Plot intensity and cycle-length effects on growth and removals estimates from forest inventories
Anahtar Kelimeler:
Forest inventory- Remote Sensing- Remeasurement Cycle- FIA dataÖz
Continuous forest inventory planners can allocate the budget to more plots per acre or a shorter remeasurement cycle. A higher plot intensity benefits small area estimation and allows for more precision in current status estimates. Shorter cycles may provide better estimates of growth, removals and mortality. On a fixed budget, the planner can't have both greater plot intensity and shorter cycles. Therefore, it is important to understand the trade-offs involved. Growth over removals ratios are important indicators of sustainability, and can be adversely affected by changes in cycle length. However, it might be possible to ameliorate negative impacts of longer cycle lengths with judicious use of aerial imagery. Increasing the cycle length reduces the value of an inventory for monitoring, but reducing the number of plots increases the variance of both current status estimates and trend estimates. There may be no optimal statistical solution to this quandary, but the best solution will depend on policy and management objectives. Continuous forest inventories use permanent plots that are remeasured to provide information on growth, removals and mortality. Typically, all plots are remeasured within a narrow time span, but the USDA Forest Service has popularized a variant referred to as an annual forest inventory where a percentage of the permanent plots are remeasured every year. We discuss trade-offs between number of field plots and cycle length and provide some insight with example applications showing how these decisions impact growth and removals estimates. We also discuss a variant of the traditional growth over removals ratio estimator that limits degradation in estimate quality as cycle lengths increase.
Referanslar
Brand, D.G. 1997. Criteria and indicators for the conservation and sustainable management of forests: progress to date and future directions. Biomass and Bioenergy, 13, 247-253.
Bechtold, W. A., Patterson, P. L., Editors. 2005. The enhanced forest inventory and analysis program - national sampling design and estimation procedures. Gen. Tech. Rep. SRS-80. Asheville, NC: U.S. Department of Agriculture, Forest Service, Southern Research Station. 85 p.
Cochran, W.G. 1977. Sampling techniques. 3rd ed. John Wiley & Sons, New York.
Condit, R. 1998. Tropical Forest Census Plots. Springer-Verlag and R. G. Landes Company, Berlin, Germany and Georgetown, Texas.
Food and Agriculture Organization (FAO). 2011. Global forest resources assessment 2010-main report. FAO Forestry Paper No. 140. Rome, Italy: Food and Agriculture Organization. 378 p.
Hall, J.P. 2001. Criteria and Indicators of Sustainable Forest Management. Environmental Monitoring and Assessment, 67, 109-119.
Prisley, S. and A. Malmquist. 2002. Impacts of rotation age changes on growth/removals ratios. Southern Journal of Applied Forestry 26(2):72-77.
Prestemon, J.P. and R.C. Abt. 2002. The Southern Timber Market to 2040. Journal of Forestry. 100(7): 16-22.
Roesch, F. A. 2007. The Components of Change for an Annual Forest Inventory Design. Forest Science. 53(3):406-413.
Skidmore, J. P., T.G Matney, E.B. Schultz, and Z. Fan. 2014. Estimation of Forest Inventory Required Sample Sizes from Easily Observed Stand Attributes. Forest Science. Available on Forest Science fast track site June 19, 2014: DOI: http://dx.doi.org/10.5849/forsci.12-630.
Strimbu, B.M. 2014. Comparing the efficiency of intensity-based forest inventories with sampling-error-based forest inventories. Forestry: An International Journal of Forest Research 87:249-255, doi:10.1093/forestry/cpt061. Advance Access publication 15 January 2014.
Thompson, S.K. 2002. Sampling. 2nd ed. John Wiley & Sons, New York.
Van Deusen, P.C. and F.A. Roesch. 2008. Alternative definitions of growth and removals and implications for forest sustainability. Forestry 81(2):177-182.
Van Deusen, P.C. and F.A. Roesch. 2009. A Volume Change Index for Forest Growth and Sustainability. Forestry 82(3): 315-322.
Webb, J.C., K. Brewer, N. Daniels, C. Maderia, R. Hamilton, M. Finco, K.A. Megown, and A.J. Lister. 2012. Image-based change estimation for land cover and land use monitoring. p. 46-53. IN: Morin R.S. and G.C. Liknes eds. Moving from Status to Trends: Forest Inventory and Analysis Symposium 2012. Gen Tech. Rep. GTR-NRS-P-105. Newtown Square, PA: U.S. Department of Agriculture Forest Service, Northern Research Station. 159 pp.
You, S. 2011. Assessing sampling plot shape and size on measures of tropical forest diversity: A simulation study. Available on Internet: http://nature.berkeley.edu/classes/es196/projects/2011final/YouS 2011.pdf
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