PeerJ Inc.
Fear and stressing in predator–prey ecology: considering the twin stressors of predators and people on mammals
Volume: 8
DOI 10.7717/peerj.9104
  • PDF   
  • XML   

Predators induce stress in prey and can have beneficial effects in ecosystems, but can also have negative effects on biodiversity if they are overabundant or have been introduced. The growth of human populations is, at the same time, causing degradation of natural habitats and increasing interaction rates of humans with wildlife, such that conservation management routinely considers the effects of human disturbance as tantamount to or surpassing those of predators. The need to simultaneously manage both of these threats is particularly acute in urban areas that are, increasingly, being recognized as global hotspots of wildlife activity. Pressures from altered predator–prey interactions and human activity may each initiate fear responses in prey species above those that are triggered by natural stressors in ecosystems. If fear responses are experienced by prey at elevated levels, on top of responses to multiple environmental stressors, chronic stress impacts may occur. Despite common knowledge of the negative effects of stress, however, it is rare that stress management is considered in conservation, except in intensive ex situ situations such as in captive breeding facilities or zoos. We propose that mitigation of stress impacts on wildlife is crucial for preserving biodiversity, especially as the value of habitats within urban areas increases. As such, we highlight the need for future studies to consider fear and stress in predator–prey ecology to preserve both biodiversity and ecosystem functioning, especially in areas where human disturbance occurs. We suggest, in particular, that non-invasive in situ investigations of endocrinology and ethology be partnered in conservation planning with surveys of habitat resources to incorporate and reduce the effects of fear and stress on wildlife.

Fardell, Pavey, Dickman, and Lambert: Fear and stressing in predator–prey ecology: considering the twin stressors of predators and people on mammals


Predators in many systems positively influence the local distribution and abundance of their prey (Polis et al., 1998; Ayal, 2007; Estes et al., 2011; Weissburg, Smee & Ferner, 2014), and indirectly but positively influence the functioning of whole ecosystems via trophic cascades (Prugh et al., 2009; Ritchie & Johnson, 2009; Estes et al., 2011; Ripple et al., 2014). Predators often elicit fear responses in prey that affect prey behaviour, energy budgets and the way they interact with the environment (Brown & Kotler, 2004; Clinchy et al., 2004; Romero, 2004). For example, the fear response of an individual of a prey species to a predator may be to change the locations or times in which they forage, which can have positive impacts on the structure of the environment (Laundré, Hernández & Ripple, 2010). Such fear responses can in turn influence ecosystem function (Schmitz, Krivan & Ovadia, 2004, Schmitz, Beckerman & O’Brien, 1997, Hawlena et al., 2012). These effects arise due to the ‘landscape of fear’ that prey individuals perceive—that is the spatial distribution of perceived predation risk that influences prey movement and behaviour as prey individuals attempt to mitigate risk and obtain essential resources (Laundré, Hernández & Altendorf, 2001; Laundré, Hernández & Ripple, 2010).

Recent studies suggest that the effects of predators are being altered, and often amplified, by human activities. For example, the demise of top predators in many parts of the world has ‘released’ populations of smaller predators, or mesopredators that have since become overabundant and now exert strong pressure on smaller species (Prugh et al., 2009). Predators that have been introduced to new areas also exert much stronger pressure on prey populations than do native predators (Salo et al., 2007). Climate change and associated shifts in primary productivity can also have bottom-up impacts on predator–prey interactions (Laws, 2017). Such novel alterations to predator–prey dynamics can depress prey populations and disrupt community structure, and as such require novel approaches to recognize and manage their effects (Carthey & Blumstein, 2018; Fleming & Bateman, 2018; Guiden et al., 2019).

Altered predator–prey interactions may contribute to declines in biodiversity, but a primary cause of biodiversity loss is the rapid global increase in human populations, driving agricultural, industrial, and urban expansions that change or destroy natural habitats (Madsen, Carroll & Moore Brands, 2010). Such expansions are resulting in novel human–wildlife interactions and secondary impacts that arise from human activities in close proximity to natural environments, and thus increasingly are becoming an additional stressor that influences ecosystem function. Pressures exerted both directly and indirectly by human activities have been likened to the pressures exerted by the presence of a top predator on prey (Frid & Dill, 2002; Rehnus, Wehrle & Palme, 2014; Patten & Burger, 2018). Natural predation pressures coupled with human-imposed predation-like pressures and/or additional exogenous stressors, such as pollution, arising from anthropogenic activities are likely to negatively affect prey species by increasing their levels or frequency of stress. Current research is developing a more nuanced understanding of the effects of human activity and predator presence on the stress of prey (Arlettaz et al., 2015; Jaatinen, Seltmann & Öst, 2014, respectively). However, few studies in terrestrial ecosystems have considered both of these pressures simultaneously or have linked behavioural responses with endocrinological evidence of stress. In one instructive recent study, human activity was shown to be positively correlated with physiological stress in ungulates, whilst in areas occupied by large predators stress was found to be lower and less variable (Zbyryt et al., 2017).

Conservation management and associated scientific research is often viewed from the perspective of a single discipline. However, ecological changes arising from anthropogenic disturbances, including the alteration of predator–prey encounter rates, creation of novel species interactions (including between people and wildlife), introduction of novel species, and the alteration of natural habitats, call for multidisciplinary solutions. This is particularly pertinent as urban edge habitats are becoming increasingly valuable global hotspots of wildlife activity (Ives et al., 2016), and human influences are spreading further into natural habitats (Otto, 2018). There is growing evidence that multiple introduced stressors (e.g. altered predator–prey interactions and disturbance from humans) can have compounding impacts on wildlife, especially when interacting with natural stressors in ecosystems (Geary et al., 2019). For these reasons, it is timely to review relevant information from the broad knowledge bases of conservation physiology, ethology, and ecology to communicate the urgent need for wildlife managers and urban planners to routinely consider how fear and stress effects from multiple sources, particularly novel predator interactions and human activities, can affect prey species and ecosystem functioning in increasingly altered systems. Our focus in this review is on mammals because of the wealth of information on this group, but we note relevant studies from other groups where appropriate. We begin our review by describing physiological responses of mammals to fear and stress, then we consider the behavioural responses of mammals to these factors, and argue that human activity should be considered as part of the ecosystem so that overall stress impacts can be managed accordingly. We then demonstrate how fear and stress can influence habitat use, how vegetation and microhabitat management potentially may be used to alleviate stress, and how to monitor for fear and stress to then create management change. Finally, we use Australia as an example to show the benefits of considering cumulative fear and stress impacts to mitigate the effects of introduced eutherian predators, increased human activity, and the possible interactive effects of the two.

Review Method

This is not a systematic review, but rather a novel synthesis of existing knowledge. It seeks to extend ideas on the physiological impacts of fear and stress, behavioural ecology, predator–prey dynamics, and conservation management to explore the influence of humans and altered predator–prey interactions in the urban environment. To ensure that all key topic areas were thoroughly covered we conducted literature searches via: Google Scholar©, Web of Science©, JSTOR© and Wiley Interscience Online Library©. Manuscripts were mined for information relevant to wildlife fear and stress in terms of ecological management under anthropogenic pressures, including introduced predators and altered predator–prey interactions. The literature searches were undertaken using the following key terms as part of their title, keywords, and/or within the abstract: ‘acute stress,’ ‘chronic stress,’ ‘homeostasis,’ ‘cumulative stress,’ ‘multiple stressors,’ ‘multiple threats,’ ‘allostatic load,’ ‘allostatic overload,’ ‘acclimitisation,’ ‘glucocorticoid response,’ ‘hypothalamic pituitary adrenal axis,’ ‘fear arousal,’ ‘fear evolution,’ ‘fear predation,’ ‘amygdala’ ‘fear,’ ‘Pavlovian fear conditioning,’ ‘glucocorticoid assay,’ ‘f(a)ecal glucocorticoid,’ ‘non-invasive glucocorticoid assay,’ ‘reactive scope model,’ ‘landscape(s) of fear,’ ‘risk allocation hypothesis,’ ‘olfaction’ + ‘fear’ + ‘mammal,’ ‘post-traumatic stress disorder,’ ‘predator’ + ‘odo(u)r’ + ‘fear,’ ‘predator cue(s),’ ‘predation stress hypothesis,’ ‘predator-sensitive food hypothesis,’ ‘human activity’ + ‘stress’ + ‘wildlife,’ ‘human disturbance,’ ‘interactive stress,’ ‘multiple stress(ors),’ ‘additive stress impacts,’ ‘synergistic stress impacts,’ ‘antagonistic stress impacts,’ ‘human’ + ‘wildlife’ + ‘resource subsidies,’ ‘predator trophic cascade,’ ‘wildlife urban adaptation,’ ‘urban ecology’ + ‘wildlife,’ ‘Australian mammal extinction,’ ‘critical weight range mammal,’ ‘diet’ + ‘change’ + ‘Australian’ + ‘predator,’ ‘red fox’ + ‘Australia,’ ‘domestic cat’ + ‘Australia,’ ‘human activity’ + ‘wildlife’ + ‘Australia,’ ‘Australia’ + ‘biodiversity’ + ‘conservation policy’ + ‘urban hotspot,’ ‘Australian environment protection and biodiversity conservation act’ + ‘cumulative stress,’ ‘Australia’ + ‘conservation’ + ‘glucocorticoids,’ ‘introduced predator control,’ ‘habitat structural complexity,’ ‘habitat structural diversity,’ ‘vegetation diversity,’ ‘vegetation heterogeneity,’ ‘habitat heterogeneity hypothesis,’ ‘cumulative effects assessments.’ Supplementary articles supporting the review narrative, suggested by reviewers on earlier versions of the manuscript, have also been included.

Mammalian Physiological Responses to Fear and Stress

Physiological stress can be broadly defined as a change in the physiological well-being of an individual following exposure to an aversive extrinsic stimulus—frequently referred to as a stressor (Selye, 1936). The physiological stress response that follows aims to restore internal homeostasis (Cannon, 1932). An individual animal experiences stress in response to conditions that threaten its survival or compromise its ability to maintain homeostasis. Examples include acute or chronic encounters with predators, inclement weather, significant natural disturbances including fire and flood, reduced oxygen availability and depleted food resources (Lima, 1998; King & Bradshaw, 2010; Malcolm et al., 2014; Santos et al., 2014; Crocker, Khudyakov & Champagne, 2016).

In mammals, activation of the hypothalamic-pituitary-adrenal (HPA) axis is a common stress response, but this may vary depending on the nature of the stressor (Mason, 1971); it is important to consider this when assessing stress impacts. Changes in abiotic conditions, such as in food availability, or the introduction of toxins or diseases can be stressful, but such changes do not arouse fear. However, a stress response involving peripheral autonomic and neuroendocrine changes (Yates, Russell & Maran, 1971; Sapolsky, Romero & Munck, 2000; McEwen & Wingfield, 2003), can be initiated by fear arousal (LeDoux, 2003; Labar & Ledoux, 2011). Animals with sophisticated nervous systems, such as mammals, exhibit a central motive state between threat stimulus and response that is driven by the amygdala (Pitkanen, 2000) and can be identified as ‘fear’ (Mineka, 1979; Öhman, 2000). Fear has been defined as a psychological state that triggers physiological responses to avoid or escape from a stressor (Epstein, 1972; LeDoux, 1996). The development of successful defense mechanisms to fear-inducing stressors has clear survival benefits for animals, and thus fear can be seen as a driver of evolutionary adaptations (Tooby & Cosmides, 1990). Common strategies of escape and avoidance allow animals to cope with recurrent stressors, such as the fear-inducing threat of predation (Lima & Dill, 1990).

The sections of the mammalian amygdala associated with fear behaviour serve as an interface between sensory input and information transport and processing, endocrine response, and motor output (Davis & Whalen, 2001). These interactions are associated with learning and memory via the involvement of the lateral and basal nuclei, as demonstrated on captive rodents using neurotoxic lesions on the basal and lateral nuclei of the amygdala (Wallace & Rosen, 2001), and are evident in Pavlovian fear conditioning paradigms (Davis, 1992; Maren, 2001). Activation of hormones, specifically glucocorticoids and norepinephrine in stress responses initiated by fear arousal provides feedback to the brain that influences emotion control and cognition, which contributes to fear conditioning (Rodrigues, LeDoux & Sapolsky, 2009). Fear responses may, therefore, be both conditioned as aversive learnt behaviours (Fanselow & Poulos, 2005), and unconditioned as innate freezing responses (e.g. Schulkin, Thompson & Rosen, 2003).

Given that fear motivates a stress response—initiating the freeze, and fight or flight actions—quantifying glucocorticoid outputs from the autonomic nervous and HPA systems should yield a measurable indication of fear from predation as a stressor. Minimally invasive techniques are available that assay glucocorticoid levels in faeces, fur, or feathers (Sheriff et al., 2011; Cook, 2012; Palme, 2019). Using minimally invasive methods to measure glucocorticoid levels in the wild does not necessarily yield an isolated ‘output’ of a fear or predator/human-induced stress response (Rosen & Schulkin, 2004). This situation results from glucocorticoids not being a molecule of fear per se but having a fundamental role in maintaining energy balance (Rosen & Schulkin, 2004). As such, glucocorticoids may change not just because of fear but also in response to other exogenous stressors, like food shortage (McEwen & Wingfield, 2003). Nevertheless, such methods could usefully compare longer-term stress responses among habitats or along disturbance gradients with variable exposure to predators, by following experimental designs that are considerate of additional stressors that may be present (MacDougall-Shackleton et al., 2019).

If two or more stressors are present, the resultant combined stress may present severe challenges to an individual’s physiological systems (Johnstone, Lill & Reina, 2012; Brearley et al., 2013; Malcolm et al., 2014; Arlettaz et al., 2015; Geary et al., 2019; Legge et al., 2019). Interactive fear and stress effects are context-dependent (Belarde & Railsback, 2016). They can be additive and combine the multiple impacts, synergistic whereby the presence of one threat amplifies another (Doherty et al., 2015), or antagonistic whereby one threat cancels the effects of the other. A reduction in the activity of mesopredators in the presence of humans provides an example of antagonism (Clinchy et al., 2016). Additive, synergistic, and antagonistic reactions have each been observed in mammalian prey in natural systems in response to exposure to multiple stressors (Crain, Kroeker & Halpern, 2008; Côté, Darling & Brown, 2016; Gunderson, Armstrong & Stillman, 2016; Jackson et al., 2016; Geary et al., 2019; Legge et al., 2019).

Exposure to a stressor(s) that is prolonged, constant, or recurring can have chronic impacts, as recovery from a stressor cannot occur whilst the threat remains (Sapolsky, Romero & Munck, 2000). Acute stress occurs as the initial response to a threat to sustain fitness in the short term; it subsides once the responding action—be it freezing, fighting, or fleeing—diminishes the threat (Wingfield & Kitaysky, 2002). Activation of the HPA axis in an acute stress response has rapid effects that increase immune system function, energise muscles via enhanced cardiovascular tone, and heighten cognition, including memory (Sapolsky, Romero & Munck, 2000). These responses occur via increased cerebral perfusion rates and use of glucose, all of which come at the cost of decreased appetite and reproductive behaviours (Sapolsky, Romero & Munck, 2000). Effectively, the acute stress response suspends non-essential behaviours in favour of altered behaviours that minimize the threat (Wingfield & Kitaysky, 2002).

Continued exposure to a stressor, or stressors, creates a state of chronic stress, which is classically described as allostatic overload (Dantzer et al., 2014). Allostatic load describes the body’s ability to maintain homeostasis in response to a stressor (Sterling & Eyer, 1988; McEwen & Stellar, 1993; McEwen & Wingfield, 2003). Allostatic overload, by extension, refers to the inability to maintain homeostasis and thus an organism’s increased susceptibility to external stressors (Sterling & Eyer, 1988; McEwen & Stellar, 1993; McEwen & Wingfield, 2003). Chronic stress reduces an organism’s resilience to future stressors by inducing extended behavioural changes in feeding, fighting, and mating (Mineur, Belzung & Crusio, 2006). Chronic stress also affects an organism’s physiological state by suppressing or impairing the reproductive system and decreasing physiological resistance to pathogens and toxins through the suppression of immune function (Dhabhar & McEwen, 1999; McEwen & Wingfield, 2003; Romero, 2004; Travers et al., 2010; Feng et al., 2012). Repeated exposure to a stressor can have population and community level consequences as homeostasis is compromised, and it increases susceptibility to additional stressors and can have flow-on effects. For example chronic risk of predation, which facilitates changes in nutrient demand for prey species and thus changes in the elemental composition of their excreta, can alter nutrient cycling in the community and ecosystem (Hawlena & Schmitz, 2010).

Cases of acclimatisation to chronic or repeated acute stressors have been observed, although the process often results in enhanced activation of the HPA axis to novel stressors, and thus may not be beneficial to fitness (Romero, 2004). Instead of acclimatising to a chronic or repeated stressor, glucocorticoid levels can remain the same, or become chronically elevated, or the HPA axis can shut down completely and render an animal vulnerable to future threats (Romero, 2004). Physiological impairment of the neurological, cardiovascular and musculoskeletal systems may also result from chronic stress: neurons of the brain can atrophy and impair memory, or grow and enhance fearfulness with extensive releases of adrenaline and cortisol (Roozendaal, 2000; McEwen, 2004); atherosclerotic plaques also may form and impede blood flow from repeated elevation of blood pressure (Manuck et al., 1988), and skeletal muscle can suffer severe protein loss (Wingfield & Kitaysky, 2002).

Although chronic and acute stress responses have been well defined for mammals in laboratory studies, results from in situ studies show that reactions vary with the stressor type that animals are exposed to, as well as habituation potential, food availability, social interactions, and density (Dickens & Romero, 2013). In situ mammalian endocrine responses to a consistent stressor, such as human activity, have not been studied sufficiently to be able to determine if there is a particular pattern of response. Avian endocrine responses to such stressors have been more extensively studied and they reveal that urban habitats, perceived as a consistent stressor, can shape endocrine responses in birds. However, a consistent stress response pattern has yet to be observed in birds (Bonier, 2012). Inconsistent behavioural responses of mammals and other animals to human activities that are often observed can perhaps be linked to modulating factors such as the level of human activity, the species and condition of the animal being observed, and the spatio-temporal context (Tablado & Jenni, 2017).

Mammalian Behavioural Responses to Fear and Stress: The Landscape of Fear Concept

The landscape of fear concept (Laundré, Hernández & Altendorf, 2001) postulates that prey are aware of microhabitat patches associated with high and low predation risk, where predators are either active and ubiquitous, or scarce (Laundré, Hernández & Altendorf, 2001; Shrader et al., 2008; Van Der Merwe & Brown, 2008; Laundré, Hernández & Ripple, 2010). Theoretically, landscape of fear effects should increase with landscape heterogeneity, since the differences between high and low risk sites become more pronounced and prey can more easily avoid high-risk sites (Bleicher, 2017; Gaynor et al., 2019). However, this relationship can depend on the species and condition of the habitat and, for some species, simple habitats can be the safest (Hammerschlag et al., 2015; Schmidt & Kuijper, 2015; Atuo & O’Connell, 2017). Landscape of fear effects will also be more pronounced in systems where interactions between predators and prey are less frequent (Schmitz, 2008), as is evident in findings from Pavlovian fear conditioning, and the ‘risk allocation hypothesis’—which states that animals exposed to constant high predation risk will increase their foraging risks over time (Lima & Bednekoff, 1999; Van Buskirk et al., 2002). Fear arousal in a landscape of fear results in two predictable outcomes: either avoidance of high risk areas, or modulation of behaviour (e.g. increased vigilance) to reduce predation risk when foraging in such areas (Gaynor et al., 2019). These outcomes indicate the potential positive benefits to conservation management of considering fear arousal and stress levels, and the direct and indirect cues that may trigger these effects (Atkins et al., 2017).

The likelihood of survival of a prey species is improved by having a well-developed perception of high predation risk, as it allows adaptive behavioural responses to be established (Bókony et al., 2009). Habitat shifts, temporal shift, grouping, vigilance and freeze, fly and fight responses are the most studied such responses to the non-consumptive effects of predators (Say-Sallaz et al., 2019). These often develop due to increased interaction rates between predators and prey. However, chronic stress impacts that are sufficient to affect reproduction and long-term survival can be experienced by prey species perceiving recurring predation risks (Thomson et al., 2010; Clinchy et al., 2011). Chronic perceived predation risk may also result in altered foraging activity driven by fear. This can affect where and what prey eat (Schmitz, Krivan & Ovadia, 2004), causing them to move from risky to sheltered microhabitats (Trussell, Ewanchuk & Matassa, 2006), in turn altering the distribution and availability of resources. Fear-based adaptive behavioural responses such as these underlie the landscape of fear concept.

For mammals, fear arousal can be triggered both by a predator’s presence or by a predator cue, such as an associated scent. Olfaction can be a key driver of fear arousal (Soso et al., 2014; Banks, Daly & Bytheway, 2016; Jones et al., 2016; Parsons et al., 2017). The mechanics of this are best understood in mammals: odours are detected by the accessory olfactory bulb that transmits information directly to the amygdala and hypothalamus, where fight or flight responses are developed (Fogaca et al., 2012; Canteras, Pavesi & Carobrez, 2015). Laboratory studies exploring the effects of post-traumatic stress disorder have exposed small mammals to predators or their cues to induce stress, and in doing so revealed that exposure to predator cues alone can affect the neural circuitry associated with fear (Rosen & Schulkin, 1998, 2004).

Subtle cues such as predator odours may precede threats and allow for a mammalian prey animal’s fear state to be conditioned to a cue that occurs before, or in correlation with, a previously encountered predation threat (Rescorla & Solomon, 1967; Rosen, 2004). Predation risk may, therefore, be perceived by prey species eavesdropping on predator scent marks, such as urine, faeces, or fur in the environment (Banks, Daly & Bytheway, 2016; Jones et al., 2016). Such odours have been observed experimentally to induce fear-like responses of freezing (Wallace & Rosen, 2000), vigilance (Nersesian, Banks & McArthur, 2012), fleeing (Anson & Dickman, 2013) and avoidance (Hayes, Nahrung & Wilson, 2006), across a wide range of species in both field and laboratory experiments (Apfelbach et al., 2005, 2015). Consequently, landscape of fear topography, where predators indirectly influence prey behaviour across a range of microhabitats, can arise from the influence of predator olfactory cues on mammalian prey foraging behaviours as much as it can from the direct threat of predation (Brown & Kotler, 2004; Parsons & Blumstein, 2010; Cremona, Crowther & Webb, 2014; Mella, Banks & McArthur, 2014; Hoffman, Sitvarin & Rypstra, 2016). It is worth noting, however, that whilst predator olfactory cues can elicit a fear or stress response, they do not always do so (Apfelbach et al., 2005). This may be because predators often leave the site after depositing a cue, and the cue intensity diminishes. Predator cues elicit responses that are modulated according to the differential intensity of the perceived threat, prior experience, or pending further information gathering, and thus can be perceived as a low risk by prey (Bedoya-Pérez et al., 2019).

Fear arousal due to predator presence or cues can deplete a prey individual’s energy budget, resulting in poor reproduction and health either via energy exhaustion from stress (i.e. the predation stress hypothesis: Boonstra et al., 1998; Clinchy et al., 2004; Romero, 2004; Støen et al., 2015), or reduced nutrition from foraging compromises (Brown & Kotler, 2004; Clinchy et al., 2016). As food resources become limited, additionally, prey may take greater risks to meet nutritional needs (i.e. the predation-sensitive food hypothesis: Sinclair & Arcese, 1995), but at a possible cost of additional stress. In areas of high human activity, this may result in wildlife increasing the stressors they are exposed to as they seek human-based food sources, such as waste or pet food, and in doing so increase their exposure to domestic pets, altered light, increased sound, and vehicles (Navara & Nelson, 2007; Morgan et al., 2009; Riley et al., 2014; Shannon et al., 2016; Doherty et al., 2017). For managers mitigating fear arousal, mapping landscapes of fear (Van Der Merwe & Brown, 2008; Kauffman, Brodie & Jules, 2010; Iribarren & Kotler, 2012; Smith et al., 2019) to identify, protect and extend safe foraging areas, could assist in the conservation of wildlife subject to human activity or multiple stressors such as human activity and predators.

Human Activity as a Fear-inducing Stressor

Human activity can influence wildlife in a wide variety of ways (Albert & Bowyer, 1991; Bowyer et al., 1999). Pressure from increased proximity to human activity or development that encroaches upon animal home ranges results in wildlife becoming either: (1) ‘urban avoiders’ that move away from human activity; (2) ‘urban adapters’ that make some use of anthropogenic resources but still rely largely upon those found naturally; or (3) ‘urban exploiters’ that are synanthropic and make full use of anthropogenic resources (McKinney, 2006). The effects of human activity can therefore differ between species and trophic levels, and even within the same species, depending on personality. Furthermore, the negative effects of a disturbance on one species may result in flow-on responses of positive consequences for its prey, predators, or competing species (Gill, Sutherland & Watkinson, 1996; Crooks & Soulé, 1999; Leighton, Horrocks & Kramer, 2010). These effects, however, depend strongly on the availability of necessary resources within the human occupied/disturbed areas, and will often differ between systems.

It has been postulated that humans may impose widespread effects on ecosystem function if they induce greater fear responses in ubiquitous small predators than in top predators (Clinchy et al., 2016), or by increasing physiological stress in large ungulates through antagonistic behaviours (Vijayakrishnan et al., 2018). Indeed, human activity can be comparable to the above-mentioned impacts of predation, creating landscapes of fear (Hofer & East, 1998; Frid & Dill, 2002; Rehnus, Wehrle & Palme, 2014; Patten & Burger, 2018), and disrupting foraging (Ciuti et al., 2012; Clinchy et al., 2016). Humans can also act as ‘super-predators’ that disproportionately kill carnivores and drive trophic cascades (Darimont et al., 2015). Trophic cascades can also arise when human activity has non-consumptive effects on the ecological roles of large predators (Smith et al., 2017). For example large predators may increase their hunting efforts in urban areas: if their own fear response to human activity results in less time spent consuming a kill, this in turn may increase their kill rate of prey in urban areas to meet their energy needs (Smith et al., 2017). When large predators avoid human activity, and/or meso-predators reduce their foraging around human activity, prey species may respond by increasing their own foraging activity (Suraci et al., 2019), effectively taking refuge behind the ‘human shield’ that is reducing predation pressure for them (Berger, 2007; Leighton, Horrocks & Kramer, 2010; Kuijper et al., 2015).

Human activity can affect the trophic structure of communities not only via top-down pressure, but also by exerting bottom-up pressure through the constant provision of alternative resources (Fischer et al., 2012), such as subsidies of shelter, water and food with year-round primary production. These resources can outweigh the stresses of human disturbance and influence population and community behaviours (Parris, 2016), resulting in urban colonisation by wildlife (Shochat, Lerman & Fernández-Juricic, 2010; Jokimäki et al., 2011). As such, human activity does not always result in fear responses, particularly for prey species that benefit from the human shield and access to food, water or shelter subsidies (Lyons et al., 2017). It is possible that, given these conditions, and provided that resource subsidies are nutritionally rich and accessing them does not increase pathogen transmission risk (Murray et al., 2016), prey species like small mammals would experience fitness benefits in urban areas. Resource subsidies can also be exploited by predators, resulting in increased predator activity in urban areas but also in altered foraging behaviours that either decrease or increase predation on small prey (Iossa et al., 2010; Bateman & Fleming, 2012; Fischer et al., 2012; Newsome et al., 2014, 2015).

Despite such positive effects of human activity on wildlife, negative impacts are more pervasive for many species. The negative effects of high levels of disturbance, for example from roads and vehicles, or of active interference from recreational activities conducted in designated conservation areas, can lead to physiological stress or displacement, countervailing any positive effects of humans on wildlife (Kloppers, St. Clair & Hurd, 2005; Banks & Bryant, 2007; Berger, 2007; Ciuti et al., 2012; Rehnus, Wehrle & Palme, 2014; Arlettaz et al., 2015; Patten & Burger, 2018; Vijayakrishnan et al., 2018).

A common response in mammals to increased exposure to human activity is a temporal shift in activity patterns, from diurnal to crepuscular or nocturnal, to avoid interaction with humans (McClennen et al., 2001; Tigas, Van Vuren & Sauvajot, 2002; Riley et al., 2003; Ditchkoff, Saalfeld & Gibson, 2006; Gaynor et al., 2018); the same or reverse may occur too, to reduce interactions with predators (Brown, 2000; Laundré, Hernández & Altendorf, 2001; Kohl et al., 2018; Smith et al., 2019). Temporal shifts can have strongly negative effects if they limit a forager’s ability to locate and capture prey (Ditchkoff, Saalfeld & Gibson, 2006). Regardless of the response, it is evident that human activity can have profound indirect effects on community interactions through altering individual behaviour, particularly foraging, through either fear arousal or a stress response (Frid & Dill, 2002; Werner & Peacor, 2003).

The ability of wildlife to cope with urban environments can occur through either plastic or evolved shifts in behaviour, foraging, food preferences, or predator avoidance, and in shifts in the timing of breeding (Ditchkoff, Saalfeld & Gibson, 2006; Møller, 2009; Shochat, Lerman & Fernández-Juricic, 2010; Rodriguez, Hausberger & Clergeau, 2010; Alberti, 2015; McDonnell & Hahs, 2015; Otto, 2018; Santini et al., 2019). It is most common for urban-occupying species to plastically adjust to human imposed stressors (Donihue & Lambert, 2015), with some ultimately evolving tolerance to urban environments. Human activity can therefore impose pressures that are strong enough to influence changes in behaviour and in physiology—endocrinology in particular (Bonier, 2012; Snell-Rood & Wick, 2013; Otto, 2018). Bolder individuals are most likely to exploit novel opportunities and have reduced stress responses to human activity (Atwell et al., 2012). Animals that routinely encounter human activity, typically provide parental care, and are capable of reproducing multiple times across their life span may produce offspring that are acclimated to human activity and accordingly show lower fear/stress responses (Schell et al., 2018). Habituation of groups of animals to human activity is being increasingly observed, often as a result of bold individuals spending significant amounts of time around human-disturbed areas and displaying reduced fear responses (Stillfried et al., 2017). This counters the idea that human activity always imposes landscapes of fear, but may reflect the combination of reduced resource availability and bold personalities that allow for urban habituation (Lowry, Lill & Wong, 2013). In some instances this may be problematic for humans if increased interactions with habituated animals increase vehicle accidents and/or transfer of zoonotic diseases; this highlights the potential need to manage some mammalian prey species in urban areas (Honda et al., 2018).

Fear and acute/chronic stress may be constant hurdles faced by wildlife, but adding the effects of anthropogenic disturbance could result in the elevation of acute stress responses to prolonged and widespread chronic stress, and upscale the possible impacts from individuals to populations (Rehnus, Wehrle & Palme, 2014). As we have outlined, human activity can both indirectly and directly create landscapes of fear, influencing and amplifying existing landscapes of fear through interactive effects. Predator presence and human activity can also interact to alter ecosystem structure and modify the predation risk perceived by prey species, with either positive or negative impacts dependent upon the circumstances. The combination of stress resulting from the pressures of altered predator–prey interactions and human activities is yet to be investigated extensively. Understanding the cumulative effects that both may impose is critical for effective conservation of wildlife in an increasingly human-influenced world.

Alleviating Fear and Stress for Wildlife Conservation

As we have illustrated, fear can produce stress and simultaneous multiple stressors can have chronic effects that negatively influence both predator and prey species populations (Allan et al., 2013). To synthesize these impacts, we note that in modern urban situations both habitat stressors and introduced stressors now collide (Fig. 1). Habitat stressors result from naturally occurring environmental factors such as native predator presence (especially for prey), social and reproductive pressures, limited access to refuges/nests and/or food and water, and disease and parasite prevalence, all of which produce predictive homeostasis responses by prey species (Fig. 1). Introduced stressors, by contrast, are additional stressors that are imposed by human actions that result in reactive homeostasis responses. These introduced anthropogenic stressors include structural developments that change landscapes, human recreational activities in natural habitats (including use of vehicles), introduced pollutants and toxins that alter landscapes and resource quality, and introduced predators and altered predator–prey interactions (Fig. 1). The combination of impacts from both naturally occurring and introduced anthropogenic stressors has the potential to cause a cumulative stress response that can result in homeostatic overload or failure, as defined by Romero, Dickens & Cyr (2009), and may result in population collapses due to increased susceptibility of individuals to the additional stressors (as we have demonstrated above, and Fig. 1). Cumulative stress may be additive or synergistic, and is likely to be particularly detrimental for prey species. For example, if prey species face multiple stressors they may take greater foraging risks, or be less able to allocate energy to vigilance or flight behaviours, and thus become more susceptible to predation or additional stressors. In the case of population-impacting stressors, the local population may be impacted to a high degree such that it becomes threatened (Sweitzer, 1996; Doherty et al., 2015). As such, conservation action in areas where simultaneous introduced stressors occur in addition to natural ecosystem pressures, like in urban and peri-urban habitats, may be urgently needed.

A Venn diagram showing two main categories of stressor.
Figure 1
On the left are stressors that occur naturally in ecosystems, such as native predators, social and breeding interactions, availability of refuge and burrow/den microhabitats, disease/parasite prevalence, and availability of food and water. On the right are introduced stressors, primarily those arising from anthropogenic disturbances, such as urban developments, human activity, introduced toxins and introduced predators. Where both categories of stressor occur together simultaneously, as in many urban environments, cumulative stress impacts can result in homeostatic overload or failure (as defined by Romero, Dickens & Cyr (2009)). In these situations populations may be at particular risk of collapse and conservation action will be most urgent.A Venn diagram showing two main categories of stressor.

The most direct way to alleviate stress in wildlife is to remove or reduce the key stressors. This may be difficult if the stressors are anthropogenic, as the needs of the expanding human population often usurp those of wildlife; alternative solutions then need to be considered. A suite of activities related to managing vegetation structure, density, and/or heterogeneity may well provide such an alternative solution. These activities result in increased availability of potential refuge sites and may be readily achieved through ongoing habitat engineering that, for example supports the growth of structurally complex plants or adds logs/rock piles to reduce areas of open space. In order to mitigate introduced fear and stress effects, it is important that future studies investigate whether vegetation management and other habitat components can alleviate some of the pressures associated with multiple introduced stressors for target species.

Managing Habitat to Alleviate Wildlife Fear and Stress

The impact of predators (or human activity) can be mitigated by changing the configuration of risky areas within a habitat (Hopcraft, Sinclair & Packer, 2005; Lone et al., 2014). Food availability often drives habitat selection (Sherman, 1984; Johnson & Sherry, 2001), but predation risk and human activity affect a suite of correlated factors such as movement decisions (Turcotte & Desrochers, 2003), foraging patterns (Gil, Zill & Ponciano, 2017), social organisation (Rodríguez, Andrén & Jansson, 2001) and reproductive success (Zanette et al., 2011). Supplementation of essential resources including refuges, nests or roosts, food and water to wildlife is a growing conservation method due to its ease of implementation, immediate results, and favourable portrayal in the media. One example of positive results includes increased parasite resistance in nestling birds after supplementation with high-quality food during the stressful young-rearing stage (Knutie, 2020). Another example is the reduction in impact from introduced predators on small desert mammals following the addition of artificial refuge structures (Bleicher & Dickman, 2020). Despite these successes, negative impacts can also ensue following supplementation. Built-up refuges may be primarily investigated by invasive species, such as the black rat (Rattus rattus ), which could potentially deter commensal native species and support the population growth of invasive species (Price & Banks, 2018). Artificial nests or roosts can support increased predation rates owing to the structure supporting a sit-and-wait predator at the exit (McComb et al., 2019). Food and water subsidies can increase pathogen transmission, reduce movement and migratory behaviours, increase predator–prey interaction rates, and competitor aggression interactions (Murray et al., 2016). However, owing to the benefits of supplementation, especially during times of stress, it may be used as a tool to mitigate the negative impacts of stress on wildlife if conducted in a targeted, monitored and well-considered manner (Freeman et al., 2020).

Considering the existing knowledge base on food and water supplementation, meta-analyses have suggested that the associated disease risk may be managed by focusing on specific natural food sources and pathogen groups subject to the target ecosystem and by increasing the spatial extent of feeding stations across potential linked habitats, which also limits microparasite host aggregations (Becker, Streicker & Altizer, 2015; Becker et al., 2018). In considering the specific needs of target animals and ecosystems, chainsaw-carved cavities have more favourable thermodynamic properties for small mammals and birds than do artificial next boxes (Griffiths et al., 2018). As they mimic natural hollows they are also less likely to increase rates of predation. Supplementation projects are therefore moving forward using this growing knowledge base to adaptively tailor methods to specific conditions, and to orchestrate pre- and post-monitoring that ensures successful stress mitigation (Civitello et al., 2018).

Survivorship of prey, in the face of predation stressors, is often positively correlated with increased structural complexity of the habitat (Hopcraft, Sinclair & Packer, 2005; Lone et al., 2014; Leahy et al., 2016). This has been demonstrated in many studies to be a consequence of the increased opportunities for prey to escape and hide, thereby mediating predator–prey dynamics by reducing encounter rates, as only a proportion of the total prey population remains available to predators (Holt, 1984; Kotler & Brown, 1988; Bianchi, Schellhorn & Van der Werf, 2009; Rieucau, Vickery & Doucet, 2009; Klecka & Boukal, 2014; Laundré et al., 2014). The extensive research on the benefits to prey of habitat structural complexity builds on the ‘habitat heterogeneity hypothesis,’ which postulates that structurally complex habitats support increased species diversity by offering a wide range of niches and diverse ways of exploiting resources (Bazzaz, 1975). Habitat complexity, by extension, has been generalized to be a primary driver of biodiversity (Pianka, 2011). The landscape of fear concept accepts this principle too, in that a wide range of microhabitat types offers multiple foraging and shelter conditions with varied predation risks for species. For example northern quolls (Dasyurus hallucatus) of the semi-arid Pilbara region in Western Australia utilise complex rocky habitats in preference to open grasslands where the threat of predation from feral cats (Felis catus ) is greater (Hernandez-Santin, Goldizen & Fisher, 2016).

Animals in habitats with high predation pressure may display foraging preferences for microhabitats or times that they perceive to be safe (Brown, 2000; Laundré, Hernández & Altendorf, 2001; Laundré, Hernández & Ripple, 2010). Some small mammals seek structurally complex vegetation owing to the reduced risk of predation and increased reward of foraging they find there (Lima & Dill, 1990; Andruskiw et al., 2008). Others, such as the Australian hopping mouse (Notomys alexis ) that exhibit bursts of speed in open habitat, are less adept at moving through complex vegetation (Spencer, Crowther & Dickman, 2014). No matter the species, in landscapes of fear a prey species’ use of the topography, refuges, and escape substrates can indicate its perceived risk of predation (Brown & Kotler, 2004; Van Der Merwe & Brown, 2008; Shrader et al., 2008), and the associated fear and stress that may arise or be alleviated due to habitat structure. The same principle should be relevant to reducing stress in proximity to human activity, considering that prey responses to human activity and predators are similar.

Human activity and disturbance can quickly reduce habitat complexity (Western, 2001). However, enhancing habitat complexity and heterogeneity is being incorporated increasingly into restoration and management efforts, with some success (Brown, 2003; Bernhardt & Palmer, 2007; Palmer, Menninger & Bernhardt, 2010). To balance the needs of people and biodiversity, local planning procedures are at times now incorporating green spaces and greening initiatives into urban areas. As habitat complexity and diversity are of particular importance in supporting biodiversity and population sustainability, it is important that habitat structure underpins the engineering of wildlife habitats in urban and urban-adjacent areas (Threlfall et al., 2016). The effectiveness of any management regime depends on recognising the direct and indirect impacts that occur across sustainable ecosystems. Consequently, habitat complexity as a management objective requires that urban landscapes are approached on a case by case basis, with full assessment before the habitat is ecologically engineered (Tews et al., 2004).

Management Tools to Observe and Alleviate Fear and Stress for Wildlife Conservation

Cumulative stress maps of human activity and stressors that occur naturally in ecosystems have allowed returns on restoration investments to be maximized by indicating key areas that will or do need intervention to mitigate the effects of severe stress on wildlife, as opposed to unsuccessful piecemeal management that focuses on one or two stressors broadly (Allan et al., 2013). Physiological and behavioural stress in wildlife may be cost-effectively and straightforwardly observed by comparing the outcomes of simultaneous measurements taken across a disturbance gradient where multiple stressors are both abundant and low, using several well-established methods. Specifically, assays of faecal/urine/fur/feather glucocorticoid metabolites can provide insight into the level of physiological stress an animal is experiencing under comparative circumstances (Cook, 2012; Cooke et al., 2013; Sheriff et al., 2011; Palme, 2019). Pairing such results for each location with those of giving-up density surveys (Brown, 1988) that can also be filmed by infrared motion sensor cameras to observe foraging behavioural responses (Leo, Reading & Letnic, 2015), yields an understanding of both physiological stress responses and foraging responses. Comparing these results may further indicate if behavioural responses are changing to moderate physiological stress impacts (Carlstead, Brown & Seidensticker, 1993; Carlstead, Brown & Strawn, 1993). Simultaneous measurements of habitat quality that include vegetation cover, refuges, distance to food/water source, and distance to disturbances (e.g. human activity or predator sighting based on spotlighting or in-field camera traps) will build a dataset for spatial correlation analyses that can geographically map the landscape of fear. Such measurements should also identify what factors influence the landscape, such as by use of behavioural data (Willems & Hill, 2009) and/or giving-up density data (Van Der Merwe & Brown, 2008).

Spatial mapping of the physiological stress response, based on the collection locations of samples, could be overlaid and compared to these results also. Such spatially mapped results may clarify important areas that are in need of protection or the habitat types that could be extended to mitigate stress impacts. It is worth noting that several authors have emphasized that these methods need to be used correctly to ensure that stress and habitat factors are linked (e.g. McMahon et al., 2018; Bleicher, 2017; Bedoya-Perez et al., 2013; MacDougall-Shackleton et al., 2019). For example collection of fresh faecal samples of a target species along a gradient of high to low human activity would allow glucocorticoid metabolites to be assayed, providing insight into potential stress induced by human activity along the gradient (Rehnus, Wehrle & Palme, 2014). A similar approach could be used to assay stress perceived by prey species in areas of high and low predator activity, and sex hormones also could be assayed to explore sex-related effects of stress. By allowing pathways of fear and stress to be mapped, including sites where stressors from predators and human activity occur simultaneously, such methods should allow managers to reliably identify where best to intervene to preserve at-risk populations and maintain community stability. We consider potential interventions in more detail below.

If cumulative stressors occur and are suspected to have detrimental effects on target wildlife populations or communities, we suggest that a potentially powerful mitigation approach could be developed based on Cumulative Effects Assessments (CEA). Devised in the 1990s amid growing concerns that Environmental Impact Assessments (EIA) did not consider all the effects of urban and peri-urban developments (Smit & Spaling, 1995), CEAs have been advocated as an effective tool for use by on-ground practitioners (Duinker et al., 2013). Numerous countries have mandated that CEAs be incorporated into EIAs, namely: the United States of America, Canada, Europe, New Zealand, and Australia each advocate some level of CEAs (Therivel & Ross, 2007). Despite this legal requirement, and the CEA concept being widely known in scientific literature, it is rarely applied in practice (Ma, Becker & Kilgore, 2009; Foley et al., 2017).

We propose further that the principles of the ‘reactive scope model’ be used to develop CEAs, to identify where cumulative stressors occur, and thus better inform conservation management initiatives in areas where wildlife is subject to homeostasis overload or failure (Fig. 2). The results from the above mentioned methods and/or other applicable established methods may be used to answer our suggested CEA questions. The reactive scope model (Romero, Dickens & Cyr, 2009) provides useful insight into the range of physiological mediators available in response to a stressor. It maps the homeostasis range of a given species in four stages: (1) predictive—change occurs in response to routine environmental change, such as seasons or day to night; (2) reactive—change occurs in response to an unpredictable change, allowing survival via classic stress responses; (3) overload—consistent changes occur in response to a stressor, and chronic stress impacts start to occur; and (4) failure—the species shows inability to sustain homeostasis, and is very susceptible to additional stressors and death (Romero, Dickens & Cyr, 2009). If our proposed CEA approach (Fig. 2), based on the reactive scope model, were applied to small mammals in urban, urban adjacent, and peri-urban ecosystems, for example then areas of conservation concern could be identified where the additive or synergistic impacts of human disturbance and introduced predators combine with stressors that occur naturally. Appropriate management, such as increasing habitat complexity or reducing human activity in conservation areas (Bleicher & Dickman, 2020), could then be implemented to alleviate these stressors.

A conservation management approach that outlines the key steps for assessing if cumulative stress impacts are occurring between stressors that occur naturally in ecosystems and those that are introduced.
Figure 2
The circled areas indicate where conservation management initiatives may be used to mitigate these effects through management of vegetation complexity or supplementation materials such as water stations or carved ‘tree-hollow’ cavities.A conservation management approach that outlines the key steps for assessing if cumulative stress impacts are occurring between stressors that occur naturally in ecosystems and those that are introduced.

Fear and Stressing in Small Mammal Ecology in Australia; The Need to Consider the Twin Stressors of Introduced Predators and People in Wildlife Management

Small mammals are often somewhat resilient to threatening processes owing to their high population growth rates (Cardillo et al., 2005, 2006). However, in Australia small mammal populations are declining quickly, and due to causes dissimilar to those driving global declines (Woinarski, Burbidge & Harrison, 2015). Declines in Australia have been attributed to a wide range of habitat stressors: habitat loss, altered fire regimes, disease, increasing temperatures, decreasing water availability, depleted soil quality and salinity (Woinarski, Burbidge & Harrison, 2015). However, mammals within a ‘critical weight range’ (CWR: 35–5,550 g) are particularly vulnerable (Chisholm & Taylor, 2007; Woinarski, Burbidge & Harrison, 2015) owing to the effects of predation by two introduced carnivores, the red fox (Vulpes vulpes) and domestic house cat (Felis catus ) that arrived in Australia over 150 years ago (Johnson, 2006). If predators are introduced, their impacts on prey are likely to be exacerbated owing to prey naïveté (Doherty et al., 2016). Such impacts have been particularly acute on wildlife in Australia, where eutherian carnivores are recent arrivals (Salo et al., 2007). However, the question of Australian native animal stress responses and the extent of their naiveté to these introduced eutherian predators is debatable (Banks & Dickman, 2007; Carthey & Banks, 2016). Although CWR mammals are of high conservation concern, predation from introduced predators poses a threat also to all native predators by reducing their food resources, which in turn may increase predation and predation-associated stress on alternative food sources such as smaller (<35 g) or larger (>5,550 g) mammal species. For example a study examining the diet of a nocturnal, avian predator, the sooty owl (Tyto tenebricosa ) before and after red fox introduction, revealed a dietary shift post introduction, with owls consuming more arboreal than terrestrial prey species after fox arrival (Bilney, Cooke & White, 2006). This shift to consuming arboreal prey increased dietary overlap with the sympatric powerful owl (Ninox strenua), providing disproportionate predation pressure on prey in the ecosystems of East Gippsland, Victoria.

Predation by red foxes and cats is prevalent not only in natural habitats but also in agricultural and urban habitats (Dickman, 1996; Morgan et al., 2009; Bino et al., 2010). The paths and roads that fragment urban and agricultural habitats are used frequently by these predators, which exacerbates their predation pressure on prey species by combining with impacts imposed by human activities (Latham et al., 2011, Červinka et al., 2013). Consequently, this can result in increased abundances of red foxes and cats in human-modified landscapes that border or include natural habitats (Towerton et al., 2011; Graham, Maron & McAlpine, 2012). Urban and agricultural habitats present many threats to wildlife, but they may also offer food and shelter opportunities (Pickett et al., 2001; Gaston et al., 2005; Hobbs, Higgs & Harris, 2009). As reported by Ives et al. (2016), 46 percent of threatened Australian animals occur in or near Australian cities. Thus, the fate of many species could depend on accommodating their needs in urban and agricultural habitats (Ives et al., 2016). A recent assessment of data collected at the Wildlife Rehabilitation Centre in Queensland Zoo, Australia, revealed that pet cat or dog attack, car strike, and entanglement in human-placed objects represented 56.4% of the causes of submission of injured wildlife; mortality rates associated with these traumas were also high, with 61.3% of admitted animals dying from their injuries (Taylor-Brown et al., 2019). These threats may contribute to landscapes of fear, through fear arousal, altered foraging behaviour, post-traumatic stress reactions, and cumulative stress exposures resulting in chronic stress responses.

Despite growing knowledge of anthropogenic impacts on threatened species, Australian conservation planning continues to exclude urban and agricultural habitats from consideration (Dales, 2011). There is recognition of the scope of this issue in Australia (Hill, Carbery & Deane, 2007; Carthey & Banks, 2012; Threlfall, Law & Banks, 2012; McCauley, Jenkins & Quintana-Ascencio, 2013; Banks & Smith, 2015; Ives et al., 2016), but few studies have explored the interactive effects of introduced predators and human activity on the survival of prey species. Despite the development of glucocorticoid analysis techniques to determine stress in animals dating to the 1960s (Jones et al., 1964), only six of the 60 extant small mammals of conservation concern in Australia have been subject to studies seeking to better understand their glucocorticoid response to stressors (Hing et al., 2014), such as predation by introduced species or human activity.

There is a need for alternative management regimes to mitigate the additional stressors of human-imposed impacts on wildlife, and the situation we have outlined in Australia underlines the urgency of this need. As there are difficulties with the current control of introduced predators in Australia (Glen & Dickman, 2005; Rayner et al., 2007; Bergstrom et al., 2009; Norton, 2009; Warburton & Norton, 2009; Carroll, 2011; Newsome et al., 2017), there is also an urgent need for alternative management regimes to mitigate the additional stressors of introduced predator-imposed impacts. As we have argued throughout this review, it is logical that biodiversity conservation managers consider stress from the combined impacts of introduced predators, altered predator interactions, human activity, and stressors that occur naturally in ecosystems. Using the example methods to conduct our proposed CEA, based on the reactive scope model, to draft appropriate management plans, such as increasing habitat complexity or reducing human interaction in areas, would be a progressive response towards preserving many species of Australian small mammals and their constituent communities.


Considering ongoing global urbanization and the acknowledged importance of urban areas to biodiversity conservation, there is a great need for increased focus on the management of urban biodiversity. Management decisions require information about fear and stress impacts on wildlife, including impacts from both human activities and predators, especially if they are novel or introduced. Understanding the impacts of human activities is a research priority for modern science. There are many gaps in our current understanding of fear and stress impacts on wildlife, and of associated impacts of altered predation pressures and the persistence of target populations. To sustain biodiversity in urban and urban-adjacent green space habitats, reserves and conservation areas, it is vital that we establish better understanding and management of the multiple stressors that operate in these systems.

Additional Information and Declarations

Competing Interests

The authors declare that they have no competing interests.

Author Contributions

Loren L. Fardell conceived and designed the experiments, performed the experiments, analyzed the data, prepared figures and/or tables, authored or reviewed drafts of the paper, and approved the final draft.
Chris R. Pavey conceived and designed the experiments, authored or reviewed drafts of the paper, and approved the final draft.
Christopher R. Dickman conceived and designed the experiments, authored or reviewed drafts of the paper, and approved the final draft.

Data Availability

The following information was supplied regarding data availability:

This is a literature review article and did not generate raw data.


Albert & Bowyer (1991) 

    Albert DM, Bowyer RT. Factors related to grizzly bear: human interactions in Denali National Park. Wildlife Society Bulletin 1991. 19: 3, pp.339-349

Alberti (2015) 

    Alberti M. Eco-evolutionary dynamics in an urbanizing planet. Trends in Ecology & Evolution 2015. 30: 2, pp.114-126, doi: 10.1016/j.tree.2014.11.007

Allan et al. (2013) 

    Allan JD, McIntyre PB, Smith SD, Halpern BS, Boyer GL, Buchsbaum A, Burton GA, Campbell LM, Chadderton WL, Ciborowski JJH, Doran PJ, Eder T, Infante DM, Johnson LB, Joseph CA, Marino AL, Prusevich A, Read JG, Rose JB, Rutherford ES, Sowa SP, Steinman AD. Joint analysis of stressors and ecosystem services to enhance restoration effectiveness. Proceedings of the National Academy of Sciences USA 2013. 110: 1, pp.372-377, doi: 10.1073/pnas.1213841110

Andruskiw et al. (2008) 

    Andruskiw M, Fryxell JM, Thompson ID, Baker JA. Habitat-mediated variation in predation risk by the American marten. Ecology 2008. 89: 8, pp.2273-2280, doi: 10.1890/07-1428.1

Anson & Dickman (2013) 

    Anson JR, Dickman CR. Behavioral responses of native prey to disparate predators: naivité and predator recognition. Oecologia 2013. 171: 2, pp.367-377, doi: 10.1007/s00442-012-2424-7

Apfelbach et al. (2005) 

    Apfelbach R, Blanchard CD, Blanchard RJ, Hayes RA, McGregor IS. The effects of predator odors in mammalian prey species: a review of field and laboratory studies. Neuroscience & Biobehavioral Reviews 2005. 29: 8, pp.1123-1144, doi: 10.1016/j.neubiorev.2005.05.005

Apfelbach et al. (2015) 

    Apfelbach R, Parsons MH, Soini HA, Novotny MV. Are single odorous components of a predator sufficient to elicit defensive behaviors in prey species?. Frontiers in Neuroscience 2015. 9: 72, pp.263, doi: 10.3389/fnins.2015.00263

Arlettaz et al. (2015) 

    Arlettaz R, Nusslé S, Baltic M, Vogel P, Palme R, Jenni-Eiermann S, Pathey P, Genoud M. Disturbance of wildlife by outdoor winter recreation: allostatic stress response and altered activity-energy budgets. Ecological Applications 2015. 25: 5, pp.1197-1212, doi: 10.1890/14-1141.1

Atkins et al. (2017) 

    Atkins A, Redpath SM, Little RM, Amar A. Experimentally manipulating the landscape of fear to manage problem animals. Journal of Wildlife Management 2017. 81: 4, pp.610-616, doi: 10.1002/jwmg.21227

Atwell et al. (2012) 

    Atwell JW, Cardoso GC, Whittaker DJ, Campbell-Nelson S, Robertson KW, Ketterson ED. Boldness behavior and stress physiology in a novel urban environment suggest rapid correlated evolutionary adaptation. Behavioral Ecology 2012. 23: 5, pp.960-969, doi: 10.1093/beheco/ars059

Atuo & O’Connell (2017) 

    Atuo FA, O’Connell TJ. The landscape of fear as an emergent property of heterogeneity: contrasting patterns of predation risk in grassland ecosystems. Ecology and Evolution 2017. 7: 13, pp.4782-4793, doi: 10.1002/ece3.3021

Ayal (2007) 

    Ayal Y. Trophic structure and the role of predation in shaping hot desert communities. Journal of Arid Environments 2007. 68: 2, pp.171-187, doi: 10.1016/j.jaridenv.2006.05.013

Banks & Bryant (2007) 

    Banks PB, Bryant JV. Four-legged friend or foe? Dog walking displaces native birds from natural areas. Biology Letters 2007. 3: , pp.611-613, doi: 10.1098/rsbl.2007.0374

Banks & Dickman (2007) 

    Banks PB, Dickman CR. Alien predation and the effects of multiple levels of prey naiveté. Trends in Ecology and Evolution 2007. 22: 5, pp.229-230, doi: 10.1016/j.tree.2007.02.006

Banks & Smith (2015) 

    Banks PB, Smith HM. The ecological impacts of commensal species: black rats, Rattus rattus, at the urban-bushland interface. Wildlife Research 2015. 42: 2, pp.86-97, doi: 10.1071/WR15048

Banks, Daly & Bytheway (2016) 

    Banks PB, Daly A, Bytheway JP. Predator odours attract other predators, creating an olfactory web of information. Biology Letters 2016. 12: 5, pp.20151053, doi: 10.1098/rsbl.2015.1053

Bateman & Fleming (2012) 

Bazzaz (1975) 

    Bazzaz FA. Plant species diversity in old-field successional ecosystems in southern Illinois. Ecology 1975. 56: 2, pp.485-488, doi: 10.2307/1934981

Becker, Streicker & Altizer (2015) 

    Becker DJ, Streicker DG, Altizer S. Linking anthropogenic resources to wildlife-pathogen dynamics: a review and meta-analysis. Ecology Letters 2015. 18: 5, pp.483-495, doi: 10.1111/ele.12428

Becker et al. (2018) 

    Becker DJ, Snedden CE, Altizer S, Hall RJ. Host dispersal responses to resource supplementation determine pathogen spread in wildlife metapopulations. American Naturalist 2018. 192: 4, pp.503-517, doi: 10.1086/699477

Bedoya-Perez et al. (2013) 

    Bedoya-Perez MA, Carthey AJR, Mella VSA, McArthur C, Banks PB. A practical guide to avoid giving up on giving-up densities. Behavioral Ecology and Sociobiology 2013. 67: 10, pp.1541-1553, doi: 10.1007/s00265-013-1609-3

Bedoya-Pérez et al. (2019) 

    Bedoya-Pérez MA, Smith KL, Kevin RC, Luo JL, Crowther MS, McGregor IS. Parameters that affect fear responses in rodents and how to use them for management. Frontiers in Ecology and Evolution 2019. 7: , pp.136, doi: 10.3389/fevo.2019.00136

Belarde & Railsback (2016) 

    Belarde TA, Railsback SF. New predictions from old theory: emergent effects of multiple stressors in a model of piscivorous fish. Ecological Modelling 2016. 326: , pp.54-62, doi: 10.1016/j.ecolmodel.2015.07.012

Bernhardt & Palmer (2007) 

Berger (2007) 

    Berger J. Fear, human shields and the redistribution of prey and predators in protected areas. Biology Letters 2007. 3: 6, pp.620-623, doi: 10.1098/rsbl.2007.0415

Bergstrom et al. (2009) 

    Bergstrom DM, Lucieer A, Kiefer K, Wasley J, Belbin L, Pedersen TK, Chown SL. Management implications of the Macquarie Island trophic cascade revisited: a reply to Dowding et al. (2009). Journal of Applied Ecology 2009. 46: 5, pp.1133-1136, doi: 10.1111/j.1365-2664.2009.01708.x

Bianchi, Schellhorn & Van der Werf (2009) 

    Bianchi FJJA, Schellhorn NA, Van der Werf W. Foraging behaviour of predators in heterogeneous landscapes: the role of perceptual ability and diet breadth. Oikos 2009. 118: 9, pp.1363-1372, doi: 10.1111/j.1600-0706.2009.17319.x

Bilney, Cooke & White (2006) 

    Bilney RJ, Cooke R, White J. Change in the diet of sooty owls (Tyto tenebricosa) since European settlement: from terrestrial to arboreal prey and increased overlap with powerful owls. Wildlife Research 2006. 33: 1, pp.17-24, doi: 10.1071/WR04128

Bino et al. (2010) 

    Bino G, Dolev A, Yosha D, Guter A, King R, Saltz D, Kark S. Abrupt spatial and numerical responses of overabundant foxes to a reduction in anthropogenic resources. Journal of Applied Ecology 2010. 47: 6, pp.1262-1271, doi: 10.1111/j.1365-2664.2010.01882.x

Bleicher (2017) 

    Bleicher SS. The landscape of fear conceptual framework: definition and review of current applications and misuses. PeerJ 2017. 5: e3772, doi: 10.7717/peerj.3772

Bleicher & Dickman (2020) 

    Bleicher SS, Dickman CR. On the landscape of fear: shelters affect foraging by dunnarts (Marsupialia, Sminthopsis spp.) in a sandridge desert environment. Journal of Mammalogy 2020. 101: 1, pp.281-290, doi: 10.1093/jmammal/gyz195

Bonier (2012) 

    Bonier F. Hormones in the city: endocrine ecology of urban birds. Hormones and Behavior 2012. 61: 5, pp.763-772, doi: 10.1016/j.yhbeh.2012.03.016

Boonstra et al. (1998) 

Bókony et al. (2009) 

    Bókony V, Lendvai AZ, Liker A, Angelier F, Wingfield JC, Chastel O. Stress response and the value of reproduction: are birds prudent parents?. American Naturalist 2009. 173: 5, pp.589-598, doi: 10.1086/597610

Bowyer et al. (1999) 

    Bowyer RT, Van Ballenberghe V, Kie JG, Maier JA. Birth-site selection by Alaskan moose: maternal strategies for coping with a risky environment. Journal of Mammalogy 1999. 80: 4, pp.1070-1083, doi: 10.2307/1383161

Brearley et al. (2013) 

    Brearley G, Rhodes J, Bradley A, Baxter G, Seabrook L, Lunney D, Liu Y, McAlpine C. Wildlife disease prevalence in human-modified landscapes. Biological Reviews 2013. 88: 2, pp.427-442, doi: 10.1111/brv.12009

Brown (1988) 

    Brown JS. Patch use as an indicator of habitat preference, predation risk, and competition. Behavioral Ecology and Sociobiology 1988. 22: 1, pp.37-47, doi: 10.1007/BF00395696

Brown (2000) 

    Brown JSHutchings MJ, John LA, Stewart AJA. Foraging ecology of animals in response to heterogeneous environments. The Ecological Consequences of Environmental Heterogeneity 2000. Oxford Blackwell, pp.181-214

Brown (2003) 

    Brown BL. Spatial heterogeneity reduces temporal variability in stream insect communities. Ecology Letters 2003. 6: 4, pp.316-325, doi: 10.1046/j.1461-0248.2003.00431.x

Brown & Kotler (2004) 

Cannon (1932) 

    Cannon WBThe wisdom of the body 1932. New York W.W. Norton and Company, pp.177-201

Canteras, Pavesi & Carobrez (2015) 

    Canteras NS, Pavesi E, Carobrez AP. Olfactory instruction for fear: neural system analysis. Frontiers in Neuroscience 2015. 9: 72, pp.276, doi: 10.3389/fnins.2015.00276

Cardillo et al. (2005) 

    Cardillo M, Mace GM, Jones KE, Bielby J, Bininda-Emonds OR, Sechrest W, Orme CDL, Purvis A. Multiple causes of high extinction risk in large mammal species. Science 2005. 309: 5738, pp.1239-1241, doi: 10.1126/science.1116030

Cardillo et al. (2006) 

    Cardillo M, Mace GM, Gittleman JL, Purvis A. Latent extinction risk and the future battlegrounds of mammal conservation. Proceedings of the National Academy of Sciences of the United States of America 2006. 103: 11, pp.4157-4161, doi: 10.1073/pnas.0510541103

Carlstead, Brown & Seidensticker (1993) 

    Carlstead K, Brown JL, Seidensticker J. Behavioral and adrenocortical responses to environmental changes in leopard cats (Felis bengalensis). Zoo Biology 1993. 12: 4, pp.321-331, doi: 10.1002/zoo.1430120403

Carlstead, Brown & Strawn (1993) 

    Carlstead K, Brown JL, Strawn W. Behavioral and physiological correlates of stress in laboratory cats. Applied Animal Behaviour Science 1993. 38: 2, pp.143-158, doi: 10.1016/0168-1591(93)90062-T

Carroll (2011) 

    Carroll SP. Conciliation biology: the eco-evolutionary management of permanently invaded biotic systems. Evolutionary Applications 2011. 4: 2, pp.184-199, doi: 10.1111/j.1752-4571.2010.00180.x

Carthey & Banks (2012) 

    Carthey AJ, Banks PB. When does an alien become a native species? A vulnerable native mammal recognises and responds to its long-term alien predator. PLOS ONE 2012. 7: 2e31804, doi: 10.1371/journal.pone.0031804

Carthey & Banks (2016) 

    Carthey AJR, Banks PB. Naiveté is not forever: responses of a vulnerable native rodent to its long term alien predators. Oikos 2016. 125: 7, pp.918-926, doi: 10.1111/oik.02723

Carthey & Blumstein (2018) 

    Carthey AJR, Blumstein DT. Predicting predator recognition in a changing world. Trends in Ecology & Evolution 2018. 33: 2, pp.106-115, doi: 10.1016/j.tree.2017.10.009

Červinka et al. (2013) 

    Červinka J, Šálek M, Padyšáková E, Šmilauer P. The effects of local and landscape-scale habitat characteristics and prey availability on corridor use by carnivores: a comparison of two contrasting farmlands. Journal for Nature Conservation 2013. 21: 2, pp.105-113, doi: 10.1016/j.jnc.2012.11.004

Chisholm & Taylor (2007) 

    Chisholm R, Taylor R. Null-hypothesis significance testing and the Critical Weight Range for Australian mammals. Conservation Biology 2007. 21: 6, pp.1641-1645, doi: 10.1111/j.1523-1739.2007.00815.x

Ciuti et al. (2012) 

    Ciuti S, Northrup JM, Muhly TB, Simi S, Musiani M, Pitt JA, Boyce MS. Effects of humans on behaviour of wildlife exceed those of natural predators in a landscape of fear. PLOS ONE 2012. 7: 11e50611, doi: 10.1371/journal.pone.0050611

Civitello et al. (2018) 

    Civitello DJ, Allman BE, Morozumi C, Rohr JR. Assessing the direct and indirect effects of food provisioning and nutrient enrichment on wildlife infectious disease dynamics. Philosophical Transactions of the Royal Society B: Biological Sciences 2018. 373: 1745, pp.20170101, doi: 10.1098/rstb.2017.0101

Clinchy et al. (2004) 

    Clinchy M, Zanette L, Boonstra R, Wingfield JC, Smith JNM. Balancing food and predator pressure induces chronic stress in songbirds. Proceedings of the Royal Society of London Series B: Biological Sciences 2004. 271: 1556, pp.2473-2479, doi: 10.1098/rspb.2004.2913

Clinchy et al. (2011) 

    Clinchy M, Zanette L, Charlier TD, Newman AEM, Schmidt KL, Boonstra R, Soma KK. Multiple measures elucidate glucocorticoid responses to environmental variation in predation threat. Oecologia 2011. 166: 3, pp.607-614, doi: 10.1007/s00442-011-1915-2

Clinchy et al. (2016) 

    Clinchy M, Zanette LY, Roberts D, Suraci JP, Buesching CD, Newman C, Macdonald DW. Fear of the human super predator far exceeds the fear of large carnivores in a model mesocarnivore. Behavioral Ecology 2016. 27: 6, pp.1826-1832

Cook (2012) 

    Cook NJ. Minimally invasive sampling media and the measurement of corticosteroids as biomarkers of stress in animals. Canadian Journal of Animal Science 2012. 92: 3, pp.227-259, doi: 10.4141/cjas2012-045

Cooke et al. (2013) 

    Cooke SJ, Sack L, Franklin CE, Farrell AP, Beardall J, Wikelski M, Chown SL. What is conservation physiology? Perspectives on an increasingly integrated and essential science. Conservation Physiology 2013. 1: 1, pp.cot001, doi: 10.1093/conphys/cot001

Côté, Darling & Brown (2016) 

    Côté IM, Darling ES, Brown CJ. Interactions among ecosystem stressors and their importance in conservation. Proceedings of the Royal Society B: Biological Sciences 2016. 283: 1824, pp.20152592, doi: 10.1098/rspb.2015.2592

Crain, Kroeker & Halpern (2008) 

    Crain CM, Kroeker K, Halpern BS. Interactive and cumulative effects of multiple human stressors in marine systems. Ecology Letters 2008. 11: 12, pp.1304-1315, doi: 10.1111/j.1461-0248.2008.01253.x

Cremona, Crowther & Webb (2014) 

    Cremona T, Crowther MS, Webb JK. Variation of prey responses to cues from a mesopredator and an apex predator. Austral Ecology 2014. 39: 7, pp.749-754, doi: 10.1111/aec.12138

Crocker, Khudyakov & Champagne (2016) 

    Crocker DE, Khudyakov JI, Champagne CD. Oxidative stress in northern elephant seals: Integration of omics approaches with ecological and experimental studies. Comparative Biochemistry and Physiology Part A: Molecular & Integrative Physiology 2016. 200: , pp.94-103, doi: 10.1016/j.cbpa.2016.02.011

Crooks & Soulé (1999) 

    Crooks KR, Soulé ME. Mesopredator release and avifaunal extinctions in a fragmented system. Nature 1999. 400: 6744, pp.563-566, doi: 10.1038/23028

Dales (2011) 

    Dales JT. Death by a thousand cuts: incorporating cumulative effects in Australia’s Environment Protection and Biodiversity Conservation Act. Pacific Rim Law & Policy Journal 2011. 20: , pp.149-178

Dantzer et al. (2014) 

    Dantzer B, Fletcher QE, Boonstra R, Sheriff MJ. Measures of physiological stress: a transparent or opaque window into the status, management and conservation of species?. Conservation Physiology 2014. 2: 1, pp.cou023, doi: 10.1093/conphys/cou023

Darimont et al. (2015) 

    Darimont CT, Fox CH, Bryan HM, Reimchen TE. The unique ecology of human predators. Science 2015. 349: 6250, pp.858-860, doi: 10.1126/science.aac4249

Davis (1992) 

Davis & Whalen (2001) 

    Davis M, Whalen PJ. The amygdala: vigilance and emotion. Molecular Psychiatry 2001. 6: 1, pp.13-34, doi: 10.1038/

Dhabhar & McEwen (1999) 

    Dhabhar FS, McEwen BS. Enhancing versus suppressive effects of stress hormones on skin immune function. Proceedings of the National Academy of Sciences USA 1999. 96: 3, pp.1059-1064, doi: 10.1073/pnas.96.3.1059

Dickens & Romero (2013) 

    Dickens MJ, Romero LM. A consensus endocrine profile for chronically stressed wild animals does not exist. General and Comparative Endocrinology 2013. 191: , pp.177-189, doi: 10.1016/j.ygcen.2013.06.014

Dickman (1996) 

    Dickman CR. Impact of exotic generalist predators on the native fauna of Australia. Wildlife Biology 1996. 2: 1, pp.185-195, doi: 10.2981/wlb.1996.018

Ditchkoff, Saalfeld & Gibson (2006) 

    Ditchkoff SS, Saalfeld ST, Gibson CJ. Animal behavior in urban ecosystems: modifications due to human-induced stress. Urban Ecosystems 2006. 9: 1, pp.5-12, doi: 10.1007/s11252-006-3262-3

Doherty et al. (2015) 

    Doherty TS, Dickman CR, Nimmo DG, Ritchie EG. Multiple threats, or multiplying the threats? Interactions between invasive predators and other ecological disturbances. Biological Conservation 2015. 190: , pp.60-68, doi: 10.1016/j.biocon.2015.05.013

Doherty et al. (2016) 

    Doherty TS, Glen AS, Nimmo DG, Ritchie EG, Dickman CR. Invasive predators and global biodiversity loss. Proceedings of the National Academy of Sciences USA 2016. 113: 40, pp.11261-11265, doi: 10.1073/pnas.1602480113

Doherty et al. (2017) 

    Doherty TS, Dickman CR, Glen AS, Newsome TM, Nimmo DG, Ritchie EG, Vanak AT, Wirsing AJ. The global impacts of domestic dogs on threatened vertebrates. Biological Conservation 2017. 210: , pp.56-59, doi: 10.1016/j.biocon.2017.04.007

Donihue & Lambert (2015) 

    Donihue CM, Lambert MR. Adaptive evolution in urban ecosystems. AMBIO 2015. 44: 3, pp.194-203, doi: 10.1007/s13280-014-0547-2

Duinker et al. (2013) 

    Duinker PN, Burbidge EL, Boardley SR, Greig LA. Scientific dimensions of cumulative effects assessment: toward improvements in guidance for practice. Environmental Reviews 2013. 21: 1, pp.40-52, doi: 10.1139/er-2012-0035

Estes et al. (2011) 

    Estes JA, Terborgh J, Brashares JS, Power ME, Berger J, Bond WJ, Carpenter SR, Essington TE, Holt RD, Jackson JBC, Marquis RJ, Oksanen L, Oksanen T, Paine RT, Pikitch EK, Ripple WJ, Sandin SA, Scheffer M, Schoener TW, Shurin JB, Sinclair ARE, Soulé ME, Virtanen R, Wardle DA. Trophic downgrading of planet Earth. Science 2011. 333: 6040, pp.301-306, doi: 10.1126/science.1205106

Epstein (1972) 

    Epstein SSpielberger CD. The nature of anxiety with emphasis upon its relationship to expectancy. Anxiety: Current Trends in Theory and Research 1972. 2: New York Academic Press, pp.291-337

Fanselow & Poulos (2005) 

Feng et al. (2012) 

    Feng S-F, Shi T-Y, Yang F, Wang W-N, Chen Y-C, Tan Q-R. Long-lasting effects of chronic rTMS to treat chronic rodent model of depression. Behavioural Brain Research 2012. 232: 1, pp.245-251, doi: 10.1016/j.bbr.2012.04.019

Fischer et al. (2012) 

    Fischer JD, Cleeton SH, Lyons TP, Miller JR. Urbanization and the predation paradox: the role of trophic dynamics in structuring vertebrate communities. BioScience 2012. 62: 9, pp.809-818, doi: 10.1525/bio.2012.62.9.6

Fleming & Bateman (2018) 

    Fleming PA, Bateman PW. Novel predation opportunities in anthropogenic landscapes. Animal Behaviour 2018. 138: , pp.145-155, doi: 10.1016/j.anbehav.2018.02.011

Fogaca et al. (2012) 

    Fogaca MV, Lisboa SF, Aguiar DC, Moreira FA, Gomes FV, Casarotto PC, Guimaraes FS. Fine-tuning of defensive behaviors in the dorsal periaqueductal gray by atypical neurotransmitters. Brazilian Journal of Medical and Biological Research 2012. 45: 4, pp.357-365, doi: 10.1590/S0100-879X2012007500029

Foley et al. (2017) 

    Foley MM, Mease LA, Martone RG, Prahler EE, Morrison TH, Murray CC, Wojcik D. The challenges and opportunities in cumulative effects assessment. Environmental Impact Assessment Review 2017. 62: , pp.122-134, doi: 10.1016/j.eiar.2016.06.008

Freeman et al. (2020) 

    Freeman NE, Norris DR, Sutton AO, Newman AEM. Raising young with limited resources: supplementation improves body condition and advances fledging of Canada jays. Ecology 2020. 101: 1e02909, doi: 10.1002/ecy.2909

Frid & Dill (2002) 

    Frid A, Dill LM. Human-caused disturbance stimuli as a form of predation risk. Conservation Ecology 2002. 6: 1, pp.11, doi: 10.5751/ES-00404-060111

Gaston et al. (2005) 

    Gaston KJ, Warren PH, Thompson K, Smith RM. Urban domestic gardens (IV): the extent of the resource and its associated features. Biodiversity and Conservation 2005. 14: 14, pp.3327-3349, doi: 10.1007/s10531-004-9513-9

Gaynor et al. (2018) 

    Gaynor KM, Hojnowski CE, Carter NH, Brashares JS. The influence of human disturbance on wildlife nocturnality. Science 2018. 360: 6394, pp.1232-1235, doi: 10.1126/science.aar7121

Gaynor et al. (2019) 

    Gaynor KM, Brown JS, Middleton AD, Power ME, Brashares JS. Landscapes of fear: spatial patterns of risk perception and response. Trends in Ecology & Evolution 2019. 34: 4, pp.355-368, doi: 10.1016/j.tree.2019.01.004

Geary et al. (2019) 

    Geary WL, Nimmo DG, Doherty TS, Ritchie EG, Tulloch AI. Threat webs: reframing the co-occurrence and interactions of threats to biodiversity. Journal of Applied Ecology 2019. 56: , pp.1992-1997

Gil, Zill & Ponciano (2017) 

    Gil MA, Zill J, Ponciano JM. Context-dependent landscape of fear: algal density elicits risky herbivory in a coral reef. Ecology 2017. 98: 2, pp.534-544, doi: 10.1002/ecy.1668

Gill, Sutherland & Watkinson (1996) 

    Gill JA, Sutherland WJ, Watkinson AR. A method to quantify the effects of human disturbance on animal populations. Journal of Applied Ecology 1996. 33: 4, pp.786-792, doi: 10.2307/2404948

Glen & Dickman (2005) 

    Glen AS, Dickman CR. Complex interactions among mammalian carnivores in Australia, and their implications for wildlife management. Biological Reviews 2005. 80: 3, pp.387-401, doi: 10.1017/S1464793105006718

Graham, Maron & McAlpine (2012) 

    Graham CA, Maron M, McAlpine CA. Influence of landscape structure on invasive predators: feral cats and red foxes in the brigalow landscapes, Queensland, Australia. Wildlife Research 2012. 39: 8, pp.661-676, doi: 10.1071/WR12008

Griffiths et al. (2018) 

    Griffiths SR, Lentini PE, Semmens K, Watson SJ, Lumsden LF, Robert KA. Chainsaw-carved cavities better mimic the thermal properties of natural tree hollows than nest boxes and log hollows. Forests 2018. 9: 5, pp.235, doi: 10.3390/f9050235

Guiden et al. (2019) 

    Guiden PW, Bartel SL, Byer NW, Shipley AA, Orrock JL. Predator–prey interactions in the Anthropocene: reconciling multiple aspects of novelty. Trends in Ecology & Evolution 2019. 34: 7, pp.616-627, doi: 10.1016/j.tree.2019.02.017

Gunderson, Armstrong & Stillman (2016) 

    Gunderson AR, Armstrong EJ, Stillman JH. Multiple stressors in a changing world: the need for an improved perspective on physiological responses to the dynamic marine environment. Annual Review of Marine Science 2016. 8: 1, pp.357-378, doi: 10.1146/annurev-marine-122414-033953

Hammerschlag et al. (2015) 

    Hammerschlag N, Broderick AC, Coker JW, Coyne MS, Dodd M, Frick MG, Godfrey MH, Godley BJ, Griffin DBB, Hartog K, Murphy SR, Murphy TM, Nelson ER, Williams KL, Witt MJ, Hawkes LA. Evaluating the landscape of fear between apex predatory sharks and mobile sea turtles across a large dynamic seascape. Ecology 2015. 96: 8, pp.2117-2126, doi: 10.1890/14-2113.1

Hawlena & Schmitz (2010) 

    Hawlena D, Schmitz OJ. Physiological stress as a fundamental mechanism linking predation to ecosystem functioning. American Naturalist 2010. 176: 5, pp.537-556, doi: 10.1086/656495

Hawlena et al. (2012) 

    Hawlena D, Strickland MS, Bradford MA, Schmitz OJ. Fear of predation slows litter decomposition. Science 2012. 336: 6087, pp.1434-1438, doi: 10.1126/science.1220097

Hayes, Nahrung & Wilson (2006) 

    Hayes RA, Nahrung HF, Wilson JC. The response of native Australian rodents to predator odours varies seasonally: a by-product of life history variation?. Animal Behaviour 2006. 71: 6, pp.1307-1314, doi: 10.1016/j.anbehav.2005.08.017

Hernandez-Santin, Goldizen & Fisher (2016) 

    Hernandez-Santin L, Goldizen AW, Fisher DO. Introduced predators and habitat structure influence range contraction of an endangered native predator, the northern quoll. 2016. Biological Conservation 203: , pp.160-167

Hill, Carbery & Deane (2007) 

    Hill NJ, Carbery KA, Deane EM. Human–possum conflict in urban Sydney, Australia: public perceptions and implications for species management. Human Dimensions of Wildlife 2007. 12: 2, pp.101-113, doi: 10.1080/10871200701195928

Hing et al. (2014) 

    Hing S, Narayan E, Thompson RCA, Godfrey S. A review of factors influencing the stress response in Australian marsupials. Conservation Physiology 2014. 2: 1, pp.cou027, doi: 10.1093/conphys/cou027

Hobbs, Higgs & Harris (2009) 

    Hobbs RJ, Higgs E, Harris JA. Novel ecosystems: implications for conservation and restoration. Trends in Ecology & Evolution 2009. 24: 11, pp.599-605, doi: 10.1016/j.tree.2009.05.012

Hofer & East (1998) 

    Hofer H, East ML. Biological conservation and stress. Advances in the Study of Behavior 1998. 27: , pp.405-525

Hoffman, Sitvarin & Rypstra (2016) 

    Hoffman CR, Sitvarin MI, Rypstra AL. Information from familiar and related conspecifics affects foraging in a solitary wolf spider. Oecologia 2016. 181: 2, pp.359-367, doi: 10.1007/s00442-015-3460-x

Holt (1984) 

    Holt RD. Spatial heterogeneity, indirect interactions, and the coexistence of prey species. American Naturalist 1984. 124: 3, pp.377-406, doi: 10.1086/284280

Honda et al. (2018) 

    Honda T, Iijima H, Tsuboi J, Uchida K. A review of urban wildlife management from the animal personality perspective: the case of urban deer. Science of the Total Environment 2018. 644: , pp.576-582, doi: 10.1016/j.scitotenv.2018.06.335

Hopcraft, Sinclair & Packer (2005) 

    Hopcraft JGC, Sinclair ARE, Packer C. Planning for success: serengeti lions seek prey accessibility rather than abundance. Journal of Animal Ecology 2005. 74: 3, pp.559-566, doi: 10.1111/j.1365-2656.2005.00955.x

Iossa et al. (2010) 

    Iossa G, Soulsbury CD, Baker PJ, Harris SGehrt SD, Riley SPD, Cypher BL. A taxonomic analysis of urban carnivore ecology. Urban Carnivores: Ecology, Conflict, and Conservation 2010. Baltimore Johns Hopkins University Press, pp.173-180

Iribarren & Kotler (2012) 

    Iribarren C, Kotler BP. Foraging patterns of habitat use reveal landscape of fear of Nubian ibex Capra nubiana. Wildlife Biology 2012. 18: 2, pp.194-202, doi: 10.2981/11-041

Ives et al. (2016) 

    Ives CD, Lentini PE, Threlfall CG, Ikin K, Shanahan DF, Garrard GE, Bekessy SA, Fuller RA, Mumaw L, Rayner L, Rowe R, Valentine LE, Kendal D. Cities are hotspots for threatened species. Global Ecology and Biogeography 2016. 25: 1, pp.117-126, doi: 10.1111/geb.12404

Jaatinen, Seltmann & Öst (2014) 

    Jaatinen K, Seltmann MW, Öst M. Context-dependent stress responses and their connections to fitness in a landscape of fear. Journal of Zoology 2014. 294: 3, pp.147-153, doi: 10.1111/jzo.12169

Jackson et al. (2016) 

    Jackson MC, Loewen CJG, Vinebrooke RD, Chimimba CT. Net effects of multiple stressors in freshwater ecosystems: a meta-analysis. Global Change Biology 2016. 22: 1, pp.180-189, doi: 10.1111/gcb.13028

Johnson & Sherry (2001) 

    Johnson MD, Sherry TW. Effects of food availability on the distribution of migratory warblers among habitats in Jamaica. Journal of Animal Ecology 2001. 70: 4, pp.546-560, doi: 10.1046/j.1365-2656.2001.00522.x

Johnson (2006) 

    Johnson CAustralia’s mammal extinctions: a 50,000-year history 2006. Cambridge Cambridge University Press

Johnstone, Lill & Reina (2012) 

    Johnstone CP, Lill A, Reina RD. Does habitat fragmentation cause stress in the agile antechinus? A haematological approach. Journal of Comparative Physiology B 2012. 182: 1, pp.139-155, doi: 10.1007/s00360-011-0598-7

Jokimäki et al. (2011) 

    Jokimäki J, Kaisanlahti-Jokimäki ML, Suhonen J, Clergeau P, Pautasso M, Fernández-Juricic E. Merging wildlife community ecology with animal behavioral ecology for a better urban landscape planning. Landscape and Urban Planning 2011. 100: 4, pp.383-385, doi: 10.1016/j.landurbplan.2011.02.001

Jones et al. (1964) 

    Jones IC, Vinson GP, Jarrett IG, Sharman GB. Steroid components in the adrenal venous blood of Trichosurus vulpecula (Kerr). Journal of Endocrinology 1964. 30: 1, pp.149-150, doi: 10.1677/joe.0.0300149

Jones et al. (2016) 

    Jones ME, Apfelbach R, Banks PB, Cameron EZ, Dickman CR, Frank A, McLean S, McGregor IS, Müller-Schwarze D, Parsons MH, Sparrow E, Blumstein DT. A nose for death: integrating trophic and informational networks for conservation and management. Frontiers in Ecology and Evolution 2016. 4: , pp.124, doi: 10.3389/fevo.2016.00124

Kauffman, Brodie & Jules (2010) 

    Kauffman MJ, Brodie JF, Jules ES. Are wolves saving Yellowstone’s aspen? A landscape-level test of a behaviorally mediated trophic cascade. Ecology 2010. 91: 9, pp.2742-2755, doi: 10.1890/09-1949.1

King & Bradshaw (2010) 

    King JM, Bradshaw SD. Stress in an island kangaroo? The Barrow Island euro, Macropus robustus isabellinus. General and Comparative Endocrinology 2010. 167: 1, pp.60-67, doi: 10.1016/j.ygcen.2010.02.018

Klecka & Boukal (2014) 

    Klecka J, Boukal DS. The effect of habitat structure on prey mortality depends on predator and prey microhabitat use. Oecologia 2014. 176: 1, pp.183-191, doi: 10.1007/s00442-014-3007-6

Kloppers, St. Clair & Hurd (2005) 

    Kloppers EL, St. Clair CC, Hurd TE. Predator-resembling aversive conditioning for managing habituated wildlife. Ecology and Society 2005. 10: 1, pp.31, doi: 10.5751/ES-01293-100131

Knutie (2020) 

    Knutie SA. Food supplementation affects gut microbiota and immunological resistance to parasites in a wild bird species. 2020. , doi: 10.1111/1365-2664.13567

Kohl et al. (2018) 

    Kohl MT, Stahler DR, Metz MC, Forester JD, Kauffman MJ, Varley N, White PJ, Smith DW, MacNulty DR. Diel predator activity drives a dynamic landscape of fear. Ecological Monographs 2018. 88: 4, pp.638-652, doi: 10.1002/ecm.1313

Kotler & Brown (1988) 

    Kotler BP, Brown JS. Environmental heterogeneity and the coexistence of desert rodents. Annual Review of Ecology and Systematics 1988. 19: 1, pp.281-307, doi: 10.1146/

Kuijper et al. (2015) 

    Kuijper DP, Bubnicki JW, Churski M, Mols B, Van Hooft P. Context dependence of risk effects: wolves and tree logs create patches of fear in an old-growth forest. Behavioral Ecology 2015. 26: 6, pp.1558-1568, doi: 10.1093/beheco/arv107

Labar & Ledoux (2011) 

    Labar KS, Ledoux JE. Coping with danger: the neural basis of defensive behavior and fearful feelings. Comprehensive Physiology 2011. 8: , pp.139-154

Latham et al. (2011) 

    Latham ADM, Latham MC, Boyce MS, Boutin S. Movement responses by wolves to industrial linear features and their effect on woodland caribou in northeastern Alberta. Ecological Applications 2011. 21: 8, pp.2854-2865, doi: 10.1890/11-0666.1

Laundré, Hernández & Altendorf (2001) 

    Laundré JW, Hernández L, Altendorf KB. Wolves, elk, and bison: reestablishing the “landscape of fear” in Yellowstone National Park, USA. Canadian Journal of Zoology 2001. 79: 8, pp.1401-1409, doi: 10.1139/z01-094

Laundré, Hernández & Ripple (2010) 

    Laundré JW, Hernández L, Ripple WJ. The landscape of fear: ecological implications of being afraid. Open Ecology Journal 2010. 3: , pp.1-7

Laundré et al. (2014) 

    Laundré JW, Hernández L, Medina PL, Campanella A, López-Portillo J, González-Romero A, Grajales-Tam KM, Burke AM, Gronemeyer P, Browning DM. The landscape of fear: the missing link to understand top-down and bottom-up controls of prey abundance?. Ecology 2014. 95: 5, pp.1141-1152, doi: 10.1890/13-1083.1

Laws (2017) 

    Laws AN. Climate change effects on predator–prey interactions. Current Opinion in Insect Science 2017. 23: , pp.28-34, doi: 10.1016/j.cois.2017.06.010

Leahy et al. (2016) 

    Leahy L, Legge SM, Tuft K, McGregor HW, Barmuta LA, Jones ME, Johnson CN. Amplified predation after fire suppresses rodent populations in Australia’s tropical savannas. Wildlife Research 2016. 42: 8, pp.705-716, doi: 10.1071/WR15011

LeDoux (1996) 

    LeDoux JEThe emotional brain 1996. New York Simon and Schuster

LeDoux (2003) 

    LeDoux JE. The emotional brain, fear, and the amygdala. Cellular and Molecular Neurobiology 2003. 23: 4/5, pp.727-738, doi: 10.1023/A:1025048802629

Legge et al. (2019) 

    Legge S, Smith JG, James A, Tuft KD, Webb T, Woinarski JC. Interactions among threats affect conservation management outcomes: Livestock grazing removes the benefits of fire management for small mammals in Australian tropical savannas. Conservation Science and Practice 2019. 1: 7e52, doi: 10.1111/csp2.52

Leighton, Horrocks & Kramer (2010) 

    Leighton PA, Horrocks JA, Kramer DL. Conservation and the scarecrow effect: can human activity benefit threatened species by displacing predators?. Biological Conservation 2010. 143: 9, pp.2156-2163, doi: 10.1016/j.biocon.2010.05.028

Leo, Reading & Letnic (2015) 

    Leo V, Reading RP, Letnic M. Interference competition: odours of an apex predator and conspecifics influence resource acquisition by red foxes. Oecologia 2015. 179: 4, pp.1033-1040, doi: 10.1007/s00442-015-3423-2

Lima & Dill (1990) 

    Lima SL, Dill LM. Behavioral decisions made under the risk of predation: a review and prospectus. Canadian Journal of Zoology 1990. 68: 4, pp.619-640, doi: 10.1139/z90-092

Lima (1998) 

    Lima SL. Stress and decision making under the risk of predation: recent developments from behavioral, reproductive, and ecological perspectives. Advances in the Study of Behavior 1998. 27: , pp.215-290

Lima & Bednekoff (1999) 

    Lima SL, Bednekoff PA. Temporal variation in danger drives antipredator behavior: the predation risk allocation hypothesis. American Naturalist 1999. 153: 6, pp.649-659, doi: 10.1086/303202

Lone et al. (2014) 

    Lone K, Loe LE, Gobakken T, Linnell JD, Odden J, Remmen J, Mysterud A. Living and dying in a multi-predator landscape of fear: roe deer are squeezed by contrasting pattern of predation risk imposed by lynx and humans. Oikos 2014. 123: 6, pp.641-651, doi: 10.1111/j.1600-0706.2013.00938.x

Lowry, Lill & Wong (2013) 

    Lowry H, Lill A, Wong BBM. Behavioural responses of wildlife to urban environments. Biological Reviews 2013. 88: 3, pp.537-549, doi: 10.1111/brv.12012

Lyons et al. (2017) 

    Lyons J, Mastromonaco G, Edwards DB, Schulte-Hostedde AI. Fat and happy in the city: Eastern chipmunks in urban environments. Behavioral Ecology 2017. 28: 6, pp.1464-1471, doi: 10.1093/beheco/arx109

Ma, Becker & Kilgore (2009) 

    Ma Z, Becker DR, Kilgore MA. Assessing cumulative impacts within state environmental review frameworks in the United States. Environmental Impact Assessment Review 2009. 29: 6, pp.390-398, doi: 10.1016/j.eiar.2009.03.004

MacDougall-Shackleton et al. (2019) 

    MacDougall-Shackleton SA, Bonier F, Romero LM, Moore IT. Glucocorticoids and “stress” are not synonymous. Integrative Organismal Biology 2019. 1: 1, pp.obz017, doi: 10.1093/iob/obz017

Madsen, Carroll & Moore Brands (2010) 

Malcolm et al. (2014) 

    Malcolm KD, McShea WJ, Garshelis DL, Luo SJ, Van Deelen TR, Liu F, Li S, Miao L, Wang D, Brown JL. Increased stress in Asiatic black bears relates to food limitation, crop raiding, and foraging beyond nature reserve boundaries in China. Global Ecology and Conservation 2014. 2: , pp.267-276, doi: 10.1016/j.gecco.2014.09.010

Manuck et al. (1988) 

    Manuck SB, Kaplan JR, Adams MR, Clarkson TB. Studies of psychosocial influences on coronary artery atherogenesis in cynomolgus monkeys. Health Psychology 1988. 7: 2, pp.113-124, doi: 10.1037/0278-6133.7.2.113

Maren (2001) 

Mason (1971) 

    Mason JW. A re-evaluation of the concept of ‘non-specificity’ in stress theory. Journal of Psychiatric Research 1971. 8: 3–4, pp.323-333, doi: 10.1016/0022-3956(71)90028-8

McCauley, Jenkins & Quintana-Ascencio (2013) 

    McCauley LA, Jenkins DG, Quintana-Ascencio PF. Isolated wetland loss and degredation over two decades in an increasingly urbanised landscape. Wetlands 2013. 33: 1, pp.117-127, doi: 10.1007/s13157-012-0357-x

McClennen et al. (2001) 

    McClennen NA, Wigglesworth RR, Anderson SH, Wachob DG. The effect of suburban and agricultural development on the activity patterns of coyotes (Canis latrans). American Midland Naturalist 2001. 146: 1, pp.27-37, doi: 10.1674/0003-0031(2001)146[0027:TEOSAA]2.0.CO;2

McComb et al. (2019) 

    McComb LB, Lentini PE, Harley DK, Lumsden LF, Antrobus JS, Eyre AC, Briscoe NJ. Feral cat predation on Leadbeater’s possum (Gymnobelideus leadbeateri) and observations of arboreal hunting at nest boxes. Australian Mammalogy 2019. 41: 2, pp.262-265, doi: 10.1071/AM18010

McDonnell & Hahs (2015) 

    McDonnell MJ, Hahs AK. Adaptation and adaptedness of organisms to urban environments. Annual Review of Ecology, Evolution, and Systematics 2015. 46: 1, pp.261-280, doi: 10.1146/annurev-ecolsys-112414-054258

McEwen & Stellar (1993) 

    McEwen BS, Stellar E. Stress and the individual: mechanisms leading to disease. Archives of Internal Medicine 1993. 153: 18, pp.2093-2101, doi: 10.1001/archinte.1993.00410180039004

McEwen & Wingfield (2003) 

    McEwen BS, Wingfield JC. The concept of allostasis in biology and biomedicine. Hormones and Behavior 2003. 43: 1, pp.2-15, doi: 10.1016/S0018-506X(02)00024-7

McEwen (2004) 

    McEwen BS. Protection and damage from acute and chronic stress: allostasis and allostatic overload and relevance to the pathophysiology of psychiatric disorders. Annals of the New York Academy of Sciences 2004. 1032: 1, pp.1-7, doi: 10.1196/annals.1314.001

McKinney (2006) 

    McKinney ML. Urbanization as a major cause of biotic homogenization. Biological Conservation 2006. 127: 3, pp.247-260, doi: 10.1016/j.biocon.2005.09.005

McMahon et al. (2018) 

    McMahon JD, Lashley MA, Brooks CP, Barton BT. Covariance between predation risk and nutritional preferences confounds interpretations of giving-up density experiments. Ecology 2018. 99: 7, pp.1517-1522, doi: 10.1002/ecy.2365

Mella, Banks & McArthur (2014) 

    Mella VSA, Banks PB, McArthur C. Negotiating multiple cues of predation risk in a landscape of fear: what scares free-ranging brushtail possums?. Journal of Zoology 2014. 294: 1, pp.22-30, doi: 10.1111/jzo.12146

Mineka (1979) 

    Mineka S. The role of fear in theories of avoidance learning, flooding, and extinction. Psychological Bulletin 1979. 86: 5, pp.985-1010, doi: 10.1037/0033-2909.86.5.985

Mineur, Belzung & Crusio (2006) 

    Mineur YS, Belzung C, Crusio WE. Effects of unpredictable chronic mild stress on anxiety and depression-like behavior in mice. Behavioural Brain Research 2006. 175: 1, pp.43-50, doi: 10.1016/j.bbr.2006.07.029

Møller (2009) 

    Møller AP. Successful city dwellers: a comparative study of the ecological characteristics of urban birds in the Western Palearctic. Oecologia 2009. 159: 4, pp.849-858, doi: 10.1007/s00442-008-1259-8

Morgan et al. (2009) 

    Morgan SA, Hansen CM, Ross JG, Hickling GJ, Ogilvie SC, Paterson AM. Urban cat (Felis catus) movement and predation activity associated with a wetland reserve in New Zealand. Wildlife Research 2009. 36: 7, pp.574-580, doi: 10.1071/WR09023

Murray et al. (2016) 

    Murray MH, Becker DJ, Hall RJ, Herandez SM. Wildlife health and supplemental feeding: a review and management recommendations. Biological Conservation 2016. 204: , pp.163-174, doi: 10.1016/j.biocon.2016.10.034

Navara & Nelson (2007) 

    Navara KJ, Nelson RJ. The dark side of light at night: physiological, epidemiological, and ecological consequences. Journal of Pineal Research 2007. 43: 3, pp.215-224, doi: 10.1111/j.1600-079X.2007.00473.x

Newsome et al. (2014) 

    Newsome TM, Ballard GA, Fleming PJ, Van de Ven R, Story GL, Dickman CR. Human-resource subsidies alter the dietary preferences of a mammalian top predator. Oecologia 2014. 175: 1, pp.139-150, doi: 10.1007/s00442-014-2889-7

Newsome et al. (2015) 

    Newsome TM, Dellinger JA, Pavey CR, Ripple WJ, Shores CR, Wirsing AJ, Dickman CR. The ecological effects of providing resource subsidies to predators. Global Ecology and Biogeography 2015. 24: 1, pp.1-11, doi: 10.1111/geb.12236

Newsome et al. (2017) 

    Newsome T, Van Eeden L, Lazenby B, Dickman C. Does culling work?. Australasian Science 2017. 38: 1, pp.28-30

Nersesian, Banks & McArthur (2012) 

    Nersesian CL, Banks PB, McArthur C. Behavioural responses to indirect and direct predator cues by a mammalian herbivore, the common brushtail possum. Behavioral Ecology and Sociobiology 2012. 66: 1, pp.47-55, doi: 10.1007/s00265-011-1250-y

Norton (2009) 

    Norton DA. Species invasions and the limits to restoration: learning from the New Zealand experience. Science 2009. 325: 5940, pp.569-571, doi: 10.1126/science.1172978

Öhman (2000) 

    Öhman AFink G. Fear. Encyclopedia of Stress 2000. 2: , pp.111-116

Otto (2018) 

    Otto SP. Adaptation, speciation and extinction in the Anthropocene. Proceedings of the Royal Society B: Biological Sciences 2018. 285: 1891, pp.20182047, doi: 10.1098/rspb.2018.2047

Palme (2019) 

    Palme R. Non-invasive measurement of glucocorticoids: advances and problems. Physiology & Behaviour 2019. 199: , pp.229-243, doi: 10.1016/j.physbeh.2018.11.021

Palmer, Menninger & Bernhardt (2010) 

    Palmer MA, Menninger HL, Bernhardt E. River restoration, habitat heterogeneity and biodiversity: a failure of theory or practice?. Freshwater Biology 2010. 55: , pp.205-222, doi: 10.1111/j.1365-2427.2009.02372.x

Parsons & Blumstein (2010) 

    Parsons MH, Blumstein DT. Familiarity breeds contempt: kangaroos persistently avoid areas with experimentally deployed dingo scents. PLOS ONE 2010. 5: 5, pp.5e10403

Parsons et al. (2017) 

    Parsons MH, Apfelbach R, Banks PB, Cameron EZ, Dickman CR, Frank AS, Jones ME, McGregor IS, McLean S, Müller-Schwarze D, Sparrow EE, Blumstein DT. Biologically meaningful scents: a framework for understanding predator–prey research across disciplines. Biological Reviews 2017. 93: 1, pp.98-114, doi: 10.1111/brv.12334

Parris (2016) 

    Parris KMEcology of urban environments 2016. New Jersey John Wiley and Sons

Patten & Burger (2018) 

    Patten MA, Burger JC. Reserves as double-edged sword: avoidance behavior in an urban-adjacent wildland. Biological Conservation 2018. 218: , pp.233-239, doi: 10.1016/j.biocon.2017.12.033

Pianka (2011) 

    Pianka EREvolutionary ecology 2011. Siskiyou County Eric R. Pianka

Pickett et al. (2001) 

    Pickett ST, Cadenasso ML, Grove JM, Nilon CH, Pouyat RV, Zipperer WC, Costanza R. Urban ecological systems: linking terrestrial ecological, physical, and socioeconomic components of metropolitan areas. Annual Review of Ecology and Systematics 2001. 32: 1, pp.127-157, doi: 10.1146/annurev.ecolsys.32.081501.114012

Pitkanen (2000) 

    Pitkanen AConnectivity of the rat amygdaloid complex 2000. The amygdala: a functional analysisOxford Oxford University Press, pp.31-115

Polis et al. (1998) 

Price & Banks (2018) 

    Price CJ, Banks PB. Habitat augmentation for introduced urban wildlife: the use of piles of railway sleepers as refuge for introduced black rats Rattus rattus. Australian Zoologist 2018. 39: 3, pp.513-519, doi: 10.7882/AZ.2017.029

Prugh et al. (2009) 

    Prugh LR, Stoner CJ, Epps CW, Bean WT, Ripple WJ, Laliberte AS, Brashares JS. The rise of the mesopredator. BioScience 2009. 59: 9, pp.779-791, doi: 10.1525/bio.2009.59.9.9

Rayner et al. (2007) 

    Rayner MJ, Hauber ME, Imber MJ, Stamp RK, Clout MN. Spatial heterogeneity of mesopredator release within an oceanic island system. Proceedings of the National Academy of Sciences USA 2007. 104: 52, pp.20862-20865, doi: 10.1073/pnas.0707414105

Rehnus, Wehrle & Palme (2014) 

    Rehnus M, Wehrle M, Palme R. Mountain hares Lepus timidus and tourism: stress events and reactions. Journal of Applied Ecology 2014. 51: 1, pp.6-12, doi: 10.1111/1365-2664.12174

Rescorla & Solomon (1967) 

    Rescorla RA, Solomon RL. Two-process learning theory: relationships between Pavlovian conditioning and instrumental learning. Psychological Review 1967. 74: 3, pp.151-182, doi: 10.1037/h0024475

Rieucau, Vickery & Doucet (2009) 

    Rieucau G, Vickery WL, Doucet GJ. A patch use model to separate effects of foraging costs on giving-up densities: an experiment with white-tailed deer (Odocoileus virginianus). Behavioral Ecology and Sociobiology 2009. 63: 6, pp.891-897, doi: 10.1007/s00265-009-0732-7

Riley et al. (2003) 

    Riley SP, Sauvajot RM, Fuller TK, York EC, Kamradt DA, Bromley C, Wayne RK. Effects of urbanization and habitat fragmentation on bobcats and coyotes in southern California. Conservation Biology 2003. 17: 2, pp.566-576, doi: 10.1046/j.1523-1739.2003.01458.x

Riley et al. (2014) 

    Riley S, Brown J, Sikich J, Schoonmaker C, Boydston EMcCleery R, Moorman C, Peterson M. Wildlife friendly roads: the impacts of roads on wildlife in urban areas and potential remedies. Urban Wildlife Conservation 2014. Boston Springer, pp.323-360

Ripple et al. (2014) 

    Ripple WJ, Estes JA, Beschta RL, Wilmers CC, Ritchie EG, Hebblewhite M, Berger J, Elmhagen B, Letnic M, Nelson MP, Schmitz OJ, Smith DW, Wallach AD, Wirsing AJ. Status and ecological effects of the world’s largest carnivores. Science 2014. 343: 6167, pp.1241484, doi: 10.1126/science.1241484

Ritchie & Johnson (2009) 

    Ritchie EG, Johnson CN. Predator interactions, mesopredator release and biodiversity conservation. Ecology Letters 2009. 12: 9, pp.982-998, doi: 10.1111/j.1461-0248.2009.01347.x

Rodríguez, Andrén & Jansson (2001) 

    Rodríguez A, Andrén H, Jansson G. Habitat-mediated predation risk and decision making of small birds at forest edges. Oikos 2001. 95: 3, pp.383-396, doi: 10.1034/j.1600-0706.2001.950303.x

Rodrigues, LeDoux & Sapolsky (2009) 

    Rodrigues SM, LeDoux JE, Sapolsky RM. The influence of stress hormones on fear circuitry. Annual Review of Neuroscience 2009. 32: 1, pp.289-313, doi: 10.1146/annurev.neuro.051508.135620

Rodriguez, Hausberger & Clergeau (2010) 

    Rodriguez A, Hausberger M, Clergeau P. Flexibility in European starlings’ use of social information: experiments with decoys in different populations. Animal Behaviour 2010. 80: 6, pp.965-973, doi: 10.1016/j.anbehav.2010.08.010

Romero (2004) 

    Romero LM. Physiological stress in ecology: lessons from biomedical research. Trends in Ecology & Evolution 2004. 19: 5, pp.249-255, doi: 10.1016/j.tree.2004.03.008

Romero, Dickens & Cyr (2009) 

    Romero LM, Dickens MJ, Cyr NE. The reactive scope model—a new model integrating homeostasis, allostasis, and stress. Hormones and Behavior 2009. 55: 3, pp.375-389, doi: 10.1016/j.yhbeh.2008.12.009

Roozendaal (2000) 

    Roozendaal B. Glucocorticoids and the regulation of memory consolidation. Psychoneuroendocrinology 2000. 25: 3, pp.213-238, doi: 10.1016/S0306-4530(99)00058-X

Rosen & Schulkin (1998) 

    Rosen JB, Schulkin J. From normal fear to pathological anxiety. Psychological Review 1998. 105: 2, pp.325-350, doi: 10.1037/0033-295X.105.2.325

Rosen (2004) 

    Rosen JB. The neurobiology of conditioned and unconditioned fear: a neurobehavioral system analysis of the amygdala. Behavioral and Cognitive Neuroscience Reviews 2004. 3: 1, pp.23-41, doi: 10.1177/1534582304265945

Rosen & Schulkin (2004) 

    Rosen JB, Schulkin JSchulkin J. Adaptive fear, allostasis, and the pathology of anxiety and depression. Allostasis, Homeostasis and the Costs of Physiological Adaptation 2004. , pp.164-227

Santini et al. (2019) 

    Santini L, González-Suárez M, Russo D, Gonzalez-Voyer A, Von Hardenberg A, Ancillotto L. One strategy does not fit all: determinants of urban adaptation in mammals. Ecology Letters 2019. 22: 2, pp.365-376, doi: 10.1111/ele.13199

Santos et al. (2014) 

    Santos X, Mateos E, Bros V, Brotons L, De Mas E, Herraiz JA, Herrando S, Miňo À., Olmo-Vidal JM, Quesada J, Ribes J, Sabaté S, Sauras-Yera T, Serra A, Vallejo VR, Viňolas A. Is response to fire influenced by dietary specialization and mobility? A comparative study with multiple animal assemblages. PLOS ONE 2014. 9: 2e88224, doi: 10.1371/journal.pone.0088224

Salo et al. (2007) 

    Salo P, Korpimäki E, Banks PB, Nordström M, Dickman CR. Alien predators are more dangerous than native predators to prey populations. Proceedings of the Royal Society B: Biological Sciences 2007. 274: 1615, pp.1237-1243, doi: 10.1098/rspb.2006.0444

Sapolsky, Romero & Munck (2000) 

    Sapolsky RM, Romero LM, Munck AU. How do glucocorticoids influence stress responses? Integrating permissive, suppressive, stimulatory, and preparative actions. Endocrine Reviews 2000. 21: 1, pp.55-89

Say-Sallaz et al. (2019) 

    Say-Sallaz E, Chamaillé-Jammes S, Fritz H, Valeix M. Non-consumptive effects of predation in large terrestrial mammals: Mapping our knowledge and revealing the tip of the iceberg. Biological Conservation 2019. 235: , pp.36-52, doi: 10.1016/j.biocon.2019.03.044

Schell et al. (2018) 

    Schell CJ, Young JK, Lonsdorf EV, Santymire RM, Mateo JM. Parental habituation to human disturbance over time reduces fear of humans in coyote offspring. Ecology and Evolution 2018. 8: 24, pp.12965-12980

Schmidt & Kuijper (2015) 

    Schmidt K, Kuijper DPJ. A “death trap” in the landscape of fear. Mammal Research 2015. 60: 4, pp.275-284, doi: 10.1007/s13364-015-0229-x

Schmitz, Beckerman & O’Brien (1997) 

Schmitz, Krivan & Ovadia (2004) 

    Schmitz OJ, Krivan V, Ovadia O. Trophic cascades: the primacy of trait-mediated indirect interactions. Ecology Letters 2004. 7: 2, pp.153-163, doi: 10.1111/j.1461-0248.2003.00560.x

Schmitz (2008) 

    Schmitz OJ. Effects of predator hunting mode on grassland ecosystem function. Science 2008. 319: 5865, pp.952-954, doi: 10.1126/science.1152355

Schulkin, Thompson & Rosen (2003) 

    Schulkin J, Thompson BL, Rosen JB. Demythologizing the emotions: adaptation, cognition, and visceral representations of emotion in the nervous system. Brain and Cognition 2003. 52: 1, pp.15-23, doi: 10.1016/S0278-2626(03)00004-6

Selye (1936) 

    Selye H. A syndrome produced by diverse noxious agents. Nature 1936. 138: 3479, pp.32-39, doi: 10.1038/138032a0

Shannon et al. (2016) 

    Shannon G, McKenna MF, Angeloni LM, Crooks KR, Fristrup KM, Brown E, Warner KA, Nelson MD, White C, Briggs J, McFarland S, Wittemyer G. A synthesis of two decades of research documenting the effects of noise on wildlife. Biological Reviews 2016. 91: 4, pp.982-1005, doi: 10.1111/brv.12207

Sheriff et al. (2011) 

    Sheriff MJ, Dantzer B, Delehanty B, Palme R, Boonstra R. Measuring stress in wildlife: techniques for quantifying glucocorticoids. Oecologia 2011. 166: 4, pp.869-887, doi: 10.1007/s00442-011-1943-y

Sherman (1984) 

    Sherman LJ. The effects of patchy food availability on nest-site selection and movement patterns of reproductively active female meadow voles Microtus pennsylvanicus. Ecography 1984. 7: 3, pp.294-299, doi: 10.1111/j.1600-0587.1984.tb01134.x

Shochat, Lerman & Fernández-Juricic (2010) 

    Shochat E, Lerman S, Fernández-Juricic EAitkenhead-Peterson J, Volder A. Birds in urban ecosystems: population dynamics, community structure, biodiversity, and conservation. Urban Ecosystem Ecology 2010. 55: , pp.75-86

Shrader et al. (2008) 

    Shrader AM, Brown JS, Kerley GI, Kotler BP. Do free-ranging domestic goats show ‘landscapes of fear’? Patch use in response to habitat features and predator cues. Journal of Arid Environments 2008. 72: 10, pp.1811-1819, doi: 10.1016/j.jaridenv.2008.05.004

Sinclair & Arcese (1995) 

    Sinclair ARE, Arcese P. Population consequences of predation-sensitive foraging: the Serengeti wildebeest. Ecology 1995. 76: 3, pp.882-891, doi: 10.2307/1939353

Smit & Spaling (1995) 

    Smit B, Spaling H. Methods for cumulative effects assessment. Environmental Impact Assessment Review 1995. 15: 1, pp.81-106, doi: 10.1016/0195-9255(94)00027-X

Smith et al. (2017) 

    Smith JA, Suraci JP, Clinchy M, Crawford A, Roberts D, Zanette LY, Wilmers CC. Fear of the human ‘super predator’ reduces feeding time in large carnivores. Proceedings of the Royal Society B: Biological Sciences 2017. 284: 1857, pp.20170433, doi: 10.1098/rspb.2017.0433

Smith et al. (2019) 

    Smith JA, Donadio E, Pauli JN, Sheriff MJ, Middleton AD. Integrating temporal refugia into landscapes of fear: prey exploit predator downtimes to forage in risky places. Oecologia 2019. 189: 4, pp.883-890, doi: 10.1007/s00442-019-04381-5

Snell-Rood & Wick (2013) 

    Snell-Rood EC, Wick N. Anthropogenic environments exert variable selection on cranial capacity in mammals. Proceedings of the Royal Society B: Biological Sciences 2013. 280: 1769, pp.20131384, doi: 10.1098/rspb.2013.1384

Soso et al. (2014) 

    Soso SB, Koziel JA, Johnson A, Lee YJ, Fairbanks WS. Analytical methods for chemical and sensory characterization of scent-markings in large wild mammals: a review. Sensors 2014. 14: 3, pp.4428-4465, doi: 10.3390/s140304428

Spencer, Crowther & Dickman (2014) 

    Spencer EE, Crowther MS, Dickman CR. Risky business: do native rodents use habitat and odor cues to manage predation risk in Australian deserts?. PLOS ONE 2014. 9: 2e90566, doi: 10.1371/journal.pone.0090566

Sterling & Eyer (1988) 

    Sterling P, Eyer JFisher K, Reason J. Allostasis: a new paradigm to explain arousal pathology. Handbook of Life Stress, Cognition and Health 1988. New York John Wiley & sons, pp.629-649

Stillfried et al. (2017) 

    Stillfried M, Fickel J, Börner K, Wittstatt U, Heddergott M, Ortmann S, Kramer-Schadt S, Frantz AC. Do cities represent sources, sinks or isolated islands for urban wild boar population structure?. Journal of Applied Ecology 2017. 54: 1, pp.272-281, doi: 10.1111/1365-2664.12756

Suraci et al. (2019) 

    Suraci JP, Clinchy M, Zanette LY, Wilmers CC. Fear of humans as apex predators has landscape-scale impacts from mountain lions to mice. Ecology Letters 2019. 22: 10, pp.1578-1586, doi: 10.1111/ele.13344

Støen et al. (2015) 

    Støen OG, Ordiz A, Evans AL, Laske TG, Kindberg J, Fröbert O, Swenson JE, Arnemo JM. Physiological evidence for a human-induced landscape of fear in brown bears (Ursus arctos). Physiology & Behavior 2015. 152: A, pp.244-248, doi: 10.1016/j.physbeh.2015.09.030

Sweitzer (1996) 

    Sweitzer RA. Predation or starvation: consequences of foraging decisions by porcupines (Erethizon dorsatum). Journal of Mammalogy 1996. 77: 4, pp.1068-1077, doi: 10.2307/1382787

Tablado & Jenni (2017) 

    Tablado Z, Jenni L. Determinants of uncertainty in wildlife responses to human disturbance. Biological Reviews 2017. 92: 1, pp.216-233, doi: 10.1111/brv.12224

Taylor-Brown et al. (2019) 

    Taylor-Brown A, Booth R, Gillett A, Mealy E, Ogbourne SM, Polkinghorne A, Conroy GC. The impact of human activities on Australian wildlife. PLOS ONE 2019. 14: 1e0206958, doi: 10.1371/journal.pone.0206958

Tews et al. (2004) 

    Tews J, Brose U, Grimm V, Tielbörger K, Wichmann MC, Schwager M, Jeltsch F. Animal species diversity driven by habitat heterogeneity/diversity: the importance of keystone structures. Journal of Biogeography 2004. 31: 1, pp.79-92, doi: 10.1046/j.0305-0270.2003.00994.x

Therivel & Ross (2007) 

    Therivel R, Ross B. Cumulative effects assessment: does scale matter?. Environmental Impact Assessment Review 2007. 27: 5, pp.365-385, doi: 10.1016/j.eiar.2007.02.001

Threlfall et al. (2016) 

    Threlfall CG, Williams NS, Hahs AK, Livesley SJ. Approaches to urban vegetation management and the impacts on urban bird and bat assemblages. Landscape and Urban Planning 2016. 153: , pp.28-39, doi: 10.1016/j.landurbplan.2016.04.011

Tigas, Van Vuren & Sauvajot (2002) 

    Tigas LA, Van Vuren DH, Sauvajot RM. Behavioral responses of bobcats and coyotes to habitat fragmentation and corridors in an urban environment. Biological Conservation 2002. 108: 3, pp.299-306, doi: 10.1016/S0006-3207(02)00120-9

Tooby & Cosmides (1990) 

    Tooby J, Cosmides L. The past explains the present: emotional adaptations and the structure of ancestral environments. Ethology and Sociobiology 1990. 11: 4–5, pp.375-424, doi: 10.1016/0162-3095(90)90017-Z

Thomson et al. (2010) 

    Thomson RL, Tomás G, Forsman JT, Broggi J, Mönkkönen M. Predator proximity as a stressor in breeding flycatchers: mass loss, stress protein induction, and elevated provisioning. Ecology 2010. 91: 6, pp.1832-1840, doi: 10.1890/09-0989.1

Threlfall, Law & Banks (2012) 

    Threlfall CG, Law B, Banks PB. Influence of landscape structure and human modifications on insect biomass and bat foraging activity in an urban landscape. PLOS ONE 2012. 7: 6e38800, doi: 10.1371/journal.pone.0038800

Towerton et al. (2011) 

    Towerton AL, Penman TD, Kavanagh RP, Dickman CR. Detecting pest and prey responses to fox control across the landscape using remote cameras. Wildlife Research 2011. 38: 3, pp.208-220, doi: 10.1071/WR10213

Travers et al. (2010) 

    Travers M, Clinchy M, Zanette L, Boonstra R, Williams TD. Indirect predator effects on clutch size and the cost of egg production. Ecology Letters 2010. 13: 8, pp.980-988

Trussell, Ewanchuk & Matassa (2006) 

    Trussell GC, Ewanchuk PJ, Matassa CM. Habitat effects on the relative importance of trait-and density-mediated indirect interactions. Ecology Letters 2006. 9: 11, pp.1245-1252, doi: 10.1111/j.1461-0248.2006.00981.x

Turcotte & Desrochers (2003) 

    Turcotte Y, Desrochers A. Landscape-dependent response to predation risk by forest birds. Oikos 2003. 100: 3, pp.614-618, doi: 10.1034/j.1600-0706.2003.12234.x

Van Buskirk et al. (2002) 

    Van Buskirk J, Müller C, Portmann A, Surbeck M. A test of the risk allocation hypothesis: tadpole responses to temporal change in predation risk. Behavioral Ecology 2002. 13: 4, pp.526-530, doi: 10.1093/beheco/13.4.526

Van Der Merwe & Brown (2008) 

    Van Der Merwe M, Brown JS. Mapping the landscape of fear of the cape ground squirrel (Xerus inauris). Journal of Mammalogy 2008. 89: 5, pp.1162-1169, doi: 10.1644/08-MAMM-A-035.1

Vijayakrishnan et al. (2018) 

    Vijayakrishnan S, Kumar MA, Umapathy G, Kumar V, Sinha A. Physiological stress responses in wild Asian elephants Elephas maximus in a human-dominated landscape in the Western Ghats, southern India. General and Comparative Endocrinology 2018. 266: , pp.150-156, doi: 10.1016/j.ygcen.2018.05.009

Wallace & Rosen (2000) 

    Wallace KJ, Rosen JB. Predator odor as an unconditioned fear stimulus in rats: elicitation of freezing by trimethylthiazoline, a component of fox feces. Behavioral Neuroscience 2000. 114: 5, pp.912-922, doi: 10.1037/0735-7044.114.5.912

Wallace & Rosen (2001) 

    Wallace KJ, Rosen JB. Neurotoxic lesions of the lateral nucleus of the amygdala decrease conditioned fear but not unconditioned fear of a predator odor: comparison with electrolytic lesions. Journal of Neuroscience 2001. 21: 10, pp.3619-3627, doi: 10.1523/JNEUROSCI.21-10-03619.2001

Warburton & Norton (2009) 

    Warburton B, Norton BG. Towards a knowledge-based ethic for lethal control of nuisance wildlife. Journal of Wildlife Management 2009. 73: 1, pp.158-164, doi: 10.2193/2007-313

Weissburg, Smee & Ferner (2014) 

    Weissburg M, Smee DL, Ferner MC. The sensory ecology of nonconsumptive predator effects. The American Naturalist 2014. 184: 2, pp.141-157, doi: 10.1086/676644

Werner & Peacor (2003) 

Western (2001) 

    Western D. Human-modified ecosystems and future evolution. Proceedings of the National Academy of Sciences USA 2001. 98: 10, pp.5458-5465, doi: 10.1073/pnas.101093598

Willems & Hill (2009) 

    Willems EP, Hill RA. Predator-specific landscapes of fear and resource distribution: effects on spatial range use. Ecology 2009. 90: 2, pp.546-555, doi: 10.1890/08-0765.1

Wingfield & Kitaysky (2002) 

    Wingfield JC, Kitaysky AS. Endocrine responses to unpredictable environmental events: stress or anti-stress hormones?. Integrative and Comparative Biology 2002. 42: 3, pp.600-609, doi: 10.1093/icb/42.3.600

Woinarski, Burbidge & Harrison (2015) 

    Woinarski JC, Burbidge AA, Harrison PL. Ongoing unraveling of a continental fauna: decline and extinction of Australian mammals since European settlement. Proceedings of the National Academy of Sciences USA 2015. 112: 15, pp.4531-4540, doi: 10.1073/pnas.1417301112

Yates, Russell & Maran (1971) 

    Yates FE, Russell SM, Maran JW. Brain-adenohypophysial communication in mammals. Annual Review of Physiology 1971. 33: 1, pp.393-444, doi: 10.1146/

Zanette et al. (2011) 

    Zanette LY, White AF, Allen MC, Clinchy M. Perceived predation risk reduces the number of offspring songbirds produce per year. Science 2011. 334: 6061, pp.1398-1401, doi: 10.1126/science.1210908

Zbyryt et al. (2017) 

    Zbyryt A, Bubnicki JW, Kuijper DPJ, Dehnhard M, Churski M, Schmidt K, Wong B. Do wild ungulates experience higher stress with humans than with large carnivores?. Behavioral Ecology 2017. 29: 1, pp.19-30, doi: 10.1093/beheco/arx142 and stressing in predator–prey ecology: considering the twin stressors of predators and people on mammals&author=Loren L. Fardell,Chris R. Pavey,Christopher R. Dickman,Max Lambert,&keyword=Fear,Stress,Anthropogenic,Urban,Endocrinology,Ethology,Landscape of fear,Cumulative,CEA,Predator,&subject=Animal Behavior,Conservation Biology,Ecology,Coupled Natural and Human Systems,Environmental Impacts,