Managing tree cover to restore farm productivity and build landscape and livelihood resilience in West Africa

Land restoration and sustainable natural resource use are critical societal concerns that impact both the health of ecosystems and human well-being. There is increasing recognition of the importance of restoring degraded land and landscapes, culminating in the UN Decade of Ecosystem Restoration (2021–2030). This special issue sheds light on how trees can help restore landscapes and is organized around 3 domains: ecological and genetic variation, restoration of species and lands, and species management in production systems. Successful tree cover interventions consider species, practices, and their management within the production systems to optimize impacts. A solid understanding of the variation in tree materials and their different functional traits can help restoration project planners and managers select the best interventions, such as direct seeding and Farmers’ Managed Natural Regeneration (FMNR). Simultaneously, the use of these approaches must be context-specific and consider the severity of land degradation. The Land Degradation Surveillance Framework (LDSF), a tool that helps determine the severity of land degradation, can be used to help tailor interventions to the local extent of land degradation.

Bootstrapping outperforms community-weighted approaches for estimating the shapes of phenotypic distributions

Estimating phenotypic distributions of populations and communities is central to many questions in ecology and evolution. These distributions can be characterized by their moments (mean, variance, skewness and kurtosis) or diversity metrics (e.g. functional richness). Typically, such moments and metrics are calculated using community-weighted approaches (e.g. abundance-weighted mean). We propose an alternative bootstrapping approach that allows flexibility in trait sampling and explicit incorporation of intraspecific variation, and show that this approach significantly improves estimation while allowing us to quantify uncertainty. We assess the performance of different approaches for estimating the moments of trait distributions across various sampling scenarios, taxa and datasets by comparing estimates derived from simulated samples with the true values calculated from full datasets. Simulations differ in sampling intensity (individuals per species), sampling biases (abundance, size), trait data source (local vs. global) and estimation method (two types of community-weighting, two types of bootstrapping). We introduce the traitstrap R package, which contains a modular and extensible set of bootstrapping and weighted-averaging functions that use community composition and trait data to estimate the moments of community trait distributions with their uncertainty. Importantly, the first function in the workflow, trait_fill, allows the user to specify hierarchical structures (e.g. plot within site, experiment vs. control, species within genus) to assign trait values to each taxon in each community sample. Across all taxa, simulations and metrics, bootstrapping approaches were more accurate and less biased than community-weighted approaches. With bootstrapping, a sample size of 9 or more measurements per species per trait generally included the true mean within the 95% CI. It reduced average percent errors by 26%–74% relative to community-weighting. Random sampling across all species outperformed both size- and abundance-biased sampling. Our results suggest randomly sampling ~9 individuals per sampling unit and species, covering all species in the community and analysing the data using nonparametric bootstrapping generally enable reliable inference on trait distributions, including the central moments, of communities. By providing better estimates of community trait distributions, bootstrapping approaches can improve our ability to link traits to both the processes that generate them and their effects on ecosystems.

Morphotype Classification Criteria and Influence of Sociocultural Factors on Perceived Shea Tree (Vitellaria paradoxa C.F. Gaertn) Natural Variation across Parklands in Benin

Trait diversity is crucial in undertaking the domestication of useful species such as Vitellaria paradoxa which makes a significant contribution to the rural household economy in Africa. This study aims to document the criteria farmers use to distinguish shea trees; how they vary according to age, education level and sociolinguistic group; and their perception of trees’ abundance and production. We surveyed 405 respondents across shea parklands in Benin using a semi-structured questionnaire. We used the Kruskal-Wallis test to evaluate the influence of sociodemographic attributes on relative criteria citation frequency and principal components analysis to characterize farmers’ perception on morphotypes’ abundance, fruits, and butter yields. The five most cited criteria were fruit size (55.5%), tree fertility (15.40%), bark colour (10.51%), timing of production (5.38%), and pulp taste (3.42%). The citation frequency of criteria varied significantly depending on the sociodemographic factors considered. Trees having small fruit (‘Yanki’) were reported to be widespread and high fruit/nuts and butter producers. Farmers perceived five important traits with variable importance depending on the sociocultural factors studied. This finding is a key step toward the development of a shea improvement program that could focus on the morphotype Yanki reported to potentially be a high fruit and butter producer. © 2022 by the authors. Licensee MDPI, Basel, Switzerland.

Amenability of priority indigenous fruit trees of West and Central Africa to grafting

Grafting scions of trees with desirable features is an important step for the domestication of indigenous forest fruit trees. Two experiments were carried out in the World Agroforestry (ICRAF) experimental nursery at Yaoundé (Cameroon) to assess the graft success of five forest fruit tree species identified as priority species for domestication in West and Central Africa namely Irvingia gabonensis, Garcinia kola, Cola nitida, Ricinodendron heudelotii and Monodora myristica. In experiment 1, various grafting methods (i.e. side tongue, top cleft, side veneer, and whip-and-tongue) were tested. In experiment 2, three Irvingia species rootstocks (i.e. I. grandifolia, I. gabonensis and I. wombolu) were tested for the grafting of scions of I. gabonensis. Experiment 1 shows that the grafting method significantly affected the percentage of graft success all the tested species except G. kola where all methods resulted in a very high percentage of graft success. The top cleft grafting method had the highest percentage of success, whatever the species. Experiment 2 shows that the type of rootstock significantly influenced the graft success of I. gabonensis scions, with I. wombolu rootstocks showing the highest percentage of graft success at 45.5 ± 7.75%. Our results can guide future propagation programs for these priority fruit tree species for domestication purposes.

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