Indigenous-led camera-trap research on traditional territories informs conservation decisions for resource extraction

The agricultural and industrial revolutions that followed European colonization led to widespread landscape change and ushered the Anthropocene era, in which global systems are largely human dominated (Vitousek et al. 1997; Steffen et al. 2011; Maxwell et al. 2016). The resource extraction that powers global economies is often manifested in Indigenous Peoples’ traditional territories (Veltmeyer 2013; Gilberthorpe and Hilson 2016). However Indigenous Peoples are often excluded from conservation decisions, and their traditional ecological knowledge is often omitted from decision-making (Thompson et al. 2020). Global economies depend on development across thousands of traditional territories worldwide; empowering Indigenous communities to manage development on their territories will scale up for positive impacts on global biodiversity (Garnett et al. 2018).

Across North America, mammalian species have declined markedly since European colonization (Laliberte and Ripple 2004). However, even in the “remote” regions of the boreal Nearctic, human occupation dates back millennia (Goebel et al. 2008). First Nations coexisted with wildlife and in some places managed the land using methods such as prescribed burning (Kimmerer and Lake 2001), and Indigenous land practices have led to increased forest biodiversity (Fisher et al. 2019). In many areas Indigenous lands’ biodiversity equals that of federally defined and managed protected areas (Schuster et al. 2019).

Indigenous Peoples have a strong tradition of oral history, so they are uniquely positioned to observe and interpret changing conditions within the context of recent history (Gilchrist et al. 2005; Kendrick and Manseau 2008; Parlee et al. 2014; Kohler et al. 2019). However, consultation for resource extraction projects is often cursory and superficial (Baker and Westman 2018) and Indigenous knowledge often discounted. Partnering Indigenous knowledge and western science holds great promise for understanding how systems work and how anthropogenic change affects those systems (Mistry and Berardi 2016; Popp et al. 2019), provided it overcomes many noted social barriers (Carman et al. 2019). Here, we illustrate how Indigenous-led research guided by traditional ecological knowledge can identify the relationships between industrial landscape features and mammal distribution, to inform better conservation decisions in areas of dramatic change.

The western Nearctic boreal forest has remained more or less intact until the late 20th century, when widespread forest harvesting caused changes to mammal (Fisher and Wilkinson 2005) and bird (Schieck and Song 2006) communities. Soon thereafter, petroleum extraction proved economically viable and spread across the western boreal forest, creating widespread disturbances unique in their shapes and in their age and size distributions (Pickell et al. 2013; Pickell et al. 2015). Resource extraction has impacted mammal distributions (Fisher and Burton 2018) and populations (Burgar et al. 2019). Pressingly, landscape change has generated precipitous woodland caribou (Rangifer tarandus) declines (Boutin et al. 2012). Within this landscape, which supports substantial North American resource extraction economies, live two dozen Indigenous communities who experience first-hand the environmental and socioeconomic effects of development stemming from ineffective government consultation and alienation from decision-making, such that that many feel resigned to suffer the loss of their land and its biodiversity (Westman and Joly 2019).

Within this landscape, the co-authors—Indigenous Peoples of the Whitefish Lake First Nation (WLFN), a Treaty 8 (Fumoleau 2004) Nation of 3000 people—have a long tradition of subsistence hunting and close ties with the land. This long relationship has provided the WLFN co-authors with traditional ecological knowledge of the land and its species; knowledge collected has been passed down inherently through generations. It has been ingrained into a way of thinking naturally. Recently the co-authors observed changes to the wildlife populations on their land: Wherever there are forest harvesting cutblocks, wolves (Canis lupus) multiply and moose (Alces alces) and white-tailed deer (Odocoileus virginianus) decline. This varies with water and snow availability in each season. When there is deeper snow, wolf travel becomes harder, and more moose survive. In summer, if there is a lot of water, moose survive in wet areas. In dry seasons with forest fires, moose move from their typical habitats and the wet habitat is lost to them. Fewer moose become available for First Nations subsistence hunting. In the northeast of the territory, a large forest fire burned in 2011. The fire left more dead trees on the ground, providing cover as the dead trees fall over. Snowshoe hares (Lepus americanus) have higher tendency to survive due to the cover provided from fallen trees, which provide protection from predators. Lynx (Lynx canadensis) follow those hares, and so do coyote (Canis latrans), so both are more common in those disturbed areas. The increase in industrial activities has also led to fewer moose. Fewer moose are observed in roaded areas due to collisions and exposure to poaching (personal observation).

Declines in moose food sources are particularly troubling. Forest harvesting usually increases moose forage and hence relative abundance, but may exclude moose where patch sizes and context are insufficient for protection cover and other life-history requirements (Fisher and Wilkinson 2005). The Nation’s knowledge suggests this latter case, with moose faring poorly in cutblocks and other cleared landscape features. Moreover, a common prey of wolves, coyotes, and lynx—snowshoe hare—increases in disturbed areas, with subsequent increases in these predators.

With traditional ecological knowledge suggesting changes to mammal populations in response to resource extraction, there is impetus to identify the landscape features and associated industrial sectors affecting mammal distribution as targets for conservation. Forestry and petroleum sectors are managed separately, and each generates different landscape features. Energy exploration creates linear “seismic lines” (Dabros et al. 2018); energy extraction creates oil wells, pipelines, and processing facilities; forest harvesting creates polygonal forest harvest blocks; and the transportation sector creates networks of roads and trails to support these activities. Cumulatively these induce marked biotic change on mammal communities (Fisher and Burton 2018; Wittische et al. 2021), but evidence for which sector has the biggest influence remains unknown. Identifying the landscape features and associated industry responsible for change allows the Nation to funnel consultation resources into discussion with that sector and is the first step to targeted conservation (Westman and Joly 2019).

We used camera trapping (Burton et al. 2015; Steenweg et al. 2017) to identify which landscape features best explained variability in mammal distribution across the territory. Traditional Knowledge held by First Nations is made of long-term observations, but we do not have companion western science data on population trends, so we are constrained to contemporary data. However, if anthropogenic landscape features are avoided by a species, and associated with lower space-use across the territory, we made the logical assumption that these measures are evidentiary of potential population declines (Hui et al. 2009; Clare et al. 2015; Linden et al. 2017). Our goal was to weigh the relative importance of anthropogenic features—such as petroleum exploration seismic lines (Dickie et al. 2017; Dabros et al. 2018; Serrouya et al. 2020), forest harvest cutblocks (Fisher and Wilkinson 2005), and well sites, industrial sites, roads, and trails (Fisher and Burton 2018)—in explaining spatial variability in boreal mammal species’ distributions. Using camera-trapping data, generalized linear models, and Indigenous knowledge, we sought to understand the extent to which different kinds of features—those offering resource subsidies, or movement subsidies, or habitat loss (Fisher and Burton 2018)—affect mammal species in this complex landscape.

We detected multiple mammal species across the Territory (Fig. 3). Snowshoe hare, moose, white-tailed deer, lynx, black bear (Ursus americanus), wolf, and coyote were most frequently detected (Table S2).

Boreal forest mammals on the First Nation’s traditional territories are affected by the petroleum, forestry, and transportation sectors. The Canadian boreal forest landscape provides economic benefits of global importance (Bayoumi and Mühleisen 2006; Giesy et al. 2010; Heyes et al. 2018) but with costs absorbed by First Nations; although they live on these resource landscapes, they are rarely involved in management (Wellstead and Stedman 2008; Parlee 2015; Baker and Westman 2018; Westman and Joly 2019).

Illustrating cumulative effects of multiple sectors has been a Western science goal (Fisher and Burton 2018; Heim et al. 2017), but identifying the landscape features and associated sectors most responsible for biotic change is a key starting point for First Nations wildlife co-management (Baker and Westman 2018; Westman and Joly 2019). Co-created research informed by traditional ecological knowledge (Abu et al. 2019; Colbourne et al. 2019; Skroblin et al. 2019; Wheeler et al. 2020) provides insights important to effective conservation. Here, the WLFN coauthors’ traditional ecological knowledge informed a series of model hypotheses that help identify landscape features associated with mammal distributions and identified the specific landscape feature(s) causing change among multiple species. Although co-authors suggested forest harvesting was a primary sector affecting wildlife, this camera-data research suggests oil and gas is generating the most change. We discovered that changes among predators and prey can be traced to changes in the density of well sites on the landscape, with a contribution of forest harvesting through inflated white-tailed deer, which are invasive on this landscape (Fisher and Burton 2020; Fisher et al. 2020). Although these changes were expected to be contextual with recent fire, we did not parse this apart with our industry-focused design.

Moose are a particularly important species here and WLFN traditional ecological knowledge indicates moose were less abundant in places with forestry and energy extraction on the traditional territory. This knowledge corroborates evidence from camera-traps and statistical models; the influence of several sectors is apparent. The Nation observed that oil wells disturb habitats and human activity on associated roads and trails—by energy workers and hunters—make these areas unsuitable habitat. The Nation also identified that new cutblocks on their lands are unable to sustain moose; although this was not the strongest driver of moose occurrence, it was nonetheless detectable. Armed with this evidence, better decisions about land management to conserve moose can be made—provided Indigenous voices are heard.

Indigenous-led research also unveils hidden complexities. Oil and gas well sites are pervasive on the western boreal landscape and they generate spatial patterns completely unique from natural disturbance (Pickell et al. 2013; Pickell et al. 2015). Well site deployment removes mature forest and replaces it with early seral vegetation. However, well sites are on average 1 ha in size (smaller than forest harvest blocks and fires) and are pervasive (Fig. 1), creating hundreds of patches of young vegetation embedded within an otherwise intact forested matrix. Well sites offer a resource subsidy that snowshoe hares capitalized upon, likely bolstered by the 2011 forest fire as per the WLFN co-authors’ observations. Also following their observations, hare predators—lynx, coyote, and wolf—then exploit this abundance of hares. Lynx, as snowshoe hare specialists (Ward and Krebs 1985; Murray et al. 1994; Stenseth et al. 1997), cue into these prey-rich sites. Coyotes, which prey upon snowshoe hares (Murray et al. 1994; O’Donoghue et al. 1997; O’Donoghue et al. 1998a, 1998b) and other small and mid-sized mammals (Dumond et al. 2001), likewise select well pads with their abundant prey. Wolves prey on these same small mammals (Floyd et al. 1978; Thurber et al. 1992; Weaver 1993; Arjo et al. 2002; Urton and Hobson 2005), and our data suggest wolves too are cueing in on well sites. Black bears use both vegetation and prey subsidies. Thus, the pattern the WLFN co-authors observed with fires—of hares increasing followed by predators—is also mirrored in areas with high well site density.

Wolves (Bergerud et al. 1983; Messier and Crête 1985; Marshal and Boutin 1999) and coyotes (Benson and Patterson 2013) prey on moose. Thus, with increased small prey use comes increased predator density, and well sites—which would otherwise offer an early-seral vegetation resource subsidy, but instead represent a high-risk landscape feature for moose, which avoid them. Indigenous knowledge corroborates this contention: the Nation has repeatedly observed that moose use developed areas for only 2–3 d then move on. Wolves follow them into these areas, pushing them off, or killing them. Given that well sites offer early seral vegetation resource subsidies embedded in escape cover, and that comparable small forest harvest areas are elsewhere selected by moose (Fisher and Wilkinson 2005), the predator avoidance hypothesis appears to offer a parsimonious explanation and is supported both by Indigenous ecological knowledge and by evidence from camera-trap data.

Past western science suggests linear features are key to wolves, as linear features expedite travel (Dickie et al. 2017) especially in winter, thereby increasing predation rates on woodland caribou (Whittington et al. 2011; McKenzie et al. 2012). In this landscape, effects of seismic lines did not predominate, and instead well sites best explained wolf distribution. Although seismic lines are the focus for landscape restoration efforts in western Canada (Dabros et al. 2018; Tattersall et al. 2019; Serrouya et al. 2020), this Indigenous-led research suggests well sites should also be a focus of restoration. Co-management of landscape planning between industry and the Nation might prevent negative effects on wildlife from the start.

Our approach identifies the most important targets for management on traditional territories, most likely to produce positive change. Though landscape management for conservation across the whole boreal may be prohibitively expensive, targeting the foremost problem for the most species is a wise approach for triage (Schneider et al. 2010; Hebblewhite 2017).

Indigenous-led research can be used as globally as the technology allows (Steenweg et al. 2017) to inform statistical models built from Indigenous knowledge (Skroblin et al. 2019), and resulting conservation decisions can yield substantial positive outcomes for conservation science (Carman et al. 2019; Kohler et al. 2019). Co-management of resources is an evolving trend globally (Castro and Nielsen 2001; Spak 2005; Ross et al. 2009), hopefully replacing consultation processes that are ineffective in implementing vital conservation knowledge and advice (Thompson et al. 2020).

The United Nations Declaration on the Rights of Indigenous Peoples (Gilbert 2007) calls for First Nations’ involvement in development of their lands. Consultation processes are often insufficient for conservation (Baker and Westman 2018; Westman and Joly 2019; Thompson et al. 2020) as witnessed by continuing biodiversity declines in extraction landscapes around the world. We illustrate how co-created Indigenous-led research that informs the conceptual foundation for research, the goals, the hypotheses, and the interpretation of results, yields valuable insights different to a single western-science perspective: in this case, multiple wildlife species are more likely to occur in areas with dense petroleum well sites. Multiple modes of knowledge are needed to tease apart the growing complexity of species interactions and response to disturbance in rapidly changing landscapes, hopefully leading to better management decisions to conserve biodiversity.

We are thankful to Environment and Climate Change Canada for funding this work. Thanks to the Elders of Whitefish Lake First Nation for their teaching and guidance to the co-authors. Thanks to Alina Fisher for manuscript review and Jeff Dixon for illustrations (Fig. 4). Finally, we are thankful to Brian Tallman, Band Administrator at Whitefish Lake First Nation, and Chief and Council for facilitating us.