Research and Development

Given the range of impacts of climate variability and projected climate change on agriculture and forestry in different regions of the world (see the section on impacts above), it is imperative that development and adoption of suitable adaptation strategies to cope with these impacts in different regions should be backed up by appropriate basic research. As Perarnaud et al. (2004) described, it is indispensable to single out two types of adaptation depending on the final user: those which can be implemented by the farmer himself (modification of sowing dates, varietal choice, use of seasonal forecasts, etc.) and those of decision makers, land and natural resource managers which necessitate investment in development and construction of infrastructures.

Needs and perspectives for agrometeorology in the 21st centuy were obtained from a previous WMO (CAgM workshop, where research priorities were identified as support systems to agrometeorological services (Stigter et al., 2000). PeArarnaud et al. (2005) identified the following as the priority areas for research, most of which takes place in industrialized countries, and its use in order to cope with climate variability and future climate change.


To study the impacts of climate change on agriculture and forestry and improve our understanding of certain mechanisms, it is important to gather regular information on the ecosystems (inventories of land use per species, phenological observations, production statistics, etc.), and their evolution over the past few decades on a large scale. It is also important to analyze the extended series of climatic data on national territories over a period which extends from the end of the nineteenth century to the present day. These data should also be complemented by phenological series coming either from observations of the natural vegetation or forest species, or from the cultivated species, in particular the perennial species (fruit trees, vines, etc.).


Even though the predictions on global temperature are generally consensual, disparities exist in the behavior of the hydrological cycle in the regional responses to the increase in atmospheric greenhouse gas content. Questions also remain on the response of our natural environment to global warming, e.g., land use changes (particularly the natural or cultivated vegetation), the storage of carbon (particularly in the ocean and in the continental biosphere) or the possible modifications in oceanic circulation. Research on the regionalization of climatic changes must be carried out, with focus on improving the techniques themselves, but also the evaluation of the impact of climate change on agriculture and the environment. In relation to the forecasts currently available, there is a need to enlarge the range of variables considered, e.g., global solar radiation, as well as air humidity and wind speed, variables which affect agricultural and forestry production. Also, it would be necessary to obtain information not only on the average values, but also on the extremes (for example, for rainfall or wind speed) and exceeded threshold values (the case of frost).


Climatic change carries several kinds of impacts on agriculture, e.g., on production (in terms of quantity and also quality), on the environment, on the species and land use changes, etc. The integration of these various components represents the main challenge to the research to be done and coordinated in the near future. Predictions must increasingly rely on crop simulation models that could effectively combine the effects of CO2 and other climate variables on the physiological processes. Retrospective evaluation of the models with series of observed data, together with their sensitivity and uncertainty analyses are essential steps to build up confidence in model predictions. Taking account of the indirect effects linked to diseases, insects, as well as weeds, however, still remains a challenge.

It is essential to apply the simulation models to a spatial unit defined according to use (simulation unit) and then aggregate the results (yield, quantity of water consumed by the crop, etc.) on the desired regional scale. One of the greatest difficulties lies in taking account of the spatial heterogeneity of the soil, which is not always available in digital form and, might suffer from a lack of precision in terms of georeferencing. The use of crop simulation models, which are not perfect, fed with spatialized information from diverse origins with varying degrees of uncertainty, leads to the propagation of errors which may distort the final results. It is therefore appropriate to carry out theoretical research to quantify such errors and try to minimize them.


In natural ecosystems, and also in cultivated or forest ecosystems, climate change is capable of disturbing the balance between the species, whether they are plant and/or animal, both in terms of the individual and the population. These changes will also modify the development of weeds, diseases and parasites among the crops, as well as their area of distribution. In order to forecast these changes, epidemiological models should be coupled to crop simulation models. However, development of such models necessitates the acquisition of field data and practical knowledge on the development of diseases in the field. At the present time, few such models are available and it is essential that progress is made in this direction.


By exceeding the local species tolerance limits or altering the balance between these species, climate change is capable of having a major direct or indirect impact (fire, anthropogenic pressures) on the biodiversity of natural as well as cultivated ecosystems. Conversely, it is possible that biodiversity constitutes a stability factor in the face of climate change. Understanding the dynamics between species therefore necessitates new functional ecophysiological and behavioral studies (for animals) but also the development of specific models which enable their simulation.


Future changes in the climate and the composition of the atmosphere as reflected by the evolution of thermal and rainfall regimes, the vegetation, and land use, will have an effect on the soil and its dynamics. Research needs to provide answers to questions on the role of soil as a sink as well as a source of CO2 changes in soil usage, etc. Modelling will be able to provide information on the consequences of changing agrosystems and ecosystems management practices simultaneously.


Climate change is projected to affect forests in different ecosystems around the world and in terms of research, it is important to

• quantify the stocks and fluxes of carbon in the large forest ecosystems,

• simulate the future of the sequestration of carbon in these major forest types based on a climatic scenario with high spatial resolution,

• inventory the various forestry practices which have a significant impact on the stocks and fluxes of carbon and estimate the impact of various forestry options on the sequestration of carbon in these ecosystems and their harvested products, and

• assess the vulnerability of woodland species to allow alternative proposals to be made: replacement of species, fire prevention methods, etc.


Agriculture in the 21st century will have to make its contribution to the reduction of GHG emissions (principally CO2, CH4, N2O) but also and above all to adapt to climate change to continue to satisfy the vital needs of populations for food, energy, fibres, etc. There are a number of promising technologies such as minimum tillage techniques combined with the use of mulches and ground cover plants, improved agroforestry systems etc., which could increase soil carbon storage while sustaining productivity, but it is often difficult to persuade farmers to adopt these often promising solutions for various economic or social reasons. It is therefore important to use integrated approaches, which take into account the farmers' decision-making process, to design operational systems. The development of innovative systems in response to many criteria necessitates combination of experimentation on the ground and complex models with varied but coupled processes.

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