Abstract (from http://www.esajournals.org/doi/abs/10.1890/12-2174.1):  Recent research on mountain-dwelling species has illustrated changes in species' distributional patterns in response to climate change. Abundance of a species will likely provide an earlier warning indicator of change than will occupancy, yet relationships between abundance and climatic factors have received less attention. We tested whether predictors of counts of American pikas (

The North Central Climate Science Center Paleoenvironmental Database serves as an archive of Pleistocene proxy records, metadata and derivative products (e.g., chronologies, vegetation and climate reconstructions), and provides a resource for environmental research, facilitating data viewing, synthesis and joint analysis of multiproxy datasets.  As of March 2014, the database consists of 1270 paleoenvironmental records, including proxies of climate (i.e., tree-rings, borehole temperatures, isotopes, diatoms, electrical conductivity, ice cores, loess accumulation), streamflow (i.e.,

ABSTRACT: U.S. National Park Service land managers face a variety of challenges to preserving the biodiversity in their parks. A principle challenge is to minimize the impacts of surrounding land use on park condition and biodiversity. In the absence of ideal sets of data and models, the present study develops methods and results that demonstrate a coarse-filter approach to understanding the effects of land use change on habitat types for four pilot study-areas. The area of analysis for each park is defined by a protected-area-centered-ecosystem.

Locating meadow study sitesMeadow centers as recorded in the ‘Copy of sitecords_areaelev from Caruthers thesis.xls’ file delivered by Debinski in November 2012 were matched to polygons as recorded in files ‘teton97map_area.shp’ and ‘gallatin97map_area.shp’ both also delivered by Debinski in November 2012.In cases where the meadow center did not fall within a meadow polygon, if there was a meadow polygon of the same meadow TYPE nearby (judgment was used here), the meadow center was matched with the meadow polygon of same meadow TYPE.

The dynamic global vegetation model MC1 simulates plant growth and biogeochemical cycles, vegetation type, wildfire, and their interactions. The model simulates competition between trees and grasses (including other herbaceous species), as affected by differential access to light and water, and fire-caused tree mortality (Bachelet et al., 2000; 2001). MC1 projects the dynamics of lifeforms, including evergreen and deciduous needleleaf and broadleaf trees, as well as C3 and C4 grasses. However, the model can also be parameterized for a particular dominant species of the associated lifeform.

Assessments of vegetation response to climate change have generally been made only by equilibrium vegetation models that predict vegetation composition under steady-state conditions. These models do not simulate either ecosystem biogeochemical processes or changes in ecosystem structure that may, in turn, act as feedbacks in determining the dynamics of vegetation change. MC1 is a new dynamic global vegetation model created to assess potential impacts of global climate change on ecosystem structure and function at a wide range of spatial scales from landscape to global.

Abstract (from http://www.srmjournals.org/doi/abs/10.2111/REM-D-13-00079.1):  Big sagebrush, 

VisTrails is an open-source management and scientific workflow system designed to integrate the best of both scientific workflow and scientific visualization systems. Developers can extend the functionality of the VisTrails system by creating custom modules for bundled VisTrails packages. The Invasive Species Science Branch of the U.S. Geological Survey (USGS) Fort Collins Science Center (FORT) and the U.S. Department of the Interior’s North Central Climate Science Center have teamed up to develop and implement such a module—the Software for Assisted Habitat Modeling (SAHM).

Abstract (from http://onlinelibrary.wiley.com/doi/10.1002/joc.4127/abstract):  Gridded topoclimatic datasets are increasingly used to drive many ecological and hydrological models and assess climate change impacts. The use of such datasets is ubiquitous, but their inherent limitations are largely unknown or overlooked particularly in regard to spatial uncertainty and climate trends.

In the North Central U.S., drought is a dominant driver of ecological, economic, and social stress. Drought conditions have occurred in the region due to lower precipitation, extended periods of high temperatures and evaporative demand, or a combination of these factors. This project aims to improve our understanding of drought in the North Central region and determine what future droughts might look like over the 21st century, as climate conditions change.