We are combining a number of approaches to gathering and analysing data in order to develop assist in the planning and implementation of forest landscape restoration. Our main methods currently include:
Field surveys of existing giant panda habitat and examination of historical records will help us to understand the species composition of undisturbed panda habitat. We will also explore the development of efficient tools for distinguishing among bamboo species (e.g. high-throughput molecular diagnostic assays).
Habitat suitability and connectivity models
Habitat suitability models for giant pandas and other key species using under contemporary and future predicted climates will help to establish the risk to species and habitats from environmental change and fragmentation. This analysis will highlight key environmental drivers and provides a tool for assessing the potential efficacy of different restoration approaches, such as habitat corridors, in different locations.
Our long term aim is to develop with forest managers a suite of GIS-supported tools that can be integrated into the forest planning process to assess the impacts of alternative management interventions and to support Forest Landscape Restoration. Managers will be able to use these tools to select appropriate woodland species that are suited to sites now and under changing environmental conditions. This will allow a landscape-scale approach to habitat management, with habitat patches of different sizes and carrying capacities arranged to maximise their connectedness and use by giant panda and other species.
These spatially explicit, evidence-based decision making tools will help to target resources and prioritise actions on the ground in an effort to improve habitats to support the long-term viability of priority and protected species such as the giant panda. They will provide the basis for an objective and transparent decision-making process.
Agent based models
A range of models will be tailored to the local context through the use of biophysical and social data. Habitat modelling will be complemented by 'agent-based' modelling of land use change, to explore the potential impacts of land management decisions and policy interventions. This will allow us to consider a range of future scenarios of climatic, environmental and social conditions, and so design suitable restoration strategies.
Our social research will also examine the conflicts and synergies between human livelihoods and panda habitat restoration, in order to support practical management and policymaking for the restoration of forest habitats, the protection of human livelihoods and the recovery of giant panda populations. Engagement with communities facilitates local involvement in shaping the future management of the forests. To balance the requirements of giant pandas (and other biodiversity) and human populations, the different trade-offs and impacts on pandas, people and forests need to be considered.
Social research to understand key human-wildlife interactions can facilitate the development or continued improvement of collaborative management approaches with local communities that support both panda conservation and livelihood development. Key research issues involve: (i) major sources of livelihoods (building on existing datasets), (ii) community resources (e.g. leadership, social networks) (iii) how people use (or want to use) the forests and how this might change in the future, (iv) experiences of wildlife/pandas (v) impacts of earthquakes and timeline of changes to livelihoods, (vi) Perceptions and experiences conservation goals, (vii) attitudes towards, and experiences of, government bodies and other institutions (vii) potential opportunities for co-management.