Territoriality drives preemptive habitat selection in recovering wolves: Implications for carnivore conservation

Abstract

1. According to the ideal-free distribution (IFD), individuals within a population are free to select habitats that maximize their chances of success. Assuming knowledge of habitat quality, the IFD predicts that average fitness will be approximately equal among individuals and between habitats, while density varies, implying that habitat selection will be density dependent. Populations are often assumed to follow an IFD, although this assumption is rarely tested with empirical data, and may be incorrect when territoriality indicates habitat selection tactics that deviate from the IFD (e.g. ideal-despotic distribution or ideal-preemptive distribution).2. When territoriality influences habitat selection, species' density will not directly reflect components of fitness such as reproductive success or survival. In such cases, assuming an IFD can lead to false conclusions about habitat quality. We tested theoretical models of density-dependent habitat selection on a species known to exhibit territorial behaviour in order to determine whether commonly applied habitat models are appropriate under these circumstances.3. We combined long-term radiotelemetry and census data from grey wolves Canis lupus in the Upper Peninsula of Michigan, USA to relate spatiotemporal variability in wolf density to underlying classifications of habitat within a hierarchical state-space modelling framework. We then iteratively applied isodar analysis to evaluate which distribution of habitat selection best described this recolonizing wolf population. 4. The wolf population in our study expanded by >1,000% during our study (~50 to >600 individuals), and density-dependent habitat selection was most consistent with the ideal-preemptive distribution, as opposed to the ideal-free or idealdespotic alternatives. Population density of terrestrial carnivores may not be positively correlated withthe fitness value of their habitats, and density-dependent habitat selection patterns may help to explain complex predator-prey dynamics and cascading indirect effects. Source-sink population dynamics appear likely when species exhibit rapid growth and occupy interspersed habitats of contrasting quality. These conditions are likely and have implications for large carnivores in many systems, such as areas in North America and Europe where large predator species are currently recolonizing their former ranges.

Patterns and processes of pathogen exposure in gray wolves across North America

“…Habitat quality was a proxy for the presence of carnivore hosts, and was a continuous variable calculated as the product of: percent forest cover 53 , percent area with slope ≤ 20° 54 , and density of hard edges (e.g., cutblocks, pipeline cuts, forest edges; R package landscapemetrics 55 ). These habitat characteristics were selected because they were considered positive predictors of carnivore presence, such as grizzly bears, lynx, bobcat, coyotes, with a focus on wolves [56][57][58][59][60][61][62][63][64][65][66][67][68] . While this proxy for carnivore presence is imperfect as carnivore distributions varied over our sampling distribution, and carnivores may select for different landscape features at different scales, it captures important features where wolves and other carnivores may interact, and therefore where cross-species pathogen transmission may occur.…”

Habitat selection patterns are density dependent under the ideal free distribution

“…Emerging remote‐sensing technologies, such as wildlife cameras and drones, could enhance our capacity to obtain such complex data. Once obtained, these estimates could be incorporated into more appropriate forms of statistical analysis where context dependency could be adequately controlled for (Holbrook et al., 2019; Matthiopoulos et al., 2011; O'Neil et al., 2020). On the other hand, if empirical patterns of density‐dependent habitat selection prove as extreme and variable as the theoretical patterns shown here, statistical adjustments alone may fall short of improving model transferability (Radchuk et al., 2019; Yates et al., 2018).…”

“…It is nonetheless difficult to see how relaxing this assumption to accommodate more realistic behaviour would counteract our qualitative predictions. For example, the added behavioural complexity of territoriality should result in even stronger density dependencies (O'Neil et al., 2020). Secondly, by considering only unidimensional differences between habitats, we have assumed that there is no spatial correlation across different habitat dimensions (e.g.…”

“…On the other hand, it is commonly assumed that relative differences in intrinsic quality among different habitats never vary, that is, the within‐habitat rate of density‐dependent decline in fitness is constant. Consequently, the relative density (distribution) of IFD consumers distributed among occupied habitats is expected to be independent of total consumer abundance (Falcy, 2015; Kacelnik et al., 1992; Lessells, 1995; McLoughlin et al., 2010; Morris, 1988; O'Neil et al., 2020). Hence, whether the classical IFD model results in density‐dependent habitat selection patterns rests on one's frame of reference, as well as on the definitions of ‘distribution’ and ‘selection’ (Matthiopoulos et al., 2015).…”

“…expend their space use to include habitats of lower quality; see further discussion in the next section). This relationship is termed ‘negative density‐dependent habitat selection’, and has been empirically documented in a variety of species and systems (Bledsoe & Ernest, 2019; Falcy, 2015; McLoughlin et al., 2010; Morris, 1988; O'Neil et al., 2020; Paterson & Blouin‐Demers, 2018; Rosenzweig, 1981, 1991; Shepherd & Litvak, 2004; Sundell et al., 2012; van Beest, McLoughlin, et al., 2014; van Beest, Uzal, et al., 2014). Nevertheless, consideration of population‐density effects is mostly absent in the empirical habitat selection literature.…”