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Collins, Adam

Publications and source records attributed to Collins, Adam.

At least 19 records
All sourcesNASA NTRSDOE OSTI
DOE OSTI2024

LiDAR Point Cloud Data from the 2018 NGEE Arctic UAS Campaign at the Kougarok 64 Field Site, Seward Peninsula, Alaska

Airborne remote sensing data collected from Los Alamos National Laboratory's (LANL) heavy-lift unoccupied aerial system (UAS) hexacopter platform operated by NGEE Arctic scientists from the EES-14 group at Los Alamos National Laboratory. These data were collected in July 2018 at a field site near mile marker 64 along the Kougarok road (Nome-Taylor Highway) between Nome, Alaska and Taylor, Alaska. A DJI Matrice 600 Pro Airframe and Routescene UAV LiDARSystem was used to collect LiDAR data. The LiDAR data has undergone basic post-processing using Routescene LidarViewer Pro software to create point cloud data (.laz files). This data package contains point clouds (.laz), processing metadata files (json.lvp), and post-processed kinematic files (.csv). Ancillary aircraft data, flight mission parameters, weather conditions, raw LiDAR data, and RGB imagery can be found in NGA298.The Next-Generation Ecosystem Experiments: Arctic (NGEE Arctic), was a research effort to reduce uncertainty in Earth System Models by developing a predictive understanding of carbon-rich Arctic ecosystems and feedbacks to climate. NGEE Arctic was supported by the Department of Energy's Office of Biological and Environmental Research. The NGEE Arctic project had two field research sites: 1) located within the Arctic polygonal tundra coastal region on the Barrow Environmental Observatory (BEO) and the North Slope near Utqiagvik (Barrow), Alaska and 2) multiple areas on the discontinuous permafrost region of the Seward Peninsula north of Nome, Alaska. Through observations, experiments, and synthesis with existing datasets, NGEE Arctic provided an enhanced knowledge base for multi-scale modeling and contributed to improved process representation at global pan-Arctic scales within the Department of Energy's Earth system Model (the Energy Exascale Earth System Model, or E3SM), and specifically within the E3SM Land Model component (ELM).

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2024

Soil Water Percolation Flux, April 2017 to March 2019, BR-Ma2, Manaus

Soil water percolation flux measurements derived from six passive wick flux meters across three topographic positions (valley, slope and plateau). Data has been processed to compute the mean for each topographic position where two flux meters were installed at each topographic position. Missing data represented a few percent of the total data set and were filled using two approaches. In the event one of the flux meters malfunctioned, we used data from the other sensor from the same topographic position without averaging. When both sensors were not working, such as during the period from September to October 2017 for the slope and valley and July 2018 for the plateau, data was filled using a nonlinear regression model that was based on local precipitation data and coefficients that were empirically derived for each topographic position. The metadata tab included in the .csv has additional information on locations where the sensors were installed, and other installation/maintenance details. Contact ksolander@lanl.gov if you need to use this dataset for additional information.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2024

Soil Water Percolation Chemistry, April 2017 to March 2019, BR-Ma2, Manaus

Soil water percolation chemistry including major cations, anions and isotope geochemistry. Samples were collected from six passive wick flux meters across three topographic positions (valley, slope and plateau). Data has been processed to compute the monthly mean for each topographic position where two flux meters were installed at each topographic position. All samples were processed at the Geology, Geochemistry and Geomaterials Research Laboratory (GGRL) in Los Alamos, NM USA. The metadata tab included in the .csv has additional information on locations where the sensors were installed, and other installation/maintenance details. Contact ksolander@lanl.gov if you need to use this dataset for additional information.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2022

CO2 response (ACi) gas exchange, calculated Vcmax & Jmax parameters, Feb2016-May2016, PA-SLZ, PA-PNM: Panama

This data package contains CO2 response (ACi) gas exchange and fitted Vcmax and Jmax parameters measured on sunlit canopy trees within the NGEE Tropics sites Parque Natural Metropolitano (PA-PNM) and Bosque Protector San Lorenzo (PA-SLZ) in Panama. Measurements were taken on a monthly basis from February to May of 2016. This data was collected as part of the 2016 El Niño-Southern Oscillation (ENSO) campaign. Included in this data package are two Excel files with data (2016ENSO_Panama_ACi, 2016ENSO_Panama_Fitted_Vcmax_Jmax) and three Excel files with associated metadata. Also included is a Word document (Metadata_description_2016_ENSO_Panama) with details such as data collection methods, equipment used, and site information and a pdf (NGEE_Tropics_ENSO_Aci_Protocol_V2). See related datasets for further sample details, leaf water potential, LMA, leaf spectra, diurnal gas exchange and leaf chemistry. VERSION 2 update. The identification of a species from the PNM site has been corrected as follows: the identification of the tree initially identified as Pseudosamanea guachapele (ALBIED) has been revised to Albizia adinocephala (ALBIAD). The updated data package includes revised data, metadata and protocol documents updated to reflect this change.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2022

Leaf sample detail, Feb2016-May2016, PA-SLZ, PA-PNM, PA-BCI: Panama

This data package contains details of the date, location, species and photographs of leaf samples collected on a monthly basis from Feb to May 2016 from Parque Natural Metropolitano (PA-PNM), Barro Colorado Island (PA-BCI) and Bosque Protector San Lorenzo (PA-SLZ) in Panama. Data from BCI only available for March. This data was collected as part of the 2016 El Niño-Southern Oscillation (ENSO) campaign. Included in this data package are an Excel file with data (2016ENSO_Panama_LeafSamples) and two Excel files with associated metadata. Sample photos are included in five zip files, organized by month and site. Also included is a Word document (Metadata_description_2016_ENSO_Panama) with details such as data collection methods, equipment used, and site information. Data to be used as a reference to linking related datasets including leaf water potential, leaf spectra, LMA, gas exchange and leaf chemistry (CHN, NSC). Most leaves were sampled from sunlit canopy trees. VERSION 2 update. The identification of a species from the PNM site has been corrected as follows: the identification of the tree initially identified as Pseudosamanea guachapele (ALBIED) has been revised to Albizia adinocephala (ALBIAD). The updated data package includes revised data, metadata and protocol documents updated to reflect this change.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2022

Diurnal leaf gas exchange survey, Feb2016-May2016, PA-SLZ, PA-PNM: Panama

This data package contains the results of a diurnal leaf gas exchange survey measured on sunlit canopy trees within the NGEE Tropics sites Parque Natural Metropolitano (PA-PNM) and Bosque Protector San Lorenzo (PA-SLZ) in Panama. Measurements were taken on a monthly basis from February to May of 2016. This data was collected as part of the 2016 El Niño-Southern Oscillation (ENSO) campaign. Included in this data package are two Excel files with data (2016ENSO_Panama_DiurnalGasEx, 2016ENSO_Panama_AreaCorrections) and additional Excel files with associated metadata. Also included is a Word document (Metadata_description_2016_ENSO_Panama) with details such as data collection methods, equipment used, and site information. See related datasets for further sample details, leaf water potential, LMA, leaf spectra, other gas exchange and leaf chemistry. VERSION 2 update. The identification of a species from the PNM site has been corrected as follows: the identification of the tree initially identified as Pseudosamanea guachapele (ALBIED) has been revised to Albizia adinocephala (ALBIAD). The updated data package includes revised data, metadata and protocol documents updated to reflect this change.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2022

Leaf mass area, Feb2016-May2016, PA-SLZ, PA-PNM, PA-BCI: Panama

This data package contains leaf mass data per unit area measured on a monthly basis from February to April, 2016, at the Bosque Protector San Lorenzo (PA-SLZ) and Parque Natural Metropolitano (PA-PNM) sites in Panama. Data from the Barro Colorado Island (PA-BCI) site are only available for March. This data was collected as part of the 2016 El Niño-Southern Oscillation (ENSO) campaign. Included in this data package are an Excel file with data (2016ENSO_Panama_LMA1) and two Excel files with associated metadata. Also included is a Word document (Metadata_description_2016_ENSO_Panama) with details such as data collection methods, equipment used, and site information. See related datasets for further sample details, leaf water potential, leaf spectra, gas exchange and leaf chemistry. VERSION 2 update. The identification of a species from the PNM site has been corrected as follows: the identification of the tree initially identified as Pseudosamanea guachapele (ALBIED) has been revised to Albizia adinocephala (ALBIAD). The updated data package includes revised data, metadata and protocol documents updated to reflect this change.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2022

Leaf spectra, Feb2016-April2016, PA-SLZ, PA-PNM, PA-BCI: Panama

This data package contains leaf spectra data measured on a monthly basis from February to April, 2016. Measurements were taken at the Bosque Protector San Lorenzo (SLZ), Barro Colorado Island (BCI) and Parque Natural Metropolitano (PNM) NGEE Tropics sites in Panama. Data from the BCI site are only available for March, 2016. Within the attached zip file are PDF manuals for instruments used, a guide to data collection protocol, and metadata files, including a PDF containing metadata for the 2016 ENSO gas exchange campaign. Also included is an additional zip file "2016_ENSO_BNL_Leaf_Spectra_Archive.zip" with data in .csv format organized by site. This data was collected as part of the 2016 ENSO campaign. See related datasets (existing and future) for further sample details, leaf water potential data, LMA, and gas exchange and leaf chemistry data. VERSION 2 update. The identification of a species from the PNM site has been corrected as follows: the identification of the tree initially identified as Pseudosamanea guachapele (ALBIED) has been revised to Albizia adinocephala (ALBIAD). The updated data package includes revised data, metadata and protocol documents updated to reflect this change.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2022

2016 Panama ENSO Non-Structural Carbohydrates (NSC), Feb2016-May2016, PA-SLZ, PA-PNM, PA-BCI

Results from Non-Structural Carbohydrate analysis of leaf and branch samples are provided in 2016ENSO_Panama_NSC.xlsx. The metadata files (Metadata_description_2016_ENSO_Panama.docx, File_Submission_Metadata_v1_2016ENSO_Panama_NSC.xlsx), field log (E-Field_Log_2016ENSO_Panama.xlsx), and protocols (ENSO NSC field protocol.pdf, Tropics NSC Assay protocol.pdf) contain additional information. Contact lee@lanl.gov for additional information. VERSION 2 update. The identification of a species from the PNM site has been corrected as follows: the identification of the tree initially identified as Pseudosamanea guachapele (ALBIED) has been revised to Albizia adinocephala (ALBIAD). The updated data package includes revised data, metadata and protocol documents updated to reflect this change.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2022

Leaf water potential, Feb2016-May2016, PA-SLZ, PA-PNM, PA-BCI: Panama

This data package contains leaf water potential data from the Barro Colorado Island (BCI), Parque Natural Metropolitano (PNM), and Bosque Protector San Lorenzo (SLZ) NGEE Tropics field sites in Panama. Pre-dawn and diurnal leaf water potential were measured on a monthly basis from February to May 2016 at SLZ and PNM. Data from BCI are only available for the month of March. This data was collected as part of the 2016 El Niño-Southern Oscillation (ENSO) campaign. Included in the attached zip file are data and metadata folders. The single data file "2016ENSO_Panama_LWP" has been provided in both Excel and CSV formats for usability purposes. The metadata file "Metadata_description_2016_ENSO_Panama" provides protocols, site descriptions, equipment information, and more, and has been provided in .docx and PDF file formats. See related datasets (existing and future) for further sample details, leaf spectra, leaf mass area (LMA), gas exchange and leaf chemistry data. VERSION 2 update. The identification of a species from the PNM site has been corrected as follows: the identification of the tree initially identified as Pseudosamanea guachapele (ALBIED) has been revised to Albizia adinocephala (ALBIAD). The updated data package includes revised data, metadata and protocol documents updated to reflect this change.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2022

Leaf C and N content, Feb2016-May2016, PA-SLZ, PA-PNM, PA-BCI: Panama

This dataset contains carbon, hydrogen and nitrogen content data of 33 tree species collected from February to May 2016 at the NGEE-Tropics Bosque Protector San Lorenzo (PA-SLZ) and Parque Natural Metropolitano (PA-PNM) sites in Panama. Data from Barro Colorado Island (PA-BCI) is only available for March 2016. This data was collected as part of the 2016 ENSO campaign. See related datasets for further sample details, leaf water potential, leaf spectra, gas exchange and leaf mass per area (LMA). Most leaves were sampled from sunlit canopy trees. VERSION 2 update. The identification of a species from the PNM site has been corrected as follows: the identification of the tree initially identified as Pseudosamanea guachapele (ALBIED) has been revised to Albizia adinocephala (ALBIAD). The updated data package includes revised data, metadata and protocol documents updated to reflect this change.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2022

Raw tensiometer soil matric potential data, from Oct 2017-Jun 2020 in Manaus, Brazil

This data package contains raw output from two Campbell Scientific CR1000 data loggers each connected to three UMS T4e tensiometer sensors in Manaus, Brazil. Tensiometers at each data logger location were installed to depths of 10 cm, 20 cm and 50 cm below the ground surface for the purpose of measuring soil matric potential at each depth. “Station 3” tensiometers were installed at approximately 2°36'31.68"S, 60°12'34.70"W. “Station 4” tensiometers were installed at approximately 2°36'32.46"S, 60°12'34.92"W. The files “tensio3.edit.202109.csv” and “tensio4.edit.202109.csv” contain raw data (with invalid data removed). A text editor will be required to view the raw files in .csv (comma-separated values) format. Data processing was limited to: 1) Editing column headers for clarity; 2) Applying a correction that converts voltage read by the data loggers to pressure units (kPa); 3) removing all data greater than 50 kPa and less than -115 kPa; 4) Adding columns entitled “Caution.10cm”, “Caution.20cm” and “Caution.50cm” that contains values of either “NA” or “Caution”, the latter of which is applied when data exceeds the manufacturer reported data validity range of less than -85 kPa to suggest use of these data with caution; 5) Adding columns entitled “Invalid.10cm”, “Invalid.20cm”, and “Invalid.50cm” that contains values of either “NA” or “Invalid”, the latter of which is applied when data accuracy is deemed compromised due to the introduction of air bubbles into the instrument. Data marked “Invalid” may still indicate general trends of wet/high matric potential and dry/low matric potential, but values are inaccurate and dry/low matric potential values are likely not low enough. Wet/high matric potential values are likely to be more accurate than dry/low matric potential values; 6) Data format changed from .dat to .csv. This research was performed as a part of the NGEE Tropics project, which aims to advance model predictions of tropical forest carbon cycle responses to a changing climate over the 21st Century.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2021

Hotter droughts alter resource allocation to chemical defenses in piñon pine

Abstract Heat and drought affect plant chemical defenses and thereby plant susceptibility to pests and pathogens. Monoterpenes are of particular importance for conifers as they play critical roles in defense against bark beetles. To date, work seeking to understand the impacts of heat and drought on monoterpenes has primarily focused on young potted seedlings, leaving it unclear how older age classes that are more vulnerable to bark beetles might respond to stress. Furthermore, we lack a clear picture of what carbon resources might be prioritized to support monoterpene synthesis under drought stress. To address this, we measured needle and woody tissue monoterpene concentrations and physiological variables simultaneously from mature piñon pines ( Pinus edulis ) from a unique temperature and drought manipulation field experiment. While heat had no effect on total monoterpene concentrations, trees under combined heat and drought stress exhibited ~ 85% and 35% increases in needle and woody tissue, respectively, over multiple years. Plant physiological variables like maximum photosynthesis each explained less than 10% of the variation in total monoterpenes for both tissue types while starch and glucose + fructose measured 1-month prior explained ~ 45% and 60% of the variation in woody tissue total monoterpene concentrations. Although total monoterpenes increased under combined stress, some key monoterpenes with known roles in bark beetle ecology decreased. These shifts may make trees more favorable for bark beetle attack rather than well defended, which one might conclude if only considering total monoterpene concentrations. Our results point to cumulative and synergistic effects of heat and drought that may reprioritize carbon allocation of specific non-structural carbohydrates toward defense.

59 BASIC BIOLOGICAL SCIENCES↗
NASA NTRS2020

Progress on LISA Colloid Microthruster Technology Development

Colloid microthrusters have been operated successfully in flight, providing drag-free and precision control for spacecraft that can be used for future applications such as gravity wave and exoplanet observatories. The Space Technology 7 Disturbance Reduction System (ST7- DRS) technology demonstration payload included eight Busek Colloid Micro-Newton Thrusters (CMNTs) as part of the Laser Interferometer Space Antenna (LISA) Pathfinder mission that launched in December of 2015. The CMNTs provided full attitude and precision drag-free control of the spacecraft with <10 nm/√Hz stability along the most sensitive axis during commissioning, nominal, and extended mission phases through April of 2017. Performance requirements (≤0.1 μN/√Hz) were met and models were validated based on on- orbit measurements of test mass motion and actuation during the 60-day nominal and 30-day extended missions. In 2018, the European Space Agency (ESA) selected LISA to be the agency’s next “large-class” mission, currently in Phase A, with a launch scheduled for 2034 and a 12.5-year duration, including the transfer (1.5 years), commissioning (1 year), nominal (4 or 6 years), and extended (6 or 4 years) phases of the mission, which sets the lifetime and consumables requirement. NASA is considering a significant contribution of hardware to the ESA-led mission, potentially including colloid microthrusters. In preparation, NASA is developing five technologies to TRL 5 and 6, including the colloid microthrusters, to be ready for infusion into LISA by the mission adoption review (MAR), currently scheduled for 2024. While ST7-DRS effectively brought the CMNTs to TRL 7, additional lower-TRL flow control components must be developed for full redundancy, reducing the system-level TRL back to 4. Key to the future of the colloid microthruster technology will be to use lessons learned and keep as much of the heritage from the ST7 design as possible while updating the system to support redundancy and lifetime requirements of a flagship-class mission. This paper describes the technology plan and progress to reach TRL 6 by the MAR, focusing on near- term plans to reach TRL 5 by the end of March 2022 for the LISA Colloid Microthrusters (CMTs). Work includes requirements development and sizing studies, breadboard and brassboard hardware developments at Busek, including relevant lifetime and environment testing, and lifetime modeling, verification and validation efforts at JPL, UCLA, and UCI.

Gamero-Castaño, Manuel↗
DOE OSTI2019

Hyperspectral vegetation identification at a legacy underground nuclear explosion test site

The detection, location, and identification of suspected underground nuclear explosions (UNEs) are global security priorities that rely on integrated analysis of multiple data modalities for uncertainty reduction in event analysis. Vegetation disturbances may provide complementary signatures that can confirm or build on the observables produced by prompt sensing techniques such as seismic or radionuclide monitoring networks. For instance, the emergence of non-native species in an area may be indicative of anthropogenic activity or changes in vegetation health may reflect changes in the site conditions resulting from an underground explosion. Previously, we collected high spatial resolution (10 cm) hyperspectral data from an unmanned aerial system at a legacy underground nuclear explosion test site and its surrounds. These data consist of visible and near-infrared wavebands over 4.3 km 2 of high desert terrain along with high spatial resolution (2.5 cm) RGB context imagery. In this work, we employ various spectral detection and classification algorithms to identify and map vegetation species in an area of interest containing the legacy test site. Here, we employed a frequentist framework for fusing multiple spectral detections across various reference spectra captured at different times and sampled from multiple locations. The spatial distribution of vegetation species is compared to the location of the underground nuclear explosion. We discover a difference in species abundance within a 130 m radius of the center of the test site.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2019

Mechanisms of a coniferous woodland persistence under drought and heat

Predictions of warmer droughts causing increasing forest mortality are becoming abundant, yet fewer studies have investigated the mechanisms of forest persistence. To examine the resistance of forests to warmer droughts, we used a five-year precipitation reduction (~45% removal), heat (+4°C above ambient) and combined drought and heat experiment in an isolated stand of mature Pinus edulis-Juniperus monosperma . Despite severe experimental drought and heating, no trees died, and we observed only minor evidence of hydraulic failure or carbon starvation. Two mechanisms promoting survival were supported. First, access to bedrock water, or ‘hydraulic refugia’ aided trees in their resistance to the experimental conditions. Second, the isolation of this stand amongst a landscape of dead trees precluded ingress by Ips confusus , frequently the ultimate biotic mortality agent of piñon. These combined abiotic and biotic landscape-scale processes can moderate the impacts of future droughts on tree mortality by enabling tree avoidance of hydraulic failure, carbon starvation, and exposure to attacking abiotic agents.

54 ENVIRONMENTAL SCIENCES↗