1.7. Situating communities in species space

Our next step was to make results more comparable across all these individual studies, which varied in the number of people surveyed, the types of food frequency or diet recall questions asked (e.g., how many days was this food consumed, or how many portions of this food do you consume per week, or how many grams of this food do you eat per day), and the level of detail to which animal species were identified. Our process of data standardization removed some of the details communicated in the already published data, including for example the overall amounts of local food that communities reported consuming. Instead, we focused only on how the local food consumption reported by a given community was distributed across various species, expressed not as an amount consumed, but as a percentage of the total reported local food consumption (e.g., species A contributes 50% of the total amount of traditional food consumption reported, species B contributes 20%, species C contributes 10%, and so on). We believe this approach makes among study comparisons more robust and less sensitive to different methodologies, and at the same time avoids re-reporting some of the more detailed and potentially sensitive information generated by these surveys (e.g., communities reporting more or less local food consumption, how much or how often a given species was consumed which could be interpreted as reflective of harvest rates, etc.).

Analysing all these community surveys together shows several general patterns (Figure 13). Across the 21 northern Canadian communities, caribou was the most widely consumed animal food species, followed by geese (including Canada Geese, Snow Geese, etc.), moose, whitefish/cisco, and grouse/ptarmigan. However, most communities consumed more than 10 different animal species or species groups and, over all communities, 45 species groups of animals were consumed.

Next, we presented these communities and their patterns of reported food use on a Non-metric Multidimensional Scaling (NMDS) plot. NMDS is a multivariate approach that we used to visualize community differences in local food use. In our community NMDS plot, a community’s food use (their proportional use of various species) is represented by a single point per community positioned in the two-dimensional space created by two multivariate axes (NMDS-1 and NMDS-2). Two communities that are positioned close to each other in this NMDS space have highly similar diets involving consumption of many of the same species in similar proportions. Conversely, two communities that are positioned far from each other in this NMDS space have low dietary similarity involving consumption of different species or some of the same species but in very different proportions. Adding species vectors to a NMDS plot helps to visualize how different species contribute to the two NMDS axes and helps to visualize where communities are situated in species space (Figure 14).

Our species space results support the well-described central importance of caribou, geese, and ptarmigan/grouse in the diets of both Inuit and First Nation communities, the particular importance of beluga, seal, and char in Inuit country food systems, and the particular importance of moose, freshwater fish, and waterfowl in the traditional foods of First Nations communities. Our results also reveal a less discussed west to east pattern in First Nations traditional foods, with northwestern First Nations consuming more ungulates and salmon but fewer birds and other types of fish, and northeastern First Nations consuming more birds, bears, and beaver, as well as a wider variety of freshwater fish.

We wondered what factors might predict the diet similarity of community pairs. We had three non mutually exclusive ideas. First, perhaps communities that are closest together, in terms of distance, have the most similar diets and those that are farthest from each other have the least similar diets. Second, because traditional food systems involve, by definition, locally available wildlife, and ecological factors should determine what species of wildlife are locally present, perhaps communities that are situated in similar ecological landscapes will have the most similar diets and those situated in the most ecological distinct landscapes will have the least similar diets. Third, perhaps dietary similarity has less to do with distance and ecology and more to do with culture, with culturally similar communities being characterized by more dietary similarity than culturally distant communities.

Before explaining how we assessed these three factors and what our analyses suggested about their relative importance, we want to explain a little about how, in our experience and opinion, academic research has struggled with these kinds of questions. Western worldview and scientific literature has perpetuated, but also at times resisted, a nature-culture separation. Social-ecological systems, biocultural systems, and ecosystem services are all concepts and approaches that seek to bridge this separation by recognizing people and nature as connected. But empirical, quantitative demonstrations of these connections remain rare, mostly because it is difficult for scientists to quantify and communicate inter-related parts of holistic outcomes.

We used something akin to google maps to estimate straight line distance between communities. We assessed ecological relatedness based on whether communities were in the same ecozone or biome and whether or not they were on or away from the coast. Assessing cultural relatedness is trickier and likely more controversial, because culture is multi-dimensional and self-defined. Yet we thought it was important to try to include in this analysis because we expected it to matter quite a lot in patterns of food use, based on our own community-based research experiences and from literature describing food and feeding as a cultural practice. Aware of the importance of language to Indigenous cultures, we used published linguistic analysis of language families and language groups, as proxy for cultural relatedness. The linguistic relationships we use as a basis for estimating cultural relatedness are illustrated in Figure 13.

Assessing the relative contributions of culture, ecology, and space as predictive of local food use is made challenging by the reality that these three features are themselves correlated (Figure 15). Similar cultures tend to live close to one another and as a result occupy similar environments.

Accordingly, we assessed the explanatory power of cultural relatedness, ecological relatedness, and spatial distance using a statistical technique called variance partitioning, so-called because it partitions shared vs. independent explanatory power of a series of partially correlated predictor variables. We follow the convention of presenting the outcome of a variance partitioning analysis as a Venn diagram, with overlapping circles reflecting predictive power of one explanatory variable that is shared with other explanatory variables and non-overlapping portions of circles indicative of unique explanatory power (Figure 16).

What did we find? If food and feeding are largely cultural and biodiversity is largely ecological, when local biodiversity is used as food, is the local food system more culturally defined or more ecologically defined or more spatially defined? In short, the surprising result is that all these food frequency questionnaires and statistical analyses end up emphasizing what can be the most difficult to quantify in academic literature: the importance of culture in defining how people interact with nature. All three variables have some importance, and all three are inter-connected, but still a very clear and striking pattern in our analyses is that communities characterized by large linguistic differences tend to have very different local diets and those that are linguistically most similar have the most similar local diets. This cultural factor tends to supersede ecological differences and spatial distance (Figure 16).

A specific example, from northern Quebec, may help clarify the general pattern we detected. In northern Quebec, the Inuit community of Kuujjuarapik and the Cree community of Whapmagoostui are separated by essentially no geographic distance (the two communities are side by side) and no ecological differences (they are both situated in the same, coastal-subarctic ecological zone), but yet harvest and consume distinct local foods. We do not have access to Kuujjuarapik-specific food consumption data, but comparing 1970’s harvest data from the two communities emphasizes this distinction (Figure 17).

We end the discussion in Tremblay et al. (2020) by considering what these results suggest about the nature of community adaptation as climate change continues to alter wildlife species distributions and abundances. The expectation that community harvest practices and food use will simply change as local ecological conditions change rests on environmental determinism independent of cultural factors, which is equivalent to the small red space labeled as ecological relatedness in our variance partitioning analysis (Figure 15). The smallness of this predictive space (representing diet predicted by ecology independent of culture and spatial distance) should give pause to this expectation; it ignores the extensive overlap among cultural, ecological, and spatial circles reflecting social-ecological coupling and biocultural relationships. The tensions and stresses created by environmental change can be envisioned as what happens when the ecological circle is moved away from the other two (Figure 15). For example, the thin red space might, if diets become more environmentally determined, expand into a larger space. For this expansion to occur, however, social-ecological coupling must decline. Whatever the response or adaptation, environmental change will cause a pulling apart of people, environment, and place. Nevertheless, all long-term relationships change over time, and the relationship between Indigenous peoples and nature is a long-term relationship. The contemporary social-ecological systems described by people through food frequency surveys and statistically summarized here are, inevitably, a product of many past episodes of cultural and environmental change, sometimes occurring in parallel and at other times with one far outpacing the other. Thus, continuity of social-ecological change is a reasonable expectation, so long as it is realized the change will be shaped by people and nature combined.

Academic research often struggles to communicate the importance of things that Indigenous Peoples know to be true, through their lived experience and traditional knowledge. Our finding that culture is important in shaping the local food choices of Indigenous Peoples, may very well be a statement of the obvious, likely accomplished through an analysis that misses some important details, and probably in a way that is too numeric and too removed from the lived-realities of communities. However, to at least the statistically and quantitatively-inclined, we hope this analysis helps to highlight the importance of culture in defining patterns of local food use.