Thinner bark increases sensitivity of wetter Amazonian tropical forests to fire

Understory fires represent an accelerating threat to Amazonian tropical forests and can, during drought, affect larger areas than deforestation itself. These fires kill trees at rates varying from < 10 to c. 90% depending on fire intensity, forest disturbance history and tree functional traits. Here, we examine variation in bark thickness across the Amazon. Bark can protect trees from fires, but it is often assumed to be consistently thin across tropical forests. Here, we show that investment in bark varies, with thicker bark in dry forests and thinner in wetter forests. We also show that thinner bark translated into higher fire‐driven tree mortality in wetter forests, with between 0.67 and 5.86 gigatonnes CO2 lost in Amazon understory fires between 2001 and 2010. Trait‐enabled global vegetation models that explicitly include variation in bark thickness are likely to improve the predictions of fire effects on carbon cycling in tropical forests

Individual-Based Modeling of Amazon Forests Suggests That Climate Controls Productivity While Traits Control Demography

Climate, species composition, and soils are thought to control carbon cycling and forest structure in Amazonian forests. Here, we add a demographics scheme (tree recruitment, growth, and mortality) to a recently developed non-demographic model—the Trait-based Forest Simulator (TFS)—to explore the roles of climate and plant traits in controlling forest productivity and structure. We compared two sites with differing climates (seasonal vs. aseasonal precipitation) and plant traits. Through an initial validation simulation, we assessed whether the model converges on observed forest properties (productivity, demographic and structural variables) using datasets of functional traits, structure, and climate to model the carbon cycle at the two sites. In a second set of simulations, we tested the relative importance of climate and plant traits for forest properties within the TFS framework using the climate from the two sites with hypothetical trait distributions representing two axes of functional variation (“fast” vs. “slow” leaf traits, and high vs. low wood density). The adapted model with demographics reproduced observed variation in gross (GPP) and net (NPP) primary production, and respiration. However, NPP and respiration at the level of plant organs (leaf, stem, and root) were poorly simulated. Mortality and recruitment rates were underestimated. The equilibrium forest structure differed from observations of stem numbers suggesting either that the forests are not currently at equilibrium or that mechanisms are missing from the model. Findings from the second set of simulations demonstrated that differences in productivity were driven by climate, rather than plant traits. Contrary to expectation, varying leaf traits had no influence on GPP. Drivers of simulated forest structure were complex, with a key role for wood density mediated by its link to tree mortality. Modeled mortality and recruitment rates were linked to plant traits alone, drought-related mortality was not accounted for. In future, model development should focus on improving allocation, mortality, organ respiration, simulation of understory trees and adding hydraulic traits. This type of model that incorporates diverse tree strategies, detailed forest structure and realistic physiology is necessary if we are to be able to simulate tropical forest responses to global change scenarios

The presence of peat and variation in tree species composition are under different hydrological controls in Amazonian wetland forests

This research was funded by the Gordon and Betty Moore Foundation, through grant #5349 ‘Monitoring protected areas in Peru to increase forest resilience to climate change’, and NERC standard grant ‘Carbon Storage in Amazonian Peatlands: Distribution and Dynamics’(NE/R000751/1).The peat-forming wetland forests of Amazonia are characterised by high below-carbon stocks and supply fruit, fibres and timber to local communities. Predicting the future of these ecosystem services requires understanding how hydrological conditions are related to tree species composition and the presence, or absence, of peat. Here, we use continuous measurements of water table depth over 2.5 years and manual measurements of pore-water pH and electrical conductivity to understand the ecohydrological controls of these variables across the large peatland complex in northern Peruvian Amazonia. Measurements were taken in permanent forest plots in four palm swamps, four seasonally flooded forests and four peatland pole forests. All trees ≥10 cm diameter were also measured and identified in the plots to assess floristic composition. Peat occurs in eight of these twelve sites; three seasonally flooded forests and one palm swamp are not associated with peat. Variation in tree species composition among forest types was linked to high flood levels (maximum flooding height) and pH: seasonally flooded forests experience high flood levels (up to 3.66 m from the ground surface) and have high pH values (6?7), palm swamps have intermediate flood levels (up to 1.34 m) and peatland pole forests experience shallow flooding (up to 0.28 m) and have low pH (4). In contrast, the presence of peat was linked to variation in maximum water table depth (ie the depth to which the water table drops below the ground surface). Surface peat is found in all forest types where maximum water table depth does not fall >0.55 m below the ground surface at any time. Peat formation and variation in tree species composition therefore have different ecohydrological controls. Predicted increases in the frequency and strength of flooding events may alter patterns of tree species composition, whereas increases in drought severity and declines in minimum river levels may pose a greater risk to the belowground carbon stores of these peatland ecosystems.Publisher PDFPeer reviewe

Fine root dynamics across pantropical rainforest ecosystems

Fine roots constitute a significant component of the net primary productivity (NPP) of forest ecosystems but are much less studied than aboveground NPP. Comparisons across sites and regions are also hampered by inconsistent methodologies, especially in tropical areas. Here, we present a novel dataset of fine root biomass, productivity, residence time, and allocation in tropical old-growth rainforest sites worldwide, measured using consistent methods, and examine how these variables are related to consistently determined soil and climatic characteristics. Our pantropical dataset spans intensive monitoring plots in lowland (wet, semi-deciduous, and deciduous) and montane tropical forests in South America, Africa, and Southeast Asia (n = 47). Large spatial variation in fine root dynamics was observed across montane and lowland forest types. In lowland forests, we found a strong positive linear relationship between fine root productivity and sand content, this relationship was even stronger when we considered the fractional allocation of total NPP to fine roots, demonstrating that understanding allocation adds explanatory power to understanding fine root productivity and total NPP. Fine root residence time was a function of multiple factors: soil sand content, soil pH, and maximum water deficit, with longest residence times in acidic, sandy, and water-stressed soils. In tropical montane forests, on the other hand, a different set of relationships prevailed, highlighting the very different nature of montane and lowland forest biomes. Root productivity was a strong positive linear function of mean annual temperature, root residence time was a strong positive function of soil nitrogen content in montane forests, and lastly decreasing soil P content increased allocation of productivity to fine roots. In contrast to the lowlands, environmental conditions were a better predictor for fine root productivity than for fractional allocation of total NPP to fine roots, suggesting that root productivity is a particularly strong driver of NPP allocation in tropical mountain regions.WHH was funded by Peruvian FONDECYT/CONCYTEC (grant contract number 213-2015-FONDECYT). The GEM network was supported by a European Research Council Advanced Investigator Grant to YM (GEM-TRAITS: 321131) under the European Union's Seventh Framework Programme (FP7/2007-2013). The field data collection was funded NERC Grants NE/D014174/1 and NE/J022616/1 for in Peru, BALI (NE/K016369/1) for work in Malaysia, the Royal Society-Leverhulme Africa Capacity Building Programme for work in Ghana and Gabon and ESPA-ECOLIMITS (NE/1014705/1) in Ghana and Ethiopia. Plot inventories in South America were supported by funding from the US National Science Foundation Long-Term Research in Environmental Biology program (LTREB; DEB 1754647) and the Gordon and Betty Moore Foundation Andes-Amazon Program. GEM data in Gabon were collected under authorization to YM and supported by the Gabon National Parks Agency. Y.M. is supported by the Jackson Foundation. We would like to acknowledge the GEM team across the tropical regions and countries of Bolivia, Brazil, Ghana, Gabon, Ethiopia, Malaysia, and Peru

Seasonal trends of Amazonian rainforest phenology, net primary productivity, and carbon allocation.:Seasonal trends of Amazonian forests.

The seasonality of solar irradiance and precipitation may regulate seasonal variations in tropical forests carbon cycling. Controversy remains over their importance as drivers of seasonal dynamics of net primary productivity in tropical forests. We use ground data from nine lowland Amazonian forest plots collected over 3 years to quantify the monthly primary productivity (NPP) of leaves, reproductive material, woody material, and fine roots over an annual cycle. We distinguish between forests that do not experience substantial seasonal moisture stress (“humid sites”) and forests that experience a stronger dry season (“dry sites”). We find that forests from both precipitation regimes maximize leaf NPP over the drier season, with a peak in production in August at both humid (mean 0.39 ± 0.03 Mg C ha−1 month−1 in July, n = 4) and dry sites (mean 0.49 ± 0.03 Mg C ha−1 month−1 in September, n = 8). We identify two distinct seasonal carbon allocation patterns (the allocation of NPP to a specific organ such as wood leaves or fine roots divided by total NPP). The forests monitored in the present study show evidence of either (i) constant allocation to roots and a seasonal trade-off between leaf and woody material or (ii) constant allocation to wood and a seasonal trade-off between roots and leaves. Finally, we find strong evidence of synchronized flowering at the end of the dry season in both precipitation regimes. Flower production reaches a maximum of 0.047 ± 0.013 and 0.031 ± 0.004 Mg C ha−1 month−1 in November, in humid and dry sites, respectively. Fruitfall production was staggered throughout the year, probably reflecting the high variation in varying times to development and loss of fruit among species

Understanding different dominance patterns in western Amazonian forests

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.Publisher PDFPeer reviewe

Tree mode of death and mortality risk factors across Amazon forests

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

Tree mode of death and mortality risk factors across Amazon forests

The&nbsp;carbon sink capacity of tropical forests&nbsp;is substantially affected by tree mortality. However, the main drivers of tropical&nbsp;tree death remain largely unknown. Here we present a pan-Amazonian assessment of how and why trees die, analysing over 120,000 trees representing &gt; 3800 species from 189 long-term&nbsp;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&nbsp;most important predictor of tree death in Amazonia, with faster-growing species being at&nbsp;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&nbsp;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&nbsp;holistic pan-Amazonian picture of tree death but large-scale&nbsp;evidence for the overarching importance of the growth–survival trade-off in driving tropical&nbsp;tree mortality

Variation in carbon and nitrogen concentrations among peatland categories at the global scale

Publisher Copyright: © 2022 This is an open access article, free of all copyright, and may be freely reproduced, distributed, transmitted, modified, built upon, or otherwise used by anyone for any lawful purpose. The work is made available under the Creative Commons CC0 public domain dedication.Peatlands account for 15 to 30% of the world's soil carbon (C) stock and are important controls over global nitrogen (N) cycles. However, C and N concentrations are known to vary among peatlands contributing to the uncertainty of global C inventories, but there are few global studies that relate peatland classification to peat chemistry. We analyzed 436 peat cores sampled in 24 countries across six continents and measured C, N, and organic matter (OM) content at three depths down to 70 cm. Sites were distinguished between northern (387) and tropical (49) peatlands and assigned to one of six distinct broadly recognized peatland categories that vary primarily along a pH gradient. Peat C and N concentrations, OM content, and C:N ratios differed significantly among peatland categories, but few differences in chemistry with depth were found within each category. Across all peatlands C and N concentrations in the 10-20 cm layer, were 440 ± 85.1 g kg-1 and 13.9 ± 7.4 g kg-1, with an average C:N ratio of 30.1 ± 20.8. Among peatland categories, median C concentrations were highest in bogs, poor fens and tropical swamps (446-532 g kg-1) and lowest in intermediate and extremely rich fens (375-414 g kg-1). The C:OM ratio in peat was similar across most peatland categories, except in deeper samples from ombrotrophic tropical peat swamps that were higher than other peatlands categories. Peat N concentrations and C:N ratios varied approximately two-fold among peatland categories and N concentrations tended to be higher (and C:N lower) in intermediate fens compared with other peatland types. This study reports on a unique data set and demonstrates that differences in peat C and OM concentrations among broadly classified peatland categories are predictable, which can aid future studies that use land cover assessments to refine global peatland C and N stocks.Peer reviewe

ENSO Drives interannual variation of forest woody growth across the tropics

Meteorological extreme events such as El Niño events are expected to affect tropical forest net primary production (NPP) and woody growth, but there has been no large-scale empirical validation of this expectation. We collected a large high–temporal resolution dataset (for 1–13 years depending upon location) of more than 172 000 stem growth measurements using dendrometer bands from across 14 regions spanning Amazonia, Africa and Borneo in order to test how much month-to-month variation in stand-level woody growth of adult tree stems (NPPstem) can be explained by seasonal variation and interannual meteorological anomalies. A key finding is that woody growth responds differently to meteorological variation between tropical forests with a dry season (where monthly rainfall is less than 100 mm), and aseasonal wet forests lacking a consistent dry season. In seasonal tropical forests, a high degree of variation in woody growth can be predicted from seasonal variation in temperature, vapour pressure deficit, in addition to anomalies of soil water deficit and shortwave radiation. The variation of aseasonal wet forest woody growth is best predicted by the anomalies of vapour pressure deficit, water deficit and shortwave radiation. In total, we predict the total live woody production of the global tropical forest biome to be 2.16 Pg C yr−1, with an interannual range 1.96–2.26 Pg C yr−1 between 1996–2016, and with the sharpest declines during the strong El Niño events of 1997/8 and 2015/6. There is high geographical variation in hotspots of El Niño–associated impacts, with weak impacts in Africa, and strongly negative impacts in parts of Southeast Asia and extensive regions across central and eastern Amazonia. Overall, there is high correlation (r = −0.75) between the annual anomaly of tropical forest woody growth and the annual mean of the El Niño 3.4 index, driven mainly by strong correlations with anomalies of soil water deficit, vapour pressure deficit and shortwave radiation