Understanding rates of change: A case study using fossil pollen records from California to assess the potential for and challenges to a regional data synthesis
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Abstract
Insights into the rates at which ecosystems and vegetation respond to a changing climate is fundamental to anticipating impacts of projected climate change. Characterization of vegetation change over millennia to centuries has potential to make an important contribution toward this goal, and regional scale syntheses of fossil pollen data can provide the foundation for this understanding. However, challenges of data analysis and integration are nontrivial. Here we present a case study in which publicly available fossil pollen data for California are assessed and analyzed. The data are selected according to a clearly defined selection criteria, and a Rate of Change (RoC) value is calculated to assess rates of vegetation change in California from ~15k BP (before A.D. 1950) to the present. Our results highlight several challenges presented by the extant data sets, including temporal sampling variation within and between records, large age control uncertainties, and sparse, geographically biased coverage. Recommendations for methodological refinements to better characterize ecological rates of change include increasing sampling frequency, maintaining a consistent temporal spacing within records, and applying probabilistic approaches to existing pollen data sets.
Study Area
| Publication type | Article |
|---|---|
| Publication Subtype | Journal Article |
| Title | Understanding rates of change: A case study using fossil pollen records from California to assess the potential for and challenges to a regional data synthesis |
| Series title | Quaternary International |
| DOI | 10.1016/j.quaint.2020.04.044 |
| Volume | 621 |
| Year Published | 2022 |
| Language | English |
| Publisher | Elsevier |
| Contributing office(s) | Geology, Minerals, Energy, and Geophysics Science Center |
| Description | 11 p. |
| First page | 26 |
| Last page | 36 |
| Country | United States |
| State | California |
| Google Analytic Metrics | Metrics page |