Environmental Stress, Bottom-up Effects, and Community Dynamics: Integrating Molecular-Physiological and Ecological...

Environmental stress and nutrient/productivity models predict the responses of community structure along gradients of physical conditions and bottom-up effects. Although both models have succeeded in helping to understand variation in ecological communities, most tests have been qualitative. Until recently, two roadblocks to more quantitative tests in marine environments have been a lack of (1) inexpensive, field-deployable technology for quantifying (e.g.) temperature, light, salinity, chlorophyll, and productivity, and (2) methods of quantifying the sub-organismal mechanisms linking environmental conditions to their ecological expression. The advent of inexpensive remote-sensing technology, adoption of molecular techniques such as quantification of heat-shock proteins and RNA:DNA ratios, and the formation of interdisciplinary alliances between ecologists and physiologists has begun to overcome these roadblocks. An integrated eco-physiological approach focuses on the determinants of: distributional limits among microhabitat patches and along (local-scale) environmental gradients (e.g., zonation); among-site (mesoscale) differences in community pattern; and geographic (macroscale) differences in ecosystem structure. These approaches promise new insights into the physiological mechanisms underlying variation in processes such as species interactions, physical disturbance, survival and growth. Here, we review two classes of models for community dynamics, and present examples of ecological studies of these models in consumer-prey systems. We illustrate the power of new molecular tools to characterize the sub-organismal responses of some of the same consumers and prey to thermal stress and food concentration. Ecological and physiological evidence tends to be consistent with model predictions, supporting our argument that we are poised to make major advances in the mechanistic understanding of community dynamics along key environmental gradients.