Skip to main content

Southeast CSC

Efforts to conserve stream and river biota could benefit from tools that allow managers to evaluate landscape-scale changes in species distributions in response to water management decisions. We present a framework and methods for integrating hydrology, geographic context and metapopulation processes to simulate effects of changes in streamflow on fish occupancy dynamics across a landscape of interconnected stream segments. We illustrate this approach using a 482 km2 catchment in the southeastern US supporting 50 or more stream fish species. A spatially distributed, deterministic and physically based hydrologic model is used to simulate daily streamflow for sub-basins composing the catchment. We use geographic data...
We developed a spatially explicit model that simulated future southern pine beetle (Dendroctonus frontalis, SPB) dynamics and pine forest management for a real landscape over 60 years to inform regional forest management. The SPB has a considerable effect on forest dynamics in the Southeastern United States, especially in loblolly pine (Pinus taeda) stands that are managed for timber production. Regional outbreaks of SPB occur in bursts resulting in elimination of entire stands and major economic loss. These outbreaks are often interspersed with decades of inactivity, making long-term modeling of SPB dynamics challenging. Forest management techniques, including thinning, have proven effective and are often recommended...
Population changes and shifts in geographic range boundaries induced by climate change have been documented for many insect species. On the basis of such studies, ecological forecasting models predict that, in the absence of dispersal and resource barriers, many species will exhibit large shifts in abundance and geographic range in response to warming. However, species are composed of individual populations, which may be subject to different selection pressures and therefore may be differentially responsive to environmental change. Asystematic responses across populations and species to warming will alter ecological communities differently across space. Common garden experiments can provide a more mechanistic understanding...
Abstract (from http://journals.plos.org/plosone/article?id=10.1371/journal.pone.0173844): Urban habitats are characterized by impervious surfaces, which increase temperatures and reduce water availability to plants. The effects of these conditions on herbivorous insects are not well understood, but may provide insight into future conditions. Three primary hypotheses have been proposed to explain why multiple herbivorous arthropods are more abundant and damaging in cities, and support has been found for each. First, less complex vegetation may reduce biological control of pests. Second, plant stress can increase plant quality for pests. And third, urban warming can directly increase pest fitness and abundance. These...
Abstract (from http://www.esajournals.org/doi/abs/10.1890/11-2296.1): Physiological tolerance of environmental conditions can influence species-level responses to climate change. Here, we used species-specific thermal tolerances to predict the community responses of ant species to experimental forest-floor warming at the northern and southern boundaries of temperate hardwood forests in eastern North America. We then compared the predictive ability of thermal tolerance vs. correlative species distribution models (SDMs) which are popular forecasting tools for modeling the effects of climate change. Thermal tolerances predicted the responses of 19 ant species to experimental climate warming at the southern site,...
View more...
ScienceBase brings together the best information it can find about USGS researchers and offices to show connections to publications, projects, and data. We are still working to improve this process and information is by no means complete. If you don't see everything you know is associated with you, a colleague, or your office, please be patient while we work to connect the dots. Feel free to contact sciencebase@usgs.gov.