Bias in species range estimates from minimum convex polygons: implications for conservation and options for improved planning

By Mark A. Burgman, Julian C. Fox. 2003

527 citations recorded by the source corpus.

Subfields: Ecology, Nature and Landscape Conservation

View Paper: https://www.semanticscholar.org/paper/7b6e8835ba88f116914c035b69dc989712a8bbf7

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In Ecology

In Nature and Landscape Conservation

Citations in the corpus

Species' geographic ranges and distributional limits: pattern analysis and statistical issues (2005, unknown): “With presence (cid:1) / absence data, a home range boundary can be determined by linking all the point locations such that no angle between points exceeds 180 8 using the minimum convex polygon algorithm or the a -hull algorithm, as recommended by Burgman and Fox (2003).”
Species Distribution Models: Ecological Explanation and Prediction Across Space and Time (2009, unknown): “Techniques for modeling very sparse data include convex or alpha hulls (Burgman & Fox 2003), and—where expert opinion is considered more reliable than species records—maps drawn by hand, GIS overlays (combinations of mapped data), or habitat suitability indices (HSIs) (Elith & Leathwick 2009,…”
Effects of sampling regime on the mean and variance of home range size estimates. (2006, background): “Worton 1995b; Burgman & Fox 2003; Getz & Wilmers 2004).”
The uncertain nature of absences and their importance in species distribution modelling (2010, methodology): “In order to reduce the frequent overprediction error of this method (Burgman and Fox 2003), we excluded discontinuities within the species range by performing separate convexhulls for regionally aggregated data and also maintaining unconnected the two most distant presence localities (Fig.”
Subpopulations, locations and fragmentation: applying IUCN red list criteria to herbarium specimen data (2010, methodology): “…subpopulation structure based on analysis of the geographic distribution of collection data was assessed with four methods: grid adjacency (IUCN 1994), circular buffer, Rapoport’s mean propinquity (Rapoport 1982) and alpha hull (Burgman and Fox 2003; Edelsbrunner et al. 1983) (Fig.”
A local nearest-neighbor convex-hull construction of home ranges and utilization distributions (2004, methodology): “(Burgman and Fox 2003).”
The sizes of species’ geographic ranges (2009, background): “For example, Burgman & Fox (2003) favour the use of α –hulls over convex polygons, because the former provide an explicit means for excluding discontinuities.”
Using species distribution models to inform IUCN Red List assessments (2014, background): “For example, the alpha-hull has been suggested as a more appropiate measure when a species has a disjunct or concave distribution, or when estimating trends in species ranges (Burgman and Fox 2003).”
The use of opportunistic data for IUCN Red List assessments (2015, methodology): “The α-hull is derived from a mathematical algorithm for converting points (the locations of records) into triangles based on a threshold parameter α (Burgmann & Fox, 2003).”