Severity: Warning
Message: file_get_contents(https://...@gmail.com&api_key=61f08fa0b96a73de8c900d749fcb997acc09&a=1): Failed to open stream: HTTP request failed! HTTP/1.1 429 Too Many Requests
Filename: helpers/my_audit_helper.php
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File: /var/www/html/application/helpers/my_audit_helper.php
Line: 197
Function: file_get_contents
File: /var/www/html/application/helpers/my_audit_helper.php
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Function: simplexml_load_file_from_url
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Function: getPubMedXML
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Function: pubMedSearch_Global
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Function: pubMedGetRelatedKeyword
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Function: require_once
Introduction: Climate change poses significant challenges to the distribution of endemics in the Mediterranean region. Assessing the impact of climate change on the distribution patterns of Mediterranean endemics is of critical importance for understanding the dynamics of these terrestrial ecosystems under the uncertainty of future changes. The population size of the has declined significantly over the previous century across its geographical region. This decline is linked to how ongoing climate change is affecting natural resources like water and the capacity of foraging sites. In fact, it is distributed in 3 fragmented locations in Egypt (Wadi Hashem (5 individuals), Wadi Um Rakham (20 individuals), Burg El-Arab (4 individuals)).
Methods: In this study, we examined 's response to predicted climate change over the next few decades (2020-2040 and 2061-2080) using species distribution models (SDMs). Our analysis involved inclusion of bioclimatic variables, in the SDM modeling process that incorporated five algorithms: generalized linear model (GLM), Random Forest (RF), Boosted Regression Trees (BRT), Support Vector Machines (SVM), and Generalized Additive Model (GAM).
Results And Discussion: The ensemble model obtained high accuracy and performance model outcomes with a mean AUC of 0.95 and TSS of 0.85 for the overall model. Notably, RF and GLM algorithms outperformed the other algorithms, underscoring their efficacy in predicting the distribution of endemics in the Mediterranean region. Analysis of the relative importance of bioclimatic variables revealed Precipitation of wettest month (Bio13) (88.3%), Precipitation of warmest quarter (Bio18) (30%), and Precipitation of driest month (Bio14) (22%) as the primary drivers shaping the potential distribution of . The findings revealed spatial variations in habitat suitability, with the highest potential distribution observed in Egypt, (especially the Arishian sub sector), Palestine, Morocco, Northern Cyprus, and different islands in the Sea of Crete. Furthermore, our models predicted that the distribution range of would drop by more than 25% during the next few decades. Surprisingly, the future potential distribution area of (SSP 126 scenario) for 2061 and 2080 showed that there is increase in the suitable habitats area. It showed high habitat suitability along the Mediterranean coastal strip of Spain, Sardinia, Morocco, Algeria, Tunisia, Libya, Egypt, (especially the Arishian sub sector), Palestine, Lebanon, Northern Cyprus, and different Aegean islands.
Download full-text PDF |
Source |
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http://www.ncbi.nlm.nih.gov/pmc/articles/PMC11882879 | PMC |
http://dx.doi.org/10.3389/fpls.2025.1461639 | DOI Listing |
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