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



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.


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.


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.


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.


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.


Land cover change Landscape modeling Deforestation New England Fragmentation Development 



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.


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)


  1. Allen JM, Leininger TJ, Hurd JD, Civco DL, Gelfand AE, Silander JA (2013) Socioeconomics drive woody invasive plant richness in New England, USA through forest fragmentation. Landscape Ecol 28:1671–1686CrossRefGoogle Scholar
  2. Beckage B, Osborne B, Gavin DG, Pucko C, Siccama T, Perkins T (2008) A rapid upward shift of a forest ecotone during 40 years of warming in the Green Mountains of Vermont. Proc Natl Acad Sci 105:4197–4202CrossRefGoogle Scholar
  3. Bliss JC, Kelly EC, Abrams J, Bailey C, Dyer J (2009) Disintegration of the U. S. Industrial Forest Estate: dynamics, trajectories, and questions. Small Scale For 9:53–66CrossRefGoogle Scholar
  4. Bormann FH, Likens GE (1979) Catastrophic disturbance and the steady state in Northern Hardwood Forests: a new look at the role of disturbance in the development of forest ecosystems suggests important implications for land-use policies. Am Sci 67:660–669Google Scholar
  5. Brighton D, Fidel J, Shupe B (2010) Informing land use planning and forestland conservation through subdivision and parcelization trend information. Vermont Natural Resources Council, MontpelierGoogle Scholar
  6. Cadenasso ML, Pickett STA (2001) Effect of edge structure on the flux of species into forest interiors. Conserv Biol 15:91–97CrossRefGoogle Scholar
  7. Dale V, Archer S, Chang M, Ojima D (2005) Ecological impacts and mitigation strategies for rural land management. Ecol Appl 15:1879–1892CrossRefGoogle Scholar
  8. de Paula MD, Costa CPA, Tabarelli M (2011) Carbon storage in a fragmented landscape of atlantic forest: the role played by edge-affected habitats and emergent trees. Trop Conserv Sci 4:349–358CrossRefGoogle Scholar
  9. Dixon RK, Solomon AM, Brown S, Houghton RA, Trexier MC, Wisniewski J (1994) Carbon pools and flux of global forest ecosystems. Science 263:185–190CrossRefGoogle Scholar
  10. Fahrig L, Girard J, Duro D, Pasher J, Smith A, Javorek S, King D, Lindsay KF, Mitchell S, Tischendorf L (2015) Farmlands with smaller crop fields have higher within-field biodiversity. Agric Ecosyst Environ 200:219–234CrossRefGoogle Scholar
  11. Federal Housing Finance Agency (2016) Percent Change in FHFA State-Level House Price Indexes (Seasonally Adjusted, Purchase-Only Index, 2016Q1): Maine, New Hampshire, New York, and Vermont. Federal Housing Finance Agency, Washington, DCGoogle Scholar
  12. Galford GL, Soares-Filho BS, Sonter LJ, Laporte N (2015) Will passive protection save congo forests? PLoS ONE 10:e0128473CrossRefGoogle Scholar
  13. Germain RH, Anderson N, Bevilacqua E (2007) The effects of forestland parcelization and ownership transfers on nonindustrial private forestland forest stocking in New York. J For 105:403–408Google Scholar
  14. Goward SN, Huang C, Zhao F, Schleeweis K, Rishmawi K, Lindsey M, Dungan JL, Michaelis A (2016) NACP NAFD Project: forest disturbance history from landsat, 1986–2010. ORNL DAAC, Oak RidgeGoogle Scholar
  15. Gudex-Cross D, Pontius J, Adams A (2017) Enhanced forest cover mapping using spectral unmixing and object-based classification of multi-temporal Landsat imagery. Remote Sens Environ 196:193–204CrossRefGoogle Scholar
  16. Hansen AJ, Knight RL, Marzluff JM, Powell S, Brown K, Gude PH, Jones K (2005) Effects of exurban development on biodiversity: patterns, mechanisms, and research needs. Ecol Appl 15:1893–1905CrossRefGoogle Scholar
  17. Hansen MC, Potapov PV, Moore R, Hancher M, Turubanova SA, Tyukavina A, Thau D, Stehman S, Goetz SJ, Loveland TR, Kommareddy A, Egorov A, Chini L, Justice CO, Townshend JRG (2013) High-resolution global maps of 21st-century forest cover change. Science 342:850–853CrossRefGoogle Scholar
  18. Homer C, Dewitz J, Yang L, Jin S, Danielson P, Xian G, Coulston J, Herold ND, Wickham JD, Megown K (2015) Completion of the 2011 National Land Cover Database for the Conterminous United States-Representing a decade of land cover change information. Photogramm Eng Remote Sens 81:346–354Google Scholar
  19. Huynh HTL, Pathirana A, Tran T (2016) Facing multiple challenges: the future of flooding in Can Tho city. VNU J Sci Earth Environ Stud 28:Google Scholar
  20. IIED (2007) International Institute for Environment and Development Annual Report 2006/7: A World of Difference. IIED, LondonGoogle Scholar
  21. Isbell F, Tilman D, Polasky S, Loreau M (2015) The biodiversity-dependent ecosystem service debt. Ecol Lett 18:119–134CrossRefGoogle Scholar
  22. Janowiak MK, D’Amato AW, Swanston CW, Iverson L, Dijak WD, Matthews S, Peters MP, Prasad A, Fraser JS, Brandt LA, Butler-Leopold P, Handler SD, Shannon PD, Burbank D, Campbell J, Cogbill C, Duveneck MJ, Emery MR, Fisichelli N, Foster J, Hushaw J, Kenefic L, Mahaffey A, Morelli TL, Reo NJ, Schaberg PG, Simmons KR, Weiskittel A, Wilmot S, Hollinger D, Lane E, Rustad L, Templer PH (2018) New England and northern New York forest ecosystem vulnerability assessment and synthesis: a report from the New England Climate Change Response Framework project. Gen Tech Rep NRS-173 Newtown Sq PA US Dep Agric For Serv North Res Stn 234 P 173:1–234Google Scholar
  23. Kautz M, Anthoni P, Meddens AJH, Pugh TAM, Arneth A (2018) Simulating the recent impacts of multiple biotic disturbances on forest carbon cycling across the United States. Glob Change Biol 24:2079–2092CrossRefGoogle Scholar
  24. Kennedy RE, Yang Z, Cohen WB (2010) Detecting trends in forest disturbance and recovery using yearly Landsat time series: 1. LandTrendr—Temporal segmentation algorithms. Remote Sens Environ 114:2897–2910CrossRefGoogle Scholar
  25. Kennedy CM, Lonsdorf E, Neel MC, Williams NM, Ricketts TH, Winfree R, Bommarco R, Brittain C, Burley AL, Cariveau D, Carvalheiro LG, Chacoff NP, Cunningham SA, Danforth BN, Dudenhöffer J, Elle E, Gaines HR, Garibaldi LA, Gratton C, Holzschuh A, Isaacs R, Javorek SK, Jha S, Klein AM, Krewenka K, Mandelik Y, Mayfield MM, Morandin L, Neame LA, Otieno M, Park M, Potts SG, Rundlöf M, Saez A, Steffan-Dewenter I, Taki H, Viana BF, Westphal C, Greenleaf SS, Kremen C (2013) A global quantitative synthesis of local and landscape effects on wild bee pollinators in agroecosystems. Ecol Lett 16:584–599CrossRefGoogle Scholar
  26. Kolb M, Gerritsen PRW, Garduño G, Lazos Chavero E, Quijas S, Balvanera P, Álvarez N, Solís J, Olmedo Camacho (2018) Land use and cover change modeling as an integration framework: a mixed methods approach for the Southern Coast of Jalisco (Western Mexico). In: Camacho Olmedo MT, Paegelow M, Mas J-F, Escobar F (eds) Geomatic approaches for modeling land change Scenarios. Springer, Cham, pp 241–268CrossRefGoogle Scholar
  27. LANDFIRE (2014) Existing Vegetation Type Layer, LANDFIRE v 2.0.0. Department of the Interior, Geological SurveyGoogle Scholar
  28. Laurance WF, Lovejoy TE, Vasconcelos HL, Bruna EM, Didham RK, Stouffer PC, Cascon C, Bierregaard RO, Laurance SG, Sampaio E (2002) Ecosystem decay of amazonian forest fragments: a 22-year investigation. Conserv Biol 16:605–618CrossRefGoogle Scholar
  29. Lee J, Park B-J, Tsunetsugu Y, Ohira T, Kagawa T, Miyazaki Y (2011) Effect of forest bathing on physiological and psychological responses in young Japanese male subjects. Public Health 125:93–100CrossRefGoogle Scholar
  30. Leigh EG, Wright SJ, Herre EA, Putz FE (1993) The decline of tree diversity on newly isolated tropical islands: a test of a null hypothesis and some implications. Evol Ecol 7:76–102CrossRefGoogle Scholar
  31. LeVert M, Stevens T, Kittredge D (2009) Willingness-to-sell conservation easements: a case study. J For Econ 15:261–275Google Scholar
  32. Liu Y, Feng Y, Zhao Z, Zhang Q, Su S (2016) Socioeconomic drivers of forest loss and fragmentation: a comparison between different land use planning schemes and policy implications. Land Use Policy 54:58–68CrossRefGoogle Scholar
  33. Mas J-F, Pérez-Vega A, Clarke KC (2012) Assessing simulated land use/cover maps using similarity and fragmentation indices. Ecol Complex 11:38–45CrossRefGoogle Scholar
  34. Matlack GR (1993) Microenvironment variation within and among forest edge sites in the eastern United States. Biol Cons 66:185–194CrossRefGoogle Scholar
  35. McGarigal K, Cushman SA, Ene E (2012) FRAGSTATS v4: patial pattern analysis program for categorical and continuous maps. University of Massachusetts, AmherstGoogle Scholar
  36. Miller EK (2011) Steady-State Critical Loads and Exceedance for Terrestrial and Aquatic Ecosystems in the Northeastern United States. NPS/Multi Agency Critical Loads ProjectGoogle Scholar
  37. Mockrin MH, Stewart SI, Radeloff VC, Hammer RG, Johnson KM (2013) Spatial and temporal residential density patterns from 1940 to 2000 in and around the Northern Forest of the Northeastern United States. Popul Environ 34:400–419CrossRefGoogle Scholar
  38. Morse CE, Strong AM, Mendez VE, Lovell ST, Troy AR, Morris WB (2014) Performing a New England landscape: viewing, engaging, and belonging. J Rural Stud 36:226–236CrossRefGoogle Scholar
  39. Murcia C (1995) Edge effects in fragmented forests: implications for conservation. Trends Ecol Evol 10:58–62CrossRefGoogle Scholar
  40. Nadrowski K, Wirth C, Scherer-Lorenzen M (2010) Is forest diversity driving ecosystem function and service? Curr Opin Environ Sustain 2:75–79CrossRefGoogle Scholar
  41. Nevins M (2019) Future forest composition under a changing climate and adaptive forest management in southeastern Vermont, USA. Graduate College Dissertations and Theses. University of VermontGoogle Scholar
  42. Nicholson CC, Koh I, Richardson LL, Beauchemin A, Ricketts TH (2017) Farm and landscape factors interact to affect the supply of pollination services. Agric Ecosyst Environ 250:113–122CrossRefGoogle Scholar
  43. O’Brien EA (2006) A question of value: what do trees and forests mean to people in Vermont? Landsc Res 31:257–275CrossRefGoogle Scholar
  44. Oliveira LJC, Costa MH, Soares-Filho BS, Coe MT (2013) Large-scale expansion of agriculture in Amazonia may be a no-win scenario. Environ Res Lett 8:24021CrossRefGoogle Scholar
  45. Oswald EM, Pontius J, Rayback SA, Schaberg PG, Wilmot SH, Dupigny-Giroux L (2018) The complex relationship between climate and sugar maple health: climate change implications in Vermont for a key northern hardwood species. For Ecol Manag 422:303–312CrossRefGoogle Scholar
  46. Oswalt SN, Smith WB, Miles PD, Pugh SA (2014) Forest Resources of the United States, 2012: A Technical Document Supporting the Forest Service Update of the 2010 RPA Assessment. United States Forest ServiceGoogle Scholar
  47. Pan Y, Chen JM, Birdsey R, McCullough K, He L, Deng F (2012) NACP Forest Age Maps at 1-km Resolution for Canada (2004) and the U.S.A. (2006). Data setGoogle Scholar
  48. Perz SG, Caldas MM, Arima E, Walker RJ (2007) Unofficial road building in the Amazon: socioeconomic and biophysical explanations. Development and Change 38:529–551CrossRefGoogle Scholar
  49. Polyakov M, Zhang D (2008) Property Tax Policy and Land-Use Change. Land Economics 84:396–408CrossRefGoogle Scholar
  50. Pontius J, Duncan J (2018) Linking science and management in a geospatial, multi- criteria decision support tool. New perspectives in forest science. New Perspectives in Forest Science, Multi- Criteria Decision Support Tool. Google Scholar
  51. PRISM Climate Group (2004) PRISM climate dataGoogle Scholar
  52. Riitters K (2002) Classification of Forest Fragmentation in North AmericaGoogle Scholar
  53. Schultz B, Hanson T, Wilmot S, Decker K, Greaves T (2014) Forest Insect and Disease Conditions in Vermont. Vermont Agency of Natural Resources, VermontGoogle Scholar
  54. Schwartz HM (2009) Subprime Nation: american power, global capital, and the housing bubble. Cornell University Press, IthacaGoogle Scholar
  55. Sieving KE, Karr JR (1997) Avian extinction and persistence mechanisms in lowland Panama. Trop For Remn Ecol Manag Conserv Fragm Communities University of Chicago Press, Chicago, pp 156–170Google Scholar
  56. Soares-Filho BS, Coutinho Cerqueira G, Lopes Pennachin C (2002) DINAMICA—a stochastic cellular automata model designed to simulate the landscape dynamics in an Amazonian colonization frontier. Ecol Model 154:217–235CrossRefGoogle Scholar
  57. Soares-Filho B, Alencar A, Nepstad D, Cerqueira G, Vera Diaz M, Rivero S, Solórzano L, Voll E (2004) Simulating the response of land-cover changes to road paving and governance along a major Amazon highway: the Santarém-Cuiabá corridor. Glob Change Biol 10:745–764CrossRefGoogle Scholar
  58. Soares-Filho BS, Rodrigues HO, Costa W (2009) Modeling environmental dynamics with Dinamica EGO. Universidade Federal de Minas Gerais, Belo Horizonte, Minas Gerais, Brazil, Centro de Sensoriamento RemotoGoogle Scholar
  59. Soares-Filho B, Moutinho P, Nepstad D, Anderson A, Rodrigues H, Garcia R, Dietzch L, Merry F, Bowman M, Hissa L, Silvestrini R, Maretti C (2010) Role of Brazilian Amazon protected areas in climate change mitigation. Proc Natl Acad Sci 107:10821–10826CrossRefGoogle Scholar
  60. Soares-Filho B, Rodrigues H, Follador M (2013) A hybrid analytical-heuristic method for calibrating land-use change models. Environ Model Softw 43:80–87CrossRefGoogle Scholar
  61. Thompson JR, Carpenter DN, Cogbill CV, Foster DR (2013) Four Centuries of Change in Northeastern United States Forests. PLoS ONE 8:e72540CrossRefGoogle Scholar
  62. Thompson JR, Plisinski JS, Olofsson P, Holden CE, Duveneck MJ (2017) Forest loss in New England: a projection of recent trends. PLoS ONE 12:e0189636CrossRefGoogle Scholar
  63. Thorn AM, Thompson JR, Plisinski JS (2016) Patterns and predictors of recent forest conversion in New England. Land. Google Scholar
  64. U.S. Census (2010a) TIGER Population DatasetGoogle Scholar
  65. U.S. Census (2010b) Urban areas boundariesGoogle Scholar
  66. U.S. Census (2014) TIGER Roads DatasetGoogle Scholar
  67. USGS (2015) eMODIS Phenology Metric dataGoogle Scholar
  68. USGS (2016) Protected Areas Database of the United States (PAD-US), version 1.4 Combined Feature ClassGoogle Scholar
  69. USGS (2017) The National MapGoogle Scholar
  70. Ward J, Worthley T, Smallidge P, Bennett K (2013) Northeastern forest regeneration handbook: a guide for forest owners, harvesting practitioners, and public officials. USDA Forest Service, Newtown SquareGoogle Scholar
  71. Watson K (2018) Conservation of Ecosystem Services and Biodiversity in Vermont, USA. Graduate College Dissertations and Theses. University of VermontGoogle Scholar
  72. Wickham J, Stehman SV, Homer CG (2018) Spatial patterns of the United States National Land Cover Dataset (NLCD) land-cover change thematic accuracy (2001–2011). Int J Remote Sens 39:1729–1743CrossRefGoogle Scholar
  73. Wright JP, Jones CG, Flecker AS (2002) An ecosystem engineer, the beaver, increases species richness at the landscape scale. Oecologia 132:96–101CrossRefGoogle Scholar
  74. NRCS (n.d.) Web Soil Survey. Natural Resources Conservation Service, United States Department of AgricultureGoogle Scholar

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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