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Item type:Publication, Variation of non-structural carbohydrates across the fast-slow continuum in Amazon forest canopy trees(Wiley, 2021-11-20)Tropical tree species span a range of life‐history strategies within a fast–slow continuum. The position of a species within this continuum is thought to reflect a negative relationship between growth and storage, with fast‐growing species allocating more carbon to growth and slow‐growing species investing more in storage. For tropical species, the relationship between storage and life‐history strategies has been largely studied on seedlings and less so in adult trees. We evaluated how stored non‐structural carbohydrates (NSC) vary across adult trees spanning the fast–slow continuum in the Peruvian Amazon by: (a) analysing whole‐tree NSC in two species of contrasting growth and (b) investigating the relationships with key life‐history traits across a broader set of species. Our results are consistent with a growth–storage trade‐off. The analysis of whole‐tree NSC revealed that the slow‐growing Eschweilera coriacea stored about 2.7 times as much NSC as the fast‐growing Bixa arborea due to markedly higher storage in woody stems and roots. B. arborea also had higher seasonality in NSC, reflecting its strong seasonality in stem growth. Across a range of species, stem starch was negatively related to species growth rate and positively related to wood density. Given the role of NSC in mediating plants' response to stress, our results suggest that slow‐growing species with greater storage reserves may be more resilient to drought than fast‐growing species. - Some of the metrics are blocked by yourconsent settings
Item type:Publication, Non-structural carbohydrates mediate seasonal water stress across Amazon forests(Nature Research, 2021-12-01)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 (NSCT) concentrations in both organs were remarkably similar across communities. However, NSCT and its soluble sugar (SS) and starch components varied much more across sites during the dry season. Notably, the proportion of leaf NSCT in the form of SS (SS:NSCT) 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. - Some of the metrics are blocked by yourconsent settings
Item type:Publication, Calibration of the SMAP soil moisture retrieval algorithm to reduce bias over the Amazon rainforest(Institute of Electrical and Electronics Engineers Inc., 2024-01-01)Soil moisture (SM) is crucial for the Earth's ecosystem, impacting climate and vegetation health. Obtaining in situ observations of SM is labor-intensive and complex, particularly in remote and densely vegetated regions like the Amazon rainforest. NASA's soil moisture active and passive (SMAP) mission, utilizing an L-band radiometer, aims to monitor global SM. While it has been validated in areas with low vegetation water content (VWC) (< 5 {text{kgm}}{ - 2}), its efficiency in the Amazon, with dense canopies and high VWC (> 10 {text{kgm}}{ - 2}), is limitedly investigated due to scarce in situ measurements. This study assessed and analyzed the SMAP SM retrievals in the Amazon, employing the single-channel algorithm and adjusting vegetation optical depth (τ) and single scattering albedo (ω), two key vegetation parameters. It incorporated in situ SM observations from three old-growth rainforest locations: Tambopata (Southwest Amazon), Manaus (Central Amazon), and Caxiuana (Eastern Amazon). The SMAP SM deviated substantially from the in situ SM. However, calibrating τ and ω values, characterized by a lower τ, resulted in better agreement with the in situ measurements. This study emphasizes the pressing need for innovative methodologies to accurately retrieve SM in high-VWC regions like the Amazon rainforest using SMAP data.1 - Some of the metrics are blocked by yourconsent settings
Item type:Publication, Calibration of the SMAP Soil Moisture Retrieval Algorithm to Reduce Bias over the Amazon Rainforest(European Organization for Nuclear Research, 2023-09-15)Soil moisture (SM) is crucial for the Earth's ecosystem, impacting climate and vegetation health. Obtaining in-situ observations of SM is labor-intensive and complex, particularly in remote and densely vegetated regions like the Amazon rainforest. NASA's Soil Moisture Active and Passive (SMAP) mission, utilizing an L-band radiometer, aims to monitor global SM. While it has been validated in areas with low Vegetation Water Content (VWC) (< 5 kg/m²), its efficiency in the Amazon, which has dense canopies and high VWC (> 10 kg/m²), is uncertain due to scarce in-situ measurements. This study validates and analyzes SMAP data in the Amazon, employing the single-channel algorithm (SCA) and adjusting vegetation optical depth (τ) and single scattering albedo (ω), two key vegetation parameters. It incorporates in-situ SM observations from three old-growth rainforest locations: Tambopata (Southwest Amazon), Manaus (Central Amazon), and Caxiuana (Eastern Amazon). There were substantial discrepancies between SMAP and in-situ data. However, using calibrated τ and ω values, characterized by a lower τ, results in better agreement with in situ measurements. The study emphasizes the pressing need for innovative methodologies to accurately assess SM in high VWC regions like the Amazon using SMAP data.