uid=MCM,o=EDI,dc=edirepository,dc=org all public read b235_model Schuyler Borges srb558@nau.edu https://orcid.org/0000-0002-4565-6463 Mark Salvatore mark.salvatore@nau.edu http://msalvatore.net https://orcid.org/0000-0002-1551-8342 Lee Stanish lstanish@gmail.com https://orcid.org/0000-0002-9775-6861 Sarah Power snpower@vt.edu https://orcid.org/0000-0002-4863-290X Eric Sokol sokole@gmail.com http://sokole.blogspot.com/ https://orcid.org/0000-0001-5952-0917 John "Jeb" Barrett jebarre@vt.edu https://www.biol.vt.edu/faculty/barrett/index.html https://orcid.org/0000-0002-7610-0505 Christian Tai Udovicic cjtu@nau.edu https://orcid.org/0000-0001-9972-1534 McMurdo Dry Valleys LTER http://mcmlter.org/ Renée Brown rfbrown@unm.edu https://orcid.org/0000-0002-4986-7663 data manager 2023-09-28 English

Long-term ecological field surveys from the McMurdo Dry Valleys Long Term Ecological Research program (MCM LTER) have documented the abundance and diversity of microbial mat types across ephemeral glacial meltwater streams in the McMurdo Dry Valleys region of Antarctica. However, field surveys are limited and are incapable of being performed across the entirety of streams within a field season. Therefore, we used remote sensing to examine the distribution of these diverse communities across streams in order to determine whether large scale distribution patterns are similar to those the MCM LTER has already thoroughly studied in situ. As part of our 2018-2019 field campaign, we established two to three 20 x 20 m plots within five different streams (Bowles Creek, McKnight Creek, a relict channel, Canada Stream, and Crescent Stream) in the Fryxell Basin of Taylor Valley. We performed point transect and quadrat field surveys of microbial mat and moss cover within each 20 x 20 m plot. We then used hyperspectral measurements of mat and moss collected in the field, previously archived in “Spectral and biological characteristics of microbial mats and mosses across Fryxell Basin, Taylor Valley, Antarctica (2018-2019),” in linear spectral mixing models to determine mat and moss coverage in the same 20 x 20 m plots within an atmospherically corrected WorldView-2 satellite image from Dec. 12, 2018. We ground truthed our modeled mat and moss abundances with our field survey coverages and determined the limitations of our methods. We then modeled mat and moss coverage across Huey Creek and Von Guerard Stream to apply our methods to streams without ground truthing measurements. Our results demonstrate the spatial distribution of moss and black, orange, red, and green microbial mat across Fryxell Basin streams. Observations of mat and moss coverage at the basin-wide scale are similar to those seen in localized stream areas.

communities global positioning systems imagery modeling models mosses physiology reflectance remote sensing stream ecology LTER Controlled Vocabulary algae Antarctic desert streams Antarctica global positioning system LTER McMurdo Dry Valleys microbial mat Moss Taylor Valley Station Keywords primary production LTER Core Areas Funding for this work was provided by the National Science Foundation grants #OPP-1758224 and #OPP-1745053 to Mark Salvatore, a Graduate Research Fellowship award to Schuyler Borges, and #OPP-1637708 and #OPP-2224760 to the MCM LTER for assistance with data management.

This data package is released under the Creative Commons Attribution 4.0 International License (CC BY 4.0; http://creativecommons.org/licenses/by/4.0/), which allows consumers (hereinafter referred to as “Data Users”) to freely reuse, redistribute, transform, or build on this work (even commercially) so long as appropriate credit is provided. Accordingly, Data Users are required to properly cite this data package in any publications or in the metadata of any derived products that result from its use (in whole or in part). A recommended citation is provided on the summary metadata page associated with this data package in the McMurdo Dry Valleys LTER Data Catalog (https://mcmlter.org/data), and a generic citation may be found on the summary metadata page in the repository where this data package was obtained. When these data contribute significantly to the contents of a publication, Data Users must also acknowledge that data were provided by the NSF-supported McMurdo Dry Valleys Long Term Ecological Research program (OPP-2224760). This data package has been released in the spirit of open scientific collaboration. Hence, Data Users are strongly encouraged to consider consultation, collaboration, and/or co-authorship (as appropriate) with the data package creator(s). Data Users should be aware these data may be actively used by others for ongoing research; thus, coordination may be necessary to prevent duplicate publication. Data Users should also recognize that misinterpretation of data may occur if they are used outside the context of the original study. Hence, Data Users are urged to contact the data package creator(s) if they have any questions regarding methodology or results. While substantial efforts are made to ensure the accuracy of this data package (with all its components), complete accuracy cannot be guaranteed. Periodic updates to this data package may occur, and it is the responsibility of Data Users to check for new versions. This data package is made available “as is” and comes with no warranty of accuracy or fitness for use. The creator(s) of this data package and the repository where these data were obtained shall not be liable for any damages resulting from misinterpretation, use, or misuse of these data. Finally, as a professional courtesy, we kindly request Data Users notify the primary contact referenced in the metadata when these data are used in the production of any derivative work or publication. Notification should include an explanation of how the data were used, along with a digital copy of the derived product(s). Thank you.

https://mcm.lternet.edu/content/distribution-models-microbial-mats-and-mosses-across-fryxell-basin-taylor-valley-antarctica This is the Taylor Valley, a subjectively approximated contour by San Gil. We use this to denote the geographical extent of studies that encompass the whole Taylor Valley.According to Wiki contributors, the Taylor Valley is the southernmost of the three large Dry Valleys in the Transantarctic Mountains, Victoria Land, located west of McMurdo Sound. The valley extends from Taylor Glacier in the west to McMurdo Sound at Explorers Cove at the northwest head of New Harbour in the east and is about 29 kilometres (18 mi) long. It was once occupied by the receding Taylor Glacier, from which it derives its name. Taylor Valley contains Lake Bonney in the west (inward), and Lake Fryxell in the east (coastward), and Lake Hoare, Lake Chad, Mummy Pond and Parera Pond close together between the two. Further east of Lake Bonney is Pearse Valley. Taylor Valley is separated from Wright Valley in the north by Asgard Range, and from Ferrar Glacier in the south by Kukri Hills. 161.707763671880 163.624877929690 -77.519802097166 -77.808487073526 2018-12-06 2019-01-25 McMurdo Dry Valleys LTER Information Manager im@mcmlter.org McMurdo Dry Valleys LTER http://mcmlter.org/ McMurdo Dry Valleys LTER

During the 2018-2019 austral summer, field surveys were conducted across 20 x 20 m plots established in several streams across the Fryxell Basin of Taylor Valley, Antarctica. Two plots were established in Bowles Creek, McKnight Creek, and Crescent Stream. Three plots were established in Canada Stream and a relict channel, but only the first and third plot in the relict channel was surveyed because plot 2 was outside the channel. Plots were assigned before the field season based on areas with homogenous NDVI signatures. Field surveys involved point transect and quadrat coverage estimates. Point transect measurements were collected by establishing cardinal (N, E, S, W), and intercardinal (NE, NW, SE, SW) transects across the 20 x 20 m plots. Every 25 cm along all transects, surface types were categorized as “dry” and “exposed” or “inundated” and “black mat, orange mat, red mat, black/orange mat, black/orange/red mat, orange/red mat, moss, cobbles/pebbles, sand, or rock.” Results were then averaged across the 20 x 20 m plots as abundances. For quadrat surveying, 1 x 1 m quadrats were randomly generated in the Esri geographic information system software, ArcGIS, within the 20 x 20 m plots. Ten quadrats per 20 x 20 m plot were established for most stream plots. However, due to field logistics and time constraints, some plots only had 6, 8, or 9 quadrats surveyed. Once in the field, 20 x 20 m general plot overview descriptions were recorded (weather, flow conditions, vegetation coverage, any notable features or changes since previous visit), and then each 1 x 1 m quadrat was surveyed. Observations of mat or moss type (black mat, orange mat, red mat, green mat, sandy orange mat, black/orange mat, black/orange/red mat, black/red mat, orange/red mat, moss, moss with black mat on top, black mat with moss on top, black mat and moss with orange mat on top), coverage, water levels (dry, moist, saturated, inundated), and substrate type were recorded. All coverages were then averaged for each quadrat and applied to the entire 20 x 20 m plot (multiple by two if ten quadrats). Further methodological details can be found in Spectral and biological characteristics of microbial mats and mosses across Fryxell Basin, Taylor Valley, Antarctica (2018-2019). For our remote sensing techniques, we first atmospherically corrected a WorldView-2 (WV2) image of Fryxell basin taken on Dec. 12, 2018 using the same methods as Salvatore et al. 2021. We then used multispectral data, found in “Spectral and biological characteristics of microbial mats and mosses across Fryxell Basin, Taylor Valley, Antarctica (2018-2019),” as endmember spectra in linear spectral mixing models in the program, Davinci. Model outputs included averaged abundances of mat and moss within each 20 x 20 m plot and the measured and modeled WV2 spectrum of the 20 x 20 m plot. After merging all coverage datasets, averaged abundances of mat and moss within each 20 x 20 m plot were statistically compared with field survey abundances to determine how well our models were fitting measured in situ data (R2, p-value, RMSE, AIC, and reduced chi-squared were calculated from the results). Other modeled results of mat and moss abundances for entire stream channels were outputted as geotiffs, which were then uploaded to the Harris geospatial deep learning software, ENVI, for further analysis. In ENVI, the reassigned WV2 bands displayed the different coverages of moss and each mat type. Using the statistics tool, percent coverages of mat and moss were found for entire stream channels. Percent coverages were converted to areal coverages by dividing the percentages by the total area of the stream channels. 

b235_modtotcov Total areal and percent coverage for models. b235-borges-modtotcov-20230925.csv 13568 1 0 column , " https://mcm.lternet.edu/sites/default/files/data/b235-borges-modtotcov-20230925.csv dataset_code Dataset code Internal dataset code. string Internal dataset code. model_id Model ID Unique model identifier that corresponds with the name of the model and field survey measurements being compared. string Unique model identifier that corresponds with the name of the model and field survey measurements being compared. stream_name Stream name Name of the stream associated with the model. string Name of the stream associated with the model. model_number Model number Model run identifier. string Model run identifier. sample_type Sample type Sample type (i.e., microbial mat type by color, moss, soil). string Sample type (i.e., microbial mat type by color, moss, soil). moisture_content Moisture content Sample coverage type, roughly corresponding with moisture content (i.e., dry, inundated, wet, total). string Sample coverage type, roughly corresponding with moisture content (i.e., dry, inundated, wet, total). areal_coverage_m2 Areal coverage Areal coverage of mat and/or moss for the associated model and stream. meterSquared real percent_coverage Percent coverage Percent coverage of mat and/or moss for the associated model and stream. percent real b235_mvmpctcov Measured vs. modeled percent coverage. b235-borges-mvmpctcov-20230925.csv 86861 1 0 column , " https://mcm.lternet.edu/sites/default/files/data/b235-borges-mvmpctcov-20230925.csv dataset_code Dataset code Internal dataset code. string Internal dataset code. model_id Model ID Unique model identifier that corresponds with the name of the model and field survey measurements being compared. string Unique model identifier that corresponds with the name of the model and field survey measurements being compared. stream_name Stream name Name of the stream associated with the field measurement or model. string Name of the stream associated with the field measurement or model. plot_id Plot ID Plot identifier within the stream where the field measurement was taken. See methods for further details. string Plot identifier within the stream where the field measurement was taken. See methods for further details. data_type Data type Data type, either field measurement (i.e., point transect or quadrat) or model. See methods for further details. string Data type, either field measurement (i.e., point transect or quadrat) or model. See methods for further details. model_number Model number Model run identifier. string Model run identifier. sample_type Sample type Sample type (i.e., microbial mat type by color, moss, soil). string Sample type (i.e., microbial mat type by color, moss, soil). moisture_content Moisture content Sample coverage type, roughly corresponding with moisture content (i.e., dry, inundated, wet, total). string Sample coverage type, roughly corresponding with moisture content (i.e., dry, inundated, wet, total). percent_coverage Percent coverage Percent coverage of mat and/or moss for the associated stream, plot number, and data type. percent real b235_mvmspectra Measured vs. modeled spectral reflectance. b235-borges-mvmspectra-20230925.csv 30686 1 0 column , " https://mcm.lternet.edu/sites/default/files/data/b235-borges-mvmspectra-20230925_0.csv dataset_code Dataset code Internal dataset code. string Internal dataset code. model_id Model ID Unique model identifier that corresponds with the name of the model and field survey measurements being compared. string Unique model identifier that corresponds with the name of the model and field survey measurements being compared. stream_name Stream name Name of the stream associated with the field measurement or model. string Name of the stream associated with the field measurement or model. plot_id Plot ID Plot identifier within the stream where the field measurement was taken. See methods for further details. string Plot identifier within the stream where the field measurement was taken. See methods for further details. data_type Data type Data type, either field measurement (i.e., point transect or quadrat) or model. See methods for further details. string Data type, either field measurement (i.e., point transect or quadrat) or model. See methods for further details. model_number Model number Model run identifier. string Model run identifier. band_um Band Wavelength of reflectance corresponding with bands from the WorldView-2 satellite: 0.427 um, 0.482 um, 0.546 um, 0.608 um, 0.659 um, 0.724 um, 0.831 um, and 0.908 um. micrometer real reflectance Reflectance Reflectance values (unitless) associated with each band and measurement/model. string Reflectance values (unitless) associated with each band and measurement/model. b235_mvmstats Measured vs. model statistics. b235-borges-mvmstats-20230925.csv 8079 1 0 column , " https://mcm.lternet.edu/sites/default/files/data/b235-borges-mvmstats-20230925_0.csv dataset_code Dataset code Internal dataset code. string Internal dataset code. model_id Model ID Unique model identifier that corresponds with the name of the model and field survey measurements being compared. string Unique model identifier that corresponds with the name of the model and field survey measurements being compared. stream_name Stream name Name of the stream associated with the field measurement or model. string Name of the stream associated with the field measurement or model. plot_id Plot ID Plot identifier within the stream where the field measurement was taken. See methods for further details. string Plot identifier within the stream where the field measurement was taken. See methods for further details. field_survey_type Field survey type Type of field measurement (i.e., point transect or quadrat). string Type of field measurement (i.e., point transect or quadrat). model_number Model number Model run identifier. string Model run identifier. regression_slope Regression slope Regression slope calculated between the modeled and measured abundances of mat and moss. string Regression slope calculated between the modeled and measured abundances of mat and moss. regression_intercept Regression intercept Regression intercept calculated between the modeled and measured abundances of mat and moss. string Regression intercept calculated between the modeled and measured abundances of mat and moss. regression_r2 Regression R2 Regression R2 value calculated between the modeled and measured abundances of mat and moss. string Regression R2 value calculated between the modeled and measured abundances of mat and moss. regression_pvalue Regression p-value Regression p-value calculated between the modeled and measured abundances of mat and moss. string Regression p-value calculated between the modeled and measured abundances of mat and moss. rmse Root mean square error Regression root mean square error (RMSE) calculated between the modeled and measured abundances of mat and moss. string Regression root mean square error (RMSE) calculated between the modeled and measured abundances of mat and moss. aic Akaike Information Criterion Akaike Information Criterion (AIC) value calculated between the modeled and measured abundances of mat and moss. string Akaike Information Criterion (AIC) value calculated between the modeled and measured abundances of mat and moss. reduced_chi_squared Reduced chi squared Reduced chi-squared value calculated between the modeled and measured abundances of mat and moss. string Reduced chi-squared value calculated between the modeled and measured abundances of mat and moss. b235_model_scripts Davinci and python scripts specific to the manuscript associated with this data package, detailing the linear unmixing model methods used to retrieve data from the “mvmspectra” and “mvmpctcov” files. This zip file also includes the multispectral data in their original format for the python script. b235-borges-model-scripts.zip 18014 application/zip https://mcm.lternet.edu/sites/default/files/data/b235-borges-model-scripts.zip undefined ratio of two quantities as percent composition (1:100)