Combining interactive GIS tools and expert knowledge in validation of tree species models

Poster presented at XIII Congreso Forestal Mundial. FAO, Buenos Aires (Argentina). 18-25 Oct 200

Training manual on spatial analysis of plant diversity and distribution

This training manual is intended for scientists and students who work with biodiversity data and are interested in developing skills to effectively carry out spatial analysis based on (free) GIS applications with a focus on diversity and ecological analyses. These analyses offer a better understanding of spatial patterns of plant diversity and distribution, helping to improve conservation efforts. The training manual focuses on plants of interest for improving livelihoods (e.g. crops, trees and crop wild relatives) and/or those which are endangered. Spatial analyses of interspecific and intraspecific diversity are explained using different types of data: • species presence • morphological characterization data • molecular data Although this training focuses on plant diversity, many of the types of analyses described can also be applied for other organisms such as animals and fungi. The manual is based on specific exercises, based on real project data. In order to use the manual, you will also need to download (please click on reference material to download exercises) the relevant exercise data (listed below). Exercise data: 2.1 Importing observation data 5.2 Diversity - Phenotypic data 2.2 Importing climate data 5.3 Diversity - Molecular marker data 3.1 Basic elements 5.4 Conservation strategies 3.2 Export to Google Earth 6.1 Realized niche 4.1 Quality control – Administrative units 6.2_potential_distribution.zip 4.2 Quality control – Atypical points 6.3 Climate change 5.1 Species diversity 6.4 Gap analysis The manual can be used for self-learning as well as for training events like seminars or short courses on the fundamentals of spatial analysis

Genetic Population Structure of Cacao Plantings within a Young Production Area in Nicaragua

Significant cocoa production in the municipality of Waslala, Nicaragua, began in 1961. Since the 1980s, its economic importance to rural smallholders increased, and the region now contributes more than 50% of national cocoa bean production. This research aimed to assist local farmers to develop production of high-value cocoa based on optimal use of cacao biodiversity. Using microsatellite markers, the allelic composition and genetic structure of cacao was assessed from 44 representative plantings and two unmanaged trees. The population at Waslala consists of only three putative founder genotype spectra (lineages). Two (B and R) were introduced during the past 50 years and occur in >95% of all trees sampled, indicating high rates of outcrossing. Based on intermediate allelic diversity, there was large farm-to-farm multilocus genotypic variation. GIS analysis revealed unequal distribution of the genotype spectra, with R being frequent within a 2 km corridor along roads, and B at more remote sites with lower precipitation. The third lineage, Y, was detected in the two forest trees. For explaining the spatial stratification of the genotype spectra, both human intervention and a combination of management and selection driven by environmental conditions, appear responsible. Genotypes of individual trees were highly diverse across plantings, thus enabling selection for farm-specific qualities. On-farm populations can currently be most clearly recognized by the degree of the contribution of the three genotype spectra. Of two possible strategies for future development of cacao in Waslala, i.e. introducing more unrelated germplasm, or working with existing on-site diversity, the latter seems most appropriate. Superior genotypes could be selected by their specific composite genotype spectra as soon as associations with desired quality traits are established, and clonally multiplied. The two Y trees from the forest share a single multilocus genotype, possibly representing the Mayan, ‘ancient Criollo’ cacao

Diversity of cacao trees in Waslala, Nicaragua: Associations between genotype spectra, product quality and yield potential

The sensory quality and the contents of quality-determining chemical compounds in unfermented and fermented cocoa from 100 cacao trees (individual genotypes) representing groups of nine genotype spectra (GG), grown at smallholder plantings in the municipality of Waslala, Nicaragua, were evaluated for two successive harvest periods. Cocoa samples were fermented using a technique mimicking recommended on-farm practices. The sensory cocoa quality was assessed by experienced tasters, and seven major chemical taste compounds were quantified by near infrared spectrometry (NIRS). The association of the nine, partially admixed, genotype spectra with the analytical and sensory quality parameters was tested. The individual parameters were analyzed as a function of the factors GG and harvest (including the date of fermentation), individual trees within a single GG were used as replications. In fermented cocoa, significant GG-specific differences were observed for methylxanthines, theobromine-to-caffeine (T/C) ratio, total fat, procyanidin B5 and epicatechin, as well as the sensory attributes global score, astringency, and dry fruit aroma, but differences related to harvest were also apparent. The potential cocoa yield was also highly determined by the individual GG, although there was significant tree-to-tree variation within every single GG. Non-fermented samples showed large harvest-to-harvest variation of their chemical composition, while differences between GG were insignificant. These results suggest that selection by the genetic background, represented here by groups of partially admixed genotype spectra, would be a useful strategy toward enhancing quality and yield of cocoa in Nicaragua. Selection by the GG within the local, genetically segregating populations of seedpropagated cacao, followed by clonal propagation of best-performing individuals of the selected GG could be a viable alternative to traditional propagation of cacao by seed from open pollination. Fast and gentle air-drying of the fermented beans and their permanent dry storage were an efficient and comparatively easy precondition for high cocoa quality. (Résumé d'auteur