Statement of Inclusion
Our camera trap study was conceived by members of the Whitefish Lake
First Nation (WLFN), and our work brings together authors from the First
Nation, where data were collected, with US and Canada-based scientists.
All authors were engaged throughout the research and study design to
ensure that their diverse perspectives were considered from the onset.
Elders from WLFN were also consulted for their expertise and
perspectives on moose ecology and changes in habitat use before and
during the writing process.
Abstract
Subsistence hunting, or “country food,” is essential for Indigenous
Peoples who face high food insecurity and is critical for Indigenous
Food Sovereignty. For many First Nations of Canada, subsistence hunting
is also inextricably linked to traditional conservation practices, as
hunting is an important way of engaging with nature. In the boreal of
Canada, large game such as moose (Alces alces) are a
primary source of protein for many First Nations. However, resource
extraction, including forestry practices and oil and gas extraction, has
shifted large game distributions and affected the availability and
abundance of food resources. Here, we used remote camera trap data and
generalized linear models to evaluate moose habitat use and
spatial-numerical response to possible stressors in north-central
Alberta, including fire, harvest, oil and gas extraction, and other
disturbances. We also examined the effects of human-caused stressors on
habitat use by sex and age class data. The proportion of various land
cover types and human land use for resource extraction were important in
moose habitat use. Overall, adult moose avoided burned areas and
grasslands. Notably, male, female, and young moose all used habitat
differently and at different spatial scales. However, young moose (with
their mothers) strongly selected natural forest disturbances such as
burned areas but avoided human-created disturbances such as petroleum
exploration “seismic” lines. Female moose with young attempting to
maximize forage opportunities do not use human-disturbed forests in the
same ways they use naturally disturbed areas. This also aligns with
observations from Indigenous communities, which have linked human
disturbance to declines in moose densities and displacement from
traditional hunting grounds. Understanding and predicting shifts in
large game distributions is critical to supporting Indigenous Food
Sovereignty and identifying where industries operating on First Nations
lands can better engage responsibly with First Nations.
Keywords
Traditional ecological knowledge, moose, subsistence hunting, resource
extraction, country food
Introduction
Indigenous communities globally have relied on subsistence hunting of
local species since time immemorial. However, communities most reliant
on local ecosystem services, such as subsistence hunting, are the most
vulnerable to threats associated with biodiversity and species loss
(Díaz et al., 2006). Subsistence hunting
sometimes exacerbates the deleterious effects of human resource use on
local systems and species (Luz et al.,
2017), particularly in regions where hunting is non-selective, or
species are already at high risk due to habitat loss, climate change, or
pollution (Lindsey et al., 2013;
Ripple et al., 2016;
Theriault, 2011). However, the assumption
that subsistence hunters solely maximizing harvest in the short-term
rather than balancing foraging with conservation (i.e., considering the
long-term benefits of sustainability) is incorrect
(Alvard, 1994;
Bodmer et al., 2020;
VanStone, 1974).
In North America, subsistence hunting (also referred to as “country
food”) is closely linked with Indigenous conservation practices
(Feit, 1973;
Gottesfeld, 1994). These conservation
practices range from limits on the number of individuals harvested to
seasonal rotations of hunting grounds. In many parts of North America,
ethical subsistence hunting (as determined by local Indigenous
communities) is essential for food security
(Theriault, 2011), supports Indigenous
Food Sovereignty (Cidro et al., 2015),
and has additional social, cultural, and spiritual importance
(Van Oostdam et al., 2005). Across much
of North America, Indigenous harvesting is declining despite the
importance of subsistence hunting for Indigenous communities
(Gilbert et al., 2021;
Shafiee et al., 2022), in part due to
cost (i.e., permits, equipment) and concerns about environmental
contaminants in hunted food (Skinner et
al., 2013), including cadmium, lead, arsenic, mercury, methylmercury,
and other persistent organic pollutants
(Chan et al., 2021). Many Indigenous
communities have expressed resignation at the continued loss of their
subsistence landbase (Westman & Joly,
2019).
Industrial resource extraction has resulted in rapid changes in the
densities, distributions, and communities of traditionally hunted
species across Canada. Energy development, specifically oil and gas
extraction, is one of the primary causes of the decline of woodland
caribou (Rangifer tarandus; atihk in Cree) across western
Canada, (Hebblewhite, 2017). Some species, such as wolves and bears,
benefit from and consistently use anthropogenically-created landscape
features in Western Canada (Dickie et al.,
2020; Dickie et al., 2017), increasing
hunting efficiency (McKenzie et al.,
2012). However, not all species benefit from these features, and many
more actively avoid them (Fisher &
Burton, 2018). Increases in predator population size due to landscape
development (Latham et al., 2011) and the
high prey-kill rates associated with anthropogenic features
(Boucher et al., 2022) impact
traditionally hunted species across Canada, leading to additional
pressures on country food.
Moose (Alces alces; moswa in Cree) are an important, but
declining, subsistence resource for the First Nations of Canada
(Kuzyk et al., 2018;
Natcher et al., 2021;
Priadka et al., 2022;
Ross & Mason, 2020), and there is
widespread recognition that resource extraction impacts moose population
dynamics, distributions, and predation rates in Alberta
(Lamy & Finnegan, 2019;
Neilson & Boutin, 2017). In the boreal,
moose select for habitat that provides security when predator abundance
is high (Ethier et al., 2024), and have
lower occurrence in areas with pipelines, seismic lines, 3D seismic
lines, unpaved roads, and new cutblocks
(Dickie et al., 2022;
Finnegan et al., 2023;
Fisher, Grey, Anderson, Sawan, Anderson,
Chai, Nolan, Underwood, Maddison, et al., 2021;
McKay & Finnegan, 2023;
McKay & Finnegan, 2022), which are often
used by predators. This suggests that perceived predation risk is a
strong driver of habitat selection, especially in areas with high human
use. There are some potential benefits of human land use for moose, as
forest cutblocks offer increased moose forage
(Francis et al., 2021;
Johnson & Rea, 2023). However, the
effects of herbicide treatment and predation risks in these cutblocks
might outweigh the benefits, as moose in high herbicide-use areas
consume fewer forbs (Koetke et al.,
2023). Finally, resource roads and trails associated with forestry and
petroleum open access to previously remote areas, facilitating poaching,
as has been observed by First Nation communities. Overall, the degree to
which moose abundance and habitat use have shifted across traditional
territories with increasing human land use is unclear, partly due to the
challenges of monitoring moose populations in traditional hunting areas.
There are many inherent challenges in assessing moose abundance and
distribution changes, primarily those associated with animal detection.
While aerial surveys are often used in moose monitoring
(Moll et al., 2022), these methods are
challenging for Indigenous communities to employ (e.g., cost, time, and
human safety risks associated with helicopters (Jones
IV et al., 2006;
Watts et al., 2010). Instead, remote
cameras (also known as “camera traps” or “trail cameras”) offer an
effective means of sampling mammal populations when appropriately
employed (Burton et al., 2015).
Furthermore, camera trap studies are an effective approach for the
coproduction of knowledge and Indigenous-led or co-created research
(Fisher et al., 2021).
We sought to quantify the effects of human disturbance, fire, and land
cover on moose relative abundance and spatial distribution using remote
camera data to inform First Nation subsistence hunting. Specifically,
our goal was to determine the relative impacts of forest harvest, linear
features (e.g., roads and pipelines), oil and gas extraction sites,
forest cover types, and age of burned areas on moose distribution. We
also sought to compare the relative effects of these features by age and
sex, as male and female moose (with and without young) may select
different features at different scales when balancing predation risk
with forage availability. We generally expected moose with higher
nutritional needs (e.g., females with young) might use “riskier”
(open) habitat when high-quality forage is available and that all moose
would be strongly associated with aquatic features due to their dietary
needs (Fraser et al., 1984). We also
expected differences in habitat use by sex and age, primarily between
young moose (young of the year and young of last year) and males due to
different dietary and safety needs. We also expected that the spatial
scales at which landscape features explain moose distribution
(Holland & Yang, 2016) might differ by
sex and age, as male moose may use broader areas, balancing foraging and
seeking mates. In contrast, cows with young moose would likely be driven
by the need for high-quality forage to support nursing young and
offspring growth.
Methods
Study area
Our study area encompassed the Whitefish Lake First Nation (WLFN)
traditional territory, a Treaty 8 Territory
(Fumoleau, 2004) in north-central Alberta,
Canada (Figure 1), characterized by expansive central mixedwood forests
interspersed with many small lakes, bogs, wetlands, fescue grasslands,
both open and closed conifer stands, and closed shrublands (AMBI 2020).
The Indigenous co-authors have been living on this land for millennia,
relying on its resources to survive in this cold and relatively
nutrient-poor boreal landscape. Recent industrial modification in the
form of forestry and oil and gas extraction – which we refer to as
“anthropogenic landscape features” and “anthropogenic disturbance”
– differs vastly from traditional stewardship techniques and is
abundant across the landscape (Figure 1). The area has experienced
forest harvest for a few decades. Harvested conifer stands are typically
replanted and treated with glyphosate (N-(phosphonomethyl) glycine) via
helicopter, resulting in notable changes to plant communities and
resources used by the First Nation. Widespread petroleum extraction is a
more recent and even more widespread and diverse disturbance (Pickell et
al. 2013, Pickell et al. 2014, Pickell et al. 2015). WLFN Elders note
that the drastic human-induced landscape changes on their Territory have
resulted in precipitous declines of many important mammal and plant
species. They also note that, like many other parts of Canada,
increasing fire frequency is ‘extreme’ (Gaboriau et al. 2022), with new
burn records being set in recent years (CIFFC, 2023; Canadian National
Fire Database, 2023; but see Chavardès et al. 2022).
Camera Trapping
WLFN co-authors designed the research study, sampling sites were
assigned based on a constrained random stratified design. The landscape
was divided into four strata based on dominant canopy cover and
hydrological conditions, and sites were randomly selected from these
strata, with some constraints based on the logistics of access.
Community members deployed 130 ReconyxTM Hyperfire 2
(Holmen, WI, USA) cameras between 2018 and 2023 (Figure 1). Of these
cameras, 75 were deployed and active from December 2018 to April/May
2019, 25 more were added in March, and all 100 were active between March
and November 2019. WLFN deployed an additional 30 cameras, which were
active from June 2022 to July 2023. Cameras were placed ca. 1.5 m
above ground at sampling sites. Sampling sites were active wildlife
trails and camera sensors were set to “high sensitivity” to record one
image with each heat-in-motion detection, with no programmed delays
between photographs, adopting techniques used in Fisher and Burton (2018). WLFN
staff and volunteers classified images to species by using TimeLapse2
Image Analysis software ( Greenberg et
al., 2019). Of the deployed cameras, timelapse data and images
were retrievable from 121 cameras (96 of the original 100 and 21 of the
subsequent 30). Images were grouped across sampling periods for our
analysis to ensure naïve occupancy was sufficiently large for meaningful
results. Images were also categorized as male, female, young of the year
(YOY), or young of last year (YLY) whenever possible.