Aim of study: Understanding small-scale patterns caused by stochastic factors or community interactions driving forest structure and diversity of Moroccan fir Abies marocana Trab.Area of study: Talassemtane fir forest, Talassemtane National Park, Rif Mountains, northern Morocco.Material and methods: Eight plots representative of the structural variability of A. marocana forests were selected, and all tree individuals with diameter at breast height (dbh) ≥2 cm were mapped and measured. We performed four types of spatial point pattern analyses: (1) Univariate analyses to explore the overall trees spatial pattern, (2) bivariate analyses to assess the spatial relationship between juveniles and A. marocana adults, (3) correlation between tree sizes (dbh) and distance between points pairs using the univariate mark correlation function, and (4) random labeling analyses between dominant and suppressed Moroccan fir individuals to assess competition patterns.Main results: We found a strong spatial aggregation of fir individuals and a positive intraspecific association between juveniles and adult trees. However, there were weak but significant distance-dependent effect on tree size and density-dependent effect on suppression pattern.Research highlights: Shade-tolerance, seed dispersal and/or microsite heterogeneity might play important roles in the observed fir patterns. Our results provide a basic knowledge on within-stand Moroccan fir spatial distribution, with implications for adaptive management of these relic forests, and prompting to further research to test advanced hypotheses.Additional key words: Moroccan fir; Talassemtane National Park; Rif forest; Spatial analysis; summary statistics; facilitation; aggregation.Abbreviations used: MF (Moroccan fir); Talassemtane National Park (TNP); dbh (diameter at breast height); Univariate pair-correlation function (g(r)); Heterogeneous Poisson (HP); Bivariate pair-correlation function (g12(r)); Univariate mark correlation function (kmm(r)), Mark connection function (p12(r)).

Fire is a concern for the sustainability of dry forests such as those of the Mediterranean region, especially under warming climate and high human use. We used data derived from Landsat and MODIS sensors to assess forest changes in the Talassemtane National Park (TNP) in North Africa from 2003–2018. The Talassemtane National Park is a protected area in northern Morocco, a biodiverse, mountainous region with endemic species of concern such as the Moroccan fir (Abies marocana) and Barbary macaque (Macaca sylvanus). To help the managers of the TNP better understand how the forest has been impacted by fire vs. other disturbances, we combined information from remotely derived datasets. The Hansen Global Forest Change (GFC) data are a global resource providing annual forest change, but without specifying the causes of change. We compared the GFC data to MODIS wildfire data from Andela’s Global Fire Atlas (GFA), a new global tool to identify fire locations and progression. We also analyzed surface reflectance-corrected Landsat imagery to calculate fire severity and vegetation death using Relative Differenced Normalized Burn Ratio analysis (RdNBR). In the park, GFC data showed a net loss of 1695 ha over 16 years, corresponding to an approximately 0.3% annual loss of forest. The GFA identified nine large fires that covered 4440 ha in the study period, coinciding with 833 ha of forest loss in the same period. Within these fires, detailed image analysis showed that GFA fire boundaries were approximately correct, providing the first quantitative test of GFA accuracy outside North America. High-severity fire, as determined by RdNBR analysis, made up about 32% of burned area. Overall, the GFA was validated as a useful management tool with only one non-detected wildfire in the study period; wildfires were linked to approximately 49% of the forest loss. This information helps managers develop conservation strategies based on reliable data about forest threats.

In recent years, changes in climate, land cover, and sociodemographic dynamics have created new challenges in wildfire management. As a result, advanced and integrated approaches in wildfire science have emerged. The objective of our study is to use geospatial analysis to identify strategic responses to wildfires in the Tangier-Tetouan-Al Hoceima (TTA) region, widely reputed to exhibit the most significant incidences of wildfires in Morocco. We adopted a combined approach, using burned area products (Fire_CCI51: 2002–2020) from the Moderate Resolution Imaging Spectroradiometer (MODIS) and active fires from the Fire Information for Resource Management System (FIRMS: 2001–2022) and processing them with spatiotemporal statistical methods: optimized hotspot analysis (OHA) and emerging hotspot analysis (EHA). The main findings indicate that the TTA region recorded an average of 39.78 km²/year of burned areas, mostly located in forests (74%), mainly cork oak and matorral stands (50%). The OHA detected hotspots covering 2081 km², with 63% concentrated in the provinces of Chefchaouen and Larache. Meanwhile, clusters of EHA extended over 740 km² and were composed of the oscillating coldspot (OCS) and oscillating hotspot (OHS) patterns at 50% and 30%, respectively. Additionally, an average of 149 fires/year occurred, located mostly in forests (75%), mainly cork oak and matorral stands (61%). The OHA detected active fire hotspots covering 3904 km², with 60% located in the provinces of Chefchaouen and Larache. Clusters of EHA over 941 km² were composed of the oscillating hotspot (OHS) and new hotspot (NHS) patterns at 57% and 25%, respectively. The prevalence of the oscillating and new models mirrors, respectively, the substantial fluctuations in wildfires within the region alternating between periods of high and low wildfire activities and the marked increase in fires in recent times, which has occasioned the emergence of novel hotspots. Additionally, we identified six homogeneous wildfire zones to which we assigned three strategic responses: “maintain” (73% of the territory), “monitor and raise awareness” (14% of the territory), and “reinforce” (13% of the territory). These strategies address current wildfire management measures, which include prevention, risk analysis, preparation, intervention, and rehabilitation. To better allocate firefighting resources, strategic responses were classified into four priorities (very high, high, medium, and low). Last, the wildfire zoning and strategic responses were validated using burned areas from 2021 to 2023, and a global scheme was suggested to assess the effectiveness of future wildfire measures.

Formulating effective policies to address or mitigate deforestation requires a comprehensive understanding of the contributing factors. This study examines the drivers of deforestation from 2001 to 2020 in the Tangier-Tetouan-Al Hoceima (TTA) region, a northern Moroccan area distinguished by the country’s highest deforestation rate. Through an extensive review of existing literature and employing Geist and Lambin’s deforestation framework, we identified five key causes: infrastructure extension, agricultural expansion, logging, wildfires as direct causes, and demographic factors as an indirect cause. Data on deforestation and its contributing factors were sourced from diverse databases, including Global Forest Change (GFC), Global Land Analysis and Discovery (GLAD), Burned Area Product (MODIS Fire_CCI51), World Population, Forest Proximate People (FPP), and National Forest Inventory (NFI) datasets. Pixel-level analysis of GFC data indicated that wildfires are the primary driver of deforestation in the region, accounting for 35.2%, followed by agricultural expansion (30.6%), logging (13.2%), and infrastructure extension (10.1%). The remaining 10.9% of losses were attributed to other disturbances, such as illegal extraction, pests, and dieback. Spatial patterns were further analyzed through Exploratory Spatial Data Analysis (ESDA) methods at a 1 km² gridded scale, revealing strong clustering for all studied factors. Spatial relationships were explored using the bivariate local Moran’s index, which highlighted the highest spatial dependence between deforestation and fires (I = 0.21). Correlations between deforestation and other factors, including agricultural expansion, logging, infrastructure extension, and demographic pressure, were assessed at 0.18, 0.17, 0.08, and 0.05, respectively. Landscape pressures (LSP), encompassing deforestation, agricultural expansion, fires, infrastructure extension, and demographic pressure, were analyzed using the local Geary index, revealing a positive correlation in approximately 59% of spatial units. Last, a composite map of LSP clusters and an explanatory diagram illustrating dominant patterns in the TTA region were generated based on the results from local Geary’s multivariate and local Moran’s univariate tests.

This study assesses the conservation effectiveness of 21 protected areas (PAs) in Northern Morocco, comprising 3 parks and 18 Sites of Ecological and Biological Interest (SBEIs), against five major landscape pressures (LSPs): deforestation, infrastructure extension, agricultural expansion, fires, and population growth. We propose a novel quantitative methodology using global remote sensing data and exploratory spatial data analysis (ESDA). Data were sourced from Global Forest Change (GFC), Global Land Analysis and Discovery (GLAD), Burned Area Product (MODIS Fire_CCI51), and World Population datasets. The combined impact of the five LSPs was measured using a cumulative effect index (CEI), calculated with the Shannon–Wiener formula at a 1 km² scale. The CEI was analyzed alongside the distance to the PAs’ network using Moran’s index, identifying four spatial association types: high–high (HH), high–low (HL), low–low (LL), low–high (LH), and non-significant (NS) cells. This analysis defined four zones: inner zone (IZ), potential spillover effect zone (PSEZ), statistically non-significant zone (SNSZ), and non-potential effect zone (NPEZ). Conservation effectiveness was quantified using the conservation ratio (CR), which compared the prevalence of LL versus HL units within IZs and PSEZs. Four disturbance levels (very high, high, medium, and low) were assigned to CR values (0–25%, 25–50%, 50–75%, 75–100%), resulting in sixteen potential conservation effectiveness typologies. Initial findings indicated similar deforestation patterns between protected and unprotected zones, with wildfires causing over half of forest losses within PAs. Conservation effectiveness results categorized the 21 PAs into nine typologies, from high conservation to very high disturbance levels. A significant positive correlation (71%) between CRs in both zones underscored the uniform impact of LSPs, regardless of protection status. However, protected natural area zones in the parks category showed minimal disruption, attributed to their advanced protection status. Finally, we developed a methodological framework for potential application in other regions based on this case study.