Bridging the divide: linking genomics to ecosystem responses to climatic change

Melinda Smith (Yale University)
melinda.smith@yale.edu

Although there remains uncertainty as to the rate and magnitude of climate change, it is clear that human-caused changes in climate are already occurring and will continue into the next century. Hence there is pressing need to understand and predict the consequences of present and projected climate changes on ecological systems. Predicting the responses of ecosystems to climate change requires scaling up from key mechanisms, such as photosynthesis or growth that are best understood at the organism level. These mechanisms are fundamentally linked to genes, gene networks, and their interplay with the environment. However, our understanding of the interplay between genes and ecological processes at levels beyond the individual organism is nonexistent. Thus, a comprehensive, mechanistic understanding of ecosystem responses to climate change requires that responses at the organism level (i.e., individual plant) be directly related to responses of the genome, and these in turn be linked to higher levels of organization.

With current technological capabilities in genomic science, we can directly assess gene expression at a genome-wide scale using microarray technology (cDNA). When related to different experimental treatments, an integrated and ‘global’ view of organism responses to the environment is the result. I and collaborators from Kansas State University, Colorado State University, and the University of Minnesota-Duluth plan to link genomic and ecological approaches by using the functional genomic information derived from model organisms to link genomic responses of two closely related and ecologically important species in a grassland system to ecological responses to climate change.

This project will take advantage of an ongoing climatic change experiment in natural grassland - the Rainfall Manipulation Plots (RaMPs, http://www.konza.ksu.edu/ramps) at the Konza Prairie Biological Station (http://www.konza.ksu.edu) in northeastern Kansas. The RaMPs experimental infrastructure examines two key, predicted environmental changes associated with energy production: (1) increased temperature (1-2 degrees C warming), and (2) more variable precipitation regimes, specifically increased time between and intensity of rainfall events. After 6 years of experimentally increased rainfall variability in the experiment, impacts at multiple levels of biological organization have been observed. Warming treatments initiated in 2003 are expected to exacerbate the effects of precipitation variability.

Top left: Aerial view of the Rainfall Manipulation Plot (RaMPs) experiment at the Konza Prairie Biological Station. Top right : View of RaMPs with IR heating lamps.

Now, within this backdrop of known and predicted ecological responses, this project is poised to gain a more detailed mechanistic and predictive understanding by explicitly linking species-level genomic data to fundamental plant physiological responses. By focusing efforts on two dominant C 4 grasses, Andropogon gerardii and Sorghastrum nutans that are closely related to a model genomic organism (Zea mays), known to respond differentially to altered precipitation, and whose responses strongly influence community and ecosystem characteristics, the project will attempt to directly and relevantly scale genome-level responses to ecological processes observed at the plant and plant population levels, as well as to those emergent responses at the community and ecosystem levels.

Specifically, a flexible tiered sampling scheme that will involve intensive, highly replicated sampling to assess independent and interactive effects of the temperature/precipitation manipulations will be used, whereas more explicit analytical foci are planned for particular climatic events within and among seasons. Information on the relative changes in gene expression determined with microarray and real-time PCR (polymerase chain reaction) technologies will be collected concurrently with a suite of physiological variables to identify genes or gene clusters related to photosynthesis, water stress, and/or heat tolerance that are consistently up- or down-regulated in response to the experimental manipulations in the target species. These then will be scaled to the emergent community and ecosystem level responses based on differential responses of the individual species. This research will bridge a fundamental divide between two disciplines in biology traditionally focusing on divergent domains of inference, strengthening both fields by developing and testing an integrative approach to studying potential effects of climatic change on the structure and functioning of terrestrial ecosystems.

For more information, visit Prof. Smith's EEB web site.