ORIGINAL RESEARCH article
Front. Ecol. Evol.
Sec. Conservation and Restoration Ecology
Volume 13 - 2025 | doi: 10.3389/fevo.2025.1573807
This article is part of the Research TopicAdvancing Nature-Based Solutions to Address the Impacts of Climate Change within the Global SouthView all articles
Modeling the Impact of Climate Change on Corvus Species Distribution in Somaliland: Bayesian Spatial Point Process Approach for Conservation
Provisionally accepted
Abdisalam Hassan Muse1*
Maysaa Elmahi Abd Elwahab2- 1Amoud University, Borama, Somalia
- 2Princess Nourah bint Abdulrahman University, Riyadh, Saudi Arabia
Select one of your emails
You have multiple emails registered with Frontiers:
Notify me on publication
Please enter your email address:
If you already have an account, please login
You don't have a Frontiers account ? You can register here
This study applied a log-Gaussian Cox process model, utilizing the R-INLA package, to predict the spatial distribution of Corvus edithae (Somali crow) in Somaliland. The model integrated spatial climatic covariates (mean annual temperature, mean annual precipitation, minimum/maximum temperature, solar radiation, wind speed) alongside structured and unstructured random effects to address spatial autocorrelation and unexplained variability. Analysis explored associations between Corvus edithae occurrence intensity and the climatic covariates. Posterior mean estimates suggested potential positive relationships with mean annual temperature, precipitation, and wind speed, and negative relationships with temperature extremes and solar radiation; however, wide 95% credible intervals encompassing zero indicated substantial uncertainty regarding these specific climatic effects at the scale analyzed. Conversely, the model revealed highly influential spatially structured (autocorrelation) and unstructured random effects, demonstrating that unmeasured spatial factors and inherent environmental heterogeneity significantly shape the species' distribution beyond the included broad-scale climate variables. Model predictions revealed generally low occurrence intensities across the region, with coastal areas exhibiting the highest expected densities, suggesting their importance as potential core habitats. Convergence diagnostics indicated stable parameter estimation, demonstrating model reliability. The findings underscore that while climate is relevant, understanding Corvus edithae distribution requires considering significant spatial dependencies and heterogeneity. This study provides a robust Bayesian spatial point process framework applicable for conservation ecology, particularly where spatial patterns are prominent and data may be uncertain.
Keywords: Somali crow, Spatial point process model, species distribution, Climate Change, Somaliland, spatial analysis
Received: 20 Feb 2025; Accepted: 04 Jun 2025.
Copyright: © 2025 Muse and Abd Elwahab. This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) or licensor are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.
* Correspondence: Abdisalam Hassan Muse, Amoud University, Borama, Somalia
Disclaimer: All claims expressed in this article are solely those of the authors and do not necessarily represent those of their affiliated organizations, or those of the publisher, the editors and the reviewers. Any product that may be evaluated in this article or claim that may be made by its manufacturer is not guaranteed or endorsed by the publisher.