By Pashupati Chaudhary, LI-BIRD, Nepal
Agrobiodiversity plays a pivotal role in securing food and nutrition and enhancing resilience of agriculture to climate change. As the climate is becoming more erratic and unpredictable than in the past, it has become increasingly difficult to properly manage agrobiodiversity to sustainably produce food. One of the challenges is the lack of scientific knowledge to predict climate dynamics in particular regions. Another challenge is to develop and deploy crop varieties that are adapted to changing climatic conditions. Climate Analogue Tool (CAT), a recently developed tool by partners of the Climate Change, Agriculture and Food Security (CCAFS) programme is a remarkable breakthrough in tackling this problem. CAT can identify a) future climate conditions of a particular location and sites that currently resemble these conditions (b) locations that currently have or in the future will have similar climate conditions, and c) locations that in the future will have current climate conditions of a particular place. Based on careful analyses done using the Climate Analogue Tool and supported by data from actual conditions in farmers’ fields, scientists can identify possible appropriate plant genetic resources, deploy suitable varieties, and develop new varieties for specific locations of interest.
Recently, the Genetic Resources Policy Initiative 2 project, led by Bioversity International, organized a three-day long training workshop on Climate Analogue Tools in order to enhance skills of Nepal and Bhutan project staff in analyzing, interpreting and presenting climate data. 18 scientists, managers, and development professionals representing government organizations, national research programs, gene banks and non-governmental organizations of both countries participated in the training that was facilitated by Bioversity International scientists.
The participants were made familiar with GIS concepts, principles, practices and applications and taught to apply ArcGIS, Maxent, DIVA GIS, and Climate Analogue Tool and related techniques for plant genetic resources work. GIS was introduced as a tool to project data, modeling, scenario analysis, gap analysis and analogue site identification. We learned that reliable data are a must for using GIS tools, i.e. properly geo-referenced, free of duplications and readable. Data can be presented either in vector model (shape files) or raster model (grid files) and there are three types of shape files—point, line and polygon—that can be used to analyze spatial and temporal variations of any given feature. Participants learned that point is often used for locations, specific features, landmarks, etc.; line is used for rivers, roads, and other similar objects; and polygon is used to represent closed boundaries and delineated areas (e.g. village, forest, biodiversity hotspot).
Following lectures, we carried out hands-on practice using Maxent, DIVA GIS and Climate Analogue Tool. Results were then presented during a plenary toward the end of the training (see, examples of maps produced). During practice, participants were able to: learn converting data from one format to another and making them readable by different tools; analyze data and interpret results; produce maps from the results obtained; play around with legend and other basic features of a map; and copy, convert and save maps in various formats (e.g. MS Word, PowerPoint, JPEG). We also were able to identify what tool should be used for what purposes and what merits one tool has over the others. In addition, we received a short introduction to using a Global Positioning System (GPS). While participants expressed satisfaction with the training course in terms of content and approach, we faced some challenges while making use of different tools. They include: not all features appear while inserting the legends, coloring legends not properly adjustable, size of legend not adjustable in DIVA GIS, cropping/clipping images not available in DIVA GIS, and using CAT not possible without high-speed internet access. These challenges will be communicated to program designers so that they can make the tools more robust, reliable, and user-friendlly.