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Cited by 332Ecology and Vegetation Dynamics StudiesForest ecology and managementForest Management and Policy

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Four Centuries of Change in Northeastern United States Forests

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Thompson, Jonathan R., Carpenter, Dunbar N., Cogbill, Charles V., Foster, David R.·2013·PLoS ONE
DOI 10.1371/journal.pone.0072540PMC PMC3762820
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Abstract

The northeastern United States is a predominately-forested region that, like most of the eastern U.S., has undergone a 400-year history of intense logging, land clearance for agriculture, and natural reforestation. This setting affords the opportunity to address a major ecological question: How similar are today's forests to those existing prior to European colonization? Working throughout a nine-state region spanning Maine to Pennsylvania, we assembled a comprehensive database of archival land-survey records describing the forests at the time of European colonization. We compared these records to modern forest inventory data and described: (1) the magnitude and attributes of forest compositional change, (2) the geography of change, and (3) the relationships between change and environmental factors and historical land use. We found that with few exceptions, notably the American chestnut, the same taxa that made up the pre-colonial forest still comprise the forest today, despite ample opportunities for species invasion and loss. Nonetheless, there have been dramatic shifts in the relative abundance of forest taxa. The magnitude of change is spatially clustered at local scales (<125 km) but exhibits little evidence of regional-scale gradients. Compositional change is most strongly associated with the historical extent of agricultural clearing. Throughout the region, there has been a broad ecological shift away from late successional taxa, such as beech and hemlock, in favor of early- and mid-successional taxa, such as red maple and poplar. Additionally, the modern forest composition is more homogeneous and less coupled to local climatic controls.

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Crossref · 10.1371/journal.pone.0072540

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Figures

Figure 1 The nine-state study region in the northeastern United States. Colors correspond to U.S. Forest Service designated ecoregions. The inner polygons correspond to the 1280 colonial town where pre-colonial forest data were collected. Of these, 701 contained an adequate sample of witness trees and modern forest data to permit comparative analyses. Town with insufficient data are grayed-out in the map. Inset: The location of the study area within the conterminous United States.
Figure 1 The nine-state study region in the northeastern United States. Colors correspond to U.S. Forest Service designated ecoregions. The inner polygons correspond to the 1280 colonial town where pre-colonial forest data were collected. Of these, 701 contained an adequate sample of witness trees and modern forest data to permit comparative analyses. Town with insufficient data are grayed-out in the map. Inset: The location of the study area within the conterminous United States.CC0 · PubMed Central
Figure 2 An illustrative example of one bootstrap sample of FIA plots or witness trees used to estimate the minimum sampling intensity necessary to capture the forest compositional diversity of a town. Each dot represents the Sørensen similarity between a bootstrap sample of FIA plots or bins of witness trees, and the town's composition with all plots included, for n in one through the total number of plots/bins in the town. The curve is a Michaelis-Menten function fit to the similarity values. Smax is the curve's asymptote and Dmin is the plot or tree density at 0.9Smax. Dmin was averaged over 100 sets of bootstrap samples from each of the most plot-dense towns in an ecoregion to determine the ecoregion's minimum sampling density.
Figure 2 An illustrative example of one bootstrap sample of FIA plots or witness trees used to estimate the minimum sampling intensity necessary to capture the forest compositional diversity of a town. Each dot represents the Sørensen similarity between a bootstrap sample of FIA plots or bins of witness trees, and the town's composition with all plots included, for n in one through the total number of plots/bins in the town. The curve is a Michaelis-Menten function fit to the similarity values. Smax is the curve's asymptote and Dmin is the plot or tree density at 0.9Smax. Dmin was averaged over 100 sets of bootstrap samples from each of the most plot-dense towns in an ecoregion to determine the ecoregion's minimum sampling density.CC0 · PubMed Central
Figure 3 Relative composition of pre-colonial era Witness Trees and modern inventory trees in 701 colonial townships in the northeastern USA.
Figure 3 Relative composition of pre-colonial era Witness Trees and modern inventory trees in 701 colonial townships in the northeastern USA.CC0 · PubMed Central
Figure 4 Town-scale relative abundance of forest taxa within 701 colonial townships. Pre-colonial (left); Modern taxa (center); change in abundance between the eras (right), A. Beech; B. Oak; C. Maple; D. Hemlock. Other taxa can be found in online supplementary materials.
Figure 4 Town-scale relative abundance of forest taxa within 701 colonial townships. Pre-colonial (left); Modern taxa (center); change in abundance between the eras (right), A. Beech; B. Oak; C. Maple; D. Hemlock. Other taxa can be found in online supplementary materials.CC0 · PubMed Central
Figure 5 Town level compositional change (Sørensen's distance) between the pre-colonial and the modern forest taxa. Higher values indicate greater compositional change over time. Inset: Spatial autocorrelation in compositional change (Sørensen's distance) over time as shown in a Moran's I spatial correlogram with 20 km distance classes. Solid points indicate that spatial autocorrelation in that distance class is significantly different than zero (P<0.01).
Figure 5 Town level compositional change (Sørensen's distance) between the pre-colonial and the modern forest taxa. Higher values indicate greater compositional change over time. Inset: Spatial autocorrelation in compositional change (Sørensen's distance) over time as shown in a Moran's I spatial correlogram with 20 km distance classes. Solid points indicate that spatial autocorrelation in that distance class is significantly different than zero (P<0.01).CC0 · PubMed Central
Figure 6 Non-metric multidimensional scaling ordination of pre-colonial and modern forest composition. (A) Points represent each town in each time period. Taxa names are position at the centroid of their distributions within the ordination. (b) Environmental parameters (Table 3) were overlaid onto the NMDS ordination diagram as fitted vectors. R-Square describe the correlation between ordination axes and environmental vectors only vectors with significant Pearson correlation (P<0.05.) were plotted.
Figure 6 Non-metric multidimensional scaling ordination of pre-colonial and modern forest composition. (A) Points represent each town in each time period. Taxa names are position at the centroid of their distributions within the ordination. (b) Environmental parameters (Table 3) were overlaid onto the NMDS ordination diagram as fitted vectors. R-Square describe the correlation between ordination axes and environmental vectors only vectors with significant Pearson correlation (P<0.05.) were plotted.CC0 · PubMed Central
Figure 7 Changes in landscape β diversity between the pre-colonial and the modern forest taxa as shown though the distribution of town-to-town compositional dissimilarities (Sørensen's distance). Higher values correspond to higher β diversity. The box represents the inner quartile range of inter-town compositional dissimilarity. The horizontal line indicates the median. The whiskers extend to 1.5 times the inner quartile range.
Figure 7 Changes in landscape β diversity between the pre-colonial and the modern forest taxa as shown though the distribution of town-to-town compositional dissimilarities (Sørensen's distance). Higher values correspond to higher β diversity. The box represents the inner quartile range of inter-town compositional dissimilarity. The horizontal line indicates the median. The whiskers extend to 1.5 times the inner quartile range.CC0 · PubMed Central
Figure 8 Mantel correlogram showing the spatial correlation for both the pre-colonial (squares) and modern (triangles) forest composition. Filled symbols indicate that the correlation is significantly different than zero using a Bonferroni adjusted α of 0.05. Significant positive correlations indicate towns that are separated by the geographic distance indicated on the x-axis are compositionally more similar than would be expected by chance, while significant negative correlations indicate that towns are more dissimilar than would be expected by chance.
Figure 8 Mantel correlogram showing the spatial correlation for both the pre-colonial (squares) and modern (triangles) forest composition. Filled symbols indicate that the correlation is significantly different than zero using a Bonferroni adjusted α of 0.05. Significant positive correlations indicate towns that are separated by the geographic distance indicated on the x-axis are compositionally more similar than would be expected by chance, while significant negative correlations indicate that towns are more dissimilar than would be expected by chance.CC0 · PubMed Central
Figure 9 Conditional inference tree showing a hierarchy of relationships between the potential predictor variables (Table 3) and the degree of compositional change (Sørensen's distance) between the pre-colonial and the modern forest taxa (Figure 4). Partitions in the dendrogram represent the lowest statistically significant P-value that is obtainable across all levels of all predictor variables.
Figure 9 Conditional inference tree showing a hierarchy of relationships between the potential predictor variables (Table 3) and the degree of compositional change (Sørensen's distance) between the pre-colonial and the modern forest taxa (Figure 4). Partitions in the dendrogram represent the lowest statistically significant P-value that is obtainable across all levels of all predictor variables.CC0 · PubMed Central

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Cites

Show all 71 references

Research works printed but not linked: 5

  1. Foster DR, Aber JD (2004) Forest in time: Environmental consequences of 1000 years of change in New England. New Haven: Yale University Press.
  2. Irland LC (1999) The Northeast's changing forests. Cambridge, MA: Harvard University Press.
  3. Foley JA, Ramankutty N, Leff B, Gibbs HK (2007) Global land use changes. In: Kling MD, Parkinson CL, Partington KC, Williams RG, editors. Our changing planet: A view from space. New York: Cambridge University Press. 262–265.
  4. PB Sears, 1925, Th natural vegetation of Ohio. I, A map of the virgin forest, Ohio Journal of Science, 25, 139
  5. Whitney G, DeCant J (2001) Government land office surveys and other early surveys. The Historical Ecology Handbook. Washington, DC: Island Press. 147–172.

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Metadata

Authors
Thompson, J. R., Carpenter, D. N., Cogbill, C. V., & Foster, D. R.
Affiliations
  • Smithsonian Institution (US)
  • University of Wisconsin–Madison (US)
  • Harvard University (US)
Corresponding author
Thompson, Jonathan R.
ORCID
Venue
PLoS ONE
Publisher
Public Library of Science (PLoS)
Published
2013-09-04
Volume
8
Issue
9
Pages
e72540
ISSN
1932-6203 (ISSN-L)
DOI
10.1371/journal.pone.0072540
PMC
PMC3762820
OpenAlex
W2130701908
Cited by
331
References
71
Citations by year
2026: 13 · 2025: 29 · 2024: 24 · 2023: 25 · 2022: 42 · 2021: 29 · 2020: 30 · 2019: 29 · 2018: 21 · 2017: 21 · 2016: 26 · 2015: 25 · 2014: 12 · 2013: 3
FWCI
19.77
Type
journal article
Language
en
Open access
Licence
Locations
  • PLoS ONE (publishedVersion, public-domain)
  • Europe PMC (PubMed Central) (publishedVersion, public-domain)
  • PubMed Central (publishedVersion, public-domain)
  • PubMed (publishedVersion)
  • Digital Access to Scholarship at Harvard (DASH) (Harvard University) (submittedVersion, cc-by)
  • DOAJ (DOAJ: Directory of Open Access Journals) (submittedVersion, cc-by-sa)
  • Smithsonian Digital Repository (Smithsonian Institution) (submittedVersion)
Funders
  • National Science Foundation (0620443)
  • Harvard University
  • U.S. Forest Service
Topics
  • Physical Sciences › Environmental Science › Nature and Landscape Conservation › Ecology and Vegetation Dynamics Studies
  • Life Sciences › Agricultural and Biological Sciences › Forestry › Forest ecology and management
  • Life Sciences › Agricultural and Biological Sciences › Forestry › Forest Management and Policy
Keywords
forest composition change, European colonization, land use history, agricultural clearing, logging, natural reforestation, forest succession, biological invasions, American chestnut, northeastern United States forests, land survey records
MeSH terms
Geography, New England, Trees, Ecosystem

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