A landscape vulnerability framework for identifying integrated conservation and adaptation pathways to climate change: the case of Madagascar’s spiny forest

Context

Integrated conservation decision-making frameworks that help to design or adjust practices that are cognisant of environmental change and adaptation are urgently needed.

Objective

We demonstrate how a landscape vulnerability framework combining sensitivity, adaptive capacity, and exposure to climate change framed along two main axes of concern can help to identify potential strategies for conservation and adaptation decision-making, using a landscape in Madagascar’s spiny forest as a case-study.

Methods

To apply such a vulnerability landscape assessment, we inferred the sensitivity of habitats using temporal and spatial botanical data-sets, including the use of fossil pollen data and vegetation surveys. For understanding adaptive capacity, we analysed existing spatial maps (reflecting anthropogenic stressors) showing the degree of habitat connectivity, matrix quality and protected area coverage for the different habitats in the landscape. Lastly, for understanding exposures, we used climate change predictions in Madagascar, together with a digital elevation model.

Results

The fossil pollen data showed how sensitive arid-adapted species were to past climate changes, especially the conditions between 1000 and 500 cal yr BP. The spatial analysis then helped locate habitats on the two-dimensional axes of concern integrating sensitivity, adaptive capacity and climate change exposure. By identifying resistant, resilient, susceptible, and sensitive habitats to climate change in the landscape under study, we identify very different approaches to integrate conservation and adaptation strategies in contrasting habitats.

Conclusion

This framework, illustrated through a case study, provides easy guidance for identifying potential integrated conservation and adaptation strategies, taking into account aspects of climate vulnerability and conservation capacity.