Search

Abstract We describe the geographical variation in tree species composition across Amazonian forests and show how environmental conditions are associated with species turnover. Our analyses are based on 2023 forest inventory plots (1 ha) that provide abundance data for a total of 5188 tree species. Within-plot species composition reflected both local environmental conditions (especially soil nutrients and hydrology) and geographical regions. A broader-scale view of species turnover was obtained by interpolating the relative tree species abundances over Amazonia into 47,441 0.1-degree grid cells. Two main dimensions of spatial change in tree species composition were identified. The first was a gradient between western Amazonia at the Andean forelands (with young geology and relatively nutrient-rich soils) and central–eastern Amazonia associated with the Guiana and Brazilian Shields (with more ancient geology and poor soils). The second gradient was between the wet forests of the northwest and the drier forests in southern Amazonia. Isolines linking cells of similar composition crossed major Amazonian rivers, suggesting that tree species distributions are not limited by rivers. Even though some areas of relatively sharp species turnover were identified, mostly the tree species composition changed gradually over large extents, which does not support delimiting clear discrete biogeographic regions within Amazonia.

Abstract Using 2.046 botanically-inventoried tree plots across the largest tropical forest on Earth, we mapped tree species-diversity and tree species-richness at 0.1-degree resolution, and investigated drivers for diversity and richness. Using only location, stratified by forest type, as predictor, our spatial model, to the best of our knowledge, provides the most accurate map of tree diversity in Amazonia to date, explaining approximately 70% of the tree diversity and species-richness. Large soil-forest combinations determine a significant percentage of the variation in tree species-richness and tree alpha-diversity in Amazonian forest-plots. We suggest that the size and fragmentation of these systems drive their large-scale diversity patterns and hence local diversity. A model not using location but cumulative water deficit, tree density, and temperature seasonality explains 47% of the tree species-richness in the terra-firme forest in Amazonia. Over large areas across Amazonia, residuals of this relationship are small and poorly spatially structured, suggesting that much of the residual variation may be local. The Guyana Shield area has consistently negative residuals, showing that this area has lower tree species-richness than expected by our models. We provide extensive plot meta-data, including tree density, tree alpha-diversity and tree species-richness results and gridded maps at 0.1-degree resolution.

Abstract A central challenge in ecology is understanding the emergence of patterns as the result of interactions among individuals. Dynamic forest models can provide a fine‐scale description of the ecological, physiological and environmental processes that explain the demography of coexisting tree species. This in turn helps predict changes under future scenarios. However, model accessibility is a major obstacle to a wide use and communication across scientific disciplines and for educational purposes. Here, we present the R package rcontroll, which provides access to the TROLL forest simulator in the R environment. TROLL is individual‐based and spatially explicit and leverages knowledge of ecology, biogeochemistry and tree ecophysiology through a trait‐based parameterisation. TROLL has been used to simulate carbon fluxes and tree diversity in tropical and subtropical forests and to explore forest resilience to disturbance and environmental changes more generally. rcontroll provides a user‐friendly environment to set up and analyse TROLL simulations with varying community compositions, ecological parameters and climate conditions. We show how to test parameter sensitivity in TROLL using the rcontroll R package. We also demonstrate the flexibility and ease of use of rcontroll by replicating a previously published study based on the TROLL simulator. Both examples are included with reproducible code documents. Complex forest simulators are important scientific tools for science and education, and wide access to these tools is an important condition for their adoption. TROLL is designed to address a wide range of ecological and environmental questions, and the new R package rcontroll is designed to be an entry point for TROLL model users.

Abstract In a time of rapid global change, the question of what determines patterns in species abundance distribution remains a priority for understanding the complex dynamics of ecosystems. The constrained maximization of information entropy provides a framework for the understanding of such complex systems dynamics by a quantitative analysis of important constraints via predictions using least biased probability distributions. We apply it to over two thousand hectares of Amazonian tree inventories across seven forest types and thirteen functional traits, representing major global axes of plant strategies. Results show that constraints formed by regional relative abundances of genera explain eight times more of local relative abundances than constraints based on directional selection for specific functional traits, although the latter does show clear signals of environmental dependency. These results provide a quantitative insight by inference from large-scale data using cross-disciplinary methods, furthering our understanding of ecological dynamics.

ABSTRACT Humiria balsamifera is an infraspecific complex of high phenotypic variation and widely distributed in northern South America. Leaf traits are traditionally considered the most relevant taxonomic characters for varietal level delimitation in the group. However, substantial phenotypic overlap among vegetative characters complicates taxonomic diagnoses in this complex. The objective of this study was to quantify and analyze phenotypic variation among individuals of the complex at a continental scale using uni- and multivariable analyses to assess whether morphometric analyses detect discontinuities. Secondarily, these quantitative data were used to test whether phenotypic similarity was related to geographic distance. Twenty- five quantitative and 27 qualitative character traits did not overtly reveal a topology corresponding to traditional varietal classification, nor to geographic structure. However, petiole length alone revealed a definitive separation of H. balsamifera var. guianensis (together with another recognized species Humiria wurdackii, and variety H. balsamifera var. laurina) from the rest of the taxa. Our results highlight substantial morphological overlap among vegetative and reproductive characters including those used in identification keys, and no morphological discontinuities suitable for clearly separating taxa within the complex were encountered demonstrating a future need to integrate multiple sources of information, including molecular data, to resolve this complex.

Abstract Resorption is the active withdrawal of nutrients before leaf abscission. This mechanism represents an important strategy to maintain efficient nutrient cycling; however, resorption is poorly characterized in old‐growth tropical forests growing in nutrient‐poor soils. We investigated nutrient resorption from leaves in 39 tree species in two tropical forests on the Guiana Shield, French Guiana, to investigate whether resorption efficiencies varied with soil nutrient, seasonality, and species traits. The stocks of P in leaves, litter, and soil were low at both sites, indicating potential P limitation of the forests. Accordingly, mean resorption efficiencies were higher for P (35.9%) and potassium (K; 44.6%) than for nitrogen (N; 10.3%). K resorption was higher in the wet (70.2%) than in the dry (41.7%) season. P resorption increased slightly with decreasing total soil P; and N and P resorptions were positively related to their foliar concentrations. We conclude that nutrient resorption is a key plant nutrition strategy in these old‐growth tropical forests, that trees with high foliar nutrient concentration reabsorb more nutrient, and that nutrients resorption in leaves, except P, are quite decoupled from nutrients in the soil. Seasonality and biochemical limitation played a role in the resorption of nutrients in leaves, but species‐specific requirements obscured general tendencies at stand and ecosystem level.

Tree mortality has been shown to be the dominant control on carbon storage in Amazon forests, but little is known of how and why Amazon forest trees die. Here the authors analyse a large Amazon-wide dataset, finding that fast-growing species face greater mortality risk, but that slower-growing individuals within a species are more likely to die, regardless of size.

A Correction to this paper has been published: https://doi.org/10.1038/s41467-020-20537-x

The forests of Kalimantan are under severe pressure from extensive land use activities dominated by logging, palm oil plantations, and peatland fires. To implement the forest moratorium for mitigating greenhouse gas emissions, Indonesia’s government requires information on the carbon stored in forests, including intact, degraded, secondary, and peat swamp forests. We developed a hybrid approach of producing a wall-to-wall map of the aboveground biomass (AGB) of intact and degraded forests of Kalimantan at 1 ha grid cells by combining field inventory plots, airborne lidar samples, and satellite radar and optical imagery. More than 110 000 ha of lidar data were acquired to systematically capture variations of forest structure and more than 104 field plots to develop lidar-biomass models. The lidar measurements were converted into biomass using models developed for 66 439 ha of drylands and 44 250 ha of wetland forests. By combining the AGB map with the national land cover map, we found that 22.3 Mha (10 ^6 ha) of forest remain on drylands ranging in biomass from 357.2 ± 12.3 Mgha ^−1 in relatively intact forests to 134.2 ± 6.1 Mgha ^−1 in severely degraded forests. The remaining peat swamp forests are heterogeneous in coverage and degradation level, extending over 3.62 Mha and having an average AGB of 211.8 ± 12.7 Mgha ^−1 . Emission factors calculated from aboveground biomass only suggest that the carbon storage potential of more than 15 Mha of degraded and secondary dryland forests will be about 1.1 PgC.

Around the world, the human-induced collapses of populations and species have triggered a sixth mass extinction crisis, with rare species often being the first to disappear. Although the role of species diversity in the maintenance of ecosystem processes has been widely investigated, the role of rare species remains controversial. A critical issue is whether common species insure against the loss of functions supported by rare species. This issue is even more critical in species-rich ecosystems where high functional redundancy among species is likely and where it is thus often assumed that ecosystem functioning is buffered against species loss. Here, using extensive datasets of species occurrences and functional traits from three highly diverse ecosystems (846 coral reef fishes, 2,979 alpine plants, and 662 tropical trees), we demonstrate that the most distinct combinations of traits are supported predominantly by rare species both in terms of local abundance and regional occupancy. Moreover, species that have low functional redundancy and are likely to support the most vulnerable functions, with no other species carrying similar combinations of traits, are rarer than expected by chance in all three ecosystems. For instance, 63% and 98% of fish species that are likely to support highly vulnerable functions in coral reef ecosystems are locally and regionally rare, respectively. For alpine plants, 32% and 89% of such species are locally and regionally rare, respectively. Remarkably, 47% of fish species and 55% of tropical tree species that are likely to support highly vulnerable functions have only one individual per sample on average. Our results emphasize the importance of rare species conservation, even in highly diverse ecosystems, which are thought to exhibit high functional redundancy. Rare species offer more than aesthetic, cultural, or taxonomic diversity value; they disproportionately increase the potential breadth of functions provided by ecosystems across spatial scales. As such, they are likely to insure against future uncertainty arising from climate change and the ever-increasing anthropogenic pressures on ecosystems. Our results call for a more detailed understanding of the role of rarity and functional vulnerability in ecosystem functioning.

Abstract Landscape restoration initiatives are mainly focusing on forest regeneration and agroforestry, especially in the Global South. However, due to a lack of monitoring tools, the carbon balance of restoration efforts remains poorly quantified. Here, we use satellite images from 2008 and 2019 to calculate carbon stocks for individual trees in Rwanda, a country which has been actively engaged in restoration activities over the past decade. We show that smallholder farmers on average planted about 3 trees per farm during 2008–2019, contributing about 50.4 million new trees at the national scale. The overall C sink of the new farmland trees was 0.13 Megagrams of Carbon per hectare per year, which is 6 times lower than gains observed from restoration of degraded forests (0.76 Megagrams of Carbon per hectare per year). If national greenhouse gas emissions remain at the level of 2019, agroforestry (~61% of national area coverage) and continued restoration of degraded natural forests (~0.5% of national area coverage) have the potential to offset about 80% of the national emissions before 2050. Our work monitors and quantifies progress and impact of landscape restoration projects and outlines a pathway to engage smallholder farmers with a limited number of on-farm trees into the expanding carbon market.

The increase in Earth observations from space in recent years supports improved quantification of carbon storage by terrestrial vegetation and fosters studies that relate satellite measurements to biomass retrieval algorithms. However, satellite observations are only indirectly related to the carbon stored by vegetation. While ground surveys provide biomass stock measurements to act as reference for training the models, they are sparsely distributed. Here, we addressed this problem by designing an algorithm that harnesses the interplay of satellite observations, modeling frameworks and field measurements, and generated global estimates of above-ground biomass (AGB) density that meet the requirements of the scientific community in terms of accuracy, spatial and temporal resolution. The design was adapted to the amount, type and spatial distribution of satellite data available around the year 2020. The retrieval algorithm estimated AGB annually by merging estimates derived from C- and L-band Synthetic Aperture Radar (SAR) backscatter observations with a Water Cloud type of model and does not rely on AGB reference data at the same spatial scale as the SAR data. This model is integrated with functions relating to forest structural variables that were trained on spaceborne LiDAR observations and sub-national AGB statistics. The yearly estimates of AGB were successively harmonized using a cost function that minimizes spurious fluctuations arising from the moderate-to-weak sensitivity of the SAR backscatter to AGB. The spatial distribution of the AGB estimates was correctly reproduced when the retrieval model was correctly set. Over-predictions occasionally occurred in the low AGB range (300 Mg ha−1). These errors were a consequence of sometimes too strong generalizations made within the modeling framework to allow reliable retrieval worldwide at the expense of accuracy. The precision of the estimates was mostly between 30% and 80% relative to the estimated value. While the framework is well founded, it could be improved by incorporating additional satellite observations that capture structural properties of vegetation (e.g., from SAR interferometry, low-frequency SAR, or high-resolution observations), a dense network of regularly monitored high-quality forest biomass reference sites, and spatially more detailed characterization of all model parameters estimates to better reflect regional differences.

Abstract Habitat fragmentation could potentially affect tree architecture and allometry. Here, we use ground surveys of terrestrial LiDAR in Central Amazonia to explore the influence of forest edge effects on tree architecture and allometry, as well as forest biomass, 40 years after fragmentation. We find that young trees colonising the forest fragments have thicker branches and architectural traits that optimise for light capture, which result in 50% more woody volume than their counterparts of similar stem size and height in the forest interior. However, we observe a disproportionately lower height in some large trees, leading to a 30% decline in their woody volume. Despite the substantial wood production of colonising trees, the lower height of some large trees has resulted in a net loss of 6.0 Mg ha−1 of aboveground biomass – representing 2.3% of the aboveground biomass of edge forests. Our findings indicate a strong influence of edge effects on tree architecture and allometry, and uncover an overlooked factor that likely exacerbates carbon losses in fragmented forests.

IntroductionIn contrast to the dynamics observed in plant/pathogen interactions, endophytic fungi have the capacity to establish enduring associations within their hosts, leading to the development of a mutually beneficial relationship that relies on specialized chemical interactions. Research indicates that the presence of endophytic fungi has the ability to significantly modify the chemical makeup of the host organism. Our hypothesis proposes the existence of a reciprocal exchange of chemical signals between plants and fungi, facilitated by specialized chemical processes that could potentially manifest within the tissues of the host. This research aimed to precisely quantify the portion of the cumulative fungal endophytic community's metabolome detectable within host leaves, and tentatively evaluate its relevance to the host-endophyte interplay. The understory palm Astrocaryum sciophilum (Miq.) Pulle was used as a interesting host plant because of its notable resilience and prolonged life cycle, in a tropical ecosystem.MethodUsing advanced metabolome characterization, including UHPLC-HRMS/MS and molecular networking, the study explored enriched metabolomes of both host leaves and 15 endophytic fungi. The intention was to capture a metabolomic "snapshot" of both host and endophytic community, to achieve a thorough and detailed analysis.Results and discussionThis approach yielded an extended MS-based molecular network, integrating diverse metadata for identifying host- and endophyte-derived metabolites. The exploration of such data (>24000 features in positive ionization mode) enabled effective metabolome comparison, yielding insights into cultivable endophyte chemodiversity and occurrence of common metabolites between the holobiont and its fungal communities. Surprisingly, a minor subset of features overlapped between host leaf and fungal samples despite significant plant metabolome enrichment. This indicated that fungal metabolic signatures produced in vitro remain sparingly detectable in the leaf. Several classes of primary metabolites were possibly shared. Specific fungal metabolites and/or compounds of their chemical classes were only occasionally discernible in the leaf, highlighting endophytes partial contribution to the overall holobiont metabolome. To our knowledge, the metabolomic study of a plant host and its microbiome has rarely been performed in such a comprehensive manner. The general analytical strategy proposed in this paper seems well-adapted for any study in the field of microbial- or microbiome-related MS and can be applied to most host-microbe interactions.

Abstract The consistent monitoring of trees both inside and outside of forests is key to sustainable land management. Current monitoring systems either ignore trees outside forests or are too expensive to be applied consistently across countries on a repeated basis. Here we use the PlanetScope nanosatellite constellation, which delivers global very high-resolution daily imagery, to map both forest and non-forest tree cover for continental Africa using images from a single year. Our prototype map of 2019 (RMSE = 9.57%, bias = −6.9%). demonstrates that a precise assessment of all tree-based ecosystems is possible at continental scale, and reveals that 29% of tree cover is found outside areas previously classified as tree cover in state-of-the-art maps, such as in croplands and grassland. Such accurate mapping of tree cover down to the level of individual trees and consistent among countries has the potential to redefine land use impacts in non-forest landscapes, move beyond the need for forest definitions, and build the basis for natural climate solutions and tree-related studies.

Measurement(s) plant trait Technology Type(s) various Factor Type(s) none Sample Characteristic - Organism Tracheophyta Sample Characteristic - Environment natural environment Sample Characteristic - Location global

The forest understory experiences temperature variations that are dampened compared to adjacent open areas, allowing the development of a forest microclimate and associated ecological conditions. It is however unclear to what extent forests will maintain this buffering effect under increasing global warming. Providing reliable projections of future forest microclimates is therefore crucial to anticipate climate change impacts on forest biodiversity, and to identify corresponding conservation strategies. Recent empirical studies suggest that the buffering of air temperature extremes in forest understory compared to open land could increase with global warming, albeit at a slower rate than macroclimate temperatures. Here, we investigate the trend of this temperature buffering effect in a high-emission global warming scenario, using the process-based Land Surface Model CLM5.1. We find biome-dependant buffering trends with strongest values in tropical forests where buffering increases for every degree of global warming by 0.1 ^∘ C for maximum soil temperature, and by 0.2 ^∘ C for maximum canopy air temperature. In boreal regions, forest microclimate exhibits a strong seasonality and the effect of global warming is more uncertain. Thus, our results highlight the importance of tropical forest canopies in particular, in maintaining hospitable conditions for understory species while increasing their climate debt under global warming. Our research also illustrates the potential and limitations of Land Surface Models to simulate forest microclimate, and calls for further collaborations between Earth system modelers and ecologists to jointly question climate and biosphere dynamics.

Over the past 2 to 3 decades, Chinese forests are estimated to act as a large carbon sink, yet the magnitude and spatial patterns of this sink differ considerably among studies. Using 3 microwave (L- and X-band vegetation optical depth [VOD]) and 3 optical (normalized difference vegetation index, leaf area index, and tree cover) remote-sensing vegetation products, this study compared the estimated live woody aboveground biomass carbon (AGC) dynamics over China between 2013 and 2019. Our results showed that tree cover has the highest spatial consistency with 3 published AGC maps (mean correlation value R = 0.84), followed by L-VOD (R = 0.83), which outperform the other VODs. An AGC estimation model was proposed to combine all indices to estimate the annual AGC dynamics in China during 2013 to 2019. The performance of the AGC estimation model was good (root mean square error = 0.05 Pg C and R2 = 0.90 with a mean relative uncertainty of 9.8% at pixel scale [0.25°]). Results of the AGC estimation model showed that carbon uptake by the forests in China was about +0.17 Pg C year−1 from 2013 to 2019. At the regional level, provinces in southwest China including Guizhou (+22.35 Tg C year−1), Sichuan (+14.49 Tg C year−1), and Hunan (+11.42 Tg C year−1) provinces had the highest carbon sink rates during 2013 to 2019. Most of the carbon-sink regions have been afforested recently, implying that afforestation and ecological engineering projects have been effective means for carbon sequestration in these regions.

Quantifying forest degradation and biodiversity losses is necessary to inform conservation and restoration policies. Here the authors analyze a large dataset for the Atlantic Forest in South America to quantify losses in forest biomass and tree species richness, functional traits, and conservation value.

Extreme wind blowdown events can significantly modify the structure and composition of forests, and the predicted shift in tropical cyclone regimes due to climate change could strongly impact forests across the tropics. In this study, we coupled an individual-based and spatially-explicit forest dynamics model (TROLL) with a mechanistic model estimating wind damage as a function of tree size, traits, and allometry (ForestGALES). We assimilated floristic trait data and climate data from a subtropical forest site in Taiwan to explore the effect of wind regimes on forest properties. We found that the average canopy height and biomass stocks decreased as wind disturbance strength increased, but biomass stocks showed a nonlinear response. Above a wind intensity threshold, both canopy height and biomass drastically decreased to near-zero, exhibiting a transition to a non-forest state. Wind intensity strongly regulated wind impact, but varying wind frequency did not cause discernible effects. The implementation of within-stand topographic heterogeneity led to weak effects on within-stand forest structure heterogeneity at the study site. In conclusion, the intensity of wind disturbances can potentially greatly impact forest structure by modifying mortality. Individual-based modeling provides a framework in which to investigate the impact of wind regimes on mortality, other factors influencing wind-induced tree mortality, as well as interaction between wind and other forms of forest disturbance and human land use legacy.

Background and aims – The evolutionary history of Amazonia’s hyperabundant tropical tree species, also known as “hyperdominant” species, remains poorly investigated. We assessed whether the hyperdominant Eschweilera coriacea (DC.) S.A.Mori (Lecythidaceae) represents a single genetically cohesive species, and how its genetic constitution relates to other species from the same clade with which it occurs sympatrically in French Guiana.Methods – We sampled 152 individuals in nine forest sites in French Guiana, representing 11 species of the genus Eschweilera all belonging to the Parvifolia clade, with emphasis on E. coriacea. Samples were genotyped at four simple sequence repeat (SSR) markers. We delimited gene pools, i.e., genetically coherent putative taxa, using STRUCTURE software and principal component analysis. We compared the genetic assignment of individuals with their morphological species determination and estimated genetic diversity and differentiation for gene pools and species. We also estimated genome size using flow cytometry.Key results – SSR profiles commonly displayed up to four alleles per genotype, suggesting that the investigated Eschweilera species bear a paleopolyploid signature. Flow cytometry suggested that the studied species are diploid with haploid genome sizes of 871–1046 Mbp. We detected five gene pools and observed a good correspondence between morphological and genetic delimitation for Eschweilera sagotiana Miers and the undescribed morphospecies E. sp. 3 (which resembles E. grandiflora (Aubl.) Sandwith), and to a lesser extent for E. decolorans Sandwith and E. micrantha (O.Berg) Miers. Eschweilera coriacea was the most genetically diverse species and included individuals assigned to each gene pool. Conclusions – We found no conclusive evidence for cryptic species within E. coriacea in French Guiana. SSRs detected fewer gene pools than expected based on morphology in the Parvifolia clade but discriminated evolutionary relationships better than available plastid markers. A positive trend between demographic abundance of species and allelic richness illustrates that hyperdominants may have a high evolutionary potential. This hypothesis can be tested using more powerful genomic data in combination with tree phenotypic trait variation and characterization of niche breadth, to enhance our understanding of the causes of hyperdominance in Amazonian trees.

Urban expansion and associated habitat transformation drives shifts in biodiversity, with declines in taxonomic and functional diversity. Forests fragments within urban landscapes offer a number of ecosystem services, and help to maintain biodiversity and ecosystem functions. Here, we focus on a tropical forest environment, and on the soil biota. Using eDNA metabarcoding, we compare forest fragments within the city of Cayenne, French Guiana, with a neighbouring continuous undisturbed forest. We wished to determine if urban forest fragments conserve high levels of alpha and beta diversity as well as similar functional composition for plants, soil animals, fungi and bacteria. We found that alpha diversity is similar across habitats for plants and fungi, lower in urban forests for metazoans and higher for bacteria. We also found that urban forests communities differ from undisturbed forests in their taxonomic composition, with urban forests exhibiting greater turnover between fragments potentially caused by ecological drift and limited dispersal. However, their functional composition exhibited limited differences, with an enrichment of palms, arbuscular mycorrhizal fungi and bacteria and a depletion of climber plants and termites. Thus, although urban forest fragments do shelter soil biodiversity that differs from native forests, the losses of soil functions may be relatively limited. This study demonstrates the strong potential of a multi-taxa eDNA approach for rapid inventories across taxonomic kingdoms, in particular for cryptic soil diversity. It also demonstrates the key role of urban forest fragments in conserving biodiversity and ecosystem function, and points to a need for more systematic monitoring of these areas in urban management plans.

The Wnt signaling pathway controls multiple events during embryonic development of multicellular animals and is carcinogenic when aberrantly activated in adults. Breast cancers are dependent on Wnt pathway overactivation mostly through dysregulation of pathway component protein expression, which necessitates the search for therapeutically relevant compounds targeting them. Highly diverse microorganisms as endophytes represent an underexplored field in the therapeutic natural products research. In the present work, the objective was to explore the chemical diversity and presence of selective Wnt inhibitors within a unique collection of fungi isolated as foliar endophytes from the long-lived tropical palm Astrocaryum sciophilum. The fungi were cultured, extracted with ethyl acetate, and screened for their effects on the Wnt pathway and cell proliferation. The endophytic strain Lasiodiplodia venezuelensis was prioritized for scaled-up fractionation based on its selective activity. Application of geometric transfer from analytical HPLC conditions to semi-preparative scale and use of dry load sample introduction enabled the isolation of 15 pure compounds in a single step. Among the molecules identified, five are original natural products described for the first time, and six are new to this species. An active fraction obtained by semi-preparative HPLC was re-purified by UHPLC-PDA using a 1.7 µm phenyl column. 75 injections of 8 µg were necessary to obtain sufficient amounts of each compound for structure elucidation and bioassays. Using this original approach, in addition to the two major compounds, a third minor compound identified as (R)-(-)-5-hydroxymellein (18) was obtained, which was found to be responsible for the significant Wnt inhibition activity recorded. Further studies of this compound and its structural analogs showed that only 18 acts in a highly specific manner, with no acute cytotoxicity. This compound is notably selective for upstream components of the Wnt pathway and is able to inhibit the proliferation of three triple negative breast cancer cell lines. In addition to the discovery of Wnt inhibitors of interest, this study contributes to better characterize the biosynthetic potential of L. venezuelensis.

Abstract Background Wet tropical forests of Chocó, along the Pacific Coast of Colombia, are known for their high plant diversity and endemic species. With increasing pressure of degradation and deforestation, these forests have been prioritized for conservation and carbon offset through Reducing Emissions from Deforestation and forest Degradation (REDD+) mechanisms. We provide the first regional assessment of forest structure and aboveground biomass using measurements from a combination of ground tree inventories and airborne Light Detection and Ranging (Lidar). More than 80,000 ha of lidar samples were collected based on a stratified random sampling to provide a regionally unbiased quantification of forest structure of Chocó across gradients of vegetation structure, disturbance and elevation. We developed a model to convert measurements of vertical structure of forests into aboveground biomass (AGB) for terra firme, wetlands, and mangrove forests. We used the Random Forest machine learning model and a formal uncertainty analysis to map forest height and AGB at 1-ha spatial resolution for the entire pacific coastal region using spaceborne data, extending from the coast to higher elevation of Andean forests. Results Upland Chocó forests have a mean canopy height of 21.8 m and AGB of 233.0 Mg/ha, while wetland forests are characterized by a lower height and AGB (13.5 m and 117.5 Mg/a). Mangroves have a lower mean height than upland forests (16.5 m), but have a similar AGB as upland forests (229.9 Mg/ha) due to their high wood density. Within the terra firme forest class, intact forests have the highest AGB (244.3 ± 34.8 Mg/ha) followed by degraded and secondary forests with 212.57 ± 62.40 Mg/ha of biomass. Forest degradation varies in biomass loss from small-scale selective logging and firewood harvesting to large-scale tree removals for gold mining, settlements, and illegal logging. Our findings suggest that the forest degradation has already caused the loss of more than 115 million tons of dry biomass, or 58 million tons of carbon. Conclusions Our assessment of carbon stocks and forest degradation can be used as a reference for reporting on the state of the Chocó forests to REDD+ projects and to encourage restoration efforts through conservation and climate mitigation policies.

Lakes play a key role in the global water cycle, providing essential water resources and ecosystem services for humans and wildlife. Quantifying long-term changes in lake volume at a global scale is therefore important to the sustainability of humanity and natural ecosystems. Yet, such an estimate is still unavailable because, unlike lake area, lake volume is three-dimensional, challenging to be estimated consistently across space and time. Here, taking advantage of recent advances in remote sensing technology, especially NASA’s ICESat-2 satellite laser altimeter launched in 2018, we generated monthly volume series from 2003 to 2020 for 9065 lakes worldwide with an area ≥ 10 km2. We found that the total volume of the 9065 lakes increased by 597 km3 (90% confidence interval 239–2618 km3). Validation against in situ measurements showed a correlation coefficient of 0.98, an RMSE (i.e., root mean square error) of 0.57 km3 and a normalized RMSE of 2.6%. In addition, 6753 (74.5%) of the lakes showed an increasing trend in lake volume and were spatially clustered into nine hot spots, most of which are located in sparsely populated high latitudes and the Tibetan Plateau; 2323 (25.5%) of the lakes showed a decreasing trend in lake volume and were clustered into six hot spots—most located in the world’s arid/semi-arid regions where lakes are scarce, but population density is high. Our results uncovered, from a three-dimensional volumetric perspective, spatially uneven lake changes that aggravate the conflict between human demands and lake resources. The situation is likely to intensify given projected higher temperatures in glacier-covered regions and drier climates in arid/semi-arid areas. The 15 hot spots could serve as a blueprint for prioritizing future lake research and conservation efforts.

Abstract  Volatile organic compounds (VOCs) are produced by a broad range of organisms, from bacteria to mammals, and they represent a vast chemical diversity. In plants, one of the preeminent roles of VOCs is their repellent or cytotoxic activity, which helps the plant deter its predators. Most studies on VOCs emitted by vegetative parts have been conducted in model plant species, and little is known about patterns of VOC emissions in diverse plant communities. We conducted a survey of the VOCs released immediately after mechanical damage of the bark and the leaves of 195 individual trees belonging to 55 tropical tree species in a lowland rainforest of French Guiana. We discovered a remarkably high chemical diversity, with 264 distinct VOCs and a mean of 37 compounds per species. Two monoterpenes (α-pinene and limonene) and two sesquiterpenes (β-caryophyllene and α-copaene), which are known to have cytotoxic and deterrent effects, were the most frequent compounds in the sampled species. As has been established for floral scents, the blend of VOCs is largely species-specific and could be used to discriminate among 43 of the 55 sampled species. The species with the most diverse blends were found in the Sapindales, Laurales, and Magnoliales, indicating that VOC diversity is not uniformly distributed among tropical species. Interspecific variation in chemical diversity was caused mostly by variation in sesquiterpenes. This study emphasizes three aspects of VOC emission by tropical tree species: the species-specificity of the mixtures, the importance of sesquiterpenes, and the wide-ranging complexity of the mixtures. [ABSTRACT FROM AUTHOR]

The opportunistic pathogen Pseudomonas aeruginosa is one of the “critical priority pathogens” due to its multidrug resistance to a wide range of antibiotics. Its ability to invade and damage host tissues is due to the use of quorum sensing (QS) to collectively produce a plethora of virulence factors. Inhibition of QS is an attractive strategy for new antimicrobial agents because it disrupts the initial events of infection without killing the pathogen. Highly diverse microorganisms as endophytes represent an under-explored source of bioactive natural products, offering opportunities for the discovery of novel QS inhibitors (QSI). In the present work, the objective was to explore selective QSIs within a unique collection of fungal endophytes isolated from the tropical palm Astrocaryum sciophilum. The fungi were cultured, extracted, and screened for their antibacterial and specific anti-QS activities against P. aeruginosa. The endophytic strain Lasiodiplodia venezuelensis was prioritized for scaled-up fractionation for its selective activity, leading to the isolation of eight compounds in a single step. Among them, two pyran-derivatives were found to be responsible for the QSI activity, with an effect on some QS-regulated virulence factors. Additional non-targeted metabolomic studies on P. aeruginosa documented their effects on the production of various virulence-related metabolites.

Amazonian tree species vary enormously in their total abundance and range size, while Amazonian tree genera vary greatly in species richness. The drivers of this variation are not well understood. Here, we construct a phylogenetic hypothesis that represents half of Amazonian tree genera in order to contribute to explaining the variation. We find several clear, broad-scale patterns. Firstly, there is significant phylogenetic signal for all three characteristics; closely related genera tend to have similar numbers of species and similar mean range size and abundance. Additionally, the species richness of genera shows a significant, negative relationship with the mean range size and abundance of their constituent species. Our results suggest that phylogenetically correlated intrinsic factors, namely traits of the genera themselves, shape among lineage variation in range size, abundance and species richness. We postulate that tree stature may be one particularly relevant trait. However, other traits may also be relevant, and our study reinforces the need for ambitious compilations of trait data for Amazonian trees. In the meantime, our study shows how large-scale phylogenies can help to elucidate, and contribute to explaining, macroecological and macroevolutionary patterns in hyperdiverse, yet poorly understood regions like the Amazon Basin.