2020 ESA Annual Meeting (August 3 - 6)

OOS 48 Abstract - Classifications as a research asset for the future: The role of classifications in lowering uncertainty in tracking ecological change

Wednesday, August 5, 2020: 1:45 PM
Esteban Muldavin, Department of Biology, University of New Mexico, Albuquerque, NM and John T. Hunter, School of Environmental & Rural Science, University of New England, Armidale, NSW, Australia
Background/Question/Methods

Vegetation classifications such as the U.S National Vegetation Classification and the International Vegetation Classification serve to organize our understanding of ecosystem types, their composition, environments and dynamics, and can help focus and define the domains of our ecological questions. In particular, as the growing literature on ecological change has increased our capacity to conduct data-rich meta-analyses of change within and among ecosystem types and geographies, the use of standardized, content rich, and well-organized vegetation classifications can promote making these meta-analyses more effective. That is, classifications can help reduce thematic confusion within and among studies that sometimes leads to high uncertainty in results. Further, within any given field or experimental study, the consistent reference to and description of ecosystem types of interest can support effective partitioning and stratification for statistical analysis and model development. This also helps set sideboards for the breadth of a study and put it within a comparative framework that aids in effective communication of results and the informing of subsequent studies. We provide examples of how vegetation classifications can help structure research designs, capture outcomes in a systematic and logical framework, bolster communication, and help track ecological change from the local to global scales.

Results/Conclusions

A review of meta-analyses of ecosystem responses to disturbance uncovered a recurring, often explicitly stated, need for a consistent approach to characterizing ecosystem types to better partition or stratify the analyses, particularly across broad geographic extents. We found that such information gaps in studies can be addressed effectively using both bottom-up and top-down classification approaches. For example, a long-term study of Chihuahuan Desert vegetation change in the U.S. benefited from assignment of sample plots from the Association up to the Group level of the U.S. National Vegetation Classification to stratify the analysis and clarify results. We also show how such outcomes can inform the content of state-and-transition models of ecosystem dynamics and aid in management of ecological change on the ground. In Australia, a current project to build a national vegetation classification from Formation level down to the Division of the International Vegetation Classification will significantly help place the ecosystems of that continent in a global framework as it becomes in and of itself a bellwether of ecological change. In the milieu of a rapidly changing world, ecological classifications can serve not only to catalog ecological knowledge but help address fundamental questions on the drivers and impacts of ecological change.