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Global invasion in progress: modeling the past, current and potential global distribution of the common myna

  • Tali Magory Cohen
  • Matthew McKinney
  • Salit Kark
  • Roi DorEmail author
Original Paper

Abstract

Determining the distribution and potential ranges of detrimental invasive species has become an essential task in light of their impacts on the environment. However, this effort has been challenging, especially for global invaders. Our goal was to test whether potential ranges of global invaders can be predicted, and examine the factors that shape them by studying the past, current and potential global distribution of a broad-ranging avian invader. We used the common myna (Acridotheres tristis), one of the most broad-ranging avian invaders whose range is currently expanding globally, as a case study. We collected the first detailed global database of global occurrence (n = 7990) of the common myna over the past 150 years, including records from the native and the introduced ranges. We employed MaxEnt to construct species distribution models (SDM) for the global database using climatic, anthropogenic and environmental factors. We provide evidence that invasive species distributions can be predicted from older records, and that model accuracy requires integrating data from the introduced range. This first comprehensive distribution for an avian invader indicates an extensive expansion in the common myna global distribution, with the potential of large areas worldwide being at risk of common myna invasion, thus threatening local biodiversity globally. Range expansion has been facilitated by proximity to urbanized areas and broad environmental tolerance. Our findings reflect the major role of anthropogenic impact in increasing the global distribution of avian invaders and emphasize the value of using SDMs to inform global management practices.

Keywords

Anthropogenic effect Avian invasion Common myna Invasive species Range expansion Species distribution models 

Notes

Acknowledgements

We thank the associate editor, Adam B. Smith, Emiliano Mori and an anonymous reviewer for their suggestions and comments. We are grateful to Emiliano Mori also for providing additional data for our analyses. We thank Takuya Iwamura, Jonathan Belmaker and Shai Meiri for their helpful comments, and to Adi Barocas for his technical assistance. We thank Naomi Paz for English editing. We also thank Steven Phillips for his vital help. Further thanks are due to Angelo Soto-Centeno for his thoughtful guidance. We are grateful to the Society for Protection of Nature in Israel, Israel Nature and Parks Authority, Shlomit Lifshitz and The Israeli Center for Yardbirds, J. L. Tella and C. Holzapfel for their valuable assistance in records collection.

Funding

This work was supported by the Tel Aviv University Global Research & Training Fellowship in Medical and Life Sciences (GRTF) fund, The Smaller-Winnikow Fellowship Fund for Environmental Research, and The Rieger Foundation-Jewish National Fund fellowship. SK is supported by the Australian Research Council.

Supplementary material

10530_2018_1900_MOESM1_ESM.docx (2.2 mb)
Supplementary material 1 (DOCX 2217 kb)

References

  1. Ancillotto L, Strubbe D, Menchetti M, Mori E (2016) An overlooked invader? Ecological niche, invasion success and range dynamics of the Alexandrine parakeet in the invaded range. Biol Invasions 18:583–595.  https://doi.org/10.1007/s10530-015-1032-y CrossRefGoogle Scholar
  2. Baker AJ, Moeed A (1987) Rapid genetic differentiation and founder effect in colonizing populations of common mynas (Acridotheres tristis). Evolution (N Y) 41:525–538Google Scholar
  3. Beaumont LJ, Gallagher RV, Thuiller W et al (2009) Different climatic envelopes among invasive populations may lead to underestimations of current and future biological invasions. Divers Distrib 15:409–420.  https://doi.org/10.1111/j.1472-4642.2008.00547.x CrossRefGoogle Scholar
  4. Blackburn TM, Cassey P, Lockwood JL (2009) The role of species traits in the establishment success of exotic birds. Glob Change Biol 15:2852–2860.  https://doi.org/10.1111/j.1365-2486.2008.01841.x CrossRefGoogle Scholar
  5. Boria RA, Olson LE, Goodman SM, Anderson RP (2014) Spatial filtering to reduce sampling bias can improve the performance of ecological niche models. Ecol Model 275:73–77.  https://doi.org/10.1016/j.ecolmodel.2013.12.012 CrossRefGoogle Scholar
  6. Broennimann O, Guisan A (2008) Predicting current and future biological invasions: both native and invaded ranges matter. Biol Lett 4:585–589CrossRefGoogle Scholar
  7. Broennimann O, Treier UA, Müller-Schärer H et al (2007) Evidence of climatic niche shift during biological invasion. Ecol Lett 10:701–709.  https://doi.org/10.1111/j.1461-0248.2007.01060.x CrossRefPubMedGoogle Scholar
  8. Buckland S, Cole NC, Aguirre-Gutiérrez J et al (2014) Ecological effects of the invasive giant madagascar day gecko on endemic Mauritian geckos: applications of binomial-mixture and species distribution models. PLoS ONE.  https://doi.org/10.1371/journal.pone.0088798 CrossRefPubMedPubMedCentralGoogle Scholar
  9. Canning G (2011) Eradication of the invasive common myna, Acridotheres tristis, from Fregate Island, Seychelles. Phelsuma 19:43–53Google Scholar
  10. Charter M, Izhaki I, Ben Mocha Y, Kark S (2016) Nest-site competition between invasive and native cavity nesting birds and its implication for conservation. J Environ Manag 181:129–134.  https://doi.org/10.1016/j.jenvman.2016.06.021 CrossRefGoogle Scholar
  11. Cramp S, Perrins CM (1994) Handbook of the birds of Europe, the Middle East and Africa. The birds of the western Palearctic vol VIII: crows to finches. Oxford University Press, OxfordGoogle Scholar
  12. Crawford KM, Whitney KD (2010) Population genetic diversity influences colonization success. Mol Ecol 19:1253–1263.  https://doi.org/10.1111/j.1365-294X.2010.04550.x CrossRefPubMedGoogle Scholar
  13. Crooks KR, Suarez AV, Bolger DT (2004) Avian assemblages along a gradient of urbanization in a highly fragmented landscape. Biol Conserv 115:451–462CrossRefGoogle Scholar
  14. Crystal-Ornelas R, Lockwood JL, Cassey P, Hauber ME (2017) The establishment threat of the obligate brood-parasitic Pin-tailed Whydah (Vidua macroura) in North America and the Antilles. Condor 119:449–458.  https://doi.org/10.1650/CONDOR-16-150.1 CrossRefGoogle Scholar
  15. Davis MA, Grime JP, Thompson K et al (2000) Fluctuating resources in plant communities: fluctuating resources a general of invasibility theory. J Ecol 88:528–534.  https://doi.org/10.1046/j.1365-2745.2000.00473.x CrossRefGoogle Scholar
  16. De Marco P, Diniz-Filho JAF, Bini LM (2008) Spatial analysis improves species distribution modelling during range expansion. Biol Lett 4:577–580CrossRefGoogle Scholar
  17. Dukes JS, Mooney HA (1999) Does global change increase the success of biological invaders? Trends Ecol Evol 14:135–139.  https://doi.org/10.1016/S0169-5347(98)01554-7 CrossRefPubMedGoogle Scholar
  18. Elith J (2013) Predicting distributions of invasive species. 1–28Google Scholar
  19. Elith J (2015) Predicting distributions of invasive species. In: Walshe TR, Robinson A, Nunn M, Burgman MA (eds) Risk-based decisions for biological threats. Cambridge University Press, CambridgeGoogle Scholar
  20. Elith J, Leathwick JR (2009) Species distribution models: ecological explanation and prediction across space and time. Annu Rev Ecol Evol Syst 40:677–697.  https://doi.org/10.1146/annurev.ecolsys.110308.120159 CrossRefGoogle Scholar
  21. Elith J, Phillips SJ, Hastie T et al (2011) A statistical explanation of MaxEnt for ecologists. Divers Distrib 17:43–57.  https://doi.org/10.1111/j.1472-4642.2010.00725.x CrossRefGoogle Scholar
  22. Feare CJ (2010) The use of Starlicide ® in preliminary trials to control invasive common myna Acridotheres tristis populations on St Helena and Ascension islands, Atlantic Ocean. Conserv Evid 7:52–61Google Scholar
  23. Feare C, Craig A (1999) Common myna, Acridotheres tristis. In: Starlings and mynas. Princeton University Press, Princeton, pp 157–160Google Scholar
  24. Forys EA, Allen CR (1999) Biological invasions and deletions: community change in south Florida. Biol Conserv 87:341–347.  https://doi.org/10.1016/S0006-3207(98)00073-1 CrossRefGoogle Scholar
  25. Fraser D, Aguilar G, Nagle W et al (2015) The house crow (Corvus splendens): a threat to New Zealand? ISPRS Int J Geo-Inf 4:725–740.  https://doi.org/10.3390/ijgi4020725 CrossRefGoogle Scholar
  26. Gallien L, Münkemüller T, Albert CH et al (2010) Predicting potential distributions of invasive species: Where to go from here? Divers Distrib 16:331–342CrossRefGoogle Scholar
  27. Gallien L, Douzet R, Pratte S et al (2012) Invasive species distribution models—how violating the equilibrium assumption can create new insights. Glob Ecol Biogeogr 21:1126–1136CrossRefGoogle Scholar
  28. Giovanelli JGR, Haddad CFB, Alexandrino J (2008) Predicting the potential distribution of the alien invasive American bullfrog (Lithobates catesbeianus) in Brazil. Biol Invasions 10:585–590.  https://doi.org/10.1007/s10530-007-9154-5 CrossRefGoogle Scholar
  29. Graham CH, Ferrier S, Huettman F et al (2004) New developments in museum-based informatics and applications in biodiversity analysis. Trends Ecol Evol 19:497–503CrossRefGoogle Scholar
  30. Grarock K, Tidemann CR, Wood J, Lindenmayer DB (2012) Is it Benign or is it a pariah? Empirical evidence for the impact of the common myna (Acridotheres tristis) on Australian birds. PLoS ONE.  https://doi.org/10.1371/journal.pone.0040622 CrossRefPubMedPubMedCentralGoogle Scholar
  31. Grarock K, Tidemann CR, Wood JT, Lindenmayer DB (2014) Are invasive species drivers of native species decline or passengers of habitat modification? A case study of the impact of the common myna (Acridotheres tristis) on Australian bird species. Austral Ecol 39:106–114.  https://doi.org/10.1111/aec.12049 CrossRefGoogle Scholar
  32. Guisan A, Thuiller W (2005) Predicting species distribution: offering more than simple habitat models. Ecol Lett 8:993–1009.  https://doi.org/10.1111/j.1461-0248.2005.00792.x CrossRefGoogle Scholar
  33. Hanberry BB, He HS (2013) Prevalence, statistical thresholds, and accuracy assessment for species distribution models. Web Ecol 13:13–19.  https://doi.org/10.5194/we-13-13-2013 CrossRefGoogle Scholar
  34. Hayes MA, Cryan PM, Wunder MB (2015) Seasonally-dynamic presence-only species distribution models for a cryptic migratory bat impacted by wind energy development. PLoS ONE 10:1–20.  https://doi.org/10.1371/journal.pone.0132599 CrossRefGoogle Scholar
  35. Hijmans RJ, Phillips S, Leathwick J, Elith J (2017) dismo: species distribution modeling. R package version 1.1-4. https://CRAN.R-project.org/package=dismo
  36. Holzapfel C, Levin N, Hatzofe O, Kark S (2006) Colonisation of the Middle East by the invasive Common Myna Acridotheres tristis L., with special reference to Israel. Sandgrouse 28:44Google Scholar
  37. Hone J (1978) Introduction and spread of the common myna in New South Wales. Emu-Austral Ornithol 78:227–230CrossRefGoogle Scholar
  38. Hulme PE (2009) Trade, transport and trouble: managing invasive species pathways in an era of globalization. J Appl Ecol 46:10–18CrossRefGoogle Scholar
  39. Jiménez-Valverde A, Decae AE, Arnedo MA (2011a) Environmental suitability of new reported localities of the funnelweb spider Macrothele calpeiana: an assessment using potential distribution modelling with presence-only techniques. J Biogeogr 38:1213–1223.  https://doi.org/10.1111/j.1365-2699.2010.02465.x CrossRefGoogle Scholar
  40. Jiménez-Valverde A, Peterson AT, Soberón J et al (2011b) Use of niche models in invasive species risk assessments. Biol Invasions 13:2785–2797.  https://doi.org/10.1007/s10530-011-9963-4 CrossRefGoogle Scholar
  41. Keane RM, Crawley MJ (2002) Exotic plant invasions and the enemy release hypothesis. Trends Ecol Evol 17:164–170CrossRefGoogle Scholar
  42. Khoury F, Alshamlih M (2015) First evidence of colonization by common myna Acridotheres tristis in Jordan, 2013–2014. Sandgrouse 37:22–24Google Scholar
  43. Kolar CS, Lodge DM (2001) Progress in invasion biology: predicting invaders. Ecol Evol 16:199–204CrossRefGoogle Scholar
  44. Kramer-Schadt S, Niedballa J, Pilgrim JD et al (2013) The importance of correcting for sampling bias in MaxEnt species distribution models. Divers Distrib 19:1366–1379.  https://doi.org/10.1111/ddi.12096 CrossRefGoogle Scholar
  45. Kurdila J (1988) The introduction of exotic species into the United States: there goes the neighborhood. Boston Coll Environ Aff Law Rev 16:95Google Scholar
  46. Liu C, Berry PM, Dawson TP, Pearson RG (2005) Selecting thresholds of occurrence in the prediction of species distributions. Ecography (Cop) 28:385–393.  https://doi.org/10.1111/j.0906-7590.2005.03957.x CrossRefGoogle Scholar
  47. Liu C, Newell G, White M (2016) On the selection of thresholds for predicting species occurrence with presence-only data. Ecol Evol 6:337–348CrossRefGoogle Scholar
  48. Lobo JM, Jiménez-Valverde A, Real R (2008) AUC: a misleading measure of the performance of predictive distribution models. Glob Ecol Biogeogr 17:145–151CrossRefGoogle Scholar
  49. Lockwood JL, Cassey P, Blackburn TM (2009) The more you introduce the more you get: the role of colonization pressure and propagule pressure in invasion ecology. Divers Distrib 15:904–910.  https://doi.org/10.1111/j.1472-4642.2009.00594.x CrossRefGoogle Scholar
  50. Long JL (1981) Introduced birds of the world: the worlwide history, distribution and influence of birds introduced to new environments. David and Charles, LondonGoogle Scholar
  51. 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. Invasive Species Specialist Group, AucklandGoogle Scholar
  52. Luque GM, Bellard C, Bertelsmeier C et al (2014) The 100th of the world’s worst invasive alien species. Biol Invasions 16:981–985.  https://doi.org/10.1007/s10530-013-0561-5 CrossRefGoogle Scholar
  53. Machovsky-Capuska GE, Senior AM, Zantis SP et al (2016) Dietary protein selection in a free-ranging urban population of common myna birds. Behav Ecol 27:219–227.  https://doi.org/10.1093/beheco/arv142 CrossRefGoogle Scholar
  54. Marambe B, Bambaradeniya C, Pushpa Kumara DK, Pallewatta N (2001) The great reshuffling: human dimensions of invasive alien species in Sri Lanka. IUCN, Gland, pp 135–142Google Scholar
  55. Marchetti MP, Moyle PB, Levine R (2004) Invasive species pro ling? Exploring the characteristics of non-native shes across invasion stages in California. Freshw Biol.  https://doi.org/10.1111/j.1365-2427.2004.01202.x CrossRefGoogle Scholar
  56. Marzluff JM, Neatherlin E (2006) Corvid response to human settlements and campgrounds: causes, consequences, and challenges for conservation. Biol Conserv 130:301–314CrossRefGoogle Scholar
  57. Marzluff JM, McGowan KJ, Donnelly R, Knight RL (2001) Causes and consequences of expanding American Crow populations. In: Marzluff JM, Donnelly R (eds) Avian ecology and conservation in an urbanizing world. Springer, Berlin, pp 331–363CrossRefGoogle Scholar
  58. McCune JL (2016) Species distribution models predict rare species occurrences despite significant effects of landscape context. J Appl Ecol 53:1871–1879.  https://doi.org/10.1111/1365-2664.12702 CrossRefGoogle Scholar
  59. McKinney ML, Lockwood JL (1999) Biotic homogenization: a few winners replacing many losers in the next mass extinction. Trends Ecol Evol 14:450–453CrossRefGoogle Scholar
  60. McNeely JA (2001) The great reshuffling: human dimensions of invasive alien species. IUCN, GlandGoogle Scholar
  61. Medley KA (2010) Niche shifts during the global invasion of the Asian tiger mosquito, Aedes albopictus Skuse (Culicidae), revealed by reciprocal distribution models. Glob Ecol Biogeogr 19:122–133CrossRefGoogle Scholar
  62. Meyerson LA, Mooney HA (2007) Invasive alien species in an era of globalization. Front Ecol Environ 5:199–208CrossRefGoogle Scholar
  63. Millett J, Climo G, Shah NJ (2004) Eradication of common mynah Acridotheres tristis populations in the granitic Seychelles: successes, failures and lessons learned. Adv Vertebr Pest Manag 3:169–183Google Scholar
  64. Møller AP, Díaz M, Flensted-Jensen E et al (2015) Urbanized birds have superior establishment success in novel environments. Oecologia 178:943–950.  https://doi.org/10.1007/s00442-015-3268-8 CrossRefPubMedGoogle Scholar
  65. Mori E, Meini S, Strubbe D et al (2018) Do alien free-ranging birds affect human health? A global. In: Mazza G, Tricarico E (eds) Invasive species and human health. CABI International Edition, New York, pp 120–129CrossRefGoogle Scholar
  66. Muscarella R, Galante PJ, Soley-Guardia M et al (2014) ENMeval: an R package for conducting spatially independent evaluations and estimating optimal model complexity for Maxent ecological niche models. Methods Ecol Evol 5:1198–1205.  https://doi.org/10.1111/2041-210X.12261 CrossRefGoogle Scholar
  67. Nenzén HK, Araújo MB (2011) Choice of threshold alters projections of species range shifts under climate change. Ecol Model 222:3346–3354CrossRefGoogle Scholar
  68. Norris D (2014) Model thresholds are more important than presence location type: understanding the distribution of lowland tapir (Tapirus terrestris) in a continuous Atlantic forest of southeast Brazil. Trop Conserv Sci 7:529–547CrossRefGoogle Scholar
  69. Oduor AMO, Leimu R, Kleunen M (2016) Invasive plant species are locally adapted just as frequently and at least as strongly as native plant species. J Ecol 104:957–968CrossRefGoogle Scholar
  70. Orchan Y, Chiron F, Shwartz A, Kark S (2013) The complex interaction network among multiple invasive bird species in a cavity-nesting community. Biol Invasions 15:429–445.  https://doi.org/10.1007/s10530-012-0298-6 CrossRefGoogle Scholar
  71. Parkes J, Avarua R (2006) Feasibility plan to eradicate common mynas (Acridotheres tristis) from Mangaia Island, Cook Islands. Unpublished Landcare Research Contract Report, Lincoln, New ZealandGoogle Scholar
  72. Peacock DS, Van Rensburg BJ, Robertson MP (2007) The distribution and spread of the invasive alien common myna, Acridotheres tristis L. (Aves: Sturnidae), in southern Africa. S Afr J Sci 103:465–473Google Scholar
  73. Pearson RG, Raxworthy CJ, Nakamura M, Townsend Peterson A (2007) Predicting species distributions from small numbers of occurrence records: a test case using cryptic geckos in Madagascar. J Biogeogr 34:102–117.  https://doi.org/10.1111/j.1365-2699.2006.01594.x CrossRefGoogle Scholar
  74. Peneaux C, Griffin AS (2016) Opportunistic observations of travel distances in common mynas (Acridotheres tristis). Canberra Bird Notes 40:228–234Google Scholar
  75. Peterson MS, Slack WT, Woodley CM, Springs O (2005) The occurrence of non-indigenous Nile tilapia, Oreochromins niloticus (Linnaeus) in coastal Mississippi, USA: ties to aquaculture and thermal effluent. Wetlands 25:112–121.  https://doi.org/10.1672/0277-5212(2005)025[0112:TOONNT]2.0.CO;2 CrossRefGoogle Scholar
  76. Phillips SJ, Anderson RP, Schapire RE (2006) Maximum entropy modeling of species geographic distributions. Ecol Model 190:231–259CrossRefGoogle Scholar
  77. Phillips SJ, Dudík M, Elith J et al (2009) Sample selection bias and presence-only distribution models: implications for background and pseudo-absence data. Ecol Appl 19:181–197CrossRefGoogle Scholar
  78. Phillips SJ, Anderson RP, Dudík M et al (2017) Opening the black box: an open-source release of Maxent. Ecography (Cop) 40:887–893CrossRefGoogle Scholar
  79. Ramadan-jaradi G (2011) Climate variation impact on birds of Lebanon—assessment and identification of main measures to help the birds the adapt to change. Leban Sci J 12:25–32Google Scholar
  80. Rödder D, Solé M, Böhme W (2008) Predicting the potential distributions of two alien invasive Housegeckos (Gekkonidae: Hemidactylus frenatus, Hemidactylus mabouia). North West J Zool 4:236–246Google Scholar
  81. Saavedra S et al (2010) Eradication of invasive mynas from islands. Is it possible. Aliens Invasive Species Bull 29:40–47Google Scholar
  82. Saavedra S, Maraver A, Anadón JD, Tella JL (2015a) A survey of recent introduction events, spread and mitigation efforts of mynas (Acridotheres sp.) in Spain and Portugal. Anim Biodivers Conserv 38:121–128Google Scholar
  83. Saavedra S, Maraver A, Anadón JD, Tella JL (2015b) A survey of recent introduction events, spread and mitigation efforts of mynas (Acridotheres sp.) in Spain and Portugal. Anim Biodivers Conserv 38:121–128Google Scholar
  84. Simberloff D (2011) How common are invasion-induced ecosystem impacts? Biol Invasions 13:1255–1268.  https://doi.org/10.1007/s10530-011-9956-3 CrossRefGoogle Scholar
  85. Sinclair SJ, White MD, Newell GR (2010) How useful are species distribution models for managing biodiverstity under future climates. Ecol Soc 15:8CrossRefGoogle Scholar
  86. Soberón J (2007) Grinnellian and Eltonian niches and geographic distributions of species. Ecol Lett 10:1115–1123CrossRefGoogle Scholar
  87. Sol D, Bartomeus I, Griffin AS (2012) The paradox of invasion in birds: competitive superiority or ecological opportunism? Oecologia 169:553–564.  https://doi.org/10.1007/s00442-011-2203-x CrossRefPubMedGoogle Scholar
  88. Steiner FM, Schlick-Steiner BC, Vanderwal J et al (2008) Combined modelling of distribution and niche in invasion biology: a case study of two invasive Tetramorium ant species. Divers Distrib 14:538–545.  https://doi.org/10.1111/j.1472-4642.2008.00472.x CrossRefGoogle Scholar
  89. Stockwell DRB, Peterson AT (2002) Effects of sample size on accuracy of species distribution models. Ecol Model 148:1–13CrossRefGoogle Scholar
  90. Strubbe D, Matthysen E (2009) Establishment success of invasive ring-necked and monk parakeets in Europe. J Biogeogr 36:2264–2278.  https://doi.org/10.1111/j.1365-2699.2009.02177.x CrossRefGoogle Scholar
  91. Strubbe D, Jackson H, Groombridge J, Matthysen E (2015) Invasion success of a global avian invader is explained by within-taxon niche structure and association with humans in the native range. Divers Distrib 21:675–685.  https://doi.org/10.1111/ddi.12325 CrossRefGoogle Scholar
  92. Syfert MM, Smith MJ, Coomes DA (2013) The effects of sampling bias and model complexity on the predictive performance of MaxEnt species distribution models. PLoS ONE.  https://doi.org/10.1371/journal.pone.0055158 CrossRefPubMedPubMedCentralGoogle Scholar
  93. Taucare-Ríos A, Bizama G, Bustamante RO (2016) Using global and regional species distribution models (SDM) to infer the invasive stage of Latrodectus geometricus (Araneae: Theridiidae) in the Americas. Environ Entomol 45:1379–1385CrossRefGoogle Scholar
  94. Theoharides KA, Dukes JS (2007) Plant invasion across space and time: factors affecting nonindigenous species success during four stage of invasion. New Phytol 176:256–273.  https://doi.org/10.1111/j.1469-8137.2007.02207.x/pdf CrossRefPubMedGoogle Scholar
  95. Thuiller W, Richardson DM, Py Ek P et al (2005) Niche-based modelling as a tool for predicting the risk of alien plant invasions at a global scale. Glob Change Biol 11:2234–2250.  https://doi.org/10.1111/j.1365-2486.2005.01018.x CrossRefGoogle Scholar
  96. VanDerWal J, Shoo LP, Graham C, Williams SE (2009) Selecting pseudo-absence data for presence-only distribution modeling: How far should you stray from what you know? Ecol Model 220:589–594.  https://doi.org/10.1016/j.ecolmodel.2008.11.010 CrossRefGoogle Scholar
  97. Waltari E, Guralnick RP (2009) Ecological niche modelling of montane mammals in the Great Basin, North America: examining past and present connectivity of species across basins and ranges. J Biogeogr 36:148–161CrossRefGoogle Scholar
  98. Ward DF (2007) Modelling the potential geographic distribution of invasive ant species in New Zealand. Biol Invasions 9:723–735.  https://doi.org/10.1007/s10530-006-9072-y CrossRefGoogle Scholar
  99. Ward DF, Harris RJ, Stanley MC (2005) Human-mediated range expansion of argentine ants Linepithema humile (Hymenoptera: Formicidae) in New Zealand. Sociobiology 45:401–407Google Scholar
  100. White JG, Antos MJ, Fitzsimons JA, Palmer GC (2005) Non-uniform bird assemblages in urban environments: the influence of streetscape vegetation. Landsc Urb Plan 71:123–135.  https://doi.org/10.1016/j.landurbplan.2004.02.006 CrossRefGoogle Scholar
  101. Wilson JRU, Dormontt EE, Prentis PJ et al (2009) Something in the way you move: dispersal pathways affect invasion success. Trends Ecol Evol 24:136–144.  https://doi.org/10.1016/j.tree.2008.10.007 CrossRefPubMedGoogle Scholar
  102. Wisz MS, Hijmans RJ, Li J et al (2008) Effects of sample size on the performance of species distribution models. Divers Distrib 14:763–773.  https://doi.org/10.1111/j.1472-4642.2008.00482.x CrossRefGoogle Scholar
  103. Young M, Carr MH (2015) Application of species distribution models to explain and predict the distribution, abundance and assemblage structure of nearshore temperate reef fishes. Divers Distrib 21:1428–1440.  https://doi.org/10.1111/ddi.12378 CrossRefGoogle Scholar
  104. Zeng Y, Low BW, Yeo DCJ (2016) Novel methods to select environmental variables in MaxEnt: a case study using invasive crayfish. Ecol Model 341:5–13.  https://doi.org/10.1016/j.ecolmodel.2016.09.019 CrossRefGoogle Scholar
  105. Zerebecki RA, Sorte CJB (2011) Temperature tolerance and stress proteins as mechanisms of invasive species success. PLoS ONE 6:e14806CrossRefGoogle Scholar

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© Springer Nature Switzerland AG 2019

Authors and Affiliations

  1. 1.School of Zoology, Faculty of Life SciencesTel Aviv UniversityTel AvivIsrael
  2. 2.The Biodiversity Research Group, The School of Biological Sciences, ARC Centre of Excellence for Environmental Decisions (CEED) and NESP Threatened Species Hub, Centre for Biodiversity and Conservation ScienceThe University of QueenslandBrisbaneAustralia

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