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Ecosystems

, Volume 19, Issue 8, pp 1401–1417 | Cite as

A Tale of Two Forest Carbon Assessments in the Eastern United States: Forest Use Versus Cover as a Metric of Change

  • C. W. Woodall
  • B. F. Walters
  • M. B. Russell
  • J. W. Coulston
  • G. M. Domke
  • A. W. D’Amato
  • P. A. Sowers
Article

Abstract

The dynamics of land-use practices (for example, forest versus settlements) is often a major driver of changes in terrestrial carbon (C). As the management and conservation of forest land uses are considered a means of reducing future atmospheric CO2 concentrations, the monitoring of forest C stocks and stock change by categories of land-use change (for example, croplands converted to forest) is often a requirement of C monitoring protocols such as those espoused by the Intergovernmental Panel on Climate Change (that is, Good Practice Guidance and Guidelines). The identification of land use is often along a spectrum ranging from direct observation (for example, interpretation of owner intent via field visits) to interpretation of remotely sensed imagery (for example, land cover mapping) or some combination thereof. Given the potential for substantial differences across this spectrum of monitoring techniques, a region-wide, repeated forest inventory across the eastern U.S. was used to evaluate relationships between forest land-use change (derived from a forest inventory) and forest cover change (derived from Landsat modeling) in the context of forest C monitoring strategies. It was found that the correlation between forest land-use change and cover change was minimal (<0.08), with an increase in forest land use but a net decrease in forest cover being the most frequent observation. Cover assessments may be more sensitive to active forest management and/or conversion activities that can lead to confounded conclusions regarding the forest C sink (for example, decreasing forest cover but increasing C stocks in industrial timberlands). In contrast, the categorical nature of direct land-use field observations reduces their sensitivity to forest management activities (for example, clearcutting versus thinning) and recent disturbance events (for example, floods or wildfire) that may obscure interpretation of C dynamics over short time steps. While using direct land-use observations or cover mapping in forest C assessments, they should not be considered interchangeable as both approaches possess idiosyncratic qualities that should be considered when developing conclusions regarding forest C attributes and dynamics across large scales.

Keywords

forest inventory climate change carbon land use land-use change stock change forest cover 

Notes

Acknowledgments

We extend gratitude to participants in initial brainstorming sessions that helped guide formulation of preliminary study objectives: Charlie Paulson, Tony Olsen, Richard Widmann, Randall Morin, Cassie Kurz, Patrick Miles, Dan Kaisershot, and Rachel Riemann. We also wish to thank anonymous reviewers who provided detailed and constructive comments.

References

  1. Amichev BY, Galbraith JM. 2004. A revised methodology for estimation of forest soil carbon from spatial soils and forest inventory data sets. Environ Manag 33(Suppl. 1):S74–86.Google Scholar
  2. Asner GP, Knapp DE, Broadbent EN, Oliveira PJC, Keller M, Silva JN. 2005. Selective logging in the Brazilian Amazon. Science 310:480–2.CrossRefPubMedGoogle Scholar
  3. Bechtold WA, Patterson PL. (Eds.), 2005. The enhanced forest inventory and analysis program—national sampling design and estimation procedures. USDA Forest Service General Technical Report SRS-80. Asheville, NC.Google Scholar
  4. Birdsey R, Pregitzer K, Lucier A. 2006. Forest carbon management in the United States: 1600–2100. J Environ Qual 35:1461–9.CrossRefPubMedGoogle Scholar
  5. Brown DG, Robinson DT, French NHF. 2013. Perspectives on land-change science and carbon management. In: Brown, DG and others, Eds. Chapter 22 in land use and the carbon cycle. Cambridge University Press, Cambridge.Google Scholar
  6. Caspersen JP, Pacala SW, Jenkins JC, Hurtt GC, Moorcroft PR, Birdsey RA. 2000. Contributions of land-use history to carbon accumulation in U.S. forests. Science 290:1148–51.CrossRefPubMedGoogle Scholar
  7. Cochran WG. 1977. Sampling techniques. New York: Wiley.Google Scholar
  8. Coulston JW, Wear DN, Vose JM. 2015. Complex forest dynamics indicate potential for slowing carbon accumulation. Sci Rep 5:8002.CrossRefPubMedPubMedCentralGoogle Scholar
  9. Coulston JW, Reams GA, Wear DN, Brewer CK. 2014. An analysis of forest land use, forest land cover and change at policy-relevant scales. Forestry 87:267–76.Google Scholar
  10. Cressie NA. 1993. Statistics for spatial data, revised edition. Wiley. 928 p.Google Scholar
  11. Domke GM, Woodall CW, Smith JE. 2011. Accounting for density reduction and structural loss in standing dead trees: implications for forest biomass and carbon stock estimates in the United States. Carbon Balance Manag 6:14.CrossRefPubMedPubMedCentralGoogle Scholar
  12. Domke GM, Woodall CW, Walters BF, Smith JE. 2013. From models to measurements: comparing down dead wood carbon stock estimates in the U.S. forest inventory. PLoS ONE 8:e59949.CrossRefPubMedPubMedCentralGoogle Scholar
  13. Domke GM, Walters BF, Perry CH, Woodall CW, Russell MB, Smith JE. In: Review. A framework for estimating litter carbon stocks in forests of the United States. Science of the Total Environment.Google Scholar
  14. Ellis EC, Goldewijk KK, Siebert S, Lightman D, Ramankutty N. 2010. Anthropogenic transformation of the biomes, 1700 to 2000. Glob Ecol Biogeogr 19:589–606.Google Scholar
  15. Environmental Protection Agency (US EPA) 2016. Forest sections of the land use, land-use change, and forestry chapter, and annex. In: US Environmental Protection Agency, Inventory of US Greenhouse Gas Emissions and Sinks: 1990–2014. EPA 430-R-16-002. https://www3.epa.gov/climatechange/ghgemissions/usinventoryreport.html. Accessed 19 April 2016.
  16. EOP. 2013. Executive office of the president: the president’s climate action plan. Climate Action Plan. http://www.whitehouse.gov/sites/default/files/image/president27sclimateactionplan.pdf. Accessed March, 2015.
  17. Foster DR. 1992. Land-use history (1730-1990) and vegetation dynamics in central New England, USA. J Ecol 80:753–71.CrossRefGoogle Scholar
  18. Fox TR, Jokela EJ, Allen HL. 2007. The development of pine plantation silviculture in the southern United States. J Forest 105:337–47.Google Scholar
  19. Friedman JH. 2001. Greedy function approximation: a gradient boosting machine. Ann Stat 29:1189–232.CrossRefGoogle Scholar
  20. Gibbs HK, Brown S, Niles JO, Foley JA. 2007. Monitoring and estimating tropical forest carbon stocks: making REDD a reality. Env Res Lett 2:045023.CrossRefGoogle Scholar
  21. GFW. 2015. Global Forest Watch. http://www.globalforestwatch.org/. Accessed November 23, 2015.
  22. Guo LB, Gifford RM. 2002. Soil carbon stocks and land-use change: a meta-analysis. Glob Change Biol 8:345–60.CrossRefGoogle Scholar
  23. Hansen MC, Potapov PV, Moore P, Hancher SA, Turubanova A, Tyukavina A, Thau D, Stehman SV, Goetz SJ, Loveland A, Kommareddy A, Egorov A, Chini L, Justice CO, Townshend JRG. 2013. High-resolution global maps of 21st—century forest cover change. Science 342:850–3.CrossRefPubMedGoogle Scholar
  24. Holmgren P. 2015. Can we trust country-level data from global forest assessments? For Source 20:8–9.Google Scholar
  25. Houghton RA, Hackler JL, Lawrence KT. 1999. The U.S. carbon budget: contributions from land-use change. Science 5427:574–8.CrossRefGoogle Scholar
  26. Houghton RA. 2003. Revised estimates of the annual net flux of carbon to the atmosphere from changes in land use and management 1850–2000. Tellus 55B:378–90.CrossRefGoogle Scholar
  27. IPCC. 2003. In: Penman J, Gytarsky M, Krug T, Kruger D, Pipatti R, Buendia L, Miwa K, Ngara T, Tanabe K, Wagner F, Eds. Intergovernmental panel on climate change: good practice guidance for land use, land-use change, and forestry. IGES, Japan.Google Scholar
  28. IPCC. 2006. Intergovernmental panel on climate change: guidelines for national greenhouse gas inventories: Volume 4 Agriculture, Forestry and Other Land Use. In: Eggleston HS, Buendia L, Miwa K, Ngara T, Tanabe K, Eds. Prepared by the National Greenhouse Gas Inventories Programme. IGES, Japan.Google Scholar
  29. Jenkins JC, Chojnacky DC, Heath LS, Birdsey RA. 2003. National scale biomass estimators for United States tree species. Forest Science 49:12–35.Google Scholar
  30. Kurz WA, Dymond CC, White TM, Stinson C, Shaw CH, Rampley GJ, Smyth C, Simpson BN, Neilson ET, Trofymow JA, Metsaranta J, Apps MJ. 2009. CBM-CFS3: a model of carbon-dynamics in forestry and land-use change implementing IPCC standards. Ecol Model 220:480–504.CrossRefGoogle Scholar
  31. Kurz WA, Stinson G, Rampley GJ, Dymond CC, Neilson ET. 2008. Risk of natural disturbances makes future contribution of Canada’s forests to the global carbon cycle highly uncertain. PNAS 105:1551–5.CrossRefPubMedPubMedCentralGoogle Scholar
  32. Larson AJ, Stover KC, Keyes CR. 2012. Effects of restoration thinning on spatial heterogeneity in mixed-conifer forest. Can J For Res 42:1505–17.CrossRefGoogle Scholar
  33. MacDicken K, Jonsson Ő, Piňa L, Maulo S, Adikari Y, Garzuglia M, Lindquist E, Reams G, D’Annunzio R. 2015. The global forest resources assessment 2015: how are the world’s forests changing?. Rome: Food and Agriculture Organization of the United Nations.Google Scholar
  34. Makler-Pick V, Gal G, Gorfine M, Hipsey MR, Carmel Y. 2011. Sensitivity analysis for complex ecological models—a new approach. Environ Modell Softw 26:124–34.CrossRefGoogle Scholar
  35. Mascorro VS, Coops NC, Kurz WA, Olguín M. 2015. Choice of satellite imagery and attribution of changes to disturbance type strongly affects forest carbon balance estimates. Carbon Balance Manag 10:30.CrossRefPubMedPubMedCentralGoogle Scholar
  36. Nabuurs G-J, Lindner M, Verkerk PJ, Gunia K, Deda P, Michalak R, Grassi G. 2013. First signs of carbon sink saturation in European forest biomass. Nat Clim Change 3:792–6.CrossRefGoogle Scholar
  37. NAIP. 2015. National Agriculture Imagery Program. U.S. Department of Agriculture, Washington, DC. http://www.fsa.usda.gov/programs-and-services/aerial-photography/imagery-programs/naip-imagery/. Accessed November 23, 2015.
  38. Nave LE, Vance ED, Swanston CW, Curtis PS. 2010. Harvest impacts on soil carbon storage in temperate forests. For Ecol Manag 259:857–66.CrossRefGoogle Scholar
  39. Nowacki GJ, Abrams MD. 2015. Is climate an important driver of post-European vegetation change in the eastern United States? Glob Change Biol 21:314–34.CrossRefGoogle Scholar
  40. Oliver CD, Larson BC. 1996. Forest stand dynamics. New York: McGraw Hill.Google Scholar
  41. Oswalt SN, Smith WB, Miles PD, Pugh SA. 2014. Forest resources of the United States, 2012: a technical document supporting the Forest Service 2015 update of the RPA Assessment. General Technical Report WO-91. Washington, DC: U.S. Department of Agriculture, Forest Service, Washington Office.Google Scholar
  42. Pan Y, Birdsey RA, Fang J, Houghton R, Kauppi PE, Kurz WA et al. 2011. A large and persistent carbon sink in the world’s forests. Science 333:988–93.CrossRefPubMedGoogle Scholar
  43. Radeloff VC et al. 2012. Economic-based projections of future land use in the conterminous United States under alternative policy scenarios. Ecol Appl 22:1036–49.CrossRefPubMedGoogle Scholar
  44. Rhemtulla JM, Mladenoff DJ, Clayton MK. 2009. Historical forest baselines reveal potential for continued carbon sequestration. PNAS 106:6082–7.CrossRefPubMedPubMedCentralGoogle Scholar
  45. Ridgeway G. 2013. GBM: generalized boosted regression models. R package version 2.1. Available from: http://CRAN.R-project.org/package=gbm.
  46. Russell WB, Domke GM, Woodall CW, D’Amato AW. 2015. Comparisons of allometric and climate-derived estimates of tree coarse root carbon in forests of the United States. Carbon Balance Manag 10:20.CrossRefPubMedPubMedCentralGoogle Scholar
  47. Smith JE, Heath LS, Hoover CM. 2013. Carbon factors and models for forest carbon estimates for the 2005–2011 National Greenhouse Gas Inventories of the United States. For Ecol Manag 307:7–19.CrossRefGoogle Scholar
  48. United Nations Framework Convention on Climate Change. 2013. Report on the individual review of the inventory submission of the United States of America submitted in 2012. FCCC/ARR/2012/USA.Google Scholar
  49. USDA 2011. National report on sustainable forests, 2010. Washington, DC: U.S. Department of Agriculture Forest Service, Washington. FS-979.Google Scholar
  50. USDA 2014a. The forest inventory and analysis database: database description and user guide for phase 2 (version 6.0.1). http://www.fia.fs.fed.us/library/database-documentation/current/ver6.0/FIADB%20User%20Guide%20P2_6-0-1_final.pdf (2014).
  51. USDA. 2014b. Forest inventory and analysis national core field guide, volume i: field, data collection procedures for phase 2 plots, version 6.1. Washington, DC: U.S. Department of Agriculture Forest Service, Forest Inventory and Analysis, Washington, D.C.: URL: http://www.fia.fs.fed.us/library/. Accessed February, 2015.
  52. USDA. 2014c. Forest inventory and analysis national program—data and tools—FIA data mart, FIADB Version 5.1. Washington, DC: U.S. Department of Agriculture, Forest Service. http://apps.fs.fed.us/fiadb-downloads/datamart.html. Accessed June 24, 2014.
  53. Westfall JA, Patterson PL, Coulston JW. 2011. Post-stratified estimation: within-strata and total sample size. Can J For Res 41:1130–9.CrossRefGoogle Scholar
  54. White D, Kimerling AJ, Overton WS. 1992. Cartographic and geometric components of a global sampling design for environmental monitoring. Cartogr Geogr Inf Syst 19:5–22.CrossRefGoogle Scholar
  55. Woodall CW, Heath LS, Domke GM, Nichols MC. 2011. Methods and equations for estimating volume, biomass, and carbon for trees in the U.S. forest inventory, 2010. US Forest Service General Technical Report NRS-GTR-88.Google Scholar
  56. Woodall CW. 2012. Where did the U.S. forest biomass/carbon go? J For 110:113–14.Google Scholar
  57. Woodall CW, Domke GM, Riley K, Oswalt CM, Crocker SJ, Yohe GW. 2013. Developing a framework for assessing global change risks to forest carbon stocks. PLoS ONE 8:e73222.CrossRefPubMedPubMedCentralGoogle Scholar
  58. Woodall CW, Coulston JW, Domke GM, Walters BF, Wear DN, Smith JE, Anderson H-E, Clough BJ, Cohen WB, Griffith DM, Hagan SC, Hanou IS, Nichols MC, Perry CH, Russell MB, Westfall JA, Wilson BT. 2015a. The US Forest Carbon Accounting Framework: Stocks and Stock Change, 1990–2016. US Forest Service General Technical Report NRS-GTR-154.Google Scholar
  59. Woodall CW, Walters BF, Coulston JW, D’Amato AW, Domke GM, Russell MB, Sowers PA. 2015b. Monitoring network confirms land use change is a substantial component of the forest carbon sink in the eastern United States. Sci Rep 5:17028.CrossRefPubMedPubMedCentralGoogle Scholar

Copyright information

© Springer Science+Business Media New York (outside USA) 2016

Authors and Affiliations

  • C. W. Woodall
    • 1
  • B. F. Walters
    • 1
  • M. B. Russell
    • 2
  • J. W. Coulston
    • 3
  • G. M. Domke
    • 1
  • A. W. D’Amato
    • 4
  • P. A. Sowers
    • 1
  1. 1.Northern Research Station, Forest Inventory and Analysis ProgramUSDA Forest ServiceSt. PaulUSA
  2. 2.Department of Forest ResourcesUniversity of MinnesotaSt. PaulUSA
  3. 3.Southern Research Station, Forest Inventory and Analysis ProgramUSDA Forest ServiceBlacksburgUSA
  4. 4.Rubenstein School of Environment and Natural ResourcesUniversity of VermontBurlingtonUSA

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