Skip to main content
U.S. flag

An official website of the United States government

Evaluation of a regional monitoring program's statistical power to detect temporal trends in forest health indicators

September 1, 2014

Forests are socioeconomically and ecologically important ecosystems that are exposed to a variety of natural and anthropogenic stressors. As such, monitoring forest condition and detecting temporal changes therein remain critical to sound public and private forestland management. The National Parks Service’s Vital Signs monitoring program collects information on many forest health indicators, including species richness, cover by exotics, browse pressure, and forest regeneration. We applied a mixed-model approach to partition variability in data for 30 forest health indicators collected from several national parks in the eastern United States. We then used the estimated variance components in a simulation model to evaluate trend detection capabilities for each indicator. We investigated the extent to which the following factors affected ability to detect trends: (a) sample design: using simple panel versus connected panel design, (b) effect size: increasing trend magnitude, (c) sample size: varying the number of plots sampled each year, and (d) stratified sampling: post-stratifying plots into vegetation domains. Statistical power varied among indicators; however, indicators that measured the proportion of a total yielded higher power when compared to indicators that measured absolute or average values. In addition, the total variability for an indicator appeared to influence power to detect temporal trends more than how total variance was partitioned among spatial and temporal sources. Based on these analyses and the monitoring objectives of theVital Signs program, the current sampling design is likely overly intensive for detecting a 5 % trend·year−1 for all indicators and is appropriate for detecting a 1 % trend·year−1 in most indicators.

Publication Year 2014
Title Evaluation of a regional monitoring program's statistical power to detect temporal trends in forest health indicators
DOI 10.1007/s00267-014-0313-z
Authors Stephanie J. Perles, Tyler Wagner, Brian J. Irwin, Douglas R. Manning, Kristina K. Callahan, Matthew R. Marshall
Publication Type Article
Publication Subtype Journal Article
Series Title Environmental Management
Index ID 70148148
Record Source USGS Publications Warehouse
USGS Organization Coop Res Unit Atlanta