Abstract: Large carnivores play a pivotal regulating role in maintaining healthy and balanced ecosystems; however, most of them are rare and elusive, and knowledge about their resource consumption is scarce. Traditional methods based on morphological identification of undigested remains are labor intensive and often not sufficiently accurate, leading to errors and biased ecological inferences. Here, we developed a multi-marker DNA metabarcoding approach to analyze the dietary diversity of giant otters (Pteronura brasiliensis) from fecal DNA while controlling predator species identity. We combined two mitochondrial markers, 12S rRNA and cytochrome c oxidase 1 (COI) gene, that target the full range of potential vertebrate and invertebrate prey. We compiled a local reference database of DNA barcodes for most potentially ingested fish, which were used to evaluate the specificity of the metabarcoding primers in silico. Most prey are identified at the species level (>90%) and the dietary profiles provided independently by the two markers are highly similar, whether in terms of list of prey or frequency of occurrences, hence validating the approach. We detected a higher number of rare fish prey with the 12S primers that amplified solely Teleost species while the degenerate COI primers revealed non-fish prey (e.g., amphibians, snakes, birds, and earthworms) and confirmed predator species identity. This study demonstrated that scat DNA metabarcoding is particularly useful to provide in-depth information on elusive carnivorous dietary profile. Our methodology opens up new opportunities to understand how top carnivores diet cope with the effects of anthropogenic alteration of ecosystems and identify conflicts with humans and livestock.

Abstract: Drought is predicted to increase in the future due to climate change, bringing with it myriad impacts on ecosystems. Plants respond to drier soils by reducing stomatal conductance in order to conserve water and avoid hydraulic damage. Despite the importance of plant drought responses for the global carbon cycle and local and regional climate feedbacks, land surface models are unable to capture observed plant responses to soil moisture stress. We assessed the impact of soil moisture stress on simulated gross primary productivity (GPP) and latent energy flux (LE) in the Joint UK Land Environment Simulator (JULES) vn4.9 on seasonal and annual timescales and evaluated 10 different representations of soil moisture stress in the model. For the default configuration, GPP was more realistic in temperate biome sites than in the tropics or high-latitude (cold-region) sites, while LE was best simulated in temperate and high-latitude (cold) sites. Errors that were not due to soil moisture stress, possibly linked to phenology, contributed to model biases for GPP in tropical savanna and deciduous forest sites. We found that three alternative approaches to calculating soil moisture stress produced more realistic results than the default parameterization for most biomes and climates. All of these involved increasing the number of soil layers from 4 to 14 and the soil depth from 3.0 to 10.8 m. In addition, we found improvements when soil matric potential replaced volumetric water content in the stress equation (the “soil14psi” experiments), when the critical threshold value for inducing soil moisture stress was reduced (“soil14p0”), and when plants were able to access soil moisture in deeper soil layers (“soil14_dr*2”). For LE, the biases were highest in the default configuration in temperate mixed forests, with overestimation occurring during most of the year. At these sites, reducing soil moisture stress (with the new parameterizations mentioned above) increased LE and increased model biases but improved the simulated seasonal cycle and brought the monthly variance closer to the measured variance of LE. Further evaluation of the reason for the high bias in LE at many of the sites would enable improvements in both carbon and energy fluxes with new parameterizations for soil moisture stress. Increasing the soil depth and plant access to deep soil moisture improved many aspects of the simulations, and we recommend these settings in future work using JULES or as a general way to improve land surface carbon and water fluxes in other models. In addition, using soil matric potential presents the opportunity to include plant functional type-specific parameters to further improve modeled fluxes.

Abstract: Purpose of Review Forest research has shown for a long time that microorganisms influence tree-insect interactions, but the complexity of microbial communities, as well as the holobiont nature of both trees and insect herbivores, has only recently been taken fully into account by forest entomologists and ecologists. In this article, we review recent findings on the effects of tree-insect-microbiome interactions on the health of tree individuals and discuss whether and how knowledge about tree and insect microbiomes could be integrated into forest health management strategies. We then examine the effects tree-insect-microbiome interactions on forest biodiversity and regeneration, highlighting gaps in our knowledge at the ecosystem scale. Recent Findings Multiple studies show that herbivore damage in forest ecosystems is clearly influenced by tripartite interactions between trees, insects and their microbiomes. Recent research on the plant microbiome indicates that microbiomes of planted trees could be managed at several stages of production, from seed orchards to mature forests, to improve the resistance of forest plantations to insect pests. Therefore, the tree microbiome could potentially be fully integrated into forest health management strategies. To achieve this aim, future studies will have to combine, as has long been done in forest research, holistic goals with reductionist approaches. Efforts should be made to improve our understanding of how microbial fluxes between trees and insects determine the health of forest ecosystems, and to decipher the underlying mechanisms, through the development of experimental systems in which microbial communities can be manipulated. Knowledge about tree-insect-microbiome interactions should then be integrated into spatial models of forest dynamics to move from small-scale mechanisms to forest ecosystem-scale predictions.

Abstract: Bromeliads represent a major component of neotropical forests and encompass a considerable diversity of life forms and nutritional modes. Bromeliads explore highly stressful habitats and root-associated fungi may play a crucial role in this, but the driving factors and variations in root-associated fungi remain largely unknown.
We explored root-associated fungal communities in 17 bromeliad species and their variations linked to host identity, life forms and nutritional modes by using ITS1 gene-based high-throughput sequencing and by characterizing fungal functional guilds.
We found a dual association of mycorrhizal and nonmycorrhizal fungi. The different species, life forms and nutritional modes among bromeliad hosts had fungal communities that differ in their taxonomic and functional composition. Specifically, roots of epiphytic bromeliads had more endophytic fungi and dark septate endophytes and fewer mycorrhizal fungi than terrestrial bromeliads and lithophytes.
Our results contribute to a fundamental knowledge base on different fungal groups in previously undescribed Bromeliaceae. The diverse root-associated fungal communities in bromeliads may enhance plant fitness in both stressful and nutrient-poor environments and may give more flexibility to the plants to adapt to changing environmental conditions.

Abstract: Tree buckling risk (actual height/critical buckling height) is an important biomechanical trait of plant growth strategies, and one that contributes to species coexistence. To estimate the diversity of this trait among wide samples, a method that minimizes damage to the plants is necessary. On the basis of the rarely used, complete version of Greenhill's model (1881, Proceedings of the Cambridge Philosophical Society 4(2): 65-73), we precisely measured all the necessary parameters on a sample of 236 saplings of 16 species. Then, using sensitivity (variance) analysis, regressions between successive models for risk factors and species ranks and the use of these models on samples of self- and nonself-supporting saplings, we tested different degrees of simplification up to the most simple and widely used formula that assumes that the tree is a cylindrical homogeneous pole. The size factor had the greatest effect on buckling risk, followed by the form factor and the modulus of elasticity of the wood. Therefore, estimates of buckling risk must consider not only the wood properties but especially the form factor. Finally, we proposed a simple but accurate method of assessing tree buckling risk that is applicable to a wide range of samples and that requires mostly nondestructive measurements.