Human presence and human footprint have non-equivalent effects on wildlife spatiotemporal habitat use
Introduction
The expanding influence of humans has greatly impacted wildlife by disrupting the distribution and activity patterns of animals globally (Dirzo et al., 2014; Gaynor et al., 2018; Tucker et al., 2018). The increasing human footprint on the landscape (i.e., urbanization, land use change) is a key threat to wildlife across virtually all taxonomic groups, not only through habitat loss and fragmentation (Hansen et al., 2005; Fischer and Lindenmayer, 2007), but also because urbanized areas represent concentrations of anthropogenic “disturbance” (i.e., real or perceived threats that elicit antipredator responses (Frid and Dill, 2002)), which may be actively avoided by wildlife. However, human impacts are not restricted to developed areas only, as the mere presence of humans has been shown to impact wildlife behavior and activity even in wildland areas (Suraci et al., 2019a). The latter is particularly salient given the rapid expansion of outdoor recreation into previously undisturbed landscapes (Cordell et al., 2008) and its potential negative effect on many wildlife species (Larson et al., 2016).
Wildlife species respond to human activities in complex ways, ranging from acute behavioral changes to chronic distributional effects, which may depend on the type, intensity, and frequency of disturbance (Larson et al., 2016; Tablado and Jenni, 2017; Gaynor et al., 2018; Tucker et al., 2018). Humans are a major source of mortality for many wildlife species, particularly mammalian predators (Darimont et al., 2015), and recent experimental work confirms that many species therefore exhibit strong fear responses to human presence (Clinchy et al., 2016; Smith et al., 2017; Suraci et al., 2019a). The fear induced by human presence has correspondingly been shown to affect behavior and activity patterns of wildlife at the landscape scale (Suraci et al., 2019a), and fear may therefore mediate many of the impacts associated with recreational activity in wildland areas (Larson et al., 2016; Tablado and Jenni, 2017). When compared to the relatively transient presence (and associated fear) of humans in wildlife habitat (e.g., during recreation), sustained and high-intensity disturbance associated with long-term land use changes (e.g., housing developments) may be expected to exert even greater impacts on wildlife habitat use. Yet many synanthropic species (e.g., mesopredators like striped skunks, Mephitis mephitis, and Virginia opossums, Didelphis virginiana) appear to benefit from increased human footprint on the landscape, taking advantage of resource subsidies such as food waste (Ordeñana et al., 2010; Wang et al., 2015) and/or decreased risk from other predators where human activity is high (Muhly et al., 2011). Indeed, multiple anthropogenic influences may simultaneously affect wildlife, potentially in opposition, if for instance some species avoid risky interactions with people but take advantage of human infrastructure or resources (Beckmann and Berger, 2003; Bateman and Fleming, 2012; Suraci et al., 2019a).
An animal's response to a particular anthropogenic disturbance may additionally depend upon the relative constancy or regularity of the disturbance type in space and time and thus the animal's ability to predict when and where potential threats from humans are likely to occur. Predator-prey theory suggests that long-term, consistent spatial variation in risk should lead to outright avoidance and thus changes in prey space use (e.g., the “risky places hypothesis”) (Creel et al., 2008; Dröge et al., 2017). Alternatively, predation risk that is more spatially variable but exhibits regular temporal fluctuations (e.g., due to the predator's daily activity cycle; Kohl et al., 2018) may lead to temporal partitioning, where prey avoid predators in time by increasing activity at times of day when the predator is less active (Suraci et al., 2019b). Thus, it is possible that human development as a long-term, spatially constant source of risk may be more likely to induce spatial displacement and altered habitat use for wildlife species (i.e., avoidance of risky places) (Frid and Dill, 2002; Tucker et al., 2018), while human presence in wildlife habitat, which is less constant and largely restricted to diurnal periods, may prompt shifts in temporal activity (Gaynor et al., 2018).
Despite ample reason to expect that human footprint and human presence will differ in their impacts on wildlife behavior and habitat use, ambiguity exists in how wildlife species respond to these two categories of anthropogenic disturbance. One reason for such ambiguity is that human footprint is often used as a proxy for multiple forms of anthropogenic disturbance, due in part to the ease of acquiring landscape level data on, e.g., land cover, human population density, and built infrastructure (Venter et al., 2016). However, such variables may be poor predictors of human presence across the landscape, particularly in wildland areas where outdoor recreation is growing (Cordell et al., 2008; Balmford et al., 2015). Using the human footprint as a proxy for human presence may therefore conflate the effects of different types of human disturbance on wildlife (Tablado and Jenni, 2017). However, measuring the spatial extent of human presence outside of developed areas, and thus the area over which human activity is likely to impact wildlife, remains a challenge. Studies of human presence in wildland areas typically rely on the localized deployment of sensors (e.g., camera traps) in the environment, a site-specific approach that may not be representative of landscape-scale patterns of human presence (Larson et al., 2016; Gutzwiller et al., 2017) and may therefore overlook human disturbance and its impacts in parts of the landscape not directly covered by camera trapping surveys (Monz et al., 2013). Thus, there is a need to predict human presence in wildland areas from readily available landscape-level variables, allowing estimation of broad-scale spatial patterns of human activity and associated impacts on wildlife beyond sites at which on-the-ground surveys have been conducted (Ladle et al., 2017).
Here we use a network of camera-traps deployed across a gradient of human recreational use and development in the Santa Cruz Mountains of California to quantify the effects of both human footprint (building density) and actual human presence (occurrence of people on camera traps) on wildlife behavior and habitat use. We then model where and when the observed impacts of human presence are likely to be greatest on the landscape using a suite of spatial predictors of human activity. We focus our analyses on large and medium-sized mammalian predators, which experience the highest per capita risk of human-caused mortality (Darimont et al., 2015) and are correspondingly known to exhibit strong behavioral responses to the immediate presence of people (Clinchy et al., 2016; Smith et al., 2017; Suraci et al., 2019a), but which also represent a range of responses to human development, from reclusive large carnivores to synanthropic mesopredators. This work was conducted in areas of the Santa Cruz Mountains ranging from undeveloped tracts of forest to moderately developed rural and exurban areas, thus typifying the mosaic of wildlife habitat and human development characteristic of the wildland-urban interface (WUI) (Radeloff et al., 2005, Radeloff et al., 2010).
Section snippets
Study area
The Santa Cruz Mountains (37° 10′ N, 122° 3′ W) encompass a diverse landscape comprised of large tracts of relatively undisturbed native vegetation intermixed with low- and intermediate-density development that are surrounded by heavily developed areas along the fringe. One-third of the landscape falls within the wildland-urban interface (Martinuzzi et al., 2015) with a substantial portion of more remote public lands being available for recreational activities (e.g., biking, hiking, dog
Effects of human presence and human footprint on wildlife habitat use
Our multi-species occupancy models revealed that human presence and human footprint are not equivalent in their effects on wildlife habitat use (Fig. 2, Tables S1 and S2), with the magnitude and sign of the effect of each human disturbance type varying substantially between species. Both human presence and human footprint models exhibited successful convergence ( < 1.1 for all model terms) and excellent fit (Bayesian p-values: 0.445 ≤ p ≤ 0.499). Several species exhibited a positive
Discussion
Although a growing body of research demonstrates that both human footprint and human presence (including recreation) can have negative impacts on wildlife (Larson et al., 2016; Gaynor et al., 2018; Tucker et al., 2018), studies aimed at disentangling the concurrent effect of both forms of disturbance on wildlife behavior are surprisingly rare. Our results demonstrate that human presence and human footprint have differing, and in some cases opposite, effects on wildlife habitat use and activity
CRediT authorship contribution statement
Barry A. Nickel: Conceptualization, Methodology, Formal analysis, Writing - original draft, Visualization. Justin P. Suraci: Conceptualization, Methodology, Formal analysis, Writing - original draft, Visualization. Maximilian L. Allen: Conceptualization, Methodology, Investigation, Writing - review & editing. Christopher C. Wilmers: Conceptualization, Methodology, Writing - review & editing, Project administration, Funding acquisition.
Acknowledgements
We thank P. Houghtaling, R. King, and K. Briner for help in the field, A. Nisi for data management assistances, and multiple undergraduate volunteers for help scoring camera trap images. We are grateful to the many Santa Cruz Mountains property owners who provided access to their land. Funding was provided by the Gordon and Betty Moore Foundation, National Science Foundation (grants 1255913 and 0963022 to CCW), the Blue Foundation, Peninsula Open Space Trust and Resources Legacy Fund.
Role of funding sources
None of the funding sources played any role in study design; in the collection, analysis, and interpretation of data; in the writing of the report; or in the decision to submit the paper for publication.
Declaration of competing interest
The authors have no conflicts of interest to declare. None of the funding sources played any role in study design; in the collection, analysis, and interpretation of data; in the writing of the report; or in the decision to submit the paper for publication.
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These authors contributed equally.