Assessment of forest stand dynamics in the Timekssaouine forest (Northern Morocco) using statistical and machine learning approaches

Farhani, Faouzi; Youssef, Boussalim; Boujraf, Amal; El Aboudi, Ahmed; Zine, Hamza; Sahel, Yassir; Dallahi, Youssef

doi:10.12912/27197050/199562

Artykuł - szczegóły

Tytuł artykułu

Assessment of forest stand dynamics in the Timekssaouine forest (Northern Morocco) using statistical and machine learning approaches

Autorzy

Farhani Faouzi , Youssef Boussalim , Boujraf Amal , El Aboudi Ahmed , Zine Hamza , Sahel Yassir , Dallahi Youssef

Treść / Zawartość

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Identyfikatory

DOI

10.12912/27197050/199562

Warianty tytułu

Języki publikacji

Abstrakty

Tracking changes in forest composition, structure, and distribution over time is essential for developing effective conservation strategies and sustainable management practices in these ecologically sensitive regions. In this study, the objective was to conduct a diachronic analysis, comparing land cover and vegetation status in the Timekssaouine forest within the Central Plateau region of Morocco over a 20-year period. The aim was to analyze the spatiotemporal evolution of plant formations. Satellite imagery, specifically Landsat images taken during the summer period (July) of 1999 and 2020, was utilized to provide a detailed observation of changes over time and space. Additionally, machine learning modeling using random forest (RF) was implemented to further explore the dynamics of change in the forest. The RF models developed achieved reasonable to good predictive performance, with AUC scores of between 0.67 and 0.80. The obtained findings revealed a concerning regression, with both the diachronic (59% of the forest area) and RF (35%) approaches highlighting extensive regression of the forest, particularly in the cork oak formations at 9%, with notable de-densification across density classes between 1999 and 2020, a diachronic study. Dense cork oak and moderately dense strata were particularly affected, experiencing regressions of 455 ha and 1204 ha, respectively, during this period. Conversely, open and sparse strata expanded, primarily sourced from the dense and moderately dense strata, resulting in an overall regression rate of 60 ha/year. The dense cork oak strata were prevalent on steep slopes with deep, slightly acidic soil, while scattered and clear strata were observed in low-lying areas with shallow soils and a pH range from neutral to slightly basic. Autumn precipitation and amplified overgrazing intensity emerged as the pivotal factors influencing the categorization of forest formations in the study forest, impacting tree density levels and posing a significant threat to forest regeneration.

Słowa kluczowe

forest dynamics diachronic analysis random forest modeling cork oak regression Morocco

Wydawca

Lubelski Oddział Polskiego Towarzystwo Inżynierii Ekologicznej
Lublin University of Technology
WNGB Wydawnictwo Naukowe

Czasopismo

Ecological Engineering & Environmental Technology

Rocznik

2025

Tom

Vol. 26, iss. 3

Strony

195--219

Opis fizyczny

Bibliogr. 87 poz., rys., tab.

Twórcy

autor

Farhani Faouzi

faouzi_farhani@um5.ac.ma

Laboratoire de Biotechnologie et Physiologie Végétales, Centre de Biotechnologie Végétale et Microbienne Biodiversité et Environnement, Faculté des Sciences, Université Mohammed V de Rabat, Morocco
Botany Team and Valorization of Plant and Fungal Resources (BOVAREF), Research Centre Biotechnology Vegetal and Microbial, Biodiversity and Environment, Faculty of Science, Mohammed V University in Rabat, Morocco

autor

Youssef Boussalim

Laboratoire de Biotechnologie et Physiologie Végétales, Centre de Biotechnologie Végétale et Microbienne Biodiversité et Environnement, Faculté des Sciences, Université Mohammed V de Rabat, Morocco

autor

Boujraf Amal

Laboratoire des Productions Végétale, Animales et Agro-industrie, Equipe de Botanique, Biotechnologie et Protection des Plantes, Faculté des Sciences, Université Ibn Tofail, Kénitra, Morocco

autor

El Aboudi Ahmed

Botany Team and Valorization of Plant and Fungal Resources (BOVAREF), Research Centre Biotechnology Vegetal and Microbial, Biodiversity and Environment, Faculty of Science, Mohammed V University in Rabat, Morocco

autor

Zine Hamza

Geology and Sustainable Mining Institute (GSMI), Mohammed VI Polytechnic University, Ben Guerir 43150, Morocco

autor

Sahel Yassir

Laboratory of Lands Equilibrium and and Territories Planning, Faculty of Literature and Human Sciences, Physical Geography Team, Mohammed V University Rabat, Morocco

autor

Dallahi Youssef

Laboratoire de Biotechnologie et Physiologie Végétales, Centre de Biotechnologie Végétale et Microbienne Biodiversité et Environnement, Faculté des Sciences, Université Mohammed V de Rabat, Morocco

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