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Understanding the distribution of marine organisms is essential for effective management of highly mobile marine predators that face a variety of anthropogenic threats. Recent work has largely focused on modelling the distribution and abundance of marine mammals in relation to a suite of environmental variables. However, biotic interactions can largely drive distributions of these predators. We aim to identify how biotic and abiotic variables influence the distribution and abundance of a particular marine predator, the bottlenose dolphin (Tursiops truncatus), using multiple modelling approaches and conducting an extensive literature review.

Western North Atlantic continental shelf.

We combined widespread marine mammal and fish and invertebrate surveys in an ensemble modelling approach to assess the relative importance and capacity of the environment and other marine species to predict the distribution of both coastal and offshore bottlenose dolphin ecotypes. We corroborate the modelled results with a systematic literature review on the prey of dolphins throughout the region to help explain patterns driven by prey availability, as well as reveal new ones that may not necessarily be a predator–prey relationship.

We find that coastal bottlenose dolphin distributions are associated with one family of fishes, the Sciaenidae, or drum family, and predictions slightly improve when using only fish versus only environmental variables. The literature review suggests that this tight coupling is likely a predator–prey relationship. Comparatively, offshore dolphin distributions are more strongly related to environmental variables, and predictions are better for environmental‐only models. As revealed by the literature review, this may be due to a mismatch between the animals caught in the fish and invertebrate surveys and the predominant prey of offshore dolphins, notably squid.

Incorporating prey species into distribution models, especially for coastal bottlenose dolphins, can help inform ecological relationships and predict marine predator distributions.

 

Body condition is a crucial and indicative measure of an animal’s fitness, reflecting overall foraging success, habitat quality, and balance between energy intake and energetic investment toward growth, maintenance, and reproduction. Recently, drone-based photogrammetry has provided new opportunities to obtain body condition estimates of baleen whales in one, two or three dimensions (1D, 2D, and 3D, respectively) – a single width, a projected dorsal surface area, or a body volume measure, respectively. However, no study to date has yet compared variation among these methods and described how measurement uncertainty scales across these dimensions. This associated uncertainty may affect inference derived from these measurements, which can lead to misinterpretation of data, and lack of comparison across body condition measurements restricts comparison of results between studies. Here we develop a Bayesian statistical model using known-sized calibration objects to predict the length and width measurements of unknown-sized objects (e.g., a whale). We use the fitted model to predict and compare uncertainty associated with 1D, 2D, and 3D photogrammetry-based body condition measurements of blue, humpback, and Antarctic minke whales – three species of baleen whales with a range of body sizes. The model outputs a posterior predictive distribution of body condition measurements and allows for the construction of highest posterior density intervals to define measurement uncertainty. We find that uncertainty does not scale linearly across multi-dimensional measurements, with 2D and 3D uncertainty increasing by a factor of 1.45 and 1.76 compared to 1D, respectively. Each standardized body condition measurement is highly correlated with one another, yet 2D body area index (BAI) accounts for potential variation along the body for each species and was the most precise body condition metric. We hope this study will serve as a guide to help researchers select the most appropriate body condition measurement for their purposes and allow them to incorporate photogrammetric uncertainty associated with these measurements which, in turn, will facilitate comparison of results across studies. 

The krill surplus hypothesis of unlimited prey resources available for Antarctic predators due to commercial whaling in the 20th century has remained largely untested since the 1970s. Rapid warming of the Western Antarctic Peninsula (WAP) over the past 50 years has resulted in decreased seasonal ice cover and a reduction of krill. The latter is being exacerbated by a commercial krill fishery in the region. Despite this, humpback whale populations have increased but may be at a threshold for growth based on these human‐induced changes. Understanding how climate‐mediated variation in prey availability influences humpback whale population dynamics is critical for focused management and conservation actions. Using an 8‐year dataset (2013–2020), we show that inter‐annual humpback whale pregnancy rates, as determined from skin‐blubber biopsy samples (n = 616), are positively correlated with krill availability and fluctuations in ice cover in the previous year. Pregnancy rates showed significant inter‐annual variability, between 29% and 86%. Our results indicate that krill availability is in fact limiting and affecting reproductive rates, in contrast to the krill surplus hypothesis. This suggests that this population of humpback whales may be at a threshold for population growth due to prey limitations. As a result, continued warming and increased fishing along the WAP, which continue to reduce krill stocks, will likely impact this humpback whale population and other krill predators in the region. Humpback whales are sentinel species of ecosystem health, and changes in pregnancy rates can provide quantifiable signals of the impact of environmental change at the population level. Our findings must be considered paramount in developing new and more restrictive conservation and management plans for the Antarctic marine ecosystem and minimizing the negative impacts of human activities in the region.

 

Six baleen whale species are found in the temperate western North Atlantic Ocean, with limited information existing on the distribution and movement patterns for most. There is mounting evidence of distributional shifts in many species, including marine mammals, likely because of climate‐driven changes in ocean temperature and circulation. Previous acoustic studies examined the occurrence of minke (Balaenoptera acutorostrata) and North Atlantic right whales (NARW;Eubalaena glacialis). This study assesses the acoustic presence of humpback (Megaptera novaeangliae), sei (B. borealis), fin (B. physalus), and blue whales (B. musculus) over a decade, based on daily detections of their vocalizations. Data collected from 2004 to 2014 on 281 bottom‐mounted recorders, totaling 35,033 days, were processed using automated detection software and screened for each species' presence. A published study on NARW acoustics revealed significant changes in occurrence patterns between the periods of 2004–2010 and 2011–2014; therefore, these same time periods were examined here. All four species were present from the Southeast United States to Greenland; humpback whales were also present in the Caribbean. All species occurred throughout all regions in the winter, suggesting that baleen whales are widely distributed during these months. Each of the species showed significant changes in acoustic occurrence after 2010. Similar to NARWs, sei whales had higher acoustic occurrence in mid‐Atlantic regions after 2010. Fin, blue, and sei whales were more frequently detected in the northern latitudes of the study area after 2010. Despite this general northward shift, all four species were detected less on the Scotian Shelf area after 2010, matching documented shifts in prey availability in this region. A decade of acoustic observations have shown important distributional changes over the range of baleen whales, mirroring known climatic shifts and identifying new habitats that will require further protection from anthropogenic threats like fixed fishing gear, shipping, and noise pollution.