Updated range metrics and a global population estimate for the Critically Endangered Philippine Eagle using a spatial ensemble habitat model

Abstract

Many range-restricted taxa are currently experiencing population declines yet lack fundamental information regarding distribution and population size. Establishing baseline estimates for both 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 = 0.927) and when converted to a binary model estimated an AOH = 23,185 km2, a maximum EOO = 605,759 km2, a minimum EOO = 272,272 km2, with an AOO = 53,867 km2. Based on inferred habitat from the AOH metric, we estimate a global population of 318 breeding pairs (range: 258-362 pairs), or 636 mature individuals, across the Philippine Eagle global range. Protected areas covered 34 % of AOH, 15 % 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 be built that enable quantification of 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, in particular for island endemics facing high extinction risk.