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Dominance of neotropical tree communities by a few species is widely documented, but dominant trees show a variety of distributional patterns still poorly understood. Here, we used 503 forest inventory plots (93,719 individuals ≥2.5 cm diameter, 2609 species) to explore the relationships between local abundance, regional frequency and spatial aggregation of dominant species in four main habitat types in western Amazonia. Although the abundance-occupancy relationship is positive for the full dataset, we found that among dominant Amazonian tree species, there is a strong negative relationship between local abundance and regional frequency and/or spatial aggregation across habitat types. Our findings suggest an ecological trade-off whereby dominant species can be locally abundant (local dominants) or regionally widespread (widespread dominants), but rarely both (oligarchs). Given the importance of dominant species as drivers of diversity and ecosystem functioning, unravelling different dominance patterns is a research priority to direct conservation efforts in Amazonian forests., (© 2023 The Authors. Ecology Letters published by John Wiley & Sons Ltd.)

The forests of Amazonia are among the most biodiverse plant communities on Earth. Given the immediate threats posed by climate and land-use change, an improved understanding of how this extraordinary biodiversity is spatially organized is urgently required to develop effective conservation strategies. Most Amazonian tree species are extremely rare but a few are common across the region. Indeed, just 227 'hyperdominant' species account for >50% of all individuals >10 cm diameter at 1.3 m in height. Yet, the degree to which the phenomenon of hyperdominance is sensitive to tree size, the extent to which the composition of dominant species changes with size class and how evolutionary history constrains tree hyperdominance, all remain unknown. Here, we use a large floristic dataset to show that, while hyperdominance is a universal phenomenon across forest strata, different species dominate the forest understory, midstory and canopy. We further find that, although species belonging to a range of phylogenetically dispersed lineages have become hyperdominant in small size classes, hyperdominants in large size classes are restricted to a few lineages. Our results demonstrate that it is essential to consider all forest strata to understand regional patterns of dominance and composition in Amazonia. More generally, through the lens of 654 hyperdominant species, we outline a tractable pathway for understanding the functioning of half of Amazonian forests across vertical strata and geographical locations.

Non-structural carbohydrates (NSC) are major substrates for plant metabolism and have been implicated in mediating drought-induced tree mortality. Despite their significance, NSC dynamics in tropical forests remain little studied. We present leaf and branch NSC data for 82 Amazon canopy tree species in six sites spanning a broad precipitation gradient. During the wet season, total NSC (NSC T ) concentrations in both organs were remarkably similar across communities. However, NSC T and its soluble sugar (SS) and starch components varied much more across sites during the dry season. Notably, the proportion of leaf NSC T in the form of SS (SS:NSC T ) increased greatly in the dry season in almost all species in the driest sites, implying an important role of SS in mediating water stress in these sites. This adjustment of leaf NSC balance was not observed in tree species less-adapted to water deficit, even under exceptionally dry conditions. Thus, leaf carbon metabolism may help to explain floristic sorting across water availability gradients in Amazonia and enable better prediction of forest responses to future climate change.

The carbon sink capacity of tropical forests is substantially affected by tree mortality. However, the main drivers of tropical tree death remain largely unknown. Here we present a pan-Amazonian assessment of how and why trees die, analysing over 120,000 trees representing > 3800 species from 189 long-term RAINFOR forest plots. While tree mortality rates vary greatly Amazon-wide, on average trees are as likely to die standing as they are broken or uprooted-modes of death with different ecological consequences. Species-level growth rate is the single most important predictor of tree death in Amazonia, with faster-growing species being at higher risk. Within species, however, the slowest-growing trees are at greatest risk while the effect of tree size varies across the basin. In the driest Amazonian region species-level bioclimatic distributional patterns also predict the risk of death, suggesting that these forests are experiencing climatic conditions beyond their adaptative limits. These results provide not only a holistic pan-Amazonian picture of tree death but large-scale evidence for the overarching importance of the growth-survival trade-off in driving tropical tree mortality.

The sensitivity of tropical forest carbon to climate is a key uncertainty in predicting global climate change. Although short-term drying and warming are known to affect forests, it is unknown if such effects translate into long-term responses. Here, we analyze 590 permanent plots measured across the tropics to derive the equilibrium climate controls on forest carbon. Maximum temperature is the most important predictor of aboveground biomass (-9.1 megagrams of carbon per hectare per degree Celsius), primarily by reducing woody productivity, and has a greater impact per °C in the hottest forests (>32.2°C). Our results nevertheless reveal greater thermal resilience than observations of short-term variation imply. To realize the long-term climate adaptation potential of tropical forests requires both protecting them and stabilizing Earth's climate., (Copyright © 2020 The Authors, some rights reserved; exclusive licensee American Association for the Advancement of Science. No claim to original U.S. Government Works.)

Background. Carnivore mammals are animals vulnerable to human interference, such as climate change and deforestation. Their distribution and persistence are affected by such impacts, mainly in tropical regions such as the Amazon. Due to the importance of carnivores in the maintenance and functioning of the ecosystem, they are extremely important animals for conservation. We evaluated the impact of climate change on the geographic distribution of carnivores in the Amazon using Species Distribution Models (SDMs). Do we seek to answer the following questions: (1) What is the effect of climate change on the distribution of carnivores in the Amazon? (2) Will carnivore species lose or gain representation within the Protected Areas (PAs) of the Amazon in the future? Methods. Weevaluated the distribution area of 16 species of carnivores mammals in the Amazon, based on two future climate scenarios (RCP 4.5 and RCP 8.5) for the year 2070. For the construction of the SDMs we used bioclimatic and vegetation cover variables (land type). Based on these models, we calculated the area loss and climate suitability of the species, as well as the effectiveness of the protected areas inserted in the Amazon. We estimated the effectiveness of PAs on the individual persistence of carnivores in the future, for this, we used the SDMs to perform the gap analysis. Finally, we analyze the effectiveness of PAs in protecting taxonomic richness in future scenarios. Results. The SDMs showed satisfactory predictive performance, with Jaccard values above 0.85 and AUC above 0.91 for all species. In the present and for the future climate scenarios, we observe a reduction of potencial distribution in both future scenarios (RCP4.5 and RCP8.5), where five species will be negatively affected by climate change in the RCP 4.5 future scenario and eight in the RCP 8.5 scenario. The remaining species stay stable in terms of total area. All species in the study showed a loss of climatic suitability. Some species lost almost all climatic suitability in the RCP 8.5 scenario. According to the GAP analysis, all species are protected within the PAs both in the current scenario and in both future climate scenarios. From the null models, we found that in all climate scenarios, the PAs are not efficient in protecting species richness. [ABSTRACT FROM AUTHOR]

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This article describes a data-driven framework based on spatiotemporal machine learning to produce distribution maps for 16 tree species (Abies alba Mill., Castanea sativa Mill., Corylus avellana L., Fagus sylvatica L., Olea europaea L., Picea abies L. H. Karst., Pinus halepensis Mill., Pinus nigra J. F. Arnold, Pinus pinea L., Pinus sylvestris L., Prunus avium L., Quercus cerris L., Quercus ilex L., Quercus robur L., Quercus suber L. and Salix caprea L.) at high spatial resolution (30 m). Tree occurrence data for a total of three million of points was used to train different algorithms: random forest, gradient-boosted trees, generalized linear models, k-nearest neighbors, CART and an artificial neural network. A stack of 305 coarse and high resolution covariates representing spectral reflectance, different biophysical conditions and biotic competition was used as predictors for realized distributions, while potential distribution was modelled with environmental predictors only. Logloss and computing time were used to select the three best algorithms to tune and train an ensemble model based on stacking with a logistic regressor as a meta-learner. An ensemble model was trained for each species: probability and model uncertainty maps of realized distribution were produced for each species using a time window of 4 years for a total of six distribution maps per species, while for potential distributions only one map per species was produced. Results of spatial cross validation show that the ensemble model consistently outperformed or performed as good as the best individual model in both potential and realized distribution tasks, with potential distribution models achieving higher predictive performances (TSS = 0.898, R²logloss = 0.857) than realized distribution ones on average (TSS = 0.874, R²logloss = 0.839). Ensemble models for Q. suber achieved the best performances in both potential (TSS = 0.968, R²logloss = 0.952) and realized (TSS = 0.959, R²logloss = 0.949) distribution, while P. sylvestris (TSS = 0.731, 0.785, R²logloss = 0.585, 0.670, respectively, for potential and realized distribution) and P. nigra (TSS = 0.658, 0.686, R²logloss = 0.623, 0.664) achieved the worst. Importance of predictor variables differed across species and models, with the green band for summer and the Normalized Difference Vegetation Index (NDVI) for fall for realized distribution and the diffuse irradiation and precipitation of the driest quarter (BIO17) being the most frequent and important for potential distribution. On average, fine-resolution models outperformed coarse resolution models (250 m) for realized distribution (TSS = +6.5%, R²logloss = +7.5%). The framework shows how combining continuous and consistent Earth Observation time series data with state of the art machine learning can be used to derive dynamic distribution maps. The produced predictions can be used to quantify temporal trends of potential forest degradation and species composition change. [ABSTRACT FROM AUTHOR]

Amazonia is extremely biodiverse, but the mechanisms for the origin of this diversity are still under debate. We propose a diversification model for Amazonia based on the interplay of intrinsic clade functional traits, habitat associations and past geological events, using as a model group the species-rich Neotropical family Marantaceae. Our results show that the species richness of the lineage is predicted by functional strategy, rather than clade age, and thus the fast vs. slow growth functional trade-off is a major determinant of clade diversification in Marantaceae. Rapidly growing clades were mostly associated with highly productive habitats, and their origin and diversification dynamics matched the expansion of fertile soils mediated by Andean uplift c. 23 Mya. Fast-growth strategies probably led to fast molecular evolution, speeding up speciation rates and species accumulation, resulting in higher numbers of extant species. Our results indicate that pure allopatric-dispersal models disconnected from past geological and ecological forces may be inadequate for explaining the evolutionary and diversity patterns in Amazonian lowlands. We suggest that a coupling of the functional trait-niche framework with diversification dynamics provides insights into the evolutionary history of tropical forests and helps elucidate the mechanisms underlying the origin and evolution of its spectacular biodiversity. [ABSTRACT FROM AUTHOR]

Key message: At the sixth and seventh years of a drought event in south of Chile, non-structural carbohydrate (NSC) concentrations were similar between healthy and unhealthy trees of Araucaria araucana (Molina) K. Koch, and growth did not decrease, suggesting that leaf loss prevented C shortage in unhealthy trees. Context: Tree drought resistance and resilience may be impaired by decreasing growth and non-structural carbohydrates (NSC). During a 7-year drought, the isohydric species Araucaria araucana (Araucariaceae) evidenced decline (foliage loss and browning). Aims: To determine whether tree decline was related to an impaired carbon status and reduced growth. Methods: In two sites of southern Chile, we selected healthy- and unhealthy-looking trees to study drought effects on NSC and growth. We measured the basal area increment (BAI) and NSC concentrations of needles and roots after 6 years of drought (2016) and following one less severe year in terms of drought (2017). Results: At both years, healthy and unhealthy trees had similar NSC and sugar concentrations in needle and roots, and furthermore, they maintained their growth rates. In 2017, NSC, starch, and sugar concentrations of needles (but not roots) increased in both healthy and unhealthy trees at one of the study sites, while growth did not vary. Conclusion: Unhealthy trees likely prevented C shortage through an acclimation mechanism such as foliage loss. The remarkable similar NSC concentrations found between healthy and unhealthy trees indicates the absence of C starvation in trees that lost a substantial fraction of their foliage under drought. [ABSTRACT FROM AUTHOR]

Key message: Tree growth of Nectandra amazonum (Lauraceae) in the Central Amazonian floodplains does not respond to the annual long-term flooding but responds to variation of minimum temperature and potential evapotranspiration. During the last two decades, the Central Amazon region has been impacted by increasingly frequent and more severe floods and droughts and increasing temperature. Little is known about the effects of these climate trends on tree growth in floodplain forests. In this study, we analysed Nectandra amazonum (Lauraceae), an evergreen and flood-adapted tree species, dominant not only in the nutrient-rich Amazonian floodplains (várzea), but also occurring in other environments within and outside the Amazon basin. For the period from 2001 to 2017, intra- and interannual climate–growth relationships of N. amazonum were analysed applying a combination of conventional dendrochronological (cross-dating) and densiometric techniques to construct a robust tree-ring chronology. Six wood parameters were derived from the chronology (ring width, width of earlywood and latewood and corresponding wood density values) and correlated with local climate and hydrologic data. The analysed 32 trees did not show correlation between wood parameters and variation of the hydrological regime. Climate–growth relationships indicated that potential evapotranspiration and minimum temperature play an important role in tree growth mainly during the period of transition between the dry and the wet seasons, and during the aquatic phase affecting physiological processes such as photosynthesis and respiration, respectively. We discuss these results in the background of changing hydroclimatic conditions induced by climate and land-use change in the Amazon basin. Based on our findings, we emphasize the need for more dendroclimatic studies in the tropics applying a multiproxy approach. This will deepen our understanding of tree growth responses, helping to elucidate the dynamic processes of tropical forests that grow under global change impacts. [ABSTRACT FROM AUTHOR]

Peruvian national and regional plans promoting oil palm have prompted a rapid expansion of the crop in the Amazonian region. This expansion has taken place primarily at the expense of forest, both undisturbed and disturbed. Assessments of carbon emissions from forest-to-oil palm conversion have essentially been confined to Southeast Asia, and research on Peruvian Amazonian forests has mainly targeted undisturbed sites. This study characterizes the vegetation structure and composition of disturbed forests and smallholder oil palm plantations and evaluates the change in ecosystem (that is, phytomass and soil) carbon stocks associated with forest-to-oil palm conversion. Inventories were conducted in four degraded forest sites neighboring six oil palm plantation sites in Ucayali. Time-averaged carbon stocks over the 30-year oil palm rotation were computed from models developed upon the sampled chronosequence (1 to 28 years old). Disturbed forests harbored species typical of primary forests, pioneer species and gaps opportunistic species. Their tree basal area (18.7 ± 1.4 m2 ha−1) and above-ground C stock (71.3 ± 4.2 Mg C ha−1) were, respectively, 50 and 60% of the values of undisturbed forests from the literature. The growth curve for oil palm above-ground biomass was consistently below models developed for plantations in Indonesia. Thirty-year time-averaged ecosystem C stock (Mg C ha−1) in oil palm plantations (78.2 ± 2.0) represented 55% of the stock in disturbed forest (140.9 ± 5.8), resulting in a 62.7 ± 6.1 loss from such conversion. These results reinforce recommendations to redirect oil palm expansion toward low-carbon degraded lands, sparing disturbed and undisturbed forests. [ABSTRACT FROM AUTHOR]

The long-term dynamics of regeneration in tropical forests dominated by single tree species remains largely undocumented, yet is key to understanding the mechanisms by which one species can gain dominance and resist environmental change. We report here on the long-term regeneration dynamics in a monodominant stand of Brosimum rubescens Taub. (Moraceae) at the southern border of the Amazon forest. Here the climate has warmed and dried since the mid-1990′s. Twenty-one years of tree and liana regeneration were evaluated in four censuses in 30 plots by assessing species abundance, dominance, and diversity in all regeneration classes up to 5 cm diameter. The density of B. rubescens seedlings declined markedly, from 85% in 1997 to 29% in 2018 after the most intense El Niño-driven drought. While the fraction contributed by other tree species changed little, the relative density of liana seedlings increased from just 1 to 54% and three-quarters of liana species underwent a ten-fold or greater increase in abundance. The regeneration community experienced a high rate of species turnover, with changes in the overall richness and species diversity determined principally by lianas, not trees. Long-term maintenance of monodominance in this tropical forest is threatened by a sharp decline in the regeneration of the monodominant species and the increase in liana density, suggesting that monodominance will prove to be a transitory condition. The close association of these rapid changes with drying indicates that monodominant B. rubescens forests are impacted by drought-driven changes in regeneration, and therefore are particularly sensitive to climatic change. [ABSTRACT FROM AUTHOR]