Using scenarios to evaluate vulnerability of grassland communities to climate change in the Southern Great Plains of the United States

Manier, Daniel J. ; Carr, Natasha B. ; Reese, Gordon C. ; Burris, Lucy

U.S. Geological Survey

DOI  :  10.3133/ofr20191046
RP-ID  :  Open-File Report 2019-1046

学科分类：地球科学(综合)

美国|英语

来源: USGS Publications Warehouse

【 摘 要 】

Scenario planning is a useful tool for identifying key vulnerabilities of ecological systems to changing climates, informed by the potential outcomes for a set of divergent, plausible, and relevant climate scenarios. We evaluated potential vulnerabilities of grassland communities to changing climate in the Southern Great Plains (SGP) and the Landscape Conservation Design pilot area (LCD) for the U.S. Fish and Wildlife Service, Science Applications Program, Great Plains Landscape Conservation Cooperative. Four climate scenarios (warm-dry, warm-wet, hot-dry, and hot-wet) from atmospheric-ocean general circulation models were selected to represent a suite of plausible future climatic conditions. For each scenario, and for contemporary climatic conditions, we predicted the spatial patterns of relative productivity for indicator grass species using statistical models of relative above-ground net primary productivity (hereafter, productivity) based on temperature, precipitation, and soil texture (percent sand, silt, or clay).

Two indicator grass species were selected to represent each of four focal grassland communities: semi-desert grasslands, shortgrass prairie, mixed-grass prairie, and tallgrass prairie. Changes in spatial patterning of bioclimatic conditions conducive for each indicator species as predicted for each climate scenario relative to current land use were used to evaluate potential vulnerability and conservation opportunities for grassland communities. Specifically, the following questions were addressed for each focal grassland community: (1) Where is the productivity of each species predicted to increase, decrease, or remain stable relative to estimated contemporary productivity for the SGP and LCD pilot area, (2) where is the productivity of the two indicator species for each community predicted to increase, decrease, or remain stable, (3) which grassland communities are most vulnerable to changes in composition and vertical structure, (4) how do current land-use patterns contribute to potential vulnerabilities of grassland communities for the climate scenarios evaluated, and (5) how can managers use the vulnerabilities identified to evaluate conservation opportunities in the SGP and LCD?

Current land-use patterns, in combination with the potential effects of a changing climate, pose greater risks to mixed-grass and tallgrass prairies of the SGP compared to semi-desert grasslands and shortgrass prairie. For most climate scenarios evaluated, bioclimatic conditions conducive to the taller species were predicted to contract within some or all the current distribution of mixed-grass and tallgrass prairies within the SGP. An increase in precipitation, however, could potentially ameliorate the negative effects of increasing temperatures as evidenced by higher productivity for the hot-wet scenario compared to the other scenarios for the most vulnerable species. Compounding their greater vulnerability to increasing temperatures coupled with decreasing precipitation, the mixed-grass and tallgrass prairies have been greatly fragmented and converted, primarily by agriculture. In contrast, the climate scenarios evaluated are generally conducive to stable or increasing productivity of indicator species for semi-desert grasslands and shortgrass prairie. In addition, conversion and fragmentation of semi-desert grasslands and shortgrass prairie were relatively low. These results suggest that the synergistic effects of land use and changing climatic conditions could have the greatest effects on the composition and structure of mixed-grass and tallgrass prairies in the SGP. ScienceBase data release files that support this report are available at https://doi.org/10.5066/P9DGJHEP
(Manier and others, 2019).