Climatic Constraints on Laggar Falcon (Falco jugger) Distribution Predicts Multidirectional Range Movements under Future Climate Change Scenarios

Sutton, Luke J.; McClure, Christopher J. W.; Kini, Sunil; Leonardi, Giovanni

doi:10.3356/0892-1016-54.1.1

Cited by 16 publications

(10 citation statements)

References 97 publications

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“…We recognise there are limitations to our approach regarding sample size, but we used the current best-practice modelling methodology combined with robust remote-sensing variables to calculate our baseline metrics. Even though unstructured occurrence data can have sampling bias (Beck et al 2014), opportunistically collected presence-only data are often the only location data available and generally sample beyond the extent of the smaller spatial scale of systematic surveys (Sutton et al 2020, Sutton & Puschendorf 2020). Thus, when used in conjunction with a modelling framework designed to account for inherent spatial biases unstructured data can fill distributional knowledge gaps (Rhoden et al 2017, Sutton et al 2023b).…”

Section: Discussionmentioning

confidence: 99%

Extensive protected area coverage and an updated global population estimate for the Endangered Madagascar Serpent-eagleEutriorchis astur

Sutton

Benjara²,

Roland³

et al. 2023

Bird Conservation International

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Summary Knowledge gaps regarding distribution, habitat associations, and population size for rare and threatened range-restricted taxa lead to uncertainty in directing conservation action. Quantifying range metrics and species–habitat associations using Species Distribution Models (SDMs) with remote-sensing habitat data can overcome these setbacks by establishing baseline estimates for biological parameters critical for conservation assessments. Area of Habitat (AOH) is a new range metric recently developed by the International Union for Conservation of Nature (IUCN) Red List. AOH seeks to quantify inferred habitat within a species’ range to inform extinction risk assessments. Here, we used SDMs correlating occurrences with remote-sensing covariates to calculate a first estimate of AOH for the Endangered Madagascar Serpent-eagle Eutriorchis astur, and then updated additional IUCN range metrics and the current global population estimate. From these baselines we then conducted a gap analysis assessing protected area coverage. Our continuous SDM had robust predictive performance (Continuous Boyce Index = 0.835) and when reclassified to a binary model estimated an AOH = 30,121 km2, 13% less than the current IUCN range map. We estimated a global population of 533 mature individuals derived from the Madagascar Serpent-eagle AOH metric, which was within current IUCN population estimates. The current protected area network covered 95% of AOH, with the binary model identifying three additional key habitat areas as new protected area designations to fully protect Madagascar Serpent-eagle habitat. Our results demonstrated that correlating presence-only occurrences with remote-sensing habitat covariates can fill knowledge gaps useful for informing conservation action. Applying this spatial information to conservation planning would ensure almost full protected area coverage for this endangered raptor. For tropical forest habitat specialists, we recommend that potential predictors derived from remote sensing, such as vegetation indices and biophysical measures, are considered as covariates, along with other variables including climate and topography.

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Section: Discussionmentioning

confidence: 99%

Extensive protected area coverage and an updated global population estimate for the Endangered Madagascar Serpent-eagleEutriorchis astur

Sutton

Benjara²,

Roland³

et al. 2023

Bird Conservation International

Self Cite

View full text Add to dashboard Cite

show abstract

“…Even though unstructured occurrence data can have sampling bias (Beck et al . 2014), opportunistically collected presence-only data are often the only location data available and generally sample beyond the extent of the smaller spatial scale of systematic surveys (Sutton et al . 2020).…”

Section: Discussionmentioning

confidence: 99%

Extensive protected area coverage and an updated global population estimate for the Endangered Madagascar Serpent-eagle identified from species-habitat associations using remote sensing data

Sutton

Benjara²,

Roland³

et al. 2022

Preprint

Self Cite

View full text Add to dashboard Cite

Knowledge gaps regarding distribution, habitat associations, and population size for rare and threatened range-restricted taxa leads to uncertainty in directing conservation action. Quantifying range metrics and species-habitat associations using Species Distribution Models (SDMs) with remote sensing habitat data can overcome these setbacks by establishing baseline estimates for biological parameters critical for conservation assessments. Area of habitat (AOH) is a new range metric developed by the International Union for the Conservation of Nature (IUCN) Red List. AOH seeks to quantify inferred habitat within a species’ range to inform extinction risk assessments. Here, we use SDMs correlating occurrences with remote-sensing covariates, to calculate a first estimate of AOH for the Endangered Madagascar Serpent-eagle (Eutriorchis astur), and then update additional IUCN range metrics and the current global population estimate. From these baselines we then conduct a gap analysis assessing protected area coverage. Our continuous SDM had robust predictive performance (Continuous Boyce Index = 0.835) and when reclassified to a binary model estimated an AOH = 30,121 km2, 13 % less than the current IUCN range map. We estimate a global population of 533 mature individuals derived from the Madagascar Serpent-eagle AOH metric, which was within the current IUCN population estimates. The current protected area network covered 95 % of AOH, with the binary model identifying three key habitat areas as new protected area designations to fully protect Madagascar Serpent-eagle habitat. Our results demonstrate that correlating presence-only occurrences with remote sensing habitat covariates can fill knowledge gaps useful for informing conservation action. Applying this spatial information to conservation planning would ensure almost full protected area coverage for this endangered raptor. For tropical forest habitat specialists, we recommend that potential predictors derived from remote sensing, such as vegetation indices and biophysical measures are considered as covariates, along with other variables including climate and topography.

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“…The first two variables are well known drivers of aquatic species distribution (Enriquez‐Urzelai et al, 2019; Iannella et al, 2017; Surasinghe & Baldwin, 2015), but also of the distribution of other taxa (Redhead et al, 2020; Sutton, 2020). Consistently with our expectation, warm monthly maximum air temperature was found to limit the most the presence of the Pyrenean brook newt.…”

Section: Discussionmentioning

confidence: 99%

Accounting for flow intermittence in freshwater species distribution modelling

et al. 2021

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To forecast species responses to environmental changes, it is crucial to understand drivers of species distribution acting at multiple spatial and temporal scales. While hydrology is acknowledged as a key driver for freshwater species, most studies have been limited to perennial river flow regimes when exploring species distribution in rivers. We developed a method to characterize stream flow to subsequently account for flow intermittence in species distribution models (SDMs). First, we used the hydrological Soil and Water Assessment Tool (SWAT) to simulate flow in the French Pyrenees at fine spatial grain and large spatial extent. Several metrics characterizing flow intermittence were subsequently included in a SDM along with topographic, hydrographic, climatic and land use variables. We applied this methodology to an extensive data set of the Pyrenean brook newt (Calotriton asper) presence in France.This amphibian is highly dependent on aquatic habitats, and its distribution could be mainly driven by hydrological and climatic variables. We found that 60% of the stream network of the study area is intermittent. Maximum air temperature and proportion of agricultural areas contribution in explaining species distribution were the most important (26.3% and 21.2%, respectively). Both variables negatively influenced the probability of presence of the Pyrenean brook newt. We also found a negative correlation with the frequency of zero-flow events (13%), emphasizing the role of flow intermittence in driving aquatic species distribution. Our study provides new insights into fine-grained hydrology in the Pyrenees and illustrates intermittence characterization and mapping methods that could be applied elsewhere.

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Climatic Constraints on Laggar Falcon (Falco jugger) Distribution Predicts Multidirectional Range Movements under Future Climate Change Scenarios

Abstract: BioOne Complete (complete.BioOne.org) is a full-text database of 200 subscribed and open-access titles in the biological, ecological, and environmental sciences published by nonprofit societies, associations, museums, institutions, and presses.

Cited by 16 publications

References 97 publications

Extensive protected area coverage and an updated global population estimate for the Endangered Madagascar Serpent-eagleEutriorchis astur

Extensive protected area coverage and an updated global population estimate for the Endangered Madagascar Serpent-eagleEutriorchis astur

Extensive protected area coverage and an updated global population estimate for the Endangered Madagascar Serpent-eagle identified from species-habitat associations using remote sensing data

Accounting for flow intermittence in freshwater species distribution modelling

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