TY - CHAP
T1 - Spatial point pattern analysis of plants
AU - Franklin, Janet
N1 - Funding Information:
I thank E. Santos for the use of unpublished data from her graduate research, and the Torrey Pines Association and D.S. Smith, California State Parks, for supporting her study. My NSF grant on spatial inference and prediction from species data (0452389) supported the writing of this chapter, and I thank my lab reading group on spatial ecology for their feedback in Fall 2006. This chapter was greatly improved by the comments of S.J. Rey and B. Boots, and I thank S.J. Rey and L. Anselin for providing me the privilege of contributing to this book.
Publisher Copyright:
© Springer-Verlag Berlin Heidelberg 2010.
PY - 2010
Y1 - 2010
N2 - Plants, especially terrestrial long-lived perennials such as trees, do not usually move once established. Spatial patterns of sessile organisms can suggest or reveal ecological processes affecting the population or community in the present or the past – dispersal, establishment, competition, mortality, facilitation, growth – and as such, patterns of plants motivated early developments in spatial statistics (Pielou, 1977; Diggle, 1983). Specifically, it is intuitive to treat individual plants (or other sessile organisms) as discrete events on a plane whose locations are known and generated by point pattern processes (Ripley, 1981; Diggle, 1983; Fortin and Dale, 2005). Second-order point pattern statistics are used to measure their spatial pattern. Arthur Getis (Getis and Franklin, 1987) introduced ecologists to the application of local spatial statistics, specifically neighborhood second-order point pattern analysis, to maps of organisms. As Wiegand and Moloney (2004) noted in their review paper, second-order global statistics based on the distribution of distances between pairs of points, especially Ripley’s K-function (Ripley, 1976, 1977) derived from distances between all pairs, have been widely used in plant ecology. However, their review does not mention neighborhood analysis or local measures of spatial association (Anselin, 1995) at all. This chapter revisits the impact of the Getis and Franklin paper on the practice of spatial point pattern analysis in plant ecology, and specifically aims to determine if local statistics are being used and how.
AB - Plants, especially terrestrial long-lived perennials such as trees, do not usually move once established. Spatial patterns of sessile organisms can suggest or reveal ecological processes affecting the population or community in the present or the past – dispersal, establishment, competition, mortality, facilitation, growth – and as such, patterns of plants motivated early developments in spatial statistics (Pielou, 1977; Diggle, 1983). Specifically, it is intuitive to treat individual plants (or other sessile organisms) as discrete events on a plane whose locations are known and generated by point pattern processes (Ripley, 1981; Diggle, 1983; Fortin and Dale, 2005). Second-order point pattern statistics are used to measure their spatial pattern. Arthur Getis (Getis and Franklin, 1987) introduced ecologists to the application of local spatial statistics, specifically neighborhood second-order point pattern analysis, to maps of organisms. As Wiegand and Moloney (2004) noted in their review paper, second-order global statistics based on the distribution of distances between pairs of points, especially Ripley’s K-function (Ripley, 1976, 1977) derived from distances between all pairs, have been widely used in plant ecology. However, their review does not mention neighborhood analysis or local measures of spatial association (Anselin, 1995) at all. This chapter revisits the impact of the Getis and Franklin paper on the practice of spatial point pattern analysis in plant ecology, and specifically aims to determine if local statistics are being used and how.
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U2 - 10.1007/978-3-642-01976-0_9
DO - 10.1007/978-3-642-01976-0_9
M3 - Chapter
AN - SCOPUS:84983737400
T3 - Advances in Spatial Science
SP - 113
EP - 123
BT - Advances in Spatial Science
PB - Springer International Publishing
ER -