Fig 1.
Location of the case study Indigenous socioecological systems and the main characteristics of their associated traditional food systems.
The Karen people constitute the largest Indigenous cultural minority of Thailand, while the Sakha people encompasses 18 different cultural groups living in the Republic of Sakha in the Russian Far East. All photographs taken by the author team. World and individual country maps reprinted from the geoBoundaries data set v. 4.0. [27] under a CC BY license, with permission from geoBoundaries, original copyright 2020.
Fig 2.
Flowchart showing the different work packages (WP), their main goals, and relationships within the overall framework of the project.
Fig 3.
Schematic of the process followed to project future impacts on Indigenous traditional food systems derived from changes in the composition and distribution of wild food species.
(a) Species occurrence data collected from a variety of sources (see main text for details), and ecologically-relevant environmental data will be used to develop statistical correlative models (species distribution models) for the prediction of probability of occurrence and range distribution (presence/absence) for the different traditional food species. Models will then be used with different scenarios of climate forcing (RCP) and socioeconomic development (SSP) to provide alternative narratives of future changes in the composition of traditional food systems in terms of their availability (diversity and composition), stability and accessibility to the Indigenous communities.
Table 1.
The semi-quantitative weight scheme that will be adopted for the computation of the ES index by reference to the individual categories of the food species occurring in each grid cell.
Categories refer to the relative contribution of each food species towards Indigenous livelihoods in terms of socioeconomic well-being and nutritional security and their number and criterion will be defined based on expert judgement and the results from the WPs 1 and 2 (see main text).
Fig 4.
Project data management structure.
Data management in RISE will follow a hierarchical structure where each national team is responsible for the documentation, storage and maintenance of all the data generated by them. A designated data manager will act as curator and contact liaison for his/her team data having the main responsibilities of keeping the centralized register up to date and dealing with both internal and external data requests. Internal requests by project team members will be made using a designated request form to keep records of who is using the data and for what purpose. Disclosable data generated by RISE can be consulted through the centralized register available from our project web site and will be made accessible to the public upon registration.