Biological Invasions

, Volume 15, Issue 5, pp 961–975 | Cite as

The grass may not always be greener: projected reductions in climatic suitability for exotic grasses under future climates in Australia

  • R. V. Gallagher
  • D. Englert Duursma
  • J. O’Donnell
  • P. D. Wilson
  • P. O. Downey
  • L. Hughes
  • M. R. Leishman
Original Paper

Abstract

Climate change presents a new challenge for the management of invasive exotic species that threaten both biodiversity and agricultural productivity. The invasion of exotic perennial grasses throughout the globe is particularly problematic given their impacts on a broad range of native plant communities and livelihoods. As the climate continues to change, pre-emptive long-term management strategies for exotic grasses will become increasingly important. Using species distribution modelling we investigated potential changes to the location of climatically suitable habitat for some exotic perennial grass species currently in Australia, under a range of future climate scenarios for the decade centred around 2050. We focus on eleven species shortlisted or declared as the Weeds of National Significance or Alert List species in Australia, which have also become successful invaders in other parts of the world. Our results indicate that the extent of climatically suitable habitat available for all of the exotic grasses modelled is projected to decrease under climate scenarios for 2050. This reduction is most severe for the three species of Needle Grass (genus Nassella) that currently have infestations in the south-east of the continent. Combined with information on other aspects of establishment risk (e.g. demographic rates, human-use, propagule pressure), predictions of reduced climatic suitability provide justification for re-assessing which weeds are prioritised for intensive management as the climate changes.

Keywords

Alert List Climate change Exotic grasses Maxent Species distribution models Weeds of national significance 

Supplementary material

10530_2012_342_MOESM1_ESM.docx (2 mb)
Supplementary material 1 (DOCX 2023 kb)
10530_2012_342_MOESM2_ESM.docx (4.4 mb)
Supplementary material 2 (DOCX 4520 kb)

References

  1. Acevedo P, Jiménez-Valverde A, Lobo JM, et al. (2012) Delimiting the geographical background in species distribution modeling. J Biogeog Online Early 39:1383–1390. doi:10.1111/j.1365-2699.2012.02713.x Google Scholar
  2. Anderson RP, Gómez-Laverde M, Peterson AT (2002) Geographical distributions of spiny pocket mice in South America: insights from predictive models. Glob Ecol Biogeogr 11:131–141. doi:10.1046/j.1466-822X.2002.00275.x CrossRefGoogle Scholar
  3. Barnard C (1964) Grasses and Grasslands. Macmillan & Company Ltd, MelbourneGoogle Scholar
  4. Beaumont LJ, Gallagher RV, Downey PO et al (2009a) Modelling the impact of Hieracium spp. on protected areas in Australia under future climates. Ecography 32:757–764. doi:10.1111/j.1600-0587.2009.05705.x CrossRefGoogle Scholar
  5. Beaumont LJ, Gallagher RV, Thuiller W et al (2009b) Different climatic envelopes among invasive populations may lead to underestimations of current and future biological invasions. Divers Distrib 15:409–420. doi:10.1111/j.1472-4642.2008.00547.x CrossRefGoogle Scholar
  6. Bourdôt GW, Lamoureaux SL, Watt MS et al. (2010) The potential global distribution of the invasive weed Nassella neesiana under current and future climates. Biol Invasions—Online First doi:10.1007/s10530-010-9905-6
  7. Bradley BA, Oppenheimer M, Wilcove DS (2009) Climate change and plant invasions: restoration opportunities ahead? Glob Chang Biol 15:1511–1521. doi:10.1111/j.1365-2486.2008.01824.x CrossRefGoogle Scholar
  8. Broenniamm O, Guisan A (2008) Predicting current and future biological invasions: both native and invaded ranges matter. Biol Lett 2008(4):585–589. doi:10.1098/rsbl.2008.0254 CrossRefGoogle Scholar
  9. Brooks KJ, Setterfield SA, Douglas MM (2010) Exotic grass invasions: applying a conceptual framework to the dynamics of degradation and restoration in Australia’s tropical savannas. Restor Ecol 18:188–197. doi:10.1071/WF9980227 CrossRefGoogle Scholar
  10. Butler BDW, Fairfax RJ (2003) Buffel grass and fire in a gidgee and brigalow woodland: a case study from central Queensland. Ecol Manag Restor 4:120–125. doi:10.1046/j.1442-8903.2003.00146.x CrossRefGoogle Scholar
  11. Chen IC, Hill JK, Ohlemüller R et al (2011) Rapid range shifts of species associated with high levels of climate warming. Science 333:1024–1026. doi:10.1126/science.1206432 PubMedCrossRefGoogle Scholar
  12. Clarke PJ, Latz PK, Albrecht DE (2005) Long-term changes in semi-arid vegetation: invasion of an exotic perennial grass has larger effects than rainfall variability. J Veg Sci 16:237–248. doi:10.1111/j.1654-1103.2005.tb02361.x CrossRefGoogle Scholar
  13. Coutts-Smith AJ, Downey PO (2006) The impact of weeds on threatened biodiversity in New South Wales. Technical series no. 11. CRC for Australian Weed Management, AdelaideGoogle Scholar
  14. CSIRO (Commonwealth Scientific and Industrial Research Organisation) (2011) Climate Change: Science and Solutions for Australia. In: Cleugh H, Stafford Smith M, Battaglia M, Graham P (eds). CSIRO Publishing. Melbourne. AustraliaGoogle Scholar
  15. D’Antonio CM, Vitousek PM (1992) Biological invasions by exotic grasses, the grass/fire cycle, and global change. Ann Rev Ecol Syst 23:63–87. doi:10.1146/annurev.es.23.110192.000431 Google Scholar
  16. Daehler CC, Strong DR (1996) Status, prediction and prevention of introduced cordgrass Spartina spp. invasions in Pacific estuaries, USA. Biol Conserv 78:51–58. doi:10.1016/0006-3207(96)00017-1 CrossRefGoogle Scholar
  17. DeWet JMJ (1981) Grasses and the culture history of man. Ann Mo Bot Gard 68:87–104CrossRefGoogle Scholar
  18. Downey PO, Johnson SB, Virtue JG et al (2010a) Assessing risk across the spectrum of weed management. CAB reviews: perspectives in agriculture. Veterinary Sci Nutr Nat Resour 5:038. doi:10.1079/PAVSNNR20100038 Google Scholar
  19. Downey PO, Scanlon TJ, Hosking JR (2010b) Prioritising alien plant species based on their ability to impact on biodiversity: a case study from New South Wales. Plant Prot Q 25:111–126Google Scholar
  20. Downey PO, Williams MC, Whiffen LK et al (2010c) Managing alien plants for biodiversity outcomes—the need for triage. Invas Plant Sci Manag 3:1–11. doi:10.1614/IPSM-09-042.1 CrossRefGoogle Scholar
  21. Elith J, Graham CH, Anderson RP et al (2006) Novel methods to improve predictions of species’ distributions from occurrence data. Ecography 29:129–151. doi:10.1111/j.2006.0906-7590.04596.x CrossRefGoogle Scholar
  22. Elith J, Phillips SJ, Hastie T et al (2010a) A statistical explanation of MaxEnt for ecologists. Divers Distrib 17:43–57. doi:10.1111/j.1472-4642.2010.00725.x CrossRefGoogle Scholar
  23. Elith J, Kearney M, Phillips SJ (2010b) The art of modelling range-shifting species. Methods Ecol Evol 1:330–342. doi:10.1111/j.2041-210X.2010.00036.x CrossRefGoogle Scholar
  24. Fairfax RJ, Fensham RJ (2000) The effect of exotic pasture development on floristic diversity in central Queensland, Australia. Biol Conserv 94:11–21. doi:10.1016/S0006-3207(99)00169-X CrossRefGoogle Scholar
  25. Fielding AH, Bell JF (1997) A review of methods for the assessment of prediction errors in conservation presence/absence models. Environ Conserv 24:38–49CrossRefGoogle Scholar
  26. Fitzpatrick MC, Weltzin JF, Sanders NJ et al (2007) The biogeography of prediction error: why does the introduced range of the fire ant over-predict its native range? Glob Ecol Biogeogr 16:24–33. doi:10.1111/j.1466-8238.2006.00258.x CrossRefGoogle Scholar
  27. Friedlingstein P, Houghton RA, Marland G et al (2010) Update on CO2 emissions. Nat Geosci 3:811–812. doi:10.1038/ngeo1022 CrossRefGoogle Scholar
  28. Gallagher RV, Hughes L, Leishman MR et al (2010) Predicted impact of exotic vines on an endangered ecological community under future climate change. Biol Invas 12:4049–4063. doi:10.1007/s10530-010-9814-8 CrossRefGoogle Scholar
  29. Graham CH, Hijmans RJ (2006) A comparison of methods for mapping species ranges and species richness. Glob Ecol Biogeogr 15:578–587. doi:10.1111/j.1466-8238.2006.00257.x CrossRefGoogle Scholar
  30. Grice AC (2003) Weeds of Significance to the Grazing Industries of Australia. Meat and Livestock Australia Ltd, SydneyGoogle Scholar
  31. Grice AC (2004) Perennial grass weeds in Australia: impacts, conflicts of interest and management issues. Plant Prot Q 19:42–47Google Scholar
  32. Grice AC (2006) The impacts of invasive plant species on the biodiversity of Australian rangelands. Rangeland J 28:27–35. doi:10.1071/RJ06014 CrossRefGoogle Scholar
  33. Hellman J, Byers JE, Bierwagen BG et al (2008) Five potential consequences of climate change for invasive species. Conserv Biol 22:534–543. doi:10.1111/j.1523-1739.2008.00951.x CrossRefGoogle Scholar
  34. Heywood VH (1989) Patterns, extents and modes of invasions by terrestrial plants. In: Drake JA, Mooney HA, di Castri F, Groves RH, Kruger FJ, Rejmanek M, Williamson M (eds) Biological Invasions: A Global Perspective. Wiley, New York, pp 31–60Google Scholar
  35. Hijmans RJ, Cameron SE, Parra JL et al (2005) Very high resolution interpolated climate surfaces for global land areas. Int J Climatol 25:1965–1978. doi:10.1002/joc.1276 CrossRefGoogle Scholar
  36. Hilbert DW, Hughes L, Johnson J et al (2007) Biodiversity conservation research in a changing climate - Workshop report: research needs and information gaps for the implementation of the key objectives of the National Biodiversity and Climate Change Action Plan. Department of the Environment and Water Resources, CanberraGoogle Scholar
  37. Houston WA, Duivenvoorden LJ (2002) Replacement of littoral native vegetation with the ponded pasture grass Hymenachne amplexicaulis: effects on plant, macroinvertebrate and fish biodiversity of backwaters in the Fitzroy River, Central Queensland, Australia. Mar Freshw Res 53:1235–1244. doi:10.1071/MF01042 CrossRefGoogle Scholar
  38. IPCC (2007) Climate Change 2007: The physical science basis. In: Solomon S, Qin D, Manning M, Chen Z, Marquis M, Averyt KB, Tignor M, Miller HL (eds) Contribution of Working Group I to the Fourth Assessment Report of the Intergovernmental Panel on Climate Change. Cambridge University Press, UKGoogle Scholar
  39. IPCC (2012) Managing the Risks of Extreme Events and Disasters to Advance Climate Change Adaptation. In: Field CB, Barros V, Stocker TF, Qin D, Dokken DJ, Ebi KL, Mastrandrea MD, Mach KJ, Plattner GK, Allen SK, Tignor M, Midgley PM (eds) A Special Report of Working Groups I and II of the Intergovernmental Panel on Climate Change Cambridge University Press, Cambridge, UK, and New York, USAGoogle Scholar
  40. Kearney M, Simpson SJ, Raubenheimer D et al (2010) Modelling the ecological niche from functional traits. Philos T Roy Soc B 365:3469–3483. doi:10.1098/rstb.2010.0034 CrossRefGoogle Scholar
  41. Keir AF, Vogler WD (2006) A review of current knowledge of the weedy species Themeda quadrivalvis (grader grass). Trop Grasslands 40:193–201Google Scholar
  42. Kleinbauer I, Dullinger S, Peterseil J et al (2010) Climate change might drive the invasive tree Robinia pseudacacia into nature reserves and endangered habitats. Biol Conserv 143:382–390. doi:10.1016/j.biocon.2009.10.024 CrossRefGoogle Scholar
  43. Klink CA, Machado RB (2005) Conservation of the Brazilian cerrado. Conserv Biol 19:707–713. doi:10.1111/j.1523-1739.2005.00702.x CrossRefGoogle Scholar
  44. Kottek MJ, Grieser C, Beck C et al (2006) World Map of the Köppen-Geiger climate classification updated. Meteorol Z 15:259–263. doi:10.1127/0941-2948/2006/0130 CrossRefGoogle Scholar
  45. Lemke D, Hulme PE, Brown JA et al (2011) Distribution modelling of Japanese honeysuckle (Lonicera japonica) invasion in the Cumberland Plateau and Mountain Region, USA. For Ecol Manag 262:139–149. doi:10.1016/j.foreco.2011.03.014 CrossRefGoogle Scholar
  46. Lenz TI, Moyle Croft JL, Facelli JM (2003) Direct and indirect effects of exotic annual grasses on species composition of a South Australian grassland. Aust Ecol 28:23–32. doi:10.1046/j.1442-9993.2003.01238.x CrossRefGoogle Scholar
  47. Lonsdale WM (1994) Inviting trouble: introduced pasture species in northern Australia. Aust J Ecol 19:345–354. doi:10.1111/j.1442-9993.1994.tb00498.x CrossRefGoogle Scholar
  48. Lunt ID (1990) The soil seed bank of a long-grazed Themeda triandra grassland in Victoria. Proc R Soc Vic 102:53–57Google Scholar
  49. Marshall NA, Friedel N, van Klinken RD et al (2010) Considering the social dimension of invasive species: the case of buffel grass. Environ Sci Policy 14:327–338. doi:10.1016/j.envsci.2010.10.005 CrossRefGoogle Scholar
  50. Martin TG, Campbell S, Grounds S (2006) Weeds of Australian rangelands. Rangeland J 28:3–26. doi:10.1071/RJ06017 CrossRefGoogle Scholar
  51. Morin X, Lechowicz MJ (2008) Contemporary perspectives on the niche that can improve models of species range shifts under climate change. Biol Lett 4:573–576. doi:10.1098/rsbl.2008.0181 PubMedCrossRefGoogle Scholar
  52. Mott JJ (1986) Planned invasions of Australian tropical savannas. In: Groves RH, Burdon JJ (eds) Ecology of Biological Invasions: an Australian perspective. Australian Academy of Science, Canberra, pp 89–96Google Scholar
  53. Mukherjee A, Christman MC, Overholt WA et al (2011) Prioritizing areas in the native range of Hygrophila for surveys to collect biological control agents. Biol Control 56:254–262. doi:10.1016/j.biocontrol.2010.11.006 CrossRefGoogle Scholar
  54. Nakicenovic N, Swart R (2000) Special Report on Emissions Scenarios. Cambridge University Press, CambridgeGoogle Scholar
  55. O’Donnell J, Gallagher RV, Wilson PD et al (2011) Invasion hotspots for non-native plants in Australia under current and future climates. Glob Chang Biol (Early View). doi:10.1111/j.1365-2486.2011.02537.x Google Scholar
  56. Parker-Allie F, Musil CF, Thuiller W (2009) Effects of climate warming on the distributions of invasive Eurasian annual grasses: a South African perspective. Clim Chang 94:87–103. doi:10.1007/s10584-009-9549-7 CrossRefGoogle Scholar
  57. Pattison RR, Mack RN (2008) Potential distribution of the invasive tree Triadica sebifera (Euphorbiaceae) in the United States: evaluating CLIMEX predictions with field trials. Glob Chang Biol 14:813–826. doi:10.1111/j.1365-2486.2007.01528.x CrossRefGoogle Scholar
  58. Perkins SE, Pitman AJ, Holbrook NJ et al (2007) Evaluation of the AR4 climate models’ simulated daily maximum temperature, minimum temperature, and precipitation over Australia using probability density functions. J Clim 20:4356–4376. doi:10.1175/JCLI4253.1 CrossRefGoogle Scholar
  59. Phillips SJ, Anderson RP, Schapire RE (2006) Maximum entropy modeling of species geographic distributions. Ecol Model 190:231–259. doi:10.1016/j.ecolmodel.2005.03.026 CrossRefGoogle Scholar
  60. Prober SM, Thiele KR (2005) Restoring Australia’s temperate grasslands and grassy woodlands: integrating function and diversity. Ecol Manag Restor 6:16–27. doi:10.1111/j.1442-8903.2005.00215.x CrossRefGoogle Scholar
  61. Richardson DM, Pysek P, Rejmanek M et al (2000) Naturalization and invasion of alien plants: concepts and definitions. Divers Distrib 6:93–107. doi:10.1046/j.1472-4642.2000.00083.x CrossRefGoogle Scholar
  62. Robertson MP, Peter CI, Villet MH et al (2003) Comparing models for predicting species’ potential distributions: a case study using correlative and mechanistic predictive modelling techniques. Ecol Model 164:153–167CrossRefGoogle Scholar
  63. Rossiter NA, Setterfield SA, Douglas MM et al (2003) Testing the grass fire cycle: alien grass invasion in the tropical savannas of northern Australia. Divers Distrib 9:169–176. doi:10.1046/j.1472-4642.2003.00020.x CrossRefGoogle Scholar
  64. Roura-Pascual N, Suarez AV, Gómez C et al (2004) Geographical potential of Argentine ants (Linepithema humile Mayr) in the face of global climate change. Proc R Soc B-Biol 271:2527–2534. doi:10.1098/rspb.2004.2898 CrossRefGoogle Scholar
  65. Scott JK, Batchelor K, Ota N et al (2008) Modelling climate change impacts on sleeper and alert weeds: final report. CSIRO, Western AustraliaGoogle Scholar
  66. Setterfield SA, Douglas MM, Hutley LB, Welch MA (2005) Effects of canopy cover and ground disturbance on establishment of an invasive grass in an Australia savanna. Biotropica 37:25–31. doi:10.1111/j.1744-7429.2005.03034.x CrossRefGoogle Scholar
  67. Setterfield SA, Rossiter Rachor NA, Hutley LB, Douglas MM, Williams RJ (2010) Turning up the heat: the impacts of Andropogon gayanus (gamba grass) invasion on fire behaviour in northern Australian savannas. Divers Distrib 16:854–861. doi:10.1111/j.1472-4642.2010.00688.x CrossRefGoogle Scholar
  68. Sinden R, Jones R, Hester S et al (2004) The economic impact of weeds in Australia. Report for the CRC for Australian Weed ManagementGoogle Scholar
  69. Stohlgren TJ, Ma P, Kumar S et al (2010) Ensemble habitat mapping of invasive plant species. Risk Anal 30:224–235. doi:10.1111/j.1539-6924.2009.01343.x PubMedCrossRefGoogle Scholar
  70. Suppiah R, Hennessy K, Whetton P et al (2007) Australian climate change projections derived from simulations performed for the IPCC 4th Assessment Report. Aust Meteorol Mag 56:131–152Google Scholar
  71. Swets JA (1988) Measuring the accuracy of diagnostic systems. Science 240:1285–1292PubMedCrossRefGoogle Scholar
  72. Thorp JR, Lynch R (2000) The Determination of Weeds of National Significance. National Weeds Strategy Executive Committee, LauncestonGoogle Scholar
  73. Thuiller W (2003) BIOMOD—optimizing predictions of species distributions and projecting potential future shifts under global change. Glob Chang Biol 9:1353–1362. doi:10.1046/j.1365-2486.2003.00666.x CrossRefGoogle Scholar
  74. Thuiller W, Richardson DM, Pyšek P et al (2005) Niche based modelling as a tool for predicting the risk of alien plant invasions at a global scale. Glob Chang Biol 11:2234–2250. doi:10.1111/j.1365-2486.2005.001018.x CrossRefGoogle Scholar
  75. Trethowan PD, Robertson MP, McConnachie AJ (2011) Ecological niche modelling of an invasive alien plant and its potential biological control agents. S Afr J Bot 77:137–146. doi:10.1016/j.sajb.2010.07.007 CrossRefGoogle Scholar
  76. VanDerWal J, Shoo LP, Grahame C et al (2009) Selecting pseudo-absence data for presence-only distribution modeling: how far should you stray from what you know? Ecol Model 220:589–594. doi:10.1016/j.ecolmodel.2008.11.010 CrossRefGoogle Scholar
  77. Vaze J, Teng J, Chiew FHS (2011) Assessment of GCM simulations of annual and seasonal rainfall and daily rainfall distribution across south-east. Hydrol Process 25:1486–1497. doi:10.1002/hyp.7916 CrossRefGoogle Scholar
  78. Watt MS, Kriticos DJ, Lamoureaux SL et al (2011) Climate change and the potential global distribution of serrated tussock (Nassella trichotoma). Weed Sci 59:538–545. doi:10.1614/WS-D-11-00032.1 CrossRefGoogle Scholar
  79. Webber BL, Yates CJ, Le Maitre DC et al (2011) Modelling horses for novel climate courses: insights from projecting potential distributions of native and alien Australian acacias with correlative and mechanistic models. Divers Distrib 17:978–1000. doi:10.1111/j.1472-4642.2011.00811.x CrossRefGoogle Scholar

Copyright information

© Springer Science+Business Media Dordrecht 2012

Authors and Affiliations

  • R. V. Gallagher
    • 1
  • D. Englert Duursma
    • 1
  • J. O’Donnell
    • 1
  • P. D. Wilson
    • 1
  • P. O. Downey
    • 2
  • L. Hughes
    • 1
  • M. R. Leishman
    • 1
  1. 1.Department of Biological SciencesMacquarie UniversityNorth RydeAustralia
  2. 2.Institute for Applied EcologyUniversity of CanberraBruceAustralia

Personalised recommendations