Abstract (from http://econpapers.repec.org/paper/agsaaea16/235895.htm): We evaluate the regional-level agricultural impacts of climate change in the Northern Great Plains. We first estimate a non-linear yield-weather relationship for all major commodities in the area: corn, soybeans, spring wheat and alfalfa. We separately identify benevolent and harmful temperature thresholds for each commodity, and control for severe-to-extreme dry/wet conditions in our yield models.

Members of the Eastern Shoshone and Northern Arapaho Tribes have been working with an interdisciplinary team of social, ecological, and climate scientists from the North Central CSC, the High Plains Regional Climate Center, and the National Drought Mitigation Center along with other university and agency partners to prepare regular climate and drought summaries to aid in managing water resources on the Wind River Reservation and in surrounding areas. 

The potential influence of seed bank composition on range shifts of species due to climate change is unclear. Seed banks can provide a means of both species persistence in an area and local range expansion in the case of increasing habitat suitability, as may occur under future climate change. However, a mismatch between the seed bank and the established plant community may represent an obstacle to persistence and expansion. In big sagebrush (Artemisia tridentata) plant communities in Montana, USA, we compared the seed bank to the established plant community.

We assessed the vulnerability of ecological processes and vegetation to climate change in the US Northern Rocky Mountains with a focus on the Greater Yellowstone Ecosystem. We found that climate has warmed substantially since 1900 while precipitation has increased. An index of aridity decreased until about 1980 and then increased slightly. Projected future climate indicates warming of about 3-7 degrees C by 2100 and a substantial increase in aridity, depending on climate scenario.

Abstract (from http://journals.ametsoc.org/doi/abs/10.1175/JAMC-D-15-0276.1): Remotely sensed land skin temperature (LST) is increasingly being used to improve gridded interpolations of near-surface air temperature. The appeal of LST as a spatial predictor of air temperature rests in the fact that it is an observation available at spatial resolutions fine enough to capture topoclimatic and biophysical variations.

Ecological abundance data are often recorded on an ordinal scale in which the lowest
category represents species absence. One common example is when plant species cover
is visually assessedwithin bounded quadrats and then assigned to pre-defined cover class
categories.We present an ordinal beta hurdle model that directly models ordinal category
probabilitieswith a biologically realistic beta-distributed latent variable.Ahurdle-at-zero
model allows ecologists to explore distribution (absence) and abundance processes in an

This research element supports vulnerability assessment for climate adaptation (Glick et al. 2011) by focusing on the provision of best available climate information for the region in order to inform analysis of ecosystem exposure to change.  Climate in the North Central United States (NCUS) is driven by a combination that includes large-scale patterns in atmospheric circulation, the region’s complex topography extending from the High Rockies to the Great Plains, and geographic variations in water and surface-energy balance.