Local ecological knowledge and incremental adaptation to changing flood patterns in the Amazon delta

Local ecological knowledge and incremental adaptation to changing flood patterns in the Amazon delta

The need for understanding the factors that trigger human responses to climate change has opened inquiries on the role of indigenous and local ecological knowledge (ILK) in facilitating or constraining social adaptation processes. Answers to the question of how ILK is helping or limiting smallholders to cope with increasing disturbances to the local hydro-climatic regime remain very limited in adaptation and mitigation studies and interventions. Herein, we discuss a case study on ILK as a resource used by expert farmer-fishers (locally known as Caboclos) to cope with the increasing threats on their livelihoods and environments generated by changing flood patterns in the Amazon delta region. While expert farmer-fishers are increasingly exposed to shocks and stresses, their ILK plays a key role in mitigating impacts and in strengthening their adaptive responses that are leading to a process of incremental adaptation (PIA). We argue that ILK is the most valuable resource used by expert farmer-fishers to adapt the spatial configuration and composition of their land-/resource-use systems (agrodiversity) and their produced and managed resources (agrobiodiversity) at landscape, community and household levels. We based our findings on ILK on data recorded for over the last 30 years using detailed ethnographic methodologies and multitemporal landscape mapping. We found that the ILK of expert farmer-fishers and their “tradition of change” have facilitated the PIA to intensify a particular production system to optimize production across a broad range of flood conditions and at the same time to manage or conserve forests to produce resources and services.

Authors: Vogt, N.D.; Pinedo-Vasquez, M.; Brondizio, E.S.; Rabelo, F.G.; Fernandes, K.; Almeida, O.T.; Riveiro, S.; Deadman, P.J.; Yue, Dou

Topic: indigenous knowledge, resilience, adaptation, sustainability, landscape model

Geographic: Amazon

Publication Year: 2016

ISSN: 1862-4065

Source: Sustainability Science 11(4): 611-623

DOI: 10.1007/s11625-015-0352-2

Altmetric score:


Export Citation

Related viewing

Top