Recent advances in tracking systems have revolutionized our ability to study animal movement in the wild. In aquatic environments, high-resolution acoustic telemetry systems make it technically possible to simultaneously monitor large amounts of individuals at unprecedented spatial and temporal resolutions, providing a unique opportunity to study the behaviour and social interactions using a reality mining approach. Despite the potential, high-resolution telemetry systems have had very limited use in coastal marine areas due to the limitations that these environments pose to the transmission of acoustic signals. This study aims at designing and testing a high-resolution acoustic telemetry system to monitor, for the first time, a natural fish population in an open marine area. First, we conducted preliminary range tests and a computer simulation study to identify the optimal design of the telemetry system. Then, we performed a series of stationary and moving tests to characterize the performance of the system in terms of positioning efficiency and precision. Finally, we obtained a dataset corresponding to the movements of 170 concurrently tagged individuals to demonstrate the overall functioning of the system with a real study case of the behaviour of a small-bodied coastal species. Our results show that high-resolution acoustic telemetry systems efficiently generate positional data in marine systems, providing a precision of few meters, a temporal resolution of few seconds, and the possibility of tracking hundreds of individuals simultaneously. Data post-processing using a trajectory filter and movement models proved to be key to achieve a sub-meter positioning precision. The main limitation detected for our system was the restricted detection range, which was negatively affected by the stratification of the water column. Our work demonstrates that high-resolution acoustic telemetry systems are an effective method to monitor the movements of free-ranging individuals at the population level in coastal sites. By providing highly precise positioning estimates of large amounts of individuals, these systems represent a powerful tool to study key ecological processes regarding the social interactions of individuals, including social dynamics, collective movements, or responses to environmental perturbations, and to extend the studies to poorly studied small-sized species or life-stages.
Despite the recognised effectiveness of networks of marine protected areas (MPAs) as a biodiversity conservation instrument, MPA network design frequently disregards the importance of connectivity patterns. In the case of sedentary marine populations, connectivity stems not only from the stochastic nature of the physical environment that affects dispersal of early life stages, but also from the spawning stock attributes that affect reproductive output (e.g. passive eggs and larvae) and survivorship. Early life stages are virtually impossible to track in the ocean. Therefore, numerical ocean current simulations coupled with egg and larval Lagrangian transport models remain the most common approach for the assessment of marine larval connectivity. Inferred larval connectivity may differ depending on the type of connectivity considered; consequently, the prioritisation of sites for the conservation of marine populations might also differ. Here, we introduce a framework for evaluating and designing MPA networks based on the identification of connectivity hotspots using graph theoretic analysis. As a case study, we used a network of open-access areas and MPAs off Mallorca Island (Spain), and tested its effectiveness for the protection of the painted comber Serranus scriba. Outputs from network analysis were used to (1) identify critical areas for improving overall larval connectivity, (2) assess the impact of species’ biological parameters in network connectivity and (3) explore alternative MPA configurations to improve average network connectivity. Results demonstrate the potential of graph theory to identify non-trivial egg/larval dispersal patterns and emerging collective properties of the MPA network, which are relevant for increasing protection efficiency.
A mass mortality event (MME) affecting the fan mussel Pinna nobilis was first detected in Spain in autumn 2016 and spread north- and eastward through the Mediterranean Sea. Various pathogens have been blamed for contributing to the MME, with emphasis in Haplosporidium pinnae, Mycobacterium sp. and Vibrio spp. In this study, samples from 762 fan mussels (necropsies from 263 individuals, mantle biopsies from 499) of various health conditions, with wide geographic and age range, taken before and during the MME spread from various environments along Mediterranean Sea, were used to assess the role of pathogens in the MME. The number of samples processed by both histological and molecular methods was 83. The most important factor playing a main role on the onset of the mass mortality of P. nobilis throughout the Mediterranean Sea was the infection by H. pinnae. It was the only non-detected pathogen before the MME while, during MME spreading, its prevalence was higher in sick and dead individuals than in asymptomatic ones, in MME-affected areas than in non-affected sites, and it was not associated with host size, infecting both juveniles and adults. Conversely, infection with mycobacteria was independent from the period (before or during MME), from the affection of the area by MME and from the host health condition, and it was associated with host size. Gram (-) bacteria neither appeared associated with MME.
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