How do we best synergise climate mitigation actions to co-benefit biodiversity?

Acknowledgements We thank Yuka Otsuki Estrada for help in designing and producing the table, and all other authors of the IPBES-IPCC report on the scientific outcome of the IPBES-IPCC co-sponsored workshop on biodiversity and climate change (Pörtner et al., 2021) for cross-cutting discussions during preparation of this analysis. Although this paper is based on the report of the IPBES-IPCC co882 sponsored workshop, the views expressed here represent the individual views of the authors. We would also like to thank the scientific steering committee of the IPBES-IPCC co-sponsored workshop, review editors, the IPCC and IPBES Secretariat, especially Anne Larigauderie, and Technical Support Units. In memory of our friend and co-author, Bob Scholes, who sadly died during the preparation of this synthesis, and who will be sorely missed by all.Peer reviewedPostprin

Quantitative and Qualitative Urinary Cellular Patterns Correlate with Progression of Murine Glomerulonephritis

The kidney is a nonregenerative organ composed of numerous functional nephrons and collecting ducts (CDs). Glomerular and tubulointerstitial damages decrease the number of functional nephrons and cause anatomical and physiological alterations resulting in renal dysfunction. It has recently been reported that nephron constituent cells are dropped into the urine in several pathological conditions associated with renal functional deterioration. We investigated the quantitative and qualitative urinary cellular patterns in a murine glomerulonephritis model and elucidated the correlation between cellular patterns and renal pathology

Predicting carbon dioxide and energy fluxes across global FLUXNET sites with regression algorithms

Gianluca Tramontana was supported by the GEOCARBON EU FP7 project (GA 283080). Dario Papale, Martin Jung and Markus Reichstein acknowledge funding from the EU FP7 project GEOCARBON (grant agreement no. 283080) and the EU H2020 BACI project (grant agreement no. 640176). Gustau Camps-Valls wants to acknowledge the support by an ERC Consolidator Grant with grant agreement 647423 (SEDAL). Kazuhito Ichii was supported by Environment Research and Technology Development Funds (2-1401) from the Ministry of the Environment of Japan and the JAXA Global Change Observation Mission (GCOM) project (no. 115). Christopher R. Schwalm was supported by National Aeronautics and Space Administration (NASA) grants nos. NNX12AP74G, NNX10AG01A, and NNX11AO08A. M. Altaf Arain thanks the support of Natural Sciences and Engineering Research Council (NSREC) of Canada. Penelope Serrano Ortiz was partially supported by the GEISpain project (CGL2014-52838-C2-1-R) funded by the Spanish Ministry of Economy and Competitiveness and the European Union ERDF funds. Sebastian Wolf acknowledges support from a Marie Curie International Outgoing Fellowship (European Commission, grant 300083). The FLUXCOM initiative is coordinated by Martin Jung, Max Planck Institute for Biogeochemistry (Jena, Germany). This work used eddy-covariance data acquired by the FLUXNET community and in particular by the following networks: AmeriFlux (US Department of Energy, Biological and Environmental Research, Terrestrial Carbon Program (DE-FG02-04ER63917 and DE-FG02-04ER63911)), AfriFlux, AsiaFlux, CarboAfrica, CarboEuropeIP, CarboItaly, CarboMont, ChinaFlux, FluxnetCanada (supported by CFCAS, NSERC, BIOCAP, Environment Canada, and NRCan), GreenGrass, KoFlux, LBA, NECC, OzFlux, TCOS-Siberia, USCCC. We acknowledge the financial support to the eddy-covariance data harmonization provided by CarboEuropeIP, FAO-GTOS-TCO, iLEAPS, the Max Planck Institute for Biogeochemistry, the National Science Foundation, the University of Tuscia and the US Department of Energy, and the databasing and technical support from Berkeley Water Center, Lawrence Berkeley National Laboratory, Microsoft Research eScience, Oak Ridge National Laboratory, the University of California - Berkeley, and the University of Virginia.Spatio-temporal fields of land–atmosphere fluxes derived from data-driven models can complement simulations by process-based land surface models. While a number of strategies for empirical models with eddy-covariance flux data have been applied, a systematic intercomparison of these methods has been missing so far. In this study, we performed a cross-validation experiment for predicting carbon dioxide, latent heat, sensible heat and net radiation fluxes across different ecosystem types with 11 machine learning (ML) methods from four different classes (kernel methods, neural networks, tree methods, and regression splines). We applied two complementary setups: (1) 8-day average fluxes based on remotely sensed data and (2) daily mean fluxes based on meteorological data and a mean seasonal cycle of remotely sensed variables. The patterns of predictions from different ML and experimental setups were highly consistent. There were systematic differences in performance among the fluxes, with the following ascending order: net ecosystem exchange (R2  0.6), gross primary production (R2> 0.7), latent heat (R2 > 0.7), sensible heat (R2 > 0.7), and net radiation (R2 > 0.8). The ML methods predicted the across-site variability and the mean seasonal cycle of the observed fluxes very well (R2 > 0.7), while the 8-day deviations from the mean seasonal cycle were not well predicted (R2 < 0.5). Fluxes were better predicted at forested and temperate climate sites than at sites in extreme climates or less represented by training data (e.g., the tropics). The evaluated large ensemble of ML-based models will be the basis of new global flux products.European Union (EU) GA 283080 283080 640176European Research Council (ERC) 647423Ministry of the Environment, Japan 2-1401JAXA Global Change Observation Mission (GCOM) project 115National Aeronautics & Space Administration (NASA) NNX12AP74G NNX10AG01A NNX11AO08ANatural Sciences and Engineering Research Council of CanadaGEISpain project - Spanish Ministry of Economy and Competitiveness CGL2014-52838-C2-1-REuropean Commission Joint Research Centre 300083United States Department of Energy (DOE) DE-FG02-04ER63917 DE-FG02-04ER63911FAO-GTOS-TCOiLEAPSMax Planck Institute for BiogeochemistryNational Science Foundation (NSF)University of Tusci

The Orbiting Carbon Observatory (OCO-2) Tracks 2-3 Peta-Gram Increase in Carbon Release to the Atmosphere During the 2014-2016 El Nino

The powerful El Nio event of 2015-2016 - the third most intense since the 1950s - has exerted a large impact on the Earth's natural climate system. The column-averaged CO2 dry-air mole fraction (XCO2) observations from satellites and ground based networks are analyzed together with in situ observations for the period of September 2014 to October 2016. From the differences between satellite (OCO-2) observations and simulations using an atmospheric chemistry-transport model, we estimate that, relative to the mean annual fluxes for 2014, the most recent El Nio has contributed to an excess CO2 emission from the Earth's surface (land+ocean) to the atmosphere in the range of 2.4+/-0.2 PgC (1 Pg = 10(exp 15) g) over the period of July 2015 to June 2016. The excess CO2 flux is resulted primarily from reduction in vegetation uptake due to drought, and to a lesser degree from increased biomass burning. It is about the half of the CO2 flux anomaly (range: 4.4-6.7 PgC) estimated for the 1997/1998 El Nio. The annual total sink is estimated to be 3.9+/-0.2 PgC for the assumed fossil fuel emission of 10.1 PgC. The major uncertainty in attribution arise from error in anthropogenic emission trends, satellite data and atmospheric transport

Regional carbon fluxes from land use and land cover change in Asia, 1980–2009

This is the final version of the article. Available from IOP Publishing via the DOI in this record.We present a synthesis of the land-atmosphere carbon flux from land use and land cover change (LULCC) in Asia using multiple data sources and paying particular attention to deforestation and forest regrowth fluxes. The data sources are quasi-independent and include the U.N. Food and Agriculture Organization-Forest Resource Assessment (FAO-FRA 2015; country-level inventory estimates), the Emission Database for Global Atmospheric Research (EDGARv4.3), the 'Houghton' bookkeeping model that incorporates FAO-FRA data, an ensemble of 8 state-of-the-art Dynamic Global Vegetation Models (DGVM), and 2 recently published independent studies using primarily remote sensing techniques. The estimates are aggregated spatially to Southeast, East, and South Asia and temporally for three decades, 1980–1989, 1990–1999 and 2000–2009. Since 1980, net carbon emissions from LULCC in Asia were responsible for 20%–40% of global LULCC emissions, with emissions from Southeast Asia alone accounting for 15%–25% of global LULCC emissions during the same period. In the 2000s and for all Asia, three estimates (FAO-FRA, DGVM, Houghton) were in agreement of a net source of carbon to the atmosphere, with mean estimates ranging between 0.24 to 0.41 Pg C yr−1, whereas EDGARv4.3 suggested a net carbon sink of −0.17 Pg C yr−1. Three of 4 estimates suggest that LULCC carbon emissions declined by at least 34% in the preceding decade (1990–2000). Spread in the estimates is due to the inclusion of different flux components and their treatments, showing the importance to include emissions from carbon rich peatlands and land management, such as shifting cultivation and wood harvesting, which appear to be consistently underreported.This work was supported by the Asia Pacific Network for Global Change Research (ARCP2013-01CMY-Patra/Canadell). LC was supported by the National Science Foundation East Asia Pacific Summer Institute (EAPSI) Fellowship. KI and PP were supported by the Environment Research and Technology Development Funds (2-1401) from the Ministry of the Environment of Japan. JGC thanks the support from the Australian Climate Change Science Program. AI and EK were supported by ERTDF (S-10) by the Ministry of the Environment, Japan. CK is supported by DOE-BER through BGC-Feedbacks SFA and NGEE-Tropics. AW was supported by the Joint UK DECC/Defra Met Office Hadley Centre Climate Programme (GA01101) and EU FP7 Funding through project LUC4C (603542)

Regional carbon fluxes from land use and land cover change in Asia, 1980-2009

Wepresent a synthesis of the land-atmosphere carbon flux from land use and land cover change (LULCC) in Asia usingmultiple data sources and paying particular attention to deforestation and forest regrowth fluxes. The data sources are quasi-independent and include the U.N. Food andAgriculture Organization-Forest Resource Assessment (FAO-FRA2015; country-level inventory estimates), the Emission Database forGlobalAtmospheric Research (EDGARv4.3), the ‘Houghton’ bookkeepingmodel that incorporates FAO-FRA data, an ensemble of 8 state-of-the-artDynamic Global Vegetation Models (DGVM), and2 recently published independent studies using primarily remote sensing techniques.The estimates are aggregated spatially to Southeast, East, and SouthAsia and temporally for three decades, 1980–1989, 1990–1999 and 2000–2009. Since 1980, net carbon emissions from LULCCin Asia were responsible for 20%–40%of global LULCCemissions, with emissions from Southeast Asia alone accounting for15%–25%of global LULCCemissions during the same period. In the 2000s and for allAsia, three estimates (FAO-FRA,DGVM,Houghton) were in agreement of a net source of carbon to the atmosphere,with meanestimates rangingbetween0.24 to0.41PgCyr$^{-1}$,whereasEDGARv4.3 suggested a net carbon sink of−0.17 Pg C yr$^{-1}$. Three of 4 estimates suggest that LULCCcarbon emissions declined by at least 34%in the preceding decade (1990–2000). Spread in the estimates is due to the inclusion of different flux components and their treatments, showing the importance to includeemissions fromcarbon rich peatlands and land management, such as shifting cultivation andwood harvesting, which appear to be consistently underreported

Finite-temperature phase transition of SU(3) gauge theory on Nt=4 and 6 lattices

The deconfining finite-temperature transition of SU(3) gauge theory is studied on the dedicated parallel computer QCDPAX. Monte Carlo simulations are performed on 122×24×4, 242×36×4, 203×6, 243×6, and 362×48×6 lattices with 376 000 to 1 112 000 iterations. The finite size scaling behavior of the first-order transition is confirmed both on the Nt=4 and Nt=6 lattices and clear two-phase structures are observed on spatially large lattices (242×36×4 and 362×48×6). The latent heat at the deconfining transition is estimated both by a direct measurement of the gap on the spatially large lattices and by applying a finite-size scaling law. The results obtained by these two independent methods are remarkably consistent with each other on both the Nt=4 lattices. The latent heat for Nt=6 is much smaller than that for Nt=4 and is about ⅓ of the Stefan-Boltzmann value 8π2/15. The details of the data and the error analysis are presented

Plant Regrowth as a Driver of Recent Enhancement of Terrestrial CO2 Uptake

The increasing strength of land CO2 uptake in the 2000s has been attributed to a stimulating effect of rising atmospheric CO2 on photosynthesis (CO2 fertilization). Using terrestrial biosphere models, we show that enhanced CO2 uptake is induced not only by CO2 fertilization but also an increasing uptake by plant regrowth (accounting for 0.33 ± 0.10 Pg C/year increase of CO2 uptake in the 2000s compared with the 1960s-1990s) with its effect most pronounced in eastern North America, southern‐eastern Europe, and southeastern temperate Eurasia. Our analysis indicates that ecosystems in North America and Europe have established the current productive state through regrowth since the 1960s, and those in temperate Eurasia are still in a stage from regrowth following active afforestation in the 1980s-1990s. As the strength of model representation of CO2 fertilization is still in debate, plant regrowth might have a greater potential to sequester carbon than indicated by this study