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Diversity: alpha – beta – gamma

Diversity: alpha – beta – gamma. Beta diversity is a concept that helps us to cope with the fact that not every species lives everywhere. Whittaker 1972.  =   avg. Lande 1996.  =  avg + . Beta diversity indices. Koleff et al. 2003 J anim Ecol 72:367. Jaccard. Sorensen. 1-.

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Diversity: alpha – beta – gamma

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  1. Diversity: alpha – beta – gamma

  2. Beta diversity is a concept that helps us to cope with the fact that not every species lives everywhere Whittaker 1972  = avg Lande 1996  = avg+ 

  3. Beta diversity indices Koleff et al. 2003 J anim Ecol 72:367

  4. Jaccard Sorensen 1- "Broad sense" measures incorporate differences in species richness as well as differences in composition Lennon et al. "Narrow sense" measures independent of differences in species richness Example 1 a = 10, b = 10, c = 100 Jaccard = 10/120 = 0.08 Sorensen = 20/130 = 0.15 Lennon = 1- 10/20 = 0.5 Example 2 a = 10, b = 10, c = 1000 Jaccard = 10/1020 = 0.010 Sorensen = 20/1030 = 0.019 Lennon = 1- 10/20 = 0.5 Koleff et al. 2003 J anim Ecol 72:367

  5. Beta diversity along e.g. latitudinal gradient: • change in community composition measured by beta diversity • change in beta diversity

  6. Latitudinal gradient in alpha diversity – owls Koleff et al. 2003

  7. Latitudinal gradient in A, B, C parameters – owls for adjacent pairs of quadrats A focal area C B Koleff et al. 2003

  8. Beta diversity A/(A+B+C) of owls along latitudinal gradient Koleff et al. 2003

  9. Beta diversity of vertebrates Birds Mammals Amphibians decrease in species overlap over 500 km

  10. Beta diversity and optimum selection of protected areas richness-based algorithm rarity-based algorithm Reyers et al. 2000 • select the most species rich plot • add the plot bringing the highest number of new species • select the plot with the rarest species • add the plot with the rarest unrepresented species

  11. Causes of species turnover in space Speciation and dispersal limitation: species migration ability vs. barriers Habitat availability: biotic and abiotic resources and limiting factors Biological interactions: competitive exclusion from suitable habitats Apparent species turnover: species too rare to be sampled

  12. Speciation and dispersal limitation:the Hubbell’s (2001) neutral model - all species ecologically identical - species turnover generated by dispersal limitation The probability F(r) that 2 trees r km apart are conspecific is modelled as depending on: speciation rate , mean dispersal distance  and population density  is predicted to decrease linearly with log r

  13. Habitat availability:altitudinal gradient, the mother of all environmental gradients

  14. Two modes of altitudinal species turnover: with complete nestedness and zero nestedness Identical altitudinal trends in species richness mean different trends in mean altitudinal range of species and beta diversity between adjacent altitudes

  15. Species turnover along altitudinal gradients: Rhododendron spp. on Mt. Kinabalu Rhododendrones: 900 spp. worldwide, 300 spp. in SE Asia, 50 spp. in Borneo, 25 spp. on Mt. Kinabalu, incl. 5 endemic spp.

  16. Altitudinal distribution of 454 bird species in Papua New Guinea 0 m asl. 4500 m asl. each row is 100 m elevation belt, each column a bird species K. Tvardikova, unpubl. data

  17. Biological interactions:“checkerboard” distributions Altitudinal segregation of competing parrots in New Guinea: Language distribution among tribal societies:

  18. “Checkeboard distribution” - not predicted by island biogeography M. nigrirostris M. mackinlayi Cockoo-dove Macropygia mackinlayi and M. nigrirostris Diamond, J.M. (1975) Community Ecology

  19. Checkerboard distribution: Zosterops birds in New Guinea

  20. Zosterops chloris Zosterops atriceps

  21. Herpetofauna on British Virgin Islands: a nested pattern of species distribution

  22. Nestedness can be used to determine extinction probabilities species islands (a) a maximally cold matrix, (b) actual data, small mammals in Rocky Mts., (c), (d) matrices randomly filled under successively relaxed constraints [Patterson & Atmar 1986].

  23. Matrix temperature T U = 1/(mn) i j uij T = U/Umax * 100

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