Characterization of climatically-driven ecological responses: Implications for the NEON continental design

Background/Question/Methods

One of the key challenges facing the ecological community lies in understanding the impacts of forecast climate change on the structure and function of ecosystems both through time and across large spatial extents. There are two main obstacles that currently hinder the ability to quantify ecosystem change in this manner within the context of a shifting climate. First, with respect to key ecosystem responses, there are limited data that have sufficient spatial-temporal resolution and extent. Second, methods for quantifying long term changes in ecosystem responses with complex spatial and temporal structure driven by climatic forcing are not well developed. Since the lack of methods is at least partly due to the limited availability of the necessary data, we have assembled a simulation framework. The simulation framework allows for the parametric specification of the following model components: measurement error, the functional form of the link between climate drivers and the ecosystem response, and annual process variability including non-separable space-time covariance structures. In addition this framework accommodates the flexible specification of distributional models for parameters which allows for explicit probabilistic characterization of the uncertainty.

Results/Conclusions

This simulation study provides a framework to characterize an “envelope” of values for these parameters that allow for the detection of trends as well as selection among different functional forms that characterize the relationship between climate drivers and ecosystem response variables of interest. This work represents an important step in the ongoing effort to refine quantitative methods that identify not only climatically driven trends in ecological responses, but also allow for the determination of the functional form of the link between climate forcing and ecosystem responses.  Our results show that an abstract representation of the NEON network allows for the detection of trends and functional forms linking climate drivers and ecological responses in the presence of commonly observed levels of variability and magnitude of signal.