Cacao (Theobroma cacao) cultivation maintaining a high proportion of shade trees in a diverse composition (agroforestry) is currently being viewed as a sustainable land use practice. Our research hypothesis was that cacao agroforests (AF) can support relatively high tree diversity, as compared to surrounding primary and/or secondary forests. The objective of this study was to assess the impact of forest conversion on tree communities by comparing tree composition, community characteristics (richness and diversity) and spatial structure (density, canopy height, basal area) among primary forest, secondary forest, and cacao AF. In total, we collected data from 30 25 x 25 m plots on three land use systems (20 in cacao AF, five in secondary, and five in primary forests) in San Alejandro, Peruvian Amazon. All trees with DBH >= 10 cm were counted, identified to species, and their height and DBH were recorded. Our results support the hypothesis that cacao AF present a relatively high tree species richness and diversity, although they are no substitute for natural habitats. We identified most common species used for shading cacao. Tree species composition similarity was highest between cacao AF and secondary forest. Vegetation structure (density, height, DBH) was significantly lower compared to primary and secondary forest. Species richness and diversity were found to be highest in the primary forest, but cacao AF and secondary forests were fairly comparable. The tree species cultivated in cacao AF are very different from those found in primary forest, so we question whether the relatively high tree diversity and richness is able to support much of the diversity of original flora and fauna
Camu-camu [Myrciaria dubia (Kunth) McVaugh] is currently an important and promising fruit species grown in the Peruvian Amazon, as well as in Brazil, Colombia, and Bolivia. The species is valued for its high content of fruit-based vitamin C. Large plantations have been established only in the last two decades, and a substantial part of the production is still obtained by collecting fruits from the wild. Domestication of the species is at an early stage; most farmers cultivate the plants without any breeding, or only through a simple mass selection process. The main objective of the study was to characterize morphological and genetic variation within and among cultivated and natural populations of camu-camu in the Peruvian Amazon. In total, we sampled 13 populations: ten wild in the Iquitos region, and three cultivated in the Pucallpa region in the Peruvian Amazon. To assess the genetic diversity using seven microsatellite loci, we analyzed samples from ten individual trees per each population (n = 126). Morphological data was collected from five trees from each population (n = 65). The analysis did not reveal statistically significant differences for most of the morphological descriptors. For wild and cultivated populations, the observed heterozygosity was 0.347 and 0.404 (expected 0.516 and 0.506), and the fixation index was 0.328 and 0.200, respectively. Wild populations could be divided into two groups according to the UPGMA and STRUCTURE analysis. In cultivated populations, their approximate origin was determined. Our findings indicate a high genetic diversity among the populations, but also a high degree of inbreeding within the populations. This can be explained by either the isolation of these populations from each other or the low number of individuals in some populations. This high level of genetic diversity can be explored for the selection of superior individuals for further breeding.
Vitellaria paradoxa (C.F.Gaertn.) is a multi-purpose tree species distributed in a narrow band across sub-Saharan Africa. The species is integrated into cropping and agroforestry systems as a nutritional and economic resource, which provides a range of environmental services. Integration of the species into land-use systems provides an essential source of livelihoods and income for local populations. The economic potential of the shea butter tree derives from its edible products, which also serve cosmetic and pharmaceutical applications. To understand the current state of knowledge about V. paradoxa, this paper summarizes information about the ecology, population structure, and genetic diversity of the species, also considering compositional variation in the pulp and kernels, management practices, and efforts towards its domestication. Despite the great potential of the shea butter tree, there are some gaps in the understanding of the genetics of the species. This review presents up-to-date information related to the species for further domestication and breeding purposes.
Baobab ( Adansonia digitata L.) is an iconic tree of African savannahs. Its multipurpose character and nutritional composition of fruits and leaves offer high economic and social potential for local communities. There is an urgent need to characterize the genetic diversity of the Kenyan baobab populations in order to facilitate further conservation and domestication programmes. This study aims at documenting the genetic diversity and structure of baobab populations in southeastern Kenya. Leaf or bark samples were collected from 189 baobab trees in seven populations distributed in two geographical groups, i.e. four inland and three coastal populations. Nine microsatellite loci were used to assess genetic diversity. Overall, genetic diversity of the species was high and similarly distributed over the populations. Bayesian clustering and principal coordinate analysis congruently divided the populations into two distinct clusters, suggesting significant differences between inland and coastal populations. The genetic differentiation between coastal and inland populations suggests a limited possibility of gene flow between these populations. Further conservation and domestications studies should take into consideration thegeographical origin of trees and more attention should be paid to morphological characterization of fruits and leaves of the coastal and inland populations to understand the causes and the impact of the differentiation.
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.
hi@scite.ai
10624 S. Eastern Ave., Ste. A-614
Henderson, NV 89052, USA
Copyright © 2024 scite LLC. All rights reserved.
Made with 💙 for researchers
Part of the Research Solutions Family.