ALBERT

Description: Networks of eddy-covariance (EC) towers such as AmeriFlux, ICOS and NEON are vital for providing the necessary distributed observations to address grand challenges in earth system and carbon cycle science. NEON, once fully operational with 47 tower sites, will represent the largest single-provider EC network globally. Its standardized observation and data processing suite is designed specifically for inter-site comparability and analysis of continental-scale ecological change, including rich contextual data such as airborne remote sensing and in-situ sampling bouts. First carbon cycle products become available in 2017, including data and software. These products strive to incorporate lessons-learned through collaborations with AmeriFlux, ICOS, LTER and others, to suggest novel systemic solutions, and to synergize ongoing research efforts across science communities. Here, we present an overview of the ongoing product release, alongside efforts to integrate and synergize with existing infrastructures, networks and communities. Near-real-time carbon cycle observations in “basic” and “expanded”, self-describing HDF5 formats become accessible from the NEON Data Portal, including an Application Program Interface. A pilot project is underway to investigate their subsequent ingest into the AmeriFlux processing pipeline, together with inclusion in FLUXNET globally harmonized data releases. Software for reproducible, extensible and portable data analysis and science operations management also becomes available. This includes the eddy4R family of R-packages underlying the carbon cycle data product generation, together with the ability to directly participate in open development via GitHub version control and Dockerhub image hosting. In addition, templates for science operations management include a web-based field maintenance application and a graphical user interface to simplify problem tracking and resolution along the entire data chain. We hope that this first release of NEON carbon cycle products can initiate further collaboration and synergies in challenge areas, and would appreciate input and discussion on continued development.

Description: Large differences in instrumentation, site setup, data format, and operating system stymie the adoption of a universal computational environment for processing and analyzing eddy-covariance (EC) data. This results in limited software applicability and extensibility in addition to often substantial inconsistencies in flux estimates. Addressing these concerns, this paper presents the systematic development of portable, reproducible, and extensible EC software achieved by adopting a development and systems operation (DevOps) approach. This software development model is used for the creation of the eddy4R family of EC code packages in the open-source R language for statistical computing. These packages are community developed, iterated via the Git distributed version control system, and wrapped into a portable and reproducible Docker filesystem that is independent of the underlying host operating system. The HDF5 hierarchical data format then provides a streamlined mechanism for highly compressed and fully self-documented data ingest and output. The usefulness of the DevOps approach was evaluated for three test applications. First, the resultant EC processing software was used to analyze standard flux tower data from the first EC instruments installed at a National Ecological Observatory (NEON) field site. Second, through an aircraft test application, we demonstrate the modular extensibility of eddy4R to analyze EC data from other platforms. Third, an intercomparison with commercial-grade software showed excellent agreement (R2  =  1.0 for CO2 flux). In conjunction with this study, a Docker image containing the first two eddy4R packages and an executable example workflow, as well as first NEON EC data products are released publicly. We conclude by describing the work remaining to arrive at the automated generation of science-grade EC fluxes and benefits to the science community at large. This software development model is applicable beyond EC and more generally builds the capacity to deploy complex algorithms developed by scientists in an efficient and scalable manner. In addition, modularity permits meeting project milestones while retaining extensibility with time.

Description: The FLUXNET2015 dataset provides ecosystem-scale data on CO2, water, and energy exchange between the biosphere and the atmosphere, and other meteorological and biological measurements, from 212 sites around the globe (over 1500 site-years, up to and including year 2014). These sites, independently managed and operated, voluntarily contributed their data to create global datasets. Data were quality controlled and processed using uniform methods, to improve consistency and intercomparability across sites. The dataset is already being used in a number of applications, including ecophysiology studies, remote sensing studies, and development of ecosystem and Earth system models. FLUXNET2015 includes derived-data products, such as gap-filled time series, ecosystem respiration and photosynthetic uptake estimates, estimation of uncertainties, and metadata about the measurements, presented for the first time in this paper. In addition, 206 of these sites are for the first time distributed under a Creative Commons (CC-BY 4.0) license. This paper details this enhanced dataset and the processing methods, now made available as open-source codes, making the dataset more accessible, transparent, and reproducible.

Description: Networks of eddy-covariance (EC) towers such as AmeriFlux, ICOS and NEON are vital for providing the necessary distributed observations to address interactions at the soil-vegetation-atmosphere interface. NEON, close to full operation with 47 tower sites, will represent the largest single-provider EC network globally. Its standardized observation and data processing suite is designed specifically for inter-site comparability and analysis of feedbacks across multiple spatial and temporal scales. Furthermore, NEON coordinates EC with rich contextual observations such as airborne remote sensing and in-situ sampling bouts. In January 2018 NEON enters its operational phase, and EC data products, software and services become fully available to the science community at large. These resources strive to incorporate lessons-learned through collaborations with AmeriFlux, ICOS, LTER and others, to suggest novel systemic solutions, and to synergize ongoing research efforts across science communities. Here, we present an overview of the ongoing product release, alongside efforts to integrate and collaborate with existing infrastructures, networks and communities. Near-real-time heat, water and carbon cycle observations in “basic” and “expanded”, self-describing HDF5 formats become accessible from the NEON Data Portal, including an Application Program Interface. Subsequently, they are ingested into the AmeriFlux processing pipeline, together with inclusion in FLUXNET globally harmonized data releases. Software for reproducible, extensible and portable data analysis and science operations management also becomes available. This includes the eddy4R family of R-packages underlying the data product generation, together with the ability to directly participate in open development via GitHub version control and DockerHub image hosting. In addition, templates for science operations management include a web-based field maintenance application and a graphical user interface to simplify problem tracking and resolution along the entire data chain. We hope that this presentation can initiate further collaboration and synergies in challenge areas, and would appreciate input and discussion on continued development. Plain Language Summary For a sustained period of time the eddy-covariance and boundary layer communities have invested technical and scientific expertise into the construction of the National Ecological Observatory Network (NEON). In January 2018 NEON enters its operational phase, and the time has come for our communities to reap the first fruits of their efforts! This presentation intends to create awareness of the resources that become available to our communities: interoperable flux data products, software and assignable asset services. We focus on how these resources will permit to elucidate interactions at the soil-vegetation-atmosphere interface for decades to come: continuous eddy-covariance observations of the surface-atmosphere exchange are tightly coordinated with rich contextual data such as airborne remote sensing and in-situ sampling bouts. In this way new investigative dimensions are provided to capture land-atmosphere feedbacks across multiple spatial and temporal scales.

Description: Author Posting. © American Society for Cell Biology, 2005. This article is posted here by permission of American Society for Cell Biology for personal use, not for redistribution. The definitive version was published in Molecular Biology of the Cell 16 (2005): 3064-3076, doi:10.1091/mbc.E05-02-0174.

Description: Metaphase spindles assemble to a steady state in length by mechanisms that involve microtubule dynamics and motor proteins, but they are incompletely understood. We found that Xenopus extract spindles recapitulate the length of egg meiosis II spindles, by using mechanisms intrinsic to the spindle. To probe these mechanisms, we perturbed microtubule polymerization dynamics and opposed motor proteins and measured effects on spindle morphology and dynamics. Microtubules were stabilized by hexylene glycol and inhibition of the catastrophe factor mitotic centromere-associated kinesin (MCAK) (a kinesin 13, previously called XKCM) and destabilized by depolymerizing drugs. The opposed motors Eg5 and dynein were inhibited separately and together. Our results are consistent with important roles for polymerization dynamics in regulating spindle length, and for opposed motors in regulating the relative stability of bipolar versus monopolar organization. The response to microtubule destabilization suggests that an unidentified tensile element acts in parallel with these conventional factors, generating spindle shortening force.

Description: This work was funded by National Institutes of Health Grants GM-39565 (to T.J.M.), GM-24364 and GM-606780 (to E.D.S.), and GM-65933 (to T.M.K.), and by Marine Biological Laboratory fellowships from Universal Imaging and Nikon.

Description: Author Posting. © American Society for Cell Biology, 2004. This article is posted here by permission of American Society for Cell Biology for personal use, not for redistribution. The definitive version was published in Molecular Biology of the Cell 15 (2004): 5603-5615, doi:10.1091/mbc.E04-05-0440.

Description: We investigated the mechanism by which meiotic spindles become bipolar and the correlation between bipolarity and poleward flux, using Xenopus egg extracts. By speckle microscopy and computational alignment, we find that monopolar sperm asters do not show evidence for flux, partially contradicting previous work. We account for the discrepancy by describing spontaneous bipolarization of sperm asters that was missed previously. During spontaneous bipolarization, onset of flux correlated with onset of bipolarity, implying that antiparallel microtubule organization may be required for flux. Using a probe for TPX2 in addition to tubulin, we describe two pathways that lead to spontaneous bipolarization, new pole assembly near chromatin, and pole splitting. By inhibiting the Ran pathway with excess importin-alpha, we establish a role for chromatin-derived, antiparallel overlap bundles in generating the sliding force for flux, and we examine these bundles by electron microscopy. Our results highlight the importance of two processes, chromatin-initiated microtubule nucleation, and sliding forces generated between antiparallel microtubules, in self-organization of spindle bipolarity and poleward flux.

Description: This work was funded by National Institutes of Health grants GM39565 (T.J.M.), GM24364 and GM606780 (E.D.S.), and by MBL fellowships from UIC Inc. and Nikon Inc.

Description: © The Author(s), 2018. This article is distributed under the terms of the Creative Commons Attribution License. The definitive version was published in Geoscientific Model Development 11 (2018): 497-519, doi:10.5194/gmd-11-497-2018.

Description: Peatlands store substantial amounts of carbon and are vulnerable to climate change. We present a modified version of the Organising Carbon and Hydrology In Dynamic Ecosystems (ORCHIDEE) land surface model for simulating the hydrology, surface energy, and CO2 fluxes of peatlands on daily to annual timescales. The model includes a separate soil tile in each 0.5° grid cell, defined from a global peatland map and identified with peat-specific soil hydraulic properties. Runoff from non-peat vegetation within a grid cell containing a fraction of peat is routed to this peat soil tile, which maintains shallow water tables. The water table position separates oxic from anoxic decomposition. The model was evaluated against eddy-covariance (EC) observations from 30 northern peatland sites, with the maximum rate of carboxylation (Vcmax) being optimized at each site. Regarding short-term day-to-day variations, the model performance was good for gross primary production (GPP) (r2 =  0.76; Nash–Sutcliffe modeling efficiency, MEF  =  0.76) and ecosystem respiration (ER, r2 =  0.78, MEF  =  0.75), with lesser accuracy for latent heat fluxes (LE, r2 =  0.42, MEF  =  0.14) and and net ecosystem CO2 exchange (NEE, r2 =  0.38, MEF  =  0.26). Seasonal variations in GPP, ER, NEE, and energy fluxes on monthly scales showed moderate to high r2 values (0.57–0.86). For spatial across-site gradients of annual mean GPP, ER, NEE, and LE, r2 values of 0.93, 0.89, 0.27, and 0.71 were achieved, respectively. Water table (WT) variation was not well predicted (r2 〈 0.1), likely due to the uncertain water input to the peat from surrounding areas. However, the poor performance of WT simulation did not greatly affect predictions of ER and NEE. We found a significant relationship between optimized Vcmax and latitude (temperature), which better reflects the spatial gradients of annual NEE than using an average Vcmax value.

Description: This study was supported by the European Research Council Synergy grant ERC-2013-SyG- 610028 IMBALANCE-P.

Description: © The Author(s), 2021. This article is distributed under the terms of the Creative Commons Attribution License. The definitive version was published in 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-Haentjens, E., Sonnentag, O., Sullivan, R. C., Suyker, A., Ueyama, M., Vargas, R., Wood, J. D., & Zona, D. Representativeness of eddy-covariance flux footprints for areas surrounding AmeriFlux sites. Agricultural and Forest Meteorology, 301, (2021): 108350, https://doi.org/10.1016/j.agrformet.2021.108350.

Description: Large datasets of greenhouse gas and energy surface-atmosphere fluxes measured with the eddy-covariance technique (e.g., FLUXNET2015, AmeriFlux BASE) are widely used to benchmark models and remote-sensing products. This study addresses one of the major challenges facing model-data integration: To what spatial extent do flux measurements taken at individual eddy-covariance sites reflect model- or satellite-based grid cells? We evaluate flux footprints—the temporally dynamic source areas that contribute to measured fluxes—and the representativeness of these footprints for target areas (e.g., within 250–3000 m radii around flux towers) that are often used in flux-data synthesis and modeling studies. We examine the land-cover composition and vegetation characteristics, represented here by the Enhanced Vegetation Index (EVI), in the flux footprints and target areas across 214 AmeriFlux sites, and evaluate potential biases as a consequence of the footprint-to-target-area mismatch. Monthly 80% footprint climatologies vary across sites and through time ranging four orders of magnitude from 103 to 107 m2 due to the measurement heights, underlying vegetation- and ground-surface characteristics, wind directions, and turbulent state of the atmosphere. Few eddy-covariance sites are located in a truly homogeneous landscape. Thus, the common model-data integration approaches that use a fixed-extent target area across sites introduce biases on the order of 4%–20% for EVI and 6%–20% for the dominant land cover percentage. These biases are site-specific functions of measurement heights, target area extents, and land-surface characteristics. We advocate that flux datasets need to be used with footprint awareness, especially in research and applications that benchmark against models and data products with explicit spatial information. We propose a simple representativeness index based on our evaluations that can be used as a guide to identify site-periods suitable for specific applications and to provide general guidance for data use.

Description: We thank the AmeriFlux site teams for sharing their data and metadata with the network. Funding for these flux sites is acknowledged in the site data DOI, shown in Table S1. This analysis was supported in part by funding provided to the AmeriFlux Management Project by the U.S. Department of Energy's Office of Science under Contract No. DE-AC02-05CH11231. All footprint climatologies, site-level representativeness indices, and monthly EVI and sensor location biases can be accessed via the Zenodo Data Repository (Datasets S1–S6, http://doi.org/10.5281/zenodo.4015350).

Description: Significant climate risks are associated with a positive carbon–temperature feedback in northern latitude carbon-rich ecosystems, making an accurate analysis of human impacts on the net greenhouse gas balance of wetlands a priority. Here, we provide a coherent assessment of the climate footprint of a network of wetland sites based on simultaneous and quasi-continuous ecosystem observations of CO2 and CH4 fluxes. Experimental areas are located both in natural and in managed wetlands and cover a wide range of climatic regions, ecosystem types, and management practices. Based on direct observations we predict that sustained CH4 emissions in natural ecosystems are in the long term (i.e., several centuries) typically offset by CO2 uptake, although with large spatiotemporal variability. Using a space-for-time analogy across ecological and climatic gradients, we represent the chronosequence from natural to managed conditions to quantify the “cost” of CH4 emissions for the benefit of net carbon sequestration. With a sustained pulse–response radiative forcing model, we found a significant increase in atmospheric forcing due to land management, in particular for wetland converted to cropland. Our results quantify the role of human activities on the climate footprint of northern wetlands and call for development of active mitigation strategies for managed wetlands and new guidelines of the Intergovernmental Panel on Climate Change (IPCC) accounting for both sustained CH4 emissions and cumulative CO2 exchange.