Biology subjects

Kindt, R.

Publications and source records attributed to Kindt, R..

5 recordsLinked to original sources

bioRxiv2025

The Agroforestry Species Switchboard, a global resource to explore information for 107,269 plant species

The Agroforestry Species Switchboard is a comprehensive vascular plant database that guides users to information for a particular taxon from a global but fragmented set of resources. Via standardized species names, a user can rapidly infer which among the 59 contributing databases contain information for a species of interest, and understand how this information can be accessed. By providing taxonomic identifiers to World Flora Online, it is straightforward to check for changes in taxonomy. Among the 59 databases referenced, ten covered over 10,000 species, 20 between 1,000 and 10,000 species, and 22 between 100 and 1,000 species. The ten species-richest plant families across covered databases were the Fabaceae (9,537 species), Asteraceae (6,041), Rubiaceae (4,812), Poaceae (3,947), Myrtaceae (3,544), Euphorbiaceae (2,689), Malvaceae (2,478), Rosaceae (2,374), Lauraceae (2,334) and Lamiaceae (2,107). Information included in the Switchboard distinguishes 54,812 tree-like species, covering most known tree species globally. Among its applications, the Switchboard can assist species selection for ecological restoration projects to synergize biodiversity and human well-being objectives.

ecology↗

bioRxiv2023

TreeGOER: a database with globally observed environmental ranges for 48,129 tree species

The BIOCLIM algorithm provides a straightforward method to estimate the effects of climate change on the distribution of species. Estimating the core ranges of species from 5% and 95% quantiles of bioclimatic variables, the algorithm remains widely used even when more sophisticated methods of species distribution modelling have become popular. Where sufficient representative observations are available, I expect that BIOCLIM correctly identifies locations that would not be suitable in a future climate. To accommodate climate change investigations based on BIOCLIM for 48,129 tree species (a substantial subset of known tree species), I developed the TreeGOER (Tree Globally Observed Environmental Ranges) database, providing information on environmental ranges for 38 bioclimatic, 8 soil and 3 topographic variables. The database can be accessed from: https://doi.org/10.5281/zenodo.7922928. Statistics that include 5% and 95% quantiles were estimated for a cleaned and taxonomically standardized occurrence data set with different methods of outlier detection, with estimates for roughly 45% of species being based on 20 or more observation records. Inferred core bioclimatic ranges of species along global temperature and moisture index gradients and across continents follow the known global distribution of tree diversity such as its highest levels in moist tropical forests and the odd man out pattern of lower levels in Africa. To demonstrate how global analyses for large numbers of tree species can easily be done in R with TreeGOER, here I present two case studies. The first case study investigated latitudinal trends of tree vulnerability and compared these with previous results obtained for urban trees. The second case study focused on tropical areas, compared trends in different longitudinal zones and investigated patterns for the moisture index. TreeGOER is expected to benefit researchers conducting biogeographical and climate change research for a wide range of tree species at a variety of spatial and temporal scales.

ecology↗

bioRxiv2022

GlobalUsefulNativeTrees, a database of 14,014 tree species and their uses, supports synergies between biodiversity recovery and local livelihoods in landscape restoration

Tree planting has the potential to improve the livelihoods of millions of people as well as to support environmental services such as biodiversity preservation. Planting however needs to be executed wisely if benefits are to be achieved. We have developed the GlobalUsefulNativeTrees (GlobUNT) database to directly support the principles advocated by the golden rules for reforestation, including planting tree mixtures that maximize the benefits to local livelihoods and the diversity of native trees. Developed primarily by combining data from GlobalTreeSearch with the World Checklist of Useful Plant Species, GlobUNT includes 14,014 tree species that can be filtered for ten major use categories, across 242 countries and territories. In a subcontinental comparison GlobUNT revealed that Malesia had the highest useful tree species richness (3,349) and was also richest for materials (2,723), medicines (1,533), human food (958), fuel (734), environmental uses (632), social uses (614), animal food (443), poisons (322) and invertebrate food (266).

ecology↗

bioRxiv2021

AlleleShift: An R package to predict and visualize population-level changes in allele frequencies in response to climate change

BackgroundAt any particular location, frequencies of alleles in organisms that are associated with adaptive traits are expected to change in future climates through local adaption and migration, including assisted migration (human-implemented when climate change is more rapid than natural migration rates). Making the assumption that the baseline frequencies of alleles across environmental gradients can act as a predictor of patterns in changed climates (typically future but possibly paleo-climates), a methodology is provided by AlleleShift of predicting changes in allele frequencies at populations locations. MethodsThe prediction procedure involves a first calibration and prediction step through redundancy analysis (RDA), and a second calibration and prediction step through a generalized additive model (GAM) with a binomial family. As such, the procedure is fundamentally different to an alternative approach recently proposed to predict changes in allele frequencies from canonical correspondence analysis (CCA). My methodology of AlleleShift is also different in modelling and predicting allele counts through constrained ordination (not frequencies as in the CCA approach) and modelling both alleles for a locus (not solely the minor allele as in the CCA method; both methods were developed for diploid organisms where individuals are homozygous (AA or BB) or heterozygous (AB)). Whereas the GAM step ensures that allele frequencies are in the range of 0 to 1 (negative values are sometimes predicted by the RDA and CCA approaches), the RDA step is based on the Euclidean distance that is also the typical distance used in Analysis of Molecular Variance (AMOVA). The AlleleShift::amova.rda enables users to verify that the same mean-square values are calculated by AMOVA and RDA, and gives the same final statistics with balanced data. ResultsBesides data sets with predicted frequencies, AlleleShift provides several visualization methods to depict the predicted shifts in allele frequencies from baseline to changed climates. These include dot plot graphics (function shift.dot.ggplot), pie diagrams (shift.pie.ggplot), moon diagrams (shift.moon.ggplot), waffle diagrams (shift.waffle.ggplot) and smoothed surface diagrams of allele frequencies of baseline or future patterns in geographical space (shift.surf.ggplot). As these were generated through the ggplot2 package, methods of generating animations for a climate change time series are straightforward, as shown in the documentation of AlleleShift and in the supplementary materials. In addition, graphical methods are provided of showing shifts of populations in environmental space (population.shift) and to assess how well the predicted frequencies reflect the original frequencies for the baseline climate (freq.ggplot). AvailabilityAlleleShift is available as an open-source R package from https://github.com/RoelandKindt/AlleleShift. Genetic input data is expected to be in the adegenet::genpop format, which can be generated from the adegenet::genind format. Climate data is available from various resources such as WorldClim and Envirem.

genomics↗

bioRxiv2020

WorldFlora: An R package for exact and fuzzy matching of plant names against the World Flora Online Taxonomic Backbone data

Premise of the studyStandardization of plant names is a critical step in various fields of biology including biodiversity, biogeography and vegetation research. WorldFlora matches lists of plant names with a static copy from World Flora Online (WFO), an ongoing global effort of completing an online flora of all known vascular plants and bryophytes by 2020. Methods and resultsBased on direct and fuzzy matching, WorldFlora inserts matching cases from the WFO to a submitted data set of with taxa. Results of selecting the expected best single matches are presented for four data sets, including a working list of commercial timber tree species, a subset from GlobalTreeSearch and 2 data sets used in previous comparisons of software tools for correcting taxon names. The success rate of credible matches varied from 94.7 (568 taxa) to 99.9 (1740 taxa) percent. ConclusionsWorldFlora offers a straightforward pipeline for semi-automatic plant name checking.

plant biology↗