Ecological Forecasting Information

Ecological forecasting uses knowledge of physics, ecology and physiology to predict how ecosystems will change in the future in response to environmental factors such as climate change. The ultimate goal of the approach is to provide people such as resource managers and designers of marine reserves with information that they can then use to respond, in advance, to future changes,^[1] a form of adaptation to global warming.

One of the most important environmental factors impacting organisms today is global warming. Most physiological processes are affected by temperature, and so even small changes in weather and climate can lead to large changes in the growth, reproduction and survival of animals and plants. The scientific consensus^[2][3] is that the increase in atmospheric greenhouse gases due to human activity caused most of the warming observed since the start of the industrial era. These changes are in turn impacting both humans and natural ecosystems.^[4]

One major challenge is to predict where, when and with what magnitude impacts are likely to occur so that we can mitigate or at least prepare for them.^[1] Ecological forecasting applies existing knowledge of how animals and plants interact with their physical environment^[5] to ask how changes in environmental factors might result in changes to the ecosystems as a whole.^[6][7]

Approaches

• Palaeobiology modeling: uses fossil and phylogenetic evidence of biodiversity in the past to project the trajectory of biodiversity in the future. Simple plots can be constructed and then adjusted based on the varying quality of the fossil record.^[8]

• Climate envelope modeling: relies on statistical correlations between existing species distributions and environmental variables to define a species' tolerance.^[9] Envelopes of tolerance are then drawn around existing ranges. By predicting future levels of factors such as temperature, rainfall, and salinity, new range boundaries are then predicted. These methods are good for examining large numbers of species, but are likely not a good means of predicting effects at fine scales.

• Niche level modeling: is a newer method which links physiological information about a species to models of animal and plant body temperature.^[10][11] In contrast to “climate envelope” approaches, environmental variables are predicted at the level of the niche and are therefore much more exact.^[5] However, the approach is also usually more time consuming.^[9]

An ecosystem in which a species resides is dependent on a range of environmental conditions, a climate envelope, that allow the species to successfully survive and reproduce. A species climate envelope incorporates a range of temperatures, the effects of invading species, and the physiological stress brought on by climate change.^[12] Biologists create climate envelope models which predict both the responses and impacts on biological systems from global climate change. There are two methods involved in producing a climate envelope, Metapopulation Modeling and Coupled Map Lattice Modeling.

Metapopulation Models investigate individual isolated patches of habitat within ecosystems. A Metapopulation consists of a set of isolated populations of the same species living in different patches of habitat within an ecosystem.^[13] These isolated populations are connected through migrating individuals. Using metapopulation dynamics to create climate envelope models, biologists can predict how a species disperses using patch networks and whether or not a species is able to migrate as a group or as individuals. Migration between patches of fragmented habitat, which are used by species to reproduce and seek resources, is based on population size and location.^[14] Corridors allow species to travel back and forth between ecosystems, seek resources, new habitats, and regroup with larger populations.^[15]

Predicting the change in climate of an ecosystem on a particular patch of habitat allows biologists to predict the movement of a population of species. There are two fundamental parameters which metapopulation models use to investigate how a species disperses, colonization or extinction.^[16] The smaller the population size the more prone is it to become extinct. Species depend on each other as dispersal agent to migrate, and a small population size deters this process.^[17]

Coupled Map Lattice Modeling (CML), is a representation much like a map, of the landscape structure of networks of surrounding ecosystems.^[18] These models portray ecosystems on topographical and terrestrial scales. The main concern of this model is to determine how landscape ecology affects a species’ ability to migrate to a new ecosystem and at what rate they are able to move. A CML is used to reference the general size, and longitudinal and latitudinal coordinates of ecosystems.

The key characteristics which develop a CML are the growth rate and carrying capacity of an ecosystem.^[19] Since a CML can be used to determine the general size of an existing ecosystem, biologists can then predict the amount of space available for both existing and invading species. A CML is a vital part in determining a climate envelope model, because it estimates an ecosystem’s carrying capacity to current and new species that live under similar suitable climate envelopes. Biologists conduct studies on particular ecosystems that measure the number of existing species and the number of invading species seeking similar environmental climate conditions.

If an ecosystem is at capacity, current species will either be forced to move to a different location because of invading species, or invading species will be forced to seek alternate ecosystem to migrate to.^[20] A CML demonstrates available ecosystems where species can migrate to given that the ecosystem has the capacity and supports the species’ similar environmental climate conditions.

Forecasting examples

Biodiversity

Using fossil evidence, studies have shown that vertebrate biodiversity has grown exponentially through Earth's history and that biodiversity is entwined with the diversity of Earth's habitats.

"Animals have not yet invaded 2/3 of Earth's habitats, and it could be that without human influence biodiversity will continue to increase in an exponential fashion." —Sahney et al.^[8]

Temperature

Forecasts of temperature, shown in the diagram at the right as colored dots, along the North Island of New Zealand in the austral summer of 2007. As per the temperature scale shown at the bottom, intertidal temperatures were forecast to exceed 30°C at some locations on February 19; surveys later showed that these sites corresponded to large die-offs in burrowing sea urchins.

See also

• Ecosystem model
• Census of Marine Life
• Climate Change
• NaGISA
• GLOBEC
• Mathematical biology
• Biostatistics

Notes

1. ^ ^{a b} Clark et al. 2001
2. ^ "Joint science academies' statement: The science of climate change" (ASP). Royal Society. 2001-05-17. http://www.royalsoc.ac.uk/displaypagedoc.asp?id=13619. Retrieved 2007-04-01. "The work of the Intergovernmental Panel on Climate Change (IPCC) represents the consensus of the international scientific community on climate change science"
3. ^ "Rising to the climate challenge". Nature 449 (7164): 755. 2007-10-18. doi:10.1038/449755a. PMID 17943093. http://www.nature.com/nature/journal/v449/n7164/full/449755a.html. Retrieved 2007-11-06.
4. ^ CCSP 2008
5. ^ ^{a b} Kearney 2006
6. ^ Gilman et al. 2006
7. ^ Wethey and Woodin 2008
8. ^ ^{a b} Sahney, S., Benton, M.J. and Ferry, P.A. (2010). "Links between global taxonomic diversity, ecological diversity and the expansion of vertebrates on land" (PDF). Biology Letters 6 (4): 544–547. doi:10.1098/rsbl.2009.1024. PMC 2936204. PMID 20106856. http://rsbl.royalsocietypublishing.org/content/6/4/544.full.pdf+html.
9. ^ ^{a b} Pearson and Dawson 2003
10. ^ Kearney et al. 2008
11. ^ Helmuth et al. 2006
12. ^ "Error: no |title= specified when using {{ }}". http://onlinelibrary.wiley.com/doi/10.1111/j.1365-2486.2005.01000.x/pdf.
13. ^ "Error: no |title= specified when using {{ }}". http://www.ma.utexas.edu/users/davis/375/popecol/lec12/metpop.html.
14. ^ "Error: no |title= specified when using {{ }}". http://en.wikipedia.org/wiki/Patch_dynamics.
15. ^ "Error: no |title= specified when using {{ }}". http://en.wikipedia.org/wiki/Habitat_corridor.
16. ^ "Error: no |title= specified when using {{ }}". http://web.ebscohost.com/ehost/pdfviewer/pdfviewer?sid=12652a53-068b-4bd3-b658-bfdcc1a1e0fa%40sessionmgr113&vid=6&hid=122.
17. ^ "Error: no |title= specified when using {{ }}". http://www.jstor.org/stable/4223647.
18. ^ "Error: no |title= specified when using {{ }}". http://www.ncbi.nlm.nih.gov/pmc/articles/PMC1689208/pdf/V4WTPR2H93JLPX8M_265_1325.pdf.
19. ^ "Error: no |title= specified when using {{ }}". http://web.ebscohost.com/ehost/pdfviewer/pdfviewer?sid=12652a53-068b-4bd3-b658-bfdcc1a1e0fa%40sessionmgr113&vid=6&hid=122.
20. ^ "Error: no |title= specified when using {{ }}". http://eco.confex.com/eco/2010/techprogram/P24857.HTM.

References

• CCSP, 2008. The effects of climate change on agriculture, land resources, water resources, and biodiversity. A Report by the U.S. Climate Change Science Program and the Subcommittee on Global Change Research., P. Backlund, A. Janetos, D. Schimel, J. Hatfield, K. Boote, P. Fay, L. Hahn, C. Izaurralde, B.A. Kimball, T. Mader, J. Morgan, D. Ort, W. Polley, A. Thomson, D. Wolfe, M. Ryan, S. Archer, R. Birdsey, C. Dahm, L. Heath, J. Hicke, D. Hollinger, T. Huxman, G. Okin, R. Oren, J. Randerson, W. Schlesinger, D. Lettenmaier, D. Major, L. Poff, S. Running, L. Hansen, D. Inouye, B.P. Kelly, L Meyerson, B. Peterson, R. Shaw. U.S. Environmental Protection Agency, Washington, D.C. 362 pp. Available online at [1]
• Clark J.S. et al. (2001). "Ecological forecasts: an emerging imperative". Science 293 (5530): 657–660. doi:10.1126/science.293.5530.657. PMID 11474103.
• Gilman S.E., Wethey D.S., Helmuth B. (2006). "Variation in the sensitivity of organismal body temperature to climate change over local and geographic scales". Proceedings of the National Academy of Sciences 103 (25): 9560–9565. doi:10.1073/pnas.0510992103.
• Helmuth, B., N. Mieszkowska, P. Moore and S.J. Hawkins. 2006. Living on the edge of two changing worlds: forecasting the responses of rocky intertidal ecosystems to climate change. Annual Review of Ecolology Evolution and Systematics 37: 373-404. [2]
• Kearney M (2006). "Habitat, environment and niche: what are we modelling?". Oikos 115 (1): 186–191. doi:10.1111/j.2006.0030-1299.14908.x.
• Kearney M, Phillips B.L., Tracy C.R., Christian K.A., Betts G., Porter W.P. (2008). "Modelling species distributions without using species distributions: the cane toad in Australia under current and future climates". Ecography 31 (4): 423–434. doi:10.1111/j.0906-7590.2008.05457.x.
• Oreskes N (2004). "The scientific consensus on climate change". Science 306: 1686.
• 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 (5): 361–371. doi:10.1046/j.1466-822X.2003.00042.x.
• Wethey, D.S,. and S.A. Woodin. 2008. Ecological hindcasting of biogeographic responses to climate change in the European intertidal zone. Hydrobiologia 606:139-151. [3]

External links

• NASA Ecological Forecasting
• NOAA Ecological Forecasting
• Ecological Forecasting at The University of South Carolina

Categories: Environmental science | Fisheries science

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