Geology topics

Steven R. Beissinger

Publications and source records attributed to Steven R. Beissinger.

5 recordsLinked to original sources

USGS2017

Climate change refugia and habitat connectivity promote species persistence

Background Climate change refugia, areas buffered from climate change relative to their surroundings, are of increasing interest as natural resource managers seek to prioritize climate adaptation actions. However, evidence that refugia buffer the effects of anthropogenic climate change is largely missing. Methods Focusing on the climate-sensitive Belding’s ground squirrel ( Urocitellus beldingi ), we predicted that highly connected Sierra Nevada meadows that had warmed less or shown less precipitation change over the last century would have greater population persistence, as measured by short-term occupancy, fewer extirpations over the twentieth century, and long-term persistence measured through genetic diversity. Results Across California, U. beldingi were more likely to persist over the last century in meadows with high connectivity that were defined as refugial based on a suite of temperature and precipitation factors. In Yosemite National Park, highly connected refugial meadows were more likely to be occupied by U. beldingi . More broadly, populations inhabiting Sierra Nevada meadows with colder mean winter temperatures had higher values of allelic richness at microsatellite loci, consistent with higher population persistence in temperature-buffered sites. Furthermore, both allelic richness and gene flow were higher in meadows that had higher landscape connectivity, indicating the importance of metapopulation processes. Conversely, anthropogenic refugia, sites where populations appeared to persist due to food or water supplementation, had lower connectivity, genetic diversity, and gene flow, and thus might act as ecological traps. This study provides evidence that validates the climate change refugia concept in a contemporary context and illustrates how to integrate field observations and genetic analyses to test the effectiveness of climate change refugia and connectivity. Conclusions Climate change refugia will be important for conserving populations as well as genetic diversity and evolutionary potential. Our study shows that in-depth modeling paired with rigorous fieldwork can identify functioning climate change refugia for conservation.

California↗

USGS2017

Erosion of refugia in the Sierra Nevada meadows network with climate change

Climate refugia management has been proposed as a climate adaptation strategy in the face of global change. Key to this strategy is identification of these areas as well as an understanding of how they are connected on the landscape. Focusing on meadows of the Sierra Nevada in California, we examined multiple factors affecting connectivity using circuit theory, and determined how patches have been and are expected to be affected by climate change. Connectivity surfaces varied depending upon the underlying hypothesis, although meadow area and elevation were important features for higher connectivity. Climate refugia that would promote population persistence were identified from downscaled climate layers, based on locations with minimal climatic change from historical conditions. This approach was agnostic to specific species, yielding a broad perspective about changes and localized habitats. Connectivity was not a consistent predictor of refugial status in the 20th century, but expected future climate refugia tended to have higher connectivity than those that recently deviated from historical conditions. Climate change is projected to reduce the number of refugial meadows on a variety of climate axes, resulting in a sparser network of potential refugia across elevations. Our approach provides a straightforward method that can be used as a tool to prioritize places for climate adaptation.

California↗

USGS2016

Incorporating imperfect detection into joint models of communites: A response to Warton et al.

Warton et al. [1] advance community ecology by describing a statistical framework that can jointly model abundances (or distributions) across many taxa to quantify how community properties respond to environmental variables. This framework specifies the effects of both measured and unmeasured (latent) variables on the abundance (or occurrence) of each species. Latent variables are random effects that capture the effects of both missing environmental predictors and correlations in parameter values among different species. As presented in Warton et al. , however, the joint modeling framework fails to account for the common problem of detection or measurement errors that always accompany field sampling of abundance or occupancy, and are well known to obscure species- and community-level inferences.

Trends in Ecology and Evolution↗

USGS2010

Uncloaking a cryptic, threatened rail with molecular markers: origins, connectivity and demography of a recently-discovered population

The threatened California Black Rail lives under dense marsh vegetation, is rarely observed, flies weakly and has a highly disjunct distribution. The largest population of rails is found in 8–10 large wetlands in San Francisco Bay (SF Bay), but a population was recently discovered in the foothills of the Sierra Nevada Mountains (Foothills), within a wetland network comprised of over 200 small marshes. Using microsatellite and mitochondrial analyses, our objectives were to determine the origins, connectivity and demography of this recently-discovered population. Analyses of individuals from the Foothills ( n = 31), SF Bay ( n = 31), the Imperial Valley ( n = 6) and the East Coast ( n = 3), combined with rigorous power evaluations, provided valuable insights into past history and current dynamics of the species in Northern California that challenge conventional wisdom about the species. The Foothills and SF Bay populations have diverged strongly from the Imperial Valley population, even more strongly than from individuals of the East Coast subspecies. The data also suggest a historical presence of the species in the Foothills. The SF Bay and Foothills populations had similar estimated effective population size over the areas sampled and appeared linked by a strongly asymmetrical migration pattern, with a greater probability of movement from the Foothills to SF Bay than vice versa. Random mating was inferred in the Foothills, but local substructure among marshes and inbreeding were detected in SF Bay, suggesting different dispersal patterns within each location. The unexpected dimensions of Black Rail demography and population structure suggested by these analyses and their potential importance for management are discussed.

California↗

USGS2006

Modeling approaches in avian conservation and the role of field biologists

This review grew out of our realization that models play an increasingly important role in conservation but are rarely used in the research of most avian biologists. Modelers are creating models that are more complex and mechanistic and that can incorporate more of the knowledge acquired by field biologists. Such models require field biologists to provide more specific information, larger sample sizes, and sometimes new kinds of data, such as habitat-specific demography and dispersal information. Field biologists need to support model development by testing key model assumptions and validating models. The best conservation decisions will occur where cooperative interaction enables field biologists, modelers, statisticians, and managers to contribute effectively. We begin by discussing the general form of ecological models—heuristic or mechanistic, "scientific" or statistical—and then highlight the structure, strengths, weaknesses, and applications of six types of models commonly used in avian conservation: (1) deterministic single-population matrix models, (2) stochastic population viability analysis (PVA) models for single populations, (3) metapopulation models, (4) spatially explicit models, (5) genetic models, and (6) species distribution models. We end by considering their unique attributes, determining whether the assumptions that underlie the structure are valid, and testing the ability of the model to predict the future correctly.

Ornithological Monographs↗