ABSTRACT
Spatial and temporal monitoring of species threatened with extinction is of critical importance for conservation and ecosystem management. In the Mediterranean coast, the fan mussel (Pinna nobilis) is listed as critically endangered after suffering from a mass mortality event since 2016, leading to 100% mortality in most marine populations. Conventional monitoring for this macroinvertebrate is done using scuba, which is challenging in dense meadows or with low visibility. Here we developed an environmental DNA assay targeting the fan mussel and assessed the influence of several environmental parameters on the species detectability in situ. We developed and tested an eDNA molecular marker and collected 48 water samples in two sites at the Thau lagoon (France) with distinct fan mussel density, depths and during two seasons (summer and autumn). Our marker can amplify fan mussel DNA but lacks specificity since it also amplifies a conspecific species (Pinna rudis). We successfully amplified fan mussel DNA from in situ samples with 46 positive samples (out of 48) using ddPCR, although the DNA concentrations measured were low over almost all samples. Deeper sampling depth slightly increased DNA concentrations, but no seasonal effect was found. We highlight a putative spawning event on a single summer day with much higher DNA concentration compared to all other samples. We present an eDNA molecular assay able to detect the endangered fan mussel and provide guidelines to optimize the sampling protocol to maximize detectability. Effective and non-invasive monitoring tools for endangered species are promising to monitor remaining populations and have the potential of ecological restoration or habitat recolonization following a mass mortality event.
ABSTRACT
Within the framework of the mitigation hierarchy, biodiversity offsetting is the main tool promoted to reach No Net Loss. One of the determining factors of offsetting success is the evaluation of ecological equivalence. Various equivalence assessment methods (EAMs) have been developed to provide a framework to evaluate the balance between expected biodiversity losses and gains. In the context of achieving No Net Loss, EAMs must address challenges of Operationality, Currency, Uncertainty, Spatial scale and Time frame. In this study, we investigated the way the most widely used EAMs address these challenges, positing that certain tools from ecological science could limit the trade-offs between these challenges and improve the ecological assessment process. To this end, we analysed the risks and benefits associated with the inclusion of genetic tools (landscape genetics and eDNA), remote sensing and metapopulation models in selected EAMs. Our results revealed trade-offs between these five challenges, in particular between Operationality and Currency. The EAMs varied strongly in these two aspects, depending on the general assessment approach and the biodiversity component they focus on. To a lesser degree, Time frame and Spatial scale also differed between the methods. We identified that the integration of the different tools differs among them, being easier for remote sensing and metapopulation models than for the genetic tools. Nevertheless, the integration resulted in benefits compared to the current use of the methods - benefits that included improving the objectivation of the assessment and the automatization potential. The tools also show potential for automatization, which could have major benefits for operationality. In terms of risks, the integration of these tools increases the technical complexity of the methods, requiring new skills, and would change the overall approach of the ecological assessment.
