메뉴 건너뛰기




Volumn 5, Issue 3, 2014, Pages 207-214

Correction of location errors for presence-only species distribution models

Author keywords

Grus americana; Inhomogeneous Poisson point process; Location errors; Measurement error; Nebraska; Opportunistic sightings; Public land survey system; Regression calibration; Whooping crane

Indexed keywords


EID: 84897802221     PISSN: None     EISSN: 2041210X     Source Type: Journal    
DOI: 10.1111/2041-210X.12144     Document Type: Article
Times cited : (44)

References (33)
  • 1
    • 33748529602 scopus 로고    scopus 로고
    • Five (or so) challenges for species distribution modelling
    • Araújo, M.B. & Guisan, A. (2006) Five (or so) challenges for species distribution modelling. Journal of Biogeography, 33, 1677-1688.
    • (2006) Journal of Biogeography , vol.33 , pp. 1677-1688
    • Araújo, M.B.1    Guisan, A.2
  • 2
    • 84897749261 scopus 로고    scopus 로고
    • A comprehensive review of observational and site evaluation data of migrant whooping cranes in the United States, 1943-99. Retrieved July 17, 2013, from
    • Austin, J. & Richert, A. (2001). A comprehensive review of observational and site evaluation data of migrant whooping cranes in the United States, 1943-99. Retrieved July 17, 2013, from http://www.npwrc.usgs.gov/resource/birds/wcdata/pdf/wcdata.pdf
    • (2001)
    • Austin, J.1    Richert, A.2
  • 3
    • 33646557004 scopus 로고    scopus 로고
    • Error and uncertainty in habitat models
    • Barry, S. & Elith, J. (2006) Error and uncertainty in habitat models. Journal of Applied Ecology, 43, 413-423.
    • (2006) Journal of Applied Ecology , vol.43 , pp. 413-423
    • Barry, S.1    Elith, J.2
  • 4
    • 84873560051 scopus 로고    scopus 로고
    • Identifying appropriate spatial scales of predictors in species distribution models with the random forest algorithm
    • Bradter, U., Kunin, W.E., Altringham, J.D., Thom, T.J. & Benton, T.G. (2013) Identifying appropriate spatial scales of predictors in species distribution models with the random forest algorithm. Methods in Ecology and Evolution, 4, 167-174.
    • (2013) Methods in Ecology and Evolution , vol.4 , pp. 167-174
    • Bradter, U.1    Kunin, W.E.2    Altringham, J.D.3    Thom, T.J.4    Benton, T.G.5
  • 7
    • 0040950948 scopus 로고
    • On Poisson laws for distributions of particles in space
    • Dobrushin, R.L. (1963) On Poisson laws for distributions of particles in space. Ukrains'kyi Matematychnyl Zhurnal, 8, 127-134.
    • (1963) Ukrains'kyi Matematychnyl Zhurnal , vol.8 , pp. 127-134
    • Dobrushin, R.L.1
  • 8
    • 84871659770 scopus 로고    scopus 로고
    • Predicting the geographic distribution of a species from presence-only data subject to detection errors
    • Dorazio, R. (2012) Predicting the geographic distribution of a species from presence-only data subject to detection errors. Biometrics, 68, 1-25.
    • (2012) Biometrics , vol.68 , pp. 1-25
    • Dorazio, R.1
  • 10
    • 34247359908 scopus 로고    scopus 로고
    • Predicting species distributions from museum and herbarium records using multiresponse models fitted with multivariate adaptive regression splines
    • Elith, J. & Leathwick, J. (2007) Predicting species distributions from museum and herbarium records using multiresponse models fitted with multivariate adaptive regression splines. Diversity and Distributions, 13, 265-275.
    • (2007) Diversity and Distributions , vol.13 , pp. 265-275
    • Elith, J.1    Leathwick, J.2
  • 11
    • 73949141293 scopus 로고    scopus 로고
    • Species distribution models: ecological explanation and prediction across space and time
    • Elith, J. & Leathwick, J.R. (2009) Species distribution models: ecological explanation and prediction across space and time. Annual Review of Ecology, Evolution, and Systematics, 40, 677-697.
    • (2009) Annual Review of Ecology, Evolution, and Systematics , vol.40 , pp. 677-697
    • Elith, J.1    Leathwick, J.R.2
  • 12
    • 84890888563 scopus 로고    scopus 로고
    • Finite-sample equivalence in statistical models for presence only data
    • in press.
    • Fithian, W. & Hastie, T. (2013). Finite-sample equivalence in statistical models for presence only data. Annals of Applied Statistics, in press.
    • (2013) Annals of Applied Statistics
    • Fithian, W.1    Hastie, T.2
  • 17
    • 0029155991 scopus 로고
    • Correction for covariate measurement error in generalized linear models-a bootstrap approach
    • Haukka, J.K. (1995) Correction for covariate measurement error in generalized linear models-a bootstrap approach. Biometrics, 51, 1127-1132.
    • (1995) Biometrics , vol.51 , pp. 1127-1132
    • Haukka, J.K.1
  • 18
    • 84890882740 scopus 로고    scopus 로고
    • Non-detection sampling bias in marked presence-only data
    • doi: 10.1002/ece3.887. in press.
    • Hefley, T., Tyre, A., Baasch, D. & Blankenship, E. (2013). Non-detection sampling bias in marked presence-only data. Ecology and Evolution. doi: 10.1002/ece3.887. in press.
    • (2013) Ecology and Evolution
    • Hefley, T.1    Tyre, A.2    Baasch, D.3    Blankenship, E.4
  • 19
    • 84897768520 scopus 로고    scopus 로고
    • Data from: Correction of location errors for presence-only species distribution models
    • doi:10.5061/dryad.h81s5.
    • Hefley, T.J., Baasch, D.M., Tyre, A.J. & Blankenship, E.E. (2013) Data from: Correction of location errors for presence-only species distribution models. Dryad Digital Repository. doi:10.5061/dryad.h81s5.
    • (2013) Dryad Digital Repository
    • Hefley, T.J.1    Baasch, D.M.2    Tyre, A.J.3    Blankenship, E.E.4
  • 20
    • 79952689980 scopus 로고    scopus 로고
    • Towards the modelling of true species distributions
    • Kéry, M. (2011) Towards the modelling of true species distributions. Journal of Biogeography, 38, 617-618.
    • (2011) Journal of Biogeography , vol.38 , pp. 617-618
    • Kéry, M.1
  • 23
    • 84899095057 scopus 로고    scopus 로고
    • How long should we ignore imperfect detection of species in the marine environment when modelling their distribution?
    • doi: 10.1111/faf.12039.
    • Monk, J. (2013). How long should we ignore imperfect detection of species in the marine environment when modelling their distribution? Fish and Fisheries. doi: 10.1111/faf.12039.
    • (2013) Fish and Fisheries
    • Monk, J.1
  • 24
    • 79955883596 scopus 로고    scopus 로고
    • Implications of ignoring telemetry error on inference in wildlife resource use models
    • Montgomery, R., Roloff, G.J. & Hoef, J.M.V. (2011) Implications of ignoring telemetry error on inference in wildlife resource use models. Journal of Wildlife Management, 75, 702-708.
    • (2011) Journal of Wildlife Management , vol.75 , pp. 702-708
    • Montgomery, R.1    Roloff, G.J.2    Hoef, J.M.V.3
  • 26
    • 84897768521 scopus 로고
    • Nebraska Department of Natural Resources. Nebraska sections boundary database. Retrieved January 16, 2013, from
    • Nebraska Department of Natural Resources. (1995). Nebraska sections boundary database. Retrieved January 16, 2013, from http://www.dnr.ne.gov/databank/PLSS
    • (1995)
  • 27
    • 33646242418 scopus 로고    scopus 로고
    • Modelling distribution and abundance with presence-only data
    • Pearce, J.L. & Boyce, M.S. (2006) Modelling distribution and abundance with presence-only data. Journal of Applied Ecology, 43, 405-412.
    • (2006) Journal of Applied Ecology , vol.43 , pp. 405-412
    • Pearce, J.L.1    Boyce, M.S.2
  • 28
    • 27944446350 scopus 로고    scopus 로고
    • Maximum entropy modeling of species geographic distributions
    • Phillips, S.J., Anderson, R.P. & Schapire, R.E. (2006) Maximum entropy modeling of species geographic distributions. Ecological Modelling, 190, 231-259.
    • (2006) Ecological Modelling , vol.190 , pp. 231-259
    • Phillips, S.J.1    Anderson, R.P.2    Schapire, R.E.3
  • 29
    • 63849333773 scopus 로고    scopus 로고
    • Sample selection bias and presence-only distribution models: implications for background and pseudo-absence data
    • Phillips, S.J., Dudík, M., Elith, J., Graham, C.H., Lehmann, A., Leathwick, J. & Ferrier, S. (2009) Sample selection bias and presence-only distribution models: implications for background and pseudo-absence data. Ecological Applications, 19, 181-197.
    • (2009) Ecological Applications , vol.19 , pp. 181-197
    • Phillips, S.J.1    Dudík, M.2    Elith, J.3    Graham, C.H.4    Lehmann, A.5    Leathwick, J.6    Ferrier, S.7
  • 30
    • 84897803450 scopus 로고    scopus 로고
    • R Development Core Team. R: a language and environment for statistical computing. Retrieved July 15, 2013
    • R Development Core Team. (2013). R: a language and environment for statistical computing. Retrieved July 15, 2013, from http://www.r-project.org/
    • (2013)
  • 31
    • 84875940984 scopus 로고    scopus 로고
    • Equivalence of MAXENT and Poisson point process models for species distribution modeling in ecology
    • Renner, I.W. & Warton, D.I. (2013) Equivalence of MAXENT and Poisson point process models for species distribution modeling in ecology. Biometrics, 69, 274-281.
    • (2013) Biometrics , vol.69 , pp. 274-281
    • Renner, I.W.1    Warton, D.I.2
  • 33
    • 79952680020 scopus 로고    scopus 로고
    • Poisson point process models solve the "pseudo-absence problem" for presence-only data in ecology
    • Warton, D.I. & Shepherd, L.C. (2010) Poisson point process models solve the "pseudo-absence problem" for presence-only data in ecology. Annals of Applied Statistics, 4, 1383-1402.
    • (2010) Annals of Applied Statistics , vol.4 , pp. 1383-1402
    • Warton, D.I.1    Shepherd, L.C.2


* 이 정보는 Elsevier사의 SCOPUS DB에서 KISTI가 분석하여 추출한 것입니다.