Occupancy frequency distribution
Inmacroecologyandcommunity ecology,anoccupancy frequency distribution(OFD) is the distribution of the numbers of species occupying different numbers of areas.[1]It was first reported in 1918 by the Danish botanistChristen C. Raunkiærin his study on plant communities. The OFD is also known as the species-range size distribution in literature.[2][3]
Bimodality
[edit]A typical form of OFD is abimodal distribution,indicating thespeciesin a community is either rare or common, known as Raunkiaer's law of distribution of frequencies.[4]That is, with each species assigned to one of five 20%-wide occupancy classes, Raunkiaer's law predicts bimodal distributions within homogenous plant formations withmodesin the first (0-20%) and last (81-100%) classes.[4]Although Raunkiaer's law has long been discounted as an index of plant community homogeneity,[5]the method of using occupancy classes to construct OFDs is still commonly used for both plant and animal assemblages.Henry Gleasoncommented on this law in a 1929Ecologyarticle: "In conclusion we may say that Raunkiaer's law is merely an expression of the fact that in any association there are more species with few individuals than with many, that the law is most apparent whenquadratsare chosen of the most serviceable size to show frequency, and that it is obscured or lost if the quadrats are either too large or too small. "[6]Evidently, there are different shapes of OFD found in literature. Tokeshi reported that approximately 46% of observations have aright-skewedunimodal shape,27% bimodal, and 27%uniform.[7]A recent study reaffirms about 24% bimodal OFDs in among 289 real communities.[8]
Factors
[edit]As pointed out by Gleason,[6]the variety shapes of OFD can be explained, to a large degree, by the size of the sampling interval. For instance, McGeoch and Gaston (2002)[1]show that the number of satellite (rare) species declines with the increase of sampling grains, but the number of core (common) species increases, showing a tendency from a bimodal OFD towards a right-skewed unimodal distribution. This is becausespecies range,measured as occupancy, is strongly affected by the spatial scale and its aggregation structure,[9]known often as thescaling pattern of occupancy.Such scale dependence of occupancy has a profound effect on other macroecological patterns, such as theoccupancy-abundance relationship.
Other factors that have been proposed to be able to affect the shape of OFD include the degree of habitat heterogeneity,[10][11]species specificity,[12]landscape productivity,[13]position in the geographic range,[14]species dispersal ability[15]and the extinction–colonization dynamics.[16]
Mechanisms
[edit]Three basic models have been proposed to explain the bimodality found in occupancy frequency distributions.
Sampling results
[edit]Random sampling of individuals from eitherlognormalorlog-seriesrank abundance distributions (where random choice of an individual from a given species was proportional to its frequency) may produce bimodal occupancy distributions.[4][17]This model is not particularly sensitive or informative as to the mechanisms generating bimodality in occupancy frequency distributions, because the mechanisms generating the lognormalspecies abundancedistribution are still under heavy debate.
Core-satellite hypothesis
[edit]Bimodality may be generated by colonization-extinction metapopulation dynamics associated with a strongrescue effect.[16][18]This model is appropriate to explain the range structure of a community that is influenced by metapopulation processes, such as dispersal andlocal extinction.[19]However, it is not robust because the shape of the occupancy frequency distribution generated by this model is highly sensitive to species immigration and extinction parameters.[7][20]The metapopulation model does also not explain scale dependence in the occupancy frequency distribution.
Occupancy probability transition
[edit]The third model that describes bimodality in the occupancy frequency distribution is based on thescaling pattern of occupancyunder aself-similarassumption of species distributions (called the occupancy probability transition [OPT] model).[21][22]The OPT model is based on Harte et al.'s bisection scheme[23](although not on their probability rule) and the recursion probability of occupancy at different scales. The OPT model has been shown to support two empirical observations:[21]
- That bimodality is prevalent in interspecific occupancy frequency distributions.
- that the number of satellite species in the distribution increases towards finer scales.
The OPT model demonstrates that the sample grain of a study, sampling adequacy, and the distribution of species saturation coefficients (a measure of the fractal dimensionality of a species distribution) in a community are together largely able to explain the patterns commonly found in empirical occupancy distributions.Huiand McGeoch (2007) further show that the self-similarity in species distributions breaks down according to a power relationship with spatial scales, and we therefore adopt a power-scaling assumption for modeling species occupancy distributions.[22]The bimodality in occupancy frequency distributions that is common in species communities, is confirmed to a result for certain mathematical and statistical properties of the probability distribution of occupancy. The results thus demonstrate that the use of the bisection method in combination with a power-scaling assumption is more appropriate for modeling species distributions than the use of a self-similarity assumption, particularly at fine scales. This model further provokes the Harte-Maddux debate: Harte et al.[23]demonstrated that thepower lawform of thespecies–area relationshipmay be derived from a bisected, self-similar landscape and a community-level probability rule.[24]However, Maddux[25][26]showed that this self-similarity model generates biologically unrealistic predictions.Huiand McGeoch (2008) resolve the Harte–Maddux debate by demonstrating that the problems identified by Maddux result from an assumption that the probability of occurrence of a species at one scale is independent of its probability of occurrence at the next, and further illustrate the importance of considering patterns of species co-occurrence, and the way in which species occupancy patterns change with scale, when modeling species distributions.[27]
See also
[edit]References
[edit]- ^abMcGeoch, Melodie A.; Kevin J. Gaston (August 2002). "Occupancy frequency distributions: patterns, artefacts and mechanisms".Biological Reviews.77(3): 311–331.doi:10.1017/S1464793101005887.PMID12227519.S2CID25363161.
- ^Gaston, Kevin J. (May 1996). "Species-range size distributions: patterns, mechanisms and implications".Trends in Ecology and Evolution.11(5): 197–201.doi:10.1016/0169-5347(96)10027-6.PMID21237808.
- ^Gaston, Kevin J. (February 1998)."Species-range size distributions: products of speciation, extinction and transformation".Philosophical Transactions of the Royal Society B: Biological Sciences.353(1366): 219–230.doi:10.1098/rstb.1998.0204.JSTOR56474.PMC1692215.
- ^abcPapp, László; János Izsák (May 1997). "Bimodality in occurrence classes: a direct consequence of lognormal or logarithmic series distribution of abundances: a numerical experimentation".Oikos.79(1): 191–194.Bibcode:1997Oikos..79..191P.doi:10.2307/3546107.JSTOR3546107.
- ^McIntosh, Robert P. (July 1962). "Raunkiaer's 'Law of Frequency'".Ecology.43(3): 533–535.Bibcode:1962Ecol...43..533M.doi:10.2307/1933384.JSTOR1933384.
- ^abGleason, H.A. (October 1929). "The significance of Raunkiaer's law of frequency".Ecology.10(4): 406–408.Bibcode:1929Ecol...10..406G.doi:10.2307/1931149.JSTOR1931149.
- ^abTokeshi, Mutsunori (1992)."Dynamics of distribution in animal communities: theory and analysis"(PDF).Researches on Population Ecology.34(2): 249–273.Bibcode:1992PopEc..34..249T.doi:10.1007/BF02514796.S2CID22912914.
- ^Hui, C (2012). "Scale effect and bimodality in the frequency distribution of species occupancy".Community Ecology.13(1): 30–35.doi:10.1556/ComEc.13.2012.1.4.hdl:10019.1/118330.
- ^Hui, Cang; Ruan Veldtman; Melodie A. McGeoch (February 2010). "Measures, perceptions and scaling patterns of aggregated species distributions".Ecography.33(1): 95–102.Bibcode:2010Egogr..33...95H.doi:10.1111/j.1600-0587.2009.05997.x.hdl:10019.1/117498.
- ^Raunkiær, Christen C.(1934).The life forms of plants and statistical plant geography: Being the collected papers of C. Raunkiær.Humphrey Gilbert-Carter et al., translators. Oxford: Clarendon Press.
- ^Brown, James H. (August 1994)."On the relationship between abundance and distribution of species"(PDF).The American Naturalist.124(4): 255–279.doi:10.1086/284267.JSTOR2461494.S2CID84276000.Retrieved2010-08-10.
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- ^Maurer, Brian A. (June 1990). "The relationship between distribution and abundance in a patchy environment".Oikos.58(2): 181–189.Bibcode:1990Oikos..58..181M.doi:10.2307/3545425.JSTOR3545425.
- ^Williams, Paul H. (May 1988). "Habitat use by bumble bees (Bombusspp.) ".Ecological Entomology.13(2): 223–237.Bibcode:1988EcoEn..13..223W.doi:10.1111/j.1365-2311.1988.tb00350.x.S2CID86675852.
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- ^Storch, David; Arnošt L. Šizling (August 2002)."Patterns of commonness and rarity in central European birds: reliability of the core-satellite hypothesis within a large scale"(PDF).Ecography.25(4): 405–416.doi:10.1034/j.1600-0587.2002.250403.x.JSTOR3683551.
- ^Scheiner, Samuel M.; José M. Rey-Benayas (1997). "Placing empirical limits on metapopulation models for terrestrial plants".Evolutionary Ecology.11(3): 275–288.doi:10.1023/A:1018464319460.S2CID22440639.
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