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Toward a new generation of Ecological Assessment tools for the Management Coastal environment

Periodic Reporting for period 2 - TEAM-Coast (Toward a new generation of Ecological Assessment tools for the Management Coastal environment)

Reporting period: 2020-07-16 to 2021-07-15

More than 60% of the worldwide population live on or near a coastline. These areas of considerable socio-cultural and economic importance host extraordinary biodiversity that supports many significant services to humankind (e.g. fisheries, carbon sequestration). However, human activities have deleterious effects (water pollution, introduction of alien species, climate changes etc.) on coastal environments and their biodiversity. These pressures often act simultaneously, yet their cumulative impacts on biodiversity are poorly understood. First, traditional approaches for monitoring coastal biodiversity present multiple constraints that limit observations to a small number of species and restrain the extent of studies. Second, studies often focus on the impact of a single stressor and ignore interacting effects between stressors. To improve the health of coastal environments, we need more integrative approaches for monitoring biodiversity and disentangling the effects of the different stressors. To reach this goal, and thus support adapted management strategies, this project aims at developing a new generation of tools, based on molecular approaches named ‘environmental DNA’ (i.e. the study of genetic material retrieved in environmental samples such as water and sediment). These methods for monitoring biodiversity (aka "eDNA biomonitoring") seek to identify species living in a given area from DNA they release in the environment. They proved to be powerful tools for obtaining comprehensive and standardised biodiversity surveys in a relatively rapid and cost-efficient way. The TEAM-Coast project pursues three main objectives. The first one aimed at developing protocols for the large-scale implementation of eDNA biomonitoring in costal environments. We validated and used efficient and cost-effective sampling strategies and protocols for collecting and analyzing eDNA samples at the landscape scale in several coastal environments. The second one aimed at precisely describing the diversity and distribution of species assemblages, and identifying the main factors affecting these communities. Based on eDNA data, several biodiversity metrics were derived and were used to assess the responses of communities to the multiple anthropogenic pressures observed. For instance, the community composition was shown to differ according to the studied estuary, as a response to the anthropogenic gradient among them. Not all species groups however responded the same way highlighting the need for multi-species approaches to assess biodiversity and the health status of these ecosystems. Ultimately, this project aimed at developing ecological risk assessment models, based on eDNA data, and test management scenarios for striking the balance between human activities and the ecological integrity of coastal environments. Several models for eukaryotes were implemented and validated, and are now in course of complexification to include multiple taxonomic groups and provide useful management scenarios.
This project was conducted in collaboration between several institutions in France and Australia, for developing a proof-of-concept for the integration of eDNA biomonitoring data into ecological risk assessment models. Study sites were located in Northern Queensland, Australia. Our work focused on the combined impacts of two of the main sources of aquatic biodiversity loss: contaminants run-offs (e.g. nutrients, pesticides) into coastal waters and the introduction of alien species. Hundreds of water and sediment samples were collected in several estuaries and one harbour, reflecting a human-induced disturbance gradient over two different seasons. We first defined and assessed the appropriate strategy for the sampling, a pre-requisite for reliable eDNA analyses. Then, we developed protocols for the large-scale implementation of eDNA biomonitoring; we notably validated the use of a fast and cheap DNA extraction protocol for eDNA biomonitoring of sediment biodiversity. DNA contained in these environmental samples was processed to identify species present at each sampling site. Five species groups of ecological and economic importance were targeted (e.g. diatoms, fish, crustacea). eDNA data provided fine-scale resolution on the diversity and the composition of each of these groups. By combining these data with environmental parameters and the levels of each stressor, we identified the main natural and anthropogenic factors that affect biodiversity and their seasonal changes. We used this information to characterize the (often contrasted) responses of the different biological communities to human pressures. Results notably show a year-long differentiation of all biological communities under the influence of human pressures, not necessarily in term of richness but rather of community composition. However, locally, natural parameters such as salinity played a predominant role in community structure, especially in the wet season. These results were disseminated through several conferences, public talks/events and publications. Meanwhile, we elaborated DNA-based strategies for monitoring invertebrate species living on hard substrate. This allowed to identify potential alien species and evaluate the threat they represent. Based on eDNA results obtained, models were developed to relate the source of stress to ecological indicators in a realistic way. They were then implemented into cutting-edge tools for assessing ecological risks. These models are used to rank the relative importance of each stressor and evaluate associated risks in each area under investigation. They will be exploited jointly by our partners managing the study areas to develop and test management scenarios.
eDNAbiomonitoring evolved rapidly in recent years, and is expected to be more and more adopted by authorities for examining ecosystem health. There is an urgent need to better connect research and practice. In this project, we developed dedicated and optimized protocols for the large-scale eDNA biomonitoring of coastal environments that will be useful to popularize the approach, and its use in informed decision-making process regarding coastal management. From these data, we characterized coastal biodiversity changes in sediments and the water column in response to anthropogenic pressures and seasons. We also obtained complementary information on communities living on hard substrate, which exhibits different response patterns, and used these data to assess the risks associated with alien species. Finally, this project proposes to go a step forward in the use of eDNA biomonitoring by developing ecological risks assessment models based on these methods. Studying a single stressor on a small number of taxa is now out-dated, and more integrative approaches are required to understand the responses of biological communities to the different pressures they are facing. Protection of coastal environments is at the heart of societal concerns due to their socio-economic importance and strong cultural identity. Models developed provide a proof-of-concept for the integration of eDNA biodiversity data into ecological risk assessment models at a scale relevant for managers. These templates will be made available for public institutions, decision-makers and managers, wishing to develop integrative management models striking the balance between socio-economic interests and the maintenance of biodiversity and ecosystem health.