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Measuring the meltdown: drivers of global amphibian extinction and decline.

Sodhi NS, Bickford D, Diesmos AC, Lee TM, Koh LP, Brook BW, Sekercioglu CH, Bradshaw CJ - PLoS ONE (2008)

Bottom Line: We present the largest global analysis of roughly 45% of known amphibians (2,583 species) to quantify the influences of life history, climate, human density and habitat loss on declines and extinction risk.Elevated habitat loss and human densities are also correlated with high threat risk.These empirical results show that amphibian species with restricted ranges should be urgently targeted for conservation.

View Article: PubMed Central - PubMed

Affiliation: Department of Biological Sciences, National University of Singapore, Singapore, Singapore.

ABSTRACT
Habitat loss, climate change, over-exploitation, disease and other factors have been hypothesised in the global decline of amphibian biodiversity. However, the relative importance of and synergies among different drivers are still poorly understood. We present the largest global analysis of roughly 45% of known amphibians (2,583 species) to quantify the influences of life history, climate, human density and habitat loss on declines and extinction risk. Multi-model Bayesian inference reveals that large amphibian species with small geographic range and pronounced seasonality in temperature and precipitation are most likely to be Red-Listed by IUCN. Elevated habitat loss and human densities are also correlated with high threat risk. Range size, habitat loss and more extreme seasonality in precipitation contributed to decline risk in the 2,454 species that declined between 1980 and 2004, compared to species that were stable (n = 1,545) or had increased (n = 28). These empirical results show that amphibian species with restricted ranges should be urgently targeted for conservation.

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Predicted probabilities of population decline for the life history terms habit, spawning site, reproductive cycle, reproductive mode, presence/absence of parental care and fertilization type (derived from the nine-term model BS+RG+RG2+HB+SS+RC+RM+PC+FT based on the BIC-selected top-ranked model; see Table 2).The observed extinction probability 95% confidence interval (dotted horizontal lines) was determined by a 10,000 iteration bootstrap of the probabilities predicted by the above model over 3,052 species. Changes to extinction probability relative to each term level were calculated by adjusting the original dataset so that all species were given the same value for that level (each level value in turn), keeping all other terms in the model as in the original dataset. Error bars represent the 10,000 iteration bootstrapped upper 95% confidence limits. aq = aquatic, arb = arboreal/phytotelms, ter = terrestrial, aq-ter = aquatic & terrestrial, ovi = oviparious, ovoviv = ovoviviparous, dir dev = direct development. See text and Supplementary Table S3 for a description of variables.
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pone-0001636-g003: Predicted probabilities of population decline for the life history terms habit, spawning site, reproductive cycle, reproductive mode, presence/absence of parental care and fertilization type (derived from the nine-term model BS+RG+RG2+HB+SS+RC+RM+PC+FT based on the BIC-selected top-ranked model; see Table 2).The observed extinction probability 95% confidence interval (dotted horizontal lines) was determined by a 10,000 iteration bootstrap of the probabilities predicted by the above model over 3,052 species. Changes to extinction probability relative to each term level were calculated by adjusting the original dataset so that all species were given the same value for that level (each level value in turn), keeping all other terms in the model as in the original dataset. Error bars represent the 10,000 iteration bootstrapped upper 95% confidence limits. aq = aquatic, arb = arboreal/phytotelms, ter = terrestrial, aq-ter = aquatic & terrestrial, ovi = oviparious, ovoviv = ovoviviparous, dir dev = direct development. See text and Supplementary Table S3 for a description of variables.

Mentions: Drivers of population decline are often decoupled from stochastic factors that can cause eventual extinction [17], [21]. To distinguish these different processes, we also collected data from 4,027 species with known population trend data from 1980 and 2004 to determine if the same set of ecological, life history and environmental drivers that explained threat, also explained the probability of decline (2,454 declining, 1,545 stable and 28 increasing species). Generally agreeing with the IUCN threat status results, small geographic range and large body size were still correlated with a higher likelihood of population decline (Table 2; Fig. 1), but there was also evidence for a nonlinear (quadratic) effect of range (Table 2). Further, despite using Bayesian inference to identify the most important drivers of correlations, there were important additional tapering effects not identified in the threat-risk phase: habit, spawning site, reproductive cycle, reproductive mode, parental care and fertilization; these accounted for an additional ∼2.3% of deviance in decline risk above the body size and nonlinear range model (Table 2a). Aquatic and arboreal species, species with specific spawning requirements, aseasonal breeders, ovoviviparous species and species with external fertilization all appear to have higher risks of declining (Fig. 3).


Measuring the meltdown: drivers of global amphibian extinction and decline.

Sodhi NS, Bickford D, Diesmos AC, Lee TM, Koh LP, Brook BW, Sekercioglu CH, Bradshaw CJ - PLoS ONE (2008)

Predicted probabilities of population decline for the life history terms habit, spawning site, reproductive cycle, reproductive mode, presence/absence of parental care and fertilization type (derived from the nine-term model BS+RG+RG2+HB+SS+RC+RM+PC+FT based on the BIC-selected top-ranked model; see Table 2).The observed extinction probability 95% confidence interval (dotted horizontal lines) was determined by a 10,000 iteration bootstrap of the probabilities predicted by the above model over 3,052 species. Changes to extinction probability relative to each term level were calculated by adjusting the original dataset so that all species were given the same value for that level (each level value in turn), keeping all other terms in the model as in the original dataset. Error bars represent the 10,000 iteration bootstrapped upper 95% confidence limits. aq = aquatic, arb = arboreal/phytotelms, ter = terrestrial, aq-ter = aquatic & terrestrial, ovi = oviparious, ovoviv = ovoviviparous, dir dev = direct development. See text and Supplementary Table S3 for a description of variables.
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getmorefigures.php?uid=PMC2238793&req=5

pone-0001636-g003: Predicted probabilities of population decline for the life history terms habit, spawning site, reproductive cycle, reproductive mode, presence/absence of parental care and fertilization type (derived from the nine-term model BS+RG+RG2+HB+SS+RC+RM+PC+FT based on the BIC-selected top-ranked model; see Table 2).The observed extinction probability 95% confidence interval (dotted horizontal lines) was determined by a 10,000 iteration bootstrap of the probabilities predicted by the above model over 3,052 species. Changes to extinction probability relative to each term level were calculated by adjusting the original dataset so that all species were given the same value for that level (each level value in turn), keeping all other terms in the model as in the original dataset. Error bars represent the 10,000 iteration bootstrapped upper 95% confidence limits. aq = aquatic, arb = arboreal/phytotelms, ter = terrestrial, aq-ter = aquatic & terrestrial, ovi = oviparious, ovoviv = ovoviviparous, dir dev = direct development. See text and Supplementary Table S3 for a description of variables.
Mentions: Drivers of population decline are often decoupled from stochastic factors that can cause eventual extinction [17], [21]. To distinguish these different processes, we also collected data from 4,027 species with known population trend data from 1980 and 2004 to determine if the same set of ecological, life history and environmental drivers that explained threat, also explained the probability of decline (2,454 declining, 1,545 stable and 28 increasing species). Generally agreeing with the IUCN threat status results, small geographic range and large body size were still correlated with a higher likelihood of population decline (Table 2; Fig. 1), but there was also evidence for a nonlinear (quadratic) effect of range (Table 2). Further, despite using Bayesian inference to identify the most important drivers of correlations, there were important additional tapering effects not identified in the threat-risk phase: habit, spawning site, reproductive cycle, reproductive mode, parental care and fertilization; these accounted for an additional ∼2.3% of deviance in decline risk above the body size and nonlinear range model (Table 2a). Aquatic and arboreal species, species with specific spawning requirements, aseasonal breeders, ovoviviparous species and species with external fertilization all appear to have higher risks of declining (Fig. 3).

Bottom Line: We present the largest global analysis of roughly 45% of known amphibians (2,583 species) to quantify the influences of life history, climate, human density and habitat loss on declines and extinction risk.Elevated habitat loss and human densities are also correlated with high threat risk.These empirical results show that amphibian species with restricted ranges should be urgently targeted for conservation.

View Article: PubMed Central - PubMed

Affiliation: Department of Biological Sciences, National University of Singapore, Singapore, Singapore.

ABSTRACT
Habitat loss, climate change, over-exploitation, disease and other factors have been hypothesised in the global decline of amphibian biodiversity. However, the relative importance of and synergies among different drivers are still poorly understood. We present the largest global analysis of roughly 45% of known amphibians (2,583 species) to quantify the influences of life history, climate, human density and habitat loss on declines and extinction risk. Multi-model Bayesian inference reveals that large amphibian species with small geographic range and pronounced seasonality in temperature and precipitation are most likely to be Red-Listed by IUCN. Elevated habitat loss and human densities are also correlated with high threat risk. Range size, habitat loss and more extreme seasonality in precipitation contributed to decline risk in the 2,454 species that declined between 1980 and 2004, compared to species that were stable (n = 1,545) or had increased (n = 28). These empirical results show that amphibian species with restricted ranges should be urgently targeted for conservation.

Show MeSH
Related in: MedlinePlus