Brainfood: GI, Collection representativeness, Miracle tree, Brave new world, Wheat roots, Dry beans, Seedling roots, Ecotourism, Citrus evolution, Mango evolution, Aboriginal translocation, Carrot cores, Potato breeding

Brainfood: Green Revolution, Pear diversity, Spider plant, Mexican maize erosion, Wheat yield, Salty carrots, Salinity tolerance, Diversification, Ancient farmers, Genebank training, Grapevine diversity, Dietary diversity, Wild chickpeas, Hulless barley

Nibbles: Grape breeding, Vanilla breeding, DSI policy, ITPGRFA, Maori taro, Dhofar memories

  • Marker-assisted breeding in grapes: like skimming through a book looking for key words.
  • Vanilla genome: going from no-frills vehicle to luxury sportscar.
  • CGN on what to do to ensure continued access to that book — or car.
  • A topic which is all the rage right now in the ITPGRFA, on which this is a one-page primer.
  • 14th century Māori grew taro as well as sweet potato.
  • Great infographics on the fascinating region of Dhofar in southern Oman, in which I collected germplasm many years ago. Great opportunity to reminisce.

Free book on mapping species

The book in question is Mapping Species Distributions: Spatial Inference and Prediction by Janet Franklin, from 2010 I think. Here’s the blurb:

Maps of species’ distributions or habitat suitability are required for many aspects of environmental research, resource management and conservation planning. These include biodiversity assessment, reserve design, habitat management and restoration, species and habitat conservation plans and predicting the effects of environmental change on species and ecosystems. The proliferation of methods and uncertainty regarding their effectiveness can be daunting to researchers, resource managers and conservation planners alike. Franklin summarises the methods used in species distribution modeling (also called niche modeling) and presents a framework for spatial prediction of species distributions based on the attributes (space, time, scale) of the data and questions being asked. The framework links theoretical ecological models of species distributions to spatial data on species and environment, and statistical models used for spatial prediction. Providing practical guidelines to students, researchers and practitioners in a broad range of environmental sciences including ecology, geography, conservation biology, and natural resources management.

Have fun.