Consistency in climate change impact reports among indigenous peoples and local communities depends on site contexts

The study investigates how consistently Indigenous Peoples and local communities (IP and LC) report climate change impacts and what factors shape consistency at site and individual levels. Prior research shows IP and LC closely observe climate changes affecting atmospheric and biophysical systems supporting livelihoods. Understanding the patterning of these reports is key for monitoring and adaptation planning. Reports are influenced by site-level factors (histories, cultures, worldviews, religions, environmental settings) and individual-level factors (socio-demographics, livelihoods). Evidence is mixed regarding associations with age, livelihoods, experience, and employment. Cultural consensus theory suggests culture manifests through agreement and can assess shared knowledge and individual deviations. This cross-cultural study across ten sites on four continents asks: (i) How consistent are climate change impact reports across sites and individuals? (ii) Which factors influence consistency at site and individual levels? The site-level focus is on consistency differences by livelihood activity; the individual-level focus is on experience with nature-dependent activities, self-assessed Indigenous and local knowledge (ILK), and local family roots. The study examines consistency for atmospheric subsystems and biophysical elements underpinning crop production, pastoralism, and gathering.

The paper situates its inquiry within literature documenting IP and LC observations of climate impacts and adaptation, noting that interpretations vary with culture and environment (e.g., glacier retreat attribution differing between Italian and Peruvian communities; elevation-exposure effects among Tibetans). Case studies show complex, sometimes contradictory links between socio-demographics/livelihoods and perceived impacts: age can correlate with reported impacts in some contexts but not others; pastoralists often report more pasture/livestock impacts than non-pastoralists, though counterexamples exist. Cultural consensus analysis has revealed both shared and disputed climate impact perceptions and differences between local communities and external stakeholders. This background motivates examining cross-cultural patterns of agreement and the role of site vs. individual factors.

Design: Cross-cultural mixed-methods study within the LICCI project. Sites: Ten of 48 LICCI sites selected based on (1) availability of survey data, (2) surveys including at least two atmospheric and two livelihood-related biophysical impacts (crop/soil, pastures/livestock, wild flora/mushrooms), and (3) local relevance of the selected livelihood activity (≥20% average lifetime engagement from pebble game). Sites spanned Africa (4), Latin America (3), Asia (2), Oceania (1), across Köppen-Geiger climate zones and areas with sparse meteorological records. Data collection: Three stages per site: (1) Semi-structured interviews (20–47 per site) eliciting observed environmental changes since youth, probing atmospheric, physical, and life systems, including direction and drivers. Reports attributed to climate change and consistently observed (≥20% of respondents with >90% direction agreement) were considered site-confirmed. Disputed items were discussed in focus groups (1–12 per site; 4–12 participants) to seek agreement; agreed items were added. This yielded on average 38 site-confirmed impacts (SD=14; 21–65). (2) Surveys in 22 sites, with 10 sites retained for this analysis; random household sampling followed by convenience quota within households across gender/age; 75–316 respondents per site (mean 186; total n=1,860). Survey sections used here: (i) Random subset of 15 site-confirmed impacts per respondent; respondents indicated observation (yes/no) and direction. (ii) Pebble distribution method to estimate lifetime effort across livelihood activities (100 pebbles). Nature-dependent activities included direct interactions with nature (e.g., fishing, hunting). (iii) Self-assessed ILK relative to locally recognized experts for 3–4 relevant activities on a 4-step scale. Variables: Dependent variables at individual level: CCIC atmospheric (consistency with site-confirmed atmospheric impacts), CCIC livelihoods (biophysical elements for selected livelihood), and livelihood-specific CCIC (crop production, pastoralism, gathering). Site-level CCIC computed as means of individual CCIC per site for atmospheric subsystems (air masses, precipitation, seasons, temperature) and livelihoods. Explanatory variables: NEX specific (above/below site mean lifetime time in selected livelihood), NEX general (above/below site mean across all nature-dependent activities), ILK specific (self-assessed high [3–4] vs. low [1–2] for selected livelihood), ILK average (mean across 3–4 activities; high 2.5–4 vs. low 1–2.4), local family roots (3–4 vs. 0–2 grandparents from area; not collected in Daasanach and Mongolian sites). Controls: age (median split per site), sex. Analysis: Site-level descriptive comparisons and linear models tested differences in CCIC across atmospheric subsystems and livelihood activities. Individual-level relationships estimated using site-specific GLMs (binomial with logit link), controlling for over-dispersion; effects expressed as associations with odds of agreement. Meta-analyses integrated site-specific estimates across sites with same livelihood and across all sites using weighted models (nlme in R), weighting by standard errors. Ethical considerations included FPIC, ethics approvals, and attention to locally adapted protocols.

- Overall consistency: On average, 68% of individual reports of atmospheric system impacts matched site-confirmed reports across sites. For biophysical elements supporting livelihoods, average CCIC was 69%. - Atmospheric subsystems: CCIC differed significantly among subsystems (p=0.003): seasons 75%, temperature 75%, precipitation 71%, air masses 52%. Site extremes: lowest for fisherfolk in Mafia Island, Tanzania (34%); highest for Mongolian pastoralists in Mu Us Desert, China (94%) and iTaukei fisherfolk in Ba, Fiji (98%). Variation ranged from SD=2% (iTaukei) to SD=32% (Tibetan agropastoralists) and SD=29% (Dagomba agriculturalists). - Livelihood activities: CCIC differed significantly across livelihoods (p=0.012): pastoralism 76% (highest), crop production 71%, gathering 60% (lowest). Site deviations: Mafia Island fisherfolk 36% vs. iTaukei fisherfolk 93% and Mongolian pastoralists 97%. Mean between-site variation highest for crop production (SD=25%), then pastoralism (SD=20%), gathering (SD=14%). Within-site variation generally lower (crop SD=12%, pastoralism SD=13%, gathering SD=11%), with very low within-site SD (1–6%) in several sites and high SD in Tibetan (32%) and Dagomba (34%) sites. - Individual-level predictors: Across sites, local family roots showed no significant association with CCIC atmospheric. ILK average associated with higher CCIC atmospheric in 3/10 sites (Bassari agriculturalists, Mafia Island fisherfolk, Tibetan agropastoralists). NEX general linked to CCIC atmospheric only among Daasanach agropastoralists. Meta-analysis across all sites found no significant overall associations of NEX general or ILK average with CCIC atmospheric. - For livelihood-related biophysical elements: Local family roots associated with higher CCIC in 3/10 sites (Dagomba, Tsimane’, iTaukei). ILK specific positively associated with CCIC in Mafia Island fisherfolk and Tibetan agropastoralists. NEX specific positively associated with CCIC among Mapuche agropastoralists (Lonquimay), iTaukei fisherfolk, and Daasanach agropastoralists. However, meta-analyses by livelihood and across all ten sites showed no significant overall effects of local family roots, ILK specific, or NEX specific on CCIC crop production, pastoralism, gathering, or overall CCIC livelihoods. - Age effects: Meta-analyses indicated age had a near-significant positive association with CCIC atmospheric (p=0.062) and a significant positive association with CCIC livelihoods (p=0.030), with older respondents showing greater consistency with site-confirmed impacts.

Findings show substantial within-site agreement on climate change impacts among IP and LC: more than two-thirds of individual reports align with culturally correct (site-confirmed) impacts for both atmospheric and livelihood-related biophysical elements. Consistency varies by atmospheric subsystem (higher for temperature, seasons, precipitation; lower for air masses) and by livelihood activity (highest in pastoralism, lower in crop production, lowest in gathering). The authors attribute high within-site consistency to shared exposure to environmental changes and social processes of knowledge exchange and validation (e.g., community meetings), which support social learning and resilience. Variation across sites reflects differences in livelihood organization, socio-cultural heterogeneity, and environmental heterogeneity. Pastoralism often involves common pastures, shared herding practices, and similar livestock species, fostering more homogeneous observations and interpretations. In contrast, crop production and gathering encompass diverse species, locations, and sometimes specialist activities, yielding more heterogeneous experiences and lower consistency. Sites with greater cultural or environmental heterogeneity (e.g., multiple ethnic groups, diverse landscapes) exhibit lower consistency; more homogeneous contexts exhibit higher consistency. Consistency patterns across atmospheric subsystems likely reflect differential relevance to livelihoods: precipitation, seasons, and temperature have direct effects on crops and pastures, encouraging observation and discussion, whereas air mass changes (e.g., wind) may be less directly relevant for the focal livelihoods except in fishing contexts. At the individual level, broad cross-site analyses reveal no generalizable effects of nature experience, ILK, or local family roots on consistency, suggesting knowledge of major impacts is widely shared, diminishing individual-level variance except in specific site contexts. Age shows a modest positive association with consistency, adding cross-cultural evidence to mixed prior findings. Overall, results emphasize that consistency is shaped more by site-specific contexts than by universal individual-level predictors.

The study demonstrates that IP and LC across ten sites exhibit high within-site consistency in reporting climate change impacts, with greater agreement for pastoralism-related impacts and for temperature, seasonal, and precipitation changes than for air masses. Cross-site variation is substantial and linked to local livelihood organization, socio-cultural composition, and environmental heterogeneity. Individual-level factors such as nature experience, ILK, and family roots show no consistent cross-cultural effects, while age is modestly positively associated with consistency. These insights underscore the value of integrating IP and LC knowledge into climate monitoring and adaptation planning and tailoring strategies to site contexts. In high-consistency sites, planning can occur at broader community levels; in low-consistency sites, subgroup or household-level approaches may be necessary. Future research should refine knowledge measurements to capture idiosyncratic expertise and expand site coverage to enhance generalizability.

- Survey item selection: Only 15 impacts per site, randomly sampled from site-confirmed lists, led to unbalanced numbers of atmospheric vs. livelihood items across sites and may not capture the full complexity of ILK, potentially confusing respondents. - Selection bias toward agreement: Focusing on site-confirmed impacts (widely acknowledged and often achieving strong direction agreement) likely elevated consistency estimates compared to sampling from all reported impacts. - Limited site sample: Ten sites, all in the Global South, limit representativeness of the global diversity of IP and LC despite cross-continental coverage. - Knowledge operationalization: Defining knowledge as agreement with culturally correct information may overlook idiosyncratic expert knowledge; alternative measures could reveal different patterns. The methodological setup may also influence individual-level results.