Long-term Ecological Dynamics (LTED)

Ecological communities are highly dynamic in space and time. Analysis of spatial variability has a long history in ecology, yet because of the historical dearth of long-term, well-documented, on-line datasets we know comparatively little about rates and patterns of temporal change in ecological communities. Fortunately, an expanding array of long-term datasets is now available through sources such as the LTER Network and LTREB program. This growing availability of high-resolution (annual) temporal data sets creates new opportunities to address questions about how ecological communities change over time in response to global environmental change.

Although, several metrics for analyzing long-term change in biotic communities have been developed, most are used in one-off approaches, frequently involving calculations, modeling, and visualization in spreadsheets or custom programs (e.g., Rank Clocks). Most of these indices are not available in common statistical packages. Our research will combine two open source programs, the statistical package R and the Kepler workflow system, to make long-term community change analysis more accessible. Taking the extra step and encoding complete workflows for community analysis in Kepler will provide the option of re-running analyses whenever new data are available. The output, a value added data product, may be used for purposes well beyond detecting and interpreting community change.

During this three year project we will improve Kepler's workflow sharing subsystems to grow an enthusiastic group of ecological researchers that create and share temporal community analyses to accelerate the study of community change. And finally, we will refactor Kepler's data handling subsystems to be compatible with the emergent DataONE repository federation.

As ecologists continue to gather long-term data at site, regional, continental and global scales, there will be an increasing need for tools to measure the pattern and rate of change in plant and animal communities in response to multiple environmental drivers. Gathering together multiple metrics of ecological dynamics into one toolbox will provide ecologists with a new set of tools for quantifying how communities change over time. Our approach will build upon many recent eco-informatics developments (EML, DataONE, LTER NIS, PASTA, Kepler) to advance ecological research. We will use long-term data sets collected by LTER sites and others to demonstrate data and system accessibility and interoperability, and through implementation of new metrics we will gain insights into community change on a continental scale. Data will be accessed via the DataONE portal and the LTER Network Information System using metadata encoded in the Ecological Metadata Language and analyzed with R routines in Kepler workflows. We will also offer community training workshops to develop metrics of change and for training the broader community to use and improve the workflows being developed as part of this research effort.