TY - JOUR
T1 - Empirical patterns of the effects of changing scale on landscape metrics
AU - Wu, Jianguo
AU - Shen, Weijun
AU - Sun, Weizhong
AU - Tueller, Paul T.
N1 - Funding Information:
We would like to thank Ellen Ellis, Michael Limb, Yuanbo Liu, and Matt Luck for their assistance with the preparation of the data sets used in this study. We are also grateful to Fangliang He, Darrel Jenerette, Habin Li, and Matt Luck for their comments on an earlier draft of the paper. We especially appreciate the comments and suggestions by R. H. Gardner and two anonymous reviewers which led to substantial im- provements of the manuscript. This research was supported in part by grants from US-EPA (R827676-01-0), USDA (NRICGP 95-37101-2028) and US-NSF (DEB 97-14833, CAP-LTER).
Funding Information:
Phoenix is located in the northern part of the Sonoran desert in the State of Arizona, and is the home of the Central Arizona-Phoenix Long-Term Ecological Research (CAPLTER) Project, one of the two new urban LTER sites supported by the US National Science Foundation. Native vegetation is characterized by desert scrub communities dominated by creosote bush (Larrea tridentata), mesquite (Prosopis glandu-losa), and several other shrub species, including the magnificent cactus, saguaro (Carnegiea gigantea) – the most recognized symbol of the Sonoran desert landscape. In the past several decades this region has experienced tremendous land transformation as Phoenix has become the fastest growing city in the United States. As a consequence of the rapid urbanization, the composition and spatial structure of the Phoenix landscape have changed dramatically (Jenerette and Wu 2002; Luck and Wu 2002). The Phoenix urban landscape data were obtained by rasterizing the vector-based 1995 land use map (originally produced by the Maricopa Association of Governments) at the 30-meter resolution. To examine the sensitivity of landscape metrics to shifting geographic locations of the study area within the same region, we clipped two study landscapes from the Phoenix area (see Figure 1D): Phx_1 (1500 × 1500 pixels in size and centering at the urban core area) and Phx_2 (1500 × 1500 pixels in size and covering the transitional zone from the Sonoran desert north of Phoenix to the city itself).
PY - 2002
Y1 - 2002
N2 - While ecologists are well aware that spatial heterogeneity is scale-dependent, a general understanding of scaling relationships of spatial pattern is still lacking. One way to improve this understanding is to systematically examine how pattern indices change with scale in real landscapes of different kinds. This study, therefore, was designed to investigate how a suite of commonly used landscape metrics respond to changing grain size, extent, and the direction of analysis (or sampling) using several different landscapes in North America. Our results showed that the responses of the 19 landscape metrics fell into three general categories: Type I metrics showed predictable responses with changing scale, and their scaling relations could be represented by simple scaling equations (linear, power-law, or logarithmic functions); Type II metrics exhibited staircase-like responses that were less predictable; and Type III metrics behaved erratically in response to changing scale, suggesting no consistent scaling relations. In general, the effect of changing grain size was more predictable than that of changing extent. Type I metrics represent those landscape features that can be readily and accurately extrapolated or interpolated across spatial scales, whereas Type II and III metrics represent those that require more explicit consideration of idiosyncratic details for successful scaling. To adequately quantify spatial heterogeneity, the metric-scalograms (the response curves of metrics to changing scale), instead of single-scale measures, seem necessary.
AB - While ecologists are well aware that spatial heterogeneity is scale-dependent, a general understanding of scaling relationships of spatial pattern is still lacking. One way to improve this understanding is to systematically examine how pattern indices change with scale in real landscapes of different kinds. This study, therefore, was designed to investigate how a suite of commonly used landscape metrics respond to changing grain size, extent, and the direction of analysis (or sampling) using several different landscapes in North America. Our results showed that the responses of the 19 landscape metrics fell into three general categories: Type I metrics showed predictable responses with changing scale, and their scaling relations could be represented by simple scaling equations (linear, power-law, or logarithmic functions); Type II metrics exhibited staircase-like responses that were less predictable; and Type III metrics behaved erratically in response to changing scale, suggesting no consistent scaling relations. In general, the effect of changing grain size was more predictable than that of changing extent. Type I metrics represent those landscape features that can be readily and accurately extrapolated or interpolated across spatial scales, whereas Type II and III metrics represent those that require more explicit consideration of idiosyncratic details for successful scaling. To adequately quantify spatial heterogeneity, the metric-scalograms (the response curves of metrics to changing scale), instead of single-scale measures, seem necessary.
KW - Anisotropy
KW - Extent
KW - Grain
KW - Landscape metric scalograms
KW - Landscape pattern analysis
KW - Scale effect
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U2 - 10.1023/A:1022995922992
DO - 10.1023/A:1022995922992
M3 - Article
AN - SCOPUS:0036968138
SN - 0921-2973
VL - 17
SP - 761
EP - 782
JO - Landscape Ecology
JF - Landscape Ecology
IS - 8
ER -