We are a multidisciplinary team from two research institutions (Mahidol University and the Local Development Institute), as well as local Karen collaborators who have lived in the study area since birth. The team from the Institute of Nutrition - Mahidol University leads the nutritional and food analyses part of the project for the two case studies in Thailand and Russia (Work Package 2). Another group of members is conducting a qualitative approach using focus group discussions and questionnaires to understand the perception of the Karen community about the contemporary effects of climate change on local socioecological systems focusing on the integrity of natural food species and adaptation responses as part of WP1. Finally, some members of the Thai team, in coordination with the local collaborators, assist the Japanese team with the collection of local food species occurrence data for informing the statistical models for prediction of species distributions (WP3).   

The Thungyai Naresuan Wildlife Sanctuary (Kanchanaburi, Thailand) supports our work with the study of community food sources, and the Thai Plant Varieties Protection Department of Agriculture is helping with the classification of local plant species.

The Russian team consists of two main research organizations of the Sakha Republic (Yakutia) - the North-Eastern Federal University and the Institute for Biological Problems of Cryolithozone (IBPC). Our multidisciplinary research group comprises of early career and senior researchers with ample experience and publication record in areas directly relevant to this project including Arctic environmental and social studies, regional economy, and medicine. The team leader, Dr Tuyara Gavrilyeva has worked actively with the indigenous communities Yakutia that are object of study in RISE.

The Russian team is leading the socioeconomic analysis of the Sakha case study (WP1),  the collection of samples for the nutritional analysis of the Sakha case study (WP2), and the collection of relevant ancillary  data on the ecology of traditional food species (WP3).

Photo by LirikaYumi, CC BY-SA 3.0

The Japanese team comprises researchers from two participating institutions (Hokkaido University and The University of Tokyo) with expertise in climate change ecology and economics.

Under the direction of Dr. García Molinos (lead principal investigator of the RISE project), the Japanese team is responsible for the socioeconomic analysis of the Karen case study (Work Package 1), the development of models to assess future changes in the composition and availability of traditional foods (WP3), and, with the participation of all teams, the final integration of all field and analytical data into the final risk assessment framework (WP4). Our project manager, Ms. Yuka Shimbo,  coordinates the overall management and outreach strategy for the entire project (WP5).

Photo by 663highland, CC BY-SA 3.0

In order to study and develop the way to deal with climate change problems in a sustainable way, we regard community engagement and participation as essential for this project. For this reason, we organized different workshops during the first year of the project for the two Karen communities where the project was introduced to them and we invited the participation of those interested in the project. Local collaborators were also trained by our project members on different field sampling techniques such as household surveys and the collection of occurrence data for food species from the field.

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Our local collaborators consist of multi-role groups of people including assistant village headmen, working-age people who find and prepare food for households, and younger generations interested in how climate change affects food security of their community. Other than providing  invaluable advice and consultation to the project, they also participate actively in the field work for WPs 1 and 3.

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In the picture below some of our collaborators learnt how to use a GPS for collecting occurrence records of natural food species from the field. These records will be later used for the statistical models for predicting current and future distributions of food species (WP3).