Favourability: concept, distinctive characteristics and potential usefulness

Acevedo, Pelayo; Real, Raimundo

doi:10.1007/s00114-012-0926-0

Cited by 112 publications

(161 citation statements)

References 42 publications

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“…We thus obtained maps describing distributions of environmentally favorable areas for species in 0.1°×0.1° resolution squares. Favorability models can show how the probability of a species' local presence differs from that expected by chance in the whole study area, and so can distinguish those localities with environmental conditions that favor the species' existence from those with detrimental characteristics for its presence [37]. In contrast to modeling techniques providing probability values, favorability models can distinguish between the effect of environmental conditions and the probability of presence derived from the species prevalence within the study area [37].…”

Section: Methodsmentioning

confidence: 99%

“…Favorability models can show how the probability of a species' local presence differs from that expected by chance in the whole study area, and so can distinguish those localities with environmental conditions that favor the species' existence from those with detrimental characteristics for its presence [37]. In contrast to modeling techniques providing probability values, favorability models can distinguish between the effect of environmental conditions and the probability of presence derived from the species prevalence within the study area [37]. This enables direct comparison between models when several species are involved in the analytical design [37], and allows for model combinations through fuzzy logic [38], [39].…”

Section: Methodsmentioning

confidence: 99%

“…In contrast to modeling techniques providing probability values, favorability models can distinguish between the effect of environmental conditions and the probability of presence derived from the species prevalence within the study area [37]. This enables direct comparison between models when several species are involved in the analytical design [37], and allows for model combinations through fuzzy logic [38], [39].…”

Section: Methodsmentioning

confidence: 99%

“…Forward-backward stepwise logistic regression was run with the resulting set of variables [44], and probability outputs were finally transformed into favorability values [37]. The estimation of the relative weight of each variable in the model was tested using Wald's [45] test.…”

Section: Methodsmentioning

confidence: 99%

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Integrating Sustainable Hunting in Biodiversity Protection in Central Africa: Hot Spots, Weak Spots, and Strong Spots

Olivero

Farfán

et al. 2014

PLoS ONE

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Wild animals are a primary source of protein (bushmeat) for people living in or near tropical forests. Ideally, the effect of bushmeat harvests should be monitored closely by making regular estimates of offtake rate and size of stock available for exploitation. However, in practice, this is possible in very few situations because it requires both of these aspects to be readily measurable, and even in the best case, entails very considerable time and effort. As alternative, in this study, we use high-resolution, environmental favorability models for terrestrial mammals (N = 165) in Central Africa to map areas of high species richness (hot spots) and hunting susceptibility. Favorability models distinguish localities with environmental conditions that favor the species' existence from those with detrimental characteristics for its presence. We develop an index for assessing Potential Hunting Sustainability (PHS) of each species based on their ecological characteristics (population density, habitat breadth, rarity and vulnerability), weighted according to restrictive and permissive assumptions of how species' characteristics are combined. Species are classified into five main hunting sustainability classes using fuzzy logic. Using the accumulated favorability values of all species, and their PHS values, we finally identify weak spots, defined as high diversity regions of especial hunting vulnerability for wildlife, as well as strong spots, defined as high diversity areas of high hunting sustainability potential. Our study uses relatively simple models that employ easily obtainable data of a species' ecological characteristics to assess the impacts of hunting in tropical regions. It provides information for management by charting the geography of where species are more or less likely to be at risk of extinction from hunting.

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Section: Methodsmentioning

confidence: 99%

Section: Methodsmentioning

confidence: 99%

Section: Methodsmentioning

confidence: 99%

Section: Methodsmentioning

confidence: 99%

See 2 more Smart Citations

Integrating Sustainable Hunting in Biodiversity Protection in Central Africa: Hot Spots, Weak Spots, and Strong Spots

Olivero

Farfán

et al. 2014

PLoS ONE

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“…In cases of high prevalence of absences, as in the lanner falcon dataset here (180 absences out of 273 UTM cells), the logistic regression does not adequately describe the species' environmental suitability; therefore a favourability function not conditioned by the presence/absence ratio (Real et al, 2006) was used. This modification of logistic regression assesses the variation in the probability of occurrence of species in certain local conditions, with respect to the overall species prevalence; so that favourability values reflect only the environmental conditions that are appropriate for the species (Acevedo and Real, 2012). Favourability values were obtained from the probability values yielded by the logistic regression in this way:…”

Section: Species Distribution Model and Environmental Favourability Amentioning

confidence: 99%

Spatial analysis of lanner falcon habitat preferences: Implications for agro-ecosystems management at landscape scale and raptor conservation

Sarà

2014

Biological Conservation

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a b s t r a c tSicily hosts the largest European population of the endangered lanner falcon, a poorly known species which needs conservation planning based on habitat preferences. A distribution model on 10 Â 10 km cells of Sicily was described using Generalized Linear Models and variation partitioning methods. This modelling approach extracted explanatory factors, pure and joint effects of greatest influence from subsets of variables controlled for multi-collinearity and spatial autocorrelation. Analytical cartography used the environmental favourability function to assess habitat preferences, and the insecurity index estimated the degree to which lanner falcon occupancy is represented in the Natura2000 networks of Sicily. The lanner population is not randomly distributed across the geographical space as the significant latitudinal effect revealed. The most parsimonious explanatory model suggested traditional agro-ecosystems (i.e. arable lowlands and grasslands, with rugged terrains and cliffs) as the best predictors of lanner occupancy, and gave strong support to the negative effects of land abandonment and intensification (i.e. increase of heterogeneous areas and shrubby vegetation). The variation partitioning method suggested how an alteration of traditional agro-ecosystems might enhance interference competition with the peregrine falcon and limit lanner falcon occupancy. Most of the lanner falcon favourable habitats fall outside the Natura2000 networks, thus the main challenge for its conservation is represented by agri-environmental measures to be taken within the Common Agricultural Policy of the European Union. Conservation of traditional agro-ecosystems devoted to top-predators, like the lanner falcon, requires single environmental management agreements for multiple farm units, deployed at landscape scale on a network of favourable areas.

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An approach to consider behavioral plasticity as a source of uncertainty when forecasting species' response to climate change

Muñoz

Márquez

Real

2015

Ecology and Evolution

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The rapid ecological shifts that are occurring due to climate change present major challenges for managers and policymakers and, therefore, are one of the main concerns for environmental modelers and evolutionary biologists. Species distribution models (SDM) are appropriate tools for assessing the relationship between species distribution and environmental conditions, so being customarily used to forecast the biogeographical response of species to climate change. A serious limitation of species distribution models when forecasting the effects of climate change is that they normally assume that species behavior and climatic tolerances will remain constant through time. In this study, we propose a new methodology, based on fuzzy logic, useful for incorporating the potential capacity of species to adapt to new conditions into species distribution models. Our results demonstrate that it is possible to include different behavioral responses of species when predicting the effects of climate change on species distribution. Favorability models offered in this study show two extremes: one considering that the species will not modify its present behavior, and another assuming that the species will take full advantage of the possibilities offered by an increase in environmental favorability. This methodology may mean a more realistic approach to the assessment of the consequences of global change on species' distribution and conservation. Overlooking the potential of species' phenotypical plasticity may under- or overestimate the predicted response of species to changes in environmental drivers and its effects on species distribution. Using this approach, we could reinforce the science behind conservation planning in the current situation of rapid climate change.

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Favourability: concept, distinctive characteristics and potential usefulness

Cited by 112 publications

References 42 publications

Integrating Sustainable Hunting in Biodiversity Protection in Central Africa: Hot Spots, Weak Spots, and Strong Spots

Integrating Sustainable Hunting in Biodiversity Protection in Central Africa: Hot Spots, Weak Spots, and Strong Spots

Spatial analysis of lanner falcon habitat preferences: Implications for agro-ecosystems management at landscape scale and raptor conservation

An approach to consider behavioral plasticity as a source of uncertainty when forecasting species' response to climate change

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