Amazon forest biogeography predicts resilience and vulnerability to drought.

Amazonia contains the most extensive tropical forests on Earth, but Amazon carbon sinks of atmospheric CO2 are declining, as deforestation and climate-change-associated droughts1-4 threaten to push these forests past a tipping point towards collapse5-8. Forests exhibit complex drought responses, indicating both resilience (photosynthetic greening) and vulnerability (browning and tree mortality), that are difficult to explain by climate variation alone9-17. Here we combine remotely sensed photosynthetic indices with ground-measured tree demography to identify mechanisms underlying drought resilience/vulnerability in different intact forest ecotopes18,19 (defined by water-table depth, soil fertility and texture, and vegetation characteristics). In higher-fertility southern Amazonia, drought response was structured by water-table depth, with resilient greening in shallow-water-table forests (where greater water availability heightened response to excess sunlight), contrasting with vulnerability (browning and excess tree mortality) over deeper water tables. Notably, the resilience of shallow-water-table forest weakened as drought lengthened. By contrast, lower-fertility northern Amazonia, with slower-growing but hardier trees (or, alternatively, tall forests, with deep-rooted water access), supported more-drought-resilient forests independent of water-table depth. This functional biogeography of drought response provides a framework for conservation decisions and improved predictions of heterogeneous forest responses to future climate changes, warning that Amazonia's most productive forests are also at greatest risk, and that longer/more frequent droughts are undermining multiple ecohydrological strategies and capacities for Amazon forest resilience.

The other side of tropical forest drought: do shallow water table regions of Amazonia act as large-scale hydrological refugia from drought?

Tropical forest function is of global significance to climate change responses, and critically determined by water availability patterns. Groundwater is tightly related to soil water through the water table depth (WT), but historically neglected in ecological studies. Shallow WT forests (WT < 5 m) are underrepresented in forest research networks and absent in eddy flux measurements, although they represent c. 50% of the Amazon and are expected to respond differently to global-change-related droughts. We review WT patterns and consequences for plants, emerging results, and advance a conceptual model integrating environment and trait distributions to predict climate change effects. Shallow WT forests have a distinct species composition, with more resource-acquisitive and hydrologically vulnerable trees, shorter canopies and lower biomass than deep WT forests. During 'normal' climatic years, shallow WT forests have higher mortality and lower productivity than deep WT forests, but during moderate droughts mortality is buffered and productivity increases. However, during severe drought, shallow WT forests may be more sensitive due to shallow roots and drought-intolerant traits. Our evidence supports the hypothesis of neglected shallow WT forests being resilient to moderate drought, challenging the prevailing view of widespread negative effects of climate change on Amazonian forests that ignores WT gradients, but predicts they could collapse under very strong droughts.

O funcionamento da floresta tropical é de importância global para as respostas às mudanças climáticas e é criticamente determinado pelos padrões de disponibilidade de água. A água subterrânea está intimamente relacionada à água do solo através da profundidade do lençol freático, que tem sido historicamente negligenciado em estudos ecológicos. Florestas com lençol freático raso (< 5 m) estão sub-representadas nas redes de pesquisa florestal e ausentes nas medições de fluxo de gases, embora representem ~ 50% da Amazônia e devam responder de forma diferente às secas relacionadas às mudanças globais. Aqui revisamos os padrões de profundidade do lençol freático e suas consequências para plantas, resultados emergentes, e avançamos em um modelo conceitual que integra o ambiente e as distribuições de características funcionais para prever os efeitos das mudanças climáticas. As florestas com lençol freático raso têm uma composição de espécies distinta, com árvores mais aquisitivas na obtenção de recursos e hidrologicamente vulneráveis, dosséis mais baixos e menor biomassa do que as florestas com lençol freático profundo. Durante os anos climáticos 'normais', as florestas com lençol freático raso têm maior mortalidade e menor produtividade do que as florestas com lençol freático profundo, mas durante secas moderadas, a mortalidade é amortecida e a produtividade aumenta. No entanto, durante secas severas, as florestas com lençol freático raso podem ser mais sensíveis devido às raízes superficiais e características funcionais de intolerância à seca. Nossas evidências apoiam a hipótese de que as florestas com lençol freático raso, historicamente negligenciadas, sejam resilientes à seca moderada, desafiando a visão predominante dos efeitos negativos generalizados da mudança climática nas florestas amazônicas que ignora gradientes de profundidade do lençol freático, mas prevê que elas podem entrar em colapso sob secas muito fortes.

La función de los bosques tropicales es de importancia mundial para las respuestas al cambio climático y está críticamente determinada por los patrones de disponibilidad de agua. El agua subterránea está estrechamente relacionada con el agua del suelo a través de la profundidad del nivel freático (NF), pero históricamente se há negligenciado en los estudios ecológicos. Los bosques con NF poco profundos (NF < 5 m) están subrepresentados en las redes de investigación forestal y ausentes en las mediciones de flujo de gases, aunque representan ~ 50% de la Amazonía y se espera que respondan de manera diferente a las sequías relacionadas con el cambio climático global. Aquí revisamos los patrones de NF y las consecuencias para las plantas, los resultados emergentes y avanzamos en un modelo conceptual que integra distribuciones ambientales y de rasgos funcionales para predecir los efectos del cambio climático. Los bosques con NF poco profundos tienen una composición de especies distinta, con árboles más adquisitivos en la obtención de recursos e hidrológicamente más vulnerables, dosel más bajo y menor biomasa que los bosques de NF profundo. Durante los años climáticos 'normales', los bosques con NF poco profundos tienen una mayor mortalidad y menor productividad que los bosques con NF profundos, pero durante sequías moderadas la mortalidad se amortigua y la productividad aumenta. Sin embargo, durante una sequía severa, los bosques de NF poco profundos pueden ser más sensibles debido a raíces poco profundas y rasgos de intolerancia a la sequía. Nuestra evidencia apoya la hipótesis de que los bosques de NF poco profundos, mayoritariamente desconsiderados, son resistentes a sequías moderadas, desafiando la visión predominante de impactos negativos generalizados del cambio climático en los bosques amazónicos, que ignora los gradientes de NF, pero predice que podrían colapsar bajo sequías muy fuertes.

Drought-driven wildfire impacts on structure and dynamics in a wet Central Amazonian forest.

While the climate and human-induced forest degradation is increasing in the Amazon, fire impacts on forest dynamics remain understudied in the wetter regions of the basin, which are susceptible to large wildfires only during extreme droughts. To address this gap, we installed burned and unburned plots immediately after a wildfire in the northern Purus-Madeira (Central Amazon) during the 2015 El-Niño. We measured all individuals with diameter of 10 cm or more at breast height and conducted recensuses to track the demographic drivers of biomass change over 3 years. We also assessed how stem-level growth and mortality were influenced by fire intensity (proxied by char height) and tree morphological traits (size and wood density). Overall, the burned forest lost 27.3% of stem density and 12.8% of biomass, concentrated in small and medium trees. Mortality drove these losses in the first 2 years and recruitment decreased in the third year. The fire increased growth in lower wood density and larger sized trees, while char height had transitory strong effects increasing tree mortality. Our findings suggest that fire impacts are weaker in the wetter Amazon. Here, trees of greater sizes and higher wood densities may confer a margin of fire resistance; however, this may not extend to higher intensity fires arising from climate change.

Leaf traits and canopy structure together explain canopy functional diversity: an airborne remote sensing approach.

Plant functional diversity is strongly connected to photosynthetic carbon assimilation in terrestrial ecosystems. However, many of the plant functional traits that regulate photosynthetic capacity, including foliar nitrogen concentration and leaf mass per area, vary significantly between and within plant functional types and vertically through forest canopies, resulting in considerable landscape-scale heterogeneity in three dimensions. Hyperspectral imagery has been used extensively to quantify functional traits across a range of ecosystems but is generally limited to providing information for top of canopy leaves only. On the other hand, lidar data can be used to retrieve the vertical structure of forest canopies. Because these data are rarely collected at the same time, there are unanswered questions about the effect of forest structure on the three -dimensional spatial patterns of functional traits across ecosystems. In the United States, the National Ecological Observatory Network's Airborne Observation Platform (NEON AOP) provides an opportunity to address this structure-function relationship by collecting lidar and hyperspectral data together across a variety of ecoregions. With a fusion of hyperspectral and lidar data from the NEON AOP and field-collected foliar trait data, we assessed the impacts of forest structure on spatial patterns of N. In addition, we examine the influence of abiotic gradients and management regimes on top-of-canopy percent N and total canopy N (i.e., the total amount of N [g/m2 ] within a forest canopy) at a NEON site consisting of a mosaic of open longleaf pine and dense broadleaf deciduous forests. Our resulting maps suggest that, in contrast to top of canopy values, total canopy N variation is dampened across this landscape resulting in relatively homogeneous spatial patterns. At the same time, we found that leaf functional diversity and canopy structural diversity showed distinct dendritic patterns related to the spatial distribution of plant functional types.

Seasonal and drought-related changes in leaf area profiles depend on height and light environment in an Amazon forest.

Seasonal dynamics in the vertical distribution of leaf area index (LAI) may impact the seasonality of forest productivity in Amazonian forests. However, until recently, fine-scale observations critical to revealing ecological mechanisms underlying these changes have been lacking. To investigate fine-scale variation in leaf area with seasonality and drought we conducted monthly ground-based LiDAR surveys over 4 yr at an Amazon forest site. We analysed temporal changes in vertically structured LAI along axes of both canopy height and light environments. Upper canopy LAI increased during the dry season, whereas lower canopy LAI decreased. The low canopy decrease was driven by highly illuminated leaves of smaller trees in gaps. By contrast, understory LAI increased concurrently with the upper canopy. Hence, tree phenological strategies were stratified by height and light environments. Trends were amplified during a 2015-2016 severe El Niño drought. Leaf area low in the canopy exhibited behaviour consistent with water limitation. Leaf loss from short trees in high light during drought may be associated with strategies to tolerate limited access to deep soil water and stressful leaf environments. Vertically and environmentally structured phenological processes suggest a critical role of canopy structural heterogeneity in seasonal changes in Amazon ecosystem function.

Persistent effects of fragmentation on tropical rainforest canopy structure after 20 yr of isolation.

Assessing the persistent impacts of fragmentation on aboveground structure of tropical forests is essential to understanding the consequences of land use change for carbon storage and other ecosystem functions. We investigated the influence of edge distance and fragment size on canopy structure, aboveground woody biomass (AGB), and AGB turnover in the Biological Dynamics of Forest Fragments Project (BDFFP) in central Amazon, Brazil, after 22+ yr of fragment isolation, by combining canopy variables collected with portable canopy profiling lidar and airborne laser scanning surveys with long-term forest inventories. Forest height decreased by 30% at edges of large fragments (>10 ha) and interiors of small fragments (<3 ha). In larger fragments, canopy height was reduced up to 40 m from edges. Leaf area density profiles differed near edges: the density of understory vegetation was higher and midstory vegetation lower, consistent with canopy reorganization via increased regeneration of pioneers following post-fragmentation mortality of large trees. However, canopy openness and leaf area index remained similar to control plots throughout fragments, while canopy spatial heterogeneity was generally lower at edges. AGB stocks and fluxes were positively related to canopy height and negatively related to spatial heterogeneity. Other forest structure variables typically used to assess the ecological impacts of fragmentation (basal area, density of individuals, and density of pioneer trees) were also related to lidar-derived canopy surface variables. Canopy reorganization through the replacement of edge-sensitive species by disturbance-tolerant ones may have mitigated the biomass loss effects due to fragmentation observed in the earlier years of BDFFP. Lidar technology offered novel insights and observational scales for analysis of the ecological impacts of fragmentation on forest structure and function, specifically aboveground biomass storage.

Biological processes dominate seasonality of remotely sensed canopy greenness in an Amazon evergreen forest.

Satellite observations of Amazon forests show seasonal and interannual variations, but the underlying biological processes remain debated. Here we combined radiative transfer models (RTMs) with field observations of Amazon forest leaf and canopy characteristics to test three hypotheses for satellite-observed canopy reflectance seasonality: seasonal changes in leaf area index, in canopy-surface leafless crown fraction and/or in leaf demography. Canopy RTMs (PROSAIL and FLiES), driven by these three factors combined, simulated satellite-observed seasonal patterns well, explaining c. 70% of the variability in a key reflectance-based vegetation index (MAIAC EVI, which removes artifacts that would otherwise arise from clouds/aerosols and sun-sensor geometry). Leaf area index, leafless crown fraction and leaf demography independently accounted for 1, 33 and 66% of FLiES-simulated EVI seasonality, respectively. These factors also strongly influenced modeled near-infrared (NIR) reflectance, explaining why both modeled and observed EVI, which is especially sensitive to NIR, captures canopy seasonal dynamics well. Our improved analysis of canopy-scale biophysics rules out satellite artifacts as significant causes of satellite-observed seasonal patterns at this site, implying that aggregated phenology explains the larger scale remotely observed patterns. This work significantly reconciles current controversies about satellite-detected Amazon phenology, and improves our use of satellite observations to study climate-phenology relationships in the tropics.

Age-dependent leaf physiology and consequences for crown-scale carbon uptake during the dry season in an Amazon evergreen forest.

Satellite and tower-based metrics of forest-scale photosynthesis generally increase with dry season progression across central Amazônia, but the underlying mechanisms lack consensus. We conducted demographic surveys of leaf age composition, and measured the age dependence of leaf physiology in broadleaf canopy trees of abundant species at a central eastern Amazon site. Using a novel leaf-to-branch scaling approach, we used these data to independently test the much-debated hypothesis - arising from satellite and tower-based observations - that leaf phenology could explain the forest-scale pattern of dry season photosynthesis. Stomatal conductance and biochemical parameters of photosynthesis were higher for recently mature leaves than for old leaves. Most branches had multiple leaf age categories simultaneously present, and the number of recently mature leaves increased as the dry season progressed because old leaves were exchanged for new leaves. These findings provide the first direct field evidence that branch-scale photosynthetic capacity increases during the dry season, with a magnitude consistent with increases in ecosystem-scale photosynthetic capacity derived from flux towers. Interactions between leaf age-dependent physiology and shifting leaf age-demographic composition are sufficient to explain the dry season photosynthetic capacity pattern at this site, and should be considered in vegetation models of tropical evergreen forests.

Ecosystem heterogeneity and diversity mitigate Amazon forest resilience to frequent extreme droughts.

The impact of increases in drought frequency on the Amazon forest's composition, structure and functioning remain uncertain. We used a process- and individual-based ecosystem model (ED2) to quantify the forest's vulnerability to increased drought recurrence. We generated meteorologically realistic, drier-than-observed rainfall scenarios for two Amazon forest sites, Paracou (wetter) and Tapajós (drier), to evaluate the impacts of more frequent droughts on forest biomass, structure and composition. The wet site was insensitive to the tested scenarios, whereas at the dry site biomass declined when average rainfall reduction exceeded 15%, due to high mortality of large-sized evergreen trees. Biomass losses persisted when year-long drought recurrence was shorter than 2-7 yr, depending upon soil texture and leaf phenology. From the site-level scenario results, we developed regionally applicable metrics to quantify the Amazon forest's climatological proximity to rainfall regimes likely to cause biomass loss > 20% in 50 yr according to ED2 predictions. Nearly 25% (1.8 million km2 ) of the Amazon forests could experience frequent droughts and biomass loss if mean annual rainfall or interannual variability changed by 2σ. At least 10% of the high-emission climate projections (CMIP5/RCP8.5 models) predict critically dry regimes over 25% of the Amazon forest area by 2100.

Linking canopy leaf area and light environments with tree size distributions to explain Amazon forest demography.

Forest biophysical structure - the arrangement and frequency of leaves and stems - emerges from growth, mortality and space filling dynamics, and may also influence those dynamics by structuring light environments. To investigate this interaction, we developed models that could use LiDAR remote sensing to link leaf area profiles with tree size distributions, comparing models which did not (metabolic scaling theory) and did allow light to influence this link. We found that a light environment-to-structure link was necessary to accurately simulate tree size distributions and canopy structure in two contrasting Amazon forests. Partitioning leaf area profiles into size-class components, we found that demographic rates were related to variation in light absorption, with mortality increasing relative to growth in higher light, consistent with a light environment feedback to size distributions. Combining LiDAR with models linking forest structure and demography offers a high-throughput approach to advance theory and investigate climate-relevant tropical forest change.

A general integrative model for scaling plant growth, carbon flux, and functional trait spectra.

Linking functional traits to plant growth is critical for scaling attributes of organisms to the dynamics of ecosystems and for understanding how selection shapes integrated botanical phenotypes. However, a general mechanistic theory showing how traits specifically influence carbon and biomass flux within and across plants is needed. Building on foundational work on relative growth rate, recent work on functional trait spectra, and metabolic scaling theory, here we derive a generalized trait-based model of plant growth. In agreement with a wide variety of empirical data, our model uniquely predicts how key functional traits interact to regulate variation in relative growth rate, the allometric growth normalizations for both angiosperms and gymnosperms, and the quantitative form of several functional trait spectra relationships. The model also provides a general quantitative framework to incorporate additional leaf-level trait scaling relationships and hence to unite functional trait spectra with theories of relative growth rate, and metabolic scaling. We apply the model to calculate carbon use efficiency. This often ignored trait, which may influence variation in relative growth rate, appears to vary directionally across geographic gradients. Together, our results show how both quantitative plant traits and the geometry of vascular transport networks can be merged into a common scaling theory. Our model provides a framework for predicting not only how traits covary within an integrated allometric phenotype but also how trait variation mechanistically influences plant growth and carbon flux within and across diverse ecosystems.

Contamination of the marine environment by Antarctic research stations: Monitoring marine pollution at Casey station from 1997 to 2015.

The contamination of the marine environment surrounding coastal Antarctic research stations remains insufficiently understood in terms of its extent, persistence, and characteristics. We investigated the presence of contaminants in marine sediments near Casey Station, located in the Windmill Islands of East Antarctica, during the period spanning from 1997 to 2015. Metals, hydrocarbons, PBDEs, PCBs, and nutrients were measured in sediments at anthropogenically disturbed sites, including the wastewater outfall, the wharf area, two former waste disposal sites, and various control locations. Sampling was carried out at three spatial scales: Locations, which were generally kilometres apart and formed the primary scale for comparison; Sites, which were 100 meters apart within each location; and Plots, which were 10 meters apart within each site. Consistently higher concentrations of most contaminants, and in some cases nutrients, were observed at disturbed locations. Some locations also exhibited an increase in contaminant concentrations over time. The spatial distribution of sediment properties (such as grain size and organic matter) and contaminants displayed intricate patterns of variation. Variation in grain size depended on the size category, with fine grains (e.g., <63 µm) showing the greatest variation at the Location scale, while coarse grains exhibited minimal variation at this scale. Contaminant levels demonstrated significant differences between Locations, accounting for approximately 55% of the overall variation for metals, while the variation within the 10-meter scale generally exceeded that within the 100-meter scale. Residual variation among replicate samples was also very high, demonstrating the need for adequate replication in studies of sediments and contaminants around stations. Some contaminants exceeded international guidelines for sediment quality, including metals, hydrocarbons, and PCBs. We conclude that Antarctic research stations such as Casey are likely to pose a moderate level of long-term ecological risk to local marine ecosystems through marine pollution. However, contamination is expected to be confined to areas in close proximity to the stations, although its extent and concentration are anticipated to increase with time. Raising awareness of the contamination risks associated with Antarctic stations and implementing monitoring programs for marine environments adjacent to these stations can contribute to informed decision-making and the improvement of environmental management practices in Antarctica.

Amazon forest carbon dynamics predicted by profiles of canopy leaf area and light environment.

Tropical forest structural variation across heterogeneous landscapes may control above-ground carbon dynamics. We tested the hypothesis that canopy structure (leaf area and light availability) - remotely estimated from LiDAR - control variation in above-ground coarse wood production (biomass growth). Using a statistical model, these factors predicted biomass growth across tree size classes in forest near Manaus, Brazil. The same statistical model, with no parameterisation change but driven by different observed canopy structure, predicted the higher productivity of a site 500 km east. Gap fraction and a metric of vegetation vertical extent and evenness also predicted biomass gains and losses for one-hectare plots. Despite significant site differences in canopy structure and carbon dynamics, the relation between biomass growth and light fell on a unifying curve. This supported our hypothesis, suggesting that knowledge of canopy structure can explain variation in biomass growth over tropical landscapes and improve understanding of ecosystem function.

Forest fragmentation impacts the seasonality of Amazonian evergreen canopies.

Predictions of the magnitude and timing of leaf phenology in Amazonian forests remain highly controversial. Here, we use terrestrial LiDAR surveys every two weeks spanning wet and dry seasons in Central Amazonia to show that plant phenology varies strongly across vertical strata in old-growth forests, but is sensitive to disturbances arising from forest fragmentation. In combination with continuous microclimate measurements, we find that when maximum daily temperatures reached 35 °C in the latter part of the dry season, the upper canopy of large trees in undisturbed forests lost plant material. In contrast, the understory greened up with increased light availability driven by the upper canopy loss, alongside increases in solar radiation, even during periods of drier soil and atmospheric conditions. However, persistently high temperatures in forest edges exacerbated the upper canopy losses of large trees throughout the dry season, whereas the understory in these light-rich environments was less dependent on the altered upper canopy structure. Our findings reveal a strong influence of edge effects on phenological controls in wet forests of Central Amazonia.

A null model of exotic plant diversity tested with exotic and native species-area relationships.

At large spatial scales, exotic and native plant diversity exhibit a strong positive relationship. This may occur because exotic and native species respond similarly to processes that influence diversity over large geographical areas. To test this hypothesis, we compared exotic and native species-area relationships within six North American ecoregions. We predicted and found that within ecoregions the ratio of exotic to native species richness remains constant with increasing area. Furthermore, we predicted that areas with more native species than predicted by the species-area relationship would have proportionally more exotics as well. We did find that these exotic and native deviations were highly correlated, but areas that were good (or bad) for native plants were even better (or worse) for exotics. Similar processes appear to influence exotic and native plant diversity but the degree of this influence may differ with site quality.

A permeable reactive barrier (PRB) media sequence for the remediation of heavy metal and hydrocarbon contaminated water: A field assessment at Casey Station, Antarctica.

A field trial was conducted at Casey Station, Antarctica to assess the suitability of a permeable reactive barrier (PRB) media sequence for the remediation of sites containing both hydrocarbon and heavy metal contamination. An existing PRB was modified to assess a sequence consisting of three sections: (i) Nutrient release/hydrocarbon sorption using ZeoPro™ and granular activated carbon; (ii) Phosphorus and heavy metal capture by granular iron and sand; (iii) Nutrient and excess iron capture by zeolite. The media sequence achieved a greater phosphorus removal capacity than previous Antarctic PRB configurations installed on site. Phosphorus concentrations were reduced during flow through the iron/sand section and iron concentrations were reduced within the zeolite section. However, non-ideal flow was detected during a tracer test and supported by analysis of media and liquid samples from the second summer of operation. Results indicate that the PRB media sequence trialled might be appropriate for other locations, especially less environmentally challenging contaminated sites.