OOS 47-6
From pollen to carbon: Lessons learned by tying vegetation, land use and climate change from the past to the present and into the future

Wednesday, August 12, 2015: 3:20 PM
314, Baltimore Convention Center
Simon J Goring, Geography, University of Wisconsin, Madison, WI
John W. (Jack) Williams, Geography, University of Wisconsin, Madison, Madison, WI
Andria E. Dawson, University of California, Berkeley, Berkeley, CA
David J. Mladenoff, Forest & Wildlife Ecology, University of Wisconsin, Madison, WI
Jason S. McLachlan, Department of Biology, University of Notre Dame, Notre Dame, IN
Michael Dietze, Earth and Environment, Boston University, Boston, MA
Sydne Record, Biology, Bryn Mawr College, Bryn Mawr, PA
Jaclyn Hattala Mathes, Geography, Dartmouth College, Hanover, NH
Ellen R. Kujawa, Nelson Institute for Environmental Studies, University of Wisconsin-Madison, Madison, WI
Charles V. Cogbill, Plainfield, VT
Stephen T. Jackson, DOI Southwest Climate Science Center, U.S. Geological Survey, Tucson, AZ

The use of cross-scale analyses is increasing in the ecological sciences. Cross-scale analysis allows us to see emergent properties within systems and provides insight into the evolution and interaction of communities through time and across space. An example of cross-scale analysis that allows us to make inference about large-scale land-use change relies on the integration of fossil pollen, forest survey data, and ecosystem models.

Sedimentary pollen data provides a valuable record of ecosystem change through space and time, historically almost exclusivly within the domain of paleoecology. With the development of new analytic techniques and accessible datasets, pollen data can now be firmly integrated into a modeling framework that accounts for past ecosystem change, modern structure, land use change, and, ultimately, future modeling.

THe PalEON Project is combining long term data from pollen with a forest snapshot at the onset of EuroAmerican Settlement (the Public Land Survey), providing an opportunity to see rapid forest cover change in both structure and composition, both through time (with pollen) and at fixed intervals (using modern forest inventory data).  These changes result in new forest assemblages, the loss of forest types, increasing homogeneity and changing patterns of species co-occurrence. Combining this approach with an ecosystem model intercomparison we begin to see the impacts of rapid ecosystem change at multiple scales on our ability to predict an uncertain future.


We present evidence that more than a quarter of modern forests in the Upper Midwestern United States (MI, WI, MN) are compositionally novel relative to PLS baselines.  These novel ecosystems corresponds with the loss of forest communities formerly present in the region, particularly in the Wisconsin Tension Zone.  These changes in community composition are accompanied by new species co-occurrences, and shifts in species-climate relationships in the region, resulting from both regional climate changes since EuroAmerican Settlement and land use conversion that is biased toward warmer and drier portions of the region.

These complex and shifting relationships make it difficult for Dynamic Vegetation Models to adequately capture the proper climate space of major plant functional types, which has significant implications for future modeling. These changes have also affected pollen-vegetation relationships and pollen climate relationships, again with significant implications for the modeling of past ecosystems using pollen.