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Simulating forest cover change in the northeastern U.S.: decreasing forest area and increasing fragmentation

  • Alison B. AdamsEmail author
  • Jennifer Pontius
  • Gillian Galford
  • David Gudex-Cross
Research Article

Abstract

Context

Understanding how the Northern Forest landscape has changed and is likely to change, both in terms of forest extent and forest configuration, has important implications for management.

Objectives

We examined historical changes in forest pattern and extent to: (1) characterize recent forest cover change and potential drivers of that change, (2) identify areas vulnerable to future forest loss, (3) assess the impact of such loss on forest fragmentation, and (4) examine correlations between projected forest loss and socioeconomic variables to help inform future planning.

Methods

We developed a cellular automata model to simulate changes in forest land cover in the Northern Forest region from 2015 to 2075. The model was parameterized from observed historical trends (1985 to 2015) and correlating spatial variables using Bayesian Weights of Evidence. Using our model outputs, we identified areas most vulnerable to change, and impacts of these changes on forest fragmentation.

Results

Though we find an overall trend of decreasing forest area across the region, rates of change vary spatially and temporally, with an overall increase in forest cover between 2000 and 2015. Areas most attractive for development (e.g. high population density, low slope and elevation) were most likely to experience deforestation. Forest fragmentation increased during observed and simulated time steps, even during an observed period of net forest regeneration.

Conclusions

Forest loss and fragmentation due to development represent a formidable threat to the Northern Forest. Historical trends indicate that simply increasing forest extent is not sufficient to restore forest connectivity in the region.

Keywords

Land cover change Landscape modeling Deforestation New England Fragmentation Development 

Notes

Acknowledgements

This research was funded by the Northern States Research Cooperative (NSRC) through the U.S. Forest Service Northern Research Station, and the McIntire-Stennis Cooperative Forestry Program through the USDA National Institute of Food and Agriculture. The authors would like to thank Noah Ahles for his assistance in gathering and preparing data, and Jim Duncan for helpful feedback during the preparation of this manuscript.

Funding

This study was funded by the U.S. Department of Agriculture National Institute of Food and Agriculture, McIntire-Stennis project (grant number 1002440) at the University of Vermont, and by the U.S. Forest Service Northern Research Station, Northern States Research Cooperative (no grant number).

Compliance with ethical standards

Conflict of interest

The authors declare that they have no conflict of interest.

Supplementary material

10980_2019_896_MOESM1_ESM.txt (8 kb)
Supplementary material 1 (TXT 7 kb)

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Copyright information

© Springer Nature B.V. 2019

Authors and Affiliations

  1. 1.Rubenstein School of Environment and Natural ResourcesUniversity of VermontBurlingtonUSA
  2. 2.University of Vermont, Gund Institute for EnvironmentBurlingtonUSA
  3. 3.United States Forest ServiceWashington, DCUSA

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