Biology subjects

Meynard, C. N.

Publications and source records attributed to Meynard, C. N..

4 recordsLinked to original sources

bioRxiv2026

Threatened species bycatch hotspots in the tropical Atlantic Ocean

Predicting bycatch patterns in tropical tuna purse seine fisheries remain challenging due to low variance explained by existing models, limiting their use for management purposes. To address this limitation, we combined ecological network analyses and community detection methods to characterize recurring bycatch assemblages in tropical tuna purse seine fisheries. Ecological network analyses consistently revealed two key bycatch communities: one dominated by bony fishes with low conservation concern, and another by IUCN-listed threatened species (NT-CR; sharks, rays, sea turtles). By focusing on sets with high numbers of threatened species, we identified bycatch hotspots near Mauritania, Gabon and Angola. These hotspots result from seasonal fishing patterns and specific bycatch compositions, with specific composition in terms of sex and age, compared to the rest of the Atlantic. We suggest that the Mauritanian region is a potential candidate for shark nursery and sea turtle foraging grounds. These insights can guide the development of bycatch reduction strategies based on predictable spatio-temporal or community-specific features and provide a basis for targeted management actions.

ecology↗

bioRxiv2023

Functional trade-offs: exploring the effects of climate change and agricultural practices as drivers of field margin plant communities

Over the past decades, agricultural intensification and climate change have led to vegetation shifts. However, functional trade-offs linking traits responding to climate and farming practices are rarely analyzed, especially on large-scale empirical studies. Here we used a standardized yearly monitoring effort of agricultural field margin flora at the national scale to assess the temporal response of diversity and functional traits to variations in climate and intensity of agricultural practices. We examined temporal trends in climate (temperature, soil moisture), intensity of agricultural practices (herbicides, fertilization, margin management), plant species richness, and community-weighted means and variances of traits expected to vary both with climate and agricultural practices (e.g. seed mass, specific leaf area), across 555 sites in France between 2013 and 2021. We found clear temporal climatic trends (temperature increased while soil moisture decreased), whereas trends in agricultural practices were weak over the past decade, with only slight decreases in herbicides and margin management intensity. During the same period, functional changes in plant communities were significant, showing an increase of thermophilic species (including some Mediterranean species) with a conservative resource acquisition strategy (high stature, late and short flowering), mainly explained by climate change. The reduction in field margin management intensity (mainly mowing), also resulted in a vegetation shift towards a more conservative strategy. In contrast, there was no impact of the slight temporal changes of practices conducted within cultivated fields (herbicides, fertilization) on vegetation changes. Our findings suggest that species adapted to climate change (including Mediterranean and conservative species) have temporally increased in proportion. Importantly, we identified functional trade-offs indicating that these species are also the most vulnerable to intensive agricultural practices, as they are less adapted to high levels of resources and disturbances. We put these results into the conceptual framework of Grimes CSR triangle and revealed a temporal decline of competitive and ruderal species in favor of stress-tolerant species better adapted to climate change. Choosing less intensive management can broaden the functional spectrum of agricultural plant communities, by maintaining the ability of stress-tolerant species selected by climate change to colonize habitats largely dominated by ruderals. Put together, these results suggest that climate change and agricultural intensification could have synergistic negative impacts on plant diversity in field margins, highlighting the need to study several biodiversity drivers at the same time in anthropized landscapes.

ecology↗

bioRxiv2023

Scale dependence in agricultural drivers of field margin plant communities: influence of spatial resolution and extent

In recent decades, agricultural intensification has led to a strong decline in biodiversity. Field margins act as shelters and dispersal corridors for biodiversity in highly disturbed landscapes, and are critical to the maintenance of ecosystem services. However, they are also impacted by agricultural practices in neighbouring fields. Agricultural impacts are often studied at field to landscape scales, and rarely across biogeographic regions. One of the challenges in large-scale studies is the lack of standardized monitoring schemes including both biodiversity and accurate estimation of agricultural practices. Here, we take advantage of a national monitoring scheme in 462 sites in France, to assess the effects of agricultural practices on field margin flora at different extents and resolutions. We used spatial simultaneous autoregressive and generalized dissimilarity models to assess the response of plant richness and composition to climatic, soil and landscape conditions, and to agricultural (fertilization, herbicides) and margin management drivers. Analyses were repeated at the site-level, 40 and 75 km resolutions, and at regional and national extents. We found that the impact of agricultural practices on species richness was most important at the site-level, whereas climate and crop diversity became more important at the 75 km resolution. Compositional variations responded differently, with climate being more important at the site-level, and fertilization and crop diversity at the coarsest resolution. There was a strong variation in the variance explained by models among regions, but climate effects were weaker within biogeographic units compared to the national level, and different agricultural practices stood out as influential in different regions, suggesting that the regional context is fundamental in determining plant community structure. To efficiently conserve biodiversity, we therefore recommend the implementation of agricultural measures adapted to each region.

ecology↗

bioRxiv2017

Theoretical solutions for the evaluation of discrimination capacity of species distribution models

The discriminating capacity (i.e., ability to correctly classify presences and absences) of species distribution models (SDMs) is commonly evaluated with metrics such as the Area Under the Receiving Operating Characteristic Curve, the Kappa statistic and the True Skill Statistic (TSS). AUC and Kappa have been repeatedly criticised, but the TSS has fared relatively well since its introduction, mainly because it has been considered as independent of prevalence. In addition, discrimination metrics have been contested because they should be calculated on presence-absence data, but are often used on presence-only or presence-background data. Here, we investigate the TSS and an alternative set of metrics -similarity indices, also known as F-measures. We first show that even in ideal conditions (i.e., perfectly random presence-absence sampling), TSS can be misleading because of its dependence on prevalence, whereas similarity/F-measures provide adequate estimations of model discrimination capacity. Second, we show that in real-world situations where sample prevalence is different from true species prevalence (i.e., biased sampling or presence-pseudoabsence), no discrimination capacity metric provide adequate estimations of model discrimination capacity, including metrics specifically designed for presence-pseudoabsence. Our conclusions are twofold. First, they unequivocally appeal SDM users to understand the potential shortcomings of discrimination metrics when quality presence-absence data are lacking, and we provide recommendations to obtain such data. Second, in the specific case of virtual species, which are increasingly used to develop and test SDM methodologies, we strongly recommend the use of similarity/F-measures, which were not biased by prevalence, contrary to TSS.

ecology↗