Skip to Main Content
Evaluating indices that measure departure of current landscape composition from historical conditionsAuthor(s): Robert E. Keane; Lisa Holsinger; Russell A. Parsons
Source: Res. Pap. RMRS-RP-83. Fort Collins, CO: U.S. Department of Agriculture, Forest Service, Rocky Mountain Research Station. 19 p.
Publication Series: Research Paper (RP)
Station: Rocky Mountain Research Station
View PDF (1.58 MB)
DescriptionA measure of the degree of departure of a landscape from its range of historical conditions can provide a means for prioritizing and planning areas for restoration treatments. There are few statistics or indices that provide a quantitative context for measuring departure across landscapes. This study evaluated a set of five similarity indices commonly used in vegetation community ecology (Sorenson's Index, Chord Distance, Morisita's Index, Euclidean Distance, and Similarity Ratio) for application in estimating landscape departure (where departure = 1 - similarity). This involved comparing composition (vegetation type by area) of a set of reference landscapes to the compositions of 1,000 simulated historical landscapes. Stochastic simulation modeling was used to create a diverse set of synthetic reference and historical landscapes for departure index evaluation. Five reference landscapes were created to represent various degrees of expected departure from historical conditions. Both reference and historical landscapes were created to contain four important factors that could potentially influence departure calculation: (1) number of classes defining landscape composition, (2) dominance of the classes, (3) variability of area with the classes, and (4) temporal autocorrelation. We found that most evaluated indices are useful but not optimal for calculating departure. The Sorenson's Index appeared to perform the best with consistent and precise behavior across the ranges of the four treatments. The number of classes used to describe vegetation had the strongest influence on index performance; landscape composition defined by few classes had the least accurate, most imprecise, and most highly variable departure estimates. While results from this study show the utility of similarity indices in evaluating departure, it is also evident that a new set of statistics are needed to provide a more comprehensive analysis of departure for future applications.
- You may send email to email@example.com to request a hard copy of this publication.
- (Please specify exactly which publication you are requesting and your mailing address.)
- We recommend that you also print this page and attach it to the printout of the article, to retain the full citation information.
- This article was written and prepared by U.S. Government employees on official time, and is therefore in the public domain.
CitationKeane, Robert E.; Holsinger, Lisa; Parsons, Russell A. 2011. Evaluating indices that measure departure of current landscape composition from historical conditions. Res. Pap. RMRS-RP-83. Fort Collins, CO: U.S. Department of Agriculture, Forest Service, Rocky Mountain Research Station. 19 p.
Keywordsecosystem management, similarity indices, landscape ecology, historical ecology, historical range and variability, HRV, neutral landscapes
- Use of landscape simulation modeling to quantify resilience for ecological applications
- Using simulated historical time series to prioritize fuel treatments on landscapes across the United States: The LANDFIRE prototype project
- Chapter 10 - Using simulation modeling to assess historical reference conditions for vegetation and fire regimes for the LANDFIRE Prototype Project
XML: View XML