Mapping Landscape Resistance to Identify Corridors and Barriers for Elephant Movement in Southern Africa

Mapping Landscape Resistance to Identify Corridors and Barriers for Elephant Movement in Southern Africa ..

Spatially-explicit estimation of Wright's neighborhood size in continuous populations

Effective population size (Ne) is an important parameter in conservation genetics because it quantifies a population’s capacity to resist loss of genetic diversity due to inbreeding and drift. The classical approach to estimate Ne from genetic data involves grouping sampled individuals into discretely defined subpopulations assumed to be panmictic. Importantly, this assumption does not capture the continuous nature of populations genetically isolated by distance. Alternative approaches based on Wright’s genetic neighborhood concept quantify the local number of breeding individuals (NS) in a continuous population (as opposed to the global Ne). However, they do not reflect the potential for NS to vary spatially nor do they account for the resistance of a heterogeneous landscape to gene flow (isolation by resistance). Here, we describe an application of Wright’s neighborhood concept that provides spatially-explicit estimates of local NS from genetic data in continuous populations isolated by distance or resistance. We delineated local neighborhoods surrounding each sampled individual based on sigma (), a measure of the local extent of breeding. When was known, the linkage disequilibrium method applied to local neighborhoods produced unbiased estimates of NS that were highly variable across the landscape. NS near the periphery or areas surrounded by high resistance was as much as an order of magnitude lower compared to the center, raising the potential for a spatial component to extinction vortex dynamics in continuous populations. When is not known, it may be estimated from genetic data, but two methods we evaluated identified analysis extents that produced considerable bias or error in the estimate of NS. When is known or accurately estimated, and the assumptions of Wright’s neighborhood are met, the method we describe provides spatially explicit information regarding short-term genetic processes that may inform conservation genetic analyses and management

Why Did the Bear Cross the Road? Comparing the Performance of Multiple Resistance Surfaces and Connectivity Modeling Methods

There have been few assessments of the performance of alternative resistance surfaces, and little is known about how connectivity modeling approaches differ in their ability to predict organism movements. In this paper, we evaluate the performance of four connectivity modeling approaches applied to two resistance surfaces in predicting the locations of highway crossings by American black bears in the northern Rocky Mountains, USA. We found that a resistance surface derived directly from movement data greatly outperformed a resistance surface produced from analysis of genetic differentiation, despite their heuristic similarities. Our analysis also suggested differences in the performance of different connectivity modeling approaches. Factorial least cost paths appeared to slightly outperform other methods on the movement-derived resistance surface, but had very poor performance on the resistance surface obtained from multi-model landscape genetic analysis. Cumulative resistant kernels appeared to offer the best combination of high predictive performance and sensitivity to differences in resistance surface parameterization. Our analysis highlights that even when two resistance surfaces include the same variables and have a high spatial correlation of resistance values, they may perform very differently in predicting animal movement and population connectivity

Operationalizing Ecological Resilience Concepts for Managing Species and Ecosystems at Risk

This review provides an overview and integration of the use of resilience concepts to guide natural resources management actions. We emphasize ecosystems and landscapes and provide examples of the use of these concepts from empirical research in applied ecology. We begin with a discussion of definitions and concepts of ecological resilience and related terms that are applicable to management. We suggest that a resilience-based framework for management facilitates regional planning by providing the ability to locate management actions where they will have the greatest benefits and determine effective management strategies. We review the six key components of a resilience-based framework, beginning with managing for adaptive capacity and selecting an appropriate spatial extent and grain. Critical elements include developing an understanding of the factors influencing the general and ecological resilience of ecosystems and landscapes, the landscape context and spatial resilience, pattern and process interactions and their variability, and relationships among ecological and spatial resilience and the capacity to support habitats and species. We suggest that a spatially explicit approach, which couples geospatial information on general and spatial resilience to disturbance with information on resources, habitats, or species, provides the foundation for resilience-based management. We provide a case study from the sagebrush biome that illustrates the use of geospatial information on ecological and spatial resilience for prioritizing management actions and determine effective strategies

Editorial: Operationalizing the Concepts of Resilience and Resistance for Managing Ecosystems and Species at Risk

Ecological resilience is essential for maintaining ecosystem services in an era of rapid global change, but successful attempts to operationalize it for managing ecosystems at risk have been limited. Clear formulation and application of ecological resilience concepts can guide ecosystem management so that it enhances the capacity of ecosystems to resist and recover from disturbances and provides adaptive space for periods of ecological reorganization. As originally defined, ecological resilience measures the amount of perturbation required to change an ecosystem from one set of processes and structures to a different set of processes and structures, or the amount of disturbance that a system can withstand before it shifts into a new regime or alternative stable state (Holling, 1973). In applied ecology, ecological resilience is increasingly used to evaluate the capacity of ecosystems to absorb, persist, and adapt to inevitable and often unpredictable change, and to use that information to determine the most effective management strategies (e.g., Chambers et al., 2014; Curtin and Parker, 2014; Pope et al., 2014; Seidl et al., 2016). As the scale and magnitude of ecological change increases, operationalizing ecological resilience for ecosystem management becomes ever more important. To date, much of the literature on ecological resilience has focused on theory, definitions, and broad conceptualizations (e.g., Gunderson, 2000; Folke et al., 2004, 2010; Walker et al., 2004; Folke, 2006; Gunderson et al., 2010). Much of the more applied research has focused on the importance of species diversity and species functional attributes in affecting responses to stress and disturbance (e.g., Pope et al., 2014; Angeler and Allen, 2016; Baho et al., 2017; Roberts et al., 2018). Recent, interdisciplinary research demonstrates that information on the relationships between an ecosystem’s environmental characteristics (climate, topography, soils, and potential biota) and its response to stress and disturbance provides a viable mechanism for assessing ecosystem resilience and relative risks (Chambers et al., 2014; Hessburg et al., 2016; Cushman et al., 2017; Kaszta et al., 2019). Approaches have been developed that enable application of resilience concepts at the scales needed for effective management of ecosystems experiencing progressive and deleterious change. For example, in the sagebrush biome of the western U.S. the concepts of resilience to fire and resistance to non-native invasive annual grasses have recently been used in an interagency framework to enhance conservation and restoration and help prevent listing of greater sage-grouse (Centrocercus urophasianus) under the Endangered Species Act (Chambers et al., 2017). In ecosystems around the globe, levels of ecological stress and disturbance are increasing while resources for natural resources management remain limited. Fully developing the capacity to operationalize the concept of ecological resilience can enable managers to prioritize the types and locations of management activities needed to optimize ecosystem conservation and restoration

Gene Flow in Complex Landscapes: Testing Multiple Hypotheses with Causal Modeling.

Predicting population-level effects of landscape change depends on identifying factors that influence population connectivity in complex landscapes. However, most putative movement corridors and barriers have not been based on empirical data. In this study, we identify factors that influence connectivity by comparing patterns of genetic similarity among 146 black bears (Ursus americanus), sampled across a 3,000-km2 study area in northern Idaho, with 110 landscape-resistance hypotheses. Genetic similarities were based on the pairwise percentage dissimilarity among all individuals based on nine microsatellite loci (average expected heterozygosityp0.79). Landscape-resistance hypotheses describe a range of potential relationships between movement cost and land cover, slope, elevation, roads, Euclidean distance, and a putative movement barrier. These hypotheses were divided into seven organizational models in which the influences of barriers, distance, and landscape features were statistically separated using partial Mantel tests. Only one of the competing organizational models was fully supported: patterns of genetic structure are primarily related to landscape gradients of land cover and elevation. The alternative landscape models, isolation by barriers and isolation by distance, are not supported. In this black bear population, gene flow is facilitated by contiguous forest cover at middle elevations

Differential Effects of Thiazolidinediones on Adipocyte Growth and Recruitment in Zucker Fatty Rats

Background: Adipose tissue grows by two mechanisms: hyperplasia (cell number increase) and hypertrophy (cell size increase). Thiazolidinediones are insulin-sensitizing peroxisome proliferator-activated receptor gamma agonists that are known to affect the morphology of adipose tissue. Methodology: In this study, adipose cell-size probability distributions were measured in six Zucker fa/fa rats over a period of 24 days, from four weeks of age, using micro-biopsies to obtain subcutaneous (inguinal) fat tissue from the animals. Three of the rats were gavaged daily with rosiglitazone, a thiazolidinedione, and three served as controls. These longitudinal probability distributions were analyzed to obtain the rate of increase in cell-size diameter in rosiglitazone-treated animals, and the hyperplasia induced by treatment quantitatively. Conclusions: We found that treatment leads to hypertrophy that leads to an approximately linear rate of cell diameter increase (2 mm/day), and that the hyperplasia evident in treated animals occurs largely within the first eight days of treatment. The availability of additional lipid storage due to treatment may alleviate lipotoxicity and thereby promote insulin sensitivity. The hypothesis that a TZD regimen involving repeated treatments of limited duration may suffice for improvements in insulin sensitivity merits further investigation