Human adaptation to biodiversity change: Building and testing concepts, methods, and tools for understanding and supporting autonomous adaptation

Biodiversity change directly threatens the livelihoods, food security, and cultural and ecological integrity of rural subsistence-oriented households across the developing world. People will be forced to respond in ways that either mitigate or exacerbate the loss of biodiversity and ecosystem services.

An unprecedented extinction of species is underway, and climate change is affecting species' range and phenology (the timing of their life cycle events), leading to new species configurations that affect ecosystem services in unpredictable ways. With growth in human population and consumption driving climate change and continued habitat alteration, 'novel' ecosystems will become even more prevalent.

There is a dearth of scientific research on the subject of human adaptation to biodiversity change, so scientists and policy-makers lack mandates, conceptual frameworks, knowledge, and tools to project or predict human responses and their actual or potential outcomes, synergies, and feedbacks.

Indeed, "A significant new research effort is required to encourage decision makers to consider biodiversity, climate change and human livelihoods together" (Royal Society 2007). At the same time, there is a call for a 'paradigm shift' in adaptation thinking away from top-down planning and toward supporting local adaptation. Local adaptation efforts go unnoticed, uncoordinated, and unaided by outsiders and, unless policy-makers become aware of the importance and extent of autonomous adaptation processes and understand what influences their outcomes, adaptation and mitigation policies may be ineffective or counter-productive.

This project aimed to kick start the development of appropriate conceptual frameworks, methods and integrated models for understanding human adaptation to changes in biodiversity and related ecosystem services that can eventually be used to predict outcomes for biodiversity, ecosystem services and human wellbeing in highly biodiversity-dependent societies, and provide evidence for the utility of these outputs to a new network of researchers and policy-makers.

The building blocks for development of concepts, methods, tools and models were: 1. local information or knowledge systems and monitoring capacity; 2. local valuation of biodiversity and related ecosystem services; 3. integrating biological resources and ecosystem services into an understanding of livelihood processes; 4. assessing perceptions, risks, needs, and ability to respond; 5. understanding biological and welfare outcomes and feedbacks.

The project joined partners from anthropology, economics and ecology/biology at Oxford, Kent and The University of London's School of Oriental and African Studies, with partners from South Africa and India. Partners jointly elaborated the conceptual framework in a first intensive workshop using a scenario building protocol. Then, teams incrementally developed and evaluated research protocols and methods and collected primary data in a field research site in the Western Ghats, and modelled initial results.

A second workshop revised the scenarios and prepared a second field data collection phase. This iteration permitted further grounding of the conceptual framework and methods, and development and testing of a stronger, less aggregative model based on much better decisions about how different variables interact. After the second field research phase, the team revised the scenarios and integrated analysis and modelling of the data. They identified variables, variable sets, or system state indicators that are useful for monitoring biodiversity, ecosystem services and human wellbeing with biodiversity/ecosystem change.

Lead Principal Investigator
Organisation: University of Kent
Country: United Kingdom
Principal Investigator
Organisation: School of Oriental & African Studies
Country: United Kingdom
Principal Investigator
Organisation: University of Oxford
Country: United Kingdom
Co Investigator
Organisation: Open University
Country: United Kingdom
Co Investigator
Organisation: University of Kent
Country: United Kingdom
Co Investigator
Organisation: University of Kent
Country: United Kingdom
Co Investigator
Organisation: University of Oxford
Country: United Kingdom