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STEPPS 8000 Year Forest Composition Estimates, Northeastern US, Level 2

General Information
Data Package:
Local Identifier:msb-paleon.44.1
Title:STEPPS 8000 Year Forest Composition Estimates, Northeastern US, Level 2
Alternate Identifier:8k-yr-ForestComp_NorthEastUS_Level2_v1.0
Alternate Identifier:DOI PLACE HOLDER
Abstract:

These reconstructions of forest composition in the northeastern US for the last 8,000 years help establish natural baselines, variability, and trajectories of forest dynamics before and during the emergence of intensive anthropogenic land use. These reconstructions are based on 1) the pollen–vegetation model (PVM) STEPPS, 2) a network of fossil and modern pollen data mostly drawn from the Neotoma Paleoecology Database (www.neotomadb.org), and 3) a vegetation calibration dataset based on a spatial statistical model of relative tree abundances from the Township Proprietor Survey (TPS) from the early EuroAmerican settlement period. STEPPS is a process-based Bayesian Hierarchical Model that is run in two stages: a parameterization stage based upon spatial data layers of forest composition and pollen assemblages, and a prediction stage based on fossil pollen assemblages. The statistical modeling of the TPS forest data and relative abundances is described by Paciorek et al. (2016, PLoS One, doi: 10.1371/journal.pone.0150087) and is available at EDI as PalEON Product msb.paleon.1, doi: 10.6073/pasta/8544e091b64db26fdbbbafd0699fa4f9. The parameterization of STEPPS and comparison to REVEALS, a different widely used PVM, is described by Trachsel et al. (2020, Quaternary Research, doi:10.1017/qua.2019.81). 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. STEPPS parameter estimates are similar between the UMW and NEUS, suggesting that STEPPS parameter estimates are transferable between floristically similar regions and scales. The parameterized STEPPS model was then run for a network of fossil pollen records from the Neotoma Paleoecology Database to produce posterior estimates of forest composition at 100-year intervals for the last 8,000 years. The work from this prediction stage was not published at the time of deposition of these records with EDI. Hence, at this time, this EDI data deposition is the primary citation endpoint. The prediction methods generally follow those described by Dawson et al. (2019, Ecology, doi: 10.1002/ecy.2856). 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:2020-12-02
Language:english

Time Period
Begin:
Timescale:Absolute
Time estimate:8000 BP
Time explanation:Radiocarbon methods paper here, text citation
End:
Timescale:Absolute
Time estimate:50 BP
Time explanation:Radiocarbon methods paper here, text citation

People and Organizations
Contact:Dawson, Andria (Mount Royal University, Lead PI) [  email ]
Contact:Trachsel, Mathias (University of Wisconsin, Madison, Lead PI) [  email ]
Creator:Trachsel, Mathias (University of Wisconsin, Madison)
Creator:Dawson, Andria (Mount Royal University)
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)
Creator:Cogbill, Charles (Harvard Forest)
Creator:Foster, David (Harvard Forest and Harvard University)
Creator:Shuman, Bryan (University of Wyoming)
Creator:Oswald, W. Wyatt (Harvard Forest and Emerson College)

Data Entities
Other Name:
STEPPS-fractional-composition_NEUS-mean
Description:
netCDF files with dimensions x (meters), y (meters) and time (from 8000 YBP to 250 YBP, in 100 year intervals). The variables that store the mean proportion of the posterior estimates of relative abundance are: "Ash","Beech", "Birch", "Chestnut", "Hemlock", "Hickory", "Maple", "Oak", "Oher conifer", "Other hardwood", "Pine", "Spruce", "Tamarack". There are also variables that store information about the projection. These variables are called:“projection” (NAD83/Great Lakes St. Lawrence Albers), “Spatial_Reference” (ESPG:3175), “Projection_Name” (Albers Equal Area)
Other Name:
STEPPS-fractional-composition_NEUS-sd
Description:
netCDF files with dimensions x (meters), y (meters) and time (from 8000 YBP to 250 YBP, in 100 year intervals). The variables that store the standard deviation of the proportion of the posterior estimates of relative abundance are: "Ash","Beech", "Birch", "Chestnut", "Hemlock", "Hickory", "Maple", "Oak", "Oher conifer", "Other hardwood", "Pine", "Spruce", "Tamarack". There are also variables that store information about the projection. These variables are called:“projection” (NAD83/Great Lakes St. Lawrence Albers), “Spatial_Reference” (ESPG:3175), “Projection_Name” (Albers Equal Area)
Other Name:
STEPPS-fractional-composition_NEUS_2.5_percentile
Description:
netCDF files with dimensions x (meters), y (meters) and time (from 8000 YBP to 250 YBP, in 100 year intervals). The variables that store the 2.5th percentile of the proportion of the posterior estimates of relative abundance are: "Ash","Beech", "Birch", "Chestnut", "Hemlock", "Hickory", "Maple", "Oak", "Oher conifer", "Other hardwood", "Pine", "Spruce", "Tamarack". There are also variables that store information about the projection. These variables are called:“projection” (NAD83/Great Lakes St. Lawrence Albers), “Spatial_Reference” (ESPG:3175), “Projection_Name” (Albers Equal Area)
Other Name:
STEPPS-fractional-composition_NEUS_5_percentile
Description:
netCDF files with dimensions x (meters), y (meters) and time (from 8000 YBP to 250 YBP, in 100 year intervals). The variables that store the 5th percentile of the proportion of the posterior estimates of relative abundance are: "Ash","Beech", "Birch", "Chestnut", "Hemlock", "Hickory", "Maple", "Oak", "Oher conifer", "Other hardwood", "Pine", "Spruce", "Tamarack". There are also variables that store information about the projection. These variables are called:“projection” (NAD83/Great Lakes St. Lawrence Albers), “Spatial_Reference” (ESPG:3175), “Projection_Name” (Albers Equal Area)
Other Name:
STEPPS-fractional-composition_NEUS_10_percentile
Description:
netCDF files with dimensions x (meters), y (meters) and time (from 8000 YBP to 250 YBP, in 100 year intervals). The variables that store the 10th percentile of the proportion of the posterior estimates of relative abundance are: "Ash","Beech", "Birch", "Chestnut", "Hemlock", "Hickory", "Maple", "Oak", "Oher conifer", "Other hardwood", "Pine", "Spruce", "Tamarack". There are also variables that store information about the projection. These variables are called:“projection” (NAD83/Great Lakes St. Lawrence Albers), “Spatial_Reference” (ESPG:3175), “Projection_Name” (Albers Equal Area)
Other Name:
STEPPS-fractional-composition_NEUS_16.6_percentile
Description:
netCDF files with dimensions x (meters), y (meters) and time (from 8000 YBP to 250 YBP, in 100 year intervals). The variables that store the 16.6th percentile of the proportion of the posterior estimates of relative abundance are: "Ash","Beech", "Birch", "Chestnut", "Hemlock", "Hickory", "Maple", "Oak", "Oher conifer", "Other hardwood", "Pine", "Spruce", "Tamarack". There are also variables that store information about the projection. These variables are called:“projection” (NAD83/Great Lakes St. Lawrence Albers), “Spatial_Reference” (ESPG:3175), “Projection_Name” (Albers Equal Area)
Other Name:
STEPPS-fractional-composition_NEUS_50_percentile
Description:
netCDF files with dimensions x (meters), y (meters) and time (from 8000 YBP to 250 YBP, in 100 year intervals). The variables that store the 50th percentile of the proportion of the posterior estimates of relative abundance are: "Ash","Beech", "Birch", "Chestnut", "Hemlock", "Hickory", "Maple", "Oak", "Oher conifer", "Other hardwood", "Pine", "Spruce", "Tamarack". There are also variables that store information about the projection. These variables are called:“projection” (NAD83/Great Lakes St. Lawrence Albers), “Spatial_Reference” (ESPG:3175), “Projection_Name” (Albers Equal Area)
Other Name:
STEPPS-fractional-composition_NEUS_83.30_percentile
Description:
netCDF files with dimensions x (meters), y (meters) and time (from 8000 YBP to 250 YBP, in 100 year intervals). The variables that store the 83.3rd percentile of the proportion of the posterior estimates of relative abundance are: "Ash","Beech", "Birch", "Chestnut", "Hemlock", "Hickory", "Maple", "Oak", "Oher conifer", "Other hardwood", "Pine", "Spruce", "Tamarack". There are also variables that store information about the projection. These variables are called:“projection” (NAD83/Great Lakes St. Lawrence Albers), “Spatial_Reference” (ESPG:3175), “Projection_Name” (Albers Equal Area)
Other Name:
STEPPS-fractional-composition_NEUS_90_percentile
Description:
netCDF files with dimensions x (meters), y (meters) and time (from 8000 YBP to 250 YBP, in 100 year intervals). The variables that store the 90th percentile of the proportion of the posterior estimates of relative abundance are: "Ash","Beech", "Birch", "Chestnut", "Hemlock", "Hickory", "Maple", "Oak", "Oher conifer", "Other hardwood", "Pine", "Spruce", "Tamarack". There are also variables that store information about the projection. These variables are called:“projection” (NAD83/Great Lakes St. Lawrence Albers), “Spatial_Reference” (ESPG:3175), “Projection_Name” (Albers Equal Area)
Other Name:
STEPPS-fractional-composition_NEUS_95_percentile
Description:
netCDF files with dimensions x (meters), y (meters) and time (from 8000 YBP to 250 YBP, in 100 year intervals). The variables that store the 95th percentile of the proportion of the posterior estimates of relative abundance are: "Ash","Beech", "Birch", "Chestnut", "Hemlock", "Hickory", "Maple", "Oak", "Oher conifer", "Other hardwood", "Pine", "Spruce", "Tamarack". There are also variables that store information about the projection. These variables are called:“projection” (NAD83/Great Lakes St. Lawrence Albers), “Spatial_Reference” (ESPG:3175), “Projection_Name” (Albers Equal Area)
Other Name:
STEPPS-fractional-composition_NEUS_97.5_percentile
Description:
netCDF files with dimensions x (meters), y (meters) and time (from 8000 YBP to 250 YBP, in 100 year intervals). The variables that store the 97.5th percentile of the proportion of the posterior estimates of relative abundance are: "Ash","Beech", "Birch", "Chestnut", "Hemlock", "Hickory", "Maple", "Oak", "Oher conifer", "Other hardwood", "Pine", "Spruce", "Tamarack". There are also variables that store information about the projection. These variables are called:“projection” (NAD83/Great Lakes St. Lawrence Albers), “Spatial_Reference” (ESPG:3175), “Projection_Name” (Albers Equal Area)
Detailed Metadata

Data Entities

Non-Categorized Data Resource

Name:STEPPS-fractional-composition_NEUS-mean
Entity Type:netCDF
Description:netCDF files with dimensions x (meters), y (meters) and time (from 8000 YBP to 250 YBP, in 100 year intervals). The variables that store the mean proportion of the posterior estimates of relative abundance are: "Ash","Beech", "Birch", "Chestnut", "Hemlock", "Hickory", "Maple", "Oak", "Oher conifer", "Other hardwood", "Pine", "Spruce", "Tamarack". There are also variables that store information about the projection. These variables are called:“projection” (NAD83/Great Lakes St. Lawrence Albers), “Spatial_Reference” (ESPG:3175), “Projection_Name” (Albers Equal Area)
Physical Structure Description:
Object Name:STEPPS-fractional-composition_NEUS-mean.nc
Externally Defined Format:
Format Name:netCDF
Data:https://pasta-s.lternet.edu/package/data/eml/msb-paleon/44/1/9f38e7b6b54ea9bc676f07cfc2e9f28d

Non-Categorized Data Resource

Name:STEPPS-fractional-composition_NEUS-sd
Entity Type:netCDF
Description:netCDF files with dimensions x (meters), y (meters) and time (from 8000 YBP to 250 YBP, in 100 year intervals). The variables that store the standard deviation of the proportion of the posterior estimates of relative abundance are: "Ash","Beech", "Birch", "Chestnut", "Hemlock", "Hickory", "Maple", "Oak", "Oher conifer", "Other hardwood", "Pine", "Spruce", "Tamarack". There are also variables that store information about the projection. These variables are called:“projection” (NAD83/Great Lakes St. Lawrence Albers), “Spatial_Reference” (ESPG:3175), “Projection_Name” (Albers Equal Area)
Physical Structure Description:
Object Name:STEPPS-fractional-composition_NEUS-sd.nc
Externally Defined Format:
Format Name:netCDF
Data:https://pasta-s.lternet.edu/package/data/eml/msb-paleon/44/1/9738c8b9c9b834ccb77c0650614cbe2e

Non-Categorized Data Resource

Name:STEPPS-fractional-composition_NEUS_2.5_percentile
Entity Type:netCDF
Description:netCDF files with dimensions x (meters), y (meters) and time (from 8000 YBP to 250 YBP, in 100 year intervals). The variables that store the 2.5th percentile of the proportion of the posterior estimates of relative abundance are: "Ash","Beech", "Birch", "Chestnut", "Hemlock", "Hickory", "Maple", "Oak", "Oher conifer", "Other hardwood", "Pine", "Spruce", "Tamarack". There are also variables that store information about the projection. These variables are called:“projection” (NAD83/Great Lakes St. Lawrence Albers), “Spatial_Reference” (ESPG:3175), “Projection_Name” (Albers Equal Area)
Physical Structure Description:
Object Name:STEPPS-fractional-composition_NEUS_2.5_percentile.nc
Externally Defined Format:
Format Name:netCDF
Data:https://pasta-s.lternet.edu/package/data/eml/msb-paleon/44/1/dafdccaf2978398c68747c156f1a76d9

Non-Categorized Data Resource

Name:STEPPS-fractional-composition_NEUS_5_percentile
Entity Type:netCDF
Description:netCDF files with dimensions x (meters), y (meters) and time (from 8000 YBP to 250 YBP, in 100 year intervals). The variables that store the 5th percentile of the proportion of the posterior estimates of relative abundance are: "Ash","Beech", "Birch", "Chestnut", "Hemlock", "Hickory", "Maple", "Oak", "Oher conifer", "Other hardwood", "Pine", "Spruce", "Tamarack". There are also variables that store information about the projection. These variables are called:“projection” (NAD83/Great Lakes St. Lawrence Albers), “Spatial_Reference” (ESPG:3175), “Projection_Name” (Albers Equal Area)
Physical Structure Description:
Object Name:STEPPS-fractional-composition_NEUS_5_percentile.nc
Externally Defined Format:
Format Name:netCDF
Data:https://pasta-s.lternet.edu/package/data/eml/msb-paleon/44/1/e3e3a0e96a2ab693d6b496191086cc28

Non-Categorized Data Resource

Name:STEPPS-fractional-composition_NEUS_10_percentile
Entity Type:netCDF
Description:netCDF files with dimensions x (meters), y (meters) and time (from 8000 YBP to 250 YBP, in 100 year intervals). The variables that store the 10th percentile of the proportion of the posterior estimates of relative abundance are: "Ash","Beech", "Birch", "Chestnut", "Hemlock", "Hickory", "Maple", "Oak", "Oher conifer", "Other hardwood", "Pine", "Spruce", "Tamarack". There are also variables that store information about the projection. These variables are called:“projection” (NAD83/Great Lakes St. Lawrence Albers), “Spatial_Reference” (ESPG:3175), “Projection_Name” (Albers Equal Area)
Physical Structure Description:
Object Name:STEPPS-fractional-composition_NEUS_10_percentile.nc
Externally Defined Format:
Format Name:netCDF
Data:https://pasta-s.lternet.edu/package/data/eml/msb-paleon/44/1/02389da4a82a109a50267cdf45f47000

Non-Categorized Data Resource

Name:STEPPS-fractional-composition_NEUS_16.6_percentile
Entity Type:netCDF
Description:netCDF files with dimensions x (meters), y (meters) and time (from 8000 YBP to 250 YBP, in 100 year intervals). The variables that store the 16.6th percentile of the proportion of the posterior estimates of relative abundance are: "Ash","Beech", "Birch", "Chestnut", "Hemlock", "Hickory", "Maple", "Oak", "Oher conifer", "Other hardwood", "Pine", "Spruce", "Tamarack". There are also variables that store information about the projection. These variables are called:“projection” (NAD83/Great Lakes St. Lawrence Albers), “Spatial_Reference” (ESPG:3175), “Projection_Name” (Albers Equal Area)
Physical Structure Description:
Object Name:STEPPS-fractional-composition_NEUS_16.6_percentile.nc
Externally Defined Format:
Format Name:netCDF
Data:https://pasta-s.lternet.edu/package/data/eml/msb-paleon/44/1/2d050e326aab7e13b49f4e32794cb216

Non-Categorized Data Resource

Name:STEPPS-fractional-composition_NEUS_50_percentile
Entity Type:netCDF
Description:netCDF files with dimensions x (meters), y (meters) and time (from 8000 YBP to 250 YBP, in 100 year intervals). The variables that store the 50th percentile of the proportion of the posterior estimates of relative abundance are: "Ash","Beech", "Birch", "Chestnut", "Hemlock", "Hickory", "Maple", "Oak", "Oher conifer", "Other hardwood", "Pine", "Spruce", "Tamarack". There are also variables that store information about the projection. These variables are called:“projection” (NAD83/Great Lakes St. Lawrence Albers), “Spatial_Reference” (ESPG:3175), “Projection_Name” (Albers Equal Area)
Physical Structure Description:
Object Name:STEPPS-fractional-composition_NEUS_50_percentile.nc
Externally Defined Format:
Format Name:netCDF
Data:https://pasta-s.lternet.edu/package/data/eml/msb-paleon/44/1/3f8dd83dadfb7c3462aec09ef05f3884

Non-Categorized Data Resource

Name:STEPPS-fractional-composition_NEUS_83.30_percentile
Entity Type:netCDF
Description:netCDF files with dimensions x (meters), y (meters) and time (from 8000 YBP to 250 YBP, in 100 year intervals). The variables that store the 83.3rd percentile of the proportion of the posterior estimates of relative abundance are: "Ash","Beech", "Birch", "Chestnut", "Hemlock", "Hickory", "Maple", "Oak", "Oher conifer", "Other hardwood", "Pine", "Spruce", "Tamarack". There are also variables that store information about the projection. These variables are called:“projection” (NAD83/Great Lakes St. Lawrence Albers), “Spatial_Reference” (ESPG:3175), “Projection_Name” (Albers Equal Area)
Physical Structure Description:
Object Name:STEPPS-fractional-composition_NEUS_83.3_percentile.nc
Externally Defined Format:
Format Name:netCDF
Data:https://pasta-s.lternet.edu/package/data/eml/msb-paleon/44/1/19fe30ff72f2571c5335e1b214f0ab19

Non-Categorized Data Resource

Name:STEPPS-fractional-composition_NEUS_90_percentile
Entity Type:netCDF
Description:netCDF files with dimensions x (meters), y (meters) and time (from 8000 YBP to 250 YBP, in 100 year intervals). The variables that store the 90th percentile of the proportion of the posterior estimates of relative abundance are: "Ash","Beech", "Birch", "Chestnut", "Hemlock", "Hickory", "Maple", "Oak", "Oher conifer", "Other hardwood", "Pine", "Spruce", "Tamarack". There are also variables that store information about the projection. These variables are called:“projection” (NAD83/Great Lakes St. Lawrence Albers), “Spatial_Reference” (ESPG:3175), “Projection_Name” (Albers Equal Area)
Physical Structure Description:
Object Name:STEPPS-fractional-composition_NEUS_90_percentile.nc
Externally Defined Format:
Format Name:netCDF
Data:https://pasta-s.lternet.edu/package/data/eml/msb-paleon/44/1/3b1e0bcaab880fda66cad5396c74a404

Non-Categorized Data Resource

Name:STEPPS-fractional-composition_NEUS_95_percentile
Entity Type:netCDF
Description:netCDF files with dimensions x (meters), y (meters) and time (from 8000 YBP to 250 YBP, in 100 year intervals). The variables that store the 95th percentile of the proportion of the posterior estimates of relative abundance are: "Ash","Beech", "Birch", "Chestnut", "Hemlock", "Hickory", "Maple", "Oak", "Oher conifer", "Other hardwood", "Pine", "Spruce", "Tamarack". There are also variables that store information about the projection. These variables are called:“projection” (NAD83/Great Lakes St. Lawrence Albers), “Spatial_Reference” (ESPG:3175), “Projection_Name” (Albers Equal Area)
Physical Structure Description:
Object Name:STEPPS-fractional-composition_NEUS_95_percentile.nc
Externally Defined Format:
Format Name:netCDF
Data:https://pasta-s.lternet.edu/package/data/eml/msb-paleon/44/1/67f687d86888ae3f81bba2a4180186ca

Non-Categorized Data Resource

Name:STEPPS-fractional-composition_NEUS_97.5_percentile
Entity Type:netCDF
Description:netCDF files with dimensions x (meters), y (meters) and time (from 8000 YBP to 250 YBP, in 100 year intervals). The variables that store the 97.5th percentile of the proportion of the posterior estimates of relative abundance are: "Ash","Beech", "Birch", "Chestnut", "Hemlock", "Hickory", "Maple", "Oak", "Oher conifer", "Other hardwood", "Pine", "Spruce", "Tamarack". There are also variables that store information about the projection. These variables are called:“projection” (NAD83/Great Lakes St. Lawrence Albers), “Spatial_Reference” (ESPG:3175), “Projection_Name” (Albers Equal Area)
Physical Structure Description:
Object Name:STEPPS-fractional-composition_NEUS_97.5_percentile.nc
Externally Defined Format:
Format Name:netCDF
Data:https://pasta-s.lternet.edu/package/data/eml/msb-paleon/44/1/018f7fdc2c9a4440928e838085bd493b

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 methods section of 1) Trachsel, M., Dawson, A., Paciorek, C.J., Williams, J.W., McLachlan, J.S., Cogbill, C.V., Foster, D.R., Goring, S.J., Jackson, S.T., Oswald,W.W., Shuman, B.N. (2020). Comparison of settlement-era vegetation reconstructions for STEPPS and REVEALS pollen–vegetation models in the northeastern United States. Quaternary Research, 95, 23-42. doi:10.1017/qua.2019.81 2) Trachsel et al in prep, Mid to late Holocene quantitative and spatially explicit reconstructions of forest composition in the northeastern United States, Journal of Biogeography

People and Organizations

Publishers:
Organization:Environmental Data Initiative
Email Address:
info@environmentaldatainitiative.org
Web Address:
https://environmentaldatainitiative.org
Creators:
Individual:Dr. Mathias Trachsel
Organization:University of Wisconsin, Madison
Individual:Dr. Andria Dawson
Organization:Mount Royal University
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
Individual:Dr. Charles Cogbill
Organization:Harvard Forest
Individual:Dr. David Foster
Organization:Harvard Forest and Harvard University
Individual:Dr. Bryan Shuman
Organization:University of Wyoming
Individual:Dr. W. Wyatt Oswald
Organization:Harvard Forest and Emerson College
Contacts:
Individual:Dr. Andria Dawson
Position:Lead PI
Organization:Mount Royal University
Phone:
4034407085 (voice)
Email Address:
adawson@mtroyal.ca
Individual:Dr. Mathias Trachsel
Position:Lead PI
Organization:University of Wisconsin, Madison
Email Address:
mtrachs@gmail.com
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:

Time Period
Begin:
Timescale:Absolute
Time estimate:8000 BP
Time explanation:Radiocarbon methods paper here, text citation
End:
Timescale:Absolute
Time estimate:50 BP
Time explanation:Radiocarbon methods paper here, text citation
Geographic Region:
Description: Northeastern United States, including Maine, New Hampshire, Vermont, Massachusetts, Rhode Island, Connecticut, parts of New York, Pennsylvania, and New Jersey.
Bounding Coordinates:
Northern:  48Southern:  39.5
Western:  -79.5Eastern:  -66
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: Chestnut
Classification:
Common Name: Castanea spp.
Classification:
Common Name: Hemlock
Classification:
Common Name: Tsuga canadensis
Classification:
Common Name: Hickory
Classification:
Common Name: Carya spp.
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.

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        |     |     |___text '\n                Publications: 1) Trachsel, M., Dawson, A., Paciorek, C.J., Williams, J.W., McLachlan, J.S., Cogbill, C.V., Foster, D.R., Goring, S.J., Jackson, S.T., Oswald,W.W., Shuman, B.N. (2020). Comparison of settlement-era vegetation reconstructions for STEPPS and REVEALS pollen–vegetation models in the northeastern United States. Quaternary Research, 95, 23-42. doi:10.1017/qua.2019.81\n\t\t\t\t2) Trachsel et al in prep, Mid to late Holocene quantitative and spatially explicit reconstructions of forest composition in the northeastern United States, Journal of Biogeography\n            '
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