Climate change may have minor impact on zooplankton functional diversity in the Mediterranean Sea

Aim To assess the impact of climate change on the functional diversity of marine zooplankton communities. Location The Mediterranean Sea. Methods We used the functional traits and geographic distributions of 106 copepod species to estimate the zooplankton functional diversity of Mediterranean surface assemblages for the 1965–1994 and 2069–2098 periods. Multiple environmental niche models were trained at the global scale to project the species habitat suitability in the Mediterranean Sea and assess their sensitivity to climate change predicted by several scenarios. Simultaneously, the species traits were used to compute a functional dendrogram from which we identified seven functional groups and estimated functional diversity through Faith's index. We compared the measured functional diversity to the one originated from null models to test if changes in functional diversity were solely driven by changes in species richness. Results All but three of the 106 species presented range contractions of varying intensity. A relatively low decrease of species richness (−7.42 on average) is predicted for 97% of the basin, with higher losses in the eastern regions. Relative sensitivity to climate change is not clustered in functional space and does not significantly vary across the seven copepod functional groups defined. Changes in functional diversity follow the same pattern and are not different from those that can be expected from changes in richness alone. Main conclusions Climate change is not expected to alter copepod functional traits distribution in the Mediterranean Sea, as the most and the least sensitive species are functionally redundant. Such redundancy should buffer the loss of ecosystem functions in Mediterranean zooplankton assemblages induced by climate change. Because the most negatively impacted species are affiliated to temperate regimes and share Atlantic biogeographic origins, our results are in line with the hypothesis of increasingly more tropical Mediterranean communities

Project based learning for mathematics in general engineering curriculum

The National Engineering School of Tarbes (ENIT) is a French engineering school with a curriculum from undergraduate to graduate studies for general engineers. Curriculum ends by an equivalent Master degree in sciences. ENIT students are particularly involved into mechanical, civil, industrial engineering, material science and design of integrated systems. From the first year of study, students tackle theoretical tools for engineers. Moreover, in a curriculum composed of several different disciplines, connections between scientific subjects may be difficult to weave. As a consequence, student activities for solving engineering problems were developed. The basic concept is to clearly illustrate how theoretical tools can be used in an activity linked to engineering and more generally to student life. In addition, future engineers must be acquainted and trained to ethic values, especially those used in team work. During team working, honesty and benevolence are important core values to be encouraged as a basis of trust that has been identified as one of the cornerstones for performing teams. Consequently, the principle of team working for students was adopted and humanities are associated into the project to manage ethical and professional standards. Thus, the chosen teaching activity is a project-based learning team work that addresses on the one hand application of integration and derivation to expression of needs of consumable supplies and notions around professional ethics on the other hands

Functional biogeography of oceanic islands and the scaling of functional diversity in the Azores

Analyses of species-diversity patterns of remote islands have been crucial to the development of biogeographic theory, yet little is known about corresponding patterns in functional traits on islands and how, for example, they may be affected by the introduction of exotic species. We collated trait data for spiders and beetles and used a functional diversity index (FRic) to test for nonrandomness in the contribution of endemic, other native (also combined as indigenous), and exotic species to functional-trait space across the nine islands of the Azores. In general, for both taxa and for each distributional category, functional diversity increases with species richness, which, in turn scales with island area. Null simulations support the hypothesis that each distributional group contributes to functional diversity in proportion to their species richness. Exotic spiders have added novel trait space to a greater degree than have exotic beetles, likely indicating greater impact of the reduction of immigration filters and/or differential historical losses of indigenous species. Analyses of species occurring in native-forest remnants provide limited indications of the operation of habitat filtering of exotics for three islands, but only for beetles. Although the general linear (not saturating) pattern of trait-space increase with richness of exotics suggests an ongoing process of functional enrichment and accommodation, further work is urgently needed to determine how estimates of extinction debt of indigenous species should be adjusted in the light of these findings

Ecological dependencies make remote reef fish communities most vulnerable to coral loss

yEcosystems face both local hazards, such as over-exploitation, and global hazards, such as climate change. Since the impact of local hazards attenuates with distance from humans, local extinction risk should decrease with remoteness, making faraway areas safe havens for biodiversity. However, isolation and reduced anthropogenic disturbance may increase ecological specialization in remote communities, and hence their vulnerability to secondary effects of diversity loss propagating through networks of interacting species. We show this to be true for reef fish communities across the globe. An increase in fish-coral dependency with the distance of coral reefs from human settlements, paired with the far-reaching impacts of global hazards, increases the risk of fish species loss, counteracting the benefits of remoteness. Hotspots of fish risk from fish-coral dependency are distinct from those caused by direct human impacts, increasing the number of risk hotspots by similar to 30% globally. These findings might apply to other ecosystems on Earth and depict a world where no place, no matter how remote, is safe for biodiversity, calling for a reconsideration of global conservation priorities.Peer reviewe

Global tropical reef fish richness could decline by around half if corals are lost

Reef fishes are a treasured part of marine biodiversity, and also provide needed protein for many millions of people. Although most reef fishes might survive projected increases in ocean temperatures, corals are less tolerant. A few fish species strictly depend on corals for food and shelter, suggesting that coral extinctions could lead to some secondary fish extinctions. However, secondary extinctions could extend far beyond those few coral-dependent species. Furthermore, it is yet unknown how such fish declines might vary around the world. Current coral mass mortalities led us to ask how fish communities would respond to coral loss within and across oceans. We mapped 6964 coral-reef-fish species and 119 coral genera, and then regressed reef-fish species richness against coral generic richness at the 1 degrees scale (after controlling for biogeographic factors that drive species diversification). Consistent with small-scale studies, statistical extrapolations suggested that local fish richness across the globe would be around half its current value in a hypothetical world without coral, leading to more areas with low or intermediate fish species richness and fewer fish diversity hotspots.Peer reviewe

Spatial scaling of forest soil microbial communities across a temperature gradient.

Temperature is an important correlate of global patterns of biodiversity, yet the mechanisms driving these relationships are not well understood. Taxa-area relationships (TARs) have been intensively examined, but the effects of temperature on TARs, particularly for microbial communities, are largely undocumented. Here we present a continental-scale description of temperature-dependent nested TARs of microbial communities (bacteria and archaea) from soils of six forest sites spanning a temperature gradient from subalpine Colorado to tropical Panama. Our results revealed that spatial scaling rates (z-values) of microbial communities varied with both taxonomic resolutions and phylogenetic groups. Additionally, microbial TAR z-values increased with temperature (r = 0.739, P < 0.05), but were not correlated with other environmental variables tested (P > 0.05), indicating that microbial spatial scaling rate is temperature-dependent. Understanding how temperature affects the spatial scaling of microbial biodiversity is of fundamental importance for preservation of soil biodiversity and management of ecosystems

An Automatic Palindrome Generator

In 1984 Dan Hoey, a US naval mathematician, wrote a computer which he used to create a 540-word expansion of Leigh Mercer\u27s Panama palindrome (PD). It began A man, a plan, a caret, a ban, a myriad, a sum, a lac... and ended ...a calmus, a diaryman, a bater, a canal Panama. (For the full PD, plus additional information, see http://www2.vo.lu/homepages/phahn/anagrams/panama/htm.

GEOAI FOR MARINE ECOSYSTEM MONITORING: A COMPLETE WORKFLOW TO GENERATE MAPS FROM AI MODEL PREDICTIONS

Mapping and monitoring marine ecosystems imply several challenges for data collection and processing: water depth, restricted access to locations, instrumentation costs or weather constraints for sampling, among others. Nowadays, Artificial Intelligence (AI) and Geographic Information System (GIS) open source software can be combined in new kinds of workflows, to annotate and predict objects directly on georeferenced raster data (e.g. orthomosaics). Here, we describe and share the code of a generic method to train a deep learning model with spatial annotations and use it to directly generate model predictions as spatial features. This workflow has been tested and validated in three use cases related to marine ecosystem monitoring at different geographic scales: (i) segmentation of corals on orthomosaics made of underwater images to automate coral reef habitats mapping, (ii) detection and classification of fishing vessels on remote sensing satellite imagery to estimate a proxy of fishing effort (iii) segmentation of marine species and habitats on underwater images with a simple geolocation. Models have been successfully trained and the models predictions are displayed with maps in the three use cases