Ecological forecasting

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 for 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 affecting human and natural ecosystems.^[4]

One major challenge is to predict where, when and with what magnitude changes 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]

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

External image
Intertidal temperature forecasting University of South Carolina

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.

Notes

1 2 Clark et al. 2001
↑ "Joint science academies' statement: The science of climate change". Royal Society. 2001-05-17. Archived from the original on October 1, 2007. 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
↑ "Rising to the climate challenge". Nature. 449 (7164): 755. 2007-10-18. doi:10.1038/449755a. PMID 17943093. Retrieved 2007-11-06.
↑ CCSP 2008
1 2 Kearney 2006
↑ Gilman et al. 2006
↑ Wethey and Woodin 2008
1 2 Sahney, S.; Benton, M.J. & 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.
1 2 Pearson and Dawson 2003
↑ Kearney et al. 2008
↑ Helmuth et al. 2006

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
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 USA. 103 (25): 9560–9565. doi:10.1073/pnas.0510992103.
Helmuth, B.; N. Mieszkowska; P. Moore & 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 Ecology, Evolution, and Systematics. 37: 373–404. doi:10.1146/annurev.ecolsys.37.091305.110149.
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 (5702): 1686. doi:10.1126/science.1103618. PMID 15576594.
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,. & S.A. Woodin (2008). "Ecological hindcasting of biogeographic responses to climate change in the European intertidal zone". Hydrobiologia. 606: 139–151. doi:10.1007/s10750-008-9338-8.

External links

Ecology: Modelling ecosystems: Trophic components

General	Abiotic component Abiotic stress Behaviour Biogeochemical cycle Biomass Biotic component Biotic stress Carrying capacity Competition Ecosystem Ecosystem ecology Ecosystem model Keystone species List of feeding behaviours Metabolic theory of ecology Productivity Resource

Producers	Autotrophs Chemosynthesis Chemotrophs Foundation species Mixotrophs Myco-heterotrophy Mycotroph Organotrophs Photoheterotrophs Photosynthesis Photosynthetic efficiency Phototrophs Primary nutritional groups Primary production

Consumers	Apex predator Bacterivore Carnivores Chemoorganotroph Foraging Generalist and specialist species Intraguild predation Herbivores Heterotroph Heterotrophic nutrition Insectivore Mesopredator release hypothesis Omnivores Optimal foraging theory Predation Prey switching

Decomposers	Chemoorganoheterotrophy Decomposition Detritivores Detritus

Microorganisms	Archaea Bacteriophage Environmental microbiology Lithoautotroph Lithotrophy Microbial cooperation Microbial ecology Microbial food web Microbial intelligence Microbial loop Microbial mat Microbial metabolism Phage ecology

Food webs	Biomagnification Ecological efficiency Ecological pyramid Energy flow Food chain Trophic level

Example webs	Cold seeps Hydrothermal vents Intertidal Kelp forests Lakes North Pacific Subtropical Gyre Rivers San Francisco Estuary Soil Tide pool

Processes	Ascendency Bioaccumulation Cascade effect Climax community Competitive exclusion principle Consumer-resource systems Copiotrophs Dominance Ecological network Ecological succession Energy quality Energy Systems Language f-ratio Feed conversion ratio Feeding frenzy Mesotrophic soil Nutrient cycle Oligotroph Paradox of the plankton Trophic cascade Trophic mutualism Trophic state index

Defense/counter	Animal coloration Antipredator adaptations Camouflage Deimatic behaviour Herbivore adaptations to plant defense Mimicry Plant defense against herbivory Predator avoidance in schooling fish

Ecology: Modelling ecosystems: Other components

Population ecology	Abundance Allee effect Depensation Ecological yield Effective population size Intraspecific competition Logistic function Malthusian growth model Maximum sustainable yield Overpopulation in wild animals Overexploitation Population cycle Population dynamics Population modeling Population size Predator–prey (Lotka–Volterra) equations Recruitment Resilience Small population size Stability

Species	Biodiversity Density-dependent inhibition Ecological effects of biodiversity Ecological extinction Endemic species Flagship species Gradient analysis Indicator species Introduced species Invasive species Latitudinal gradients in species diversity Minimum viable population Neutral theory Occupancy–abundance relationship Population viability analysis Priority effect Rapoport's rule Relative abundance distribution Relative species abundance Species diversity Species homogeneity Species richness Species distribution Species-area curve Umbrella species

Species interaction	Antibiosis Biological interaction Commensalism Community ecology Ecological facilitation Interspecific competition Mutualism Storage effect

Spatial ecology	Biogeography Cross-boundary subsidy Ecocline Ecotone Ecotype Disturbance Edge effects Foster's rule Habitat fragmentation Ideal free distribution Intermediate Disturbance Hypothesis Island biogeography Landscape ecology Landscape epidemiology Landscape limnology Metapopulation Patch dynamics r/K selection theory Source–sink dynamics

Niche	Ecological niche Ecological trap Ecosystem engineer Environmental niche modelling Guild Habitat Marine habitats Limiting similarity Niche apportionment models Niche construction Niche differentiation

Other networks	Assembly rules Bateman's principle Bioluminescence Ecological collapse Ecological debt Ecological deficit Ecological energetics Ecological indicator Ecological threshold Ecosystem diversity Emergence Extinction debt Kleiber's law Liebig's law of the minimum Marginal value theorem Thorson's rule Xerosere

Other	Allometry Alternative stable state Balance of nature Biological data visualization Constructal theory Ecocline Ecological economics Ecological footprint Ecological forecasting Ecological humanities Ecological stoichiometry Ecopath Ecosystem based fisheries Endolith Evolutionary ecology Functional ecology Industrial ecology Macroecology Microecosystem Natural environment Regime shift Systems ecology Urban ecology Theoretical ecology

List of ecology topics

This article is issued from Wikipedia - version of the 8/6/2016. The text is available under the Creative Commons Attribution/Share Alike but additional terms may apply for the media files.