Information and Communication Technologies for climate change adaptation, with a focus on the agricultural sector

Climate change is widely recognized as one of the most complex challenges that humankind has to face in the next decades. As agriculture is likely to suffer the biggest impacts, sound adaptation processes are required to sustain agricultural production and food system as a whole. IPCC, the Intergovernmental Panel for Climate Change, stressed the ability of decision-makers to manage information as an important factor determining the chance for a community to adapt to climate change. This is one of the reason why the Information and Communication Technologies (ICT) can play an important role in this challenge. This paper summarizes the main categories of information systems applied in this field, particularly referring to the adaptation dimension and the agricultural sector. Introduction: the challenges of climate change in Agriculture Climate change is one of the most complex challenges that humankind has to face in the next decades. As the change process seems to be irreversible, it became urgent to develop sound adaptation processes to the current and future shifts in the climate system. In particular, it is likely that the biggest impacts of changes will be on agricultural and food systems over the next few decades (M. E. Brown, C. C. Funk, 2008). Some scientists (Lobell et al., 2008), thanks to the application of crop modeling tools, have pointed out that climate change is likely to reduce food availability because of a reduction in agricultural production. The Intergovernmental Panel for Climate Change, IPCC, a committee of the United Nations that every five years collects and reviews the most important scientific contributions to this issue, put in evidence that higher frequency and diffusion of climate fluctuations is likely to produce more severe and frequent droughts and floods, which already are the main causes of short-term fluctuations in food production in semiarid and sub-humid areas. Sub-saharan Africa and South Asia occupy the majority of these lands, meaning that the poorest regions of the world are going to face the highest degree of instability in food production (J. Bruinsma, 2003). J. Schmidhuber and F. N. Tubiello (2007) included investments in communications as an effective mean to address future climate change. Within this framework, it is crucial to identify information and communication systems that the farmers need in order to cope with the new conditions. This is particularly true for poor smallholder farmers, as in Africa where the majority of African farmers do not have access to the scientific and technological advances that support agricultural decision-making because of the lack of reliable communication networks (M. Boulahya et al, 2005). With regard to agronomic research, one of the major challenges will be to study how to fill the information needs of policy makers, and how to report and communicate research results in an effective way for supporting the adaptation of food systems to climate change (J.S.I. Ingram et al, 2008). To the same aim, in 2001 the IPCC underlined the local conditions that could determine if a community is likely to be able to adapt to changes: among the others, the ability of decision-makers to manage information was particularly stressed (IPCC, 2001). Information systems on climate change at local to regional level At the present time it is possible to recognize three major categories of information systems developed to study the issue at local to regional level. The three categories of information systems are the following: 1. comprehensive systems and methodologies for institutions; 2. downscaling tools for working at national and sub-national level; 3. systems and tools for specific sectors (e.g. agriculture, forestry, etc.). The first category comprises essentially theoretical methodologies based on different assumptions and approaches, developed to identify and quantify climate change impacts (e.g. IPCC Guidelines, UNEP handbook), assess vulnerability to climate change (e.g. UNEP Adaptation Policy Framework, APF) or do both kind of analysis (e.g. Assessments of Impacts and Adaptations to Climate Change, AIACC; UNFCCC Guidelines for National Adaptation Programmes of Action, NAPA) at an institutional level with a systemic approach. The second category includes all the tools needed to produce climatic data at an appropriate scale for impact modeling and scenarios development at local to regional level (e.g. the ‘Statistical Downscaling Model’, SDSM; the ‘Country Specific Model for Intertemporal Climate’, COSMIC; the ‘Providing REgional Climates for Impacts Studies’ tool, PRECIS). Downscaling tools are applied in order to develop climate information at high resolution through the processing of global climate models built with General Circulation Models (GCM): these global models cover areas of 150-300 kilometers, so cannot be used to study climate impacts at local levels. Two different downscaling techniques do exist: the dynamic and statistical one (Patz et al, 2005). The former is the most complex and expensive method, and it’s the result of the application of high-resolution and regional climate models: it’s particularly useful in data-poor regions, but it requires high computing power and expertise. Statistical downscaling (often used jointly with atmospheric/weather generators) is a two-step process, which starts from the definition of statistical relationships between GCM-scale variables (assumed constants) and observed smallscale variables; the second step is the application of this relationship to the results of GCM experiments. Compared to the former technique this method is cheaper and simpler to use, but it needs large quantity of data and therefore it can be applied in data-rich areas only. The third and final category is composed by all the information tools through which it’s possible to investigate climate change issues within specific sectors: economy, human health, coastal protection, agriculture, water management, forestry, and so on. The range of systems and tools which belongs to this category is extremely wide, covering (or at least trying to cover) all the information-based issues of such a crosscutting phenomenon. The next paragraphs briefly describe the ICT dimension within climate change linking it to the single agricultural sector, as well as looking at development steps of an adaptation strategy. A focus on ICT for climate change within the agricultural sector In the intersection between climate change and agriculture there are several tools available, because of the high number of crops and because of the complexity of replicating the same conditions across different regions. Every tool allows analyzing different processes of the agricultural sector, from local crop modeling under climate change conditions to the management of economic impacts of climate change on the agriculture sector (soil value variations, demand and supply, production, etc.), and so on. As many tools exist, it’s interesting to focus on their common aspects rather than their specific peculiarities. Some of the tools allow simulating the growth of specific crops, verifying their variations under different climate change scenarios. Usually these tools are sitespecific, but they can be applied at national and/or regional level through a link to an appropriate Geographic Information System (GIS). The first step of the applications happen with the definition of boundary conditions (which include data on crop calendar, soil status, etc.) and input climate parameters and data (such as: temperature, precipitations, wind speed, global radiation, soil moisture, air humidity, water flows...); some of the tools include also data related to crop management conditions. The second step is the development of the growth simulation in a specific state of potential crop production (e.g. with a certain fixed amount of water resources and nitrogen production) for different management options and for a chosen climate change scenario, through the link to an appropriate GCM or an ad hoc expert system. The general output of this kind of software is the assessment of crop production under given scenarios, facilitating decision making at farm level up to a whole crop system. Examples of these tools are: • WOFOST, developed by the Centre for World Food Studies, CFWS, in cooperation with the Dutch University of Wageningen: it can be applied on several different crops, such as barley, field bean, maize, potato, rice, soybean, sunflower, wheat, etc. • GOSSYM/COMAX, developed by the Universities of Clemson and Mississipi and the Agriculture Department of United States: it is the merge of the GOSSYM model, used to simulate cotton growth, with COMAX (CrOp Management eXpert, an expert system), GCMs and weather generators to study the effects of climate change on cotton production. • APSIM (Agricultural Production Systems SIMulator), developed by a consortium of universities and departments of the Australian state of Queensland named Agricultural Production Systems Research Unit (APSRU): it can be applied on more than twenty crops and plants, such as alfalfa, barley, chickpea, cotton, eucalyptus, lupin, maize, peanuts, sugarcane, sunflower, tomato, wheat, etc. Another class of information tools is applied at a higher scale, up to the regional level, with the aim of supporting decision-making in the agricultural sector from a broader perspective. These systems can focus on a variety of factors that can influence climate change and related responses, which can be either exogenous (e.g. government policies, economy, etc.) or endogenous (e.g. location, scale, etc.) in relation to a specific farming system. As a result, these systems facilitate the planning of adaptation responses into a set of actions at farm and regional level, starting from comprehensive assessment of the impacts of climate change and different farming techniques on crop productivity and agro-ecological systems sustainability, up to support the adoption of appropriate agronomy techniques or setting up an agro-technology transfer system. An example of these systems are: DSSAT (Decision Support System for Agrotechnology Transfer), developed by the International Consortium for Agricultural Systems Applications (ICASA);CENTURY, developed by the Natural Resource Ecology Laboratory of Colorado University (NREL); and MAACV (Model of Agricultural Adaptation to Climatic Variation), developed by the Canadian Universities of Guelph and Carleton. ICT for climate change adaptation: the application process In relation to the application of ICT for climate change adaptation, different strategies are being developed according to local conditions and following the main steps of every adaptation process: Observation. This phase is crucial to understand how climate variations are occurring in a specific (regional/national/local) area. Observation can be carried out through data collection tools, such as remote sensing techniques and sensor-based networks. Data can then be stored in digital repositories and shared among the institutions committed to develop an appropriate adaptation strategy. Analysis and planning. Data is analyzed by scientists and policy makers in a cooperative environment, in order to plan and design sound adaptation strategies. ICT supports the analysis of climate change scenarios through software-based modeling systems, like the ones described in the above paragraph: these tools (e.g. software-based models, Decision Support Systems –DSSand GIS) facilitate the development of adaptation plans capable to carry out what-if analysis for different sectors on a multi-stakeholder basis. Implementation and management. The nature of adaptation interventions varies depending on a wide range of elements, such as the set of stakeholders, the sector and the scale of application. As a result, ICT support the implementation and management of adaptation strategies with a wide variety of tools: among the others, forecasting tools, early warning system and resource management systems play a prominent role in this phase. Capacity building. In this phase ICT can be employed for awareness raising and advocacy (particularly through the use of the Internet), as well as for providing adhoc on and off-line training for facing climate change challenges. Networking. ICTs play a key role in producing, storing, retrieving and comparing information related to climate change issues. This allows both North-South and South-South knowledge sharing and the development of partnerships aimed at facing climate change challenges in different areas of the world. Monitoring and evaluation. The final stage of every adaptation process is its monitoring and assessment: the performance of the initiative must be constantly verified in order to reach the goal defined during the planning phase. ICT tools provide an effective way to analyse, store and communicate the impact of an adaptation strategy: GIS are likely to be at the forefront of supporting monitoring and evaluation of adaptation strategies, due to their layer-based nature which allows including large geo-referenced information and the related