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      The Effects of Human-Mediated Habitat Fragmentation on a Sedentary Woodland-Associated Species (Rhinolophus hipposideros) at Its Range Margin

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          Confounding factors in the detection of species responses to habitat fragmentation.

          Habitat loss has pervasive and disruptive impacts on biodiversity in habitat remnants. The magnitude of the ecological impacts of habitat loss can be exacerbated by the spatial arrangement -- or fragmentation -- of remaining habitat. Fragmentation per se is a landscape-level phenomenon in which species that survive in habitat remnants are confronted with a modified environment of reduced area, increased isolation and novel ecological boundaries. The implications of this for individual organisms are many and varied, because species with differing life history strategies are differentially affected by habitat fragmentation. Here, we review the extensive literature on species responses to habitat fragmentation, and detail the numerous ways in which confounding factors have either masked the detection, or prevented the manifestation, of predicted fragmentation effects. Large numbers of empirical studies continue to document changes in species richness with decreasing habitat area, with positive, negative and no relationships regularly reported. The debate surrounding such widely contrasting results is beginning to be resolved by findings that the expected positive species-area relationship can be masked by matrix-derived spatial subsidies of resources to fragment-dwelling species and by the invasion of matrix-dwelling species into habitat edges. Significant advances have been made recently in our understanding of how species interactions are altered at habitat edges as a result of these changes. Interestingly, changes in biotic and abiotic parameters at edges also make ecological processes more variable than in habitat interiors. Individuals are more likely to encounter habitat edges in fragments with convoluted shapes, leading to increased turnover and variability in population size than in fragments that are compact in shape. Habitat isolation in both space and time disrupts species distribution patterns, with consequent effects on metapopulation dynamics and the genetic structure of fragment-dwelling populations. Again, the matrix habitat is a strong determinant of fragmentation effects within remnants because of its role in regulating dispersal and dispersal-related mortality, the provision of spatial subsidies and the potential mediation of edge-related microclimatic gradients. We show that confounding factors can mask many fragmentation effects. For instance, there are multiple ways in which species traits like trophic level, dispersal ability and degree of habitat specialisation influence species-level responses. The temporal scale of investigation may have a strong influence on the results of a study, with short-term crowding effects eventually giving way to long-term extinction debts. Moreover, many fragmentation effects like changes in genetic, morphological or behavioural traits of species require time to appear. By contrast, synergistic interactions of fragmentation with climate change, human-altered disturbance regimes, species interactions and other drivers of population decline may magnify the impacts of fragmentation. To conclude, we emphasise that anthropogenic fragmentation is a recent phenomenon in evolutionary time and suggest that the final, long-term impacts of habitat fragmentation may not yet have shown themselves.
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            Enhanced Bayesian modelling in BAPS software for learning genetic structures of populations

            Background During the most recent decade many Bayesian statistical models and software for answering questions related to the genetic structure underlying population samples have appeared in the scientific literature. Most of these methods utilize molecular markers for the inferences, while some are also capable of handling DNA sequence data. In a number of earlier works, we have introduced an array of statistical methods for population genetic inference that are implemented in the software BAPS. However, the complexity of biological problems related to genetic structure analysis keeps increasing such that in many cases the current methods may provide either inappropriate or insufficient solutions. Results We discuss the necessity of enhancing the statistical approaches to face the challenges posed by the ever-increasing amounts of molecular data generated by scientists over a wide range of research areas and introduce an array of new statistical tools implemented in the most recent version of BAPS. With these methods it is possible, e.g., to fit genetic mixture models using user-specified numbers of clusters and to estimate levels of admixture under a genetic linkage model. Also, alleles representing a different ancestry compared to the average observed genomic positions can be tracked for the sampled individuals, and a priori specified hypotheses about genetic population structure can be directly compared using Bayes' theorem. In general, we have improved further the computational characteristics of the algorithms behind the methods implemented in BAPS facilitating the analyses of large and complex datasets. In particular, analysis of a single dataset can now be spread over multiple computers using a script interface to the software. Conclusion The Bayesian modelling methods introduced in this article represent an array of enhanced tools for learning the genetic structure of populations. Their implementations in the BAPS software are designed to meet the increasing need for analyzing large-scale population genetics data. The software is freely downloadable for Windows, Linux and Mac OS X systems at .
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              Linkage disequilibrium estimates of contemporary Ne using highly variable genetic markers: a largely untapped resource for applied conservation and evolution

              Genetic methods are routinely used to estimate contemporary effective population size (N e) in natural populations, but the vast majority of applications have used only the temporal (two-sample) method. We use simulated data to evaluate how highly polymorphic molecular markers affect precision and bias in the single-sample method based on linkage disequilibrium (LD). Results of this study are as follows: (1) Low-frequency alleles upwardly bias , but a simple rule can reduce bias to
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                Author and article information

                Journal
                Acta Chiropterologica
                Acta Chiropterologica
                Museum and Institute of Zoology at the Polish Academy of Sciences
                1508-1109
                1733-5329
                December 2016
                December 2016
                : 18
                : 2
                : 377-393
                Article
                10.3161/15081109ACC2016.18.2.006
                afd121fb-9ced-42cc-814e-035b6ba588ea
                © 2016

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