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.

     

Multi-scale prediction of landscape resistance for tiger dispersal in central India

Context

Connectivity models for animal movement frequently use resistance surfaces, but rarely incorporate actual movement data and multiple scale drivers of landscape resistance.

Objectives

Using GPS data, we developed a multi-scale model of landscape resistance for tiger (Panthera tigris) dispersal in central India and evaluated the performance, interpretation and predictions against single scale models.

Methods

Six dispersing tiger paths were subjected to a path level analysis with conditional logistic regression to parameterize a resistance surface. We evaluated for 21 scales of available habitat and selected the best scale for each variable. We derived a scale-optimized multivariate path selection function and predicted landscape resistance across the landscape.

Results

The tigers preferred to move along areas with forest cover at relatively high elevations along the ridges with rugged topography at broad scale, while avoiding areas with agriculture-village matrix at fine scale. We found that the scale that was most supported by Akaike’s information criterion was not always the scale that maximized the magnitude (effect size) of the relationship. Further, the multi-scale optimized model differed substantially from the single scale models in terms of variable importance, magnitude of coefficients and predictions of connectivity.

Conclusions

Our results demonstrate that the variables in landscape resistance models produce markedly different predictions of population connectivity depending on the scales of analyses and interpretation. Thus, scale optimization in parameterization is critical for appropriate inferences and sound management strategies.

     

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-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.

     

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.

     

Influence of separating home range and dispersal movements on characterizing corridors and effective distances

Context

Corridors are usually delineated as areas of minimum cumulative resistance to movement through a resistance surface and characterized by their effective distance (accumulated resistance along the least-cost path). The results of these assessments depend on resistance values, which are typically derived from the inverse of habitat suitability models or from presence data of individuals within their home ranges, rather than from data on dispersal or exploratory movements.

Objective

Evaluate the extent to which corridor delineation and effective distance estimates may vary depending on whether home range locations or dispersal data are used to characterize species habitat selection and landscape resistance to movement.

Methods

We analyzed a large telemetry dataset (GPS collars) for the endangered Iberian lynx. We modeled corridors and effective distances three ways: (1) considering only GPS locations within home ranges, (2) considering only locations in dispersal or exploratory movements outside home ranges, and (3) considering all locations together.

Results

Delineated least-cost corridors followed similar trajectories and sometimes overlapped in the three models. The estimated effective distances were 42 % lower in the dispersal-based model than in the model based solely on home range use.

Conclusions

Models derived exclusively from locations within home ranges may provide lower connectivity estimates than models derived from dispersal locations, affecting estimates of resistance to move between habitat areas, even when the most likely movement routes are similar. Although dispersal data are costly to gather, they potentially provide more realistic assessments of the actual isolation of populations in heterogeneous landscapes.

     

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.

     

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.

     

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.

     

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.

     

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.

     

Integrating animal movement with habitat suitability for estimating dynamic migratory connectivity

Context

High-resolution animal movement data are becoming increasingly available, yet having a multitude of empirical trajectories alone does not allow us to easily predict animal movement. To answer ecological and evolutionary questions at a population level, quantitative estimates of a species’ potential to link patches or populations are of importance.

Objectives

We introduce an approach that combines movement-informed simulated trajectories with an environment-informed estimate of the trajectories’ plausibility to derive connectivity. Using the example of bar-headed geese we estimated migratory connectivity at a landscape level throughout the annual cycle in their native range.

Methods

We used tracking data of bar-headed geese to develop a multi-state movement model and to estimate temporally explicit habitat suitability within the species’ range. We simulated migratory movements between range fragments, and calculated a measure we called route viability. The results are compared to expectations derived from published literature.

Results

Simulated migrations matched empirical trajectories in key characteristics such as stopover duration. The viability of the simulated trajectories was similar to that of the empirical trajectories. We found that, overall, the migratory connectivity was higher within the breeding than in wintering areas, corroborating previous findings for this species.

Conclusions

We show how empirical tracking data and environmental information can be fused for meaningful predictions of animal movements throughout the year and even outside the spatial range of the available data. Beyond predicting migratory connectivity, our framework will prove useful for modelling ecological processes facilitated by animal movement, such as seed dispersal or disease ecology.

     

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.

     

Multi-scale network analysis shows scale-dependency of significance of individual protected areas for connectivity

Context

The problem of how ecological mechanisms create and interact with patterns across different scales is fundamental not only for understanding ecological processes, but also for interpretations of ecological dynamics and the strategies that organisms adopt to cope with variability and cross-scale influences.

Objectives

Our objective was to determine the consistency of the role of individual habitat patches in pattern-process relationships (focusing on the potential for dispersal within a network of patches in a fragmented landscape) across a range of scales.

Methods

Network analysis was used to assess and compare the potential connectivity and spatial distribution of highland fynbos habitat in and between protected areas of the Western Cape of South Africa. Connectivity of fynbos patches was measured using ten maximum threshold distances, ranging from five to 50 km, based on the known average dispersal distances of fynbos endemic bird species.

Results

Network connectivity increased predictably with scale. More interestingly, however, the relative contributions of individual protected areas to network connectivity showed strong scale dependence.

Conclusions

Conservation approaches that rely on single-scale analyses of connectivity and context (e.g., based on data for a single species with a given dispersal distance) are inadequate to identify key land parcels. Landscape planning, and specifically the assessment of the value of individual areas for dispersal, must therefore be undertaken with a multi-scale approach. Developing a better understanding of scaling dependencies in fragmenting landscapes is of high importance for both ecological theory and conservation planning.

     

Effects of large-scale wetland loss on network connectivity of the Rainwater Basin,Nebraska

Context

The Rainwater Basin region in south-central Nebraska supports a complex network of spatially-isolated wetlands that harbor diverse floral and faunal communities. Since European settlement, many wetlands have been lost from the network, which has increased distances among remaining wetlands. As a result, populations of wildlife species with limited dispersal capabilities may have become isolated and face greater local extinction risks.

Objectives

We compared the pre-European settlement and current extent of the Rainwater Basin network to assess the effects of wetland losses on network connectivity for a range of maximum dispersal distances.

Methods

We constructed network models for a range of maximum dispersal distances and calculated network metrics to assess changes in network connectivity and the relative importance of individual wetlands in regulating flow.

Results

Since European settlement, the number of wetlands in the Rainwater Basin has decreased by?>?90%. The average distance to the nearest neighboring wetland has increased by 150% to ~?1.2 km, and the dispersal distance necessary to travel throughout the whole network has increased from 3.5 to 10.0 km. Last, relative importance of individual wetlands depended on the maximum dispersal distance. Which wetlands to preserve to maintain connectivity might therefore depend on the dispersal capabilities of the species or taxa of interest.

Conclusions

To preserve a broad range of biodiversity, conservation efforts should focus on preserving dense clusters of wetlands at fine spatial scales to maintain current levels of network connectivity, and restoring connections between clusters to facilitate long-range dispersal of species with limited dispersal capabilities.

     

Assessing landscape functional connectivity in a forest carnivore using path selection functions

Context

Understanding connectivity patterns in relation to habitat fragmentation is essential to landscape management. However, connectivity is often judged from expert opinion or species occurrence patterns, with very few studies considering the actual movements of individuals. Path selection functions provide a promising tool to infer functional connectivity from animal movement data, but its practical application remains scanty.

Objectives

We aimed to describe functional connectivity patterns in a forest carnivore using path-level analysis, and to explore how connectivity is affected by land cover patterns and road networks.

Methods

We radiotracked 22 common genets in a mixed forest-agricultural landscape of southern Portugal. We developed path selection functions discriminating between observed and random paths in relation to landscape variables. These functions were used together with land cover information to map conductance surfaces.

Results

Genets moved preferentially within forest patches and close to riparian habitats. Functional connectivity declined with increasing road density, but increased with the proximity of culverts, viaducts and bridges. Functional connectivity was favoured by large forest patches, and by the presence of riparian areas providing corridors within open agricultural land. Roads reduced connectivity by dissecting forest patches, but had less effect on riparian corridors due to the presence of crossing structures.

Conclusions

Genet movements were jointly affected by the spatial distribution of suitable habitats, and the presence of a road network dissecting such habitats and creating obstacles in areas otherwise permeable to animal movement. Overall, the study showed the value of path-level analysis to assess functional connectivity patterns in human-modified landscapes.

     

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.

     

Step-wise drops in modularity and the fragmentation of exploited marine metapopulations

Context

Many nearshore species are distributed in habitat patches connected only through larval dispersal. Genetic research has shown some spatial structure of such metapopulations and modeling studies have shed light onto possible patterns of connectivity and barriers. However, little is known about human impact on their spatial structure and patterns of connectivity.

Objectives

We examine the effects of fishing on the spatial and temporal dynamics of metapopulations of sedentary marine species (red sea urchin and red abalone) interconnected by larval dispersal.

Methods

We constructed a metapopulation model to simulate abalone and sea urchin metapopulations experiencing increasing levels of fishing mortality. We performed the modularity analysis on the yearly larval connectivity matrices produced by these simulations, and analyzed the changes of modularity and the formation of modules over time as indicators of spatial structure.

Results

The analysis revealed a strong modular spatial structure for abalone and a weak spatial signature for sea urchin. In abalone, under exploitation, modularity takes step-wise drops on the path to extinction, and modules breakdown into smaller fragments followed by module and later metapopulation collapse. In contrast, sea urchin showed high modularity variation, indicating high- and low-mixing years, but an abrupt collapse of the metapopulation under strong exploitation.

Conclusions

The results identify a disruption in larval connectivity and a pattern of collapse in highly modular nearshore metapopulations. These results highlight the ability of modularity to detect spatial structure in marine metapopulations, which varies among species, and to show early changes in the spatial structure of exploited metapopulations.

     

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.