Sarika Mittra
In module 2, you learned how to model crop adaptation using spatial data in a geographic information system (GIS) and how to select appropriate software and tools. Learning included the identification, preparation, downloading, and analysis of useful data, as well as cleaning and preparation of data to make it compatible with the selected GIS software. Climate change analysis can help identify differences in climate variables at different sites over various periods. This, in turn, can enable researchers, farmers, and other stakeholders to identify potential adaptation measures, such as assessing the vulnerability of the target sites (i.e., your own project site) to climate change and selecting pre-adapted genotypes from reference sites (one or more climate-matching or analogous sites) for testing and implementing measures to conserve agricultural biodiversity.
In this module, you will learn how to conduct climate change analysis and use the results to identify promising gene bank collections. The key questions are: How can geographic coordinates be added to an accession that was collected without such coordinates? How can a collection be classified according to climate to make it more manageable? What are the current climate conditions at the collection site? What changes in climate have occurred at that site over what period? Which climate variables have been most affected? For any target site, what reference site best matches its changed climate?Which germplasm accessions from the reference site are the best candidates for potential adaptation at the target site?
At the end of the module you will have a list of germplasm accessions of interest, some or all of which you might want to access for field testing at your research site.
At the end of this module, you will be able to:
Climate is the general long-term (at least 30 years) prevailing weather conditions of a region, including temperature, precipitation, sunlight, wind, and cloud cover. Climate change, which is a direct result of increased concentrations of carbon dioxide in the atmosphere, refers to alterations in weather patterns for an extended period that have a profound impact on agriculture, water resources, forests, and other sectors. The complex effects on agriculture include changes in the growing season and the availability of arable land globally, which, in turn, have implications for global food security. Studies have shown that for the period 1980-2008 global maize and wheat production declined by 3.8% and 5.5%, respectively, with current climate trends (Lobell et al. 2011). Global food yields will generally decrease by roughly 1.5% per decade with the current warming trends if adaptation measures are not taken (Lobell and Gourdji 2012). The use of various GIS software and tools to model the impact of climate change and develop adaptation strategies has been well documented. A composite approach is used for spatial analysis that incorporates the required climate variables, which can be visualized at the local, regional, or global level, to interpret outcomes at the desired spatial level. This is an important feature of GIS tools, as current climate modeling relies predominantly on the numerical general circulation models (GCMs), which are both complex and global in scope. To make them relevant to local applications, these projections must be downscaled to a local or regional level to make the outcomes interpretable. GIS software and tools are generally designed to allow the modeling of spatial data and its visualization in an easy form.
A key function of plant genetic resources centres is germplasm collection, which has been practised throughout the world in varying degrees over centuries. Although the norm has always been to note the location of the collection site, standardized formats for passport data attached to accessions are relatively new. Even more recent is the method of noting location by recording geographic coordinates. Although earlier collectors noted such details as administrative unit, closest town or village, distance from the road, etc., this information can never be as precise as geographic coordinates, which are unique to any point on the Earth’s surface.
Geographic coordinates are a set of numbers (or letters) assigned to every location on the Earth. They are derived from a mathematical model to calculate the horizontal position (using two numbers) and the vertical position (using one number) of a location. Longitude and latitude (for horizontal position) and altitude (for vertical position) are the most common geographic coordinates. Handheld Global Positioning System (GPS) units are usually used to record geographic coordinates, and this method became available only after 1980 when the United States Department of Defense made the GPS available for civilian use. Even in the 1980s and the 1990s, handheld GPS units were too expensive for general use, and most collectors recorded only qualitative location information. However, methods are available to determine geographic coordinates from secondary sources that are precise or nearly so.
The availability of precise location information is important, as that will affect the subsequent analyses and results. Currently, the most popular method for determining locations is to use Google Earth, which has a huge database of georeferenced sites. In addition, on several websites (e.g., http://www.latlong.net/ and http://mynasadata.larc.nasa.gov/latitudelongitude-finder/), one can enter the name of a location or the nearest town or village and obtain the geographic coordinates instantly. Most of these sites are available free to the user. If digital databases on the Internet do not provide a useful result, then detailed analogue maps, such as large-scale topographical sheets, can be used to find the coordinates.
Geographic coordinates are needed to derive other data about a collection site, such as climate, soil type, water availability, and other factors affecting growing conditions. Once accessions have been assigned geographic coordinates, the random dataset can be classified according to climate, which will organize the collection in a more efficient manner and allow patterns to be easily deduced.
Several methods can be used to extract information (past, present, and future) from climate databases in GIS software based on geographic coordinates; these are explained in Module 2. Online platforms, such as the MarkSim DSSAT Weather File Generator (http://gismap.ciat.cgiar.org/MarkSimGCM/), can be used both to find geographic coordinates (through its Google Earth plugin) and to extract daily data for a year for the three key climate variables: rainfall, temperature, and radiation (Jones et al. 2011). Although MarkSim has web versions for both IPCC CMIP3 and CMIP5 data, other available online tools contain global, regional, or country-specific data (e.g., http://www.hko.gov.hk/wxinfo/pastwx/extract.htm) or offline tools with any GIS software can be used to extract data from climate databases. Extracted climate data can then be used to classify sites (Scheldeman and van Zonneveld, 2010). GIS software or statistical software, such as MS Excel and R, can be used to classify accessions using a variety of clustering techniques.
 Jones, P.G., Thornton, P.K., Heinke, J. , 2011 Generating characteristic daily weather data using downscaled climate model data from the IPCC Fourth Assessment This article describes the method for the downscaling GCM data that are available in the MarkSim DSSAT Weather File Generator, the use of the tool, and the accuracy of the downscaled data. |
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 Scheldeman, X., van Zonneveld, M., 2010 Training manual on spatial analysis of plant diversity and distribution Bioversity International, Rome, Italy This manual describes in detail all the tools available in the DIVA-GIS software. It contains links to exercise data that can be downloaded and used to perform spatial analysis of plant diversity and distribution using DIVA-GIS and visualization methods to display the end results. |
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Wilby, R.L., Troni, J., Biot, Y., Tedd, L., Hewitson, B.C., Smith, D.M., Sutton, R.T., 2009 A review of climate risk information for adaptation and development planning International Journal of Climatology 29: 1193–1215, This paper describes the development of tools for forecasting climate change scenarios for use in the assessment of adaptation mechanisms in several sectors and the knowledge gaps and improvements required to improve adaptation planning. |
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Vogel, K.P., Schmer, M.R., Mitchell, R.B. , 2005 Plant adaptation regions: ecological and climatic classification of plant materials. . United States Department of Agriculture, Agricultural Research Service, Paper 206 This paper offers an example of how a database of plant species can be made more meaningful and useful by classifying the data by ecology and climate. |
Selection of the suitable adaptation measures to cope with changing climate conditions requires climate models that simulate future conditions and provide a glimpse of a set of possibilities both spatially and temporally. As mentioned, GCMs can provide a view of current and future scenarios (under various probable conditions) and allow evaluation of the vulnerability of a site to changing climate. Subsequently, adaptation measures can be implemented that are best suited to mitigate the adverse effects. These measures include “corrective strategies” aimed at undoing or coping with the adverse effects through a diverse set of actions and “pre-emptive strategies” that anticipate future changes and implement actions to prevent the simulated future change.
Corrective strategies include developing improved genotypes that are resilient to such stresses as extreme temperatures, flooding, or drought. In case of the pre-emptive strategies, scientists and researchers can find a reference site whose climate matches (with a degree of probability) the climate of the target site, although they may be separated both spatially and temporally. One could then identify germplasm that might have traits of interest and explore options to test it in the target site. This is known as the climate analogue technique. Although still under development, its application in crop research is underway in a number of research sites around the world. Using climate analogues can provide a set of potential options for adaptation for the target site.
Once a site’s vulnerability to climate change has been assessed and its potential climate-matched sites identified, it is necessary to apply the outcomes of the analysis to identify those genotypes that can be tested in the vulnerable site. For example, if the temperature and precipitation conditions in target site A (in Asia) for 2020 match the temperature and precipitation conditions in reference site B (in Africa) for 2012 with a degree of probability of more than 60%, then the accessions grown currently in reference site B can be considered potentially pre-adapted for target site A and planted at target site A for testing.
However, although suitable climate conditions are a basic requirement for growing crops, other physical factors such as soil conditions and topography and non-physical factors such as socioeconomic conditions and the market also play an important part. Hence, testing for a few seasons under various conditions is necessary to conclude whether the identified genotype from reference site B can be grown successfully at target site A.
 Ramírez-Villegas, J., Lau, C., Köhler, A.K., Signer, J., Jarvis, A., Arnell, N., Osborne, T., Hooker, J. , 2011 Climate analogues: finding tomorrow’s agriculture today Working paper 12. CGIAR Research Program on Climate Change, Agriculture and Food Security, Cali, Colombia. This working paper on climate analogues was prepared by the developers of the tool. It explains the concept, its terms and assumptions, the method, how to use the tool, interpretation of the results, and its applications. |
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 Phillips, S.J., Anderson, R.P., Schapire, R.E. , 2006 Maximum entropy modeling of species geographic distributions. Ecological Modelling 190, , 231–259 This is a study of the background of the Maxent tool, explaining the concept and interpretation of results and assessing its accuracy. |
Here is a quiz that will help you test your newly acquired knowledge. Once you have covered the content sections and completed the assigned readings, please answer the Climate change analysis quiz.
In this module, you learned about the various GIS software programs and tools available both online and offline. Now your task is to establish the current and future climate conditions of a site and identify potential pre-adapted genotypes that can be tested at that site. Please document this step of the research process by identifying the following:
The next module in our research process is Germplasm acquisition. Let us begin!
