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Algeria has a diverse bird fauna, yet data from arid and semi-arid regions are scarce. To fill this knowledge gap, we conducted a study on the composition and conservation status of bird species of Djebel Aïssa National Park in the Naama province of Southwestern Algeria between September 2021 and September 2023. We collected data by using progressive frequency sampling (PFS) and line transects, which allowed us to systematically assess bird species across different habitats within the park. We recorded 94 species of birds belonging to 11 orders and 27 families. Passeriformes was the most abundant order, comprising 16 families and 67 species. The bird species detected were predominantly sedentary (50%) or wintering (39%), and some were visiting (8%) or migratory (3%). Most species were insectivores (45%), followed by granivores/insectivores (24%), carnivores (13%), omnivores (7%), granivores (6%), and carnivores/insectivores (5%). Most bird species were classified as “Least Concern” by the IUCN Red List, two species were “Near Threatened”, and one was “Vulnerable”. In addition, 29 species are protected under Executive Fiat 12–235 of 24 May 2012. Our study provides a baseline for future monitoring efforts and a basis for the development and implementation of conservation strategies in Djebel Aïssa National Park and the surrounding regions.

Global climate models (GCMs) are crucial for analysing climate change. With more than 50 models available from the Coupled Model Intercomparison Project Phase 6 (CMIP6), selecting the most appropriate models for accurate assessments of climate impacts is a major challenge. The variability of climate projections among these models further complicates this process. This study addresses this issue by proposing a framework for selecting representative GCMs using t-distributed stochastic neighbour embedding (t-SNE) in Tunisia and Algeria. To implement this framework, spatial grid data representing baseline conditions (1970–2000) and future climate scenarios of 20 GCMs under SSP2-4.5 were compiled from the WorldClim database. Six bioclimatic variables were selected for the analysis. For the temperature-related variables, we calculated the differences between the future projections (2050 and 2070) and the baseline climate, as well as the relative changes for the precipitation-related variables. We then performed t-SNE to reduce the dimensionality of the resulting data, testing perplexity values from 3 to 6 to determine the optimal setting. The k- means clustering algorithm was then applied to the reduced data to group GCMs with similar climate projections into clusters, and the quality of clustering was assessed using the silhouette score. From each cluster, we identified the GCM that was closest to the centroid and served as a representative model. Using these selected GCMs, we calculated the Emberger and modified thermicity indices and assessed the bioclimatic shifts in the distribution of forest trees. As a result, we identified three clusters of GCMs, each representing different patterns of climate projections. In particular, the model UKESM1-0-LL, representing cluster 3, systematically projected a more pronounced shift towards drier conditions in the future for most forest species compared to the other models. This study highlights the importance of selecting representative GCMs to capture the variability in climate projections, which is essential for reliable assessments of climate change impacts on forest ecosystems.

This study combines niche overlap analysis with species distribution modeling (SDM) to examine the niche dynamics of Atlantoxerus getulus, a ground squirrel native to Morocco and Algeria that has been introduced to the Canary Islands. We compiled 1272 records of A. getulus in its native and exotic ranges and five bioclimatic variables for present and future climate conditions for the years 2050 and 2070. We assessed the ecological niche of the species using exploratory and ordination analyses, followed by the prediction of its distribution using the SpatialMaxent model. Our results showed that the niches of A. getulus exhibited equivalence (p > 0.05) and significant similarity (p < 0.05) between the native and exotic ranges. No observed niche expansion in the exotic area is shown to be associated with complete niche stability. However, 90% of the niche in the Canary Islands remains unfilled, suggesting potential for further invasion. Our results highlighted habitat contractions ranging from 41% (SSP245-2050) to 60% (SSP585-2070), associated with a shift in the centroid of suitable habitat towards the Atlantic coast. These contractions are particularly severe in Algeria, where suitable habitats could disappear by 2050, contrasting with stable habitats maintained in the Canary Islands under all scenarios. Urgent habitat restoration in Algeria is crucial, including efforts to combat poaching. In Morocco, targeted in situ conservation is recommended, while in the Canary Islands, the focus should be on invasive species management and public awareness campaigns to prevent further spread.