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STEPPS 2000 Year Forest Composition Estimates, Upper Midwest US, Level 2

General Information
Data Package:
Local Identifier:msb-paleon.22.0
Title:STEPPS 2000 Year Forest Composition Estimates, Upper Midwest US, Level 2
Alternate Identifier:2k-yr-ForestComp_UpperMidwest_Level2_v1.0
Alternate Identifier:DOI PLACE HOLDER
Abstract:

Forest ecosystems in eastern North America have been in flux for the last several thousand years, well before Euro-American land clearance and the 20th-century onset of anthropogenic climate change. However, the magnitude and uncertainty of prehistoric vegetation change have been difficult to quantify because of the multiple ecological, dispersal, and sedimentary processes that govern the relationship between forest composition and fossil pollen assemblages. Here we extend STEPPS, a Bayesian hierarchical spatio-temporal pollen-vegetation model, to estimate changes in forest composition in the upper Midwestern United States from about 2,100 to 300 years ago. Using this approach, we find evidence for large changes in the relative abundance of some species, and significant changes in community composition. However, these changes took place against a regional background of changes that were small in magnitude or not statistically significant, suggesting complexity in the spatio-temporal patterns of forest dynamics. The single largest change is the infilling of Tsuga canadensis in northern Wisconsin over the past 2000 years. Despite range in-filling, the range limit of T. canadensis was largely stable, with modest expansion westward. The regional ecotone between temperate hardwood forests and northern mixed hardwood/conifer forests shifted southwestward by 15-20 km in Minnesota and northwestern Wisconsin. Fraxinus, Ulmus, and other mesic hardwoods expanded in the Big Woods region of southern Minnesota. The increasing density of paleoecological data networks and advances in statistical modeling approaches now enables the confident detection of subtle but significant changes in forest composition over the last 2,000 years.This material is based upon work supported by the National Science Foundation under grants #DEB-1241874, 1241868, 1241870, 1241851, 1241891, 1241846, 1241856, 1241930.

Publication Date:2019
Language:english

People and Organizations
Contact:Dawson, Andria (Mount Royal University, Lead PI) [  email ]
Creator:Dawson, Andria (Mount Royal University)
Creator:Goring, Simon (University of Wisconsin, Madison)
Creator:Paciorek, Christopher J. (University of California, Berkeley)
Creator:Jackson, Stephen T. (Southwest Climate Science Center and University of Arizona)
Creator:McLachlan, Jason S. (University of Notre Dame)
Creator:Williams, John W. (University of Wisconsin, Madison)

Data Entities
Other Name:
2Kyrs_Comp_Mean_Level2_v1.0
Description:
netCDF files with dimensions x, y and time (from 2150 YBP to 150 YBP, in 100 year intervals). The variables that store the mean of the posterior estimates of relative abundance are: "ASH","BEECH", "BIRCH", "ELM", "HEMLOCK", "MAPLE", "OAK", "OTHER.CONIFER", "OTHER.HARDWOOD", "PINE", "SPRUCE", "TAMARACK". There are also variables that store information about the projection. These variables are called:“projection”, “Spatial_Reference”, “Projection_Name”
Other Name:
2Kyrs_Comp_SD_Level2_v1.0
Description:
netCDF files with dimensions x, y and time (from 2150 YBP to 150 YBP, in 100 year intervals). The variables that store the standard deviation of the posterior estimates of relative abundance are: "ASH","BEECH", "BIRCH", "ELM", "HEMLOCK", "MAPLE", "OAK", "OTHER.CONIFER", "OTHER.HARDWOOD", "PINE", "SPRUCE", "TAMARACK". There are also variables that store information about the projection. These variables are called:“projection”, “Spatial_Reference”, “Projection_Name”
Detailed Metadata

Data Entities

Non-Categorized Data Resource

Name:2Kyrs_Comp_Mean_Level2_v1.0
Entity Type:netCDF
Description:netCDF files with dimensions x, y and time (from 2150 YBP to 150 YBP, in 100 year intervals). The variables that store the mean of the posterior estimates of relative abundance are: "ASH","BEECH", "BIRCH", "ELM", "HEMLOCK", "MAPLE", "OAK", "OTHER.CONIFER", "OTHER.HARDWOOD", "PINE", "SPRUCE", "TAMARACK". There are also variables that store information about the projection. These variables are called:“projection”, “Spatial_Reference”, “Projection_Name”
Physical Structure Description:
Object Name:2Kyrs_Comp_Mean_Level2_v1.0.nc
Externally Defined Format:
Format Name:netCDF
Data:https://pasta-s.lternet.edu/package/data/eml/msb-paleon/22/0/0081bff74e1d27e6c85186b41d531cd2

Non-Categorized Data Resource

Name:2Kyrs_Comp_SD_Level2_v1.0
Entity Type:netCDF
Description:netCDF files with dimensions x, y and time (from 2150 YBP to 150 YBP, in 100 year intervals). The variables that store the standard deviation of the posterior estimates of relative abundance are: "ASH","BEECH", "BIRCH", "ELM", "HEMLOCK", "MAPLE", "OAK", "OTHER.CONIFER", "OTHER.HARDWOOD", "PINE", "SPRUCE", "TAMARACK". There are also variables that store information about the projection. These variables are called:“projection”, “Spatial_Reference”, “Projection_Name”
Physical Structure Description:
Object Name:2Kyrs_Comp_SD_Level2_v1.0.nc
Externally Defined Format:
Format Name:netCDF
Data:https://pasta-s.lternet.edu/package/data/eml/msb-paleon/22/0/571191cb7209a55ef962c9b40292bc4e

Data Package Usage Rights

We are using the CC-BY 4.0 (Creative Commons Attribution 4.0 International) License. Details of this license can be found here: http://creativecommons.org/licenses/by/4.0/legalcode

Keywords

By Thesaurus:
LTER controlled vocabularybiogeography, community composition, community patterns, maps, plant species, spatial variability, species composition, tree maps, trees

Methods and Protocols

These methods, instrumentation and/or protocols apply to all data in this dataset:

Methods and protocols used in the collection of this data package
Description:

See the methods sections in: Dawson et al., 2019, Quantifying trends and uncertainty in prehistoric forest composition in the upper Midwestern United States, Ecology Dawson et al., 2016, Quantifying pollen-vegetation relationships to reconstruct ancient forests using 19th-century forest composition and pollen data, Quaternary Science Reviews

People and Organizations

Creators:
Individual:Dr. Andria Dawson
Organization:Mount Royal University
Individual:Dr. Simon Goring
Organization:University of Wisconsin, Madison
Individual:Dr. Christopher J. Paciorek
Organization:University of California, Berkeley
Individual:Dr. Stephen T. Jackson
Organization:Southwest Climate Science Center and University of Arizona
Individual:Dr. Jason S. McLachlan
Organization:University of Notre Dame
Individual:Dr. John W. Williams
Organization:University of Wisconsin, Madison
Contacts:
Individual:Dr. Andria Dawson
Position:Lead PI
Organization:Mount Royal University
Phone:
4034407085 (voice)
Email Address:
adawson@mtroyal.ca
Metadata Providers:
Organization:McLachlan Lab
Address:
Notre Dame Biology Department,
Bio Dept address,
Notre Dame, IN 46615 USA
Email Address:
jmclachl@nd.edu
Web Address:
https://sites.nd.edu/paleonproject/

Temporal, Geographic and Taxonomic Coverage

Temporal, Geographic and/or Taxonomic information that applies to all data in this dataset:
Geographic Region:
Description: Uppwer Midwestern United States. Specifically Minnesota, Wisconsin and Michigan's Upper Peninsula.
Bounding Coordinates:
Northern:  49.75Southern:  41.5
Western:  -98.6Eastern:  -81.5
Taxonomic Range:
General Coverage: Other hardwood and conifer tree species are grouped into an “Other hardwood” and "Other conifer" categories.
Classification:
Common Name: Ash
Classification:
Common Name: Fraxinus spp.
Classification:
Common Name: Beech
Classification:
Common Name: Fagus spp.
Classification:
Common Name: Birch
Classification:
Common Name: Betula spp.
Classification:
Common Name: Elm
Classification:
Common Name: Ulmus spp.
Classification:
Common Name: Hemlock
Classification:
Common Name: Tsuga canadensis
Classification:
Common Name: Maple
Classification:
Common Name: Acer spp.
Classification:
Common Name: Oak
Classification:
Common Name: Quercus spp.
Classification:
Common Name: Pine
Classification:
Common Name: Pinus spp.
Classification:
Common Name: Spruce
Classification:
Common Name: Picea spp.
Classification:
Common Name: Tamarack
Classification:
Common Name: Larix laricina

Project

Parent Project Information:

Title: Paleo-ecological Observatory Network (PalEON)
Personnel:
Individual: Jason McLachlan
Address:
100 Galvin Life Sciences,
Notre Dame, IN 46615 USA
Phone:
(574) 631 1850 (voice)
Email Address:
jmclachl@nd.edu
Role:Lead PI
Individual: Jody Peters
Address:
100 Galvin Life Sciences,
Notre Dame, IN 46615 USA
Email Address:
peters.63@nd.edu
Role:Co - Information Manager
Abstract:

PalEON (the PaleoEcological Observatory Network) is an interdisciplinary team of paleoecologists, ecological statisticians, and ecosystem modelers. Our goal is to reconstruct forest composition, fire regime, and climate in forests across the northeastern US and Alaska over the past 2000 years and then use this to drive and validate terrestrial ecosystem models. We will develop a coherent spatiotemporal inference framework to quantify trends and extreme events in paleoecological and paleoclimatic time series. Variables such as forest composition, fire regime, and moisture balance will be inferred from corresponding paleoecological proxies, with rigorous estimates of uncertainty.

These datasets will be applied to improve terrestrial ecosystem models in two contexts. First, we are developing specific data products, such as high- resolution settlement-era forest composition maps from witness tree and General Land Office data, that can be used to drive ecosystem models. PalEON will develop formal data assimilation tools that will allow the models we use to forecast on centennial scales to be informed by decadal- to centennial-scale data. Second, are developing data products for the purpose of model validation (e.g. fire-frequency reconstructions from sedimentary charcoal data). These long-term validation datasets will help us assess the ability of these models to capture past dynamics correctly, and will help us understand why their future projections are so divergent.

Funding:

This material is based upon work supported by the National Science Foundation under Grants #DEB-1241874, 1241868, 1241870, 1241851, 1241891, 1241846, 1241856, 1241930. Any opinions, findings, conclusions, or recommendations expressed in the material are those of the author(s) and do not necessarily reflect the views of the National Science Foundation.

Other Metadata

Additional Metadata

additionalMetadata
        |___text '\n    '
        |___element 'metadata'
        |     |___text '\n      '
        |     |___element 'description'
        |     |     |___text '\n                Publications: 1) Dawson et al., 2019, Quantifying trends and uncertainty in prehistoric forest composition in the upper Midwestern United States, Ecology 2) Dawson et al., 2016, Quantifying pollen-vegetation relationships to reconstruct ancient forests using 19th-century forest composition and pollen data, Quaternary Science Reviews\n            '
        |     |___text '\n    '
        |___text '\n  '

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