Originating from the Andean region and co-evolved with its food plant, the potato (Solanum sp.), the potato tuber moth Phthorimaea operculella (Zeller) has become an invasive potato pest globally. The hypothesis of our present study was that the future distribution and abundance (damage potential) of this pest will be greatly affected by climate-change-caused changes in temperature. We used a process-based climatic phenology model for P. operculella and applied three risk indices (establishment-, generation, and activity index) in a geographic information system (GIS) environment to map and quantify changes for climate change scenarios of the year 2050 based on downscaled climate-change data of the scenario A1B from the WorldClim database. All applications and simulations were made using the Insect Life Cycle Modeling (ILCYM) software recently developed by The International Potato Center, Lima, Peru. The study concludes that there are three possible main scenarios of changes that may simultaneously occur: (1) the P. operculella damage potential will progressively increase in all regions where the pest already prevails today with an excessive increase in warmer cropping regions of the tropics and subtropics. In regions where P. operculella is established and develops >4 generations per year, economic losses are likely to occur; under the current climate, >4 generations are developed on 30.1% of the total potato production area worldwide, which will increase until the year 2050 to 42.4%, equal to an increase of 2,409,974 ha of potato under new infestation. (2) A range expansion in temperate regions of the northern hemisphere with additionally 8.6% (699,680 ha), 4.2% (32,873 ha), and 2.7% (234,404 ha) of the potato production area under higher risk in Asia, North America, and Europe, with moderate increases of its damage potential. (3) A range expansion in tropical temperate mountainous regions with a moderate increase of its damage potential; e.g., in Bolivia, Ecuador and Peru 44,281 ha, 9569 ha, and 39,646 ha of potato will be under new risk of infestation. The ILCYM software allowed a detailed analysis of possible climate-change-induced changes in temperature on P. operculella distribution and damage potential. Further, this tool offers means of overcoming limitations in predictions and mapping experienced with climate data interpolation and resolution by spatial point-by-point simulations at locations of interest. The methodology is proposed as a very helpful tool for adaptation planning in integrated pest management.
GRIN-Global (GG) is a database application that enables genebanks to store and manage information associated with plant genetic resources (germplasm) and deliver that information globally. The GRIN-Global project’s mission is to provide a scalable version of the Germplasm Resource Information Network (GRIN) suitable for use by any interested genebank in the world. The GRIN-Global database platform has been and is being implemented at various genebanks around the world. The first version, 1.0.7, was released in December, 2011 in a joint effort by the Global Crop Diversity Trust, Bioversity International, and the Agricultural Research Service of the USDA. The U.S. National Plant Germplasm System version (22.214.171.124) entered into production on November 30, 2015.
Typically set up in a networked environment, GG can also run stand-alone on a single personal computer. GG has been developed with open source software and its source code is available, and Genebanks can thus tailor GG to meet their specific requirements. GG comprises a suite of programs, including a Curator Tool, Updater, Search Tool, Admin Tool, and Public Website with Shopping Cart. Through the Public Website, researchers can access germplasm information; search the entire GG database and download results; and order germplasm from the genebank. Data are also associated with Google Maps.
Current installations include Bolivia (INIAF), Chile (INIA), CIMMYT (CGIAR), Czech Republic (Crop Research Institute), Portugal (INIAV), USDA (NPGS), Tunisia (BNG), CIP (CGIAR), Genetic Resources of Madeira Island (Portugal), CIAT (CGIAR) with many others under evaluation.