Navigation is a critical ability for animal survival and is important for food foraging, finding shelter, seeking mates and a variety of other behaviors. Given their fundamental role and universal function in the animal kingdom, it makes sense to explore whether space representation and navigation mechanisms are dependent on the species, ecological system, brain structures, or whether they share general and universal properties. One way to explore this issue behaviorally is by domain transfer methodology, where one species is embedded in another species’ environment and must cope with an otherwise familiar (in our case, navigation) task. Here we push this idea to the limit by studying the navigation ability of a fish in a terrestrial environment. For this purpose, we trained goldfish to use a Fish Operated Vehicle (FOV), a wheeled terrestrial platform that reacts to the fish’s movement characteristics, location and orientation in its water tank to change the vehicle’s; i.e., the water tank’s, position in the arena. The fish were tasked to “drive” the FOV towards a visual target in the terrestrial environment, which was observable through the walls of the tank, and indeed were able to operate the vehicle, explore the new environment, and reach the target regardless of the starting point, all while avoiding dead-ends and correcting location inaccuracies. These results demonstrate how a fish was able to transfer its space representation and navigation skills to a wholly different terrestrial environment, thus supporting the hypothesis that the former possess a universal quality that is species-independent.
Identifying and quantifying the effects of climate change that alter the habitat overlap of marine predators and their prey population distributions is of great importance for the sustainable management of populations. This study uses Bayesian joint models with integrated nested Laplace approximation (INLA) to predict future spatial density distributions in the form of common spatial trends of predator–prey overlap in 2050 under the “business-as-usual, worst-case” climate change scenario. This was done for combinations of six mobile marine predator species (gray seal, harbor seal, harbor porpoise, common guillemot, black-legged kittiwake, and northern gannet) and two of their common prey species (herring and sandeels). A range of five explanatory variables that cover both physical and biological aspects of critical marine habitat were used as follows: bottom temperature, stratification, depth-averaged speed, net primary production, and maximum subsurface chlorophyll. Four different methods were explored to quantify relative ecological cost/benefits of climate change to the common spatial trends of predator–prey density distributions. All but one future joint model showed significant decreases in overall spatial percentage change. The most dramatic loss in predator–prey population overlap was shown by harbor seals with large declines in the common spatial trend for both prey species. On the positive side, both gannets and guillemots are projected to have localized regions with increased overlap with sandeels. Most joint predator–prey models showed large changes in centroid location, however the direction of change in centroids was not simply northwards, but mostly ranged from northwest to northeast. This approach can be very useful in informing the design of spatial management policies under climate change by using the potential differences in ecological costs to weigh up the trade-offs in decisions involving issues of large-scale spatial use of our oceans, such as marine protected areas, commercial fishing, and large-scale marine renewable developments.
Passive acoustic monitoring (PAM) involves recording the sounds of animals and environments for research and conservation. PAM is used in a range of contexts across terrestrial, marine and freshwater environments. However, financial constraints limit applications within aquatic environments; these costs include the high cost of submersible acoustic recorders. We quantify this financial constraint using a systematic literature review of all ecoacoustic studies published in 2020, demonstrating that commercially available autonomous underwater recording units are, on average, five times more expensive than their terrestrial equivalents. This pattern is more extreme at the low end of the price range; the cheapest available aquatic autonomous units are over 40 times more expensive than their terrestrial counterparts. Following this, we test a prototype low-cost, low-specification aquatic recorder called the ‘HydroMoth’: this device is a modified version of a widely used terrestrial recorder (AudioMoth), altered to include a waterproof case and customisable gain settings suitable for a range of aquatic applications. We test the performance of the HydroMoth in both aquaria and field conditions, recording artificial and natural sounds, and comparing outputs with identical recordings taken with commercially available hydrophones. Although the signal-to-noise ratio and the recording quality of HydroMoths are lower than commercially available hydrophones, the recordings with HydroMoths still allow for the identification of different fish and marine mammal species, as well as the calculation of ecoacoustic indices for ecosystem monitoring. Finally, we outline the potential applications of low-cost, low-specification underwater sound recorders for bioacoustic studies, discuss their likely limitations, and present important considerations of which users should be aware. Several performance limitations and a lack of professional technical support mean that low-cost devices cannot meet the requirements of all PAM applications. Despite these limitations, however, HydroMoth facilitates underwater recording at a fraction of the price of existing hydrophones, creating exciting potential for diverse involvement in aquatic bioacoustics worldwide.
Marine animals equipped with biological and physical electronic sensors have produced long-term data streams on key marine environmental variables, hydrography, animal behavior and ecology. These data are an essential component of the Global Ocean Observing System (GOOS). The Animal Borne Ocean Sensors (AniBOS) network aims to coordinate the long-term collection and delivery of marine data streams, providing a complementary capability to other GOOS networks that monitor Essential Ocean Variables (EOVs), essential climate variables (ECVs) and essential biodiversity variables (EBVs). AniBOS augments observations of temperature and salinity within the upper ocean, in areas that are under-sampled, providing information that is urgently needed for an improved understanding of climate and ocean variability and for forecasting. Additionally, measurements of chlorophyll fluorescence and dissolved oxygen concentrations are emerging. The observations AniBOS provides are used widely across the research, modeling and operational oceanographic communities. High latitude, shallow coastal shelves and tropical seas have historically been sampled poorly with traditional observing platforms for many reasons including sea ice presence, limited satellite coverage and logistical costs. Animal-borne sensors are helping to fill that gap by collecting and transmitting in near real time an average of 500 temperature-salinity-depth profiles per animal annually and, when instruments are recovered (∼30% of instruments deployed annually, n = 103 ± 34), up to 1,000 profiles per month in these regions. Increased observations from under-sampled regions greatly improve the accuracy and confidence in estimates of ocean state and improve studies of climate variability by delivering data that refine climate prediction estimates at regional and global scales. The GOOS Observations Coordination Group (OCG) reviews, advises on and coordinates activities across the global ocean observing networks to strengthen the effective implementation of the system. AniBOS was formally recognized in 2020 as a GOOS network. This improves our ability to observe the ocean’s structure and animals that live in them more comprehensively, concomitantly improving our understanding of global ocean and climate processes for societal benefit consistent with the UN Sustainability Goals 13 and 14: Climate and Life below Water. Working within the GOOS OCG framework ensures that AniBOS is an essential component of an integrated Global Ocean Observing System.
The trophic ecology of epibenthic mesopredators is not well understood in terms of prey partitioning with sympatric elasmobranchs or their effects on prey communities, yet the importance of omnivores in community trophic dynamics is being increasingly realised. This study used stable isotope analysis of 15N and 13C to model diet composition of wild southern stingrays Dasyatis americana and compare trophic niche space to nurse sharks Ginglymostoma cirratum and Caribbean reef sharks Carcharhinus perezi on Glovers Reef Atoll, Belize. Bayesian stable isotope mixing models were used to investigate prey choice as well as viable Diet-Tissue Discrimination Factors for use with stingrays. Stingray δ15N values showed the greatest variation and a positive relationship with size, with an isotopic niche width approximately twice that of sympatric species. Shark species exhibited comparatively restricted δ15N values and greater δ13C variation, with very little overlap of stingray niche space. Mixing models suggest bivalves and annelids are proportionally more important prey in the stingray diet than crustaceans and teleosts at Glovers Reef, in contrast to all but one published diet study using stomach contents from other locations. Incorporating gut contents information from the literature, we suggest diet-tissue discrimination factors values of Δ15N ≊ 2.7‰ and Δ13C ≊ 0.9‰ for stingrays in the absence of validation experiments. The wide trophic niche and lower trophic level exhibited by stingrays compared to sympatric sharks supports their putative role as important base stabilisers in benthic systems, with the potential to absorb trophic perturbations through numerous opportunistic prey interactions.
Sawfishes are considered one of the most endangered families of fishes globally. Their diadromous ecology and vulnerability to fishing nets have brought most populations to the brink of collapse. Conservation of surviving populations is hindered by limited knowledge of historic and contemporary distribution. Colombia and Panamá are 2 of 22 countries considered as high priority for the development of species-specific national legal protection of the Critically Endangered largetooth sawfish Pristis pristis. To construct a baseline for the temporal and spatial distribution of the largetooth sawfish in Colombia and Panamá, we collected historical records from museum databases and literature over the past century, analysed available small-scale fisheries landings databases, and conducted interviews with fishers in 38 locations. We found 248 records of sawfish occurrences across both countries between 1896 and 2015, with 69% of the records from before 2000. The declining frequency of observations was corroborated by fishers, who reported fewer sawfish sightings and catches over the last 20 yr. Results from a regression model of total length and observed date suggest that the maximum size of observed sawfish individuals has also declined over time. We use location data from sawfish records to identify potential ‘bright spots’ that may foster remaining populations of sawfish. The locations of sawfish records were broadly characterised as remote areas with high mangrove forest cover. Given the length and cultural diversity of the Pacific coastlines of Colombia and Panamá, our findings provide important guidance to implement rapid conservation and fisheries interventions in these priority areas and highlight geographical gaps in knowledge for further work.
The ability to exert self-control varies within and across taxa. Some species can exert self-control for several seconds whereas others, such as large-brained vertebrates, can tolerate delays of up to several minutes. Advanced self-control has been linked to better performance in cognitive tasks and has been hypothesized to evolve in response to specific socio-ecological pressures. These pressures are difficult to uncouple because previously studied species face similar socio-ecological challenges. Here, we investigate self-control and learning performance in cuttlefish, an invertebrate that is thought to have evolved under partially different pressures to previously studied vertebrates. To test self-control, cuttlefish were presented with a delay maintenance task, which measures an individual's ability to forgo immediate gratification and sustain a delay for a better but delayed reward. Cuttlefish maintained delay durations for up to 50–130 s. To test learning performance, we used a reversal-learning task, whereby cuttlefish were required to learn to associate the reward with one of two stimuli and then subsequently learn to associate the reward with the alternative stimulus. Cuttlefish that delayed gratification for longer had better learning performance. Our results demonstrate that cuttlefish can tolerate delays to obtain food of higher quality comparable to that of some large-brained vertebrates.
The quantification of positively buoyant marine plastic debris is critical to understanding how concentrations of trash from across the world's ocean and identifying high concentration garbage hotspots in dire need of trash removal. Currently, the most common monitoring method to quantify floating plastic requires the use of a manta trawl. Techniques requiring manta trawls (or similar surface collection devices) utilize physical removal of marine plastic debris as the first step and then analyze collected samples as a second step. The need for physical removal before analysis incurs high costs and requires intensive labor preventing scalable deployment of a real-time marine plastic monitoring service across the entirety of Earth's ocean bodies. Without better monitoring and sampling methods, the total impact of plastic pollution on the environment as a whole, and details of impact within specific oceanic regions, will remain unknown. This study presents a highly scalable workflow that utilizes images captured within the epipelagic layer of the ocean as an input. It produces real-time quantification of marine plastic debris for accurate quantification and physical removal. The workflow includes creating and preprocessing a domain-specific dataset, building an object detection model utilizing a deep neural network, and evaluating the model's performance. YOLOv5-S was the best performing model, which operates at a Mean Average Precision (mAP) of 0.851 and an F1-Score of 0.89 while maintaining near-real-time speed.
Underwater visual monitoring methods are used broadly to evaluate coral reef conditions in the natural environment, but quantitative measurements of the coral holobiont has been largely restricted to photophysiological assessment of the endosymbionts. An underwater respirometer has been designed to make routine, diver-operated, non-invasive measurements at coral surfaces, but the realistic in situ accuracy and precision capabilities of this device has not been critically assessed; an essential step if these measurements are to be useful for quantifying spatial and seasonal patterns of coral metabolism. We developed specific protocols for this system to survey shallow coral colonies and detect metabolic profiles (respiration, photosynthesis, and biocalcification), diel cycles (day and night), and photosynthesis-irradiance curves. Analysis of data from in situ and laboratory-controlled conditions showed good replication among coral colonies and high precision measurements of temperature, oxygen and pH fluxes over 15-min incubation times without noticeable detrimental effects on coral health. Moreover, marked differences were observed in coral calcification rates between estuarine-influenced and coastal marine conditions, despite the absence of significant differences in visual appearance or other health indicators, revealing the system’s potential for early detection of marginally adverse conditions for coral metabolism. Its ease of operation and rapid quantification of the physiological status of the corals make this respirometer well suited for use by reef scientists, monitoring agencies, and stakeholders in biogenic reefs conservation efforts. Moreover, the high spatial and temporal resolution of these underwater respirometer data will have the potential to discriminate the effects of local stressors on coral health from those generated by broader changes associated with climate drivers.