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Chambers, Jeff

Publications and source records attributed to Chambers, Jeff.

Comparative analysis of nutrient concentrations in generalist and specialist tree species and soils, Manaus, Brazil

This dataset was collected near Manaus, Brazil, at ZF-2 site, inside the North-South transect plots from 20221011 to 20221020. Measurements were made on specialists and generalist tree species along topographic gradient (in upland high-clay content soils of plateaus and high sandy content and partially flooded soils of valleys). We selected nine species (with four replicates each, totaling 35 individuals) occurring in different topographic positions: three plateau specialists, three valley specialists, and three generalists, where leaf and trunk samples were collected from each individual, and soil samples for carbon and nutrient analysis and quantification. Three soil pits were opened around each sample tree, about one meter apart (total of 105 soil pits each 60-cm deep), where soil samples were collected at four depths: 0-5, 5-10, 10-30 and 30-50 cm. In each of the three pits around each tree, one single sample was taken at each depth and combined to obtain a composite sample per depth per individual tree (35 trees × 4 depths = 140 soil samples). The files “Plant_Nutrient_Concentrations_NS_Transect_Manaus.csv” and “Soil_Nutrient_Concentrations_NS_Transect_Manaus.csv” contain the nutrient concentration data from plant and soil material, respectively. Additionally, the file “Sample_Info.csv” contains details about each variable including units and data type. The file “Species_Info.csv” includes information about each sampled individual, such as species, family, diameter at the breast height (DBH), and more. The dataset is ready to be used in any programming language like python or R. This dataset was originally published on the NGEE Tropics Archive and is being mirrored on ESS-DIVE for long-term archival Acknowledgement: Funding for NGEE-Tropics data resources was provided by the U.S. Department of Energy Office of Science, Office of Biological and Environmental Research.

54 ENVIRONMENTAL SCIENCES↗

Harmonized wood density data for Central Amazon species in the BIONTE experimental area in Manaus, Brazil

BIONTE (BIOmass and NuTrient Experiment) is a selective logging experiment established at the Experimental Station of Tropical Forestry (EEST, aka “ZF2”) field research station in the mid 1980s in the central Amazon (Higuchi et al. 1997, Amaral et al. 2019). The main data related to BIONTE are available as a separate dataset (Lima et al. 2022). Only species identified within the BIONTE plots were included in this dataset. Wood density, expressed in g cm-3, was collated from multiple sources that were integrated to compose the wood density for BIONTE. The starting point used was wood density data available from Chave et al. (2006), which was then adapted by Marra et al. (2016) and Marra et al. (2018). We also included data collected and synthesized by Ramírez-Méndez (2018) and Gimenez et al.(2021), who combined local estimates of wood density at the site with other sources collected in the Central Amazon. Data are included in .csv files, while BIONTE_WD_headers.txt provides descriptions of data file headers.

54 ENVIRONMENTAL SCIENCES↗

Growth, mortality, wood density, biomass data from BIONTE inventories in Manaus, Brazil

BIONTE (BIOmass and NuTrient Experiment) is a selective logging experiment established at the Experimental Station of Tropical Forestry (EEST, aka “ZF2”) field research station in the mid 1980s in the central Amazon (Higuchi et al. 1997, Amaral et al. 2019). Led by the National Institute for Amazon Research (INPA) in Brazil, the project aimed at assessing the effects of logging intensity on forest dynamics and enabling the creation of a model of forest management for the Central Amazon. The experiment included three levels of increasing selective logging intensity and controls, with 1 hectare sample plots (12 total) located at the center of 4 hectare treatment plots. The site’s Köppen classification is tropical rainforest (Af), characterized by high temperatures and humidity, with mean annual temperatures around 27 ℃ and mean annual precipitation around 2200 mm of rain. The vegetation has a high floristic diversity, the soils of the region are poor in nutrients, and the topography is characterized by plateaus (where BIONTE is located), and also valley bottoms and slopes. The inventory (growth and mortality) and biomass data included here covers the 1990 to 2019 period, with wood density being averaged from existing datasets. This dataset includes a data file in .csv file format and a .txt file, BIONTE_mortality-rates_headers.txt, that provides descriptions for the data file headers.

54 ENVIRONMENTAL SCIENCES↗

Forcing data (CESM2/CMIP6) for projection of drought impacts (2015-2100) at the K34 site in Manaus, Brazil

Historical and projected output data variables extracted and derived from Community Earth System Model 2 (CESM2) runs from the Coupled Model Intercomparison Project Phase 6 (CMIP6) archive. CESM2 is a fully coupled Earth system model used in simulations of Earth's past, present, and future climates (Danabasoglu et al., 2020). Variables in this dataset are in six-hourly resolution, and include air temperature (both in K and ℃), specific humidity (kg kg-1), air pressure (Pa), relative humidity (%), and vapor pressure deficit (kPa). CESM2 was the only CMIP6 model that provided VPD at the high temporal resolution required for this analysis. Data are included in .csv files, and the text file CESM2-CMIP6_forcing_K34-Manaus_headers.txt provides descriptions of data file headers.

54 ENVIRONMENTAL SCIENCES↗

Drought index using micrometeorological data from Embrapa weather station at Adolpho Ducke Reserve in Manaus, Brazil

This dataset includes daily resolution time series data including precipitation, minimum and maximum daily air temperature, and air relative humidity downloaded from the Embrapa InfoClima portal (https://www.cnpaf.embrapa.br/infoclima/), with data for the Adolpho Ducke Reserve climatological station in Manaus, Brazil, for the period of January 1, 1980 to December 31, 2016. Using this precipitation record, a Standardized Precipitation Index (SPI) was calculated and added to the dataset, using daily resolution for 180 day intervals and with 20 years for calibration (1980-1999) and adopting a gamma distribution. These data were applied as a proxy for analyzes of precipitation and SPI for the Manaus ZF2 Research station, located approximately 50 Km North of the Adolpho Ducke Reserve. Data are included in a .csv file, and the text file Drought-Indices-Embrapa-Ducke_met_spi_headers.txt provides descriptions of the data file headers.

54 ENVIRONMENTAL SCIENCES↗

Experimental Evaluation of Refrigerant Leak Characteristics for Different HVAC&R Equipment Types–Phase 2

The US Department of Energy (DOE) Building Technology Office (BTO) and the Air-conditioning, Heating & Refrigeration Technology Institute (AHRTI) collaborated to sponsor an experimental study of refrigerant leak characteristics at Oak Ridge National Laboratory (ORNL); AHRTI project 9012. The project has been conducted in two phases with objectives to conduct refrigerant leak tests on several heating, ventilating, air-conditioning and refrigeration (HVAC&R) systems under operating conditions representative of actual applications to document the pressure decay rate and the mass flow rate of leaked refrigerant as a function of time. Phase 1 of the project ran from late 2017 to late 2018 with refrigerant leaks imposed on five systems and the collection of data to meet the project objectives. Systems chosen covered three air-conditioning (AC) applications (packaged terminal AC or PTAC, 3-ton residential split system AC, and 5-ton packaged rooftop AC) and two refrigeration applications (split system unit cooler, and standalone display case). AHRTI members donated the test systems used for the project. The systems were tested at two different leak rates (catastrophic high rate simulating full line break and a lower flow rate), two leak locations (high-pressure side and low-pressure side), and two operating conditions (compressor ON or OFF). Phase 1 results were summarized in a project report by Baxter, et al. (2019)1. The leak rates imposed in Phase 1 led to much more rapid charge releases than the more typical much slower rates seen in practice that would take days, weeks, or months to empty a system of its entire charge. For Phase 2, the project sponsors asked that the “higher” leak rate target a total charge release time of about 4 min. This was intended to represent a “reasonable” worst case release scenario to match the refrigerant leak rate assumption used in the International Electrotechnical Commission (IEC) standard IEC 60335-2-40 (2016 version [IEC 2016]. A charge release time of about 20–40 min (leak release rate 5 to 10 times lower than higher rate) was targeted for the “lower” leak rate. This report provides a summary of the Phase 2 effort. Two additional HVAC systems were selected for testing in this phase. First was a multi-split air-conditioning (MS-AC) system with one outdoor section and two indoor units and a nameplate refrigerant charge of 1.75 kg (3.86 lb.) of R-410A. The MS-AC was tested in cooling only or AC operation. Second was a split system heat pump coupled to two different representative supply duct systems (HP-duct) and a nameplate charge of 3.83 kg (8.44 lb.) of R-410A. This system was tested in both space heating and AC modes. As in Phase 1 of the project, all tests were conducted using R-410A.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

Amazon windthrow disturbances are likely to increase with storm frequency under global warming: Data and Codes

This zipfile includes datasets and codes that were used to produce the results in the paper entitled Amazon windthrow disturbances are likely to increase with storm frequency under global warming. Datasets include: 1. Windthrow density across the entire Amazon - GIS shapefile format 2. Current ERA 5 mean afternoon convective available potential energy (CAPE) (1990-2019) - Remote Sensing TIFF format 3. Estimated future mean CAPE from 10 models in CMIP 6 (2070-2099) - Remote Sensing TIFF format 4. Python codes in jupyter notebook and processed datasets used to generate Fig.2a and Table 1 in the paper. You will need to use Jupyter Notebook and Python for accessing and reading the codes. Please contact Yanlei Feng (ylfeng@berkeley.edu) for any questions. Paper associated with this dataset: Feng, Y., Negrón-Juárez, R.I., Romps, D.M. and Chambers, J.Q., 2023. Amazon windthrow disturbances are likely to increase with storm frequency under global warming. Nature communications, 14(1), p.101.

54 ENVIRONMENTAL SCIENCES↗

Stability of tropical forest tree carbon-water relations in a rainfall exclusion treatment through shifts in effective water uptake depth

Increasing severity and frequency of drought is predicted for large portions of the terrestrial biosphere, with major impacts already documented in wet tropical forests. Using a 4-year rainfall exclusion experiment in the Daintree Rainforest in northeast Australia, we examined canopy tree responses to reduced precipitation and soil water availability by quantifying seasonal changes in plant hydraulic and carbon traits for 11 tree species between control and drought treatments. Even with reduced soil volumetric water content in the upper 1 m of soil in the drought treatment, we found no significant difference between treatments for predawn and midday leaf water potential, photosynthesis, stomatal conductance, foliar stable carbon isotope composition, leaf mass per area, turgor loss point, xylem vessel anatomy, or leaf and stem nonstructural carbohydrates. While empirical measurements of aboveground traits revealed homeostatic maintenance of plant water status and traits in response to reduced soil moisture, modeled belowground dynamics revealed that trees in the drought treatment shifted the depth from which water was acquired to deeper soil layers. Finally, these findings reveal that belowground acclimation of tree water uptake depth may buffer tropical rainforests from more severe droughts that may arise in future with climate change.

54 ENVIRONMENTAL SCIENCES↗

Hydraulically‐vulnerable trees survive on deep‐water access during droughts in a tropical forest

Summary Deep‐water access is arguably the most effective, but under‐studied, mechanism that plants employ to survive during drought. Vulnerability to embolism and hydraulic safety margins can predict mortality risk at given levels of dehydration, but deep‐water access may delay plant dehydration. Here, we tested the role of deep‐water access in enabling survival within a diverse tropical forest community in Panama using a novel data‐model approach. We inversely estimated the effective rooting depth (ERD, as the average depth of water extraction), for 29 canopy species by linking diameter growth dynamics (1990–2015) to vapor pressure deficit, water potentials in the whole‐soil column, and leaf hydraulic vulnerability curves. We validated ERD estimates against existing isotopic data of potential water‐access depths. Across species, deeper ERD was associated with higher maximum stem hydraulic conductivity, greater vulnerability to xylem embolism, narrower safety margins, and lower mortality rates during extreme droughts over 35 years (1981–2015) among evergreen species. Species exposure to water stress declined with deeper ERD indicating that trees compensate for water stress‐related mortality risk through deep‐water access. The role of deep‐water access in mitigating mortality of hydraulically‐vulnerable trees has important implications for our predictive understanding of forest dynamics under current and future climates.

54 ENVIRONMENTAL SCIENCES↗

Soil Water Potentials (1990-2018) from a calibrated ELM-FATES, and rooting depth analyses scripts, PA-BCI, Panama

This dataset has ELM-FATES simulation outputs and scripts that accompany and reproduce the manuscript, Chitra-Tarak et al. (2021) Hydraulically-vulnerable trees survive on deep-water access during droughts in a tropical forest. New Phytologist. https: //doi.org/10.1111/nph.17464”. This dataset is organized into four parts: (1) source code for the model, Energy Exascale Earth System Land Model-Functionally Assembled Advanced Terrestrial simulator (ELM-FATES) (2) R scripts associated with ELM-FATES simulations: to prepare files for parameter ensemble simulation runs, calibrate the model with observed hydrological fluxes observed at BCI, re-run the model with tuned parameters and obtain long-term soil matric potentials by depth (3) ELM-FATES hydrological simulation outputs at PA-BCI, Panama (1990-2018, daily), and (4) R scripts for inverse rooting depth modeling and post-processing: prepare datasets and inversely model tree rooting depths at BCI, test hypotheses about the relationship of rooting depths with plant hydraulic traits and drought-induced mortality, and reproduce the manuscript itself. n.b. 1. Data needed to run R scripts in (2) and (4) and thus to reproduce the manuscript are sourced from various public datasets. Refer to the data availability section of the accompanying manuscript. 2. This dataset version (prepared on May 12, 2021) matches the revised and published version of the accompanying manuscript (published May 16, 2021) replacing a previous version. In the publication, this dataset is cited as follows: Chitra-Tarak R, Xu C, Aguilar S, Anderson-Teixeira K, Chambers J, Detto M, Faybishenko B, Fisher R, Knox R, Koven C et al. 2020. Soil water potentials (1990–2018) from a calibrated ELM-FATES, and rooting depth analyses scripts, PA-BCI, Panama. 2.0. NGEE Tropics Data Collection. doi: 10.15486/ngt/1696806

54 ENVIRONMENTAL SCIENCES↗

Diurnal observations of basal stem CO2 efflux in three canopy dominant trees in the central Amazon

We explored mechanisms responsible for disturbance-induced shifts in carbon metabolism in forests north of Manaus, Brazil (S2º 38' 17", W60º 09' 25"), using data from a selective logging experiment (BIONTE). BIONTE (the BIOmass and NuTrient Experiment) selective logging treatments were initiated in the mid-1980s and comprised variable removal of commercial tree (not total) species basal area (T1 =32%, T2 = 42%, T3 = 69%), and control plots with no logging (T0). Raw data including tree base diameter (Db), CO2 concentration versus time inside a static stem chamber, and wood density were used to derive stem respiration rates (Rw), wood production rates (Pw), and wood carbon use efficiency (CUE). Changes in tree base diameter (Db; measured at 1.3 m height, or above the buttresses) was used to calculate wood production for individual trees (Pw). Wood density enabled calculation of stem growth rate in the same units as stem respiration (mmol C m-2 s-1). Four trees were randomly selected from five tree growth rate classes for each treatment block, for a total of 20 trees per treatment block, or 80 trees total from the BIONTE plots. Each of the 80 trees selected for the Rw study were outfitted with dendrometer bands (da Silva et al. 2002). Stem respiration was measured using the method described in Chambers et al. (2004). Briefly, an infra-red gas analyzer (LiCor 820) was operated as a closed dynamic chamber with a flow rate of 1.0 L min-1. Polyvinyl chloride (PVC) semi-cylindrical chambers (250–400 mL) were secured to the tree stem near the dendrometer bands using nylon straps. The measurement interval spanned 1–2 min, and the CO2 flux from the stem of each tree was quantified using the enclosed stem area and slope of the stem CO2 concentration versus time.

54 ENVIRONMENTAL SCIENCES↗