A statistical power analysis of woody carbon flux from forest inventory data
详细信息 查看全文
- 作者：James A. Westfall (1)
Christopher W. Woodall (2)
Mark A. Hatfield (2) - 刊名：Climatic Change
- 出版年：2013
- 出版时间：4 - June 2013
- 年：2013
- 卷：118
- 期：3
- 页码：919-931
- 全文大小：302KB
- 参考文献：1. Bechtold WA, Patterson PL (eds) (2005) The enhanced Forest Inventory and Analysis program—national sampling design and estimation procedures. Gen. Tech. Rep. SRS-80. U.S. Department of Agriculture, Forest Service, Southern Research Station, Asheville, NC, p 85
2. Dale VH, Joyce LA, Mcnulty S, Neilson RP, Ayres MP, Flannigan MD, Hanson PJ, Irland LC, Lugo AE, Peterson CJ, Simberloff D, Swanson FJ, Stocks BJ, Wotton BM (2001) Climate change and forest disturbance. BioSci 51:723-34 CrossRef
3. Fairweather PG (1991) Statistical power and design requirements for environmental monitoring. Aust J Mar and Freshw Res 42:555-67 CrossRef
4. Forest Service (2005) Forest inventory and analysis national core field guide: field data collection procedures for phase 3 plots. Version 3.0. Unpublished information on file at http://socrates.lv-hrc.nevada.edu/fia/dab/databandindex.html
5. Harmon M, Woodall CW, Fasth B, Sexton J (2008) Woody detritus density and density reduction factors for tree species in the United States: a synthesis. Gen. Tech. Rep. NRS-29. U.S. Department of Agriculture, Forest Service, Northern Research Station, Newtown Square, PA, p 84
6. Heath LS, Smith JE, Skog KE, Nowak DJ, Woodall CW (2011) Managed forest carbon estimates for the US Greenhouse Gas Inventory, 1990-2008. J Forestry 109:167-73
7. Iverson LR, Matthews SN, Prasad AM, Peters MP, Yohe G (2012) Development of risk matrices for evaluating climatic change responses of forested habitats. Clim Change. doi:10.1007/s10584-012-0412-x
8. Kleinbaum D, Kupper L, Nizam A, Muller K (2008) Applied regression analysis and other multivariable methods, 4th edn. Duxbury, Belmont, CA
9. 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. Proc Natl Acad Sci 105:1551-555 CrossRef
10. Malhi Y, Baldocchi DD, Jarvis PG (1999) The carbon balance of tropical, temperate, and boreal forests. Plant Cell Environ 22:715-40 CrossRef
11. Mapstone BD (1995) Scalable decision rules for environmental impact studies: effect size, Type I, and Type II errors. Ecol Appl 5:401-10 CrossRef
12. Pan Y, Birdsey RA, Fang J, Houghton R, Kauppi PE, Kurz WA, Phillips OL, Shvidenko A, Lewis SL, Canadell JG, Ciais P, Jackson RB, Pacala SW, McGuire AD, Piao S, Rautiainen A, Sitch S, Hayes D (2011) A large and persistent carbon sink in the world’s forests. Sci 333:988-93 CrossRef
13. Reich PB (2011) Taking stock of forest carbon. Nat Clim Change 1:346-47 CrossRef
14. Ryan MG, Harmon ME, Birdsey RA, Giardina CP, Heath LS, Houghton RA, Jackson RB, McKinley DC, Morrison JF, Murray BC, Pataki DE, Skog KE (2010) A synthesis of the science on forests and carbon for U.S. forests. Ecol Soc Am: Issues in Ecol 13:1-6
15. SAS Institute Inc (2008) SAS/STAT? 9.2 User’s Guide. SAS Institute Inc, Cary
16. Schreuder HT, Ernst R, Ramirez-Maldonado H (2004) Statistical techniques for sampling and monitoring natural resources. Gen. Tech. Rep. RMRS-126. U.S. Department of Agriculture, Forest Service, Rocky Mountain Research Station, Fort Collins, CO, p 111
17. US EPA (2011) Inventory of U.S. greenhouse gas emissions and sinks: 1990-2009. Chapter 7. Land use, land-use change, and forestry. Annex 3.12. Methodology for estimating net carbon stock changes in forest land remaining forest lands. #430-R-11-005. U.S. EPA, Washington, DC
18. Van Deusen PC (2004) Forest inventory estimation with mapped plots. Can J For Res 34:493-97 CrossRef
19. Woodall CW, Monleon VJ (2008) Sampling protocol, estimation, and analysis procedures for the Down Woody Materials indicator of the FIA program. USDA Forest Service, Gen. Tech. Rep. NRS-22. U.S. Department of Agriculture, Forest Service, Northern Research Station, Newtown Square, PA, p 68
20. Woodall CW (2012) Where did the U.S. forest biomass/carbon go? J For 110:113-14
21. Woodall CW, Nagel LM (2007) Down woody fuel loadings dynamics of a large-scale blowdown in northern Minnesota. For Ecol Manage 247:194-99 CrossRef
22. Woodall CW, Heath LS, Domke GM, Nichols MC (2011) Methods and equations for estimating aboveground volume, biomass, and carbon for trees in the U.S. forest inventory, 2010. Gen. Tech. Rep. NRS-88. U.S. Department of Agriculture, Forest Service, Northern Research Station, Newtown Square, PA, p 30
23. Woodall CW, Conkling BL, Amacher MC, Coulston JW, Jovan S, Perry CH, Schulz B, Smith GC, Will-Wolf S (2010) The forest inventory and analysis database version 4.0: description and users manual for phase 3. Gen. Tech. Rep. NRS-61. U.S. Department of Agriculture, Forest Service, Northern Research Station, Newtown Square, PA
24. Yohe G (2009) Toward an integrated framework derived from a risk-management approach to climate change. Clim Change 95:325-39 CrossRef
25. Zheng B (2004) Poverty comparisons with dependent samples. J Appl Econ 19:419-28 CrossRef - 作者单位：James A. Westfall (1)
Christopher W. Woodall (2)
Mark A. Hatfield (2)
1. USDA Forest Service, Northern Research Station, Newtown Square, PA, USA
2. USDA Forest Service, Northern Research Station, St. Paul, MN, USA - ISSN：1573-1480
文摘
At a national scale, the carbon (C) balance of numerous forest ecosystem C pools can be monitored using a stock change approach based on national forest inventory data. Given the potential influence of disturbance events and/or climate change processes, the statistical detection of changes in forest C stocks is paramount to maintaining the net sequestration status of these stocks. To inform the monitoring of forest C balances across large areas, a power analysis of a forest inventory of live/dead standing trees and downed dead wood C stocks (and components thereof) was performed in states of the Great Lakes region, U.S. Using data from the Forest Inventory and Analysis (FIA) program of the U.S. Forest Service, it was found that a decrease in downed wood C stocks (?.87?Mg/ha) was nearly offset by an increase in standing C stocks (1.77?Mg/ha) across the study region over a 5-year period. Carbon stock change estimates for downed dead wood and standing pools were statistically different from zero (α--.10), while the net change in total woody C (?.10?Mg/ha) was not statistically different from zero. To obtain a statistical power to detect change of 0.80 (α--.10), standing live C stocks must change by at least 0.7?%. Similarly, standing dead C stocks would need to change by 3.8?%; while downed dead C stocks require a change of 6.9?%. While the U.S.’s current forest inventory design and sample intensity may not be able to statistically detect slight changes (<1?%) in forest woody C stocks at sub-national scales, large disturbance events (>3?% stock change) would almost surely be detected. Understanding these relationships among change detection thresholds, sampling effort, and Type I (α) error rates allows analysts to evaluate the efficacy of forest inventory data for C pool change detection at various spatial scales and levels of risk for drawing erroneous conclusions.