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International audience; Siberia experienced an unprecedented strong and persistent heatwave in winter to spring of 2020. Using bottom-up and top-down approaches, we evaluated seasonal and annual CO2 fluxes of 2020 in the northern hemisphere (north of 30 °N), focusing on Siberia where the pronounced heatwave occurred. We found that, over Siberia, CO2 respiration loss in response to the pronounced positive winter temperature anomaly was greater than in previous years. However, continued warming in the spring enhanced photosynthetic CO2 uptake, resulting in the largest seasonal transition in net ecosystem CO2 exchange; that is, the largest magnitude of the switch from the net CO2 loss in winter to net CO2 uptake in spring until June. However, this exceptional transition was followed by the largest reduction in CO2 uptake in late summer due to multiple environmental constraints, including a soil moisture deficit. Despite a substantial increase of CO2 uptake by 22 ± 9 gC m-2 in the spring in response to the heatwave, the mean annual CO2 uptake over Siberia was slightly lower (3 ± 13 gC m-2yr-1) than the average of the previous five years. These results highlight the highly dynamic response of seasonal carbon fluxes to extreme temperature anomalies at high latitudes, indicating a seasonal compensation between abnormal uptake and release of CO2 in response to extreme warmth that may limit carbon sink capacity in high northern latitudes.

Top‐down estimates of CO₂ fluxes are typically constrained by either surface‐based or space‐based CO₂ observations. Both of these measurement types have spatial and temporal gaps in observational coverage that can lead to differences in inferred fluxes. Assimilating both surface‐based and space‐based measurements concurrently in a flux inversion framework improves observational coverage and reduces sampling related artifacts. This study examines the consistency of flux constraints provided by these different observations and the potential to combine them by performing a series of 6‐year (2010–2015) CO₂ flux inversions. Flux inversions are performed assimilating surface‐based measurements from the in situ and flask network, measurements from the Total Carbon Column Observing Network (TCCON), and space‐based measurements from the Greenhouse Gases Observing Satellite (GOSAT), or all three data sets combined. Combining the data sets results in more precise flux estimates for subcontinental regions relative to any of the data sets alone. Combining the data sets also improves the accuracy of the posterior fluxes, based on reduced root‐mean‐square differences between posterior flux‐simulated CO₂ and aircraft‐based CO₂ over midlatitude regions (0.33–0.56 ppm) in comparison to GOSAT (0.37–0.61 ppm), TCCON (0.50–0.68 ppm), or in situ and flask measurements (0.46–0.56 ppm) alone. These results suggest that surface‐based and GOSAT measurements give complementary constraints on CO₂ fluxes in the northern extratropics and can be combined in flux inversions to improve constraints on regional fluxes. This stands in contrast with many earlier attempts to combine these data sets and suggests that improvements in the NASA Atmospheric CO₂ Observations from Space (ACOS) retrieval algorithm have significantly improved the consistency of space‐based and surface‐based flux constraints.

Through this White Paper, which gathers contributions from experts of 3D data as well as professionals concerned with the interoperability and sustainability of 3D research data, the PARTHENOS project aims at highlighting some of the current issues they have to face, with possible specific points according to the discipline, and potential practices and methodologies to deal with these issues. During the workshop, several tools to deal with these issues have been introduced and confronted with the participants' experiences, this White Paper now intends to go further by also integrating participants feedbacks and suggestions of potential improvements. Therefore, even if the focus is put on specific tools, the main goal is to contribute to the development of standardized good practices related to the sharing, publication, storage and long-term preservation of 3D data.

A warming climate is altering land-atmosphere exchanges of carbon, with a potential for increased vegetation productivity as well as the mobilization of permafrost soil carbon stores. Here we investigate land-atmosphere carbon dioxide (CO2) cycling through analysis of net ecosystem productivity (NEP) and its component fluxes of gross primary productivity (GPP) and ecosystem respiration (ER) and soil carbon residence time, simulated by a set of land surface models (LSMs) over a region spanning the drainage basin of Northern Eurasia. The retrospective simulations cover the period 1960–2009 at 0.5° resolution, which is a scale common among many global carbon and climate model simulations. Model performance benchmarks were drawn from comparisons against both observed CO2 fluxes derived from site-based eddy covariance measurements as well as regional-scale GPP estimates based on satellite remote-sensing data. The site-based comparisons depict a tendency for overestimates in GPP and ER for several of the models, particularly at the two sites to the south. For several models the spatial pattern in GPP explains less than half the variance in the MODIS MOD17 GPP product. Across the models NEP increases by as little as 0.01 to as much as 0.79 g C m−2 yr−2, equivalent to 3 to 340 % of the respective model means, over the analysis period. For the multimodel average the increase is 135 % of the mean from the first to last 10 years of record (1960–1969 vs. 2000–2009), with a weakening CO2 sink over the latter decades. Vegetation net primary productivity increased by 8 to 30 % from the first to last 10 years, contributing to soil carbon storage gains. The range in regional mean NEP among the group is twice the multimodel mean, indicative of the uncertainty in CO2 sink strength. The models simulate that inputs to the soil carbon pool exceeded losses, resulting in a net soil carbon gain amid a decrease in residence time. Our analysis points to improvements in model elements controlling vegetation productivity and soil respiration as being needed for reducing uncertainty in land-atmosphere CO2 exchange. These advances will require collection of new field data on vegetation and soil dynamics, the development of benchmarking data sets from measurements and remote-sensing observations, and investments in future model development and intercomparison studies.

A common assumption of remote sensing-based light use efficiency (LUE) models for estimating vegetation gross primary productivity (GPP) is that plants in a biome matrix operate at their photosynthetic capacity under optimal climatic conditions. A prescribed constant biome maximum light use efficiency parameter (LUEmax) defines the maximum photosynthetic carbon conversion rate under these conditions and is a large source of model uncertainty. Here we used tower eddy covariance measurement-based carbon (CO2) fluxes for spatial estimation of optimal LUE (LUEopt) across North America. LUEopt was estimated at 62 Flux Network sites using tower daily carbon fluxes and meteorology, and satellite observed fractional photosynthetically active radiation from the Moderate Resolution Imaging Spectroradiometer. Ageostatistical model was fitted to 45 flux tower-derived LUEopt data points using independent geospatial environmental variables, including global plant traits, soil moisture, terrain aspect, land cover type, and percent tree cover, and validated at 17 independent tower sites. Estimated LUEopt shows large spatial variability within and among different land cover classes indicated from the sparse tower network. Leaf nitrogen content and soil moisture regime are major factors explaining LUEopt patterns. GPP derived from estimated LUEopt shows significant correlation improvement against tower GPP records (R2 = 76.9%; mean root-mean-square error (RMSE) = 257gCm-2yr-1), relative to alternative GPP estimates derived using biome-specific LUEmax constants (R2 = 34.0%; RMSE = 439gCm-2yr-1). GPP determined from the LUEopt map also explains a 49.4% greater proportion of tower GPP variability at the independent validation sites and shows promise for improving understanding of LUE patterns and environmental controls and enhancing regional GPP monitoring from satellite remote sensing.

[Notes_IRSTEA]European Union 7th Framework Programme under project Page21 (grant 282700) [Departement_IRSTEA]Eaux [TR1_IRSTEA]ARCEAU; International audience; A warming climate is altering land-atmosphere exchanges of carbon, with a potential for increased vegetation productivity as well as the mobilization of permafrost soil carbon stores. Here we investigate land-atmosphere carbon dioxide (CO 2) cycling through analysis of net ecosystem productivity (NEP) and its component fluxes of gross primary productivity (GPP) and ecosystem respiration (ER) and soil carbon residence time, simulated by a set of land surface models (LSMs) over a region spanning the drainage basin of Northern Eurasia. The retrospective simulations cover the period 1960–2009 at 0.5 • resolution, which is a scale common among many global carbon and climate model simulations. Model performance benchmarks were drawn from comparisons against both observed CO 2 fluxes derived from site-based eddy covariance measurements as well as regional-scale GPP estimates based on satellite remote-sensing data. Published by Copernicus Publications on behalf of the European Geosciences Union. 4386 M. A. Rawlins et al.: CO 2 Exchange Across Northern Eurasia The site-based comparisons depict a tendency for overestimates in GPP and ER for several of the models, particularly at the two sites to the south. For several models the spatial pattern in GPP explains less than half the variance in the MODIS MOD17 GPP product. Across the models NEP increases by as little as 0.01 to as much as 0.79 g C m −2 yr −2 , equivalent to 3 to 340 % of the respective model means, over the analysis period. For the multimodel average the increase is 135 % of the mean from the first to last 10 years of record (1960–1969 vs. 2000–2009), with a weakening CO 2 sink over the latter decades. Vegetation net primary productivity increased by 8 to 30 % from the first to last 10 years, contributing to soil carbon storage gains. The range in regional mean NEP among the group is twice the multimodel mean, indicative of the uncertainty in CO 2 sink strength. The models simulate that inputs to the soil carbon pool exceeded losses, resulting in a net soil carbon gain amid a decrease in residence time. Our analysis points to improvements in model elements controlling vegetation productivity and soil respiration as being needed for reducing uncertainty in land-atmosphere CO 2 exchange. These advances will require collection of new field data on vegetation and soil dynamics, the development of benchmarking data sets from measurements and remote-sensing observations, and investments in future model development and intercomparison studies.

Building facades can fail in a variety of ways. Masonry can crack or deteriorate over time, supports can corrode, surface seals can leak, or the wall may trap moisture-laden air that triggers condensation and mold growth. Some types of facades have characteristics that make them more susceptible to failure. An understanding of these vulnerable facade characteristics can help building designers and owners avoid (or at least be prepared for) facade failures.

The northern terrestrial net ecosystem carbon balance (NECB) is contingent on inputs from vegetation gross primary productivity (GPP) to offset the ecosystem respiration (Reco) of carbon dioxide (CO2) and methane (CH4) emissions, but an effective framework to monitor the regional Arctic NECB is lacking. We modified a terrestrial carbon flux (TCF) model developed for satellite remote sensing applications to evaluate wetland CO2 and CH4 fluxes over pan-Arctic eddy covariance (EC) flux tower sites. The TCF model estimates GPP, CO2 and CH4 emissions using in situ or remote sensing and reanalysis-based climate data as inputs. The TCF model simulations using in situ data explained > 70% of the r2 variability in the 8 day cumulative EC measured fluxes. Model simulations using coarser satellite (MODIS) and reanalysis (MERRA) records accounted for approximately 69% and 75% of the respective r2 variability in the tower CO2 and CH4 records, with corresponding RMSE uncertainties of &leq; 1.3 g C m−2 d−1 (CO2) and 18.2 mg C m−2 d−1 (CH4). Although the estimated annual CH4 emissions were small (< 18 g C m−2 yr−1) relative to Reco (> 180 g C m−2 yr−1), they reduced the across-site NECB by 23% and contributed to a global warming potential of approximately 165 ± 128 g CO2eq m−2 yr−1 when considered over a 100 year time span. This model evaluation indicates a strong potential for using the TCF model approach to document landscape-scale variability in CO2 and CH4 fluxes, and to estimate the NECB for northern peatland and tundra ecosystems.

Prior to the 20th century, building walls were often constructed of stone or brick up to several feet thick. Such massive walls served not only to support the floors and roof but also to keep out the weather. In the early 1900s economic pressures and the need for taller buildings led to the development of thinner, lighter, and less costly wall systems. While these thinner walls did not usually carry gravity loads, they often involved a combination of materials and components requiring more complex leak control and connection/support mechanisms. A wide variety of unanticipated problems, such as accumulated differential thermal or moisture expansion, increased water leakage due to a lack of drainage redundancy, and cracking or displacement related to material incompatibility, sometimes accompanied these new wall systems.

Ten scientific organizations formed a joint international committee to provide expert recommendations for clinical pathology testing of laboratory animal species used in regulated toxicity and safety studies. For repeated-dose studies in rodent species, clinical pathology testing is necessary at study termination. Interim study testing may not be necessary in long-duration studies provided that it has been done in short-duration studies using dose levels not substantially lower than those used in the long-duration studies. For repeated-dose studies in nonrodent species, clinical pathology testing is recommended at study termination and at least once at an earlier interval. For studies of 2 to 6 weeks in duration in nonrodent species, testing is also recommended within 7 days of initiation of dosing, unless it compromises the health of the animals. If a study contains recovery groups, clinical pathology testing at study termination is recommended. The core hematology tests recommended are total leukocyte (white blood cell) count, absolute differential leukocyte count, erythrocyte (red blood cell) count, evaluation of red blood cell morphology, platelet (thrombocyte) count, hemoglobin concentration, hematocrit (or packed cell volume), mean corpuscular volume, mean corpuscular hemoglobin, and mean corpuscular hemoglobin concentration. In the absence of automated reticulocyte counting capabilities, blood smears from each animal should be prepared for reticulocyte counts. Bone marrow cytology slides should be prepared from each animal at termination. Prothrombin time and activated partial thromboplastin time (or appropriate alternatives) and platelet count are the minimum recommended laboratory tests of hemostasis. The core clinical chemistry tests recommended are glucose, urea nitrogen, creatinine, total protein, albumin, calculated globulin, calcium, sodium, potassium, total cholesterol, and appropriate hepatocellular and hepatobiliary tests. For hepatocellular evaluation, measurement of a minimum of two scientifically appropriate blood tests is recommended, e.g., alanine aminotransferase, aspartate aminotransferase, sorbitol dehydrogenase, glutamate dehydrogenase, or total bile acids. For hepatobiliary evaluation, measurement of a minimum of two scientifically appropriate blood tests is recommended, e.g., alkaline phosphatase, gamma glutamyltransferase, 5′-nucleotidase, total bilirubin, or total bile acids. Urinalysis should be conducted at least once during a study. For routine urinalysis, an overnight collection (approximately 16 hr) is recommended. It is recommended that the core tests should include an assessment of urine appearance (color and turbidity), volume, specific gravity or osmolality, pH, and either the quantitative or semiquantitative determination of total protein and glucose. For carcinogenicity studies, only blood smears should be made from unscheduled sacrifices (decedents) and at study termination to aid in the identification and differentiation of hematopoietic neoplasia.

To facilitate the creation of easily comparable, low-resolution genetic maps with evenly distributed markers in rice (Oryza sativa L.), we conceived of and developed a Universal Core Genetic Map (UCGM). With this aim, we derived a set of 165 anchors, representing clusters of three microsatellite or simple sequence repeat (SSR) markers arranged into non-recombining groups. Each anchor consists of at least three, closely linked SSRs, located within a distance below the genetic resolution provided by common, segregating populations (< 500 individuals). We chose anchors that were evenly distributed across the rice chromosomes, with spacing between 2 and 3.5 Mbp (except in the telomeric regions, where spacing was 1.5 Mbp). Anchor selection was performed using in silico tools and data: the O. sativa cv. Nipponbare rice genome sequence, the CHARM tool, information from the Gramene database and the OrygenesDB database. Sixteen AA-genome accessions of the Oryza genus were used to evaluate polymorphisms for the selected markers, including accessions from O. sativa, O. glaberrima, O. barthii, O. rufipogon, O. glumaepatula and O. meridionalis. High levels of polymorphism were found for the tested O. sativa x O. glaberrima or O. sativa x wild rice combinations. We developed Paddy Map, a simple database that is helpful in selecting optimal sets of polymorphic SSRs for any cross that involves the previously mentioned species. Validation of the UCGM was done by using it to develop three interspecific genetic maps and by comparing genetic SSR locations with their physical positions on the rice pseudomolecules. In this study, we demonstrate that the UCGM is a useful tool for the rice genetics and breeding community, especially in strategies based on interspecific hybridisation.

Water leakage through brick‐clad walls is one of the most difficult masonry problems to correct. These leaks can cause severe damage to underlying wall elements and to interior finishes as well as disrupt building occupants. Excessive water entry into the wall usually results from poor brick workmanship. Subsequent water penetration into interior spaces may result from errors in design and/or construction of the wall‐drainage system. In most cases, leaks can easily be avoided if the designer properly details the flashing‐and‐weep system and carefully monitors construction for quality workmanship and conformance with design. The two most common types of exterior brick‐clad walls in existence today are the barrier and the cavity walls. Barrier walls block water from passing completely through the wall, thus preventing leakage into the building's interior. Cavity walls provide a continuous void within the wall that serves as a channel to guide water out of the wall before it reaches the interior. Both barrie...