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Predicting the potential invasive range of raccoon in the world

Warianty tytułu
Języki publikacji
EN
Abstrakty
EN
Invasive alien species are considered to be one of the most important causes for the extinction and the reason for diminishing of the wild native species. Considering that nowadays the raccoon (Procyon lotor, Linnaeus 1758) is found in several European and Asian countries where it can amplification its ranges remarkably, but it is actually native to North and Central America. Here, we use the Maxent model to generate a preliminary map of the potential distribution of the raccoon around the world and enumerate its relative risk of invasion across all countries. In a study, MaxEnt predicted a significantly large area as the eco-climatically suitable habitat for the raccoon in the world. The predicted habitats are consistent with the wide-ranging habitat associations of the raccoon in its well-established sites. The results identified the hotspots of the raccoon invasion and indicated the possible dispersal pathways. Results also showed that both precipitation and temperature variables were strongly correlated with the raccoon distribution and the species would be absent in cold environments with average sub-zero temperatures.
Rocznik
Strony
594--600
Opis fizyczny
Bibliogr. 43 poz., mapa, tab., wykr.
Twórcy
autor
  • Department of Environmental Sciences, Faculty of natural resource and environment, Ferdowsi University of Mashhad, Iran
autor
  • Department of Environmental Sciences, Faculty of Agriculture and Natural Resources, Arak University, Arak, Iran
autor
  • Department of Habitats and Biodiversity, Faculty of environment and energy, Islamic Azad University of Tehran - Sciences and Research Branch, Tehran, Iran
Bibliografia
  • [1] Bartoszewicz M., Okarma H., Zalewski A., Szczęsna J. 2008 — Ecology of the raccoon (Procyon lotor) from western Poland — Ann. Zool. Fennici. 45: 291–298.
  • [2] Canova L., Rossi S. 2008 — First records of the northern raccoon Procyon lotor in Italy — Hystrix It. J. Mamm. 19: 179–182.
  • [3] Dormann C. F., Elith J., Bacher S., Buchmann C., Carl G., Carre G., Marquez J. R. G., Gruber B., Lafourcade B., Leitao P. J., Munkemuller T., McClean C., Osborne P. E., Reineking B., Schroder B., Skidmore A. K., Zureil D., Lautenbach S. 2013 — Collinearity: a review of methods to deal with it and a simulation study evaluating their performance — Ecography, 36: 27–46.
  • [4] Elith J., Kearney M., Phillips S. 2010 — The art of modelling range shifting species — Methods Ecol. Evol. 1: 330–342.
  • [5] Evangelista P. H., Kumar S., Stohlgren T. J., Jarnevich C. S., Crall A. W. et al. 2008 — Modelling invasion for a habitat generalist and a specialist plant species — Divers Distrib. 14: 808–817.
  • [6] Farashi A., Kaboli M., Karami M. 2013 — Predicting range expansion of Invasive Raccoons in Northern Iran Using GARP and ENFA Models at Two Different Scales — Ecol. Inform. 15: 96–102.
  • [7] Farashi A., Naderi M. 2016 – Predicting Invasion Risk of Raccoon Procyon lotor in Iran Using Environmental Niche Models — Landscape Ecol. Eng. (in publish).
  • [8] Franklin J. 2009 — Mapping Species Distributions: Spatial Inference and Prediction — Cambridge University Press, Cambridge, UK, 320 p.
  • [9] Frantz A. C., Cyriacks P., Schley L. 2005 — Spatial behaviour of a female raccoon (Procyon lotor) at the edge of the species' European distribution range — Eur. J. Wildl. Res. 51: 126–130.
  • [10] Giovanelli J. G. R., Haddad C. F. B., Alexandrino J. 2007 — Predicting the potential distribution of the alien invasive American bullfrog (Lithobates catesbeianus) in Brazil — Biol. Invas. 10: 585–590.
  • [11] Guisan A., Graham C. H., Elith J., Huettmann F., the NCEAS Species Distribution Modelling Group, 2007a — Sensitivity of predictive species distribution models to change in grain size — Divers Distrib. 13: 332–340.
  • [12] Guisan A., Zimmermann N. E., Elith J., Graham C. H., Phillips S., Peterson A. T. 2007b — What matters for predicting the occurrences of trees: techniques, data or species' characteristics? — Ecol. Monogr. 77: 615–630.
  • [13] Helgen K. M., Maldonado J. E., Wilson D. E., Buckner S. D. 2008 — Molecular confirmation of the origin and invasive status of West Indian raccoons — J. Mammal. 89:282–291.
  • [14] Hijmans R. J., Cameron S. E., Parra J. L., Jones P. G., Jarvis A. 2005 — Very high resolution interpolated climate surfaces for global land areas — Int. J. Climatol. 25: 1965–1978.
  • [15] Hutchinson G. E. 1957 — Concluding Remarks — Cold Spring Harbor Symposia on Quant Biol. 22:415–427.
  • [16] Hutchinson G. E. 1978 — An introduction to population ecology — New Haven, CT: Yale University Press, 260 pp.
  • [17] Jeschke J. M., Strayer D. L. 2008 — Usefulness of bioclimatic models for studying climate change and invasive species — Ann N.Y. Acad. Sci. 1134: 1–24.
  • [18] Kadmon R., Farber O., Danin A. 2004 — Effect of roadside bias on the accuracy of predictive maps produced by bioclimatic models — Ecol. Appl. 14: 401–413.
  • [19] Kauhala K. 1996 — Introduced carnivores in Europe with special reference to central and northern Europe — Wildl. Biol. 2: 197–204.
  • [20] Liu C. R., White M., Newell G. 2011 — Measuring and comparing the accuracy of species distribution models with presence-absence data — Ecography 34: 232–243.
  • [21] Lowe S., Browne M., Boudjelas S., De Poorter M. 2000 — 100 of the world's worst invasive alien species. A selection from the Global Invasive Species Database. ISSG, Auckland, New Zealand. www.issg.org.
  • [22] Menke S. B., Holway D. A., Fisher R. N., Jetz W. 2009 — Characterizing and predicting species distributions across environments and scales: Argentine ant occurrences in the eye of the beholder — Glob. Ecol. Biogeogr. 18: 50–63.
  • [23] Okabe F., Agetsuma N. 2007 — Habitat use by introduced raccoons and native raccoon dogs in a deciduous forest of Japan — J. Mammal. 88: 1090–1097.
  • [24] Peterson A. T. 2001 — Predicting species' geographic distributions based on ecological niche modelling — Condor, 103: 599–605.
  • [25] Peterson A. T. 2003 — Predicting the geography of species' invasions via ecological niche modelling — Rev. Biol. 78: 419–433.
  • [26] Peterson A. T., Soberon J., Pearson R. G., Anderson R. P., Martinez-Meyer E., Nakamura M., Araujo M. B. 2011 — Ecological Niches and Geographic Distributions — Princeton University Press, Princeton, NJ, 328 pp.
  • [27] Peterson A. T., Vieglais D. A. 2001 — Predicting species invasions using ecological niche modeling: new approaches from bioinformatics attack a pressing problem — BioSci. 51: 363–371.
  • [28] Phillips S. J. 2008 — Transferability, sample selection bias and background data in presenceonly modelling: a response to Peterson et al. (2007) — Ecography, 31: 272–278.
  • [29] Phillips S. J., Anderson R. P., Schapire R. E. 2006 — Maxent entropy modeling of species geographic distribution — Ecol. Model. 190: 231–259.
  • [30] Phillips S. J., Dudik M. 2008 — Modeling of species distributions with Maxent: new extensions and a comprehensive evaluation — Ecography, 31: 161–175.
  • [31] Phillips S. J., Dudik 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 — Ecol. Appl. 19:181–197.
  • [32] Rödder D. 2009 — ‘Sleepless in Hawaii’ — does anthropogenic climate change enhance ecological and socioeconomic impacts of the alien invasive Eleutherodactylus coqui Thomas, 1966 (Anura: Eleutherodactylidae)? — North-West J. Zool. 5: 16–25.
  • [33] Rödder D., Solé M., Böhme W. 2008 — Predicting the potential distribution of two alien invasive Housegeckos (Gekkonidae: Hemidactylus frenatus,Hemidactylus mabouia) — North-West J. Zool. 4: 236–246.
  • [34] Schrader B., Hennon P. 2005 — Assessment of invasive species in Alaska and its national forests — United States Department of Agriculture and Forest Service, Regional Office, Anchorage.
  • [35] Segurado P., Araujo M. B., Kunin W. E. 2006 — Consequences of spatial autocorrelation for nichebased models — J. Appl. Ecol. 43: 433–444.
  • [36] Soberón J., Peterson A. T. 2005 — Interpretation of models of fundamental ecological niches and species' distributional areas — Biodiv. Inform. 2:1–10.
  • [37] Stockwell D. R. B., Peterson A. T. 2002 — Effects of sample size on accuracy of species distribution models — Ecol. Model. 148: 1–13.
  • [38] VanDerWal J., Shoo L. P., Graham C., William S. E. 2009 — Selecting pseudo-absence data for presence-only distribution modeling: how far should you stray from what you know? — Ecol. Model. 220: 589–594.
  • [39] Wandeler A., Salsberg D. E. 1999 — Raccoon rabies in eastern Ontario — Can. Vet. J. 40: 731.
  • [40] Weber T. C. 2011 — Maximum entropy modeling of mature hardwood forest distribution in four U.S. states — Forest Ecol. Manag. 261: 779–788.
  • [41] Welk, Schubert K., Hoffman M. H. 2002 — Present and potential distribution of invasive garlic mustard (Alliaria petiolata) in North America — Divers Distrib. 8: 219–233.
  • [42] Winter M. 2009 — Procyon lotor (In: Handbook of Alien species in Europe, Ed: Aisie), Springer, Dordrecht, 368 pp.
  • [43] Xu Z., Peng H., Feng Z., Abdulsalih N. 2014 — Predicting current and future invasion of Solidagocanadensis: a study from China — Pol. J. Ecol. 62: 263–271.
Uwagi
Opracowanie ze środków MNiSW w ramach umowy 812/P-DUN/2016 na działalność upowszechniającą naukę (zadania 2017).
Typ dokumentu
Bibliografia
Identyfikator YADDA
bwmeta1.element.baztech-c9bb52cb-4b2a-4f55-bb5c-be73188d11d2
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