Climate Change and Grasslands: A Life-Zone and Biota Perspective

Grasslands experiencing climatic and atmospheric change may be altered with respect to: (1) geographic extent and location of local/ regional boundaries; (2) productivity, organic matter dynamics and nutrient cycling; and (3) the relative abundance of constituent life forms (woody v. herbaceous), growth forms (tall vs. shorl-statured grasses), and/or photosynthetic physiologies (C3 v. C4). Classification models based on vegetation-climate correlations predict an increase in the global acreage of grassland and savanna at the expense of boceal forest and dry tropical forest. However, extrapolation of these relationships to climates with atmospheric CO2 concentrations without present-day analogues is suspect. Dynamic models of plant succession and process models accounting for plant physiological limitations and constraints imposed by disturbance, competition and lopo-edaphic factors ace promising, but are challenged at regional and global scales. Correlative and mechanistic models highlight precipitation as a key variable in predicting ecological consequences of climate change and CO2 enrichment on grasslands. Anthropogenic and climate-related natural disturbance (fire, pathogen outbreaks, floods, windstorms) will affect the rate, extent and nature of vegetation change. Whole­ system experiments in tallgrass prairie suggest C4 grasses may be more responsive to increased CO2 than previously. thought. However, increases in above-ground net primary production accompanied by reductions in nutrient concentrations may reduce litter decomposition rates and decrease ruminant intake and performance. Dynamic simulations of C3 and C4 grasses indicate variation in precipitation will have a much greater influence on production than doubling CO2 or raising temperature. Predicting the ecosystem level effects of climate change is difficult because temperature, precipitation and CO2 will change together and interact in synergistic or offselting ways with disturbance to influence ecosystem processes. The potential complexity of responses calls for direct experimentation on systems with diverse characteristics at scales where feedbacks between biotic systems and atmospheric properties can be manipulated and quantified.