Where are the alien species? Predictions of global plant species invasions under current environmental conditions and the human footprint

• Autorzy: Wang Y. , Xu Z.
• Języki publikacji: EN

Abstrakty

EN

Species invasion is a significant concern because of its substantial effect on native ecosystems. A number of species-specific invasion predictions that correspond to environmental conditions are available, but literature predicting global species invasion that corresponds to environmental conditions and human activity is scarce. In this study, the potential geographic ranges of 308 alien plant species were predicted under current environmental conditions and human activities. Environmental conditions were delineated by bioclimatic (mean annual temperature, mean annual precipitation, mean temperature of wettest quarter, and precipitation of driest quarter) and topographic variables (annual solar radiation and topographic wetness index). Human activity was delineated by the human footprint, which is a raster data layer created from nine global data layers that describe human population pressure, land use and infrastructure, and human access. The potential distribution of the target species was predicted using the different types of models. By searching the correlated literature, we identified and excluded the native geographic range of the studied species in the predicted geographic range to obtain the exclusive invasive range. Results demonstrated that the invasion hotspots included the southern part of North America, Southern and Western Europe, the south coast of Asia, coastal regions of Australia and New Zealand, the coast of West Africa, the Ivory Coast of Africa, and the southern part of Brazil. In addition, the land areas of the low- (proper for less than 50 alien species), moderate- (51-100 aliens), and high-risk regions (more than 100 aliens) are 213.23, 18.15, and 2.50 million km2, respectively. All variables (bioclimatic and topographic variables and human footprint) were positively correlated with increasing richness of alien species. The highest correlation coefficient was obtained for the human footprint.

• Wydawca: -
• Czasopismo: Polish Journal of Environmental Studies
• Rocznik: 2016
• Tom: 25
• Numer: 4
• Opis fizyczny: p.1729-1738,fig.,ref.

Twórcy

autor

Wang Y.

• The Meteorological Bureau of Changji, Changji 831100, China

autor

Xu Z.

• College of Resource and Environmental Science, Key Laboratory of Oasis Ecology of the Ministry of Education, Xinjiang University, Urumqi 830046, China

Bibliografia

• 1. BELLARD C., THUILLER W., Leroy B., et al. Will climate change promote future invasion? Global. Change. Biol., 19, 3740, 2013.
• 2. ZHU G., BU W., GAO Y. Potential geographic distribution of brown marmorated stink bug invasion (Halyomorpha halys). PLOS ONE, 7, e31246, 2012.
• 3. PRAKASH S., BALAMURUGAN J., KUMAR T.A. Invasion and richness of reef-inhabiting fishes in the Vellar estuary, southeast coast of India, especially the lionfish Pterois volitans Linnaeus. Curr. Sci., 103, 941, 2012.
• 4. MÜLLEROVÁ J., PERGL J., PYŠEK P. Remote sensing as a tool for monitoring plant invasions: Testing the effects of data resolution and image classification approach on the detection of a model plant species Heracleum mantegazzianum (giant hogweed). Int. J. Appl. Earth Observ. Geoinf., 25, 55, 2013.
• 5. FICETOLA G.F., THUILLER W., MIAUD C. Prediction and validation of the potential global distribution of a problematic alien invasive species - the American bullfrog. Divers. Distrib., 13, 476, 2007.
• 6. ELITH J., KEARNEY M., PHILLIPS S. The art of modelling range-shifting species. Methods. Ecol. Evol., 1, 330, 2010.
• 7. BERTELSMEIER C., GUÉNARD B., COURCHAMP F. Climate Change May Boost the Invasion of the Asian Needle Ant. PLOS ONE, 8, e75438, 2013.
• 8. MEDLEY K.A. Niche shifts during the global invasion of the Asian tiger mosquito, Aedes albopictus Skuse (Culicidae), revealed by reciprocal distribution models. Global. Ecol. Biogeogr., 19, 122, 2010.
• 9. GUO W.Y., LAMBERTINI C., LI X.Z. Invasion of Old World Phragmites australis in the New World: precipitation and temperature patterns combined with human influences redesign the invasive niche. Global Change Biol., 19, 3406, 2013.
• 10. BRADLEY B.A., OPPENHEIMER M., WILCOVE D.S. Climate change and plant invasions: restoration opportunities ahead? Global. Change Biol., 15, 1511, 2009.
• 11. GALLIEN L., DOUZET R., PRATTE S., et al. Invasive species distribution models – how violating the equilibrium assumption can create new insights. Global. Ecol. Biogeogr., 21, 1126, 2012.
• 12. MCCONNACHIE A.J., STRATHIE L.W., MERSIE W., et al. Current and potential geographical distribution of the invasive plant Parthenium hysterophorus (Asteraceae) in eastern and southern Africa. Weed. Res., 51, 71, 2011.
• 13. SEABLOOM E.W., WILLIAMS J.W., SLAYBACK D. Human impacts, plant invasion, and imperilled plant species in California. Ecol. Appl., 16, 1338, 2006.
• 14. PEJCHAR L., MOONEY H.A. Invasive species, ecosystem services and human well-being. Trends. Ecol. Evol., 24, 497, 2009.
• 15. PYŠEK P., JAROŠÍK V., HULME P.E., et al. Disentangling the role of environmental and human pressures on biological invasions across Europe. Proc. Natl. Acad. Sci. USA., 107, 12157, 2010.
• 16. WICHMANN M.C., ALEXANDER M.J., SOONS M.B. Human-mediated dispersal of seeds over long distances. Proc. R. Soc. B., 276, 523, 2009.
• 17. Global Biodiversity Information Facility (http://www.gbif. org/). Accessed 7 Nov 2012 to 12 Mar 2013.
• 18. Global Invasive Species Database (http://www.issg.org/database). Accessed 7 Nov 2012 to 12 Oct 2013.
• 19. LOWE S., BROWNE M., BOUDJELAS S., et al. 100 of the World’s Worst Invasive Alien Species A selection from the Global Invasive Species Database. The Invasive Species Specialist Group (ISSG) a specialist group of the Species Survival Commission (SSC) of the World Conservation Union (IUCN), Auckland, 2000.
• 20. HIJMANS R.J., CAMERON S.E., PARRA J.L., et al. Very high resolution interpolated climate surfaces for global land areas. I. J. Climatol., 25, 1965, 2005.
• 21. BEVEN K., KIRKBY M. A physically based, variable contributing area model of basin hydrology. Hydrol. Sci. J., 24, 43, 1979.
• 22. XU Z., FENG Z., YANG J., et al. Nowhere to Invade: Rumex crispus and Typha latifolia Projected to Disappear under Future Climate Scenarios. PLOS ONE 8, e70728, 2013.
• 23. GRABS T., SEIBERT J., BISHOP K., et al. Modeling spatial patterns of saturated areas: a comparison of the topographic wetness index and a dynamic distributed model. J. Hydrol., 373, 15, 2000.
• 24. PEI T., QIN CZ., ZHU A.X., et al. Mapping soil organic matter using the topographic wetness index: a comparative study based on different flow-direction algorithms and kriging methods. Ecol. Indic., 10, 610, 2010.
• 25. KUMAR L., SKIDMORE A.K., KNOWLES E. Modelling topographic variation in solar radiation in a GIS environment. Int. J. Geogr. Inf. Sci., 11, 475, 1997.
• 26. SANDERSON E.W., JAITEH M., LEVY M.A., et al. The Human Footprint and the Last of the Wild: The human footprint is a global map of human influence on the land surface, which suggests that human beings are stewards of nature, whether we like it or not. BioScience, 5, 891, 2002.
• 27. GUO Q., LIU Y. ModEco: an integrated software package for ecological niche modeling. Ecography, 33, 637, 2010.
• 28. BUSBY J.R. A biogeoclimatic analysis of nothofagus cunninghamii (hook.) oerst. In southeastern australia, Aust. J. Ecol., 11, 1, 1986.
• 29. CARPENTER G., GILLISON A.N., WINTER J. Domain – a flexible modeling procedure for mapping potential distributions of plants and animals. Biodivers. Conserv., 2, 667, 1993.
• 30. GUISAN A., EDWARDS T.C., HASTIE T. Generalized linear and generalized additive models in studies of species distributions: Setting the scene. Ecol. Model., 157, 89, 2002.
• 31. HASTIE T., TIBSHIRANI R., FRIEDMAN J. The elements of statistical learning: Data mining, inference and prediction. New York, Springer, 2001.
• 32. GUO Q., LIU Y. ModEco: an integrated software package for ecological niche modeling. Ecography, 33, 637, 2010.
• 33. GUO Q.H., KELLY M., GRAHAM C.H. Support vector machines for predicting distribution of sudden oak death in California. Ecol. Model., 182, 75, 2005.
• 34. DE'ATH G., FABRICIUS K. Classification and regression trees: A powerful yet simple technique for ecological data analysis. Ecology, 81, 3178, 2000.
• 35. PAWLAK Z. Rough Sets: Theoretical Aspects of Reasoning About Data. Dordrecht, Kluwer Academic Publishing, 1991.
• 36. PHILLIPS S.J., ANDERSON R.P., Schapire R.E. MaxEnt entropy modeling of species geographic distribution. Ecol. Model., 190, 231, 2006.
• 37. LIU C., WHITE M., NEWELL G. Measuring and comparing the accuracy of species distribution models with presence–absence data. Ecography, 34, 232, 2011.
• 38. ALLOUCHE O., TSOAR A., KADMON R. Assessing the accuracy of species distribution models: prevalence, kappa and the true skill statistic (TSS). J. Appl. Ecol., 43, 1223, 2006.
• 39. GENOVESI P. Eradications of invasive alien species in Europe: a review. Issues in Bioinvasion Science. Berlin, Springer Netherlands, 2005.
• 40. McGeoch M.A., Butchart S.H.M., Spear D., et al. Global indicators of biological invasion: species numbers, biodiversity impact and policy responses. Divers. Distrib., 16, 95, 2010.
• 41. Thuiller W., Richardson D.M., Pyšek P., et al. Niche-based modelling as a tool for predicting the risk of alien plant invasions at a global scale. Global. Change. Biol., 11, 2234, 2005.
• 42. Bellard C., Leclerc C., Leroy B., et al. Vulnerability of biodiversity hotspots to global change. Global. Ecol. Biogeogr., 23, 1376, 2014.
• 43. Tingley R., Vallinoto M., Sequeira F., et al. Realized niche shift during a global biological invasion. P. Natl. Acad. Sci. USA., 111, 10233, 2014.
• 44. Richardson D.M., Rejmánek M. Trees and shrubs as invasive alien species – a global review. Divers. Distrib., 17, 788, 2011.
• 45. Miller A.W. Shipping and invasive species in the Arctic. In Marine invasive species in the Arctic (Eds, Fernandez L., Kaiser B., Vestergaard N.). Copenhagen, Norden, 2014.
• 46. DORMANN C.F. Promising the future? Global change projections of species distributions. Basic. Appl. Ecol., 8, 387, 2007.
• 47. WESTPHAL M.I., BROWNE M., MACKINNON K., et al. The link between international trade and the global distribution of invasive alien species. Biol.Invasions., 10, 391, 2008.
• 48. LENZEN M., MORAN D., KANEMOTO K., et al. International trade drives biodiversity threats in developing nations. Nature, 486, 109, 2012.
• 49. KEARNEY M., PORTER W. Mechanistic niche modelling: combining physiological and spatial data to predict species’ ranges. Ecol. Lett., 12, 334, 2009.
• 50. PRESTON K.L., ROTENBERRY J.T., REDAK R.A., et al. Habitat shifts of endangered species under altered climate conditions: importance of biotic interactions. Global. Change. Biol., 14, 2501, 2008.
• 51. WILSON J.R., RICHARDSON D.M., ROUGET M., et al. Residence time and potential range: crucial considerations in modelling plant invasions. Divers. Distrib., 13, 11, 2007.
• 52. PRINGLE E.G., AKCAY E., RAAB T.K., et al. Water Stress Strengthens Mutualism Among Ants, Trees, and Scale Insects. PLOS Biol., 11, e1001705, 2013.
• 53. RAMASWAMI G., SUKUMAR R. Long-Term Environmental Correlates of Invasion by Lantana camara (Verbenaceae) in a Seasonally Dry Tropical Forest. PLOS ONE, 8, e76995, 2013.
• 54. POTTIER J., DUBUIS A., PELLISSIER L., et al. The accuracy of plant assemblage prediction from species distribution models varies along environmental gradients. Global. Ecol. Biogeogr., 22, 52, 2013.
• 55. LAVERGNE S., MOUQUET N., THUILLER W., et al. Biodiversity and climate change: integrating evolutionary and ecological responses of species and communities. Ann. Rev. Ecol. Evol. Syst., 41, 321, 2010.
• 56. SAVOLAINEN O., PYHÄJÄRVI T., KNÜRR T. Gene flow and local adaptation in trees. Ann. Rev. Ecol. Evol. Syst., 38, 595, 2007.
• 57. SKELLY D.K., FREIDENBURG L.K. Evolutionary responses to climate change. eLS, 2010.
• 58. VISSER M.E. Keeping up with a warming world; assessing the rate of adaptation to climate change. Proc. R. Soc. B., 275, 649, 2008.

Identyfikatory

DOI

10.15244/pjoes/62094