Integrating Environmental and Socio-Economic Indicators of a Linked Catchment–Coastal System Using Variable Environmental Intensity

Can we develop land use policy that balances the conflicting views of stakeholders in a catchment while moving toward long term sustainability? Adaptive management provides a strategy for this whereby measures of catchment performance are compared against performance goals in order to progressively improve policy. However, the feedback loop of adaptive management is often slow and irreversible impacts may result before policy has been adapted. In contrast, integrated modelling of future land use policy provides rapid feedback and potentially improves the chance of avoiding unwanted collapse events. Replacing measures of catchment performance with modelled catchment performance has usually required the dynamic linking of many models, both biophysical and socio-economic—and this requires much effort in software development. As an alternative, we propose the use of variable environmental intensity (defined as the ratio of environmental impact over economic output) in a loose coupling of models to provide a sufficient level of integration while avoiding significant effort required for software development. This model construct was applied to the Motueka Catchment of New Zealand where several biophysical (riverine water quantity, sediment, E. coli faecal bacteria, trout numbers, nitrogen transport, marine productivity) models, a socio-economic (gross output, gross margin, job numbers) model, and an agent-based model were linked. An extreme set of land use scenarios (historic, present, and intensive) were applied to this modelling framework. Results suggest that the catchment is presently in a near optimal land use configuration that is unlikely to benefit from further intensification. This would quickly put stress on water quantity (at low flow) and water quality (E. coli). To date, this model evaluation is based on a theoretical test that explores the logical implications of intensification at an unlikely extreme in order to assess the implications of likely growth trajectories from present use. While this has largely been a desktop exercise, it would also be possible to use this framework to model and explore the biophysical and economic impacts of individual or collective catchment visions. We are currently investigating the use of the model in this type of application.     

Data Requirements for Developing Adaptations to Climate Variability and Change

An extensive foundation of high quality data and information on the climate and on the biological, environmental and social systems affected by climate is required in order to understand the climate impact processes involved, to develop new adaptation practices, and to subsequently implement these practices. Experience of the impacts of current and past variability of climate and sea level is a prime source of information. Many practices are in use to reduce climate impacts, for example in engineering design, agricultural risk management and climate prediction services, though their roles as adaptations to climate change are not widely appreciated. While there are good data sets on some factors and in some regions, in many cases the databases are inadequate and there are few data sets on adaptation-specific quantities such as vulnerability, resilience and adaptation effectiveness. Current international action under the United Nations Framework Convention on Climate Change (UNFCCC) pays little attention to adaptation and its information requirements. Furthermore there are trends toward reduced data gathering and to restrictions on access to data sets, especially arising from cost and commercialisation pressures. To effectively respond to the changes in climate that are now inevitable, governments will need to more clearly identify adaptation as a central feature of climate change policy and make a renewed shared commitment to collecting and freely exchanging the necessary data.