These datasets are not necessarily representative of the long-term standardized data otherwise available on the NEON data portal. Prototype data are provided as downloadable zip files.

Optimization of a gas sampling system for measuring eddy-covariance fluxes of H2O and CO2, 2013 Atmosphere
Enclosed infrared gas analysers utilize a gas sampling system, which can substantially increase spectral corrections for eddy-covariance applications. Here, we show that a requirements-based design can reduce high-frequency attenuation for H2O by ≈3/4, with the remaining flux correction not exceeding 3%. The resulting gas sampling system can be used across a wide range of eco-climates and site layouts, and enables more automated and comparable eddy-covariance data processing across sites.
Science theme:
Atmosphere  
Locations:
Niwot Ridge Mountain Research Station (D13; CO; NIWO)  
Time range:
2013-2013
Abstract:
Several initiatives are currently emerging to observe the exchange of energy and matter between the earth''s surface and atmosphere standardized over larger space and time domains. For example, the National Ecological Observatory Network (NEON) and the Integrated Carbon Observing System (ICOS) will provide the ability of unbiased ecological inference across eco-climatic zones and decades by deploying highly scalable and robust instruments and data processing. In the construction of these observatories, enclosed infrared gas analysers are widely employed for eddy-covariance applications. While these sensors represent a substantial improvement compared to their open- and closed-path predecessors, remaining high-frequency attenuation varies with site properties, and requires correction. Here, we show that the gas sampling system substantially contributes to high-frequency attenuation, which can be minimized by careful design. From laboratory tests we determine the frequency at which signal attenuation reaches 50 % for individual parts of the gas sampling system. For different models of rain caps and particulate filters, this frequency falls into ranges of 2.5–16.5 Hz for CO2, 2.4–14.3 Hz for H2O, and 8.3–21.8 Hz for CO2, 1.4–19.9 Hz for H2O, respectively. A short and thin stainless steel intake tube was found to not limit frequency response, with 50 % attenuation occurring at frequencies well above 10 Hz for both H2O and CO2. From field tests we found that heating the intake tube and particulate filter continuously with 4 W was effective, and reduced the occurrence of problematic relative humidity levels (RH > 60 %) by 50 % in the infrared gas analyser cell. No further improvement of H2O frequency response was found for heating in excess of 4 W. These laboratory and field tests were reconciled using resistor-capacitor theory, and NEON''s final gas sampling system was developed on this basis. The design consists of the stainless steel intake tube, a pleated mesh particulate filter, and a low-volume rain cap in combination with 4 W of heating and insulation. In comparison to the original design, this reduced the high-frequency attenuation for H2O by ≈ 3/4, and the remaining cospectral correction did not exceed 3 %, even at a very high relative humidity (95 %). This standardized design can be used across a wide range of eco-climates and site layouts, and maximizes practicability due to minimal flow resistance and maintenance needs. Furthermore, due to minimal high-frequency spectral loss, it supports the routine application of adaptive correction procedures, and enables more automated data processing across sites.
Methods:
A comprehensive field experiment under various environmental conditions was performed in July 2013 and July 2014 at the Niwot Ridge AmeriFlux site.
The test philosophy is that a GSS component has better performance where it results in less IRGA CO2 and/or H2O signal attenuation when used individually and when integrated with other GSS components. Initially nine different types of particulate filters were tested in the laboratory, and it was found that the Swagelok FW 2 μm stainless steel mesh filter (Swagelok, Solon, OH, U.S.A.) provided the most suitable characteristics. This filter was then integrated with three different types of rain caps (Figure 1) and two different intake tubes, and further tested under laboratory conditions.
Responsible Neon Team:
Terrestrial Instrumented Systems (TIS)  
Related data products:
NEON.DOM.SITE.DP3.00010.001; NEON.DOM.SITE.DP3.00009.001  
Related publications:
Metzger, S., Burba, G., Burns, S. P., Blanken, P. D., Li, J., Luo, H., and Zulueta, R. C.: Optimization of a gas sampling system for measuring eddy-covariance fluxes of H2O and CO2, Atmos. Meas. Tech. Discuss., 8, 10983-11028, doi:10.5194/amtd-8-10983-2015, 2015.  
Keywords:
atmospheric fluxes; water; carbon dioxide  
Dataset ID:
30d084e0-ff4d-4bbe-a527-6e4366c6e545
Additional Information
File size:
1.9 GB
File type:
DOCX, PDF, TXT, GHG, GZ  

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Citation: National Ecological Observatory Network. 2016. Optimization of a gas sampling system for measuring eddy-covariance fluxes of H2O and CO2, 2013. Downloaded from data.neonscience.org on December, 10, 2019

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Data Hosted by NEON

NEON_Metzger_etal_2015_GasSamplingSystem.zip

Soil microbe prototype 16S sequence data, 2009-2010 Organisms, Populations, and Communities
Bacterial sequencing metadata and sequence accession numbers from 2009-2010 sampling efforts in AK, HI, UT, and FL
Science theme:
Organisms, Populations, and Communities  
Locations:
Caribou Creek-Poker Flats Watershed (D19; AK; ); Laupahoehoe (D20; HI; ); Onaqui (D15; UT; ); Ordway-Swisher Biological Station (D03; FL; )  
Time range:
2009-2010
Abstract:
Soil microbial communities play a critical role in nutrient transformation and storage in all ecosystems. Quantifying the seasonal and long-term temporal etxent of genetic and functional variation of soil microorganisms in response to biotic and abiotic changes within and across ecosystems will inform our understanding of the effect of climate change on these processes. We examined spatial and seasonal variation in microbial communities based on 16S rRNA gene sequencing and PLFA composition across four biomes. In this study, we used a team-based instructional approach leveraging the iPlant Collaborative to examine publicly available NEON data that quantify diversity, composition, and growth. Both profiling techniques revealed that microbial communities grouped strongly by ecosystem and were predominantly influenced by pH, soil water content, and cation exchange capacity. Temporal differences between profiling methods may be due to the premise that 16S-based measurements are predominantly influenced by large shifts in the abiotic soil environment, while PLFA-based analyses reflect the metabolically active fraction of the microbial community, which is more sensitive to local disturbances and biotic interactions.
Methods:
This study took place in soil habitats at four NEON domains. The sampling locations differ greatly in climatic and physico-chemical characteristics in order to capture the range of soil conditions that will be encountered at NEON sites.
408 soil samples were collected at 4-5 time points during a year from four sites with different levels of intra-annual variability in temperature and precipitation. Samples were collected within a gride measuring 160x320 m divided into eigth 80x80 m cells. Soil cores were 7.5 cm in diameter and sampled from 0-10cm depth. Sub-sets of the three cores corresponding to each cell were combined for a composite sample representative of each cell. Core samples were homogenized, sieved through a 2 mm mesh, and either air-dried or frozen at -80 degrees celcius for downstream analyses. Air-dried samples were analyzed for a suite of biogeochemical measurements.
Responsible Neon Team:
Terrestrial Observational Systems (TOS)  
Related data products:
NEON.DOM.SITE.DP1.10108.001  
Related publications:
Metzger, S., Burba, G., Burns, S. P., Blanken, P. D., Li, J., Luo, H., and Zulueta, R. C.: Optimization of a gas sampling system for measuring eddy-covariance fluxes of H2O and CO2, Atmos. Meas. Tech. Discuss., 8, 10983-11028, doi:10.5194/amtd-8-10983-2015, 2015.  
Keywords:
marker gene sequences; soil microbes; microbial ecology  
Dataset ID:
bfe3bcf1-558a-49d0-a90a-9ed4ff3717d0
Additional Information
File size:
55.6 MB
File type:
CSV, TXT, ZIP, FASTQ  

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Citation: National Ecological Observatory Network. 2016. Soil microbe prototype 16S sequence data, 2009-2010. Downloaded from data.neonscience.org on December, 10, 2019

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Data Hosted by NEON

NEON_MicrobePrototypeData-2009-2010.zip

Data Hosted Externally

Warning: clicking a link below will navigate to a page outside the Data Portal
http://www.ncbi.nlm.nih.gov/bioproject/288822
Test certificate issue Atmosphere Ecohydrology Land Cover and Processes Organisms, Populations, and Communities Biogeochemistry
aab
Science theme:
Atmosphere; Ecohydrology; Land Cover and Processes; Organisms, Populations, and Communities; Biogeochemistry  
Locations:
aaj (aak; AL; aal; [-3.000, 2.000]); aaj2 (aak2; CO; aal2; [-3.000, 2.000])  
Time range:
1500-1600
Abstract:
aae
Methods:
aad
aac
Responsible Neon Team:
Airborne Observation Platform (AOP) ; Aquatic Instrumented Systems (AIS) ; Aquatic Observational Systems (AOS) ; Terrestrial Instrumented Systems (TIS)  
Related data products:
NEON.DOM.SITE.DP1.00001.001  
Related publications:
 
Keywords:
atmospheric fluxes; water; carbon dioxide; marker gene sequences; soil microbes; microbial ecology; diversity; abundance; beetles; aar  
Dataset ID:
0d5e2cb6-4f23-4051-b3ab-39051d5aea64
Additional Information
File size:
32.9 MB
File type:
aam  

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Citation: National Ecological Observatory Network. 2017. Test certificate issue. Downloaded from data.neonscience.org on December, 10, 2019

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Data Hosted by NEON

76C45423047B4E11AEC73D2406D6E62F.zip

Data Hosted Externally

Warning: clicking a link below will navigate to a page outside the Data Portal
https://www.saucelabs.com/beta/dashboard/manual
bbb Atmosphere Ecohydrology Land Cover and Processes Organisms, Populations, and Communities Biogeochemistry
bbb1
Science theme:
Atmosphere; Ecohydrology; Land Cover and Processes; Organisms, Populations, and Communities; Biogeochemistry  
Locations:
bbb (bbb; AL; bbb; [-3.000, 2.000])  
Time range:
1500-1600
Abstract:
bbb
Methods:
bbb
bbb
Responsible Neon Team:
Airborne Observation Platform (AOP) ; Aquatic Instrumented Systems (AIS) ; Aquatic Observational Systems (AOS) ; Terrestrial Instrumented Systems (TIS) ; Terrestrial Observational Systems (TOS)  
Related data products:
 
Related publications:
bbb  
Keywords:
 
Dataset ID:
ee33e698-5156-4ea9-a4df-d8b47f054e38
Additional Information
File size:
0 kB
File type:
bbb  

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Citation: National Ecological Observatory Network. 2016. bbb. Downloaded from data.neonscience.org on December, 10, 2019

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Data Hosted Externally

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us3319 Atmosphere
test
Science theme:
Atmosphere  
Locations:
test (test; AL; test; [-4.000, 3.000])  
Time range:
2017-2017
Abstract:
test
Methods:
test
test
Responsible Neon Team:
Airborne Observation Platform (AOP)  
Related data products:
NEON.DOM.SITE.DP1.00001.001  
Related publications:
 
Keywords:
atmospheric fluxes  
Dataset ID:
90c818be-632e-4993-b4ed-7f4b4638941e
Additional Information
File size:
32.9 MB
File type:
ZIP  

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Citation: National Ecological Observatory Network. 2017. us3319. Downloaded from data.neonscience.org on December, 10, 2019

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Data Hosted by NEON

76C45423047B4E11AEC73D2406D6E62F.zip

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