Contributors:Serbin, Shawn, Meng, Ran, Wu, Jin, Ely, Kim
Measurements of leaf full-spectrum (i.e. 350-2500 nm) reflectance and transmittance across 54 tropical tree species. Data includes leaves collected from fully sunlit and shaded canopy strata as well as leaves for you, mature, old and senescent leaf ages. Data for each sample includes the relative age estimate, leaf canopy position, and sample number. This data was collected as part of the 2017 NGEE-Tropics / NASA G-LiHT airborne campaign. See related datasets for sample details including photographs, leaf traits including leaf mass per area (LMA), water content, and leaf carbon and nitrogen.
This data package contains raw, unprocessed leaf surface temperature data for five trees and sap velocity data for four trees near the Km67 flux tower in Santarem, Brazil. Data was collected over the course of three months. Datalogger output from sapflow ICT sensors was translated using ICT software and is included in the attached zip file. Raw data is in .csv and .xls formats. Leaf surface temperature sensor photos, sensor manual PDFs, and three file-level metadata excel files are also included in the attached file.
Pre-dawn and diurnal leaf water potential measured on a monthly basis from Feb to May 2016 at SLZ and PNM. Data from BCI only available for March. This data was collected as part of the 2016 ENSO campaign. See related datasets (existing and future) for further sample details, leaf spectra, LMA, gas exchange and leaf chemistry.
Fluorescence excitation-emission matrix (EEM) spectroscopy, humification index (HIX) and specific UV absorbance (SUVA) at 254 nm were to characterize depth and seasonal variations of Dissolved Organic Matter (DOM) composition within sediments of a semi-arid floodplain at Rifle, Colorado, USA. It is expected that these relatively simple spectroscopic measurements (e.g., EEM spectroscopy, HIX and SUVA) applied to depth- and temporally-distributed pore-water samples can provide useful insights into transport and humification of DOM in other subsurface environments as well.
Raw sapflow data from K34 tower site on a plateau near Manaus, Brazil. These are mostly raw data from the data loggers, except in the case of the ICT sensors where the datalogger output was translated using ICT software. One heat ratio sap flow sensor (SFM1, ICT international) was installed per tree. Tree biophysical characteristics for each tree were used with Sap Flow Tool version 1.4.1 (ICT International/Phyto-IT) to calculate sap velocities from raw data downloaded from the SFM1 sap flow sensors in the field. Attached data files include data, sensor manuals, and detailed methods. Related metadata is contained in referenced dataset. This dataset replaces the sapflow data of two retired packages, http://dx.doi.org/10.15486/ngt/1507764 and http://dx.doi.org/10.15486/ngt/1507767
In this study, the oxidation of 2-methoxyhydroquinone (MH2Q) by ferric iron (Fe(III)) under dark conditions in the absence and presence of oxygen was investigated within a pH range of 4 – 6. While Fe(III) was capable of stoichiometrically oxidizing MH2Q under anaerobic conditions, catalytic oxidation of MH2Q was observed in the presence of O2 due to further cycling between oxygen, semiquinone radicals, and iron species. A detailed kinetic model was developed to describe the predominant mechanisms, which indicated that both the undissociated and mono-dissociated anions of MH2Q were kinetically active species towards Fe(III) reduction, with the mono-dissociated anion being the key species accounting for the pH dependence of the oxidation. The generated radical intermediates, namely semiquinone and superoxide, are of great importance in reaction chain propagation. The kinetic model may provide critical insight into the underlying mechanisms of the thermodynamic and kinetic characteristics of metal-organic interactions and assist in understanding and predicting the factors controlling iron and organic matter transformation and bioavailability in aquatic systems.
The data included in this data package are a demonstration of an inverse relationship in the early successional species Vismia guianensis in the central Amazon between stomatal conductance (gs) and leaf temperature, while net photosynthesis (Pn) showed an optimum value of 32.6 ± 0.4°C. In contrast to Pn, photosynthetic electron transport rates (ETR) and the QA oxidation state (qL) increased linearly with leaf temperature. Leaf isoprene emissions, a primary product of photosynthesis and strongly linked to plant high temperature stress tolerance, showed strong linear correlations with ETR (ρ = 0.98) and qL (ρ = 0.99). Furthermore, inhibition of isoprenoid biosynthesis repressed Pn at high temperatures through a mechanism that was independent of stomatal closure. Data will be used in the publication, "Stimulation of isoprene emissions and electron transport rates as a key mechanism of thermal tolerance in the tropical species Vismia guianensis." See the below Dataset References field for the full citation.
This dataset provides the tabular summary of analysis of 14 reaches of 13 Arctic rivers for river bank erosion and accretion rates, as well as, river channel properties such as channel width, bank curvature, and the aspect/orientation of the river banks. These rivers include the: Colville River, Alaska; Indigirka River, Russia; Kolyma River, Russia; Koyukuk River, Alaska; Lena River, Alaska; Noatak River, Alaska; Ob River, Russia; Pechora River, Russia; Selawik River, Alaska; Taz River, Russia; Yana River, Russia; Yenisei River, Russia;, and the Yukon River, Alaska. The dataset was generated from a total of 114 images including: Landsat, higher resolution satellite imagery, and aerial photography over time periods ranging from the 1970s and 2016. A full list of the image dates, row and path (for Landsat), and pixel resolutions is provided in the dataset. The masks were analyzed using the Spatially Continuous Riverbank Erosion and Accretion Measurements (SCREAM) software detailed in Rowland et al. 2016. The masks used in this analysis can be found an accompanying dataset (DOI: ess-dive-cfcff853f5ad92c-20191022T180804907). In files with "summary" in the name, the data is provided at a pixel level, where each mapped bank pixel has an associated erosion or accretion value, a channel width, a curvature value, and an aspect each river and time period will have an individual file. Files with "Segments" in name provide data that is averaged along segments of the rivers. These data are consolidated into a single file each for the erosion and accretion measurements. These segments are approximately 10 channel widths in length. In addition to erosion and accretion rates, the segment-based results include area measurements of erosion and accretion, islands, and channels. The number of islands is also included.Rowland JC, et al. (2016) A morphology independent methodology for quantifying planview river change and characteristics from remotely sensed imagery. Remote Sens Environ 184. doi:10.1016/j.rse.2016.07.005.
Data tables used in Arora et al. 2016b Influence of hydrological, biogeochemical and temperature transients on subsurface carbon fluxes in a flood plain environment. Biogeochemistry, 127(2-3), 367-396. Files include reactive transport model parameters describing soil physical and thermal parameters, geochemical reaction network and rate laws, as well as initial and boundary conditions. The last table documents modeling results with respect to annual carbon fluxes from the site to the river.
This data package contains a set of Functionally Assembled Terrestrial Ecosystem Simulator (FATES) history files and parameter values for the set of model simulations used in Koven et al. Manuscript "Benchmarking and Parameter Sensitivity of Physiological and Vegetation Dynamics using the Functionally Assembled Terrestrial Ecosystem Simulator (FATES) at Barro Colorado Island, Panama." It includes several ensembles of FATES runs, where each ensemble is comprised of a set of 576 runs that have different values of PFT traits. The ensembles include 1 PFT, 2 PFT, 3 PFT, and 10 PFT simulations. Different ensembles also have different values of disturbance and height sorting parameters, and structural differences including running FATES within different LSMs.