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Robert J Whittaker - One of the best experts on this subject based on the ideXlab platform.
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habitat fragmentation and the species area Relationship a focus on total species richness obscures the impact of habitat loss on habitat specialists
Diversity and Distributions, 2014Co-Authors: Thomas J Matthews, Eden H W Cotteejones, Robert J WhittakerAbstract:Aim The species–area Relationship (SAR) is widely used in conservation science to predict the number of species likely to go extinct as a result of habitat loss. Often, studies employing the SAR use total species richness as the dependent variable. However, this overlooks the fact that habitat specialists and generalists differ in their susceptibility to habitat loss. We undertook a synthetic review of 23 habitat island datasets for birds to determine the impact of habitat generalists on the SAR. Location Global. Methods We sourced 19 habitat island datasets from the literature and combined these data with four of our own empirically gathered datasets. For each dataset, we classified all bird species as either forest habitat specialists or generalists. We then fitted the power SAR model (log–log and nonlinear forms) to the specialists, generalists and all species for each dataset and compared the resulting model parameters. We compared differences in the rate of change in richness with area between specialists and generalists using the first derivative of a multimodel SAR. Results We found that the slope of the power model was steeper for habitat specialists in the majority of datasets, and this difference was significant in 15 and 16 of the 23 datasets, for the nonlinear and log–log forms of the power model, respectively. Comparison of the multimodel SAR curve derivatives revealed further differences in the rate of change in species richness with area between subsets. Main conclusions The z values of both forms of the power model of the specialists' SARs were generally larger, often considerably so, than the values used in most SAR studies predicting extinctions from habitat loss. Thus, studies that have used z values derived from SAR studies using total richness may be underestimating the impact of habitat loss on specialist species, which are likely to be those of greatest conservation concern.
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thresholds and the species area Relationship a synthetic analysis of habitat island datasets
Journal of Biogeography, 2014Co-Authors: Thomas J Matthews, Robert J Whittaker, Manuel J Steinbauer, Elli Tzirkalli, Kostas A TriantisAbstract:Aim The application of island biogeography theory in habitat fragmentation research assumes a simple Relationship between species richness and fragment area. However, previous work has suggested that in some cases thresholds can be detected, at which the form of the island species–area Relationship (ISAR) changes abruptly. Piecewise regression has been advocated as a suitable statistical technique to model such thresholds. Here we first provide a comparative analysis of piecewise regression models to determine the prevalence and type of thresholds in habitat island ISARs. Second, we evaluate piecewise regression as a method for locating thresholds in the ISAR, with particular emphasis on the implications of data transformation. Location World-wide. Methods Seventy-six habitat island datasets were sourced from the literature. An information theoretic approach was employed to compare linear regression ISAR models with piecewise regression models. The models were applied to untransformed (species–area), semi-log (species–log area) and log–log (log species–log area) data. Three types of piecewise regression models were evaluated: continuous, discontinuous and zero slope. Model performance was compared using the Akaike information criterion. We also examined the influence on model performance of taxon, number of habitat islands, and area of smallest island. Results Linear regression models performed best, although piecewise models were preferred in a number of cases. Cases in which no model was significant were most prevalent in untransformed space relative to the semi-log and log–log transformations. Piecewise fits were more prevalent in datasets with a larger numbers of islands. Main conclusions Data transformation is a key part of model selection and needs to be explicitly considered, especially in terms of drawing inferences from models. Piecewise models, even if selected as the favoured model in our analyses, were often ecologically unintelligible in relation to area alone. When detected, breakpoint values ranged over five orders of magnitude, although with one exception all were under 50 ha. Our findings highlight the limitations of using individual threshold values to inform conservation practice.
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biodiversity conservation uncertainty in predictions of extinction risk
Nature, 2004Co-Authors: Wilfried Thuiller, Robert J Whittaker, Miguel B Araujo, Richard G Pearson, Lluis Brotons, Sandra LavorelAbstract:Arising from: C. D. Thomas et al. Nature 427, 145–148 (2004); see also communication from Buckley & Roughgarden and communication from Harte et al.;Thomas et al. reply Thomas et al.1 model species-distribution responses to a range of climate-warming scenarios and use a novel application of the species–area Relationship to estimate that 15–37% of modelled species in various regions of the world will be committed to extinction by 2050. Although we acknowledge the efforts that they make to measure the uncertainties associated with different climate scenarios, species' dispersal abilities and z values (predictions ranged from 5.6% to 78.6% extinctions), we find that two additional sources of uncertainty may substantially increase the variability in predictions.
Thomas J Matthews - One of the best experts on this subject based on the ideXlab platform.
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habitat fragmentation and the species area Relationship a focus on total species richness obscures the impact of habitat loss on habitat specialists
Diversity and Distributions, 2014Co-Authors: Thomas J Matthews, Eden H W Cotteejones, Robert J WhittakerAbstract:Aim The species–area Relationship (SAR) is widely used in conservation science to predict the number of species likely to go extinct as a result of habitat loss. Often, studies employing the SAR use total species richness as the dependent variable. However, this overlooks the fact that habitat specialists and generalists differ in their susceptibility to habitat loss. We undertook a synthetic review of 23 habitat island datasets for birds to determine the impact of habitat generalists on the SAR. Location Global. Methods We sourced 19 habitat island datasets from the literature and combined these data with four of our own empirically gathered datasets. For each dataset, we classified all bird species as either forest habitat specialists or generalists. We then fitted the power SAR model (log–log and nonlinear forms) to the specialists, generalists and all species for each dataset and compared the resulting model parameters. We compared differences in the rate of change in richness with area between specialists and generalists using the first derivative of a multimodel SAR. Results We found that the slope of the power model was steeper for habitat specialists in the majority of datasets, and this difference was significant in 15 and 16 of the 23 datasets, for the nonlinear and log–log forms of the power model, respectively. Comparison of the multimodel SAR curve derivatives revealed further differences in the rate of change in species richness with area between subsets. Main conclusions The z values of both forms of the power model of the specialists' SARs were generally larger, often considerably so, than the values used in most SAR studies predicting extinctions from habitat loss. Thus, studies that have used z values derived from SAR studies using total richness may be underestimating the impact of habitat loss on specialist species, which are likely to be those of greatest conservation concern.
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thresholds and the species area Relationship a synthetic analysis of habitat island datasets
Journal of Biogeography, 2014Co-Authors: Thomas J Matthews, Robert J Whittaker, Manuel J Steinbauer, Elli Tzirkalli, Kostas A TriantisAbstract:Aim The application of island biogeography theory in habitat fragmentation research assumes a simple Relationship between species richness and fragment area. However, previous work has suggested that in some cases thresholds can be detected, at which the form of the island species–area Relationship (ISAR) changes abruptly. Piecewise regression has been advocated as a suitable statistical technique to model such thresholds. Here we first provide a comparative analysis of piecewise regression models to determine the prevalence and type of thresholds in habitat island ISARs. Second, we evaluate piecewise regression as a method for locating thresholds in the ISAR, with particular emphasis on the implications of data transformation. Location World-wide. Methods Seventy-six habitat island datasets were sourced from the literature. An information theoretic approach was employed to compare linear regression ISAR models with piecewise regression models. The models were applied to untransformed (species–area), semi-log (species–log area) and log–log (log species–log area) data. Three types of piecewise regression models were evaluated: continuous, discontinuous and zero slope. Model performance was compared using the Akaike information criterion. We also examined the influence on model performance of taxon, number of habitat islands, and area of smallest island. Results Linear regression models performed best, although piecewise models were preferred in a number of cases. Cases in which no model was significant were most prevalent in untransformed space relative to the semi-log and log–log transformations. Piecewise fits were more prevalent in datasets with a larger numbers of islands. Main conclusions Data transformation is a key part of model selection and needs to be explicitly considered, especially in terms of drawing inferences from models. Piecewise models, even if selected as the favoured model in our analyses, were often ecologically unintelligible in relation to area alone. When detected, breakpoint values ranged over five orders of magnitude, although with one exception all were under 50 ha. Our findings highlight the limitations of using individual threshold values to inform conservation practice.
Stephen P Hubbell - One of the best experts on this subject based on the ideXlab platform.
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species area Relationships always overestimate extinction rates from habitat loss
Nature, 2011Co-Authors: Stephen P HubbellAbstract:Extinction from habitat loss is the signature conservation problem of the twenty-first century. Despite its importance, estimating extinction rates is still highly uncertain because no proven direct methods or reliable data exist for verifying extinctions. The most widely used indirect method is to estimate extinction rates by reversing the Species-Area accumulation curve, extrapolating backwards to smaller areas to calculate expected species loss. Estimates of extinction rates based on this method are almost always much higher than those actually observed. This discrepancy gave rise to the concept of an 'extinction debt', referring to species 'committed to extinction' owing to habitat loss and reduced population size but not yet extinct during a non-equilibrium period. Here we show that the extinction debt as currently defined is largely a sampling artefact due to an unrecognized difference between the underlying sampling problems when constructing a Species-Area Relationship (SAR) and when extrapolating species extinction from habitat loss. The key mathematical result is that the area required to remove the last individual of a species (extinction) is larger, almost always much larger, than the sample area needed to encounter the first individual of a species, irrespective of species distribution and spatial scale. We illustrate these results with data from a global network of large, mapped forest plots and ranges of passerine bird species in the continental USA; and we show that overestimation can be greater than 160%. Although we conclude that extinctions caused by habitat loss require greater loss of habitat than previously thought, our results must not lead to complacency about extinction due to habitat loss, which is a real and growing threat.
Erik Ockinger - One of the best experts on this subject based on the ideXlab platform.
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the landscape matrix modifies the effect of habitat fragmentation in grassland butterflies
Landscape Ecology, 2012Co-Authors: Erik Ockinger, Jochen Krauss, Mikko Kuussaari, Juha Poyry, Karlolof Bergman, Markus Franzen, Tomas Kadlec, Henrik G Smith, Ingolf Steffandewenter, Riccardo BommarcoAbstract:The landscape matrix is suggested to influence the effect of habitat fragmentation on species richness, but the generality of this prediction has not been tested. Here, we used data from 10 independent studies on butterfly species richness, where the matrix surrounding grassland patches was dominated by either forest or arable land to test if matrix land use influenced the response of species richness to patch area and connectivity. To account for the possibility that some of the observed species use the matrix as their main or complementary habitat, we analysed the effects on total species richness and on the richness of grassland specialist and non-specialist (generalists and specialists on other habitat types) butterflies separately. Specialists and non-specialists were defined separately for each dataset. Total species richness and the richness of grassland specialist butterflies were positively related to patch area and forest cover in the matrix, and negatively to patch isolation. The strength of the Species-Area Relationship was modified by matrix land use and had a slope that decreased with increasing forest cover in the matrix. Potential mechanisms for the weaker effect of grassland fragmentation in forest-dominated landscapes are (1) that the forest matrix is more heterogeneous and contains more resources, (2) that small grassland patches in a matrix dominated by arable land suffer more from negative edge effects or (3) that the arable matrix constitutes a stronger barrier to dispersal between populations. Regardless of the mechanisms, our results show that there are general effects of matrix land use across landscapes and regions, and that landscape management that increases matrix quality can be a complement to habitat restoration and re-creation in fragmented landscapes.
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life history traits predict species responses to habitat area and isolation a cross continental synthesis
Ecology Letters, 2010Co-Authors: Erik Ockinger, Oliver Schweiger, Thomas O Crist, Diane M Debinski, Jochen Krauss, Mikko Kuussaari, Jessica D Petersen, Juha Poyry, Josef Settele, Keith S SummervilleAbstract:There is a lack of quantitative syntheses of fragmentation effects across species and biogeographic regions, especially with respect to species life-history traits. We used data from 24 independent studies of butterflies and moths from a wide range of habitats and landscapes in Europe and North America to test whether traits associated with dispersal capacity, niche breadth and reproductive rate modify the effect of habitat fragmentation on species richness. Overall, species richness increased with habitat patch area and connectivity. Life-history traits improved the explanatory power of the statistical models considerably and modified the butterfly Species-Area Relationship. Species with low mobility, a narrow feeding niche and low reproduction were most strongly affected by habitat loss. This demonstrates the importance of considering life-history traits in fragmentation studies and implies that both species richness and composition change in a predictable manner with habitat loss and fragmentation.
Joao Augusto Alves Meiraneto - One of the best experts on this subject based on the ideXlab platform.
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relacion especie area y distribucion de la abundancia de especies en una comunidad vegetal de un inselberg tropical efecto del tamano de los parches
Revista De Biologia Tropical, 2018Co-Authors: Pedro Manuel Villa, Andreza Viana Neri, Lucas Siqueira Cardinelli, Luiz Fernando Silva Magnago, Gustavo Heringer, Primula Viana Campos, Alice Cristina Rodrigues, Sebastiao Venâncio Martins, Joao Augusto Alves MeiranetoAbstract:Species-Area relation and species abundance distribution in a plant community on a tropical inselberg : effect of patch size. Although inselbergs are iconic rock outcrops with a high biogeographic value, little is known about drivers responsible for the plant community assembly. The aim of this research was to evaluate how the patch size distribution of vegetation influences the Species-Area Relationship and species abundance distribution of a community in an inselberg of the “Piedra La Tortuga” Natural Monument of the Guayana region, Venezuela. In this context, three research questions were established: What is the effect of patch size on species richness? What Species-Area model (SAR) has the best fit in those vegetation patches? How is the distribution of species abundances (SADs) induced by the patch size distribution? A stratified random sampling was performed in patches ranging from 0.34 to 14.8 m 2 , totaling 40 sampling units (226 m 2 ). All individuals found in the 40 patches were identified at species level. The floristic composition in the different samples was represented by 19 families, 22 genera and 24 species, of which 50 % are endemic to inselbergs and two, are threatened of extinction. Two groups of patch sizes were identified (large 8-15 m 2 and small ≤ 7.9 m 2 ) in relation to the abundance and composition of species. The species accumulation curves for each patch size group show a contrasting tendency with marked differences in the observed richness among patch size groups. The curves of the SADs models had a significant adjustment of the geometric series in the two categories of patches. The SAR model of the power function presented the best Species-Area adjustments, where the increase in patch area accounted for 82 % of the variation in the increase in the number of species. The results of this study demonstrate for the first time how vegetation patches of a tropical inselberg have a strong influence on richness, abundance distribution and species composition. Likewise, it was determined that the SAD geometric model presented the best fit in the community as a function of patch size as a resource indicator, where the abundance of a species can be equivalent to a proportion of the space occupied. It is also presumed that changes in patch sizes could be associated with nutrient and water availability, as has been demonstrated in other dryland environments. In some studies it has been argued that variation in species composition among vegetation profiles of tropical inselbergs is mainly conditioned by habitat structure and water deficit. However, it had not been discussed how the size of patches of vegetation has an effect on richness. SADs and SAR analyzes can provide complementary explanations on community assembly in inselbergs . Rev. Biol. Trop. 66(2): 937-951. Epub 2018 June 01.
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relacion especie area y distribucion de la abundancia de especies en una comunidad vegetal de un inselberg tropical efecto del tamano de los parches
Revista De Biologia Tropical, 2018Co-Authors: Pedro Manuel Villa, Andreza Viana Neri, Lucas Siqueira Cardinelli, Luiz Fernando Silva Magnago, Gustavo Heringer, Primula Viana Campos, Alice Cristina Rodrigues, Sebastiao Venâncio Martins, Joao Augusto Alves MeiranetoAbstract:Species-Area relation and species abundance distribution in a plant community on a tropical inselberg : effect of patch size. Although inselbergs are iconic rock outcrops with a high biogeographic value, little is known about drivers responsible for the plant community assembly. The aim of this research was to evaluate how the patch size distribution of vegetation influences the Species-Area Relationship and species abundance distribution of a community in an inselberg of the “Piedra La Tortuga” Natural Monument of the Guayana region, Venezuela. In this context, three research questions were established: What is the effect of patch size on species richness? What Species-Area model (SAR) has the best fit in those vegetation patches? How is the distribution of species abundances (SADs) induced by the patch size distribution? A stratified random sampling was performed in patches ranging from 0.34 to 14.8 m 2 , totaling 40 sampling units (226 m 2 ). All individuals found in the 40 patches were identified at species level. The floristic composition in the different samples was represented by 19 families, 22 genera and 24 species, of which 50 % are endemic to inselbergs and two, are threatened of extinction. Two groups of patch sizes were identified (large 8-15 m 2 and small ≤ 7.9 m 2 ) in relation to the abundance and composition of species. The species accumulation curves for each patch size group show a contrasting tendency with marked differences in the observed richness among patch size groups. The curves of the SADs models had a significant adjustment of the geometric series in the two categories of patches. The SAR model of the power function presented the best Species-Area adjustments, where the increase in patch area accounted for 82 % of the variation in the increase in the number of species. The results of this study demonstrate for the first time how vegetation patches of a tropical inselberg have a strong influence on richness, abundance distribution and species composition. Likewise, it was determined that the SAD geometric model presented the best fit in the community as a function of patch size as a resource indicator, where the abundance of a species can be equivalent to a proportion of the space occupied. It is also presumed that changes in patch sizes could be associated with nutrient and water availability, as has been demonstrated in other dryland environments. In some studies it has been argued that variation in species composition among vegetation profiles of tropical inselbergs is mainly conditioned by habitat structure and water deficit. However, it had not been discussed how the size of patches of vegetation has an effect on richness. SADs and SAR analyzes can provide complementary explanations on community assembly in inselbergs . Rev. Biol. Trop. 66(2): 937-951. Epub 2018 June 01.