Assessing without harvesting: Pros and cons of environmental DNA sampling and image analysis for marine biodiversity evaluation

Marine stock assessments or biodiversity monitoring studies, which historically relied on extractive techniques (e.g., trawl or grab surveys), are being progressively replaced by non-extractive approaches. For instance, species abundance indices can be calculated using data obtained from high-definition underwater cameras that enable to identify taxa at low taxonomical level. In biodiversity studies, environmental DNA (eDNA) has proven to be a useful tool for characterising fish species richness. However, several marine phyla remain poorly represented in reference gene databases or release limited amounts of DNA, restricting their detection. The absence of amplification of some invertebrate taxa might also reflect primer bias. We here explore and compare the performance of eDNA and image data in describing the marine communities of several sites in the Bay of Biscay. This was achieved by deploying a remotely operated vehicle to both record images and collect seawater samples. A total of 88 taxa were identified from the eDNA samples and 121 taxa from the images. For both methods, the best characterised phylum was Chordata, with 29 and 27 Actinopterygii species detected using image versus eDNA, respectively. Neither Bryozoa nor Cnidaria was detected in the eDNA samples while the phyla were easily identifiable by imagery. Similarly, Asteroidea (Echinodermata) and Cephalopoda (Mollusca) were scarcely detected in the eDNA samples but present on the images, while Annelida were mostly identified by eDNA (18 taxa vs 7 taxa from imagery). The complementary community descriptions we highlight from these two methods therefore advocate for using both eDNA and imagery in tandem in order to capture the macroscopic biodiversity of bentho-demersal marine communities.

Brief Oil Exposure Reduces Fitness in Wild Gulf of Mexico Mahi-Mahi (Coryphaena hippurus)

The Deepwater Horizon (DWH) disaster released 3.19 million barrels of crude oil into the Gulf of Mexico (GOM) in 2010, overlapping the habitat of pelagic fish populations. Using mahi-mahi (Coryphaena hippurus)─a highly migratory marine teleost present in the GOM during the spill─as a model species, laboratory experiments demonstrate injuries to physiology and behavior following oil exposure. However, more than a decade postspill, impacts on wild populations remain unknown. To address this gap, we exposed wild mahi-mahi to crude oil or control conditions onboard a research vessel, collected fin clip samples, and tagged them with electronic tags prior to release into the GOM. We demonstrate profound effects on survival and reproduction in the wild. In addition to significant changes in gene expression profiles and predation mortality, we documented altered acceleration and habitat use in the first 8 days oil-exposed individuals were at liberty as well as a cessation of apparent spawning activity for at least 37 days. These data reveal that even a brief and low-dose exposure to crude oil impairs fitness in wild mahi-mahi. These findings offer new perspectives on the lasting impacts of the DWH blowout and provide insight about the impacts of future deep-sea oil spills.

The choice of droplet size probability distribution function for oil spill modeling is not trivial

The droplet size distribution (DSD) formed by gas-saturated oil jets is one of the most important characteristics of the flow to understand and model the fate of uncontrolled deep-sea oil spills. The shape of the DSD, generally modeled as a theoretical lognormal, Rosin-Rammler or non-fundamental distribution function, defines the size and the mass volume range of the droplets. Yet, the fundamental DSD shape has received much less attention than the volume median size (d50) and range of the DSD during ten years of research following the Deepwater Horizon (DWH) blowout. To better understand the importance of the distribution function of the droplet size we compare the oil rising time, surface oil mass, and sedimented and beached masses for different DSDs derived from the DWH literature in idealized and applied conditions, while keeping d50 constant. We highlight substantial differences, showing that the probability distribution function of the DSD for far-field modeling is, regardless of the d50, consequential for oil spill response.

Atlantic Multidecadal Oscillations drive the basin-scale distribution of Atlantic bluefin tuna

The Atlantic bluefin tuna (hereafter referred to as "bluefin tuna"), one of the world's most valuable and exploited fish species, has been declining in abundance throughout the Atlantic from the 1960s until the mid-2000s. Following the establishment of drastic management measures, the stock has started to recover recently and, as a result, stakeholders have raised catch quotas by 50% for the period 2017-2020. However, stock assessments still omit the natural, long-term variability in the species distribution. Here, we explore the century-scale fluctuations in bluefin tuna abundance and distribution to demonstrate a prevailing influence of the Atlantic Multidecadal Oscillation (AMO) to provide new insights into both the collapse of the Nordic bluefin tuna fishery circa 1963 and the recent increase in bluefin tuna abundance in the Northeast Atlantic. Our results demonstrate how climatic variability can modulate the distribution of a large migrating species to generate rapid changes in its regional abundance, and we argue that climatic variability must not be overlooked in stock management plans for effective conservation.