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1. Automated Integration of Continental-scale Observations in Near-Real Time for Simulation and Analysis of Biosphere–Atmosphere Interaction

   https://doi.org/10.1007/978-3-030-63393-6_14  

   Durden, D.J.; Chu, H; Collier, N.; Davis, K.J.; Desai, A.R.; Kumar, J.; Metzger, S.; Wieder, W.R.; Xu, M.; Hoffman, F.M. (January 2020, Driving Scientific and Engineering Discoveries Through the Convergence of HPC, Big Data and AI. SMC 2020. Communications in Computer and Information Science, vol 1315)

   null; null; null; null; null; null (Ed.)

   The National Ecological Observatory Network (NEON) is a continental-scale observatory with sites across the US collecting standardized ecological observations that will operate for multiple decades. To maximize the utility of NEON data, we envision edge computing systems that gather, calibrate, aggregate, and ingest measurements in an integrated fashion. Edge systems will employ machine learning methods to cross-calibrate, gap-fill and provision data in near-real time to the NEON Data Portal and to High Performance Computing (HPC) systems, running ensembles of Earth system models (ESMs) that assimilate the data. For the first time gridded EC data products and response functions promise to offset pervasive observational biases through evaluating, benchmarking, optimizing parameters, and training new ma- chine learning parameterizations within ESMs all at the same model-grid scale. Leveraging open-source software for EC data analysis, we are al- ready building software infrastructure for integration of near-real time data streams into the International Land Model Benchmarking (ILAMB) package for use by the wider research community. We will present a perspective on the design and integration of end-to-end infrastructure for data acquisition, edge computing, HPC simulation, analysis, and validation, where Artificial Intelligence (AI) approaches are used throughout the distributed workflow to improve accuracy and computational performance. 

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2. Core Site Grid Quadrat Data for the Net Primary Production Study at the Sevilleta National Wildlife Refuge, New Mexico

   https://doi.org/10.6073/pasta/1f8b7af36b6ad51f36f5f4ab9f899a42  

   Baur, Lauren; Collins, Scott; Muldavin, Esteban; Rudgers, Jennifer A; Pockman, William T. (January 2021, Environmental Data Initiative)

   {"Abstract":["Begun in spring 2013, this project is part of a long-term study at\n the Sevilleta LTER measuring net primary production (NPP) across\n three distinct ecosystems: creosote-dominant shrubland (Site C),\n black grama-dominant grassland (Site G), and blue grama-dominant\n grassland (Site B). Net primary production is a fundamental\n ecological variable that quantifies rates of carbon consumption and\n fixation. Estimates of NPP are important in understanding energy\n flow at a community level as well as spatial and temporal responses\n to a range of ecological processes. Above-ground net primary\n production is the change in plant biomass, represented by stems,\n flowers, fruit and foliage, over time and incorporates growth as\n well as loss to death and decomposition. To measure this change the\n vegetation variables in this dataset, including species composition\n and the cover and height of individuals, are sampled twice yearly\n (spring and fall) at permanent 1m x 1m plots within each site. A\n third sampling at Site C is performed in the winter. The data from\n these plots is used to build regressions correlating biomass and\n volume via weights of select harvested species obtained in SEV999,\n "Net Primary Productivity (NPP) Weight Data." This biomass\n data is included in SEV999, "Seasonal Biomass and Seasonal and\n Annual NPP for Core Grid Research Sites.""]} 

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3. Pinon-Juniper (Core Site) Quadrat Data for the Net Primary Production Study at the Sevilleta National Wildlife Refuge, New Mexico

   https://doi.org/10.6073/pasta/97e478b38a0e114c58e370e4cefa6f47  

   Baur, Lauren; Collins, Scott; Muldavin, Esteban; Rudgers, Jennifer A; Pockman, William T. (January 2021, Environmental Data Initiative)

   {"Abstract":["This dataset contains pinon-juniper woodland quadrat data and is\n part of a long-term study at the Sevilleta LTER measuring net\n primary production (NPP) across four distinct ecosystems:\n creosote-dominant shrubland (Site C, est. winter 1999), black\n grama-dominant grassland (Site G, est. winter 1999), blue\n grama-dominant grassland (Site B, est. winter 2002), and\n pinon-juniper woodland (Site P, est. winter 2003). Net primary\n production is a fundamental ecological variable that quantifies\n rates of carbon consumption and fixation. Estimates of NPP are\n important in understanding energy flow at a community level as well\n as spatial and temporal responses to a range of ecological\n processes. Above-ground net primary production is the change in\n plant biomass, represented by stems, flowers, fruit and and foliage,\n over time and incorporates growth as well as loss to death and\n decomposition. To measure this change the vegetation variables in\n this dataset, including species composition and the cover and height\n of individuals, are sampled twice yearly (spring and fall) at\n permanent 1m x 1m plots within each site. A third sampling at Site C\n is performed in the winter. The data from these plots is used to\n build regressions correlating biomass and volume via weights of\n select harvested species obtained in SEV157, "Net Primary\n Productivity (NPP) Weight Data." This biomass data is included\n in SEV182, "Seasonal Biomass and Seasonal and Annual NPP for\n Core Research Sites.""]} 

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4. Lidar digital elevation models and topographic change detection results from burned and unburned plots in the Sevilleta LTER.

   https://doi.org/10.6073/pasta/c47cbb0327db815386cfca45c75a9b9c  

   Kasprak, Alan (January 2022, Environmental Data Initiative)

   These data were generated as part of a research project focused on montiroing sediment flux in dryland ecosystems following wildfire. In six separate small plots, three burned and three unburned, we conducted light detection and ranging (lidar) topographic surveys in 2016, 2017, and 2018 to document elevation changes and the volume of sediment deposition and erosion. At the down-wind edge of each plot, we used sediment catchers to trap sediment exiting the plots and thus estimate erosion volumes using in-situ equipment, which provided a secondary measurement of sediment efflux from all sites in addition to the lidar data. We used the geomorphic change detection software (https://gcd.riverscapes.xyz/) to produce maps of topographic change from the lidar digital elevation models for the 2016-2017 and 2017-2018 periods at all plots, burned and unburned. Results from this project may aid in understanding post-fire transport of sediment and nutrients from drylands following wildfire. 

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5. Macrophyte and microbial mat biomass co-variation along a hydrologic gradient and response to a removal experiment in temporary wetlands Everglades, FL, USA, February 2003 – November 2006

   https://doi.org/10.6073/pasta/01ef607bc7090c3488e5bcb7475847e9  

   Kleindl, Paige Marie; Gaiser, Evelyn; Wachnicka, Anna; Sah, Jay; Ross, Michael (January 2024, Environmental Data Initiative)

   This data package encompasses hydrologic variables, soil depth, hydrologically-regulated macrophyte community types, macrophyte biomass and community structure, and microbial mat biomass that was collected in two observational surveys and one in-situ experimental manipulation in six temporary wetland regions located in the Everglades, FL, USA. The goal of this project was to examine the co-variation in macrophyte and microbial mat biomass along the hydrologic gradient present across wetland regions and to determine the type and strength of interactions occurring between the two communities, which was tested using a biomass (macrophyte or microbial mat) removal experiment. The census observational survey took place at 140 sites from 2003-04-09 to 2004-05-26, which were randomly distributed across the hydrologic gradient present across the six temporary wetland regions. The transect observational survey occurred along six transects and each was deliberately established along the present hydrologic gradient within each region; a total of 254 sites were sampled from 2003-02-19 to 2005-03-04. The experiment took place at three temporary wetland sites with contrasting hydroperiods (3 – 6 months), and four transects were established per site with 24 pairs of control and treatment plots per transect. The removal treatment occurred one year before data collection, and data collection occurred from 2004-06-20 to 2006-11-25. The package includes six datasets, one R code file, and two shape files associated with the R code. Data collection for all datasets is complete. FCE1274_Census_Survey includes hydrologically-regulated macrophyte community type classifications, macrophyte biomass, microbial mat ash-free dry mass, mean soil depth, water depth, mean annual hydroperiod, and vegetation-inferred hydroperiod; each site was sampled once during the survey period and a subset of sites were sampled each year. FCE1274_Transect_Survey includes macrophyte community type classifications, macrophyte biomass, microbial mat ash-free dry mass, mean soil depth, water depth, mean annual hydroperiod, and vegetation-inferred hydroperiod. Each site was sampled once during the survey period; all sites along each transect were sampled before moving to the next transect. FCE1274_Removal_Experiment includes total macrophyte biomass, live macrophyte biomass, dead macrophyte biomass, and live macrophyte stem density within each microbial mat removal control and treatment plot along each transect at all three sites. Microbial mat dry mass, microbial mat ash-free dry mass, microbial mat chlorophyll-a concentration, and microbial mat organic content for each macrophyte removal control and treatment plot along each transect at all three sites are included as well. Data was collected once from each plot during the data collection period, and one pair of macrophyte removal plots and microbial mat removal plots were randomly sampled on a bimonthly basis until all plots had been sampled. FCE1274_Removal_Experiment_Macrophyte_Biomass includes total macrophyte biomass for each macrophyte species found within each microbial mat removal control and treatment plot along each transect at all three sites. Data was collected once from each plot during the data collection period, and one pair of microbial mat removal plots were randomly sampled on a bimonthly basis until all plots had been sampled. FCE1274_Removal_Experiment_Macrophyte_Density includes total macrophyte stem density for each macrophyte species found within each microbial mat removal control and treatment plot along each transect at all three sites. Data was collected once from each plot during the data collection period, and one pair of microbial mat removal plots were randomly sampled on a bimonthly basis until all plots had been sampled. FCE1274_Removal_Experiment_Macrophyte_Codes includes the taxon codes assigned to each macrophyte species identified in the FCE1274_Removal_Experiment_Macrophyte_Biomass and FCE1274_Removal_Experiment_Macrophyte_Density datasets. 

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