The workshops address and discuss issues of approaches, methodologies and challenges related to interdisciplinary research collaboration - specifically related to four pertinent research themes related to human dimensions of global change. These themes are briefly summarised below. Two themes will be dealt with in workshop 1, two others in workshop 2.
1. Interactions between the human and biophysical subsystems
The study of interactions between changes in agricultural land use and practices, associated changes in land cover (e.g. de- and afforestation) and changes in climate is obviously a key to understanding the changes in food security and human living conditions in general during the 21st century.
The rate of change of the atmospheric composition is unprecedented, and the challenges to the human ability to mitigate and adapt are great. It is well-established that approximately 1/3 of the net CO2 –input into the atmosphere over the last 200 years derives from changes in land use/cover, not the least conversion of forests into farmland. While reversed in Europe and North America, this trend continues in the tropics.
Conversely, current and projected climate change will have great effects on agricultural land use and the natural vegetation. The net effects on global and regional are not known with certainty, yet model projections envisage substantial changes e.g. in the global distribution of ‘biomes’, ‘plant functional types’ and individual species.
Changes in land use/cover and agricultural practices: its effects on climate, as well as inverse effects of climate change on food production, quality and security.
Effects of climate on water resource availability in river basins with competing water uses.
The implication of agricultural intensification and technology change on greenhouse gas emissions, and the potential for making agriculture sustainable.
Quantification of ecosystem services, e.g. food and fibre production, water and air quality, biodiversity, greenhouse gas emissions.
2. Economic, social and ethical perspectives of changes in ecosystem services and the role of institutions and economic incentives.
Climate change, and the measures taken at all levels to mitigate them, involves strong elements of both intra- and inter-generational justice. While the emissions causing climatic change are concentrated in one part of the world, and mainly associated with one century of massive use of fossile fuels (and two-three centuries of deforestation), the effects are felt most strongly by people in other parts of the world and in the next couple of centuries.
Global climate change thus needs to be seen in a perspective embracing biophysical, social and economic perspectives. Policies of controlling and adapting to change must be based on proper valuation of all the economic, social and environmental effects. One way of looking at environmental effects from an economic perspective is to consider the value of the ‘ecosystem services’ provided by our terrestrial environment. Current attempts to quantify the value of such services are quite restricted in scope. In addition, standard economic approaches seem unsuited to deal with consequences at the time scale of centuries, which are relevant in the case of climate change. Thus, there is scope for development of novel approaches to ‘valuation’, in a broad sense of the term, integrating biophysical, economic, social and ethical aspects.
Notions of ‘ecosystem services’ and means of assessing their ‘value’.
Ethical frameworks for analysis of the appropriate distribution of the burdens of climate change and mitigation measures.
3. Environmental and agricultural land use history and its implications for the understanding of global (including climate) change and human adaptations to it.
The expanding discipline of environmental history provide new opportunities to cross the conventional boundaries between natural and social sciences, and to harness critical insights of the multiple dimensions of resource degradation in wider systems and landscapes. The development of contextualised histories which explicitly recognize layered scales of analysis in both time and space can highlight the complexity of specific local geographical and historical settings, reinterpret and redefine baseline conditions and identify, for example, the importance of massive disturbance régimes that have altered vegetation-environment relationships across broader geographic regions.
Longitudinal studies at the national, regional or local levels using composite methodologies (for example, remotely-sensed data, archival records, and oral histories) to explore the dynamic interactions between social conditions, the economy and the state of environmental resources
Studies of the changing values, ideologies and interests of decision-makers in economic and political structures to improve understanding of environmental policymaking processes
4. Multiscale data-integration and modelling in land system science
The ability of the research community to understand biophysical aspects of global change processes has been strongly improved by the access to datasets with global or near-global coverage, not the least from Earth Observation satellites. Information on atmospheric processes, land surface properties, vegetation cover and, to some extent, land use may be derived from the ever increasing number of satellites.
Models play a major role in land system science. In one end of the spectrum, ‘global climate models’ allow analysis of the effects of changing concentrations of greenhouse gases in the atmosphere. Models of the bio-geochemical cycles link greenhouse gas emissions to changes in land use/cover and agricultural practices, including the use of agricultural inputs. On the human side, use of spatial models of land use/cover change is made to predict the likely effects of population growth and changes in agricultural technology and inputs on land use/cover, and thereby on carbon stocks in vegetation and soils. While developed within each their discipline, these model obviously need to be interlinked.
Methods and models allowing for integrated analysis of human-biophysical causal relationships, combining data with different spatial scales and from widely different sources.
Uncertainties associated with interpretation of spatial datasets and the implication for linkages with models. Uncertainties in models and their parameterisation in particular for projections into the future.