Luke J. Sutton

Summary: As habitat loss intensifies due to expanding human infrastructure, balancing biodiversity conservation with resource extraction has become a global challenge. Thus, quantifying the extent and location of proposed mining operations can be key to mitigating the impacts on threatened species. This issue is particularly acute in the biodiversity hotspots of southeast Asia, where rapid economic growth needs to be balanced with sustainable conservation management of the remaining tropical forest. The Philippine Eagle Pithecophaga jefferyi , a Critically Endangered tropical forest raptor endemic to the Philippines, faces potential threats from mining activities that may destroy and fragment its tropical forest habitat. Here, we integrate species distribution modelling (SDM) with a gap and hotspot analysis to assess the spatial overlap between Philippine Eagle nest habitat and mining concessions across a protected area network on Mindanao, where the largest population remains. Using a landscape-scale SDM built with remote sensing covariates and eagle occurrence data, we identified high-suitability nest habitats and projected these into the Eastern Mindanao Biodiversity Corridor (EMBC). Hotspot analysis revealed that 41% of the total mining concessions area contained high-suitability nest habitat, highlighting potential conservation risks. Additionally, 46% of indigenous ancestral domains contain high-suitability nest habitat, emphasising the importance of indigenous land management in safeguarding eagle habitats. Our gap analysis demonstrated that 35% of the EMBC protects high-suitability nest habitat, which here represents the remaining montane tropical forest. To mitigate mining impacts, we propose targeted nest surveys in high-risk areas, implementation of mining moratoriums near critical nesting zones, and strengthening indigenous and protected area land management. By integrating SDMs with spatial analysis, we provide a framework for directing conservation efforts to balance resource extraction with the preservation of the Philippine Eagle’s habitat. Our findings offer crucial insights for policy development and land-use planning to protect this iconic species and its threatened habitat.

The Journal of Raptor Research publishes the biology and conservation of diurnal and nocturnal raptors, such as their ecology, behavior, and conservation.

As habitat destruction intensifies due to expanding human infrastructure, balancing biodiversity conservation with resource extraction has become a global challenge. Thus, quantifying the extent and location of proposed mining operations is key to mitigating the impacts on threatened species. This issue is particularly acute in the biodiversity hotspots of southeast Asia, where rapid economic growth needs to be balanced with sustainable conservation management of the remaining tropical forest. The Philippine Eagle ( Pithecophaga jefferyi ), a critically endangered tropical forest raptor endemic to the Philippines, faces increasing threats from mining activities that destroy and fragment its tropical forest habitat. Here, we integrate Species Distribution Modelling with gap and hotspot analysis to assess the spatial overlap between Philippine Eagle nest habitat and mining concessions across a protected area network on Mindanao, where the largest population remains. Using a landscape-scale SDM built with remote sensing covariates and eagle occurrence data, we identified high-suitability nest habitats and projected these into the Eastern Mindanao Biodiversity Corridor (EMBC). Hotspot analysis revealed that 41 % of the total mining concessions area contained high-suitability nest habitat, highlighting significant conservation risks. Additionally, 46 % of indigenous ancestral domains contain high-suitability nest habitat, emphasizing the importance of indigenous land management in safeguarding eagle habitats. Our gap analysis demonstrated that 35 % of the EMBC protects high-suitability nest habitat, which here represents the remaining montane tropical forest. To mitigate mining impacts, we propose targeted nest surveys in high-risk areas, implementation of mining moratoriums near critical nesting zones, and strengthening indigenous and protected area land management. By integrating SDMs with spatial analysis, we provide a framework for directing conservation efforts to balance resource extraction with the preservation of the Philippine Eagle’s habitat. Our findings offer crucial insights for policy development and land-use planning to protect this iconic species and its threatened habitat.

Predicting invasion risk to novel environments is essential for risk management and conservation decision making but the evolutionary lineage at which to make these predictions is often unclear. Here we predict the current suitability across the United Kingdom (UK) for the alpine newt Ichthyosaura alpestris, a species with a complex evolutionary history, a broad native range, a growing number of introduced populations and anecdotal reports of ecological consequences to native amphibian communities. We use species distribution and ecological niche modelling to predict environmental suitability of the alpine newt in the UK at both the species-level and lineage-level and to quantify evolutionary lineage niche overlap. We show good model transferability at the species-level and parts of the UK—especially central and eastern England and parts of central and northern Scotland—to be highly environmentally suitable for the alpine newt. Our findings provide evidence of environmental niche differences at the lineage-level, with the Greek lineage being distinct from most other lineages, but with low confidence in maxent predictions for the Greek, Balkan and Italian lineages due to high levels of extrapolation. In contrast, the niche of the UK records appear to share the same niche as the Central lineage. We find 66% of currently known alpine newt records to fall within areas predicted to be environmentally suitable at the species-level, providing a series of testable hypotheses to better understand the invasion ecology of this species in the UK.

Individual diet specialization is known to occur in populations of generalist predators, where specific individuals develop specialist feeding strategies. Diet specialization has been reported in many raptor species and it may be an important driver of intraspecific population structure. Here, we quantify the diet of Peregrine Falcons Falco peregrinus from five breeding territories on an island determined from prey remains collected over four breeding seasons. Three prey species accounted for 69.8% of total prey frequency, with Manx Shearwater Puffinus puffinus being the primary prey accounting for 47.3% by frequency and 40.8% by biomass. European Herring Gull Larus argentatus was the second most important prey species by frequency (13.8%) and biomass (29.8%) followed by Feral Pigeon Columba livia (frequency: 8.7%, biomass: 7.0%). Prey frequency on specific prey groups varied substantially between breeding pairs and months. Two pairs specialized on Manx Shearwater, one pair specialized on Herring Gull and Manx Shearwater, with the remaining two pairs having a relatively generalist diet of Manx Shearwaters, Feral Pigeon and small passerines. Prey frequency on Manx Shearwaters increased throughout the breeding season with a peak in total diet frequency of 63.8% in July, with a concurrent decrease in Herring Gull prey frequency. Higher percentage of Manx Shearwater in the diet explained 87% of the variation in a narrower dietary breadth for the Peregrine pairs. Our results suggest individual diet specialization may be one of multiple factors important for understanding population density in insular raptor populations.

Quantifying home‐range size and habitat resource selection are important elements in wildlife ecology and are useful for informing conservation action. Many home‐range estimators and resource selection functions are currently in use. However, both methods are fraught with analytical issues inherent within autocorrelated movement data from irregular sampling and interpretation of resource selection model parameters to inform conservation management. Here, we apply satellite remote sensing technologies to provide updated estimates of home‐range size and first estimates of fine‐scale resource selection for six adult Philippine Eagles Pithecophaga jefferyi using a space–time autocorrelated kernel density estimate (AKDE) home‐range estimator and non‐parametric resource selection functions. All six adult Eagles showed distinct site fidelity, with continuous range residency between 2 and 18 km, 1 month after tagging. The space–time AKDE home‐range estimators had a median 95% home‐range size = 68 km² (95% confidence interval (95% CI) 62–74 km², range: 39–161 km²), with the median 50% core range size = 13 km² (95% CI 11–14 km², range 9–33 km²). From the resource selection functions, all adult Philippine Eagles used habitat high in photosynthetic leaf and canopy structure but avoided areas of old‐growth biomass and denser areas of vegetation. This is possibly due to foraging forays into secondary forest and fragmented agricultural areas away from nesting sites. For the first time, we determine two important fine‐scale spatial processes for this Critically Endangered raptor that can help in directing conservation management. Rather than employing traditional home‐range estimators and resource selection functions, we recommend that analysts consider space–time approaches and non‐parametric resource selection functions to animal movement data to explore fully space–time and resource selection.

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-eagleEutriorchis 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.

Many range‐restricted taxa are experiencing population declines, yet we lack fundamental information regarding their distribution and population size. Establishing baseline estimates for both of these key biological parameters is however critical for directing conservation planning for at‐risk range‐restricted species. The International Union for the Conservation of Nature (IUCN) Red List uses three range metrics that define species distributions and inform extinction risk assessments: extent of occurrence (EOO), area of occupancy (AOO) and area of habitat (AOH). However, calculating all three metrics using standard IUCN approaches relies on a geographically representative sample of locations, which for rare species is often spatially biased. Here, we apply model‐based interpolation using Species Distribution Models (SDMs), correlating occurrences with remote‐sensing covariates, to calculate IUCN range metrics, protected area coverage and a global population estimate for the Critically Endangered Philippine Eagle (Pithecophaga jefferyi). Our final range wide continuous SDM had high predictive accuracy (continuous Boyce Index = 0.934) and when converted to a binary model estimated an AOH as 28 624 km², a maximum EOO as 617 957 km², and a minimum EOO as 275 459 km², with an AOO as 53 867 km². Based on inferred habitat from the AOH metric, we estimate a global population of 392 breeding pairs (range: 318–447 pairs), or 784 mature individuals, across the Philippine Eagle global range. Protected areas covered 32% of AOH, 13% less than the target representation, with the continuous model identifying key habitat as priority conservation areas. We demonstrate that even when occurrences are geographically biased, robust habitat models can quantify baseline IUCN range metrics, protected area coverage and a population size estimate. In the absence of adequate location data for many rare and threatened taxa, our method is a promising spatial modelling tool with widespread applications, particularly for island endemics facing high extinction risk.