Prey attracting but not avoiding predators suggests an asymmetric investment in the predation sequence

  1. Nicolas Ferry
  2. Christian Fiderer
  3. Anne Peters
  4. Axel Ballmann
  5. Marco Heurich

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Abstract

Understanding predator-prey interactions, particularly how species use space and time to influence encounter rates, is fundamental in community and behavioural ecology. However, for large, free-ranging animals, encounter rates are rarely quantified directly, because of logistical and methodological challenges associated with tracking both predators and prey simultaneously. Instead, studies commonly rely on proxies such as spatial or temporal overlap. While informative, these proxies provide only incomplete estimates of encounter rates because they typically consider only one dimension of the interaction process (spatial or temporal). Although camera traps cannot directly measure encounters among large free-roaming species, they offer the opportunity to quantify the proximal co-occurrence, i.e., the extent to which species tolerate or avoid one another’s proximity in space and time. We analysed data from a one-year study conducted across four German protected areas using 283 camera traps and applying recurrent event analysis to investigate interactions among three prey species, red deer ( Cervus elaphus) , roe deer ( Capreolus capreolus) , wild boar ( Sus scrofa ) and two large predators grey wolf ( Canis lupus) , and Eurasian lynx ( Lynx lynx ). Prey visitation rates were unaffected by predator presence, whereas wolves exhibited a strong attraction to prey, with visitation rates four to six times higher immediately after prey detections. The limited sample size prevented robust conclusions regarding Eurasian lynx responses. These findings point towards an asymmetry in the predation sequence (i.e., spatio-temporal proximity, encounter, ignorance or avoidance post-encounter, capture or escape from attack): Predators must succeed at every stage of the sequence to capture prey, while prey can avoid predation by disrupting the process at any single stage. Our results suggest that prey species do not necessarily reduce large-scale spatio-temporal proximity to predators and may instead rely on anti-predator responses occurring later in the predation sequence.

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  1. Peer Community in Ecology

    Predator–prey interactions are one of the core elements of ecological and behavioural research. They drive virtually all dynamic ecological and evolutionary processes, not only governing the relationship between two species and defining behavioural and social traits, but producing cascading effects across whole ecosystems. As a consequence they have been studied for decades, yet large knowledge gaps remain in how, mechanistically, predators and prey allocate space use and timing: prey to avoid being predated, predators to hunt successfully (Lima & Dill, 1990; Sih, 1984). This arms race, and the consequences that ensue, mesmerise.
    With camera traps, we obtain a minimally invasive insight into how wild animals allocate their time across space, and into where and when they can be encountered. The field has grown rapidly with the affordability of the devices and the use of image recognition and artificial intelligence, which allow rapid analysis of the large data volumes collected. Accordingly, the field is also in highly dynamic growth when it comes to analytical methods, that allow insights truly beginning to address some of the core questions in ecological research, such as predator–prey interactions.
    As someone working predominantly with GPS devices, I understand the limitations such interactions still pose when one tries to observe them through a Lagrangian sampling method. There is a blind spot that camera-trap studies can illuminate in the wild: the chances of quantitatively studying predator–prey interactions by attaching GPS devices to animals are vanishingly small, given the population sizes involved and the rarity of a marked predator encountering a marked prey while both are under surveillance. This is precisely where the present study (Ferry et al., 2026) closes a unique gap, showing how camera-trap studies, with their Eulerian observation approach, can perfectly complement studies in which we follow individuals rather than survey space.
    I accepted the role of recommender because, in an ideal world, we would combine the best methodological approaches to obtain a holistic perspective on what is, in fact, the core of wildlife ecology. So, beyond and above the findings of this specific study, I was drawn by how it showcases a complementarity and a strength in resolving an important question where other approaches cannot reach.
    Instead of the usual static descriptors (spatial overlap, occupancy, diel-activity overlap), or a time-sensitive but single-species activity analysis, Ferry et al. (2026) apply recurrent-event survival analysis — specifically piece-wise exponential additive mixed models (PAMM) — to their camera-trap detections (Ferry et al., 2024). In their design, each detection of a primary species opens a time window during which detections of the secondary species are treated as recurrent events, with censoring rules for confounding species, camera downtime, and a 30-day cap tied to olfactory-cue persistence. They thus recover a time course rather than a yes/no co-occurrence, a richer characterisation than the avoidance–attraction ratios that have dominated this kind of analysis (Niedballa et al., 2019; Dymit, 2025). On the basis of this quantification, they shed light on bidirectionality by running every pairing both ways (prey-after-predator and predator-after-prey), still uncommon in observational camera-trap work, and what surfaces an asymmetry. This asymmetry not only reflects the two sides of the same coin; it moves us from mapping the landscape of fear (Laundré et al., 2001) and the resource landscape to quantifying their temporal dynamics.
    This asymmetry, which I read more as a one-sided reaction than a true asymmetry, suggests that, along the predation sequence, a predator must win every stage, from detection through pursuit to kill, so it pays them to track prey actively. Prey, however, can break the chain at any single later stage (vigilance, flight, reduced visit duration), and so need not necessarily minimise fine-scale proximity. Indeed, controlled scent experiments show red deer can reduce visit duration in response to carnivore cues even without changing how often they visit (van Beeck Calkoen et al., 2021). This is an interesting finding with potentially stark consequences for the concept of the landscape of fear, and for how movement ecologists should reconsider the expected behavioural consequences and decision landscape of prey when they treat such landscapes as the simple inverse of the predators' resource landscape (Gaynor et al., 2019).
    The review process allowed the authors to refine some of their statistical analyses and adjust their claims to the results obtained. The addition of seasonal and daily control variables materially changed some of the outcomes and led to a more careful formulation of the interactions documented and their interpretation. The review also broadened the work to be more conservation-relevant, a timely emphasis, given the ongoing recovery of wolves and lynx across human-dominated Europe (Chapron et al., 2014) and helped it engage more accurately with previous, similar work. In general, it tightened the narrative and analytical positioning without changing the core.
    The reviewers appreciated the scale, the thoroughness, and the resulting solidity of the findings. What I liked most is how well the research question and the methodology fit together to close a gap no other method can fill in such a befitting manner. And it is, of course, intriguing to contemplate how what looks like two sides of the same coin turns out to be time-sensitive and possibly not quite the same, depending on whether the prey's or the predator's perspective is considered.

    References

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  2. Version published to 10.1101/2024.11.13.623348 on bioRxiv