Modeling landscape connectivity for bobcats using expert‐opinion and empirically derived models: how well do they work?

Genetic analysis of harvest samples reveals population structure in a highly mobile generalist carnivore

Delineating wildlife population boundaries is important for effective population monitoring and management. The bobcat (Lynx rufus) is a highly mobile generalist carnivore that is ecologically and economically important. We sampled 1225 bobcats harvested in South Dakota, USA (2014-2019), of which 878 were retained to assess genetic diversity and infer population genetic structure using 17 microsatellite loci. We assigned individuals to genetic clusters (K) using spatial and nonspatial Bayesian clustering algorithms and quantified differentiation (F ST and G ST ″ ) among clusters. We found support for population genetic structure at K = 2 and K = 4, with pairwise F ST and G ST ″ values indicating weak to moderate differentiation, respectively, among clusters. For K = 2, eastern and western clusters aligned closely with historical bobcat management units and were consistent with a longitudinal suture zone for bobcats previously identified in the Great Plains. We did not observe patterns of population genetic structure aligning with major rivers or highways. Genetic divergence observed at K = 4 aligned roughly with ecoregion breaks and may be associated with environmental gradients, but additional sampling with more precise locational data may be necessary to validate these patterns. Our findings reveal that cryptic population structure may occur in highly mobile and broadly distributed generalist carnivores, highlighting the importance of considering population structure when establishing population monitoring programs or harvest regulations. Our study further demonstrates that for elusive furbearers, harvest can provide an efficient, broad-scale sampling approach for genetic population assessments.

Predicting areas important for ecological connectivity throughout Canada

Governments around the world have acknowledged that urgent action is needed to conserve and restore ecological connectivity to help reverse the decline of biodiversity. In this study we tested the hypothesis that functional connectivity for multiple species can be estimated across Canada using a single, upstream connectivity model. We developed a movement cost layer with cost values assigned using expert opinion to anthropogenic land cover features and natural features based on their known and assumed effects on the movement of terrestrial, non-volant fauna. We used Circuitscape to conduct an omnidirectional connectivity analysis for terrestrial landscapes, in which the potential contribution of all landscape elements to connectivity were considered and where source and destination nodes were independent of land tenure. Our resulting map of mean current density provided a seamless estimate of movement probability at a 300 m resolution across Canada. We tested predictions in our map using a variety of independently collected wildlife data. We found that GPS data for individual caribou, wolves, moose, and elk that traveled longer distances in western Canada were all significantly correlated with areas of high current densities. The frequency of moose roadkill in New Brunswick was also positively associated with current density, but our map was not able to predict areas of high road mortality for herpetofauna in southern Ontario. The results demonstrate that an upstream modelling approach can be used to characterize functional connectivity for multiple species across a large study area. Our national connectivity map can help governments in Canada prioritize land management decisions to conserve and restore connectivity at both national and regional scales.

Missing Interactions: The Current State of Multispecies Connectivity Analysis

Designing effective habitat and protected area networks, which sustain species-rich communities is a critical conservation challenge. Recent decades have witnessed the emergence of new computational methods for analyzing and prioritizing the connectivity needs of multiple species. We argue that the goal of prioritizing habitat for multispecies connectivity should be focused on long-term persistence of a set of species in a landscape or seascape. Here we present a review of the literature based on 77 papers published between 2010 and 2020, in which we assess the current state and recent advances in multispecies connectivity analysis in terrestrial ecosystems. We summarize the four most employed analytical methods, compare their data requirements, and provide an overview of studies comparing results from multiple methods. We explicitly look at approaches for integrating multiple species considerations into reserve design and identify novel approaches being developed to overcome computational and theoretical challenges posed by multispecies connectivity analyses. There is a lack of common metrics for multispecies connectivity. We suggest the index of metapopulation capacity as one metric by which to assess and compare the effectiveness of proposed network designs. We conclude that, while advances have been made over the past decade, the field remains nascent by its ability to integrate multiple species interactions into analytical approaches to connectivity. Furthermore, the field is hampered its ability to provide robust connectivity assessments for lack of a clear definition and goal for multispecies connectivity conservation.

Habitat connectivity and resource selection in an expanding bobcat (Lynx rufus) population

Terrestrial carnivores are among the most imperiled species worldwide, yet some species are resilient and are recovering in human-dominated landscapes after decades or centuries of absence. Bobcat (Lynx rufus) populations were extirpated from much of Midwestern US in the mid-1800's, and are currently expanding and recolonizing their former range. In this study, we investigated multi-scale habitat selection for Ohio's expanding bobcat population, and examined habitat connectivity in order to evaluate the conduits for dispersal statewide. We used citizen observations collected between 1978 and 2019 and logistic regression to evaluate population-level habitat selection, and GPS telemetry data for 20 individuals collected between 2012 and 2014 and a distribution-weighted exponential Resource Selection Function to evaluate individual-level habitat selection within home ranges. At the population level, bobcats selected for higher amounts of forest and pasture (at a 50 km² scale) and herbaceous vegetation (at 15-50 50 km² scales), thus overall heterogeneous forested habitat. At individual (home range) level, bobcats selected for forested habitats with low road density and farther away from high traffic roads; they also showed weak selection for open habitat at the home range level. Male home ranges were significantly greater than female home ranges. Lastly, we used the population-level spatial outputs (i.e. habitat suitability map) to parameterize habitat connectivity models using circuit theory in the program Circuitscape. We tested three relationships between habitat suitability and resistance to movement and used a subset of data on potential dispersing individuals to evaluate which relationship performed best. All three relationships performed almost equally well, and we calculated a weighted averaged connectivity map as our final map. Habitat was highly permeable to movements between core areas of two genetically distinct subpopulations located in southeastern Ohio. We also identified potential dispersal corridors from the core areas to other regions of Ohio dominated by agriculture and suburban development via forested riparian corridors. Overall, our analysis offers new information on habitat selection and connectivity in a rebounding felid population and offers important ecological information for wildlife management strategies. We recommend that the suitability and connectivity models should be periodically updated until the population reaches an equilibrium, and be integrated with data from neighboring states for a comprehensive assessment of a conservation success story.

A Multispecies Assessment to Identify the Functional Connectivity of Amphibians in a Human-Dominated Landscape

Preserving functional connectivity is a key goal of conservation management. However, the spatially confined conservation areas may not allow for dispersal and gene flow for the intended long-term persistence of populations in fragmented landscapes. We provide a regional multi-species assessment to quantify functional connectivity for five amphibian species in a human dominated landscape in the Swiss lowlands. A set of resistance maps were derived based on expert opinion and a sensitivity analysis was conducted to compare the effect of each resistance scenario on modelled connectivity. Deriving multi-species corridors is a robust way to identify movement hotspots that provide valuable baseline information to reinforce protective measures and green infrastructure.

Conceptual framework and uncertainty analysis for large-scale, species-agnostic modelling of landscape connectivity across Alberta, Canada

Sustainable land-use planning should consider large-scale landscape connectivity. Commonly-used species-specific connectivity models are difficult to generalize for a wide range of taxa. In the context of multi-functional land-use planning, there is growing interest in species-agnostic approaches, modelling connectivity as a function of human landscape modification. We propose a conceptual framework, apply it to model connectivity as current density across Alberta, Canada, and assess map sensitivity to modelling decisions. We directly compared the uncertainty related to (1) the definition of the degree of human modification, (2) the decision whether water bodies are considered barriers to movement, and (3) the scaling function used to translate degree of human modification into resistance values. Connectivity maps were most sensitive to the consideration of water as barrier to movement, followed by the choice of scaling function, whereas maps were more robust to different conceptualizations of the degree of human modification. We observed higher concordance among cells with high (standardized) current density values than among cells with low values, which supports the identification of cells contributing to larger-scale connectivity based on a cut-off value. We conclude that every parameter in species-agnostic connectivity modelling requires attention, not only the definition of often-criticized expert-based degrees of human modification.

Contribution of Connectivity Assessments to Green Infrastructure (GI)

A major goal of green infrastructure (GI) is to provide functional networks of habitats and ecosystems to maintain biodiversity long-term, while at the same time optimizing landscape and ecosystem functions and services to meet human needs. Traditionally, connectivity studies are informed by movement ecology with species-specific attributes of the type and timing of movement (e.g., dispersal, foraging, mating) and movement distances, while spatial environmental data help delineate movement pathways across landscapes. To date, a range of methods and approaches are available that (a) are relevant across any organism and movement type independent of time and space scales, (b) are ready-to-use as standalone freeware or custom GIS implementation, and (c) produce appealing visual outputs that facilitate communication with land managers. However, to enhance the robustness of connectivity assessments and ensure that current trends in connectivity modeling contribute to GI with their full potential, common denominators on which to ground planning and design strategies are required. Likewise, comparable, repeatable connectivity assessments will be needed to put results of these scientific tools into practice for multi-functional GI plans and implementation. In this paper, we discuss use and limitations of state-of-the-art connectivity methods in contributing to GI implementation.

Mapping the fine-scale spatial pattern of artificial light pollution at night in urban environments from the perspective of bird habitats

The increase in artificial light at night (ALAN) is a global concern, while the pattern of ALAN pollution inside urban areas has not yet been fully explored. To fill this gap, we developed a novel method to map fine-scale ALAN pollution patterns in urban bird habitats using high spatial resolution ALAN satellite data. First, an ALAN pollution map was derived from JL1-3B satellite images. Then, the core habitat nodes (CHNs) representing the main habitats for urban birds to inhabit were identified from the land cover map, which was produced using Gaofen2 (GF2) data, and the high probability corridors (HPCs), indicating high connectivity paths, were derived from Circuitscape software. Finally, the ALAN patterns in the CHNs and HPCs were analysed, and the mismatch index was proposed to evaluate the trade-off between human activity ALAN demands and ALAN supply for the protection of urban birds. The results demonstrated that 115 woodland patches covering 4149.0 ha were selected as CHNs, and most of the CHNs were large urban parks or scenic spots located in the urban fringe. The 2923 modelled HPCs occupying 1179.2 ha were small remaining vegetation patches and vegetated corridors along the major transport arteries. The differences in the ALAN pollution patterns between CHNs and HPCs were mainly determined by the characteristics of the green space patches and the light source types. The polluted regions in the CHNs were clustered in a few regions that suffered from concentrated and intensive ALAN, while most of the CHNs remained unaffected. In contrast, the 727 HPCs were mainly polluted by street lighting was scattered and widely distributed, resulting a more varying influence to birds than that in the CHNs. Relating patterns of the ALAN to bird habitats and connectivity provides meaningful information for comprehensive planning to alleviate the disruptive effects of ALAN pollution.

Environmental impact assessment of development projects improved by merging species distribution and habitat connectivity modelling

Environmental impact assessment (EIA) is performed to limit potential impacts of development projects on species and ecosystem functions. However, the methods related to EIA actually pay little attention to the landscape-scale effects of development projects on biodiversity. In this study we proposed a methodological framework to more properly address the landscape-scale impacts of a new stadium project in Lyon (France) on two representative mammal species exemplary for the endemic fauna, the red squirrel and the Eurasian badger. Our approach combined species distribution model using Maxent and landscape functional connectivity model using Graphab at two spatial scales to assess habitat connectivity before and after development project implementation. The development project had a negative impact on landscape connectivity: overall habitat connectivity (PC index) decreased by -6.8% and -1.8% and the number of graph components increased by +60.0% and +17.6% for the red squirrel and the European badger respectively, because some links that formerly connected habitat patches were cut by the development project. Changes affecting landscape structure and composition emphasized the need to implement appropriate avoidance and reduction measures. Our methodology provides a useful tool both for EIA studies at each step of the way to support decision-making in landscape conservation planning. The method could be also developed in the design phase to compare the effectiveness of different avoidance or mitigation measures and resize them if necessary to maximize habitat connectivity.

Simulating impacts of rapid forest loss on population size, connectivity and genetic diversity of Sunda clouded leopards (Neofelis diardi) in Borneo

Habitat loss is the greatest threat to biodiversity in Borneo, and to anticipate and combat its effects it is important to predict the pattern of loss and its consequences. Borneo is a region of extremely high biodiversity from which forest is being lost faster than in any other. The little-known Sunda clouded leopard (Neofelis diardi) is the top predator in Borneo and is likely to depend critically on habitat connectivity that is currently being rapidly lost to deforestation. We modeled the effects of landscape fragmentation on population size, genetic diversity and population connectivity for the Sunda clouded leopard across the entirety of Borneo. We modelled the impacts of land use change between the years 2000, 2010 and projected forwards to 2020. We found substantial reductions across all metrics between 2000 and 2010: the proportion of landscape connected by dispersal fell by approximately 12.5% and the largest patch size declined by around 15.1%, leading to a predicted 11.4% decline in clouded leopard numbers. We also predict that these trends will accelerate greatly towards 2020, with the percentage of the landscape being connected by dispersal falling by about 57.8%, the largest patch size falling by around 62.8% and the predicted clouded leopard population falling by 62.5% between 2010 and 2020. We predicted that these large declines in clouded leopard population size and connectivity will also substantially reduce the genetic diversity of the remaining clouded leopard population.

Landscape connectivity for bobcat (Lynx rufus) and lynx (Lynx canadensis) in the Northeastern United States

Landscape connectivity is integral to the persistence of metapopulations of wide ranging carnivores and other terrestrial species. The objectives of this research were to investigate the landscape characteristics essential to use of areas by lynx and bobcats in northern New England, map a habitat availability model for each species, and explore connectivity across areas of the region likely to experience future development pressure. A Mahalanobis distance analysis was conducted on location data collected between 2005 and 2010 from 16 bobcats in western Vermont and 31 lynx in northern Maine to determine which variables were most consistent across all locations for each species using three scales based on average 1) local (15 minute) movement, 2) linear distance between daily locations, and 3) female home range size. The bobcat model providing the widest separation between used locations and random study area locations suggests that they cue into landscape features such as edge, availability of cover, and development density at different scales. The lynx model with the widest separation between random and used locations contained five variables including natural habitat, cover, and elevation—all at different scales. Shrub scrub habitat—where lynx’s preferred prey is most abundant—was represented at the daily distance moved scale. Cross validation indicated that outliers had little effect on models for either species. A habitat suitability value was calculated for each 30 m² pixel across Vermont, New Hampshire, and Maine for each species and used to map connectivity between conserved lands within selected areas across the region. Projections of future landscape change illustrated potential impacts of anthropogenic development on areas lynx and bobcat may use, and indicated where connectivity for bobcats and lynx may be lost. These projections provided a guide for conservation of landscape permeability for lynx, bobcat, and species relying on similar habitats in the region.