|BAGCHI, SUMANTA - Indian Institute Of Science|
|SINGH, NAVINDER - University Of Umea|
|BRISKE, DAVID - Texas A&M University|
Submitted to: Ecological Society of America (ESA)
Publication Type: Abstract Only
Publication Acceptance Date: 2/23/2015
Publication Date: 8/9/2015
Citation: Bagchi, S., Singh, N.J., Bestelmeyer, B.T., Briske, D.D. 2015. Distinguishing linear, nonlinear, transient and persistent vegetation dynamics to characterize empirical signatures of ecological resilience [abstract]. 100th Annual Meeting of the Ecological Society of America (ESA). August 9-14, 2015. Baltimore, MD. OOS 71-6.
Technical Abstract: Background/Question/Methods To characterize and interpret ecological resilience and state change is a fundamental question in ecology. In the same ecosystem, across different communities, one can encounter relative stability, abrupt directional shifts, transient reversible change, as well as nondirectional drift through time. These behaviors can be regarded as varying expressions of ecological resilience. Analytical protocols, which can characterize and distinguish such behaviors and clarify relevant timescales, are generally limited in their ability to detect nonlinear events in multivariate ecological data. We explore whether and how four major types of vegetation dynamics: reversible change, nondirectional drift, abrupt directional change, and relative stability, can be distinguished in ecological time series. We analyzed 12 long-term replicated vegetation records based on permanent plots in North American grasslands to quantify the four types of vegetation dynamics through distance-based metrics of community change. Results/Conclusions: Overall, relative stability and non-directional drift were the most common behaviors. Compositional stability was most common in the shortgrass and tallgrass sites. Abrupt directional vegetation shifts were recorded at the mixedgrass sites, sagebrush steppes, and in annual grasslands. Reversible dynamics were less frequent, but occurred in nearly all sites. These results quantify relative occurrence of different dynamics and offer insights into resilience-profiles of ecosystems. They also provide quantitative metrics that offer opportunities for application of resilience concepts to interpret ecosystem dynamics.