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Aim:The conservation and effective use of crop genetic diversity are crucial to overcome challenges related to human nutrition and agricultural sustainability. Farmers' traditional varieties ("landraces") are major sources of genetic variation. The degree of representation of crop landrace diversity in ex situ conservation is poorly understood, partly due to a lack of methods that can negotiate both the anthropogenic and environmental determinants of their geographic distributions. Here, we describe a novel spatial modelling and ex situ conservation gap analysis modelling framework for crop landraces, using common bean (Phaseolus vulgaris L.) as a case study. Location: The Americas. Methods: The modelling framework includes five main steps: (a) determining relevant landrace groups using literature to develop and test classification models; (b) modelling the potential geographic distributions of these groups using occurrence (landrace presences) combined with environmental and socioeconomic predictor data; (c) calculating geographic and environmental gap scores for current genebank collections; (d) mapping ex situ conservation gaps; and (e) compiling expert inputs. Results: Modelled distributions and conservation gaps for the two genepools of common bean (Andean and Mesoamerican) were robustly predicted and align well with expert opinions. Both genepools are relatively well conserved, with Andean ex situ collections representing 78.5% and Mesoamerican 98.2% of their predicted geographic distributions. Modelling revealed additional collection priorities for Andean landraces occur primarily in Chile, Peru, Colombia and, to a lesser extent, Venezuela. Mesoamerican landrace collecting priorities are concentrated in Mexico, Belize and Guatemala. Conclusions:The modelling framework represents an advance in tools that can be deployed to model the geographic distributions of cultivated crop diversity, to assess the comprehensiveness of conservation of this diversity ex situ and to highlight geographic areas where further collecting may be conducted to fill gaps in ex situ conservation. | 731RAMIREZ-VILLEGAS Et AL.

Crop landraces have unique local agroecological and societal functions and offer important genetic resources for plant breeding. Recognition of the value of landrace diversity and concern about its erosion on farms have led to sustained efforts to establish ex situ collections worldwide. The degree to which these efforts have succeeded in conserving landraces has not been comprehensively assessed. Here we modelled the potential distributions of eco-geographically distinguishable groups of landraces of 25 cereal, pulse and starchy root/tuber/fruit crops within their geographic regions of diversity. We then analysed the extent to which these landrace groups are represented in genebank collections, using geographic and ecological coverage metrics as a proxy for genetic diversity. We find that ex situ conservation of landrace groups is currently moderately comprehensive on average, with substantial variation among crops; a mean of 63% ± 12.6% of distributions is currently represented in genebanks. Breadfruit, bananas and plantains, lentils, common beans, chickpeas, barley and bread wheat landrace groups are among the most fully represented, whereas the largest conservation gaps persist for pearl millet, yams, finger millet, groundnut, potatoes and peas. Geographic regions prioritized for further collection of landrace groups for ex situ conservation include South Asia, the Mediterranean and West Asia, Mesoamerica, sub-Saharan Africa, the Andean mountains of South America and Central to East Asia. With further progress to fill these gaps, a high degree of representation of landrace group diversity in genebanks is feasible globally, thus fulfilling international targets for their ex situ conservation.

The datasets and code presented in this article are related to the research article entitled “Comprehensiveness of conservation of useful wild plants: an operational indicator for biodiversity and sustainable development targets”1. The indicator methodology includes five main steps, each requiring and producing data, which are fully described and available here. These data include: species taxonomy, uses, and general geographic information (dataset 1); species occurrence data (dataset 2); global administrative areas data (dataset 3); eco-geographic predictors used in species distribution modeling (dataset 4); a world map raster file (dataset 5); species spatial distribution modeling outputs (dataset 6); ecoregion spatial data used in conservation analyses (dataset 7); protected area spatial data used in conservation analyses (dataset 8); and countries, sub-regions, and regions classifications data (dataset 9). These data are available at http://dx.doi.org/10.17632/2jxj4k32m2.1. In combination with the openly accessible methodology code (https://github.com/CIAT-DAPA/UsefulPlants-Indicator), these data facilitate indicator assessments and serve as a baseline against which future calculations of the indicator can be measured. The data can also contribute to other species distribution modeling, ecological research, and conservation analysis purposes.

Very similar morphologies have always been pointed out for subsections Natrix and Viscosae of the genus Ononis L. Morphological, environmental and biogeographic approaches do not show significant differences between taxa of both subsections, and only life form was pointed out as biological descriptor to explain taxonomic and ecological strategies for these taxa: Natrix is composed by perennial life forms, while Viscosae is solely represented by annual life forms. The discussion of results was conducted through the insurance hypothesis, according to which resilient or resistant behaviours, here represented by taxonomic diversity and morpho-environmental variability, described the ecological strategies for these taxa. In this way, wider morpho-environmental variability induced more responses (higher taxonomic diversity and life forms), i.e. more resilience. On contrary, the narrower morpho-environmental variability induced less taxonomic diversity and only perennial life forms, i.e. more resistance. Two future climate change scenarios were also used to confirm these resilience and resistance strategies for both subsections.