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IntroductionManaging the degradation and loss of Sudanian woodlands to ensure sustainable use for mainly firewood, poles, and timber is receiving increasing attention, and it requires tailored strategies to improve stand productivity. This study determined: (i) tree response (density, recruitment, and height growth) to selective stem thinning and branch pruning; and (ii) tree species that are most affected by selective stem thinning and branch pruning in the Sudanian woodland of Benin.MethodsThree homogeneous vegetation units of 80 m × 80 m each were identified, representing the three stages of woodland development (WDS): early and young WDS of 3 and 3–5 years old, respectively, and the advanced to mature secondary WDS of 6–9 years old. Three random blocks of 20 m × 20 m each, subdivided into four 10 m × 10 m treatment plots, were delineated per vegetation unit. Each of these plots was randomly assigned a treatment (T): T1—no thinning and no pruning; T2—30% thinning; T3—60% thinning; T4—100% thinning. Branch pruning was applied to all remaining stems in T2 and T3. Tree species, stem abundance and height of individuals = 1 m were recorded every 6 months in 2015 and 2016.Results and discussionThinning intensity significantly influence tree density both in WDS 2 and 3 with the 30% thinning showing the best tree density (3355.56 ± 250.19 stems/ha and 3255.56 ± 772.68 stems/ha, respectively). However, more stem recruitment was observed without thinning and pruning (883.33 ± 212.13 stems/ha), and 30% thinning and pruning (383.33 ± 164.99 stems/ha). There was a significant increase in tree height growth both in WDS 2 and 3 with an increasing thinning intensity. The two most affected tree species were Terminalia avicennioides and Pteleopsis suberosa with an average growth in height after 6 months of 105.5 ± 1.05 mm (for 30% thinning and pruning in stage 3), and 61.75 ± 0.67 mm (for 60% thinning and pruning in stage 3), respectively. Overall, moderate stem thinning (30%) at WDS 1 and more severe thinning at WDS 2 and 3 resulted in the best tree height growth and recruitment.

Les ressources forestières en bois énergie sont fortement exploitées en Afrique, entraînant la dégradation des peuplements d'espèces comme Detarium microcarpum. La présente étude, réalisée dans trois phytodistricts au nord du Bénin, vise à contribuer à l’élaboration de techniques durables d’exploitation de bois de feu dans les peuplements naturels de D. microcarpum. Différentes modalités de hauteur (à ras du sol, 10 cm, 20 cm, 30 cm, 40 cm et 50 cm du sol) et de diamètre ([4-10[, [10-15[et [15-20] cm) de coupe ont été testées sur D. microcarpum. Les données ont été collectées sur 240 souches coupées de manière aléatoire dans huit sites. Les mesures ont concerné le nombre de rejets par souche, la hauteur et le diamètre au collet des rejets. Les résultats issus des données collectées et les analyses de Kruskall-Wallis sur les variables « nombre de rejets », « croissance en diamètre » et « croissance en hauteur » révèlent une influence des modalités de coupe sur le développement des rejets. Cette influence est significativement plus importante sur les souches de grande taille. En effet, le nombre de rejets, la croissance en hauteur et la croissance en diamètre des rejets sont plus élevés lorsque la souche est coupée à une hauteur de 50 cm du sol avec un diamètre compris entre 15 et 20 cm. La coupe à 50 cm du sol avec un diamètre des souches compris entre 15 et 20 cm est par conséquent la meilleure option pour une gestion durable des peuplements naturels de D. microcarpum pour la fourniture de bois-énergie. Des études complémentaires pourraient se concentrer sur d'autres aspects de la régénération et de la croissance des rejets, ainsi que sur l'efficacité des pratiques de gestion recommandées, afin de fournir des informations supplémentaires pour une exploitation et une conservation plus efficaces de D. microcarpum.

Aims: This study aims to: i) differentiate the plant associations in the Biosphere Reserve of Pendjari (BRP), ii) determine the ecological characteristics of their habitats and iii) present distribution maps on different soil types. Study area: The BRP, located in the Sudanian Zone of Benin. Methods: 202 phytosociological relevés were sampled according to the Braun-Blanquet method within the BRP. Ordination was performed using Detrended Correspondence Analysis to evaluate vegetation patterns. Soil parameters were used to characterize the vegetation types. Results: The numerical analysis of 202 plots and 249 plant species showed two major floristic groups that correlated with a moisture gradient: drylands versus wetlands. The dryland group was a mixture of woodland and shrub savanna, the dominant ecosystems of the study area. The wetland group encompassed species primarily from riparian forest, tree savanna and grass savanna on floodplains. Syntaxonomical analysis of the dryland group showed rocky and gravelly soil associations (Burkeo africanae-Detarietum microcarpi) and soils associated with or without fine gravels (Andropogono gayani-Terminalietum avicennioidis, Andropogono gayani-Senegalietum dudgeonii and Terminalietum leiocarpae). Syntaxonomical analysis of the wetland group showed riparian forest associations on sandy-clay soil (Coletum laurifoliae, Borassetum aethiopi and Hyparrhenio glabriusculae-Mitragynetum inermis) and floodplain associations on silt-clay soil (Terminalio macropterae-Mitragynetum inermis, Brachiario jubatae-Terminalietum macropterae, Sorghastro bipennati-Vachellietum hockii). Conclusions: Eleven new associations were identified in this study. If the distribution of plant associations was determined by different soil properties, the soil humidity would be one of the main ecological factors determining the establishment of plant species and thus plant association development. Taxonomic reference: Akoègninou et al. (2006), Angiosperm Phylogeny Group classification for the orders and families of flowering plants (APG IV, 2016). Abbreviations: BRP = Biosphere Reserve of Pendjari; CBD = Convention on Biological Diversity; CCA = Constrained Correspondence Analysis; DCA = Detrended Correspondence Analysis; GPS UTM = Global Positioning System Universal Transverse Mercator.