The DOI matches its Crossref record.
Animal Movement Data: GPS Telemetry, Autocorrelation and the Need for Path-Level Analysis
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Autocorrelation, spatial scale of movement, and mortality risk have well-established and fundamental importance in shaping movement patterns.
“For example, these models do not account for autocorrelation, spatial scale of movement, or mortality risk, despite the well-established and fundamental importance these factors have in shaping movement patterns5,35–37.”
From Connectivity modelling in conservation science: a comparative evaluation (2022) · cites this paper as [36]
These models do not account for autocorrelation, spatial scale of movement, or mortality risk.
“For example, these models do not account for autocorrelation, spatial scale of movement, or mortality risk, despite the well-established and fundamental importance these factors have in shaping movement patterns5,35–37.”
From Connectivity modelling in conservation science: a comparative evaluation (2022) · cites this paper as [36]
Citations
Cites
No references could be resolved yet.
Research works printed but not linked: 24
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- Allderedge JR, Ratti JT (1986) Comparison of some statistical techniques for analysis of resource selection. J Wildl Manag 50:157–165 · DOI
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- Litvaitis JA, Titus K, Anderson EM (1994) Measuring vertebrate use of terrestrial habitats and foods. Invited contribution. In: T. Bookhout (Ed.) Research and management techniques for wildlife and habitats. The Wildlife Society, Washington, DC, pp. 254–274
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- Oden NL, Sokal RR (1986) Directional autocorrelation: an extension of spatial correlograms to two dimensions. Syst Zool 35:526–530 · DOI
- Otis DL, White GC (1999) Autocorrelation of location estimates and the analysis of radio tracking data. J Wildl Manag 63:1039–1044 · DOI
- Palomares F, Delibes M (1992) Data analysis and potential bias in radio-tracking studies of animal habitat use. Acta Oecol 13:221–226
- Rooney S, Wolfe MA, Kayden TJ (1998) Autocorrelated data in telemetry studies: time to independence and the problem of behavioral effects. Mammal Rev 28:89–98 · DOI
- Schoener TW (1981) An empirically based estimate of home range. Theor Popul Biol 20:281–325 · DOI
- Sokal RR (1986) Spatial data analysis and historical processes. In: Daly E, et al. (eds) Data analysis and informatics, I V. North-Holland, Amsterdam
- Springer JT (1979) Some sources of bias and sampling error in radio triangulation. J Wildl Manag 43:926–935 · DOI
- Swihart RK, Slade NA, (1985) Influence of sampling interval on estimates of home-range size. J Wildl Manag 49:1019–1025 · DOI
- Swihart RK, Slade NA (1997) On testing for independence of animal movements. J Agric Biol Environ Statist 2:48–63 · DOI
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Cited by
Sorted by citations
Connectivity modelling in conservation science: a comparative evaluation
Unnithan Kumar, S., & Cushman, S. A. (2022) · Scientific Reports · doi:10.1038/s41598-022-20370-w · Cited by 83
Self-citation
Metadata
- Authors
- Cushman, S. A.
- Venue
- Spatial Complexity, Informatics, and Wildlife Conservation
- Publisher
- Springer Japan
- Published
- 2010
- Pages
- 131-149
- Cited by
- 27
- References
- 0
- Language
- en
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Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
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