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Threats of future climate change and land use to vulnerable tree species native to Southern California

Published online by Cambridge University Press:  20 August 2014

ERIN C. RIORDAN ,
THOMAS W. GILLESPIE ,
LINCOLN PITCHER ,
STEPHANIE S. PINCETL ,
G. DARREL JENERETTE  and
DIANE E. PATAKI
ERIN C. RIORDAN
Affiliation:
Department of Ecology and Evolutionary Biology, University of California Los Angeles, Los Angeles, CA 90095, USA
THOMAS W. GILLESPIE*
Affiliation:
Department of Geography, University of California Los Angeles, Los Angeles, CA 90095, USA
LINCOLN PITCHER
Affiliation:
Department of Geography, University of California Los Angeles, Los Angeles, CA 90095, USA
STEPHANIE S. PINCETL
Affiliation:
Institute of the Environment and Sustainability, University of California Los Angeles, Los Angeles, CA 90095, USA
G. DARREL JENERETTE
Affiliation:
Department of Botany and Plant Sciences, University of California Riverside, Riverside, CA 92521, USA
DIANE E. PATAKI
Affiliation:
Department of Biology, The University of Utah, Salt Lake City, UT 84112, USA
*
*Correspondence: Dr Thomas Gillespie Tel: +1 310 968 2360 e-mail: [email protected]
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Summary

Climate and land-use changes are expected to drive high rates of environmental change and biodiversity loss in Mediterranean ecosystems this century. This paper compares the relative future impacts of land use and climate change on two vulnerable tree species native to Southern California (Juglans californica and Quercus engelmannii) using species distribution models. Under the Intergovernmental Panel for Climate Change's A1B future scenario, high levels of both projected land use and climate change could drive considerable habitat losses on these two already heavily-impacted tree species. Under scenarios of no dispersal, projected climate change poses a greater habitat loss threat relative to projected land use for both species. Assuming unlimited dispersal, climate-driven habitat gains could offset some of the losses due to both drivers, especially in J. californica which could experience net habitat gains under combined impacts of both climate change and land use. Quercus engelmannii, in contrast, could experience net habitat losses under combined impacts, even under best-case unlimited dispersal scenarios. Similarly, projected losses and gains in protected habitat are highly sensitive to dispersal scenario, with anywhere from > 60% loss in protected habitat (no dispersal) to > 170% gain in protected habitat (unlimited dispersal). The findings underscore the importance of dispersal in moderating future habitat loss for vulnerable species.

Keywords

climate changeJuglans californicaland-use changeMediterranean ecosystemsprotected areasQuercus engelmanniispecies distribution modelling
Type
Papers
Information
Environmental Conservation , Volume 42 , Issue 2 , June 2015 , pp. 127 - 138
Copyright
Copyright © Foundation for Environmental Conservation 2014 

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References

Ackerly, D.D., Loarie, S.R., Cornwell, W.K., Wiess, S.B., Hamilton, H., Branciforte, R. & Kraft, N.J.B. (2010) The geography of climate change: implications for conservation. Diversity and Distribution 12: 476–487.CrossRefGoogle Scholar
Anderson, E.N. (2002) Some observations on the California black walnut (Juglans californica). Fremonia 30: 12–29.Google Scholar
Araújo, M.B. & Guisan, A. (2006) Five (or so) challenges for species distribution modeling. Journal of Biogeography 33: 1677–1688.Google Scholar
Araújo, M.B. & New, M. (2007) Ensemble forecasting of species distributions. Trends in Ecology and Evolution 22: 42–47.Google Scholar
Barbet-Massin, M., Thuiller, W. & Jiguet, F. (2012) The fate of European breeding birds under climate, land-use and dispersal scenarios. Global Change Biology 18: 881–890.Google Scholar
CA-DOF (2011) Historical census populations of counties and incorporated cities in California, 1850–2010. [www document]. URL http://www.dof.ca.gov/research/demographic/reports/estimates/e-5/2011-20/view.php Google Scholar
CCAFS (2011) GMC downscaled GCM data portal. [www document]. URL http://ccafs-climate.org Google Scholar
CCH (2011) Consortium of California Herbaria. [www document]. URL http://ucjeps.berkeley.edu/consortium/ Google Scholar
CNPS Rare Plant Program (2014) Inventory of Rare and Endangered Plants (online edition, v8–02). California Native Plant Society, Sacramento, CA. [www document]. URL http://www.rareplants.cnps.org Google Scholar
CPAD (2012) California's Protected Area Database version 1.8. [www document]. URL http://www.calands.org/ Google Scholar
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.CrossRefGoogle Scholar
Elith, J., Graham, C.H., Anderson, R.P., Dudik, M., Ferrier, S., Guisan, A., Hijmans, R. J., Huettmann, F., Leathwick, J.R, Lehmann, A., Li, J., Lohmann, L.G., Loiselle, B.A., Manion, G., Moritz, C., Nakamura, M., Nakazawa, Y., Overton, J.M., Peterson, A.T., Phillips, S.J., Richardson, K., Scachetti-Pereira, R., Schapire, R. E., Soberon, J., Williams, S., Wisz, M.S. & Zimmermann, N.E. (2006) Novel methods improve prediction of species’ distributions from occurrence data. Ecography 29: 129–151.Google Scholar
Forister, M.L., McCall, A.C., Sanders, N.J., Fordyce, J.A., Thorne, J.H., O’Brien, J., Waetjen, D.P. & Shapiro, A.M. (2010) Compounded effects of climate change and habitat alteration shift patterns of butterfly diversity. Proceedings of the National Academy of Sciences USA 107: 2088–2092.Google Scholar
Garcia, A., Ortega-Huerta, M. & Martinez-Meyer, E. (2013) Potential distributional changes and conservation priorities of endemic amphibians in western Mexico as a result of climate change. Environmental Conservation 41: 1–12.Google Scholar
GBIF (2011) Global Biodiversity Informatics Facility Data Portal [www document]. URL http://www.gbif.org/ Google Scholar
Graham, C.H., Ferrier, S., Huettman, F., Moritz, C. & Peterson, A.T. (2004) New developments in museum-based informatics and application in biodiversity analysis. Trends in Ecology and Evolution 19: 497–503.Google Scholar
Guisan, A. & Thuiller, W. (2005) Predicting species distribution: offering more than simple habitat models. Ecology Letters 8: 993–1009.Google Scholar
Heikkinen, R.K., Luoto, M. & Araújo, M.B. (2006) Methods and uncertainties in bioclimatic envelope modelling under climate change. Progress in Physical Geography 30: 751–777.CrossRefGoogle Scholar
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. International Journal of Climate 25: 1965–1978.Google Scholar
IUCN (2011) IUCN Red List of Threatened Species Version 2011.1 [www document]. URL http://www.iucnredlist.org Google Scholar
Jongsomjit, D., Stralberg, D., Gardali, T., Salas, L. & Wiens, J. (2013) Between a rock and a hard place: the impacts of climate change and housing development on breeding birds in California. Landscape Ecology 28: 187–200.Google Scholar
Keeley, J.E. (1990) Demographic structure of California black walnut (Juglans californica; Juglandaceae) woodlands in southern California. Madroño 37: 237–248.Google Scholar
Klausmeyer, K.R. & Shaw, M.R. (2009) Climate change, habitat loss, protected area and the climate adaption potential of species in Mediterranean ecosystems worldwide. PLoS ONE 4: e6392.Google Scholar
Kueppers, L.M., Snyder, M.A., Sloan, L.C., Zavaleta, E.S. & Fulfrost, B. (2005) Modeled regional climate change and California endemic oak ranges. Proceedings of the National Academy of Sciences USA 102: 16281–16286.Google Scholar
Levin, D.A., Francisco-Ortega, J. & Jansen, R.K. (1996) Hybridization and the extinction of rare plant species. Conservation Biology 10: 10–16.CrossRefGoogle Scholar
Liu, C., Berry, P.M., Dawson, T.P. & Pearson, R.G. (2005) Selecting thresholds of occurrence in the prediction of species distributions. Ecography 28: 385–393.Google Scholar
Loarie, S.R., Carter, B.E., Hayhoe, K., McMahon, S., Moe, R., Knight, C.A. & Ackerly, D.D. (2008) Climate change and the future of California's endemic flora. PLoS ONE 3: e2502.CrossRefGoogle ScholarPubMed
Mastrandrea, M.D. & Luers, A.L. (2012) Climate change in California: scenarios and approaches for adaptation. Climatic Change 111: 5–16.Google Scholar
Meehl, G.A., Stocker, T.F., Collins, W.D., Friedlingstein, P., Gaye, A.T., Gregory, J.M., Kitoh, A., Knutti, R., Murphy, J.M., Noda, A., Raper, S.C.B., Watterson, I.G., Weaver, A.J. & Zhao, Z.C. (2007) Global climate projections. In: Climate Change 2007: The Physical Science Basis Contribution of Working Group I to the Fourth Assessment Report of the Intergovernmental Panel on Climate Change, eds. Solomon, S., Qin, D., Manning, M., Chen, Z., Marquis, M., Avert, K. B., Tignor, M. & Miller, H. L., pp. 747–845. Cambridge, UK: Cambridge University Press.Google Scholar
Merow, C., Smith, M. J. & Silander, J. A. (2013) A practical guide to MaxEnt for modeling species’ distributions: what it does, and why inputs and settings matter. Ecography 36 (10): 1058–1069.CrossRefGoogle Scholar
Midgley, G.F., Hannah, L., Millar, D., Rutherford, M. C. & Powrie, L. W. (2002) Assessing the vulnerability of species richness to anthropogenic climate change in a biodiversity hotspot. Global Ecology and Biogeography 11: 445–451.Google Scholar
Myers, N., Mittermeier, R.A., Mittermeier, C.G., da Fonseca, G.A.B. & Kent, J. (2000) Biodiversity hotspots for conservation priorities. Nature 403: 853–858.CrossRefGoogle ScholarPubMed
Nix, H. (1986) A biogeographic analysis of Australian elapid snakes. In: Atlas of Elapid Snakes of Australia, ed. Longmore, R., pp. 4–15. Canberra, Australia: Australian Government Publishing Service.Google Scholar
Ortego, J., Riordan, E. C., Gugger, P. F. & Sork, V. L. (2012) Influence of environmental heterogeneity on genetic diversity and structure in an endemic southern Californian oak. Molecular Ecology 21 (13): 3210–3223.Google Scholar
Pearson, R.G. & Dawson, T. P. (2003) Predicting the impacts of climate change on the distribution of species: are bioclimate envelope models useful? Global Ecology and Biogeography 12: 361–371.CrossRefGoogle Scholar
Phillips, S.J., Anderson, R.P. & Schapire, R.E. (2006) Maximum entropy modeling of species geographic distributions. Ecological Modeling 190: 231–259.Google Scholar
Phillips, S.J., Williams, P., Midgley, G. & Archer, A. (2008) Optimizing dispersal corridors for the cape proteaceae using network flow. Ecological Applications 18: 1200–1211.Google Scholar
Pincetl, S.S. (2003) Transforming California: A Political History of Land Use and Development. Baltimore, Maryland, USA: The Johns Hopkins University Press. Rhymer, J.M. & Simberloff, D. (1996) Extinction by hybridization and introgression. Annual Review of Ecology and Systematics 27: 83–109.Google Scholar
Roberts, F.M. (1995) The Oaks of the Southern California Floristic Province. Encinitas, CA, USA: F. M. Roberts Publications.Google Scholar
Sala, O.E., Chapin, F.S., Armesto, J.J., Berlow, R., Bloomfield, J., Dirzo, R., Huber-Sanwald, E., Huenneke, L.F., Jackson, R.B., Kinzig, A., Leemans, R., Lodge, D., Mooney, H.A., Oesterheld, M., Poff, N.L., Sykes, M.T., Walker, B.H., Walker, M. & Wall, D.H. (2000) Global biodiversity scenarios for the year 2100. Science 287: 1770–1774.Google Scholar
Sanstad, A.H., Johnson, H., Goldstein, N. & Franco, G. (2011) Projecting long-run socioeconomic and demographic trends in California under the SRES A2 and B1 scenarios. Climatic Change 109: 21–42.Google Scholar
Santos, M.J. & Thorne, J.H. (2010) Comparing culture and ecology: conservation planning of oak woodlands in Mediterranean landscapes of Portugal and California. Environmental Conservation 37: 155–168.Google Scholar
Scott, T.A. (1990) Conserving California's rarest white oak: the Engelmann Oak. Fremontia 18: 26–29.Google Scholar
Scott, T.A. (1991) The distribution of Engelmann Oak (Quercus engelmannii) in California. USDA Forest Service General Technical Report, PSW-126, pp. 351–359, USDA, USA.Google Scholar
Seager, R., Ting, M.F., Held, I., Kushnir, Y., Lu, J., Vecchi, G., Huang, H.P., Harnik, N., Leetmaa, A., Lau, N. C., Li, C. H., Velez, J. & Naik, N. (2007) Model projections of an imminent transition to a more arid climate in southwestern North America. Science 316: 1181–1184.Google Scholar
SEINet (2011) Southwest Environmental Information Network. [www document]. URL http://swbiodiversity.org/seinet/ Google Scholar
Soberón, J. (2007) Grinnellian and Eltonian niches and geographic distributions of species. Ecology Letters 10: 1115–1123.Google Scholar
Sleeter, B.M., Sohl, T.L., Bouchard, M.A., Reker, R.R., Soulard, C.E., Acevedo, W., Griffith, G.E., Sleeter, R.R., Auch, R.F., Sayler, K.L., Prisley, S. & Zhu, Z. (2012) Scenarios of land use and land cover change in the conterminous United States: utilizing the special report on emission scenarios at ecoregional scales. Global Environmental Change 22: 896–914.Google Scholar
Svenning, J.-C. & Sandel, B. (2013) Disequilibrium vegetation dynamics under future climate change. American Journal of Botany 100: 1266–1286.CrossRefGoogle ScholarPubMed
Tebaldi, C., Hayhoe, K., Arblaster, J.M. & Meehl, G.A. (2006) Going to the extremes. Climate Change 79: 185–211.Google Scholar
USDA (2011) PLANTS profile Quercus engelmannii [www document]. URL http://plants.usda.gov/java/profile?symbol=QUEN Google Scholar
USGS (2013) Future land use and land cover scenarios [www document]. URL http://www.usgs.gov/climate_landuse/land_carbon/Scenarios.asp Google Scholar
Underwood, E.C., Viers, J.H., Klausmeyer, K.R., Cox, R.L. & Shaw, M.R. (2009) Threats and biodiversity in the Mediterranean biome. Diversity and Distribution 15: 188–197.Google Scholar
Verbruggen, H., Tyberghein, L., Belton, G. S., Mineur, F., Jueterbock, A., Hoarau, G., Gurgel, C. F. D. & De Clerck, O. (2013) Improving transferability of introduced species’ distribution models: new tools to forecast the spread of a highly invasive seaweed. Plos One 8 (6): e68337.CrossRefGoogle ScholarPubMed
Wenger, S. J. & Olden, J. D. (2012) Assessing transferability of ecological models: an underappreciated aspect of statistical validation. Methods in Ecology and Evolution 3 (2): 260–267.Google Scholar
Wiens, J.A., Stralberg, D., Jongsomjit, D., Howell, C.A. & Snyder, M.A. (2009) Niches, models, and climate change: Assessing the assumptions and uncertainties. Proceedings of the National Academy of Sciences USA 106: 19729–19736.Google Scholar
Willis, K.J. & Bhagwat, S.A. (2009) Biodiversity and climate change. Science 326: 806–807.Google Scholar
Wolf, D.E., Takebayashi, N. & Rieseberg, L.H. (2001) Predicting the risk of extinction through hybridization. Conservation Biology 15: 1039–1053.Google Scholar
World Conservation Monitoring Centre (1998) Juglans californica. In: IUCN, IUCN Red List of Threatened Species Version 2011.1 [www document]. URL http://www.iucnredlist.org Google Scholar
WorldClim (2011) Global Climate Data. [www document]. URL http://www.worldclim.org/ Google Scholar
Yates, C.J., Elith, J., Latimer, A.M., Le Maitre, D., Midgley, G.F., Schurr, F.M. & West, A.G. (2010) Projecting climate change impacts on species distributions in megadiverse South African Cape and Southwest Australian Floristic Regions: opportunities and challenges. Austral Ecology 35: 374–391.Google Scholar
Zamudio, K.R., Harrison, R.G. & Matocq, M. (2010) Hybridization in threatened and endangered animal taxa: Implications for conservation and management of biodiversity. In: Molecular Approaches in Natural Resource Conservation and Management, ed. DeWoody, J.A., Bickham, J.W., Michler, C.H., Nichols, K.M., Rhodes, O.E. & Woeste, K.E., pp. 169–189. New York, NY, USA: Cambridge University Press.Google Scholar
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