Skip to main content Accessibility help
×
Hostname: page-component-76fb5796d-x4r87 Total loading time: 0 Render date: 2024-04-26T05:38:08.446Z Has data issue: false hasContentIssue false

10 - Biodiversity informatics for climate change studies

from Section 3 - Biogeography, migration and ecological niche modelling

Published online by Cambridge University Press:  16 May 2011

A. Culham
Affiliation:
University of Reading, UK
C. Yesson
Affiliation:
Institute of Zoology, Zoological Society of London, UK
Trevor R. Hodkinson
Affiliation:
Trinity College, Dublin
Michael B. Jones
Affiliation:
Trinity College, Dublin
Stephen Waldren
Affiliation:
Trinity College, Dublin
John A. N. Parnell
Affiliation:
Trinity College, Dublin
Get access

Summary

Abstract

Modelling the impacts of climate change on biodiversity in a phylogenetic context combines the disparate disciplines of phylogenetics, geographic information systems, niche ecology and climate change research. Each subject has its own approach, literature and data. The strength of an integrative research, known as ‘phyloclimatic modelling’, is that it provides novel insights into the possible interactions of life and climate over millions of years. However, the risk is that problems associated with each subject area might be compounded if analyses are not conducted with care. The continuous development of analytical approaches and the steady increase in data availability have offered new opportunities for data combination. Modelling techniques and output for climate, ecological niche modelling, phylogeny reconstruction and temporal calibration are becoming stronger, and the reliability of results is quantifiable. In contrast, there is still a desperate lack of fundamental data on organismal distribution and on fossil history of lineages. When theories of taxonomic delimitation change, there are subsequent changes in organismal names. This creates difficulty for name-based data retrieval, but techniques are being developed to reduce this problem. Improvements in theory, associated tools and data availability will broaden the applicability of phyloclimatic modelling.

Background

Modelling the impact of climate change on the world's biota is an aspirational goal dependent on the availability of both large amounts of data and substantial computing resources. These models can be used to help us understand evolutionary relationships and ecological requirements of species, and to estimate their past, present and future distributions.

Type
Chapter
Information
Publisher: Cambridge University Press
Print publication year: 2011

Access options

Get access to the full version of this content by using one of the access options below. (Log in options will check for institutional or personal access. Content may require purchase if you do not have access.)

References

Bisby, F., Roskov, Y., Orrell, T. et al. (2009). Species 2000 and ITIS Catalogue of Life: 2009 Annual Checklist. Reading: Species 2000. www.Catalogueoflife.Org/annual-checklist/2009.
Busby, J. R. (1991). BIOCLIM: a bioclimatic analysis and prediction system. In Nature Conservation: Cost Effective Biological Surveys and Data Analysis, ed. Margules, C. R. and Austin, M. P.. Melbourne: CSIRO, pp. 64–68.Google Scholar
Carstens, B. C. and Richards, C. L. (2007). Integrating coalescent and ecological niche modeling in comparative phylogeography. Evolution, 61, 1439–1454.CrossRefGoogle ScholarPubMed
Clark, T., Martin, S. and Liefeld, T. (2004). Globally distributed object identification for biological knowledgebases. Briefings in Bioinformatics, 5, 59–70.CrossRefGoogle ScholarPubMed
Collen, B., Ram, M., Zamin, T. and McRae, L. (2008). The tropical biodiversity data gap: addressing disparity in global monitoring. Tropical Conservation Science, 1, 75–88.CrossRefGoogle Scholar
Eaton, M. D., Soberon, J. and Peterson, T. (2008). Phylogenetic perspective on ecological niche evolution in American blackbirds (family Icteridae). Biological Journal of the Linnean Society, 94, 869–878.CrossRefGoogle Scholar
Elith, J., Graham, C. H., Anderson, R. P. et al. (2006). Novel methods improve prediction of species' distributions from occurrence data. Ecography, 29, 129–151.CrossRefGoogle Scholar
Evans, M. E. K., Smith, S. A., Flynn, R. S. and Donoghue, M. J. (2009). Climate, niche evolution, and diversification of the ‘Bird-cage’ Evening primroses (Oenothera, sections Anogra and Kleinia). American Naturalist, 173, 225–240.CrossRefGoogle Scholar
Graham, C. H., Ferrier, S., Huettman, F., Moritz, C. and Peterson, A. T. (2004). New developments in museum-based informatics and applications in biodiversity analysis. Trends in Ecology and Evolution, 19, 497–503.CrossRefGoogle ScholarPubMed
Guralnick, R. and Hill, A. (2009). Biodiversity informatics: automated approaches for documenting global biodiversity patterns and processes. Bioinformatics, 25, 421–428.CrossRefGoogle ScholarPubMed
Hartmann, F. A., Wilson, R., Gradstein, S. R., Schneider, H. and Heinrichs, J. (2006). Testing hypotheses on species delimitations and disjunctions in the liverwort Bryopteris (Jungermanniopsida: Lejeuneaceae). International Journal of Plant Sciences, 167, 1205–1214CrossRefGoogle Scholar
Hernandez, P. A., Graham, C. H., Master, L. L. and Albert, D. L. (2006). The effect of sample size and species characteristics on performance of different species distribution modeling methods. Ecography, 29, 773–785.CrossRefGoogle Scholar
Heywood, V. H. (2009). The impacts of climate change on plant species in Europe, with contributions by A. Culham. Strasbourg: Convention on the Conservation of European Wildlife and Natural Habitats Standing Committee.
Hutchinson, G. E. (1957). Concluding remarks. Cold Spring Harbor Symposium. Quantitative Biology, 22, 415–427.CrossRefGoogle Scholar
,Intergovernmental Panel on Climate Change (IPCC) (2007). Climate Change 2007: Synthesis Report. Contribution of Working Groups I, II and III to the Fourth Assessment Report of the Intergovernmental Panel on Climate Change, ed. Pachauri, R. K. and Reisinger, A.. Geneva: IPCC.Google Scholar
Jakob, S. S., Martinez-Meyer, E. and Blattner, F. R. (2009). Phylogeographic analyses and paleodistribution modeling indicate Pleistocene in situ survival of Hordeum species (Poaceae) in southern Patagonia without genetic or spatial restriction. Molecular Biology and Evolution, 26, 907–923.CrossRefGoogle ScholarPubMed
Leliaert, F., Verbruggen, H., Wysor, B. and Clerck, O. (2009). DNA taxonomy in morphologically plastic taxa: algorithmic species delimitation in the Boodlea complex (Chlorophyta: Cladophorales). Molecular Phylogenetics and Evolution, 53, 122–133.CrossRefGoogle Scholar
Lo Presti, R. M. and Oberprieler, C. (2009). Evolutionary history, biogeography and eco-climatological differentiation of the genus Anthemis L. (Compositae, Anthemideae) in the circum-Mediterranean area. Journal of Biogeography, 36, 1313–1332.CrossRefGoogle Scholar
Page, R. D. M. (2005). A taxonomic search engine: federating taxonomic databases using web services. BMC Bioinformatics, 6, 48.CrossRefGoogle ScholarPubMed
Pahwa, J. S., Jones, A. C., White, R. J. et al. (2006). Supporting the construction of workflows for biodiversity problem-solving accessing secure, distributed resources. Scientific Programming, 14, 195–208.CrossRefGoogle Scholar
Patterson, D. J., Remsen, D., Marino, W. A. and Norton, C. (2006). Taxonomic indexing: extending the role of taxonomy. Systematic Biology, 55, 367–373.CrossRefGoogle ScholarPubMed
Peterson, A. T. (2006). Uses and requirements of ecological niche models and related distributional models. Biodiversity Informatics, 3, 59–72.CrossRefGoogle Scholar
Phillips, S. J., Anderson, R. P. and Schapire, R. E. (2006). Maximum entropy modeling of species geographic distributions. Ecological Modelling, 190, 231–259.CrossRefGoogle Scholar
Sellwood, B. W. and Valdes, P. J. (2006). Mesozoic climates: general circulation models and the rock record. Sedimentary Geology, 190, 269–287.CrossRefGoogle Scholar
Slingo, J., Bates, K., Nikiforakis, N. et al. (2009). Developing the next-generation climate system models: challenges and achievements. Philosophical Transactions of the Royal Society of London A, 367, 815–831.CrossRefGoogle ScholarPubMed
Soberón, J. (2007). Grinnellian and Eltonian niches and geographic distributions of species. Ecological Letters, 10, 1115–1123.CrossRefGoogle ScholarPubMed
Stockwell, D. R. B. and Peters, D. P. (1999). The GARP modelling system: problems and solutions to automated spatial prediction. International Journal of Geographic Information Systems, 13, 143–158.CrossRefGoogle Scholar
Verbruggen, H., Tyberghein, L., Pauly, K. et al. (2009). Macroecology meets macroevolution: evolutionary niche dynamics in the seaweed Halimeda. Global Ecology and Biogeography, 18, 393–405.CrossRefGoogle Scholar
Washington, W. M., Buja, L. and Craig, A. (2009). The computational future for climate and earth system models: on the path to petaflop and beyond. Philosophical Transactions of the Royal Society of London A, 367, 833–846.CrossRefGoogle ScholarPubMed
Williams, M., Haywood, A. M., Gregory, J. and Schmidt, D. N. (2007). Deep-time Perspectives on Climate Change: Marrying the Signal From Computer Models and Biological Proxies. London: Geological Society of London on behalf of the Micropalaeontological Society.Google Scholar
Wisz, M. S., Hijmans, R. J., Li, J. et al. (2008). Effects of sample size on the performance of species distribution models. Diversity and Distributions, 14, 763–773.CrossRefGoogle Scholar
Yesson, C. and Culham, A. (2006a). Phyloclimatic modelling: combining phylogenetics and bioclimatic modelling. Systematic Biology, 55, 785–802.CrossRefGoogle Scholar
Yesson, C. and Culham, A. (2006b). A phyloclimatic study of Cyclamen. BMC Evolutionary Biology, 6, 72.CrossRefGoogle ScholarPubMed
Yesson, C., Brewer, P. W., Sutton, T. et al. (2007). How global is the Global Biodiversity Information Facility?PLoS ONE, 2, e1124.CrossRefGoogle ScholarPubMed
Yesson, C., Toomey, N. H. and Culham, A. (2009). Cyclamen: time, sea and speciation biogeography using a temporally calibrated phylogeny. Journal of Biogeography, 36, 1234–1252.CrossRefGoogle Scholar

Save book to Kindle

To save this book to your Kindle, first ensure coreplatform@cambridge.org is added to your Approved Personal Document E-mail List under your Personal Document Settings on the Manage Your Content and Devices page of your Amazon account. Then enter the ‘name’ part of your Kindle email address below. Find out more about saving to your Kindle.

Note you can select to save to either the @free.kindle.com or @kindle.com variations. ‘@free.kindle.com’ emails are free but can only be saved to your device when it is connected to wi-fi. ‘@kindle.com’ emails can be delivered even when you are not connected to wi-fi, but note that service fees apply.

Find out more about the Kindle Personal Document Service.

Available formats
×

Save book to Dropbox

To save content items to your account, please confirm that you agree to abide by our usage policies. If this is the first time you use this feature, you will be asked to authorise Cambridge Core to connect with your account. Find out more about saving content to Dropbox.

Available formats
×

Save book to Google Drive

To save content items to your account, please confirm that you agree to abide by our usage policies. If this is the first time you use this feature, you will be asked to authorise Cambridge Core to connect with your account. Find out more about saving content to Google Drive.

Available formats
×