Show simple item record

Moving forward in global‐change ecology: capitalizing on natural variability

dc.contributor.authorIbáñez, Inésen_US
dc.contributor.authorGornish, Elise S.en_US
dc.contributor.authorBuckley, Laurenen_US
dc.contributor.authorDebinski, Diane M.en_US
dc.contributor.authorHellmann, Jessicaen_US
dc.contributor.authorHelmuth, Brianen_US
dc.contributor.authorHilleRisLambers, Jannekeen_US
dc.contributor.authorLatimer, Andrew M.en_US
dc.contributor.authorMiller‐rushing, Abraham J.en_US
dc.contributor.authorUriarte, Mariaen_US
dc.date.accessioned2013-02-12T19:00:45Z
dc.date.available2013-02-12T19:00:45Z
dc.date.issued2012-01en_US
dc.identifier.citationIbáñez, Inés ; Gornish, Elise S.; Buckley, Lauren; Debinski, Diane M.; Hellmann, Jessica; Helmuth, Brian; HilleRisLambers, Janneke; Latimer, Andrew M.; Miller‐rushing, Abraham J. ; Uriarte, Maria (2012). "Moving forward in globalâ change ecology: capitalizing on natural variability." Ecology and Evolution 3(1): 170-181. <http://hdl.handle.net/2027.42/96312>en_US
dc.identifier.issn2045-7758en_US
dc.identifier.issn2045-7758en_US
dc.identifier.urihttps://hdl.handle.net/2027.42/96312
dc.description.abstractNatural resources managers are being asked to follow practices that accommodate for the impact of climate change on the ecosystems they manage, while global‐ecosystems modelers aim to forecast future responses under different climate scenarios. However, the lack of scientific knowledge about short‐term ecosystem responses to climate change has made it difficult to define set conservation practices or to realistically inform ecosystem models. Until recently, the main goal for ecologists was to study the composition and structure of communities and their implications for ecosystem function, but due to the probable magnitude and irreversibility of climate‐change effects (species extinctions and loss of ecosystem function), a shorter term focus on responses of ecosystems to climate change is needed. We highlight several underutilized approaches for studying the ecological consequences of climate change that capitalize on the natural variability of the climate system at different temporal and spatial scales. For example, studying organismal responses to extreme climatic events can inform about the resilience of populations to global warming and contribute to the assessment of local extinctions. Translocation experiments and gene expression are particular useful to quantitate a species' acclimation potential to global warming. And studies along environmental gradients can guide habitat restoration and protection programs by identifying vulnerable species and sites. These approaches identify the processes and mechanisms underlying species acclimation to changing conditions, combine different analytical approaches, and can be used to improve forecasts of the short‐term impacts of climate change and thus inform conservation practices and ecosystem models in a meaningful way. In this manuscript, we describe several underutilized approaches and techniques to address the study of short‐term species and ecosystem responses to climate change and highlight why these approaches are particularly valuable for generating information relevant for conservation practices and predictive models. These methods optimize the use of available information and can improve the reliability of our predictions by better exploring the range of potential outcomes of species and ecosystem responses to climate change.en_US
dc.publisherSinauer Associates, Inc.en_US
dc.publisherWiley Periodicals, Inc.en_US
dc.subject.otherClimate Changeen_US
dc.subject.otherForecastingen_US
dc.subject.otherRange Shiftsen_US
dc.subject.otherTranslocationen_US
dc.subject.otherEnvironmental Gradientsen_US
dc.titleMoving forward in global‐change ecology: capitalizing on natural variabilityen_US
dc.typeArticleen_US
dc.rights.robotsIndexNoFollowen_US
dc.subject.hlbsecondlevelEcology and Evolutionary Biologyen_US
dc.subject.hlbtoplevelScienceen_US
dc.description.peerreviewedPeer Revieweden_US
dc.identifier.pmid23404535en_US
dc.description.bitstreamurlhttp://deepblue.lib.umich.edu/bitstream/2027.42/96312/1/ece3433.pdf
dc.identifier.doi10.1002/ece3.433en_US
dc.identifier.sourceEcology and Evolutionen_US
dc.identifier.citedreferenceOgle, K., and J. J. Barber. 2008. Bayesian data‐model integration in plant physiological and ecosystem ecology. Progr. Bot. 69: 281 – 311.en_US
dc.identifier.citedreferenceMonaco, C. J., and B. Helmuth. 2011. Tipping points, thresholds and the keystone role of physiology in marine climate change research. Adv. Mar. Biol. 60: 123 – 162.en_US
dc.identifier.citedreferenceMonahan, W. B. 2009. A mechanistic niche model for measuring species' distributional responses to seasonal temperature gradients. PLoS ONE 4: 7921.en_US
dc.identifier.citedreferenceMorin, X., and M. J. Lechowicz. 2008. Contemporary perspectives on the niche that can improve models of species range shifts under climate change. Biol. Lett. 4: 573 – 576.en_US
dc.identifier.citedreferenceMumby, P. J., I. A. Elliott, C. M. Eakin, W. Skirving, C. B. Paris, H. J. Edwards, et al. 2011. Reserve design for uncertain responses of coral reefs to climate change. Ecol. Lett. 14: 132 – 140.en_US
dc.identifier.citedreferencePaine, R. T., M. J. Tagener, and E. A. Johnson. 1998. Compounded perturbations yield ecological surprises. Ecosystems 1: 535 – 545.en_US
dc.identifier.citedreferenceParmesan, C., and J. Matthews. 2006. Biological impacts of climate change. Pp. 333 – 360 in M. J. Groom, G. K. Meffe and C. R. Carroll, eds. Principles of conservation biology. Sinauer Associates, Inc., Sunderland.en_US
dc.identifier.citedreferenceParmesan, C., and G. Yohe. 2003. A globally coherent fingerprint of climate change impacts across natural systems. Nature 421: 37 – 42.en_US
dc.identifier.citedreferencePelini, S. L., J. D. Dzurisin, K. M. Prior, C. M. Williams, T. D. Marsico, B. J. Sinclair, et al. 2009. Translocation experiments with butterflies reveal limits to enhancement of poleward populations under climate change. Proc. Natl Acad. Sci. USA 106: 11160 – 11165.en_US
dc.identifier.citedreferencePettorelli, N. 2012. Climate change as a main driver of ecological research. J. Appl. Ecol. 49: 542 – 545.en_US
dc.identifier.citedreferencePincebourde, S., E. Sanford, and B. Helmuth. 2008. Body temperature during low tide alters the feeding performance of a top intertidal predator. Limnol. Oceanogr. 53: 1562 – 1573.en_US
dc.identifier.citedreferencePressey, R. L., M. Cabeza, M. E. Watts, R. M. Cowling, and K. A. Wilson. 2007. Conservation planning in a changing world. Trends Ecol. Evol. 22: 583 – 592.en_US
dc.identifier.citedreferencePreston, K., J. T. Rotenberry, R. A. Redak, and M. F. Allen. 2008. Habitat shifts of endangered species under altered climate conditions: importance of biotic interactions. Glob. Change Biol. 14: 2501 – 2515.en_US
dc.identifier.citedreferencePrice, T. D., and M. Kirkpatrick. 2009. Evolutionarily stable range limits set by interspecific competition. Proc. R. Soc. B Biol. Sci. 276: 1429 – 1434.en_US
dc.identifier.citedreferenceRissler, L. J., and J. J. Apodaca. 2007. Adding more ecology into species delimitation: ecological niche models and phylogeography help define cryptic species in the Black Salamander ( Aneides flavipunctatus ). Syst. Biol. 56: 924 – 942.en_US
dc.identifier.citedreferenceRutter, M. T., and C. B. Fenster. 2007. Testing for adaptation to climate in Arabidopsis thaliana: a calibrated common garden approach. Ann. Bot. 99: 529 – 536.en_US
dc.identifier.citedreferenceSará, G., M. Kearney, and B. Helmuth. 2011. Combining heat‐transfer and energy budget models to predict thermal stress in Mediterranean intertidal mussels. Chem. Ecol. 27: 135 – 145.en_US
dc.identifier.citedreferenceSinclair, S. J., M. D. White, and G. R. Newell. 2010. How useful are species distribution models for managing biodiversity under future climates? Ecol. Soc. 15: 8.en_US
dc.identifier.citedreferenceSkelly, D. K., L. N. Joseph, H. P. Possingham, L. K. Freidenburg, T. J. Farrugia, M. T. Kinnison, et al. 2007. Evolutionary responses to climate change. Conserv. Biol. 21: 1353 – 1355.en_US
dc.identifier.citedreferenceStachowicz, J. J., J. R. Terwin, R. B. Whitlatch, and R. W. Osman. 2002. Linking climate change and biological invasions: ocean warming facilitates nonindigenous species invasions. Proc. Natl Acad. Sci. USA 99: 15497 – 15500.en_US
dc.identifier.citedreferenceStokstad, E. 2011. Open‐source ecology takes root across the world. Science 334: 308 – 309.en_US
dc.identifier.citedreferenceTrotter, R. T., N. S. Cobb, and T. G. Whitham. 2002. Herbivory, plant resistance, and climate in the tree ring record: interactions distort climatic reconstructions. Proc. Natl Acad. Sci. USA 99: 10197 – 10202.en_US
dc.identifier.citedreferenceUrban, M. C., J. J. Tewksbury, and K. S. Sheldon. 2012a. On a collision course: competition and dispersal differences create no‐analogue communities and cause extinctions during climate change. Proc. R. Soc. B Biol. Sci. ???: ??? – ???. doi: 10.1098/rspb.2011.2367.en_US
dc.identifier.citedreferenceUrban, M. C., L. De Meester, M. Vellend, R. Stoks, and J. Vanoverbeke. 2012b. A crucial step toward realism: responses to climate change from an evolving metacommunity perspective. Evol. Appl. 5: 154 – 167.en_US
dc.identifier.citedreferenceWilliams, J. W., and S. T. Jackson. 2007. Novel climates, no‐analog communities, and ecological surprises. Front. Ecol. Environ. 5: 475 – 485.en_US
dc.identifier.citedreferenceZakharov, E. V., and J. J. Hellmann. 2008. Genetic differentiation across a latitudinal gradient in two co‐occurring butterfly species: revealing population differences in a context of climate change. Mol. Ecol. 17: 189 – 208.en_US
dc.identifier.citedreferenceZarnetske, P. L., D. K. Skelly, and M. C. Urban. 2012. Biotic multipliers of climate change. Science 336: 1516 – 1518.en_US
dc.identifier.citedreferenceZhang, X., M. A. Friedl, C. B. Schaaf, A. H. Strahler, J. C. F. Hodges, F. Gao, et al. 2003. Monitoring vegetation phenology using MODIS. Remote Sens. 84: 471 – 475.en_US
dc.identifier.citedreferenceZimmermann, N. E., N. G. Yoccoz, T. C. Edwards, E. S. Meier, W. Thuiller, A. Guisan, et al. 2009. Climatic extremes improve predictions of spatial patterns of tree species. Proc. Natl Acad. Sci. 106 ( Suppl 2 ): 19723 – 19728.en_US
dc.identifier.citedreferenceAgrawal, A. A., A. P. Hastings, M. T. J. Johnson, J. L. Maron, and J. Salminen. 2012. Insect herbivores drive real‐time ecological and evolutionary change in plant populations. Science 338: 113 – 116.en_US
dc.identifier.citedreferenceAngert, A. L., S. N. Sheth, and J. R. Paul. 2011. Incorporating population‐level variation in thermal performance into predictions of geographic range shifts. Integr. Comp. Biol. ???: ??? – ???. doi: 10.1093/icb/icr048, pp 1‐18.en_US
dc.identifier.citedreferenceAngilletta, M. J., Jr, A. F. Bennett, H. Guderley, C. A. Navas, F. Seebacher, and R. S. Wilson. 2006. Coadaptation: a unifying principle in evolutionary thermal biology. Physiol. Biochem. Zool. 79: 282 – 294.en_US
dc.identifier.citedreferenceAraujo, M. B., D. Nogues‐Bravo, J. A. F. Diniz‐Filho, A. M. Haywood, P. J. Valdes, and C. Rahbek. 2008. Quaternary climate changes explain diversity among reptiles and amphibians. Ecography 31: 8 – 15.en_US
dc.identifier.citedreferenceBeier, C., C. Beierkuhnlein, T. Wohlgemuth, J. Peñuelas, B. Emmett, C. Körner, et al. 2012. Precipitation manipulation experiments – challenges and recommendations for the future. Ecol. Lett. 15: 899 – 911.en_US
dc.identifier.citedreferenceBeukema, J. J., R. Dekker, and J. M. Jansen. 2009. Some like it cold: populations of the tellinid bivalve Macoma balthica (L.) suffer in various ways from a warming climate. Mar. Ecol. Progr. Ser. 384: 135 – 145.en_US
dc.identifier.citedreferenceBolker, B. 2009. Learning hierarchical models: advice for the rest of us. Ecol. Appl. 19: 588 – 592.en_US
dc.identifier.citedreferenceBrook, B. W., H. R. Akcakaya, D. A. Keith, G. M. Mace, R. G. Pearson, and M. B. Araujo. 2009. Integrating bioclimate with population models to improve forecasts of species extinctions under climate change. Biol. Lett. 23: 723 – 725.en_US
dc.identifier.citedreferenceBuckley, L. B. 2008. Linking traits to energetics and population dynamics to predict lizard ranges in changing environments. Am. Nat. 171: E1 – E19.en_US
dc.identifier.citedreferenceBuckley, L. B., and J. G. Kingsolver. 2012. The demographic impacts of shifts in climate means and extremes on alpine butterflies. Funct. Ecol. 26: 969 – 977.en_US
dc.identifier.citedreferenceBuckley, L. B., M. C. Urban, M. J. Angilletta, L. G. Crozier, L. J. Rissler, and M. W. Sears. 2010. Can mechanism inform species' distribution models? Ecol. Lett. 13: 1041 – 1054.en_US
dc.identifier.citedreferenceBuckley, L. B., S. A. Waaser, H. J. MacLean, and R. Fox. 2011. Does including physiology improve species distribution model predictions of responses to recent climate change? Ecology 92: 2214 – 2221.en_US
dc.identifier.citedreferenceChambers, J. Q., G. P. Asner, D. C. Morton, L. O. Anderson, S. S. Saatchi, F. D. B. Espirito‐Santo, et al. 2007. Regional ecosystem structure and function: ecological insights from remote sensing of tropical forests. Trends Ecol. Evol. 22: 414 – 423.en_US
dc.identifier.citedreferenceChown, S. L., and J. S. Terblanche. 2007. Physiological diversity in insects: ecological and evolutionary contexts. Adv. Insect Phys. 33: 50 – 152.en_US
dc.identifier.citedreferenceChown, S. L., A. A. Hoffmann, T. N. Kristensen, M. J. Angilletta, N. C. Stenseth, and C. Pertoldi. 2010. Adapting to climate change: a perspective from evolutionary physiology. Clim. Res. 43: 3 – 15.en_US
dc.identifier.citedreferenceClark, J. S. 2005. Why environmental scientists are becoming Bayesians. Ecol. Lett. 8: 2 – 14.en_US
dc.identifier.citedreferenceClark, J. S., D. M. Bell, M. Hersch, and L. Nichols. 2011. Climate change vulnerability of forest biodiversity: climate and competition tracking of demographic rates. Glob. Change Biol. 17: 1834 – 1849.en_US
dc.identifier.citedreferenceCrain, C. M., K. Kroeker, and B. Halpern. 2008. Interactive and cumulative effects of multiple stressors in marine systems. Ecol. Lett. 12: 1304 – 1315.en_US
dc.identifier.citedreferenceCrozier, L. G. 2004. Field transplants reveal summer constraints on a butterfly range expansion. Oecologia 141: 148 – 157.en_US
dc.identifier.citedreferenceCrozier, L., and G. Dwyer. 2006. Combining population‐dynamic and ecophysiological models to predict climate‐induced insect range shifts. Am. Nat. 167: 853 – 866.en_US
dc.identifier.citedreferenceDavis, M. B., R. G. Shaw, and J. R. Etterson. 2005. Evolutionary responses to changing climate. Ecology 86: 1704 – 1714.en_US
dc.identifier.citedreferenceDebinski, D. M., R. E. VanNimwegen, and M. E. Jakubauskas. 2006. Quantifying relationships between bird and butterfly community shifts and environmental change. Ecol. Appl. 16: 380 – 393.en_US
dc.identifier.citedreferenceDebinski, D. M., H. Wickham, K. Kindscher, J. C. Caruthers, and M. Germino. 2010. Montane meadow change during drought varies with background hydrologic regime and plant functional group. Ecology 91: 1672 – 1681.en_US
dc.identifier.citedreferenceDeutsch, C. A., J. J. Tewksbury, R. B. Huey, K. S. Sheldon, C. K. Ghalambor, D. C. Haak, et al. 2008. Impacts of climate warming on terrestrial ectotherms across latitude. Proc. Natl Acad. Sci. USA 105: 6668 – 6672.en_US
dc.identifier.citedreferenceGallien, L., T. Munkemuller, C. H. Albert, I. Boulangeat, and W. Thuiller. 2010. Predicting potential distributions of invasive species: where to go from here? Divers. Distrib. 16: 331 – 342.en_US
dc.identifier.citedreferenceGaston, K. J., S. L. Chown, P. Calosi, J. Bernardo, D. T. Bilton, A. Clarke, et al. 2009. Macrophysiology: a conceptual reunification. Am. Nat. 174: 595 – 612.en_US
dc.identifier.citedreferenceGilman, S. E., M. C. Urban, J. Tewksbury, G. W. Gilchrist, and R. D. Holt. 2010. A framework for community interactions under climate change. Trends Ecol. Evol. 25: 325 – 331.en_US
dc.identifier.citedreferenceGornish, E. S., and T. E. Miller. 2010. Effects of storm frequency on dune vegetation. Glob. Change Biol. 16: 2668 – 2675.en_US
dc.identifier.citedreferenceGrace, J. B., S. Harrison, and E. Damschen. 2011. Local richness along gradients in the Siskiyou herb flora: R. H. Whittaker revisited. Ecology 9: 108 – 120.en_US
dc.identifier.citedreferenceHarley, C. D. G. 2011. Climate change, keystone predation, and biodiversity loss. Science 334: 1124 – 1127.en_US
dc.identifier.citedreferenceHelmuth, B., C. D. G. Harley, P. M. Halpin, M. O'Donnell, G. E. Hofmann, and C. A. Blanchette. 2002. Climate change and latitudinal patterns of intertidal thermal stress. Science 298: 1015 – 1017.en_US
dc.identifier.citedreferenceHelmuth, B., J. G. Kingsolver, and E. Carrington. 2005. Biophysics, physiological ecology, and climate change: does mechanism matter? Annu. Rev. Physiol. 67: 177 – 201.en_US
dc.identifier.citedreferenceHelmuth, B., B. R. Broitman, L. Yamane, S. E. Gilman, K. Mach, K. A. S. Mislan, et al. 2010. Organismal climatology: analyzing environmental variability at scales relevant to physiological stress. J. Exp. Biol. 213: 995 – 1003.en_US
dc.identifier.citedreferenceHoffmann, A. A., R. J. Hallas, J. A. Dean, and M. Schiffer. 2003. Low potential for climatic stress adaptation in a rainforest Drosophila species. Science 301: 1000 – 1102.en_US
dc.identifier.citedreferenceHonnay, O., K. Verheyen, J. Butaye, H. Jacquemyn, B. Bossuyt, and M. Hermy. 2002. Possible effects of habitat fragmentation and climate change on the range of forest plant species. Ecol. Lett. 5: 525 – 530.en_US
dc.identifier.citedreferenceHuey, R. B., G. W. Gilchrist, M. L. Carlson, D. Berrigan, and L. Serra. 2000. Rapid evolution of a geographic cline in size in an introduced fly. Science 287: 308 – 309.en_US
dc.identifier.citedreferenceHugall, A., C. Moritz, A. Moussalli, and J. Stanisic. 2002. Reconciling paleodistribution models and comparative phylogeography in the Wet Tropics rainforest land snail Gnarosophia bellendenkerensis (Brazier 1875). Proc. Natl Acad. Sci. USA 99: 6112 – 6117.en_US
dc.identifier.citedreferenceIbáñez, I., J. S. Clark, S. LaDeau, and J. HilleRisLambers. 2007. Exploiting temporal variability to understand tree recruitment response to climate change. Ecol. Monogr. 77: 163 – 177.en_US
dc.identifier.citedreferenceIbáñez, I., J. S. Clark, and M. C. Dietze. 2008. Evaluating the sources of potential migrant species. Implications under climate change. Ecol. Appl. 18: 1664 – 1678.en_US
dc.identifier.citedreferenceIbáñez, I., R. B. Primack, A. J. Miller‐Rushing, E. Ellwood, H. Higuchi, S. D. Lee, et al. 2010. Forecasting phenology under global warming. Philos. Trans. R. Soc. B Biol. Sci. 365: 3247 – 3260.en_US
dc.identifier.citedreferenceJarema, S. I., J. Samson, B. J. Mcgill, and M. M. Humphries. 2009. Variation in abundance across a species' range predicts climate change responses in the range interior will exceed those at the edge: a case study with North American beaver. Glob. Change Biol. 15: 508 – 522.en_US
dc.identifier.citedreferenceJump, A. S., and J. Penuelas. 2005. Running to stand still: adaptation and the response of plants to rapid climate change. Ecol. Lett. 8: 1010 – 1020.en_US
dc.identifier.citedreferenceKearney, M., and W. Porter. 2009. Mechanistic niche modelling: combining physiological and spatial data to predict species' ranges. Ecol. Lett. 12: 334 – 350.en_US
dc.identifier.citedreferenceKearney, M., W. P. Porter, C. Williams, S. Ritchie, and A. A. Hoffmann. 2009a. Integrating biophysical models and evolutionary theory to predict climatic impacts on species' ranges: the dengue mosquito Aedes aegypti in Australia. Funct. Ecol. 23: 528 – 538.en_US
dc.identifier.citedreferenceKearney, M., R. Shine, and W. P. Porter. 2009b. The potential for behavioral thermoregulation to buffer “cold‐blooded” animals against climate warming. Proc. Natl Acad. Sci. USA 106: 3835 – 3840.en_US
dc.identifier.citedreferenceKearney, M., E. Ferguson, S. Fumei, A. Gallacher, P. Mitchell, and R. Woodford. 2011. A cost‐effective method of assessing thermal habitat quality for endotherms. Austral Ecol. 36: 1442 – 9985.en_US
dc.identifier.citedreferenceKerr, J. T., H. Kharouba, and D. J. Currie. 2007. The macroecological contribution to global change solutions. Science 316: 1581 – 1584.en_US
dc.identifier.citedreferenceKolbe, J. J., M. Kearney, and R. Shine. 2010. Modeling the consequences of thermal trait variation for the cane toad invasion of Australia. Ecol. Appl. 20: 2273 – 2285.en_US
dc.identifier.citedreferenceLatimer, A. L., S. Wu, A. E. Gelfand, and J. Silander. 2006. Building statistical models to analyze species distributions. Ecol. Appl. 16: 33 – 50.en_US
dc.identifier.citedreferenceLau, J. A., and J. T. Lennon. 2012. Rapid responses of soil microorganisms improve plant fitness in novel environments. Proc. Natl Acad. Sci. 109: 14058 – 14062.en_US
dc.identifier.citedreferenceLavergne, S., N. Mouquet, W. Thuiller, and O. Ronce. 2010. Biodiversity and climate change: integrating evolutionary and ecological responses of species and communities. Annu. Rev. Ecol. Evol. Syst. 41: 321 – 350.en_US
dc.identifier.citedreferenceLenoir, J., J. C. Gegout, P. A. Marquet, P. de Ruffray, and H. Brisse. 2008. A significant upward shift in plant species optimum elevation during the 20th century. Science 320: 1768 – 1771.en_US
dc.identifier.citedreferenceLeuzinger, S., Y. Q. Luo, C. Beier, W. Dieleman, S. Vicca, and C. Korner. 2011. Do global change experiments overestimate impacts on terrestrial ecosystems? Trends Ecol. Evol. 26: 236 – 241.en_US
dc.identifier.citedreferenceMarsico, T. D., and J. J. Hellmann. 2009. Dispersal limitation inferred from an experimental translocation of Lomatium ( Apiaceae ) species outside their geographic ranges. Oikos 118: 1783 – 1792.en_US
dc.identifier.citedreferenceMenzel, A., T. H. Sparks, N. Estrella, E. Koch, A. Aasa, R. Ahas, et al. 2006. European phenological response to climate change matches the warming pattern. Glob. Change Biol. 12: 1969 – 1976.en_US
dc.identifier.citedreferenceMiller‐Rushing, A. J., and R. B. Primack. 2008. Global warming and flowering times in Thoreau's concord: a community perspective. Ecology 89: 332 – 341.en_US
dc.identifier.citedreferenceMislan, K. A. S., and D. S. Wethey. 2011. Gridded meteorological data as resource for mechanistic ecology in coastal environments. Ecol. Appl. 21: 2679 – 2690.en_US
dc.owningcollnameInterdisciplinary and Peer-Reviewed


Files in this item

Show simple item record

Remediation of Harmful Language

The University of Michigan Library aims to describe library materials in a way that respects the people and communities who create, use, and are represented in our collections. Report harmful or offensive language in catalog records, finding aids, or elsewhere in our collections anonymously through our metadata feedback form. More information at Remediation of Harmful Language.

Accessibility

If you are unable to use this file in its current format, please select the Contact Us link and we can modify it to make it more accessible to you.