Socioeconomic analysis (WP1)

The purpose of this package is to characterise household conditions in our study communities through the collection of economic data and traditional food use. To this end, as described below, we will conduct systematic household surveys for which we will develop and utilise questionnaires similar to those of national surveys in the target countries. Depending on the conditions of the localities, such as population and literacy, the survey may target all village households or a representative sample of village households. These quantitative surveys were supplemented by qualitative focus group discussions, in-depth interviews, and other ancillary sources of information (see below).

We will pay special attention to estimating the associated costs and time spent on the gathering and processing of traditional food by household, the use of and seasonal access to traditional food throughout the year, and existing dependencies on marketed goods and wage employment (i.e., the cost of modern life). Adopting the framework of the almost ideal demand system (AIDS) [34], we perform statistical regression analyses to determine the relationship between household economic conditions (expenditure, income, etc.) and other household characteristics and quantitatively estimate the elasticities of food availability conditions on the household economy (i.e., the household production function). Ethical considerations associated with each type of survey will be handled properly, as described below, and managed based on the procedures formulated in the IRB-approved protocols. Socioeconomic work comprises four levels of data collection.

1. Systematic household surveys will be conducted to obtain information about the socioeconomic characteristics of the households, such as their composition, educational and employment status, economic conditions (e.g., income, expenditure, assets), demography, and an inventory of food sources by household, including their type (natural or marketed) and consumption patterns (frequency and quantity). Key participants will be the family head or other members who play major roles in procuring and managing food in the household. The survey is based on official household socioeconomic surveys adapted to the requirements of our project (i.e., focus on traditional food systems) and case studies. We will adopt research ethical standards for qualitative one-to-one interviews [35, 36]. All participants will be adequately informed about the study purpose and content prior to the interview and asked to provide their free, prior, and informed consent (see section ‘Indigenous cultural and intellectual property [ICIP] rights and benefit-sharing’). To respect their right to reconsider their participation, participants will be informed before the start of the interview that they can withdraw their consent at any time during the course of the interview. To reduce the risk of unintended harm to the respondent, all participants will be informed before the interview that they can freely refuse to answer any question they feel uneasy or hesitant to respond to. The fact that local collaborators from the communities, previously trained by our research team, will help conduct the interviews, and that several members of our research team have worked previously in related research with these communities, provides a level of familiarity and trust that should facilitate communication on these sensitive issues, reducing the risk of unanticipated harm. All information and data collected by the survey will be treated and analysed anonymously.
   For the Karen case study, an all-household survey at each village will be conducted, contingent on the participation rate (initial contacts with community leaders suggest that the response rate will be high). Surveys will be repeated once a year for the first two years of the project to cover seasonal effects (winter 2021 for the dry season and spring 2022 for the wet season).
   In the Sakha case study, given the much larger scale of the study region and higher number of communities involved (Fig 1), a two-stage approach is to be followed instead. Eighteen settlements in each of the five geographical zones of Yakutia have been selected for the first stage (Fig 1). During the first year of the project, all communities will be visited once and anonymous surveys will be conducted for a representative number of households. The rural population of Yakutia of working age and older was selected as the pool of population to calculate the sample size because these people are most dependent on traditional food systems and are responsible for food decisions in their households. The total (i.e., across settlements) sample size for the surveys is calculated according to the Slovin formula [37]: (1)
   Where n and N are the sample and total population sizes, respectively, and e is the level of precision (0.05 in this study). For the total registered population of 12,321 people of working age and older across all eighteen settlements (S1 Appendix), the resulting sample size is 387 people, which was finally rounded up to 400 participants. To maintain a balanced distribution of the sample size among settlements, both geographically and demographically, given the vast extension of the study area and size differences of the rural settlements, the total sample size was then divided among the 18 settlements according to the five recognised economic zones of Yakutia (i.e., Arctic and southern, central, eastern, and western Yakutia), and proportional to the population size of working age and older of each rural settlement (see S1 Appendix). Based on the results from the first-year survey, an all-household survey, similar to that conducted for the Karen case study in Thailand, will be conducted in two of the communities selected based on the degree of their dependence on traditional food systems. The two communities, contrasting in terms of their geographic and cultural-social characteristics, and the food and harvesting activities will be selected for this second stage of the research. The research methods and objectives match those of the Karen case study.
2. Focus group discussions (n = 12–18 with six participants each) and in-depth interviews (n = 30) were then used to understand the perceived effects of ongoing climate change on socioecological systems, the integrity of natural food species, and the adaptation capacity of Indigenous communities. The questions will focus on the social and cultural relations and obligations of Indigenous communities, including rituals, beliefs, and cultural traits, as well as patterns of use of natural resources in relation to the status quo of the ecological system and the integrity of natural/traditional food species according to ecosystem types. Questions will also address changes in socioecological systems over the last decade perceived by the community, particularly in relation to climate change, and any adaptation response made by the community to those changes. Similar to the household surveys, data will be collected for the first two years of the project to cover seasonal patterns.
   Although seasonal dynamics are better captured by multi-year longitudinal studies [13], we are limited by the duration of the project and available resources. Nonetheless, we will use the information collected in the interviews and focus-group discussions to detect whether the two years of field sampling are perceived as unusual by the locals and use historical records from nearby weather stations to check if they sit climatologically outside the regional historical baseline.
   Key participants in the interviews and group discussions will be community leaders and local residents who play roles in producing, hunting, gathering, cooking, and consuming natural foods according to each socioecological system. In order to gain a longer-term, historical (life-time) perspective of these changes, their drivers, and implications, a representative number of elders will also be included as the living memory of the community. Discussion sessions will be tape-recorded and will include taking notes and drawing pictures to communicate efficiently with the group participants. Focus group data, including all interviews, observation notes, and images or visual data, will then be transcribed.
   We will apply the triangulation method and follow the analytical framework proposed by Creswell and Creswell [38] for the sequential organisation and preparation of the data, data codification, and generation and representation of the description and themes. Given the distinctive ethical challenges of the focus group methodology relative to those of one-to-one interviews in terms of consent, confidentiality, and anonymity, as well as the risk of harm [39], we will follow specific recommended strategies to address and minimise these issues. First, to ensure their active consent during the consent process, we will read aloud and distribute among the participants an information sheet [40] to help participants create appropriate expectations by providing sufficient, clear information about the purpose of the focus group, examples of the types of questions that will be discussed, as well as clarification of what will be done with the data to be collected, and the steps to be taken to preserve confidentiality and/or anonymity.
   During the preliminary briefing session prior to starting the discussion, the moderator will then discuss and agree with the participants on a set of ground rules emphasising the public nature of a focus group and the need for confidentiality and anonymity, as well as provide guidance on identified subjects that the participants might feel as sensitive (e.g., specific information on the areas for collection of wild food species within the natural reserve). At this point, participants will be given the opportunity to withdraw their decision to participate in the group discussion if they wish to do so before the start of the group discussion. During the discussion, the moderator will strive to ensure that all members of the group have the opportunity to willingly contribute to the discussion, while remaining vigilant for signs of distress, breaches of confidentiality, or over-disclosure by the participants.
   Finally, a debriefing session will be provided after the focus group discussion, where the moderator reminds participants about the need for confidentiality and anonymity and gives an opportunity to address any remaining concerns or issues. To this end, the moderator will remain in the room for a while, as well as making himself or herself available for individual contact.
3. A survey of all food stores in each community will be conducted during the first two years of the project to produce a seasonal inventory of the type, quantity, frequency, and price of marketed food that is accessible to each community. Some local residents do not gather or hunt food species by themselves but still have access to seasonal food species through community food stores and mobile grocery stores (e.g., bicycles and motorcycles). Therefore, identifying the types of food available from these stores and their importance within the study communities is important for our study.

A search for ancillary demographic and socioeconomic data on the case study communities from official reports and archival material produced by regional and national government bodies, as well as published and unpublished research will be conducted during the first year of the project.

Both of the Karen community objects of study in RISE are matriarchal, with egalitarian decision-making based on the principles of mutual care, collaboration, consensus, and cosmological respect [41]. The decision process relies on both official and natural community leaders, who can be male or female, old or young, working or non-working members of the community, and who participate in the formation of community norms. Vulnerable or marginalised members are uncommon in these communities and refer chiefly to women, particularly single mothers, and the young who recently moved into the community, the disabled, and those who cannot provide themselves and their families with food and necessities, such as those with chronic ailments.

In the case of the Sakha case study, specific considerations related to social structure and relationships will be considered after the selection of the two study settlements based on the results of the first-stage survey that covers 18 settlements, including multiple ethnic minority groups across Yakutia. Traditional social structures in these communities include both patrilineal (e.g., Even) and matrilineal (e.g., Yukaghir) clans, although women often command relatively high positions in family and social life, even in patriarchal structures [42]. Overall, the situation of the dominant Turkic-speaking Sakha concentrated around the central and urban areas of the Sakha Republic is in clear contrast with the remote and isolated communities of small minority groups in its northern regions. The remoteness of these communities, with all the accompanying socioeconomic factors such as high unemployment rates, low living standards, and unreliable or non-existent communication, implies a high risk of marginalisation for vulnerable groups [43]. Common marginalised members include people with extremely low incomes and no relatives as well as alcoholics and people without a steady source of income. Immobile disabled, pensioners living alone, and single-parent families also have a higher risk of poverty.

To take the challenges faced by marginalised persons into consideration, we will use snowball sampling techniques to identify a representative number of vulnerable and/or marginalised members of our study communities. Identified members will then be asked to participate, where consent can be obtained, in the in-depth interviews and focus-group interviews. To do so, we will follow the recommended ethical considerations to design more inclusive processes [44] related to (1) ground rules (e.g., assuring and ensuring confidentiality in the interviews, ensuring equal right to speak, and clearly defining how community members’ views and ideas can be communicated in the focus groups), (2) space (e.g., selecting settings that make vulnerable participants feel comfortable), (3) facilitation (e.g., interviews conducted by our local collaborators who are regular members of the community), (4) documentation (e.g., outputs made available to participants in their local language), and (5) synthesis (e.g., ensuring results and research priorities are shared with the marginalised groups to give them a final say as a way to share power and allow their voices to be heard). They will also be invited to join project workshops and community meetings arranged with sufficient space and time for them to share their perspectives, problems, and needs with other community members and local stakeholders to jointly develop responses and solutions for capacity building and adjustment to cope with existing problems, ensuring that they have a representation and voice in our project. In doing so, we will follow a stepped approach [44], where small groups comprising vulnerable members with similar characteristics meet first in a safe space where they can express themselves and share their ideas comfortably before progressing into larger group discussions.

Nutritional analysis (WP2)

This package focuses on understanding the role and importance of traditional foods in Indigenous diet and nutrition. Food composition analysis will be used to profile the nutritional value of representative Indigenous foods, locally available and consumed, relative to commercially available foods. Nutritional assessment will then be used to characterise the nutritional status and food consumption patterns of the IPs in each study community. The importance of traditional food in the diet of IPs will be considered from its seasonally adapted nutrient profile and consumption relative to their nutritional status [45].

Samples of raw Indigenous food products for food composition analysis will be collected from each study community following selection criteria based on their representability and availability, as well as their contribution to the dietary pattern of the local people in terms of consumption amount and frequency. Twenty samples of raw food products will be collected during the first two years of the project to capture seasonal effects (10 samples each during the 2021 dry season and the 2022 wet season), and 20–40 samples during the second year only for the Sakha case study during summer and winter (seasonality). The list of nutrient-dense foods to be sampled for analysis will be decided upon through discussions with representative household members who play a prominent role in gathering or cooking. The food list will include protein-rich foods (e.g., legumes) and foods important for their vitamin and mineral content (e.g., vegetables and fruits).

Food samples will be collected, prepared, and stored at -20°C for transportation to the analytical laboratory following standard procedures. Proximate composition analysis of foods, including moisture, protein, fat, dietary fibre, ash, and carbohydrate (by difference), will be determined according to the standard analytical procedures detailed by the Association of Official Analytical Chemists [46]. The food energy content per 100 g of the analysed foods will be estimated by the sum of the carbohydrate, fat, and protein percentages after multiplying them by the Atwater factors (4, 9, and 4, respectively).

Nutritional assessment of the IP from each settlement, covering school-age children, adults, and the elderly, will then be performed through on-site anthropometric (first year of the project only), biochemical (first year), and dietary (first and second year) assessments. All medical analyses will be conducted by practitioners following established medical protocols to guarantee the welfare and security of participants.

Anthropometric assessments will collect data on body height and weight using a portable stadiometer and a bioelectrical impedance scale. Adult Body Mass Index BMI (kg/m²) will be calculated from participants’ measured weight and height, whereas BMI for age will be considered for children aged 5–19 years according to their nutritional status.

Biochemical assessment of venous blood samples taken from each participant after a 12-h overnight fast will be immediately transferred to the hospital laboratory for biochemical analysis. Whole blood samples in EDTA vacutainers will be analysed for complete blood counts using an automated analyser following standard procedures. Other blood samples will be centrifuged and analysed for lipid profiles, including total cholesterol, high-density lipoprotein cholesterol, low-density lipoprotein cholesterol, and triglycerides, using an enzymatic colorimetric technique [46].

Dietary assessments will be collected from an adequate sample size determined according to Eq (1) and divided by demographic group (i.e., school-age children, adults, and the elderly) according to their ratios in the study communities. A 24-hour dietary recall interview will be used to determine individual dietary intake, and food frequency questionnaires will be used to determine food consumption pattern [47]. A repeat 24-h dietary recall will be conducted on a random subset (10%) of the participants on nonconsecutive days from each settlement proportional to the size of each demographic group in order to reduce random measurement error. Dietary assessments will be conducted seasonally (dry and wet seasons) to examine differences in the usual diet between the two seasons. Data will be analysed for energy and nutrient intake using the INMUCAL Nutrients v4 program (INMU, Thailand).

Although project duration and resource constraints do not allow us to explicitly detect or measure nutrition transitions, understood as shifts in traditional Indigenous diets, physical activity, and multiple causes of malnutrition [48], the quantitative and qualitative data collected by our socioeconomic surveys (e.g., wild and marketed foods available to and consumed by the community, expenditure and sources of income by household, roles of local wisdom relevant to the food system, effects of media and information technology on food consumption and lifestyle) and nutritional surveys (e.g., food processing, cooking, consumption practices, nutritional profiles and deficits, and nutrition-related health disorders) will be assessed as indirect evidence of this important issue through comparison with existing previous reports. These include existing reports from education and healthcare agencies as well as previous work by some of our research team members. For example, studies conducted by members of our research team more than a decade ago [30, 31] in one of the Karen communities under study reported indications of community development and change affecting food availability, accessibility, and related concerns by the community leader regarding changes in land and environmental sustainability, culture and tradition, food diversity, and food security. The studies also detected underweight and overweight cases among schoolchildren, raising concerns about diseases associated with nutritional transitions.

Projecting future changes in traditional food species (WP3)

During the second year of the project, this package will use correlative statistical models (i.e., species distribution models) to project changes in habitat suitability and the range distribution of traditional food plants and animals, representative of each TFS, under a set of alternative future Shared Socioeconomic Pathways (SSPs) and Representative Concentration Pathways (RCPs) with their associated climate change outcomes [49] (Fig 3). These changes will then be translated into projected alterations in the TFS, supporting the studied Indigenous communities (see below). A group of target food species that are important to the community and are representative of the TFS will be selected together with our local Indigenous collaborators, particularly those actively involved in subsistence practices as well as the storage, handling, and preparation of food, and by reference to the information collected by WPs 1 and 2. The importance of a food species will be defined in terms of its nutritional and household contributions, as well as the existence of any other complementary value provided to the community, such as cultural or recreational values.

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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.

https://doi.org/10.1371/journal.pone.0271792.g003

Estimation of risk (WP4)

Based on the information collected from WPs 1 to 3 and supported by continuous engagement and consultation with representatives of the Indigenous communities and other relevant stakeholders, we will use a narrative-oriented, ‘bottom-up’ approach to risk assessment and guidance for adaptation [68]. This will apply an iterative approach that begins with the semi-quantitative evaluation of the exposure and sensitivity of TFS to projected changes in the composition of food species under alternative emission scenarios. It will then be followed by the qualitative assessment of risks posed by those projected future impacts and the identification of adaptation alternatives.

Classic risk conceptualisation considers risk as the probability of an event relative to the consequences of its occurrence [69]. This relationship can be further decomposed into three elements of risk, namely the hazard, exposure and vulnerability [70]. Whereas hazard represents the probability of occurrence of hazardous events, the combination of exposure and vulnerability (sensitivity and adaptation capacity) refers to the consequences of these hazardous events occurring. Here, we draw on this conceptualisation and adapt it to our study by framing risk as the potential for adverse effects that change the local availability and accessibility of traditional food species generated by future changes in local climatic conditions may have on dependent Indigenous socioecological systems (i.e., the TFS).

Our system is represented by Indigenous communities and the ecosystems with which they interact. The hazard, the impacting force on the asset of interest, comprises future changes in local climate and environmental conditions that translate into changes in the distribution of traditional food species. The asset exposed to the hazard is a traditional food system comprising the pool of food species that are locally available from the environment and are used by the Indigenous community. To capture this dual socioecological dimension of the asset, we develop an index that combines exposure and sensitivity by calculating the level of exposure relative to the degree of human reliance on the asset in terms of its relative contribution to socioeconomic well-being and nutritional security. This approach is conceptually akin to the concept of benefit-relevant indicators [71], which describes how ecosystems provide benefits to society by linking biophysical outcomes to benefits for an identifiable group of people.

Based on an index originally developed for the selection of priority areas in conservation biology [72], our Exposure-Sensitivity (ES) index considers the diversity of locally available food species (i.e., in each grid cell within the study area) and weights the relative importance of each species in that locale by their individual contribution towards Indigenous livelihoods in terms of socioeconomic well-being and nutritional security, giving important species more contribution to the index than those that are less relevant (Table 1). (2) where α_i is the weight assigned to the ith contribution category; C_i is the number of food species present in the local assemblage belonging to the ith contribution category; n is the total number of species in the local assemblage; k is the number of contribution categories represented in the assemblage; and α_max is the weight corresponding to the highest contribution category occurring in the species pool for the entire study area (not just in the local assemblage). The index ranges from 0 when all species belong to the lowest contribution category (accessory socioeconomic and nutritional contributions) to 1 when all species belong to the highest category (critical socioeconomic and nutritional contributions). Hence, this index combines traditional food exposure with the sensitivity of Indigenous communities as a metric of the consequences of climatic hazards that impact the traditional food system. The weights for each contribution category are chosen according to a geometric progression scheme, with the relative contribution of both components (socioeconomic and nutritional) weighted equally (Table 1). Assignment of each food species to a contribution category will be made by consensus through discussions between researchers and IPs based on traditional environmental knowledge of the species and the results from socioeconomic (e.g., relative importance of traditional food to household economies) and nutritional (e.g., proportions of reported food consumption and nutritional/dietary contribution) surveys conducted for WPs 1 and 2.

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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).

https://doi.org/10.1371/journal.pone.0271792.t001

The projected impacts of climate change on TFS will then be calculated as the relative change in local ES values projected for future periods relative to their current values. The uncertainty associated with these projected impacts will be assessed by comparing the results under different GCMs and alternative emission scenarios to provide a suite of alternative narratives of the nature and degree of impacts that different possible futures may bring.

These alternative narratives will then be presented to representatives of Indigenous communities and other relevant local stakeholders (e.g., the National Park authority) to guide focus-group discussions and qualitatively assess the potential risks posed by projected future impacts of climate change on TFS. Discussions will focus on identifying decision thresholds (i.e., points where the optimal decision changes as a function of risk) based on current adaptive capacity, assessed from local Indigenous knowledge and consideration of the traits of the Indigenous communities that confer resilience to traditional food insecurity, such as economic stability, educational attainment, or job diversity, and the impact scenarios that cross those thresholds.

Scientific growth, transferability and public outreach (WP5)

The main objective of RISE is to influence policy and contribute to regional development and the long-term sustainability of Indigenous socioecological systems through applied, transferable science. This WP will ensure adequate scientific growth, particularly of our early career team members, meaningful stakeholder engagement, and public outreach throughout the entire lifespan of the project and beyond. The project’s outreach strategy followed a continuous communication strategy. Dissemination of results will be conducted in the form of scientific publications from our case studies and presentations at national and international meetings as well as through the publication of materials such as press-releases, an end-project summary of the main results and conclusions for policy makers. Our project website and social media platforms will be used to disseminate results among, and engage with, the general public. The transferability of results across case studies and elsewhere will be reinforced through the organisation of stakeholder workshops and exploration of international and regional policy implications with a focus on linking our results with the 2030 sustainability agenda and the Paris Agreement on Climate Change. Other relevant forums such as the UN Permanent Forum on Indigenous Issues or the Sustainable Development Working Group of the Arctic Research Council will also be engaged.

An important deliverable of this work package is the generation of a protocol to define the norms for the use and sharing of data, and the creation of a project database to facilitate both the internal use of data among project members and the efficient release of the open data generated by the project. To do so, RISE will follow a hierarchical structure in which each national team is responsible for the generation, curation, and storage of their own data, as well as to keep an updated centralised register of all data used and generated by the project that project members can internally refer to whenever they need to access data produced by other teams and external users can consult (Fig 4). Each data product listed in the register contains metadata describing its original source, type of data, and status (private or public). This register will be available to the public on our project website and periodically updated and expanded as needed throughout the lifespan of the project.

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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.

https://doi.org/10.1371/journal.pone.0271792.g004

The data generated by each of the three participating national teams will be handled at the national level by a designated data manager (Fig 4). The data manager will be responsible for the management and storage of the data generated by his/her own team, as well as the registration of that data into the centralised register, and for dealing with data queries of internal or external users regarding the data produced by his/her own team. In principle, all data generated by the project should be internally available to other team members, which is necessary for their research. Specific conditions for data sharing and attribution among team members will be established through joint research agreements between the participating research and funding institutions. As a general rule, project members who want to use data produced by other teams will need to fill in a request form containing details of the data they request and the intended use of the data. Forms will be submitted to the data manager who will process the request by contacting the member of his/her team primarily responsible for that data set and keeping the record of all the request forms submitted to his/her team.

While some of the data we will compile and generate will be copyright or non-disclosable (e.g., sensitive information), other data (particularly processed data produced by our project) will be disclosable and should be made accessible to the public. By making our centralised register public through our project website (currently under construction), end users will be able to check the data produced by RISE’s disclosure status. Disclosable data generated by the project will be made available upon publication of project results and hosted on a public repository accessible upon registration through our website. Registration will require basic user information such as name, email, country, or intended use of data to maintain records of data usage. Users will also be requested to sign an agreement on data-use restrictions for non-commercial purposes.

Indigenous cultural and intellectual property (ICIP) rights and benefit-sharing

RISE will respect and uphold ICIP rights by following recommended best practice guidelines [32, 33] under the key ethical principles of OCAP (ownership, control, access, and possession) and the Four R’s (respect, relevance, reciprocity, and responsibility) toward those who hold knowledge.

We will follow a principle of ‘active protection’ that promotes the active engagement of researchers with the knowledge holders and relevant community members, ensuring that the data generated by the project is recorded and stored in tangible form and encouraging opportunities for inter‐generational knowledge transmission throughout the project (i.e., intangible knowledge transfer). For example, the local team of collaborators collecting data on the distribution of traditional food species will comprise a mixture of young and experienced hunters/gatherers to facilitate the learning of young people from their elders. RISE is also committed to a ‘two-way’ transfer of knowledge. On one hand, Indigenous People have access to the benefits provided by scientific knowledge and tools. On the other hand, the project integrates and uses Indigenous knowledge (IK) according to existing local customary protocols directing decision making over knowledge sharing, and the free, prior, and informed consent of the Indigenous custodians of that knowledge.

We will follow a continuous process of clear consultation and provide free, prior, and informed consent at the group and individual levels. These will be carried out to ensure that participants in the project have been fully informed and have a clear understanding of the project purpose, methodology, and intended outcomes, including potential uses of the data related to IK generated by the project (i.e., full disclosure of risks and benefits). Participants will be given adequate opportunities and timeframes to make their own decisions regarding their consent to participate without coercion or pressure. Participants will be adequately informed that the consent form is a formal agreement of engagement between the community and the researcher that can nonetheless be revised, suspended, or withdrawn if needed during participation. To ensure correct understanding by all participating members, explanations will be made bilingual, including the official as well as the local Indigenous language, and supported by the use of visuals (time table, diagrams, pictures, information board, etc.) to reinforce the understanding of participants and promote open discussion and communication among the parts. Further, continuous oral and informed consent will be used for those who are illiterate or willing to participate in the project but are reluctant to sign the consent form. More importantly, consent is a necessary protocol that formalises the process of mutual understanding and agreement with the participation of local residents in our project. This is a gradual process that builds on the long-term working relationship of our local teams with the study communities. It will start with the introductory workshops and practical sessions that we are holding in the study communities to provide information on the project rationale, objectives, and operation (approach, materials, milestones, actors, community participation). This will continue throughout the project and beyond, reinforcing co-management and ownership of the project by the Indigenous community through the transparent and open assessment of project outputs, joint decision taking, benefit-sharing, and the discussion of research output with the community and other relevant local stakeholders (e.g., representatives of the Wildlife Sanctuary for the Karen case study).

All information gathered by our project related to IK will be recorded and stored in a form (data products) that is available, and accessible to community members. These include human materials, cultural assets, and knowledge systems, as well as any related products, such as written material (published and unpublished), digital material (e.g., video and audio files, GPS coordinate files), or maps. Data products will be appropriately stored in databases that will protect IK by respecting intellectual property, providing access and benefit-sharing to the IPs, and observing cultural integrity. Any intended external use of data concerning IK will require free, prior, and informed consent from Indigenous participants. Intended uses will first be discussed jointly with the Indigenous participants by presenting in clear, understandable terms the type and format of information/data to be used, specific purpose, dissemination channels (e.g., scientific publication, public lecture, project website, and blog posts), and providing a clear and honest explanation of the potential risks and benefits. We will pay particular attention to ensuring that research reports and project outcomes are not used in any way that is likely to adversely affect the interests of participants and Indigenous communities.

By promoting capacity building through training exchanges and technology transfer to the Indigenous communities, RISE will produce a wide range of direct benefits to the Indigenous community as a whole, as well as the individual members directly collaborating and participating in the project. First, through the active participation and engagement of Indigenous People in the research decision-making process, the project will generate valuable information on potential future risks from climate change to Indigenous traditional food systems with a focus on local needs and Indigenous priorities. This information should help improve the conservation and management of natural resources, as well as open opportunities for regional development and informed discussions with local authorities on the access and use of these natural resources. For example, maps showing projected changes in the future distribution of food species within communal lands, combined with Indigenous traditional environmental knowledge, can provide critical information on potential changes in the future availability and accessibility of food resources, allowing for prioritising management and conservation strategies. This is of special importance where land use and resource accessibility are already restricted, as in the case of the Karen communities and the wildlife sanctuary authority. Similarly, information provided by the project to the community on nutrition (food consumption, growth, and biochemical tests) and the benefits associated with traditional foods (e.g., prevention of non-communicable diseases linked to unhealthy diets and malnutrition) can promote a knowledge-based revitalisation of traditional food use. This is particularly important for the younger generations, because it provides an effective toolkit for adaptation to climate change, making them more resilient through nutritional diversification.

Second, participating members of Indigenous communities will be trained by our research teams on the use of equipment (e.g., GPS) and methodologies for data collection (e.g., how to conduct household interviews, how to operate a GPS, record locations where food species are found, and management of local databases to store data generated). RISE has also provided equipment to support these activities (e.g., GPS devices, solar-powered electricity generators, and digital cameras), which will be donated to the communities once the project runs its course.

Third, by making the data generated by the project accessible and available to participants, RISE will also generate important and valuable information that will help improve their livelihoods. For example, all analytical and anthropometric medical results (including blood analysis) will be shared with the participants and properly explained by a health center/officer, providing further advice and access to medication or intervention if a health problem is reported. This is a rare and important asset for them, as these analyses are expensive and access to health services is often difficult for these isolated communities.

Lastly, Indigenous research collaborators participating in the collection of field data (e.g., household interviews and food species distribution data) will be paid appropriate and agreed upon rates by the project in due recognition of their work.

Ethics statement