Beyond the least-cost path: evaluating corridor redundancy using a graph-theoretic approach

The impact of the landscape matrix on patterns of animal movement and population dynamics has been widely recognized by ecologists. However, few tools are available to model the matrix’s influence on the length, relative quality, and redundancy of dispersal routes connecting habitat patches. Many GIS software packages can use land use/land cover maps to identify the route of least resistance between two points—the least-cost path. The limitation of this type of analysis is that only a single path is identified, even though alternative paths with comparable costs might exist. In this paper, we implemented two graph theory methods that extend the least-cost path approach: the Conditional Minimum Transit Cost (CMTC) tool and the Multiple Shortest Paths (MSPs) tool. Both methods enable the visualization of multiple dispersal routes that, together, are assumed to form a corridor. We show that corridors containing alternative dispersal routes emerge when favorable habitat is randomly distributed in space. As clusters of favorable habitat start forming, corridors become less redundant and dispersal bottlenecks become visible. Our approach is illustrated using data from a real landscape in the Brazilian Atlantic forest. We explored the effect of small, localized disturbance on dispersal routes linking conservation units. Simulated habitat destruction caused the appearance of alternative dispersal routes, or caused existing corridors to become narrower. These changes were observed even in the absence of significant differences in the length or cost of least-cost paths. Last, we discuss applications to animal movement studies and conservation initiatives.     

Connecting mountains and desert valleys for black bears in northern Mexico

Context

Black bear connectivity studies are scarce in the southern distribution where the species is endangered. The identification of corridors is a strategy to promote conservation in human-modified landscapes.

Objectives

Assess and validate long-distance corridors in the southern black bear distribution using resistance models, occurrence records, and radio-telemetry of an individual that dispersed between the Sierras Madres of Mexico.

Methods

We acquired black bear occurrence records from several sources and telemetry records from one dispersal individual in northern Mexico. We generated ensemble habitat suitability models and resistance landscape surfaces to generate cumulative resistant kernel and least-cost paths to identify connectivity core areas and corridors of importance through Natural Protected Areas. Finally, we assessed long-distance corridors.

Results

We developed three habitat suitability models for black bears southern range; one matches the current distribution of the species. When including radio-tracking records, the landscape resistance is reduced to arid sites with low habitat suitability. We used least resistance connectivity surfaces to merge subpopulations within each Sierra Madre. The long-distance corridor models indicate narrow routes that require individuals with plastic behavioral dispersal capacity. Almost 20% of the connectivity core areas are within Natural Protected Areas. These are the first large-scale corridors using resistance layers in the southern black bear distribution.

Conclusions

Corridors can be functional for a range of temperate and dry habitat species. Landscape connectivity models should include the monitoring of dispersal individuals to identify the plasticity of organisms and the tangible barriers for them.

     

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.

     

The sensitivity of least-cost habitat graphs to relative cost surface values

Maintaining and restoring connectivity among high-quality habitat patches is recognized as an important goal for the conservation of animal populations. To provide an efficient measure of potential connectivity pathways in heterogeneous landscapes, least-cost route analysis has been combined with graph-theoretical techniques. In this study we use spatially explicit least-cost habitat graphs to examine how matrix quality and spatial configuration influence assessments of habitat connectivity. We generated artificial landscapes comprised of three landcover types ranked consistently from low to high quality: inhospitable matrix, hospitable matrix, and habitat. We controlled the area and degree of fragmentation of each landcover in a factorial experiment for a total of 20 combinations replicated 100 times. In each landscape we compared eight sets of relative landcover qualities (cost values of 1 for habitat, between 1.5 and 150 for hospitable matrix, and 3–10,000 for inhospitable matrix). We found that the spatial location of least-cost routes was sensitive to differences in relative cost values assigned to landcover types and that the degree of sensitivity depended on the spatial structure of the landscape. Highest sensitivity was found in landscapes with fragmented habitat and between 20 and 50% hospitable matrix; sensitivity decreased as habitat fragmentation decreased and the amount of hospitable matrix increased. As a means of coping with this sensitivity, we propose identifying multiple low-cost routes between pairs of habitat patches that collectively delineate probable movement zones. These probable movement zones account for uncertainty in least-cost routes and may be more robust to variation in landcover cost values.     

Connectivity of mule deer (Odocoileus hemionus) populations in a highly fragmented urban landscape

Context

Urbanization is a substantial force shaping the genetic and demographic structure of natural populations. Urban development and major highways can limit animal movements, and thus gene flow, even in highly mobile species. Characterizing varying species responses to human activity and fragmentation is important for maintaining genetic continuity in wild animals and for preserving biodiversity. As one of the only common and wide-ranging large wild herbivores in much of urban North America, deer play an important ecological role in urban ecosystems, yet the genetic impacts of development on deer are not well known.

Objectives

We assessed genetic connectivity for mule deer to understand their genetic response to habitat fragmentation, due to development and highway barriers, in an increasingly urbanized landscape.

Methods

Using non-invasive sampling across a broad region of southern California, we investigated genetic structure among several natural areas that were separated by major highways and applied least-cost path modelling to determine if landscape context and highway attributes influence genetic distance for mule deer.

Results

We observed significant yet variable differentiation between subregions. We show that genetic structure corresponds with highway boundaries in certain habitat patches, and that particular landscape configurations more greatly limit gene flow between patches.

Conclusions

As a large and highly mobile species generally considered to be well adapted to human activity, mule deer nonetheless showed genetic impacts of intensive urbanization. Because of this potential vulnerability, mule deer and other ungulates may require further consideration for effective habitat management and maintenance of landscape connectivity in human-dominated landscapes.

     

Maintaining or restoring connectivity of modified landscapes: evaluating the least-cost path model with multiple sources of ecological information

Habitat connectivity is an important element of functioning landscapes for mobile organisms. Maintenance or creation of movement corridors is one conservation strategy for reducing the negative effects of habitat fragmentation. Numerous spatial models exist to predict the location of movement corridors. Few studies, however, have investigated the effectiveness of these methods for predicting actual movement paths. We used an expert-based model and a resource selection function (RSF) to predict least-cost paths of woodland caribou. Using independent data for model evaluation, we found that the expert-based model was a poor predictor of long-distance animal movements; in comparison, the RSF model was effective at predicting habitat selection by caribou. We used the Path Deviation Index (PDI), cumulative path cost, and sinuosity to quantitatively compare the spatial differences between inferred caribou movement paths and predicted least-cost paths, and quasi-random null models of directional movement. Predicted movement paths were on average straighter than inferred movement paths for collared caribou. The PDI indicated that the least-cost paths were no better at predicting the inferred paths than either of two null models—straight line paths and randomly generated paths. We found statistically significant differences in cumulative cost scores for the main effects of model and path type; however, post-hoc comparisons were non-significant suggesting no difference among inferred, random, and predicted least cost paths. Paths generated from an expert based cost surface were more sinuous than those premised on the RSF model, but neither differed from the inferred path. Although our results are specific to one species, they highlight the importance of model evaluation when planning for habitat connectivity. We recommend that conservation planners adopt similar techniques when validating the effectiveness of movement corridors for other populations and species.     

Habitat suitability and connectivity modeling reveal priority areas for Indiana bat (Myotis sodalis) conservation in a complex habitat mosaic

Context

Conservation for the Indiana bat (Myotis sodalis), a federally endangered species in the United States of America, is typically focused on local maternity sites; however, the species is a regional migrant, interacting with the environment at multiple spatial scales. Hierarchical levels of management may be necessary, but we have limited knowledge of landscape-level ecology, distribution, and connectivity of suitable areas in complex landscapes.

Objectives

We sought to (1) identify factors influencing M. sodalis maternity colony distribution in a mosaic landscape, (2) map suitable maternity habitat, and (3) quantify connectivity importance of patches to direct conservation action.

Methods

Using 3 decades of occurrence data, we tested a priori, hypothesis-driven habitat suitability models. We mapped suitable areas and quantified connectivity importance of habitat patches with probabilistic habitat availability metrics.

Results

Factors improving landscape-scale suitability included limited agriculture, more forest cover, forest edge, proximity to medium-sized water bodies, lower elevations, and limited urban development. Areas closer to hibernacula and rivers were suitable. Binary maps showed that 30% of the study area was suitable for M. sodalis and 29% was important for connectivity. Most suitable patches were important for intra-patch connectivity and far fewer contributed to inter-patch connectivity.

Conclusions

While simple models may be effective for small, homogenous landscapes, complex models are needed to explain habitat suitability in large, mixed landscapes. Suitability modeling identified factors that made sites attractive as maternity areas. Connectivity analysis improved our understanding of important areas for bats and prioritized areas to target for restoration.

     

Least-cost path length versus accumulated-cost as connectivity measures

Least-cost modelling has become a popular method for measuring connectivity. By representing the landscape as a cost-surface, least-cost paths can be calculated that represent the route of maximum efficiency between two locations as a function of the distance travelled and the costs traversed. Both the length and the accumulated-cost of a least-cost path have been used as measures of connectivity between pairs of locations. However, we are concerned that in some situations the length of a least-cost path may provide a misleading measure of connectivity as it only accounts for the distance travelled while ignoring the costs traversed, and results in a measure that may be little better than Euclidean distance. Through simulations using fractal landscapes we demonstrate that least-cost path length is often highly correlated with Euclidean distance. This indicates that least-cost path length provides a poor measure of connectivity in many situations, as it does not capture sufficient information about the ecological costs to movement represented by the cost-surface. We recommend that in most situations the accumulated-cost of a least-cost path provides a more appropriate measure of connectivity between locations as it accounts for both the distance travelled and costs traversed, and that the generation of vector least-cost paths should be reserved for visualisation purposes.     

Measuring landscape connectivity: On the importance of within-patch connectivity

Context

Many connectivity metrics have been used to measure the connectivity of a landscape and to evaluate the effects of land-use changes and potential mitigation measures. However, there are still gaps in our understanding of how to accurately quantify landscape connectivity.

Objectives

A number of metrics only measure between-patch connectivity, i.e. the connectivity between different habitat patches, which can produce misleading results. This paper demonstrates that the inclusion of within-patch connectivity is important for accurate results.

Methods

The behavior of two metrics is compared: the Connectance Index (CONNECT), which measures only between-patch connectivity, and the effective mesh size (m_eff), which includes both within-patch and between-patch connectivity. The connectivity values of both metrics were calculated on a set of simulated landscapes. Twenty cities were then added to these landscapes to calculate the resulting changes in connectivity.

Results

We found that when using CONNECT counter-intuitive results occurred due to not including within-patch connectivity, such as scenarios where connectivity increased with increasing habitat loss and fragmentation. These counter-intuitive results were resolved when using m_eff. For example, landscapes with low habitat amount may be particularly sensitive to urban development, but this is not reflected by CONNECT.

Conclusions

Applying misleading results from metrics like CONNECT can have detrimental effects on natural ecosystems, because reductions in within-patch connectivity by human activities are neglected. Therefore, this paper provides evidence for the crucial need to consider the balance between within-patch connectivity and between-patch connectivity when calculating the connectivity of landscapes.

     

Not all forests are alike: the role of commercial forest in the conservation of landscape connectivity for the giant panda

Context

The downlisting of giant panda (Ailuropoda melanoleuca) from Endangered to Vulnerable in IUCN Red List confirms the effectiveness of current conservation practices. However, future survival of giant panda is still in jeopardy due to habitat fragmentation and climate change. Maintaining movement corridors between habitat patches in the newly established Giant Panda National Park (GPNP) is the key for the long-term sustainability of the species.

Objectives

We evaluated the impacts of conversion from natural forest to plantation on giant panda habitat connectivity, which is permitted within collective forests and encouraged by the policies for the economic benefits of local communities. We modeled distribution of giant panda habitat in Minshan Mountains which harbors its largest population, and delineated movement corridors between core habitat patches under management scenarios of different forest conversion proportions.

Methods

We applied an integrated species distribution model based on inhomogeneous Poisson point process to combine presence-only data and site occupancy data, and least-cost models to identify potential movement corridors between core habitat patches.

Results

We found that current distribution of plantation has not damaged connectivity between core habitat patches of giant panda. However, it could be severely degraded if mass conversion occurred. Since the GPNP incorporates all the core habitats identified from our model, controlling natural forest conversion inside GPNP would maintain the movement corridors for giant panda.

Conclusions

We recommend no expansion of plantations inside the GPNP, and improving collective forest management for expansion of ecological forest in adjoining habitat patches.

     

Effects of different matrix representations and connectivity measures on habitat network assessments

Assessing landscape connectivity is important to understand the ecology of landscapes and to evaluate alternative conservation strategies. The question is though, how to quantify connectivity appropriately, especially when the information available about the suitability of the matrix surrounding habitat is limited. Our goal here was to investigate the effects of matrix representation on assessments of the connectivity among habitat patches and of the relative importance of individual patches for the connectivity within a habitat network. We evaluated a set of 50 × 50 km² test areas in the Carpathian Mountains and considered three different matrix representations (binary, categorical and continuous) using two types of connections among habitat patches (shortest lines and least-cost paths). We compared connections, and the importance of patches, based on (1) isolation, (2) incidence-functional, and (3) graph measures. Our results showed that matrix representation can greatly affect assessments of connections (i.e., connection length, effective distance, and spatial location), but not patch prioritization. Although patch importance was not much affected by matrix representation, it was influenced by the connectivity measure and its parameterization. We found the biggest differences in the case of the integral index of connectivity and equally weighted patches, but no consistent pattern in response to changing dispersal distance. Connectivity assessments in more fragmented landscapes were more sensitive to the selection of matrix representation. Although we recommend using continuous matrix representation whenever possible, our results indicated that simpler matrix representations can be also used as a proxy to delineate those patches that are important for overall connectivity, but not to identify connections among habitat patches.     

Connectivity providers for semi-aquatic vertebrates: the case of the endangered otter in Italy

Modeling habitat connectivity for conservation of semi-aquatic vertebrates is a particularly challenging task, due to the fine-scale and linear distribution of riverine habitats and to the capacity of species to move both on freshwater and terrestrial realms. We showed how the integrated analytical framework provided by the habitat availability (reachability) metrics and their fractions can be used to effectively evaluate the distinctive roles and contributions of both habitat patches (aquatic and riparian) and linkage areas (permeable land matrix) to the connectivity and functioning of a complex system composed of multiple river catchments. Analysis focused on the Eurasian otter (Lutra lutra L.), one of the most endangered mammals in Italy. We developed a network connectivity model based on suitable otter habitats and multiple least-cost paths between catchments. A graph analytical approach was used to identify critical nodes and links for the potential expansion and long-term viability of the species in the region. Our results showed that few basins concentrate most of the importance for sustaining the overall habitat connectivity, due to the extension of suitable habitats they contain, their strong connections with other basins, and their importance as stepping stones that uphold ecological fluxes between otherwise weakly connected habitats. The potential contribution of each basin to enhance the dispersal and expansion of otters in the area strongly depended on the key functional paths (sequences of links and nodes) among the catchments. We identified vacant basins that could be colonized by otters in the near future, and connecting areas in the intermediate matrix that might be preferentially used to conduct and promote dispersal movements and gene flow in the area. The novel approach here adopted could be easily extended to other semiaquatic species and catchment systems, offering a management strategy to preserve the hydrographic network as an integrated system, as well as a joint evaluation of the role of both the river courses and the matrix in between in a single landscape model.     

A comparison of metrics predicting landscape connectivity for a highly interactive species along an urban gradient in Colorado, USA

Many organisms persist in fragmented habitat where movement between patches is essential for long-term demographic and genetic stability. In the absence of direct observation of movement, connectivity or isolation metrics are useful to characterize potential patch-level connectivity. However, multiple metrics exist at varying levels of complexity, and empirical data on species distribution are rarely used to compare performance of metrics. We compared 12 connectivity metrics of varying degrees of complexity to determine which metric best predicts the distribution of prairie dog colonies along an urban gradient of 385 isolated habitat patches in Denver, Colorado, USA. We found that a modified version of the incidence function model including area-weighting of patches and a cost-weighted distance surface best predicted occupancy, where we assumed roads were fairly impermeable to movement, and low-lying drainages provided dispersal corridors. We also found this result to be robust to a range of cost weight parameters. Our results suggest that metrics should incorporate both patch area and the composition of the surrounding matrix. These results provide guidance for improved landscape habitat modeling in fragmented landscapes and can help identify target habitat for conservation and management of prairie dogs in urban systems.     

Circuit theory emphasizes the importance of edge-crossing decisions in dispersal-scale movements of a forest passerine

Measuring landscape connectivity in ways that reflect an animal’s propensity or reluctance to move across a given landscape is key for planning effective conservation strategies. Resistance distance, based on circuit theory, is one such measure relevant for modeling how broad-scale animal movements over long time periods may lead to gene flow across the landscape. Despite the success of circuit theory in landscape genetic studies, its applicability to model finer-scale processes such as the movement patterns of individual animals within their breeding grounds (e.g., while prospecting for territories) has yet to be tested. Here, we applied both circuit models and least-cost models to understand the relationship between landscape connectivity and return time of Ovenbirds (Seiurus aurocapilla) that had been translocated at least 20 km from their home territory near Québec City, Canada. Using an iterative optimization process, we derived resistance values for three cover types (forest, edge, and open) that resulted in resistance distance values that best explained Ovenbird return times. We also identified the cover-type resistance values that yielded length of least-cost path estimates that best explained return times of the translocated birds. The circuit theory and least-cost path methods were equally supported by the data despite being based on different sets of resistance values. The optimal resistance values for calculating resistance distance indicated that for Ovenbirds, traversing a given distance of edge habitat presented a substantially greater resistance than that of open areas. On the other hand, optimized resistances of edge and open were very similar for calculating length of least-cost path. The circuit theory approach suggested that for an Ovenbird moving through fragmented habitat, the number of forest-open transitions (i.e., edge-crossings) that an individual must make is critical to understanding return times after translocation. The least-cost path approach, on the other hand, suggested that the birds strongly avoid all open areas, regardless of size. Circuit theory offers an important new approach for understanding landscapes from the perspective of individuals moving within their breeding range, at finer spatial scales and shorter time scales than have been previously considered.     

Functional rather than structural connectivity explains grassland plant diversity patterns following landscape scale habitat loss

Context

Functional connectivity is vital for plant species dispersal, but little is known about how habitat loss and the presence of green infrastructure interact to affect both functional and structural connectivity, and the impacts of each on species groups.

Objectives

We investigate how changes in the spatial configuration of species-rich grasslands and related green infrastructure such as road verges, hedgerows and forest borders in three European countries have influenced landscape connectivity, and the effects on grassland plant biodiversity.

Methods

We mapped past and present land use for 36 landscapes in Belgium, Germany and Sweden, to estimate connectivity based on simple habitat spatial configuration (structural connectivity) and accounting for effective dispersal and establishment (functional connectivity) around focal grasslands. We used the resulting measures of landscape change to interpret patterns in plant communities.

Results

Increased presence of landscape connecting elements could not compensate for large scale losses of grassland area resulting in substantial declines in structural and functional connectivity. Generalist species were negatively affected by connectivity, and responded most strongly to structural connectivity, while functional connectivity determined the occurrence of grassland specialists in focal grasslands. Restored patches had more generalist species, and a lower density of grassland specialist species than ancient patches.

Conclusions

Protecting both species rich grasslands and dispersal pathways within landscapes is essential for maintaining grassland biodiversity. Our results show that increases in green infrastructure have not been sufficient to offset loss of semi-natural habitat, and that landscape links must be functionally effective in order to contribute to grassland diversity.

     

Targeting and evaluating biodiversity conservation action within fragmented landscapes: an approach based on generic focal species and least-cost networks

The focus of biodiversity conservation is shifting to larger spatial scales in response to habitat fragmentation and the need to integrate multiple landscape objectives. Conservation strategies increasingly incorporate measures to combat fragmentation such as ecological networks. These are often based on assessment of landscape structure but such approaches fail to capitalise on the potential offered by more ecologically robust assessments of landscape function and connectivity. In this paper, we describe a modelling approach to identifying functional habitat networks and demonstrate its application to a fragmented landscape where policy initiatives seek to improve conditions for woodland biodiversity including increasing woodland cover. Functional habitat networks were defined by identifying suitable habitat and by modelling connectivity using least-cost approaches to account for matrix permeability. Generic focal species (GFS) profiles were developed, in consultation with stakeholders, to represent species with high and moderate sensitivity to fragmentation. We demonstrated how this form of analysis can be used to aid the spatial targeting of conservation actions. This ‘targeted’ action scenario was tested for effectiveness against comparable scenarios, which were based on random and clumped actions within the same landscape. We tested effectiveness using structural metrics, network-based metrics and a published functional connectivity indicator. Targeting actions within networks resulted in the highest mean woodland area and highest connectivity indicator value. Our approach provides an assessment of landscape function by recognising the importance of the landscape matrix. It provides a framework for the targeting and evaluation of alternative conservation options, offering a pragmatic, ecologically-robust solution to a current need in applied landscape ecology.     

Influence of land-use/land-cover change on landscape connectivity for an endemic threatened amphibian (Argenteohyla siemersi pederseni,Anura: Hylidae)

Context

Modifications in natural landcover generally result in a loss of habitat availability for wildlife and it’s persistence will depend largely on their spatial configuration and functional connections. Argenteohyla siemersi is a threatened and endemic amphibian whose habitat is composed of forest patches near rivers and water bodies edges.

Objectives

This study aimed to analyse the accessible habitat for this species and identify key elements to maintain its ecological network in two different types of land uses: an anthropized area with extensive cattle raising and a protected area.

Methods

The structural and functional characteristics of both landscapes were analyzed. The connectivity at landscape level and the contribution of each habitat patch were evaluated through simulation models with different dispersion distances in the context of the graph theory.

Results

In both landscapes, nine types of landcover were identified with different compositions. Remarkable differences were found in habitat connectivity for this amphibian species between both landscapes. As the percentage of dispersion distance increases, reachable habitat increases as well, although with higher percentages in the protected area. Two corridors were identified in the protected landscape and one in the rangeland one; patches and key links constituted all of them.

Conclusions

The present work provides spatially explicit results with a quantitative basis. It could be useful as a tool for the development of management plans aimed at guaranteeing the functionality of the ecological network for this endangered species and, therefore, contribute to its long-term conservation.

     

Evaluation of landscape connectivity at community level using satellite-derived NDVI

Landscape connectivity, defined as the degree to which the landscape facilitates or impedes movement among resource patches, has been considered to be a key issue for biodiversity conservation. However, the use of landscape connectivity measurements has been strongly criticised due to uncertainties in the methods used and the lack of validation. Moreover, measurements are typically restricted to the population level, whereas management is generally carried out at the community level. Here, we used satellite imagery and network metrics to predict the landscape connectivity at community level for semi-natural herbaceous patches in an urban area near Paris (France). We tested different measurement methods, both taking into account and ignoring the spatial heterogeneity of matrix resistance estimated by the normalised difference vegetation index (NDVI), and quantifying the link strength between patches with the shortest path and flow metrics. We assessed the fit of these connectivity predictions with empirical data on plant communities embedded in an urban matrix. Our results indicate that the best fit with the empirical data is obtained when the connectivity is estimated with the flow metric and takes into account the matrix heterogeneity. Overall, our study helps to estimate the landscape connectivity of urban areas and makes recommendations for ways in which we might optimise landscape planning with respect to conservation of urban biodiversity.     

Multiscale effects of habitat and surrounding matrices on waterbird diversity in the Yangtze River Floodplain

Context

With the expansion in urbanization, understanding how biodiversity responds to the altered landscape becomes a major concern. Most studies focus on habitat effects on biodiversity, yet much less attention has been paid to surrounding landscape matrices and their joint effects.

Objective

We investigated how habitat and landscape matrices affect waterbird diversity across scales in the Yangtze River Floodplain, a typical area with high biodiversity and severe human-wildlife conflict.

Methods

The compositional and structural features of the landscape were calculated at fine and coarse scales. The ordinary least squares regression model was adopted, following a test showing no significant spatial autocorrelation in the spatial lag and spatial error models, to estimate the relationship between landscape metrics and waterbird diversity.

Results

Well-connected grassland and shrub surrounded by isolated and regular-shaped developed area maintained higher waterbird diversity at fine scales. Regular-shaped developed area and cropland, irregular-shaped forest, and aggregated distribution of wetland and shrub positively affected waterbird diversity at coarse scales.

Conclusions

Habitat and landscape matrices jointly affected waterbird diversity. Regular-shaped developed area facilitated higher waterbird diversity and showed the most pronounced effect at coarse scales. The conservation efforts should not only focus on habitat quality and capacity, but also habitat connectivity and complexity when formulating development plans. We suggest planners minimize the expansion of the developed area into critical habitats and leave buffers to maintain habitat connectivity and shape complexity to reduce the disturbance to birds. Our findings provide important insights and practical measures to protect biodiversity in human-dominated landscapes.

     

Mapping landscape connectivity for large spatial extents

Context

Mapping landscape connectivity across large spatial extents is an important component of ecological reserve network designs and species recovery plans. It can, however, be limited by computational power. One way to overcome this problem is to split the study area into smaller tiles, map landscape connectivity within each of those tiles, and then merge tiles back together to form composite connectivity maps.

Objectives

We tested the effects of landscape structure on the accuracy of composite landscape connectivity maps created from tiles and tested two methods to increase this accuracy.

Methods

We correlated replicate, composite current density maps with untiled maps. We tested whether our findings depended on the composition of the landscape by testing maps with corridors, barriers, different mixtures of high- and low-cost habitat, and road networks.

Results

We found that composite current density maps underestimated large-scale connectivity and overestimated the contribution of small habitat patches to overall connectivity. These biases became more pronounced as the tiles became relatively smaller. Landscapes with corridors or barriers were particularly sensitive. We increased the accuracy of tiled maps by increasing pixel size or by averaging several maps created using a “moving window” approach.

Conclusions

There is a trade-off between tile size and pixel size when modelling connectivity across large spatial extents. We suggest using the largest tile size possible when tiling is necessary, in conjunction with increased pixel size and a moving window method to increase accuracy of the composite current density maps.