Abstract: For highly specialized insect herbivores, plant chemical defenses are often co-opted as cues for oviposition and sequestration. In such interactions, can plants evolve novel defenses, pushing herbivores to trade off benefits of specialization with costs of coping with toxins? We tested how variation in milkweed toxins (cardenolides) impacted monarch butterfly ( Danaus plexippus ) growth, sequestration, and oviposition when consuming tropical milkweed ( Asclepias curassavica ), one of two critical host plants worldwide. The most abundant leaf toxin, highly apolar and thiazolidine ring–containing voruscharin, accounted for 40% of leaf cardenolides, negatively predicted caterpillar growth, and was not sequestered. Using whole plants and purified voruscharin, we show that monarch caterpillars convert voruscharin to calotropin and calactin in vivo, imposing a burden on growth. As shown by in vitro experiments, this conversion is facilitated by temperature and alkaline pH. We next employed toxin-target site experiments with isolated cardenolides and the monarch’s neural Na + /K + -ATPase, revealing that voruscharin is highly inhibitory compared with several standards and sequestered cardenolides. The monarch’s typical >50-fold enhanced resistance to cardenolides compared with sensitive animals was absent for voruscharin, suggesting highly specific plant defense. Finally, oviposition was greatest on intermediate cardenolide plants, supporting the notion of a trade-off between benefits and costs of sequestration for this highly specialized herbivore. There is apparently ample opportunity for continued coevolution between monarchs and milkweeds, although the diffuse nature of the interaction, due to migration and interaction with multiple milkweeds, may limit the ability of monarchs to counteradapt.

Abstract: Rivers of French Guiana are still little invaded by non-native fish, but several fish introductions were recently recorded through the development of aquarium fish trade and fish farms. Here we report records of 11 non-native fish species. Among them, four (Cichla monoculus, Heros efasciatus, Mesonauta guyanae and Poecilia reticulata) are established and one of them (Heros efasciatus) is rapidly increasing its spatial range. Two species (Hyphessobrycon eques and Pterophyllum scalare) were not retrieved in recent records and are probably extinct from French Guiana. The establishment status of the five other species (Arapaima gigas, Colossoma macropomum, Cyprinus carpio, Oreochromis mossambicus and Osteoglossum bicirrhosum) is uncertain and only a few specimens were observed in the wild. Nevertheless, these species, intensively reared in nearby countries, belong to highly invasive species able to cause detrimental impacts on recipient ecosystems. Those first occurrences of invasive fish species in French Guiana should therefore act as an early warning for both researchers and environmental managers.

Abstract: Amazonian forests are extraordinarily diverse, but the estimated species richness is very much debated. Here, we apply an ensemble of parametric estimators and a novel technique that includes conspecific spatial aggregation to an extended database of forest plots with up-to-date taxonomy. We show that the species abundance distribution of Amazonia is best approximated by a logseries with aggregated individuals, where aggregation increases with rarity. By averaging several methods to estimate total richness, we confirm that over 15,000 tree species are expected to occur in Amazonia. We also show that using ten times the number of plots would result in an increase to just ~50% of those 15,000 estimated species. To get a more complete sample of all tree species, rigorous field campaigns may be needed but the number of trees in Amazonia will remain an estimate for years to come. © 2020, The Author(s).

Abstract: Little is known regarding how trophic interactions shape community assembly in tropical forests. Here we assess multi-taxonomic community assembly rules using a rare standardized coordinated inventory comprising exhaustive surveys of five highly-diverse taxonomic groups exerting key ecological functions: trees, fungi, earthworms, ants and spiders. We sampled 36 1.9-ha plots from four remote locations in French Guiana including precise soil measurements, and we tested whether species turnover was coordinated among groups across geographic and edaphic gradients. All species group pairs exhibited significant compositional associations that were independent from soil conditions. For some of the pairs, associations were also partly explained by soil properties, especially soil phosphorus availability. Our study provides evidence for coordinated turnover among taxonomic groups beyond simple relationships with environmental factors, thereby refining our understanding regarding the nature of interactions occurring among these ecologically important groups. © 2019, The Author(s).

Abstract: The FLUXNET2015 dataset provides ecosystem-scale data on CO2, water, and energy exchange between the biosphere and the atmosphere, and other meteorological and biological measurements, from 212 sites around the globe (over 1500 site-years, up to and including year 2014). These sites, independently managed and operated, voluntarily contributed their data to create global datasets. Data were quality controlled and processed using uniform methods, to improve consistency and intercomparability across sites. The dataset is already being used in a number of applications, including ecophysiology studies, remote sensing studies, and development of ecosystem and Earth system models. FLUXNET2015 includes derived-data products, such as gap-filled time series, ecosystem respiration and photosynthetic uptake estimates, estimation of uncertainties, and metadata about the measurements, presented for the first time in this paper. In addition, 206 of these sites are for the first time distributed under a Creative Commons (CC-BY 4.0) license. This paper details this enhanced dataset and the processing methods, now made available as open-source codes, making the dataset more accessible, transparent, and reproducible.