IND_CHANGE - Ferramentas de modelação baseadas em indicadores para prever alterações na paisagem e promover a aplicação da
Many rural landscapes are changing rapidly, with uncertain outcomes for biodiversity, landscape function and the corresponding
landscape services. Therefore, monitoring and adaptively managing the drivers and consequences of landscape change while
sustaining the production of essential resources have become research and policy priorities. Landscape change can have profound
impacts on conditions, resources, values, hazards and services. Due to its synthetic, integrative nature, land use pattern and change
analysis is at the core of ecological and environmental research. Ecological assessment and monitoring are nowadays important
tools for the management and reporting on the condition of natural resources. The need for international standards has fostered the
selection of essential indicators, from biodiversity and agriculture to water resources and rural development. Models of land use
dynamics can support forecasts of ecological change under realistic social-ecological scenarios. Moreover, the integration of data
and predictions for multiple indicators under common spatially-explicit computational environments can foster adaptive land
management through web-based spatial decision-support systems, promoting communication and sharing in multi-user
An integrative view of the effects of pressures on multiple indicators across scales would support more consistent decisions by
administration agencies and private stakeholders. The IND_CHANGE project is aimed to provide such an integrative view, by
applying multiple modelling tools under a common theoretical and computational framework and from a spatially and temporally
explicit approach. The focus will be on improving the existing capacity to accurately forecast responses of standard ecological
indicators to landscape change under alternative management scenarios. This collaborative project involving scientists and
stakeholders will address three sequential questions: (1) How fit are pre-existing data to inform on relevant indicators of socialecological
change, and which are the key data gaps? (2) Which modelling frameworks are more suitable to predict and forecast
estimates of such indicators under current and future conditions? And (3) Can integrative and collaborative computational tools
improve and disseminate the application of model-based social-ecological research in adaptive land planning and management?
The project will be organized around eight tasks. Tasks 1 and 2 will provide the supporting data and sampling strategy for field
surveys to be performed in the test areas (task 3). Modelling tasks (4-6) will develop complementary modelling frameworks for
biodiversity, landscape functions and services. Finally, two integrative tasks (7-8) will combine the several modelling frameworks
within a common predictive and decision-supporting computational tool. The framework will be tested in the catchments of two
medium-sized rivers (Sabor and Vez) in the North of Portugal, representing a major climatic and ecological contrast in the region.
These areas have a background of previous research and a history of collaboration between scientific partners and local authorities.
IND_CHANGE will be conducted by experienced researchers in the study of biodiversity, landscape ecology, and environmental and
social-ecological change. A consortium of five national research institutions led by CIBIO/ICETA (InBio Associate Lab) will be advised
by three top international experts on social-ecological system analysis, spatial planning and natural resource management, and
international reporting. Excellence training and mobility opportunities will thus be awarded to six young researchers who will be
hired to support specific tasks. Two administration stakeholders will provide the context and requirements for developing and
testing the new tools while ensuring post-project system sustainability. A stakeholder advisory commission with representatives
from relevant regional administration and private stakeholders will also be organized.
IND_CHANGE is expected to contribute to improve the application of research to support strategic options for sustainable
development, strategic land planning and management with involvement of public and private stakeholders. The main final output
will be a web-based spatial decision support system allowing the combined querying, visualization and analysis of spatially-explicit
forecasts of ecological change for multiple indicators under complex social-ecological scenarios. This tool is due to be applicable in
territorial management by national, regional and local administration, as well as by public and private companies dealing with
natural resource management, strategic and project impact assessment, land use planning and other environmentally-oriented
services. Several workshops and training courses will be organized to enhance the applicability of the new proposed framework.