Landscape and Urban Planning 82 (2007) 41–55 A spatial analysis of cumulative habitat loss in Southern California under the Clean Water Act Section 404 Program Daniel P. Swenson a,∗ , Richard F. Ambrose b a U.S. Army Corps of Engineers, Regulatory Branch, P.O. Box 532711, Los Angeles, CA 90053-2325, USA b Environmental Science and Engineering Program, Department of Environmental Health Sciences, Room 46-081 CHS, Box 951772, University of California, Los Angeles, CA 90095-1772, USA Received 20 May 2006; received in revised form 20 January 2007; accepted 31 January 2007 Available online 13 March 2007 Abstract Habitat loss is the leading cause of biodiversity reduction in the world today, with wetlands having experienced especially large losses in the United States and elsewhere. Using remote sensing and GIS techniques, this study quantified cumulative habitat loss in two Southern California watersheds associated with Clean Water Act Section 404 permits, primarily for developments, issued by the U.S. Army Corps of Engineers from 1984 to 2002. While the majority of habitat loss occurred outside of explicitly 404-authorized developments, non-explicitly authorized development represented a substantial fraction of observed habitat loss. The spatial distribution of habitat loss and 404 permits were analyzed statistically. In almost all cases, percent habitat loss was significantly correlated with variables representing 404 authorizations. These correlations may indicate the presence of incidental authorizations, suggesting that 404 authorizations within the study area may have indirectly facilitated nearby development (i.e., growth-inducing impacts). This study expanded the use of remote sensing, GIS, and spatial statistics for the purpose of regulatory-driven cumulative impact assessment. Until resource agencies quantify cumulative impacts in a spatially explicit manner and analyze those data statistically, there can be little rigorous scientific basis for formulating regulatory or policy decisions regarding cumulative impacts. © 2007 Elsevier B.V. All rights reserved. Keywords: Development; GIS; Permits; Remote sensing; Spatial autocorrelation; Wetlands 1. Introduction More than ever before, human beings are putting the world’s natural ecosystems under increasing strain (Sanderson et al., 2002). Among the effects attributable to humans, habitat loss is the leading cause of species extinctions and biodiversity reduc- tion in the world today (Chapin et al., 2000; Kerr and Deguise, 2004; Wilcove et al., 1998). Habitat loss, as for many environ- mental phenomena of concern, typically occurs as a cumulative process, in which the contribution of any one event may seem negligible but the aggregate sum of cumulative events may be substantial. ∗ Corresponding author. Tel.: +1 213 452 3414; fax: +1 213 452 4196. E-mail addresses: daniel.p.swenson@usace.army.mil (D.P. Swenson), rambrose@ucla.edu (R.F. Ambrose). The distribution and accumulation of many direct and indirect impacts across space and time are known as cumulative impacts (Hemond and Benoit, 1988; Johnston, 1994). The scientific com- munity and resource agencies continue to search for better ways to detect, quantify, and analyze on-going, cumulative impacts. In general, cumulative impact assessment has suffered from a lack of statistical analysis, leading to relatively subjective and quali- tative cumulative impact assessments. Because of the difficulty in collecting quantitative cumulative impact data, most cumu- lative impact assessment studies have been qualitative (Bedford and Preston, 1988). Even when quantitative data are collected, the spatial aspect, or locational context, of the data has rarely been analyzed or analyzed properly. For example, some studies have analyzed spatially distributed variables without account- ing for spatial autocorrelation (Lee and Marsh, 1995; Roth et al., 1996; Tischendorf, 2001; but see Kitron et al., 1996). Other studies have analyzed spatial autocorrelation or “clustering” of 0169-2046/$ – see front matter © 2007 Elsevier B.V. All rights reserved. doi:10.1016/j.landurbplan.2007.01.019