators’ movements.

Results

The influence of landscape structure on plant abundance is species and scale-specific. Pollen dispersal decreases with distance from the source. For E. serrata, it was preferentially dispersed via field margins, confirming the relevance of the least-cost algorithm, while C. sancta dispersal followed a straight-line.

Conclusions

Euphorbia serrata, which grows strictly on field margins with a greater dispersal ability and a more diversified pollinator guild than C. sancta, is less affected by land-use changes. Our study demonstrates the contrasting contributions of field margins to pollen dispersal as they may act as functional corridors favouring pollinators’ movement depending on the species of interest.

     

Can we face different types of storms under the same umbrella? Efficiency and consistency of connectivity umbrellas across different patchy landscape patterns

Context

The umbrella approach applied to landscape connectivity is based on the principle that the conservation or restoration of the dispersal habitats for some species also can facilitate the movement of others. Species traits alone do not seem to be enough to identify good connectivity umbrella species, showing the need to investigate the influence of additional factors on this property.

Objectives

We test whether the potential of a species as a connectivity umbrella can be influenced by landscape composition and configuration.

Methods

We simulated movement routes for eight hypothetical species in artificial patchy landscapes with different levels of fragmentation, habitat amount and matrix permeability. We determined the effectiveness of the connectivity umbrella of the virtual species using pairwise intersections of important habitats for their movements in all landscapes.

Results

The connectivity umbrella performance of all species was affected by the interaction of fragmentation level and habitat amount. In general, species performance increased with decreasing fragmentation and increasing habitat amount. In most landscapes and considering the same dispersal threshold, species able to move more easily through the matrix showed higher umbrella performance than those for which the matrix offered greater resistance.

Conclusions

The connectivity umbrella is not a static feature that depends only on the species traits, but rather a dynamic property that also varies according to the landscape attributes. Therefore, we do not recommend spatial transferability of the connectivity umbrella species identified in a landscape to others that have divergent levels of fragmentation and habitat quantity.

     

Examining speed versus selection in connectivity models using elk migration as an example

Context

Landscape resistance is vital to connectivity modeling and frequently derived from resource selection functions (RSFs). RSFs estimate relative probability of use and tend to focus on understanding habitat preferences during slow, routine animal movements (e.g., foraging). Dispersal and migration, however, can produce rarer, faster movements, in which case models of movement speed rather than resource selection may be more realistic for identifying habitats that facilitate connectivity.

Objective

To compare two connectivity modeling approaches applied to resistance estimated from models of movement rate and resource selection.

Methods

Using movement data from migrating elk, we evaluated continuous time Markov chain (CTMC) and movement-based RSF models (i.e., step selection functions [SSFs]). We applied circuit theory and shortest random path (SRP) algorithms to CTMC, SSF and null (i.e., flat) resistance surfaces to predict corridors between elk seasonal ranges. We evaluated prediction accuracy by comparing model predictions to empirical elk movements.

Results

All connectivity models predicted elk movements well, but models applied to CTMC resistance were more accurate than models applied to SSF and null resistance. Circuit theory models were more accurate on average than SRP models.

Conclusions

CTMC can be more realistic than SSFs for estimating resistance for fast movements, though SSFs may demonstrate some predictive ability when animals also move slowly through corridors (e.g., stopover use during migration). High null model accuracy suggests seasonal range data may also be critical for predicting direct migration routes. For animals that migrate or disperse across large landscapes, we recommend incorporating CTMC into the connectivity modeling toolkit.

     

Using step and path selection functions for estimating resistance to movement: pumas as a case study

Context

GPS telemetry collars and their ability to acquire accurate and consistently frequent locations have increased the use of step selection functions (SSFs) and path selection functions (PathSFs) for studying animal movement and estimating resistance. However, previously published SSFs and PathSFs often do not accommodate multiple scales or multi-scale modeling.

Objectives

We present a method that allows multiple scales to be analyzed with SSF and PathSF models. We also explore the sensitivity of model results and resistance surfaces to whether SSFs or PathSFs are used, scale, prediction framework, and GPS collar sampling interval.

Methods

We use 5-min GPS collar data from pumas (Puma concolor) in southern California to model SSFs and PathSFs at multiple scales, to predict resistance using two prediction frameworks (paired and unpaired), and to explore potential bias from GPS collar sampling intervals.

Results

Regression coefficients were extremely sensitive to scale and pumas exhibited multiple scales of selection during movement. We found PathSFs produced stronger regression coefficients, larger resistance values, and superior model performance than SSFs. We observed more heterogeneous surfaces when resistance was predicted in a paired framework compared with an unpaired framework. Lastly, we observed bias in habitat use and resistance results when using a GPS collar sampling interval longer than 5 min.

Conclusions

The methods presented provide a novel way to model multi-scale habitat selection and resistance from movement data. Due to the sensitivity of resistance surfaces to method, scale, and GPS schedule, care should be used when modeling corridors for conservation purposes using these methods.

     

Past and predicted future effects of housing growth on open space conservation opportunity areas and habitat connectivity around National Wildlife Refuges

Context

Housing growth can alter suitability of matrix habitats around protected areas, strongly affecting movements of organisms and, consequently, threatening connectivity of protected area networks.

Objectives

Our goal was to quantify distribution and growth of housing around the U.S. Fish and Wildlife Service National Wildlife Refuge System. This is important information for conservation planning, particularly given promotion of habitat connectivity as a climate change adaptation measure.

Methods

We quantified housing growth from 1940 to 2000 and projected future growth to 2030 within three distances from refuges, identifying very low housing density open space, “opportunity areas” (contiguous areas with <6.17 houses/km²), both nationally and by USFWS administrative region. Additionally, we quantified number and area of habitat corridors within these opportunity areas in 2000.

Results

Our results indicated that the number and area of open space opportunity areas generally decreased with increasing distance from refuges and with the passage of time. Furthermore, total area in habitat corridors was much lower than in opportunity areas. In addition, the number of corridors sometimes exceeded number of opportunity areas as a result of habitat fragmentation, indicating corridors are likely vulnerable to land use change. Finally, regional differences were strong and indicated some refuges may have experienced so much housing growth already that they are effectively too isolated to adapt to climate change, while others may require extensive habitat restoration work.

Conclusions

Wildlife refuges are increasingly isolated by residential housing development, potentially constraining the movement of wildlife and, therefore, their ability to adapt to a changing climate.

     

Synthetic Aperture Radar (SAR) images improve habitat suitability models

Context

The ability to detect ecological networks in landscapes is of utmost importance for managing biodiversity and planning corridors.

Objectives

The objective of this study was to evaluate the information provided by a synthetic aperture radar (SAR) image for landscape connectivity modeling compared to aerial photographs (APs).

Methods

We present a novel method that integrates habitat suitability derived from remote sensing imagery into a connectivity model to explain species abundance. More precisely, we compared how two resistance maps constructed using landscape and/or local metrics derived from AP or SAR imagery yield different connectivity values (based on graph theory), considering hedgerow networks and forest carabid beetle species as a model.

Results

We found that resistance maps using landscape and local metrics derived from SAR imagery improve landscape connectivity measures. The SAR model is the most informative, explaining 58% of the variance in forest carabid beetle abundance. This model calculates resistance values associated with homogeneous patches within hedgerows according to their suitability (canopy cover density and landscape grain) for the model species.

Conclusions

Our approach combines two important methods in landscape ecology: the construction of resistance maps and the use of buffers around sampling points to determine the importance of landscape factors. This study was carried out through an interdisciplinary approach involving remote sensing scientists and landscape ecologists. This study is a step forward in developing landscape metrics from satellites to monitor biodiversity.

     

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 and habitat type shape divergent dispersal behavior in a desert-dwelling fish

Context

Dispersal has important fitness consequences for individuals, populations, and species. Despite growing theoretical insights into the evolution of dispersal, its behavioral underpinnings remain empirically understudied, limiting our understanding of the extent and impact of responses to landscape-level heterogeneity of environments, and increasing the risk of inferring species-level responses from biased population sampling.

Objectives

We asked if predictable ecological variation among naturally fragmented arid waterbodies is correlated with disparate dispersal responses of populations of the desert goby Chlamydogobius eremius, which naturally inhabits two habitat “types” (permanent springs, ephemeral rivers), and different levels of hydrological connectivity (high and low) that potentially convey different costs and benefits of dispersal.

Methods

To test for possible behavioral divergence between such populations, we experimentally compared the movement behaviors (correlates of emigration and exploration) of wild-caught fish. We used two biologically relevant spatial scales to test movement relevant to different stages of the dispersal process.

Results

Behavior differed at both spatial scales, suggesting that alternative dispersal strategies enable desert gobies to exploit diverse habitat patches. However, while emigration was best predicted by the connectivity (flood risk) of fish habitats, exploration was linked to their habitat type (spring versus river).

Conclusions

Our findings demonstrate that despite a complex picture of ecological variation, key landscape factors have an overarching effect on among-population variation in dispersal traits. Implications include the maintenance of within-species variation, potentially divergent evolutionary trajectories of naturally or anthropogenically isolated populations, and the direction of future experimental studies on the ecology and evolution of dispersal behavior.

     

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.

     

Connectivity or area: what drives plant species richness in habitat corridors?

Context

The relative importance of habitat area and connectivity for species richness is often unknown. Connectivity effects may be confounded with area effects or they may be of minor importance as posited by the habitat-amount hypothesis.

Objectives

We studied effects of habitat area and connectivity of linear landscape elements for plant species richness at plot level. We hypothesized that connectivity of linear landscape elements, assessed by resistance distance, has a positive effect on species richness beyond the effect of area and, further, that the relative importance of connectivity varies among groups of species with different habitat preferences and dispersal syndromes.

Methods

We surveyed plant species richness in 50 plots (25 m²) located on open linear landscape elements (field margins, ditches) in eight study areas of 1 km² in agricultural landscapes of Northwest Germany. We calculated the area of linear landscape elements and assessed their connectivity using resistance distance within circular buffers (500 m) around the plots. Effects of area and connectivity on species richness were modelled with generalised linear mixed models.

Results

Species richness did not increase with area. Resistance distance had significant negative effects on total richness and on the richness of typical species of grasslands and wetlands. Regarding dispersal syndromes, resistance distance had negative effects on the richness of species with short-distance, long-distance and aquatic dispersal. The significant effects of resistance distance indicated that species richness increased with connectivity of the network of linear landscape elements.

Conclusions

Connectivity is more important for plant species richness in linear landscape elements than area. In particular, the richness of plant species that are dispersal limited and confined to semi-natural habitats benefits from connective networks of linear landscape elements in agricultural landscapes.

     

Using animal movement behavior to categorize land cover and predict consequences for connectivity and patch residence times

Context

Landscape-scale population dynamics are driven in part by movement within and dispersal among habitat patches. Predicting these processes requires information about how movement behavior varies among land cover types.

Objectives

We investigated how butterfly movement in a heterogeneous landscape varies within and between habitat and matrix land cover types, and the implications of these differences for within-patch residence times and among-patch connectivity.

Methods

We empirically measured movement behavior in the Baltimore checkerspot butterfly (Euphydryas phaeton) in three land cover classes that broadly constitute habitat and two classes that constitute matrix. We also measured habitat preference at boundaries. We predicted patch residence times and interpatch dispersal using movement parameters estimated separately for each habitat and matrix land cover subclass (5 categories), or for combined habitat and combined matrix land cover classes (2 categories). We evaluated the effects of including edge behavior on all metrics.

Results

Overall, movement was slower within habitat land cover types, and faster in matrix cover types. Butterflies at forest edges were biased to remain in open areas, and connectivity and patch residence times were most affected by behavior at structural edges. Differences in movement between matrix subclasses had a greater effect on predictions about connectivity than differences between habitat subclasses. Differences in movement among habitat subclasses had a greater effect on residence times.

Conclusions

Our findings highlight the importance of careful classification of movement and land cover in heterogeneous landscapes, and reveal how subtle differences in behavioral responses to land cover can affect landscape-scale outcomes.