Introduction
The global urban population is expected to increase by 2.5 billion
people over the next 30 years (Seto, Güneralp and Hutyra 2012),
following decades of continued urban growth (Seto, Fragkias, Güneralp
and Reilly 2011). Consequently, urban landscapes have doubled in the
last few decades leading to direct and indirect forest loss (van Vliet
2019). By 2030, global urban land cover is projected to increase between
430,000 km2 and 12,568,000 km2(Seto, Güneralp and Hutyra 2012). With urbanization comes a loss of
natural habitats – especially tree cover – and increase in impervious
surfaces, of low value to biodiversity (Nowak and Greenfield 2020). Thus
urbanization generally correlates to losses in biodiversity (McDonald,
Güneralp, Huang, Seto and You 2018, van Vliet 2019). However, many
anthrophilic species continue to coexist with humans in urban
environments (Magle, Hunt, Vernon and Crooks 2012, Møller 2012) and
there is sustained advocacy, research, and planning for urban areas that
promote wildlife-human coexistence (Apfelbeck, Snep, Hauck, Ferguson,
Holy, Jakoby, Scott MacIvor, Schär, Taylor and Weisser 2020, Larson,
Lerman, Nelson, Narango, Wheeler, Groffman, Hall and Grove 2022).
Although urban wildlife ecology as a discipline was advocated by Aldo
Leopold in the 1930s it remains markedly understudied in academia (Adams
2005). The biodiversity outcomes of urban development have been varied,
from local extirpation of undesirable species such as predators
(McCance, Decker, Colturi, Baydack, Siemer, Curtis and Eason 2017) to
multi-taxic rapid phenotypic changes in urban centers, implicating
urbanization as a mode of evolutionary change (Alberti, Correa,
Marzluff, Hendry, Palkovacs, Gotanda, Hunt, Apgar and Zhou 2017). In
summary species’ responses vary within and among cities and
contextualizing the mechanisms behind responses remains a key endeavor
(Magle, Hunt, Vernon and Crooks 2012, McDonald, Mansur, Ascensão,
Crossman, Elmqvist, Gonzalez, Güneralp, Haase, Hamann and Hillel 2020,
Seto, Güneralp and Hutyra 2012).
We know that globally, large carnivores are one of the first groups
extirpated, as we seek to “make safe” urban places for humans. One of
the outcomes of extirpating large carnivores from urban environments is
providing prey species with refugia from predation (Gallo, Fidino,
Lehrer and Magle 2019, Møller 2012), often combined with substantial
foraging subsidies for browsing and grazing herbivores (DeStefano and
DeGraaf 2003). These anthropogenic changes to landscapes and wildlife
communities have led to the perception of an “urban deer
(Odocoileus spp .) problem” (Bowman 2011, Conover 1995, Rondeau
and Conrad 2003) in wildlife management. Fifty-four percent of the
world’s population lives in urban areas and is expected to increase to
66% by 2050 (Soulsbury & White 2019). Within cities, low-medium
density housing areas the highest likelihood of urban wildlife
interactions due to high species richness and low species extinction
rates (Magle et al. 2016) and the greatest areas of greenspace and
diversity of landcover (Loram et al. 2007). Yet people living within
these low-medium density housing tend to react most negatively to
human-wildlife conflict (Wine et al. 2015).
More than a problem however, urban wildlife is an unplanned scientific
experiment that allows us to examine the roles of different forms of
landscape heterogeneity on species’ space-use and resource selection.
Urban areas are complex mosaics of impervious surfaces (buildings,
roads, parking lots), natural or semi-natural greenspaces (parks), and
heavily modified greenspaces (yards, gardens, golf courses), each
offering different resources and risks for different species. Those
resources are the outcome of social and economic drivers within the
human population (Belaire, Westphal and Minor 2016).
One interesting outcome observed in urban ecology is the “luxury
effect” wherein differences in affluence among neighborhoods generates
differences in biodiversity. Evidence for a luxury effect dates back
thousands of years, arising from Egyptian archaeological records, and
continue through the Anthropocene (Leong, Dunn and Trautwein 2018). The
luxury effect spans spatial scales, occurring both within and among
cities (Magle, Lehrer and Fidino 2016), albeit inconsistently. Among 20
North American cities studied (Magle, Fidino, Lehrer, Gallo, Mulligan,
Ríos, Ahlers, Angstmann, Belaire and Dugelby 2019) per capita income
played a role in explaining vertebrate diversity in half; instead
species richness was highly (negatively) correlated with urban intensity
(Magle, Fidino, Sander, Rohnke, Larson, Gallo, Kay, Lehrer, Murray and
Adalsteinsson 2021). Affluence is thus a proxy measure for biological
properties associated with rich neighborhoods (Magle, Fidino, Sander,
Rohnke, Larson, Gallo, Kay, Lehrer, Murray and Adalsteinsson 2021): low
human density, energy subsidy, and especially greenness. Indeed the
luxury effect is generally amplified in arid environments (Leong, Dunn
and Trautwein 2018).
Most research on luxury effect uses species richness of plant or animal
assemblages as the metric. For large mammals, individual behavior is a
key mechanism explaining response to urban development (Honda, Iijima,
Tsuboi and Uchida 2018), so we examine luxury effect from this different
angle. We examine resource selection by highly abundant urban
black-tailed deer (Odocoileus hemionus columbianus ; deer), a
native to the western Nearctic including the Canadian province of
British Columbia (BC). They are important prey for BC’s diverse
carnivore population (Ballard, Lutz, Keegan, Carpenter and deVos Jr
2001) but the changing landscape has led to abundant urban deer
populations. Predator persecution is an obvious culprit, but we suspect
landscape change is an important driver. Deer select high-energy and
high-nutrient plants as forage (Weckerly 1994) and are very sensitive to
factors affecting the recruitment of young deer into the breeding
population (Forrester and Wittmer 2013, Gilbert and Raedeke 2004). The
abundant backyard gardens of urban and suburban areas in affluent
neighborhoods (Larson, Lerman, Nelson, Narango, Wheeler, Groffman, Hall
and Grove 2022) provide ample deer food, potentially allowing deer to
breed more often and more successfully than in ‘natural’ (non-urban)
landscapes.
However, even in natural systems the trade-off between security from
predation and food resources is not well understood (Bowyer, Kie and Van
Ballenberghe 1998), so how deer perceive risk in urban areas – and how
they capitalize upon potential resource subsidies – remains unknown.
Urban environments have been shown to impact wildlife behaviour,
resulting in unique adaptations that differ from their non-urban
counterparts (Schell, Stanton, Young, Angeloni, Lambert, Breck and
Murray 2021, Wright, Adams, Stent and Ford 2020). Similarly animal
behaviour and personalities influence the efficacy of behavioural tools
for urban wildlife management such as hazing deterrents and culls
(Honda, Iijima, Tsuboi and Uchida 2018). A better understanding of urban
deer resource selection, avoidance, and spatial landscape use would help
determine if the luxury effect is impacting individual deer behavioural,
and if so, what are some of the proximal mechanisms for this effect.
This information is also an important tool for suburban deer management,
both in terms of minimizing the impacts on wildlife population processes
as well as negative human-wildlife interactions (Klees van Bommel et al.
2020).
We quantified deer locations via satellite telemetry collars and
estimated home-range sizes to better understand urban deer habitat
selection. To evaluate our hypotheses about the luxury effect, we
used resource selection function (RSF) analyses to make inferences about
how deer use different landcover features (Boyce and McDonald 1999,
Seidel, Dougherty, Carlson and Getz 2018). RSFs have been used
extensively to assess animal movement patterns, response to novel
anthropogenic features, and identify movement pathways (Abrahms, Sawyer,
Jordan, McNutt, Wilson and Brashares 2017, Anderson, Turner, Forester,
Zhu, Boyce, Beyer and Stowell 2005, Chetkiewicz and Boyce 2009,
Darlington, Ladle, Burton, Volpe and Fisher 2022, Laforge, Brook, van
Beest, Bayne and McLoughlin 2016, Stewart, Darlington, Volpe, McAdie and
Fisher 2019). We examined the role of (1) vegetation productivity and
tree cover, (2) residential lot size, (3) road density, (4) golf courses
and public green spaces, and combinations thereof. We included variables
measuring these features in a generalized linear model and examined
effect sizes (β coefficients). We hypothesized that if the luxury effect
was apparent, then residential lot size would show the significantly
positive effect size. We also predicted that road density was a risk
deer avoided, and that native (parks) and non-native (golf courses)
forage sources would be selected, but with smaller effect sizes.