Understanding the combined effects of multiple stressors: A new perspective on a longstanding challenge

Pirotta, Enrico; Thomas, Len; Costa, Daniel P.; Hall, Ailsa J.; Harris, Catriona M.; Harwood, John; Kraus, Scott D.; Miller, Patrick J. O.; Moore, Michael J.; Photopoulou, Theoni; Rolland, Rosalind M.; Schwacke, Lori H.; Simmons, Samantha E.; Southall, Brandon L.; Tyack, Peter L.

doi:10.1016/j.scitotenv.2022.153322

Cited by 88 publications

(86 citation statements)

References 128 publications

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“…Our results also support calls for more experimental evidence to characterise the functional relationships between stressors and response variables (Pirotta et al, 2022; Schäfer & Piggott, 2018). This requires experiments with treatments across gradients of stress – rather than in just two levels – to more accurately identify the processes that underpin how stressors interact (Jackson et al, 2021; Pirotta et al, 2022) and to predict the ecological outcomes of multiple stressors in natural ecosystems (also see Galic et al, 2018). Currently, most multiple stressor studies apply stressors at only two levels (excluding controls; Ostrowski et al, 2021).…”

Section: Discussionsupporting

confidence: 89%

“…novel combinations of stressors or stressor magnitudes – Côté et al, 2016). When used naively, however, incorrect underlying assumptions can lead to flawed conclusions (Pirotta et al, 2022). We acknowledge that our models made several assumptions (i.e.…”

Section: Discussionmentioning

confidence: 99%

“…PBMs can be defined as ‘ models that characterize the changes in a system’s state as explicit functions of the events that drive those state changes ’ (Connolly et al, 2017). Stressor–response relationships are fundamental to PBMs, as they quantify the often non‐linear processes that drive change in biological responses and allow more informative predictions than methods such as linear statistical extrapolation because they explicitly model the mechanisms rather than fitting a phenomenological relationship between stressor and response (Griffen et al, 2016; Pirotta et al, 2022). Here, we integrate PBMs within a framework to classify interaction types and explore how two stressors interact to impact responses at physiological, population and consumer‐resource levels.…”

Section: Introductionmentioning

confidence: 99%

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Interactive effects of multiple stressors vary with consumer interactions, stressor dynamics and magnitude

et al. 2022

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Predicting the impacts of multiple stressors is important for informing ecosystem management but is impeded by a lack of a general framework for predicting whether stressors interact synergistically, additively or antagonistically. Here, we use process‐based models to study how interactions generalise across three levels of biological organisation (physiological, population and consumer‐resource) for a two‐stressor experiment on a seagrass model system. We found that the same underlying processes could result in synergistic, additive or antagonistic interactions, with interaction type depending on initial conditions, experiment duration, stressor dynamics and consumer presence. Our results help explain why meta‐analyses of multiple stressor experimental results have struggled to identify predictors of consistently non‐additive interactions in the natural environment. Experiments run over extended temporal scales, with treatments across gradients of stressor magnitude, are needed to identify the processes that underpin how stressors interact and provide useful predictions to management.

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Section: Discussionsupporting

confidence: 89%

Section: Discussionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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Interactive effects of multiple stressors vary with consumer interactions, stressor dynamics and magnitude

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“…Combined, these factors will be especially important in monitoring how variation in body condition is related to changes in sea ice, krill abundance, individual residency times, the krill fishery, and tourism. Linking repeated measurements of known individuals over time with vital rates will characterize the energetic demands of each reproductive class and help monitor population response to these environmental and anthropogenic disturbances (Pirotta et al, 2018;Pirotta et al, 2022).…”

Section: Caveats and Considerationsmentioning

confidence: 99%

Seasonal gain in body condition of foraging humpback whales along the Western Antarctic Peninsula

et al. 2022

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Most baleen whales are capital breeders that use stored energy acquired on foraging grounds to finance the costs of migration and reproduction on breeding grounds. Body condition reflects past foraging success and can act as a proxy for individual fitness. Hence, monitoring the seasonal gain in body condition of baleen whales while on the foraging grounds can inform how marine mammals support the costs of migration, growth, and reproduction, as well as the nutritional health of the overall population. Here, we use photogrammetry from drone-based imagery to examine how the body condition of humpback whales (Megaptera novaeangliae) changed over the foraging season (November to June) along the Western Antarctic Peninsula (WAP) from 2017 to 2019. This population (IWC stock G) is recovering from past whaling and is growing rapidly, providing an opportunity to study how whales store energy in a prey-rich environment. We used a body area index (BAI) to estimate changes in body condition and applied a Bayesian approach to incorporate measurement uncertainty associated with different drone types used for data collection. We used biopsy samples to determine sex and pregnancy status, and a length-based maturity classification to assign reproductive classes (n = 228; calves = 31, juveniles = 82, lactating females = 31, mature males = 12, mature unknown sex = 56, non-pregnant females = 12, pregnant females = 3, pregnant & lactating females = 1). Average BAI increased linearly over the feeding season for each reproductive class. Lactating females had lower BAI compared to other mature whales late in the season, reflecting the high energetic costs of nursing a calf. Mature males and non-pregnant females had the highest BAI values. Calves and juvenile whales exhibited an increase in BAI but not structural size (body length) over the feeding season. The body length of lactating mothers was positively correlated with the body length of their calves, but no relationship was observed between the BAI of mothers and their calves. Our study establishes a baseline for seasonal changes in the body condition for this humpback whale population, which can help monitor future impacts of disturbance and climate change.

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“…Thus, in order to implement management measures to ensure the sustainability of whale watching activity, it is essential to assess both short-and long-term effects on cetaceans (Lusseau and Bejder, 2007;Bearzi, 2017). This is even more critical, as these effects may interact and add up with effects from other anthropogenic stressors (e.g., global warming, marine debris and ocean noise) (Pirotta et al, 2022).…”

Section: Introductionmentioning

confidence: 99%

Exposure to whale watching vessels affects dive ascents and resting behavior in sperm whales

et al. 2022

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Disturbance from whale watching can induce a wide range of behavioral responses in cetaceans, some of which can affect their energetic balance and, ultimately, their long-term fitness. However, assessing disturbance effects on deep-diving cetaceans remains challenging, as the majority of their activities occurs underwater and are difficult to monitor from surface observations. To surpass this limitation, we attached high-resolution multi-sensor tags (DTAGs) on 24 sperm whales (Physeter macrocephalus) off the Azores, an area of intense whale watching, to evaluate changes in movement and acoustic parameters related to foraging effort and dives, locomotion effort, and non-foraging behavior. These parameters were compared between periods of exposure and non-exposure to whale watching vessels, using linear mixed-effect models to assess the presence of short-term effects, accounting for individual differences in behavior. We found no significant changes in foraging effort (number of buzzes, bottom phase depth, proportion of search and foraging phases) and overall dive behavior (dive duration, proportion of dive phases, and descending or ascending pitch) between non-exposure and exposure periods. In contrast, variation in body pitch during non-foraging periods increased during exposure but not variation in body roll. Taken together, these results suggest increased movements during resting activity, which may carry energetic costs to whales and impact their health. Vertical velocity during ascents was also significantly higher in response to vessel exposure, suggesting that sperm whales increased the frequency of fluke strokes, which was consistent with a higher Overall Dynamic Body Acceleration (ODBA) during ascents, incurring in higher energy expenditure. If the detected changes are repeated across multiple exposures, they might affect the individual’s energetic budget, and consequently their fitness. Our study contributes to a better understanding of the short-term behavioral responses of sperm whales to whale watching vessels and highlights the need for further studies examining the potential consequences from repeated disturbance to individuals.

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Understanding the combined effects of multiple stressors: A new perspective on a longstanding challenge

Cited by 88 publications

References 128 publications

Interactive effects of multiple stressors vary with consumer interactions, stressor dynamics and magnitude

Interactive effects of multiple stressors vary with consumer interactions, stressor dynamics and magnitude

Seasonal gain in body condition of foraging humpback whales along the Western Antarctic Peninsula

Exposure to whale watching vessels affects dive ascents and resting behavior in sperm whales

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