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Biology subjects

Ballester, C.

Publications and source records attributed to Ballester, C..

2 recordsLinked to original sources

Environmental DNA enables rapid detection of invasive coypu and complements camera trapping

Effective management of invasive species requires surveillance methods that reliably detect populations while minimizing field effort. Environmental DNA (eDNA) offers a potentially rapid alternative to conventional monitoring, but direct comparisons with other non-invasive methods remain limited for invasive mammals. Here, we compared eDNA water sampling and camera trapping for detecting established populations of coypu (Myocastor coypus), an invasive semi-aquatic rodent. Using replicated data collected across Mediterranean river systems in southern France, we estimated detection probabilities conditional on coypu presence using Bayesian generalized linear mixed models and quantified the sampling effort required to achieve high cumulative detection probability. Detection probability was 93.0% (95% credible interval: 72.1-98.9%) for a single eDNA water sample, compared with 52.8% (22.6-91.1%) for 30 camera-trap days, with a 96.9% posterior probability that eDNA detection was higher. Two eDNA samples were sufficient to achieve a median cumulative detection probability above 95%, compared with four 30-day camera-trapping periods. Detection also varied at different spatial scales, with camera-trap detectability being heterogeneous among local camera locations and eDNA detectability varying more among catchments. These results show that eDNA provides a rapid and reliable approach for confirming the presence of established coypu populations, while camera traps provide complementary information on activity, behaviour and habitat use. Combining rapid eDNA screening with targeted camera trapping may therefore provide an efficient surveillance strategy for invasive semi-aquatic mammals.

ecology↗

Towards predictive nanotoxicology: from roundabout of molecular events to chronic inflammation prediction

Nanomaterial-induced diseases cannot be reliably predicted because of the lack of clearly identified causal relationships, in particular between acute exposures and chronic symptoms. By applying advanced microscopies and omics to in vitro and in vivo systems, together with in silico molecular modelling, we have here determined that the long-lasting response to a single exposure originates in the counteracting of a newly discovered nanomaterial quarantining and nanomaterial cycling among different lung cell types. This allows us to predict the nanomaterial-induced spectrum of lung inflammation using only in vitro measurements and in silico modelling. Besides its profound implications for cost-efficient animal-free predictive toxicology, our work also paves the way to a better mechanistic understanding of nanomaterial- induced cancer, fibrosis, and other chronic diseases.

molecular biology↗