A framework for assessing ecosystem dynamics in response to chronic resource alterations induced by global change

TitleA framework for assessing ecosystem dynamics in response to chronic resource alterations induced by global change
Publication TypeJournal Article
Year of Publication2009
AuthorsSmith, MD, Knapp, AK, Collins, SL
Pagination3279 -3289
Accession NumberKNZ001252

In contrast to pulses in resource availability following disturbance events, many of the most pressing global changes, such as elevated atmospheric carbon dioxide concentrations and nitrogen deposition, lead to chronic and often cumulative alterations in available resources. Therefore, predicting ecological responses to these chronic resource alterations will require the modification of existing disturbance-based frameworks. Here, we present a conceptual framework for assessing the nature and pace of ecological change under chronic resource alterations. The “hierarchical-response framework” (HRF) links well-documented, ecological mechanisms of change to provide a theoretical basis for testing hypotheses to explain the dynamics and differential sensitivity of ecosystems to chronic resource alterations. The HRF is based on a temporal hierarchy of mechanisms and responses beginning with individual (physiological/metabolic) responses, followed by species reordering within communities, and finally species loss and immigration. Each mechanism is hypothesized to differ in the magnitude and rate of its effects on ecosystem structure and function, with this variation depending on ecosystem attributes, such as longevity of dominant species, rates of biogeochemical cycling, levels of biodiversity, and trophic complexity. Overall, the HRF predicts nonlinear changes in ecosystem dynamics, with the expectation that interactions with natural disturbances and other global-change drivers will further alter the nature and pace of change. The HRF is explicitly comparative to better understand differential sensitivities of ecosystems, and it can be used to guide the design of coordinated, cross-site experiments to enable more robust forecasts of contemporary and future ecosystem dynamics.