Use the information below for citation of this site. See the Data Policy page for more details.

DOI(s) for citing CA-NS1 data

Data Use Policy: AmeriFlux CC-BY-4.0 License

This site’s data can also be used under the more restrictive AmeriFlux Legacy Policy.
The AmeriFlux Legacy Policy must be followed if CA-NS1 data are combined with data from sites that require the AmeriFlux Legacy Policy.

AmeriFlux BASE: https://doi.org/10.17190/AMF/1245998
Citation: Mike Goulden (2019), AmeriFlux BASE CA-NS1 UCI-1850 burn site, Ver. 3-5, AmeriFlux AMP, (Dataset). https://doi.org/10.17190/AMF/1245998
AmeriFlux FLUXNET: https://doi.org/10.17190/AMF/1902824
Citation: Mike Goulden (2022), AmeriFlux FLUXNET-1F CA-NS1 UCI-1850 burn site, Ver. 3-5, AmeriFlux AMP, (Dataset). https://doi.org/10.17190/AMF/1902824

Find global FLUXNET datasets, like FLUXNET2015 and FLUXNET-CH4, and their citation information at fluxnet.org.

To cite BADM when downloaded on their own, use the publications below for citing site characterization. When using BADM that are downloaded with AmeriFlux BASE and AmeriFlux FLUXNET products, use the DOI citation for the associated data product.

Publication(s) for citing site characterization

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Acknowledgments

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Resources

AmeriFlux Logos & Acknowledgments

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MODIS NDVI

The time series shows the 16-day Normalized Difference Vegetation Index (NDVI) average from the MOD13Q1 data product.
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Includes all pixels that have acceptable quality

To view / download these data and other MOD13Q1 products for this site, visit MODIS/Terra Vegetation Indices.

For other related products, visit MODIS/VIIRS Fixed Sites Subsets Tool.

Citation:

ORNL DAAC. 2018. Terrestrial Ecology Subsetting & Visualization Services (TESViS) Fixed Sites Subsets. ORNL DAAC, Oak Ridge, Tennessee, USA. https://doi.org/10.3334/ORNLDAAC/1567

Read more on how to cite these MODIS products. Data come from NASA’s MODIS instruments installed on satellites Terra and Aqua, which scan the entire Earth’s surface every one to two days.

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For a complete list of AmeriFlux sites, visit ORNL DAAC's MODIS/VIIRS Fixed Sites Subsets Tool.

PhenoCam Images and Derived Time Series Data

PhenoCams are high-resolution digital cameras that take repeated images of studied ecosystems and provide quantitative information about the canopy phenology. The PhenoCam Network coordinates the camera installation and data reporting/analyses across sites in the Americas, providing automated, near-surface remote sensing of canopy phenology across a range of ecosystems and climate zones. Use of PhenoCam images / data should follow the PhenoCam Data Use Policy .

No PhenoCam data for this site

GeoNEX Data Products

Beta: This AmeriFlux GeoNEX Products feature is in beta. If you spot any issues, please help us out by emailing geonex-feedback@lbl.gov with a description and/or screenshot of the issue. Thanks in advance!

GeoNEX led by NASA Earth eXchange (NEX) is a collaborative effort for generating Earth monitoring products from the new generation of geostationary satellite sensors. GeoNEX has produced a suite of geostationary data products including surface reflectance, land surface temperature, surface solar radiation, and many others.

The GeoNEX Common Grid locates GeoNEX data in the geographic (latitude/longitude) projection. Pixels (grid cells) are created at regular 0.005°, 0.01°, and 0.02° resolutions.

GeoNEX pixels below cover the area 0.06° x 0.06° around and including site .

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NDVI: Normalized Difference Vegetation Index

Resolution: 0.01° x 0.01° & 10 minutes

Coordinates for pixel:

NIRv Near-Infrared Reflectance of vegetation

Resolution: 0.01° x 0.01° & 10 minutes

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DSR: Surface downward shortwave radiation

Resolution: 0.01° x 0.01° & Hourly

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LST: Land Surface Temperature

Resolution: 0.02° x 0.02° & Hourly

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Citation

This material can be used without obtaining permission from NASA. NASA should be acknowledged as the source of this material.

Subset Data Citation:

Hashimoto, H., Wang, W., Park, T., Khajehei, S., Ichii, K., Michaelis, A.R., Guzman, A., Nemani, R.R., Torn, M., Yi, K., Brosnan, I.G. (in preparation). Subsets of geostationary satellite data over international observing network sites for studying the diurnal dynamics of energy, carbon, and water cycles.

Relevant Science Publication Citation:

GeoNEX Surface Reflectance for Vegetation Indices (NDVI & NIRv)

Wang, W., Wang, Y., Lyapustin, A., Hashimoto, H., Park, T., Michaelis, A., & Nemani, R. (2022). A novel atmospheric correction algorithm to exploit the diurnal variability in hypertemporal geostationary observations. Remote Sensing, 14(4), 964.

GeoNEX Surface Downward Solar Radiation (DSR):

Li, R., Wang, D., Wang, W., & Nemani, R. (2023). A GeoNEX-based high-spatiotemporal-resolution product of land surface downward shortwave radiation and photosynthetically active radiation. Earth System Science Data, 15(3), 1419-1436.

GeoNEX Land Surface Temperature (LST):

Jia, A., Liang, S., & Wang, D. (2022). Generating a 2-km, all-sky, hourly land surface temperature product from Advanced Baseline Imager data. Remote Sensing of Environment, 278, 113105.

Search Publications for this Site Publications Found: 8

AmeriFlux Publications

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Year	Publication
2020	Xu, B., Arain, M. A., Black, T. A., Law, B. E., Pastorello, G. Z., Chu, H. (2020) Seasonal Variability Of Forest Sensitivity To Heat And Drought Stresses: A Synthesis Based On Carbon Fluxes From North American Forest Ecosystems, Global Change Biology, 26(2), 901-918. https://doi.org/10.1111/gcb.14843
2021	Chu, H., Luo, X., Ouyang, Z., Chan, W. S., Dengel, S., Biraud, S. C., Torn, M. S., Metzger, S., Kumar, J., Arain, M. A., Arkebauer, T. J., Baldocchi, D., Bernacchi, C., Billesbach, D., Black, T. A., Blanken, P. D., Bohrer, G., Bracho, R., Brown, S., Brunsell, N. A., Chen, J., Chen, X., Clark, K., Desai, A. R., Duman, T., Durden, D., Fares, S., Forbrich, I., Gamon, J. A., Gough, C. M., Griffis, T., Helbig, M., Hollinger, D., Humphreys, E., Ikawa, H., Iwata, H., Ju, Y., Knowles, J. F., Knox, S. H., Kobayashi, H., Kolb, T., Law, B., Lee, X., Litvak, M., Liu, H., Munger, J. W., Noormets, A., Novick, K., Oberbauer, S. F., Oechel, W., Oikawa, P., Papuga, S. A., Pendall, E., Prajapati, P., Prueger, J., Quinton, W. L., Richardson, A. D., Russell, E. S., Scott, R. L., Starr, G., Staebler, R., Stoy, P. C., Stuart-Haëntjens, E., Sonnentag, O., Sullivan, R. C., Suyker, A., Ueyama, M., Vargas, R., Wood, J. D., Zona, D. (2021) Representativeness Of Eddy-Covariance Flux Footprints For Areas Surrounding Ameriflux Sites, Agricultural And Forest Meteorology, 301-302, 108350. https://doi.org/10.1016/j.agrformet.2021.108350
2019	Zhang, Q., Ficklin, D. L., Manzoni, S., Wang, L., Way, D., Phillips, R. P., Novick, K. A. (2019) Response Of Ecosystem Intrinsic Water Use Efficiency And Gross Primary Productivity To Rising Vapor Pressure Deficit, Environmental Research Letters, 14(7), 074023. https://doi.org/10.1088/1748-9326/ab2603
2013	Barr, A., Richardson, A., Hollinger, D., Papale, D., Arain, M., Black, T., Bohrer, G., Dragoni, D., Fischer, M., Gu, L., Law, B., Margolis, H., McCaughey, J., Munger, J., Oechel, W., Schaeffer, K. (2013) Use Of Change-Point Detection For Friction–Velocity Threshold Evaluation In Eddy-Covariance Studies, Agricultural And Forest Meteorology, 171-172, 31-45. https://doi.org/10.1016/j.agrformet.2012.11.023
2018	Baldocchi, D., Penuelas, J. (2018) The Physics And Ecology Of Mining Carbon Dioxide From The Atmosphere By Ecosystems, Global Change Biology, . https://doi.org/10.1111/gcb.14559
2018	Chu, H., Baldocchi, D. D., Poindexter, C., Abraha, M., Desai, A. R., Bohrer, G., Arain, M. A., Griffis, T., Blanken, P. D., O'Halloran, T. L., Thomas, R. Q., Zhang, Q., Burns, S. P., Frank, J. M., Christian, D., Brown, S., Black, T. A., Gough, C. M., Law, B. E., Lee, X., Chen, J., Reed, D. E., Massman, W. J., Clark, K., Hatfield, J., Prueger, J., Bracho, R., Baker, J. M., Martin, T. A. (2018) Temporal Dynamics Of Aerodynamic Canopy Height Derived From Eddy Covariance Momentum Flux Data Across North American Flux Networks, Geophysical Research Letters, 45, 9275–9287. https://doi.org/10.1029/2018GL079306
2015	Dennis Baldocchi, Cove Sturtevant (2015) Does day and night sampling reduce spurious correlation between canopy photosynthesis and ecosystem respiration?, Agricultural and Forest Meteorology, 207, 117-126. https://doi.org/10.1016/j.agrformet.2015.03.010
2006	Goulden, M. L., Winston, G. C., McMillan, A. M., Litvak, M. E., Read, E. L., Rocha, A. V., Rob Elliot, J. (2006) An Eddy Covariance Mesonet To Measure The Effect Of Forest Age On Land-Atmosphere Exchange, Global Change Biology, 12(11), 2146-2162. https://doi.org/10.1111/j.1365-2486.2006.01251.x

BADM for This Site

Access the Biological, Ancillary, Disturbance and Metadata (BADM) information and data for this site.

BADM contain information for many uses, such as characterizing a site’s vegetation and soil, describing disturbance history, and defining instrumentation for flux processing. They complement the flux/met data.

Download BADM for this site^*

View Site General Info for this site (Overview tab)^*

Use Online Editor to update Site General Info or DOI Authorship

Update information about submitted data (Variable Information tool)

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^* Online updates are shown on the Overview tab real time. However, downloaded BADM files will not reflect those updates until they have been reviewed for QA/QC.

Wind Roses

Click an image below to enlarge it, or use the navigation panel.

Image scale: 569m x 569m

Data Collected:

Wind roses use variables ‘WS’ and ‘WD’.
Download Data Download Wind Rose as Image File (PNG)

Wind Speed (m/s)

Graph Type

Wind Speed Scale

Wind Direction Scale (%)

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Annual Average

About Ameriflux Wind Roses

Wind Rose Explanation

A wind rose gives a succinct view of how wind speed and direction are typically distributed at a particular location. Presented in a circular format, a wind rose shows the frequency and intensity of winds blowing from particular directions. The length of each “spoke” around the circle indicates the amount of time (frequency) that the wind blows from a particular direction. Colors along the spokes indicate categories of wind speed (intensity). Each concentric circle represents a different frequency, emanating from zero at the center to increasing frequencies at the outer circles

Utility

This information can be useful to gain insight into regions surrounding a flux tower that contribute to the measured fluxes, and how those regions change in dependence of the time of day and season. The wind roses presented here are for four periods of the year, and in 16 cardinal directions. Graphics are available for all sites in the AmeriFlux network based on reported wind measurements at each site.

Data from each site can be downloaded by clicking the ‘download’ button.

Hover the cursor over a wind rose to obtain directions, speeds and intensities.

Note that wind roses are not equivalent to flux footprints. Specifically, the term flux footprint describes an upwind area “seen” by the instruments measuring vertical turbulent fluxes, such that heat, water, gas and momentum transport generated in this area is registered by the instruments. Wind roses, on the other hand, identify only the direction and speed of wind.

Where do these data come from?

The wind roses are based on observed hourly data from the sites registered with the AmeriFlux Network.

Parameters for AmeriFlux Wind Roses

To use wind roses for a single AmeriFlux site, the following parameters may be most useful:

Wind Speed Scale: Per Site
Wind Direction Scale (%): Per Site

To compare wind roses from more than one single AmeriFlux site, the following parameters may be most useful:

Wind Speed Scale: Non-Linear
Wind Direction Scale (%): AmeriFlux

Mar - Jun; 6am - 6pm

Mar - Jun; 6pm - 6am

Jun - Sep; 6am - 6pm

Jun - Sep; 6pm - 6am

Sep - Dec; 6am - 6pm

Sep - Dec; 6pm - 6am

Dec - Mar; 6am - 6pm

Dec - Mar; 6pm - 6am

Tower_team:
PI:	Mike Goulden mgoulden@uci.edu - University of California - Irvine
Lat, Long:	55.8792, -98.4839
Elevation(m):	260
Network Affiliations:	AmeriFlux
Vegetation IGBP:	ENF (Evergreen Needleleaf Forests: Lands dominated by woody vegetation with a percent cover >60% and height exceeding 2 meters. Almost all trees remain green all year. Canopy is never without green foliage.)
Climate Koeppen:	Dfc (Subarctic: severe winter, no dry season, cool summer)
Mean Annual Temp (°C):	-2.89
Mean Annual Precip. (mm):	500.29
Flux Species Measured:	CO2
Years Data Collected:	2002 - 2005
Years Data Available:	AmeriFlux BASE 2001 - 2005 Data Citation AmeriFlux FLUXNET 2001 - 2005 Data Citation
Data Use Policy:	AmeriFlux CC-BY-4.0 Policy¹
Description:	The UCI-1850 site is located in a continental boreal forest, dominated by black spruce trees, within the BOREAS northern study area in central Manitoba, ... The UCI-1850 site is located in a continental boreal forest, dominated by black spruce trees, within the BOREAS northern study area in central Manitoba, Canada. The site is a member of a chronological series of sites that are representative secondary succession growth stages after large stand replacement fires. Black spruce trees undergo a slow growth process enabling the accurate determination of the chronosequence of stand age disturbance. Additionally, boreal forests make up approximately 25% of forest ecosystems on earth. With both of these in mind, the UCI sites provide an excellent location to study the CO2 exchange between the atmosphere and boreal forest ecosystems as a function of sequential wildfires. See More Show Less
URL:	http://www.ess.uci.edu/~boreal_canada/B1850_Page.html
Research Topics:	The research objectives and goals are as follows (in no particular order): 1) Determine how rapidly midday net CO2 exchange recovers following catastrophic ... The research objectives and goals are as follows (in no particular order): 1) Determine how rapidly midday net CO2 exchange recovers following catastrophic fire and how the phenology and seasonality of landatmosphere exchange vary with stand age; 2) Estimate the relative contributions of O horizon decomposition vs. plant sources by comparing the soil respiration in heterotrophic (decomposing organic horizons) and autotrophic (root and moss) components; 3) Comparison of photosynthesis sensitivity and ecosystem respiration as a function of interannual weather variability to estimate the combined effect on annual carbon exchange and successional dynamics; 4) Examine the components of NPP and their relation to stand structural characteristics; 5) Quantify temporal NPP and NEP changes over a variety of time scales. See More Show Less
Acknowledgment:	—

CA-NS1: UCI-1850 burn site

CA-NS1: UCI-1850 burn site

DOI(s) for citing CA-NS1 data

Publication(s) for citing site characterization

Acknowledgments

Resources

CA-NS1: UCI-1850 burn site

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CA-NS1: UCI-1850 burn site

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CA-NS1: UCI-1850 burn site

CA-NS1: UCI-1850 burn site

BADM for This Site

CA-NS1: UCI-1850 burn site

Wind Roses

Wind Speed (m/s)

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