Comparison of settlement-era vegetation reconstructions for STEPPS and REVEALS pollen–vegetation models in the northeastern United States. Issue 1 (May 2020)
- Record Type:
- Journal Article
- Title:
- Comparison of settlement-era vegetation reconstructions for STEPPS and REVEALS pollen–vegetation models in the northeastern United States. Issue 1 (May 2020)
- Main Title:
- Comparison of settlement-era vegetation reconstructions for STEPPS and REVEALS pollen–vegetation models in the northeastern United States
- Authors:
- Trachsel, Mathias
Dawson, Andria
Paciorek, Christopher J.
Williams, John W.
McLachlan, Jason S.
Cogbill, Charles V.
Foster, David R.
Goring, Simon J.
Jackson, Stephen T.
Oswald, W. Wyatt
Shuman, Bryan N. - Abstract:
- Abstract: Reconstructions of prehistoric vegetation composition help establish natural baselines, variability, and trajectories of forest dynamics before and during the emergence of intensive anthropogenic land use. Pollen–vegetation models (PVMs) enable such reconstructions from fossil pollen assemblages using process-based representations of taxon-specific pollen production and dispersal. However, several PVMs and variants now exist, and the sensitivity of vegetation inferences to PVM selection, variant, and calibration domain is poorly understood. Here, we compare the reconstructions, parameter estimates, and structure of a Bayesian hierarchical PVM, STEPPS, both to observations and to REVEALS, a widely used PVM, for the pre–Euro-American settlement-era vegetation in the northeastern United States (NEUS). We also compare NEUS-based STEPPS parameter estimates to those for the upper midwestern United States (UMW). Both PVMs predict the observed macroscale patterns of vegetation composition in the NEUS; however, reconstructions of minor taxa are less accurate and predictions for some taxa differ between PVMs. These differences can be attributed to intermodel differences in structure and parameter estimates. Estimates of pollen productivity from STEPPS broadly agree with estimates produced for use in REVEALS, while comparison between pollen dispersal parameter estimates shows no significant relationship. STEPPS parameter estimates are similar between the UMW and NEUS,Abstract: Reconstructions of prehistoric vegetation composition help establish natural baselines, variability, and trajectories of forest dynamics before and during the emergence of intensive anthropogenic land use. Pollen–vegetation models (PVMs) enable such reconstructions from fossil pollen assemblages using process-based representations of taxon-specific pollen production and dispersal. However, several PVMs and variants now exist, and the sensitivity of vegetation inferences to PVM selection, variant, and calibration domain is poorly understood. Here, we compare the reconstructions, parameter estimates, and structure of a Bayesian hierarchical PVM, STEPPS, both to observations and to REVEALS, a widely used PVM, for the pre–Euro-American settlement-era vegetation in the northeastern United States (NEUS). We also compare NEUS-based STEPPS parameter estimates to those for the upper midwestern United States (UMW). Both PVMs predict the observed macroscale patterns of vegetation composition in the NEUS; however, reconstructions of minor taxa are less accurate and predictions for some taxa differ between PVMs. These differences can be attributed to intermodel differences in structure and parameter estimates. Estimates of pollen productivity from STEPPS broadly agree with estimates produced for use in REVEALS, while comparison between pollen dispersal parameter estimates shows no significant relationship. STEPPS parameter estimates are similar between the UMW and NEUS, suggesting that STEPPS parameter estimates are transferable between floristically similar regions and scales. … (more)
- Is Part Of:
- Quaternary research. Volume 95:Issue 1(2020)
- Journal:
- Quaternary research
- Issue:
- Volume 95:Issue 1(2020)
- Issue Display:
- Volume 95, Issue 1 (2020)
- Year:
- 2020
- Volume:
- 95
- Issue:
- 1
- Issue Sort Value:
- 2020-0095-0001-0000
- Page Start:
- 23
- Page End:
- 42
- Publication Date:
- 2020-05
- Subjects:
- Bayesian, -- Pollen, -- Vegetation, -- Fossil, -- Forest, -- Calibration, -- Prediction
Geology, Stratigraphic -- Quaternary -- Periodicals
Glacial epoch -- Periodicals
Stratigraphie -- Quaternaire -- Périodiques
Époque glaciaire -- Périodiques
Geology, Stratigraphic
Glacial epoch
Quaternary Geologic Period
Electronic journals
Periodicals
551.79 - Journal URLs:
- http://www.idealibrary.com ↗
http://firstsearch.oclc.org ↗
http://firstsearch.oclc.org/journal=0033-5894;screen=info;ECOIP ↗
http://www.idealibrary.com/links/toc/qres ↗
http://www.sciencedirect.com/science/journal/00335894 ↗
https://www.cambridge.org/core/journals/quaternary-research ↗ - DOI:
- 10.1017/qua.2019.81 ↗
- Languages:
- English
- ISSNs:
- 0033-5894
- Deposit Type:
- Legaldeposit
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- Physical Locations:
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