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Loss of an apex predator in the wild induces physiological changes in prey

Citation

Hammerschlag, Neil et al. (2022), Loss of an apex predator in the wild induces physiological changes in prey, Dryad, Dataset, https://doi.org/10.5061/dryad.jwstqjq9r

Abstract

Predators can impact prey via predation or risk effects, which can initiate trophic cascades. Given widespread population declines of apex predators, understanding and predicting the associated ecological consequences is a priority. When predation risk is relatively unpredictable or uncontrollable by prey, the loss of predators is hypothesized to release prey from stress; however, there are few tests of this hypothesis in the wild. A well-studied predator-prey system between white sharks (Carcharodon carcharias) and Cape fur seals (Arctocephalus pusillus pusillus) in False Bay, South Africa has previously demonstrated elevated fecal glucocorticoid metabolite concentrations (fGCM) in seals exposed to high levels of predation risk from white sharks. A recent decline and disappearance of white sharks from the system has coincided with a pronounced decrease in seal fGCM concentrations. Seals have concurrently been rafting farther from shore and over deeper water, a behavior that would have previously rendered them vulnerable to attack. These results show rapid physiological and behavioral responses by seals to release from predation stress. To our knowledge, this represents the first demonstration in the wild of physiological changes in prey from predator decline, and such responses are likely to increase given the scale and pace of apex predator declines globally.

Methods

Boat-based surveys

Between 2000 and 2020, white shark relative abundance and predatory activity during winter months at Seal Island were monitored daily from standardized boat-based observation surveys (as described in Hammerschlag et al. 2017; see electronic supplementary material). Water temperatures (°C) were recorded using the vessel’s onboard temperature sensor and the following environmental variables were estimated: percentage cloud cover, wind speed (kt) and direction, swell height (m), and water visibility (m). Additionally, the relative distances of rafting seal groups off the Island’s perimeter were estimated according to one of three distance categories: (1) seals rafting < 5 m from the Island; (2) seals rafting > 5 and < 10 m from the Island; and (3) seals rafting > 10 m from the Island perimeter.

Between 07:00 and 09:30 h, instances of predation by white sharks on Cape fur seals were recorded following the approach outlined in Fallows et al. 2016 (see electronic supplementary material). The duration of each observational period along with the number of predatory attacks by sharks on seals during this period were recorded to calculate white shark predation rates (i.e. number of predation events per hour). After 09:30 h, the vessel anchored and conducted standardized boat-based baited surveys of white sharks following the approach described in Hammerschlag et al. 2019 (see electronic supplementary material). Between 10:00 and 12:00 h, sharks were attracted to the boat using a large tuna head and a seal decoy. Individual sharks were identified based on a combination of unique scarring, presence/absence of claspers, and individual variation in pigmentation patterns. The duration of each baited survey was recorded, along with the number of individuals observed. The number of different individual sharks observed per hour during these baited surveys were calculated as a metric of relative white shark abundance.

Seal fecal sample collection and immunoassay

Seal fecal samples were collected from Seal Island during 2014 and 2015 prior to the onset of shark decline (results published in Hammerschlag et al. 2017) and during the decline and eventual disappearance of white sharks from the study site in 2016, 2017, and 2019. To enable scats of different individuals, ~20 g  of sample was collected from clearly distinct defecation piles. Each sample was placed in 50 ml screw-lid vials and frozen within 1-2 hours of collection, which occurred between sunrise and noon.

Steroid hormone metabolites were extracted from fecal samples by drying the scat and boiling a known mass of dry feces in ethanol following Creel et al. 2009. Glucocorticoid metabolite concentrations in fecal extracts (fGCM) were analyzed as detailed in Hammerschlag et al. 2017 and measured using an enzyme-linked immunoassay with a cortisol antibody (Enzo Life Sciences ADI-900-071; see electronic supplementary material for details on procedural validation). We expressed fGCM concentrations as nanograms of cortisol immunoreactivity per gram of dry feces.

Statistical analysis

Previous analyses applied to annual trends in white shark relative abundance data at the study site, collected between 2000 and 2018, revealed a significant change point in 2015, after which (2016 onwards) white shark relative abundance began to precipitously decline (Hammerschlag et al. 2019). Therefore, we classified the period prior to shark decline as the years 2000 to 2015 and the post-decline period as years 2016 through 2020.

To examine annual trends in white shark relative abundance and predation rates across the 2000–2020 time-series, we calculated the mean number of white sharks sighted per hour and the mean number of shark predations per hour, for each year, following the approach of Hammerschlag et al. 2019. To compare changes in seal behavior in relation to white shark relative abundance and predatory activity, we evaluated annual trends in seal rafting distance from the Island by calculating the mean daily rafting category for each year.

To compare seal stress responses to annual trends in white shark relative abundance and predatory activity, we calculated mean fGCM concentrations by sampling year and by period (pre-decline versus post-decline of white sharks).

Previous laboratory studies that have subjected sea lions (Eumetopias jubatus) to an adrenocorticotropic hormone (ACTH) challenge found a lag of up to 4 d between ACTH injection and peak fGCM (Hunt et al. 2004). Accordingly, here we considered that measured fGCM values reflected hormone values in seals based on stress experienced within the week prior. Indeed, Hammerschlag et al. 2017 found a very strong correlation between seal fGCM concentrations and mean predation rates (attacks/h) measured within the week prior to scat collections. Accordingly, here we used Spearman Correlation to test for a correlation between weekly shark attack rates and associated fGCM concentrations spanning the pre- and post- decline period. We also separately tested for correlations of seal fGCM levels against water temperature, wind speed, swell height, water visibility, and cloud cover. As in our analysis of the correlation between fGCM with predation rates, we used mean values of the environmental variables recorded during the previous week and up to the day of scat sampling in this analysis.

Because white sharks only actively prey on seals at Seal Island during winter months, we restricted analyses to data collected from May through September, such that all data reflected seal behavior and physiology during the season in which seals historically experienced high predation risk. All statistical analyses were performed in SAS with P < 0.05 used as a threshold for strong evidence of an effect.

Usage Notes

The files 'Shark_Sightings_MaytoSept_summarized.csv', 'Predations_MaytoSept_summarized.csv', and 'Seal_Rafting_MaytoSept_summarized.csv' were all used to create Figure 1A, 1B, and 1C, respectively in the manuscript.

The file 'fGCM_samples_raw_data.csv' was used to create Figure 2A in the manuscript, and the file "GW_Predations_7days_priorto_FGCM_collections_Environmental data.csv' was used to create Figure 2B.