Major changes in barren-ground caribou (Rangifer tarandus groenlandicus) habitat around the circumpolar north are leading to significant population declines (Vors and Boyce, 2009). There is no singular global driver of these declines. Herds are experiencing a mix of local, regional, and hemispheric anthropogenic and climate-driven changes that can alter caribou ecology (Post and Forchhammer, 2008; Vors and Boyce, 2009; Rickbeil et al., 2017; Zamin et al., 2017). In Canada’s north, barren-ground, caribou habitat has recently been subject to two principal drivers of change: intensification and expansion of industrial land uses; and climate warming and resultant changes to eco-hydrological processes (Joly et al., 2011).

The Bathurst caribou herd (BCH) traverses a range from their calving grounds on Bathurst Inlet south to their winter range north of Great Slave Lake. The BCH is an integral part of the cultural and spiritual lives of the ThchQ peoples who have lived with the herd for centuries. Population surveys have estimated a decline of over 95%, from over 470,000 animals in the 1980s to less than 10,000 in the most recent estimates (ENR, 2020).

Without a single known cause for the decline, management “solutions” must be locally embedded within the cultural communities that interact with the herd and its range. The Government of Northwest Territories (GNWT) has

Proposed conceptual model applied to Bathurst caribou herd population decline in Northwest Territories, Canada

FIGURE 8.3 Proposed conceptual model applied to Bathurst caribou herd population decline in Northwest Territories, Canada.

regulatory responsibility for the herd. Natural resource management decisions of GWNT must recognize traditional knowledge as a “valid and essential source of information about the natural environment and its resources” (GNWT Traditional Knowledge Policy, 2005). In our Eco-Healthscape model for the herd (Figure 8.3), it is essential to consider which actors are involved in each variable and how they might be engaged to achieve healthier outcomes. For instance, ThchQ communities in and around the winter range have long hunted and monitored the herd. Yet, with declines, modernization, loss of traditional ways of living, these “eyes on the land” need bolstering through targeted investments and resources to get local people involved in monitoring the herd. Such culturally integrated monitoring might then lead to insights that direct resource extraction and hunting regulations. Indigenous governments are indeed taking these steps. The EkwQ Naxoede K’e: Boots on the Ground Programme developed by the TljcliQ government, for example, focuses on field monitoring in the BCH summer range and “everything that relates to them” - focusing on four broad indicators: (1) habitat, (2) caribou, (3) predators, and (4) industrial development (TljcliQ Research and Training Institute, 2019). Such Indigenous-led stewardship is a viable means for conservation of ecosystem integrity and individual populations (Hunter, 2008; Artelle et ah, 2019).

Scientific management and monitoring, including GWNT ungulate biologists, data analysts, academic researchers, consultants, etc., remain essential components of research and monitoring herd size, habitat quality, and developing actionable insights into BCH management and recovery. The GNWT traditional knowledge implementation programme is helping to build a community of conservation with indigenous communities and scientific staff. Thus, when controversial control measures such as a total hunting ban are proposed, as was the case in 2016, they are more acceptable by both scientific and indigenous communities than would otherwise be the case. These proactive approaches, rooted in co-management, relationship building, and culturally integrated health promotion, reveal promising tools for an Eco-Healthscape approach.


Practical Considerations in Taking an Eco-Healthscape Approach

The complexity involved in understanding and taking action that changes health outcomes in favour of a group of species is staggering. There will be no statistical recipe or data analytic approach that will work in every context. We have, however, identified several key practical considerations when considering how to employ space and place thinking across species boundaries.

1. Getting the scale(s) right

The geographic scale(s) of health promotion activities is critically important. When attempting to translate a finding about, for example, features of the landscape (e.g. edge habitat) impacting disease risk, one must consider the magnitude of this feature in a given locale, and how people already interact with such features and how people’s experiences and activities relate to the landscape configuration. If human-modified aspects of the landscape relate to the population health, consider how to engage with local cultural communities shaping those places rather than through generic messaging.

2. Isolating key variables without reducing complexity

While any given Eco-Healthscape context necessarily includes a multitude of species and their internal and external factors, it becomes important to isolate key variables that create conditions for health. For example, while “climate change” may be a driver of ecosystem change and community response(s), tracking changes in temperature may not be the most effective means to understand or impact future health states. What data can be collected or analysis performed that maximizes coverage of key processes? In the case study above, while Indigenous-led stewardship may not reduce threats, they will inform on key internal variables, and do so in a way that can incentivize future actions.

3. Developing generic data synthesis tools

The most important data analytic task that will facilitate Eco-Healthscape research is developing tools for data integration. Given that data are frequently repurposed to look at spatial and platial associations with health, bringing data into a common representation is critical. Often, data integration is akin to mapping spatial data onto specific units of analysis, for example census units or ecozones. Generic data representations, such as pixel arrays, or functions of space such as Delaunay triangulations, can provide consistent, reproducible tools for bringing disparate datasets into a common spatial fabric. Discrete global grid system is an emerging geographic data standard that can also serve as an intermediate data integration node (Robertson et al„ 2020). Given the need to mobilize analytical results across different user communities, having clearly documented data collection, integration, and analysis procedures is important.


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