Genetic alterations and cancer formation in a European flatfish at sites of different contamination burdens

Fish diseases are an indicator for marine ecosystem health since they provide a biological end-point of historical exposure to stressors. Liver cancer has been used to monitor the effects of exposure to anthropogenic pollution in flatfish for many years. The prevalence of liver cancer can exceed 20%. Despite the high prevalence and the opportunity of using flatfish to study environmentally induced cancer, the genetic and environmental factors driving tumor prevalence across sites are poorly understood. This study aims to define the link between genetic deterioration, liver disease progression, and anthropogenic contaminant exposures in the flatfish dab (Limanda limanda). We assessed genetic changes in a conserved cancer gene, Retinoblastoma (Rb), in association with histological diagnosis of normal, pretumor, and tumor pathologies in the livers of 165 fish from six sites in the North Sea and English Channel. The highest concentrations of metals (especially cadmium) and organic chemicals correlated with the presence of tumor pathology and with defined genetic profiles of the Rb gene, from these sites. Different Rb genetic profiles were found in liver tissue near each tumor phenotype, giving insight into the mechanistic molecular-level cause of the liver pathologies. Different Rb profiles were also found at sampling sites of differing contaminant burdens. Additionally, profiles indicated that histological “normal” fish from Dogger sampling locations possessed Rb profiles associated with pretumor disease. This study highlights an association between Rb and specific contaminants (especially cadmium) in the molecular etiology of dab liver tumorigenesis

Determining Plant – Leaf Miner – Parasitoid Interactions: A DNA Barcoding Approach

A major challenge in network ecology is to describe the full-range of species interactions in a community to create highly-resolved food-webs. We developed a molecular approach based on DNA full barcoding and mini-barcoding to describe difficult to observe plant – leaf miner – parasitoid interactions, consisting of animals commonly regarded as agricultural pests and their natural enemies. We tested the ability of universal primers to amplify the remaining DNA inside leaf miner mines after the emergence of the insect. We compared the results of a) morphological identification of adult specimens; b) identification based on the shape of the mines; c) the COI Mini-barcode (130 bp) and d) the COI full barcode (658 bp) fragments to accurately identify the leaf-miner species. We used the molecular approach to build and analyse a tri-partite ecological network of plant – leaf miner – parasitoid interactions. We were able to detect the DNA of leaf-mining insects within their feeding mines on a range of host plants using mini-barcoding primers: 6% for the leaves collected empty and 33% success after we observed the emergence of the leaf miner. We suggest that the low amplification success of leaf mines collected empty was mainly due to the time since the adult emerged and discuss methodological improvements. Nevertheless our approach provided new species-interaction data for the ecological network. We found that the 130 bp fragment is variable enough to identify all the species included in this study. Both COI fragments reveal that some leaf miner species could be composed of cryptic species. The network built using the molecular approach was more accurate in describing tri-partite interactions compared with traditional approaches based on morphological criteria

Wildfire alters the structure and seasonal dynamics of nocturnal pollen‐transport networks

Wildfires drive global biodiversity patterns and affect plant–pollinator interactions, and are expected to become more frequent and severe under climate change. Post-fire plant communities often have increased floral abundance and diversity, but the effects of wildfires on the ecological process of pollination are poorly understood. Nocturnal moths are globally important pollinators, but no previous study has examined the effects of wildfire on nocturnal pollination interactions. We investigated the effects of wildfire on nocturnal pollen-transport networks. We analysed the abundance and species richness of moths and flowers, and the structure of these networks, at three burned and three unburned sites in Portugal for two years, starting eight months after a large fire. Nocturnal pollen-transport networks had lower complexity and robustness following the fire than at nearby unburned sites. Overall, 70% of individual moths carried pollen, and moths were found to be transporting pollen from 83% of the flower species present. Burned sites had significantly more abundant flowers, but less abundant and species-rich moths. Individual moths transported more pollen in summer at burned sites, but less in winter; however, total pollen transport by the moth assemblage at burned sites was just 20% of that at unburned sites. Interaction turnover between burned and unburned networks was high. Negative effects of fire upon moths will likely permeate to other taxa through loss of mutualisms. Therefore, if wildfires become more frequent under climate change, community resilience may be eroded. Understanding the responses of ecological networks to wildfire can inform management that promotes resilience and facilitates whole-ecosystem conservation

A Replicated Network Approach to 'Big Data' in Ecology

International audienceGlobal environmental change is a pressing issue as evidenced by the rise of extreme weather conditions in many parts of the world, threatening the survival of vulnerable species and habitats. Effective monitoring of climatic and anthropogenic impacts is therefore critical to safeguarding ecosystems, and it would allow us to better understand their response to stressors and predict long-term impacts. Ecological networks provide a biomonitoring framework for examining the system-level response and functioning of an ecosystem, but have been, until recently, constrained by limited empirical data due to the laborious nature of their construction. Hence, most experimental designs have been confined to a single network or a small number of replicate networks, resulting in statistical uncertainty, low resolution, limited spatiotemporal scale and oversimplified assumptions. Advances in data sampling and curation methodologies, such as next-generation sequencing (NGS) and the Internet 'Cloud', have facilitated the emergence of the 'Big Data' phenomenon in Ecology, enabling the construction of ecological networks to be carried out effectively and efficiently. This provides to ecologists an excellent opportunity to expand the way they study ecological networks. In particular, highly replicated networks are now within our grasp if new NGS technologies are combined with machine learning to develop network building methods. A replicated network approach will allow temporal and spatial variations embedded in the data to be taken into consideration, overcoming the limitations in the current 'single network' approach. We are still at the embryonic stage in exploring replicated networks, and with these new opportunities we also face new challenges. In this chapter, we discuss some of these challenges and highlight potential approaches that will help us build and analyse replicated networks to better understand how complex ecosystems operate, and the services and functioning they provide, paving the way for deciphering ecological big data reliably in the future

Chapter Ten - Informing marine spatial planning decisions with environmental DNA

Marine management areas provide a key tool for efforts towards sustainable development, reconciling socio-economic goals with those for biodiversity conservation. Decisions about where and when to establish spatial management areas in the oceans are currently hampered by the uncertainties of incomplete, or overly general, information about biodiversity. The analysis of environmental DNA (eDNA) provides a potentially powerful tool to overcome this lack of data in the future. Here we present directions to develop robust approaches to integrate eDNA and spatial planning processes, aiming to provide guidance to underpin tool development. The potential of eDNA use in conservation is widely recognised, although direct applications almost exclusively focus on detection of invasive or threatened species and not spatial management decisions. The implementation of broader interaction between the fields of conservation science and eDNA analysis could create substantial benefits to biodiversity conservation and management. In particular, eDNA analysis can provide information on biodiversity over spatial-temporal scales that are currently prohibitive in spatial planning studies. Here, we provide an overview of how eDNA is currently used in conservation practice, in addition to understanding its limitations and benefits within the context of spatial planning. With the goal to harness rapid technological developments in both molecular and conservation sciences, we provide a horizon scan of the future of eDNA analysis and its application to inform biodiversity conservation in a rapidly changing world

Essai d'étude de l'impact de la « fiche avenir » de ParcourSup sur la réussite en L1 STAPS à l'université de Bourgogne

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Réflexions sur les résultats en L1 STAPS des néobacheliers à l'université de Bourgogne pour la construction d'un outil d'aide à la réussite des lycéens et à l'accompagnement des nouveaux étudiants

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