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Leroy, C., Maes, A. Q. M., Louisanna, E., Schimann, H., & Séjalon-Delmas, N. (2021). Taxonomic, phylogenetic and functional diversity of rootassociated fungi in bromeliads: effects of host identity, life forms and nutritional modes. New Phytologist, 231(3), 1195–1209.
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.
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Essebtey, S. E. I., Villard, L., Borderies, P., Koleck, T., Burban, B., & Le Toan, T. (2021). Long-Term Trends of P-Band Temporal Decorrelation Over a Tropical Dense Forest-Experimental Results for the BIOMASS Mission. IEEE Transactions on Geoscience and Remote Sensing, 60, 1–15.
Abstract: Fostered by the upcoming BIOMASS mission, this article explores long-term trends of P-band temporal decorrelation over a tropical forest due to a time series of 617 days acquired during the TropiScat-2 experiment. The interest in this unique time series is twofold. First, it provides consistent statistics to monitor the yearly evolution of temporal coherences according to specific time scales of the BIOMASS tomographic and interferometric phases. Second, it provides key insights to explore new processing approaches with the combination of data from different orbit directions (ascending/descending) and different mission cycles separated by about seven months according to the current acquisition plan. For the first time, this study shows that 18-day coherences (corresponding to the time interval between the first and last acquisitions of the BIOMASS tomographic processing) can vary significantly according to rainy and dry seasons (medians from 0.3 to 0.9). The extension to time intervals of up to 90 days within both seasons and over two consecutive years puts forward the key role of the typical sporadic rainfalls occurring during dry periods in tropical rainforests, with a stronger impact on temporal coherence evolution compared to the more reproducible rainy seasons. Furthermore, outstanding values significantly above zero have been obtained for the 7- and 14-month coherences (medians of 0.35 and 0.2, respectively), opening the way to new methods of change detection. Overall, this study highlights the role of P-band temporal decorrelation not only as a disturbance factor for coherent applications but also as a relevant indicator of forest changes.
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Vacher, C., Castagneyrol, B., Jousselin, E., & Schimann, H. (2021). Trees and Insects Have Microbiomes: Consequences for Forest Health and Management. Current Forestry Reports, 7(2), 81–96.
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.
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Poyatos, R., Granda, V., Flo, V., Adams, M. A., Adorjan, B., Aguadé, D., et al. (2021). Global transpiration data from sap flow measurements: the SAPFLUXNET database. Earth System Science Data, 13(6), 2607–2649.
Abstract: Plant transpiration links physiological responses of vegetation to water supply and demand with hydrological, energy, and carbon budgets at the land–atmosphere interface. However, despite being the main land evaporative flux at the global scale, transpiration and its response to environmental drivers are currently not well constrained by observations. Here we introduce the first global compilation of whole-plant transpiration data from sap flow measurements (SAPFLUXNET, https://sapfluxnet.creaf.cat/, last access: 8 June 2021). We harmonized and quality-controlled individual datasets supplied by contributors worldwide in a semi-automatic data workflow implemented in the R programming language. Datasets include sub-daily time series of sap flow and hydrometeorological drivers for one or more growing seasons, as well as metadata on the stand characteristics, plant attributes, and technical details of the measurements. SAPFLUXNET contains 202 globally distributed datasets with sap flow time series for 2714 plants, mostly trees, of 174 species. SAPFLUXNET has a broad bioclimatic coverage, with woodland/shrubland and temperate forest biomes especially well represented (80 % of the datasets). The measurements cover a wide variety of stand structural characteristics and plant sizes. The datasets encompass the period between 1995 and 2018, with 50 % of the datasets being at least 3 years long. Accompanying radiation and vapour pressure deficit data are available for most of the datasets, while on-site soil water content is available for 56 % of the datasets. Many datasets contain data for species that make up 90 % or more of the total stand basal area, allowing the estimation of stand transpiration in diverse ecological settings. SAPFLUXNET adds to existing plant trait datasets, ecosystem flux networks, and remote sensing products to help increase our understanding of plant water use, plant responses to drought, and ecohydrological processes. SAPFLUXNET version 0.1.5 is freely available from the Zenodo repository (https://doi.org/10.5281/zenodo.3971689; Poyatos et al., 2020a). The “sapfluxnetr” R package – designed to access, visualize, and process SAPFLUXNET data – is available from CRAN.
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Harper, A. B., Williams, K. E., McGuire, P., Duran Rojas, M. C., Hemming, D., Verhoef, A., et al. (2021). Improvement of modeling plant responses to low soil moisture in JULESvn4.9 and evaluation against flux tower measurements. Geoscientific Model Development, 14(6), 3269–3294.
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.
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