Suitable Habitat

14,000,000 Leading Edge Experts on the ideXlab platform

Scan Science and Technology

Contact Leading Edge Experts & Companies

Scan Science and Technology

Contact Leading Edge Experts & Companies

The Experts below are selected from a list of 49992 Experts worldwide ranked by ideXlab platform

André E. Punt - One of the best experts on this subject based on the ideXlab platform.

  • bayesian posterior prediction of the patchy spatial distributions of small pelagic fish in regions of Suitable Habitat
    Canadian Journal of Fisheries and Aquatic Sciences, 2015
    Co-Authors: Charlotte Boyd, Mathieu Woillez, Ramiro Castillo, Arnaud Bertrand, Sophie Bertrand, André E. Punt
    Abstract:

    Small pelagic fish aggregate within areas of Suitable Habitat to form patchy distributions with localized peaks in abundance. This presents challenges for geostatistical methods designed to investigate the processes underpinning the spatial distribution of stocks and simulate distributions for further analysis. In two-stage models, presence–absence is treated as separable and independent from the process explaining nonzero densities. This is appropriate where gaps in the distribution are attributable to one process and conditional abundance to another, but less so where patchiness is attributable primarily to the strong schooling tendencies of small pelagic fish within Suitable Habitat. We therefore developed a new modelling framework based on a truncated Gaussian random field (GRF) within a Bayesian framework. We evaluated this method using simulated test data and then applied it to acoustic survey data for Peruvian anchoveta (Engraulis ringens). We assessed the method’s performance in terms of posterior...

  • Bayesian posterior prediction of the patchy spatial distributions of small pelagic fish in regions of Suitable Habitat
    Canadian Journal of Fisheries and Aquatic Sciences, 2015
    Co-Authors: Charlotte Boyd, Mathieu Woillez, Ramiro Castillo, Arnaud Bertrand, Sophie Bertrand, André E. Punt
    Abstract:

    Small pelagic fish aggregate within areas of Suitable Habitat to form patchy distributions with localized peaks in abundance. This presents challenges for geostatistical methods designed to investigate the processes underpinning the spatial distribution of stocks and simulate distributions for further analysis. In two-stage models, presence-absence is treated as separable and independent from the process explaining nonzero densities. This is appropriate where gaps in the distribution are attributable to one process and conditional abundance to another, but less so where patchiness is attributable primarily to the strong schooling tendencies of small pelagic fish within Suitable Habitat. We therefore developed a new modelling framework based on a truncated Gaussian random field (GRF) within a Bayesian framework. We evaluated this method using simulated test data and then applied it to acoustic survey data for Peruvian anchoveta (Engraulis ringens). We assessed the method's performance in terms of posterior densities of spatial parameters, and the density distribution, spatial pattern, and overall spatial distribution of posterior predictions. We conclude that Bayesian posterior prediction based on a truncated GRF is effective at reproducing the patchiness of the observed spatial distribution of anchoveta.

Daniel J Rogers - One of the best experts on this subject based on the ideXlab platform.

  • predicting the distribution of a Suitable Habitat for the white stork in southern sweden identifying priority areas for reintroduction and Habitat restoration
    Animal Conservation, 2009
    Co-Authors: Ola Olsson, Daniel J Rogers
    Abstract:

    The loss of wetlands and semi-natural grasslands throughout much of Europe has led to a historic decline of species associated with these Habitats. The reinstatement of these Habitats, however, requires spatially explicit predictions of the most Suitable sites for restoration, to maximize the ecological benefit per unit effort. One species that demonstrates such declines is the white stork Ciconia ciconia, and the restoration of Habitat for this flagship species is likely to benefit a suite of other wetland and grassland biota. Storks are also being reintroduced into southern Sweden and elsewhere, and the a priori identification of Suitable sites for reintroduction will greatly improve the success of such programmes. Here a simple predictive Habitat-use model was developed, where only a small but reliable presence-only dataset was available. The model is based on the extent and relative soil moisture of semi-natural pastures, the extent of wetlands and the extent of hayfields in southern Sweden. Here the model was used to predict the current extent of stork Habitat that is Suitable for successful breeding, and the extent of Habitat that would become Suitable with moderate Habitat restoration. The Habitat model identifies all 10 occupied nesting sites where breeding is currently successful. It also identifies similar to 300 km(2) of Habitat that is predicted to be Suitable stork Habitat, but that is presently unused; these sites were identified as potential areas for stork reintroduction. The model also identifies over 100 areas where moderate Habitat restoration is predicted to have a disproportionate effect (relative to the restoration effort) on the area of Suitable Habitat for storks; these sites were identified as priorities for Habitat restoration. By identifying areas for reintroduction and restoration, such Habitat suitability models have the potential to maximize the effectiveness of such conservation programmes.

  • predicting the distribution of a Suitable Habitat for the white stork in southern sweden identifying priority areas for reintroduction and Habitat restoration
    Animal Conservation, 2009
    Co-Authors: Ola Olsson, Daniel J Rogers
    Abstract:

    The loss of wetlands and semi-natural grasslands throughout much of Europe has led to a historic decline of species associated with these Habitats. The reinstatement of these Habitats, however, requires spatially explicit predictions of the most Suitable sites for restoration, to maximize the ecological benefit per unit effort. One species that demonstrates such declines is the white stork Ciconia ciconia, and the restoration of Habitat for this flagship species is likely to benefit a suite of other wetland and grassland biota. Storks are also being reintroduced into southern Sweden and elsewhere, and the a priori identification of Suitable sites for reintroduction will greatly improve the success of such programmes. Here a simple predictive Habitat-use model was developed, where only a small but reliable presence-only dataset was available. The model is based on the extent and relative soil moisture of semi-natural pastures, the extent of wetlands and the extent of hayfields in southern Sweden. Here the model was used to predict the current extent of stork Habitat that is Suitable for successful breeding, and the extent of Habitat that would become Suitable with moderate Habitat restoration. The Habitat model identifies all 10 occupied nesting sites where breeding is currently successful. It also identifies similar to 300 km(2) of Habitat that is predicted to be Suitable stork Habitat, but that is presently unused; these sites were identified as potential areas for stork reintroduction. The model also identifies over 100 areas where moderate Habitat restoration is predicted to have a disproportionate effect (relative to the restoration effort) on the area of Suitable Habitat for storks; these sites were identified as priorities for Habitat restoration. By identifying areas for reintroduction and restoration, such Habitat suitability models have the potential to maximize the effectiveness of such conservation programmes.

Charlotte Boyd - One of the best experts on this subject based on the ideXlab platform.

  • bayesian posterior prediction of the patchy spatial distributions of small pelagic fish in regions of Suitable Habitat
    Canadian Journal of Fisheries and Aquatic Sciences, 2015
    Co-Authors: Charlotte Boyd, Mathieu Woillez, Ramiro Castillo, Arnaud Bertrand, Sophie Bertrand, André E. Punt
    Abstract:

    Small pelagic fish aggregate within areas of Suitable Habitat to form patchy distributions with localized peaks in abundance. This presents challenges for geostatistical methods designed to investigate the processes underpinning the spatial distribution of stocks and simulate distributions for further analysis. In two-stage models, presence–absence is treated as separable and independent from the process explaining nonzero densities. This is appropriate where gaps in the distribution are attributable to one process and conditional abundance to another, but less so where patchiness is attributable primarily to the strong schooling tendencies of small pelagic fish within Suitable Habitat. We therefore developed a new modelling framework based on a truncated Gaussian random field (GRF) within a Bayesian framework. We evaluated this method using simulated test data and then applied it to acoustic survey data for Peruvian anchoveta (Engraulis ringens). We assessed the method’s performance in terms of posterior...

  • Bayesian posterior prediction of the patchy spatial distributions of small pelagic fish in regions of Suitable Habitat
    Canadian Journal of Fisheries and Aquatic Sciences, 2015
    Co-Authors: Charlotte Boyd, Mathieu Woillez, Ramiro Castillo, Arnaud Bertrand, Sophie Bertrand, André E. Punt
    Abstract:

    Small pelagic fish aggregate within areas of Suitable Habitat to form patchy distributions with localized peaks in abundance. This presents challenges for geostatistical methods designed to investigate the processes underpinning the spatial distribution of stocks and simulate distributions for further analysis. In two-stage models, presence-absence is treated as separable and independent from the process explaining nonzero densities. This is appropriate where gaps in the distribution are attributable to one process and conditional abundance to another, but less so where patchiness is attributable primarily to the strong schooling tendencies of small pelagic fish within Suitable Habitat. We therefore developed a new modelling framework based on a truncated Gaussian random field (GRF) within a Bayesian framework. We evaluated this method using simulated test data and then applied it to acoustic survey data for Peruvian anchoveta (Engraulis ringens). We assessed the method's performance in terms of posterior densities of spatial parameters, and the density distribution, spatial pattern, and overall spatial distribution of posterior predictions. We conclude that Bayesian posterior prediction based on a truncated GRF is effective at reproducing the patchiness of the observed spatial distribution of anchoveta.

Ola Olsson - One of the best experts on this subject based on the ideXlab platform.

  • predicting the distribution of a Suitable Habitat for the white stork in southern sweden identifying priority areas for reintroduction and Habitat restoration
    Animal Conservation, 2009
    Co-Authors: Ola Olsson, Daniel J Rogers
    Abstract:

    The loss of wetlands and semi-natural grasslands throughout much of Europe has led to a historic decline of species associated with these Habitats. The reinstatement of these Habitats, however, requires spatially explicit predictions of the most Suitable sites for restoration, to maximize the ecological benefit per unit effort. One species that demonstrates such declines is the white stork Ciconia ciconia, and the restoration of Habitat for this flagship species is likely to benefit a suite of other wetland and grassland biota. Storks are also being reintroduced into southern Sweden and elsewhere, and the a priori identification of Suitable sites for reintroduction will greatly improve the success of such programmes. Here a simple predictive Habitat-use model was developed, where only a small but reliable presence-only dataset was available. The model is based on the extent and relative soil moisture of semi-natural pastures, the extent of wetlands and the extent of hayfields in southern Sweden. Here the model was used to predict the current extent of stork Habitat that is Suitable for successful breeding, and the extent of Habitat that would become Suitable with moderate Habitat restoration. The Habitat model identifies all 10 occupied nesting sites where breeding is currently successful. It also identifies similar to 300 km(2) of Habitat that is predicted to be Suitable stork Habitat, but that is presently unused; these sites were identified as potential areas for stork reintroduction. The model also identifies over 100 areas where moderate Habitat restoration is predicted to have a disproportionate effect (relative to the restoration effort) on the area of Suitable Habitat for storks; these sites were identified as priorities for Habitat restoration. By identifying areas for reintroduction and restoration, such Habitat suitability models have the potential to maximize the effectiveness of such conservation programmes.

  • predicting the distribution of a Suitable Habitat for the white stork in southern sweden identifying priority areas for reintroduction and Habitat restoration
    Animal Conservation, 2009
    Co-Authors: Ola Olsson, Daniel J Rogers
    Abstract:

    The loss of wetlands and semi-natural grasslands throughout much of Europe has led to a historic decline of species associated with these Habitats. The reinstatement of these Habitats, however, requires spatially explicit predictions of the most Suitable sites for restoration, to maximize the ecological benefit per unit effort. One species that demonstrates such declines is the white stork Ciconia ciconia, and the restoration of Habitat for this flagship species is likely to benefit a suite of other wetland and grassland biota. Storks are also being reintroduced into southern Sweden and elsewhere, and the a priori identification of Suitable sites for reintroduction will greatly improve the success of such programmes. Here a simple predictive Habitat-use model was developed, where only a small but reliable presence-only dataset was available. The model is based on the extent and relative soil moisture of semi-natural pastures, the extent of wetlands and the extent of hayfields in southern Sweden. Here the model was used to predict the current extent of stork Habitat that is Suitable for successful breeding, and the extent of Habitat that would become Suitable with moderate Habitat restoration. The Habitat model identifies all 10 occupied nesting sites where breeding is currently successful. It also identifies similar to 300 km(2) of Habitat that is predicted to be Suitable stork Habitat, but that is presently unused; these sites were identified as potential areas for stork reintroduction. The model also identifies over 100 areas where moderate Habitat restoration is predicted to have a disproportionate effect (relative to the restoration effort) on the area of Suitable Habitat for storks; these sites were identified as priorities for Habitat restoration. By identifying areas for reintroduction and restoration, such Habitat suitability models have the potential to maximize the effectiveness of such conservation programmes.

Henrik Andrén - One of the best experts on this subject based on the ideXlab platform.

  • Population responses to Habitat fragmentation: statistical power and the random sample hypothesis
    Oikos, 1996
    Co-Authors: Henrik Andrén
    Abstract:

    Oikos 76: 235-242. The random sample hypothesis states that small Habitat fragments are random samples from large ones. Therefore, the effect of Habitat fragmentation on population size is only related to pure Habitat loss, the area and isolation of Habitat fragments do not influence the population size in the landscape. An alternative hypothesis is that probability of occupation of a Habitat fragment is related to area and isolation of the Habitat fragment. Simulation models that included effects of area and isolation were used to investigate the effect of Habitat fragmentation on population survival in landscapes with different proportions of Suitable Habitat. Four different combinations of area sensitivity and dispersal ability were used. These models were used to estimate the statistical power to reject the random sample hypothesis. The statistical power to detect differences, between a model based on the random sample hypothesis and a model which included effects of Habitat fragment size and isolation between Habitat fragments on population survival, was low in landscapes with a high proportion of Suitable Habitat, but increased as the proportion of Suitable Habitat decreased. Therefore, the results of different tests that support or reject the random sample hypothesis might be due to differences in the proportion of Suitable Habitat in the landscape. In landscapes where there are no effects of fragment size and isolation the Habitat is functionally still continuous and the two hypotheses will give very similar predictions about the effects of Habitat fragmentation. The threshold value in proportion of Suitable Habitat in the landscape where there is a true effect of Habitat fragmentation (threshold for fragmentation) will vary across species and landscapes. H.

  • effects of Habitat fragmentation on birds and mammals in landscapes with different proportions of Suitable Habitat a review
    Oikos, 1994
    Co-Authors: Henrik Andrén
    Abstract:

    Habitat fragmentation implies a loss of Habitat, reduced patch size and an increasing distance between patches, but also an increase of new Habitat. Simulations of patterns and geometry of landscapes with decreasing proportion of the Suitable Habitat give rise to the prediction that the effect of Habitat fragmentation on e.g. population size of a species would be primarily through Habitat loss in landscape with a high proportion of Suitable Habitat. However, ast the proportion of Suitable Habitat