The GlobalUsefulNativeTrees species selection App combines species data from the Botanic Gardens Conservation International GlobalTreeSearch database (GTS) ( website ; Beech et al. 2017 ) with data available from the World Checklist of Useful Plant Species (WCUPS) ( Diazgranados et al. 2020 ). GTS documents the native country distribution of close to 60,000 tree species, whereas the WCUPS contains 40,283 plant species names from the Plantae kingdom, documenting human usage across 10 categories of usage that was modified from the Economic Botany Data Collections Standard.
Tag: computer software
ShadeMotion: tree shade patterns in coffee and cocoa agroforestry systems
Shade trees in coffee and cocoa agroforestry systems provide valuable livelihoods and other ecosystem services. Unfortunately, most shade canopies are sub-optimally designed and managed and the reasons behind this sub-optimality are poorly known. There is evidence, however, indicating that farmers and extension agents lack both the knowledge and access to user-friendly tools to optimally design their shade canopies. To fill this gap, we developed ShadeMotion, a simple to parameterize, yet powerful software, capable of calculating the spatial and temporal distribution of the shade cast by trees on a plot (horizontal or tilted) anywhere on Earth. Trees may be planted in any spatial arrangement, their population density can change according to planting, thinning, mortality or harvest, tree crowns may take any of eight possible, regular, geometric shapes, vary in density and monthly leaf fall patterns, and may be pollarded or not. Shade patterns may be calculated for one instant, 1 year or less, or for the entire life cycle of a plantation; in the latter case, tree growth data must be added as input. Shade can be measured at ground level or at any height above the ground. In this article, we: (1) describe the key features of the software, and (2) simulate the spatial and temporal shade patterns of a traditional agroforestry system of Coffea arabica cv. Caturra, Erythrina poeppigiana and Cordia alliodora in Costa Rica. ShadeMotion can realistically model farm scenarios and may be used in the participatory design of agroforestry systems in farmers field schools and in classrooms.
Redundancy analysis with vegan and BiodiversityR as an alternative to Discriminant Analysis of Principal Components for the analysis of genetically structured populations
Jombart et al. 2010 described their methodology of Discriminant Analysis of Principal Components(DAPC) for the analysis of genetically structured populations as a new methodological approach that retained all the assets of Discriminant Analysis, whereas not being burdened by its limitation of requiring the number of variables (alleles) to be less than the number of observations (individuals).
Cluster diagrams with pvclust ggraph and ggplot2
The main objective of this document is to show a pathway of generating dendrograms via the ggraph package for results that were obtained via pvclust. I expect that similar pathways can be used to generate dendrograms with ggraph.
Adding dendrograms to ordination graphs with pvclust, vegan, BiodiversityR and ggplot2
The main objective of this document is to show a pathway of how dendrograms for results that were obtained via pvclust can be added to ordination graphs in ggplot2. This documents builds on previous document where I showed how to generate ordination graphs with vegan, BiodiversityR and ggplot2 and how to create dendrograms for pvclust results with ggraph.
Analysis of Molecular Variance (AMOVA) with vegan and BiodiversityR, including a graphical method to identify potential migrants
Over a decade ago, while working on a manual for statistical analysis of dominant markers (this manual was partially inspired by a previous manual on the statistical analysis of biodiversity and community ecology data), I had explored the similarities between (i) Analysis of Molecular Variance (AMOVA) that was originally developed by Excoffier et al. 1992 ( See here for a recent expansion of the framework to autopolyploids ) and (ii) Ordination methods and Multivariate Analysis of Variance Using Distance Matrices in the field of community ecology (I provide references for these in subsequent sections). Whereas the manual is now more than a decade old (although many methods are still relevant; those interested could compare with this recent Review of Best Practices Population Genetic Analysis), in my opinion it remains valid to still highlight the connections between AMOVA and several methods of community ecology that are directly available via the vegan and BiodiversityR packages.
Calculating Distance Matrices with Weighted Combinations of Functional Traits and Taxonomic Distinctness
The FD package includes methods for calculating the weighted Gower dissimilarity index, through methods described in A distance‐based framework for measuring functional diversity from multiple traits. The vegan package includes methods for calculating taxonomic distances, through methods described in A taxonomic distinctness index and its statistical properties.
Renyi Diversity Profiles with vegan, BiodiversityR and ggplot2
The main objective of this document is to give some examples of how data on Renyi diversity profiles, obtained via vegan and BiodiversityR, can be plotted via ggplot2. I expect that researchers and students will modify the scripts given here to create their own graphs. This obviously requires some working knowledge of the ggplot2 package, for which I will not give details here on specific functions, arguments and choices that I selected (as an introduction to ggplot2, I would especially recommend a two-part online workshop given by Thomas Lin Pedersen).
Ordination graphs with vegan, BiodiversityR and ggplot2
The main objective of this document is to give some examples of how data from ordination, such non metric multidimensional scaling or redundancy analysis that were obtained via vegan and BiodiversityR, can be plotted via ggplot2. The key intermediate steps to allow plotting with ggplot2 is to get data in the ‘long’ (tidy) format that is used in ggplot2, which can be achieved with some functions in BiodiversityR that should work with most ordination results.
Species Accumulation Curves with vegan, BiodiversityR and ggplot2
The main objective of this document is to give some examples of how data on species accumulation curves, obtained via vegan and BiodiversityR, can be plotted via ggplot2. I expect that researchers and students will modify the scripts given here to create their own graphs. This obviously requires some working knowledge of the ggplot2 package, for which I will not give details here on specific functions, arguments and choices that I selected (as an introduction to ggplot2, I would especially recommend a two-part online workshop given by Thomas Lin Pedersen).