Current and Future Distribution Modeling of Socotra Cormorants Using MaxEnt

Author:

Jaradat AreejORCID,Ksiksi TaoufikORCID,Muzaffar Sabir BinORCID

Abstract

The Socotra Cormorant (Phalacrocorax nigrogularis) is a regionally endemic seabird that is vulnerable due to human disturbance and habitat degradation. This study aimed to predict the potential current and future marine distribution of the species under different climate change scenarios using environmental variables affecting distribution using MaxEnt. Occurrence data were collected over several years using satellite tagged adults in the Arabian Gulf. The current model showed large areas of high suitability, mainly in the Arabian Gulf and in the Red Sea, where 31,300 km2 or 48% of total highly suitable areas existed. These areas are currently not utilized by the species. The future model predicted a sharp decline in suitable areas with 73% loss under the SSP5-8.5 climate change scenario of 2050 (extreme scenario). Nevertheless, the Red Sea is predicted to still hold considerable moderately suitable areas. Suitable areas increased around the Socotra archipelago. The model did not include biological variables due to lack of fish distribution data. Two variables, namely, mixed layer thickness and sea floor depth, explained most of the species’ distribution. These variables significantly influence nutrient cycling and forage fish distribution patterns, which in turn influence seabird distributions. Thus, the model could be useful in predicting the distribution of Socotra cormorants. However, the model outcomes should be interpreted with caution as potential areas of future expansion of the species to be further tested and validated. Conserving these areas as a precaution might encourage the Socotra Cormorant to colonize the region and persist in the future under the most extreme climate change scenarios, given that small forage fish that are eaten by the species are abundant in the predicted areas outside of the Arabian Gulf.

Funder

United Arab Emirates University graduate student fund

Publisher

MDPI AG

Subject

Nature and Landscape Conservation,Agricultural and Biological Sciences (miscellaneous),Ecological Modeling,Ecology

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