Jeffrey Q. Chambers’s research while affiliated with University of California, Berkeley and other places

The apparent respiratory quotient (ARQ) of tree stems, defined as the ratio of net stem CO2 efflux (ES_CO2) to net stem O2 influx (ES_O2), offers insights into the balance between local respiratory CO2 production and CO2 transported via the xylem. Traditional static chamber methods for measuring ARQ can introduce artifacts and obscure natural diurnal variations. Here, we employed an open flow-through stem chamber with ambient air coupled with cavity ring-down spectrometry, which uses the molecular properties of CO2 and O2 molecules to continuously measure ES_CO2, ES_O2, and ARQ, at the base of a California cherry tree (Prunus ilicifolia) during the 2024 growing season. Measurements across three stem chambers over 3–11-day periods revealed strong correlations between ES_CO2 and ES_O2 and mean ARQ values ranging from 1.3 to 2.9, far exceeding previous reports. Two distinct diurnal ARQ patterns were observed: daytime suppression with nighttime recovery, and a morning peak followed by gradual decline. Partitioning ES_CO2 into local respiration and xylem-transported CO2 indicated that the latter can dominate when ARQ exceeds 2.0. Furthermore, transported CO2 exhibited a higher temperature sensitivity than local respiration, with both processes showing declining temperature sensitivity above 20 °C. These findings underscore the need to differentiate stem CO2 flux components to improve our understanding of whole-tree carbon cycling.

Tropical forest soils generally have low nutrient availability. Some species exhibit specialized behavior, occurring exclusively in a single soil type, while others are generalists, thriving across different soils and water table depths. This study assessed the influence of topographic variation on leaf and trunk macronutrient and carbon amounts of tree species occurring only in one topographic position and species occurring across topographic positions and their relationship with soil macronutrient and carbon stocks. We selected nine species occurring in different topographic positions: three plateau specialists, three valley specialists, and three generalists (with four replicates each, totalling 35 individuals), where leaf and trunk samples were collected from each individual, and soil samples for carbon and nutrient analysis and quantification. Leaf and trunk nutrient concentrations varied across specialist and generalist functional groups, with valley specialists showing the highest concentrations of leaf and trunk nutrients and carbon. Nutrient concentrations within generalists remained consistent across topographic positions, underscoring their adaptive strategy to sustain productivity across environments. The concentrations of certain trunk nutrients of plateau and valley specialists and generalists mirrored those found in leaves, albeit at lower relative concentrations. Trunk carbon concentrations did not vary significantly compared to leaves, suggesting that other biological or environmental factors influenced tree nutritional status. We found evidence of variations in plant carbon and nutrient concentrations between generalist and specialist species inhabiting plateau and valley habitats in Central Amazonia, and a weak correlation between the stocks of some soil nutrients and leaf and trunk nutrient amounts.

The global demand for tropical hardwood continues to rise. However, exacerbated by a warming climate, high temperatures, and drought conditions during the dry season in many tropical regions is likely a contributing factor in the low survival rates of some planted hardwood tree seedlings grown under natural field conditions without watering. Here, we present a leaf-gas exchange and chlorophyll fluorescence experiment with tree seedlings of three species ( Astronium fraxinifolium - AF, Cariniana legalis - CL, and Handroanthus serratifolius - HS) under well-watered and water stress conditions. Following the cessation of watering, leaf temperatures increased as soil water content and transpiration rates decreased. A gradual reduction of soil water content over 4-days negatively impacted assimilation net CO 2 rates ( A net ), stomatal conductance ( g s ) and transpiration (E) with CL showing the greatest reduction in A net (94%), HS (90%), and AF the smallest reduction (77%). Moreover, the decline in A net was not solely attributed to partial stomatal closure, as F v /F m photosynthetic parameters derived from chlorophyll fluorescence also declining throughout the drought. While HS did not show detectable emissions of volatile isoprenoids, AF and CL maintained leaf isoprene emissions in the light throughout the drought. Drought induced the leaf accumulation of absiscic acid in HS, although an unknown interference following ABA leaf extraction prevented its quantification in AF and CL. The results indicate that common tropical hardwood species in Brazil are highly sensitive to water stress, with partial stomatal closure and isoprenoid synthesis playing an important role in the thermotolerance of photosynthesis during moisture stress.

Extreme rainfall events drive the amount and spatial distribution of rainfall in the Amazon and are a key driver of forest dynamics across the basin. This study investigates how the 3-hourly predictions in the High Resolution Model Intercomparison Project (HighResMIP, a component of the recent Coupled Model Intercomparison Project, CMIP6) represent extreme rainfall events at annual, seasonal, and sub-daily time scales. TRMM 3B42 (Tropical Rainfall Measuring Mission) 3 h data were used as observations. Our results showed that eleven out of seventeen HighResMIP models showed the observed association between rainfall and number of extreme events at the annual and seasonal scales. Two models captured the spatial pattern of number of extreme events at the seasonal and annual scales better (higher correlation) than the other models. None of the models captured the sub-daily timing of extreme rainfall, though some reproduced daily totals. Our results suggest that higher model resolution is a crucial factor for capturing extreme rainfall events in the Amazon, but it might not be the sole factor. Improving the representation of Amazon extreme rainfall events in HighResMIP models can help reduce model rainfall biases and uncertainties and enable more reliable assessments of the water cycle and forest dynamics in the Amazon.

Future climate presents conflicting implications for forest biomass. We evaluate how plant hydraulic traits, elevated CO2 levels, warming, and changes in precipitation affect forest primary productivity, evapotranspiration, and the risk of hydraulic failure. We used a dynamic vegetation model with plant hydrodynamics (FATES‐HYDRO) to simulate the stand‐level responses to future climate changes in a wet tropical forest in Barro Colorado Island, Panama. We calibrated the model by selecting plant trait assemblages that performed well against observations. These assemblages were run with temperature and precipitation changes for two greenhouse gas emission scenarios (2086–2100: SSP2‐45, SSP5‐85) and two CO2 levels (contemporary, anticipated). The risk of hydraulic failure is projected to increase from a contemporary rate of 5.7% to 10.1–11.3% under future climate scenarios, and, crucially, elevated CO2 provided only slight amelioration. By contrast, elevated CO2 mitigated GPP reductions. We attribute a greater variation in hydraulic failure risk to trait assemblages than to either CO2 or climate. Our results project forests with both faster growth (through productivity increases) and higher mortality rates (through increasing rates of hydraulic failure) in the neo‐tropics accompanied by certain trait plant assemblages becoming nonviable.

We present a representation of nitrogen and phosphorus cycling in the Functionally Assembled Terrestrial Ecosystem Simulator, a demographic vegetation model within the Energy Exascale Earth System land model. This representation is modular, and designed to allow testing of multiple hypothetical approaches for carbon‐nutrient coupling in plants. Novel model hypotheses introduced in this work include, (a) the controls on plant acquisition of aqueous mineralized nutrients in the soil and (b) fairly straight forward methods of allocating nutrients to specific plant organs and their losses through live plant turnover as well as litter fluxes generated through plant mortality. This combines the new with pre‐existing hypotheses (such as nitrogen fixation and soil decomposition) into a system that can accommodate plant‐soil dynamics for a large number of size‐ and functional‐type‐resolved plant cohorts within a time‐since‐disturbance‐resolved ecosystem. Root uptake of nutrients is governed by fine root biomass, and plants vary in their fine root biomass allocation in order to balance carbon and nutrient limitations to growth. We test the sensitivity of the model to a wide range of parameter variations and structural representations, and in the context of observations at Barro Colorado Island, Panama. A key model prediction is that plants in the high‐light‐availability canopy positions allocate more carbon to fine roots than plants in low‐light understory environments, given the widely different carbon versus nutrient constraints of these two niches within a given ecosystem. This model provides a basis for exploring carbon‐nutrient coupling with vegetation demography within Earth system models.

Tropical forest dynamics are key to global carbon, water, and energy cycles. Modeling the coexistence of diverse plant functional types (PFTs) in tropical forests presents a significant challenge. This study aims to enhance PFTs coexistence modeling in the Functionally Assembled Terrestrial Ecosystem Simulator (FATES), as implemented in the E3SM land model (ELM), known as ELM-FATES. We investigate three approaches to assess their impact on PFTs coexistence modeling: 1) field-measured plant trait relationships, 2) empirical parameter correlations, and 3) ML-based surrogate models for parameter optimization.

Forest disturbances increase the proportion of fast-growing tree species compared to slow-growing ones. To understand their relative capacity for carbon uptake and their vulnerability to climate change, and to represent those differences in Earth system models, it is necessary to characterise the physiological differences in their leaf-level control of water use efficiency and carbon assimilation. We used wood density as a proxy for the fast-slow growth spectrum and tested the assumption that trees with a low wood density (LWD) have a lower water-use efficiency than trees with a high wood density (HWD). We selected 5 LWD tree species and 5 HWD tree species growing in the same location in an Amazonian tropical forest and measured in situ steady-state gas exchange on top-of-canopy leaves with parallel sampling and measurement of leaf mass area and leaf nitrogen content. We found that LWD species invested more nitrogen in photosynthetic capacity than HWD species, had higher photosynthetic rates and higher stomatal conductance. However, contrary to expectations, we showed that the stomatal control of the balance between transpiration and carbon assimilation was similar in LWD and HWD species and that they had the same dark respiration rates.

Windthrow (i.e., trees broken and uprooted by wind) is a major natural disturbance in Amazon forests. Images from medium-resolution optical satellites combined with extensive field data have allowed researchers to assess patterns of windthrow tree-mortality and to monitor forest recovery over decades of succession in different regions. Although satellites with high spatial-resolution have become available in the last decade, they have not yet been employed for the quantification of windthrow tree-mortality. Here, we address how increasing the spatial resolution of satellites affects plot-to-landscape estimates of windthrow tree-mortality. We combined forest inventory data with Landsat 8 (30 m pixel), Sentinel 2 (10 m), and WorldView 2 (2 m) imagery over an old-growth forest in the Central Amazon that was disturbed by a single windthrow event in November 2015. Remote sensing estimates of windthrow tree-mortality were produced from Spectral Mixture Analysis and evaluated with forest inventory data (i.e., ground true) by using Generalized Linear Models. Field measured windthrow tree-mortality (3 transects and 30 subplots) crossing the entire disturbance gradient was 26.9 ± 11.1% (mean ± 95% CI). Although the three satellites produced reliable and statistically similar estimates (from 26.5% to 30.3%, p < 0.001), Landsat 8 had the most accurate results and efficiently captured field-observed variations in windthrow tree-mortality across the entire gradient of disturbance (Sentinel 2 and WorldView 2 produced the second and third best results, respectively). As expected, mean-associated uncertainties decreased systematically with increasing spatial resolution (i.e., from Landsat 8 to Sentinel 2 and WorldView 2). However, the overall quality of model fits showed the opposite pattern. We suggest that this reflects the influence of a relatively minor disturbance, such as defoliation and crown damage, and the fast growth of natural regeneration, which were not measured in the field nor can be captured by coarser resolution imagery. Our results validate the reliability of Landsat imagery for assessing plot-to-landscape patterns of windthrow tree-mortality in dense and heterogeneous tropical forests. Satellites with high spatial resolution can improve estimates of windthrow severity by allowing the quantification of crown damage and mortality of lower canopy and understory trees. However, this requires the validation of remote sensing metrics using field data at compatible scales.