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Robust estimates of CO₂ budget, CO₂ exchanged between the atmosphere and terrestrial biosphere, are necessary to better understand the role of the terrestrial biosphere in mitigating anthropogenic CO₂ emissions. Over the past decade, this field of research has advanced through understanding of the differences and similarities of two fundamentally different approaches: “top-down” atmospheric inversions and “bottom-up” biosphere models. Since the first studies were undertaken, these ap-proaches have shown an increasing level of agreement, but disagreements in some regions still persist, in part because they do not estimate the same quantity of atmos-phere–biosphere CO₂ exchange. Here, we conducted a thorough comparison of CO₂ budgets at multiple scales and from multiple methods to assess the current state of the science in estimating CO₂ budgets. Our set of atmospheric inversions and bio-sphere models, which were adjusted for a consistent flux definition, showed a high level of agreement for global and hemispheric CO₂ budgets in the 2000s. Regionally, improved agreement in CO₂ budgets was notable for North America and Southeast Asia. However, large gaps between the two methods remained in East Asia and South America. In other regions, Europe, boreal Asia, Africa, South Asia, and Oceania, it was difficult to determine whether those regions act as a net sink or source because of the large spread in estimates from atmospheric inversions. These results highlight two research directions to improve the robustness of CO₂ budgets: (a) to increase repre-sentation of processes in biosphere models that could contribute to fill the budget gaps, such as forest regrowth and forest degradation; and (b) to reduce sink–source compensation between regions (dipoles) in atmospheric inversion so that their esti-mates become more comparable. Advancements on both research areas will increase the level of agreement between the top-down and bottom-up approaches and yield more robust knowledge of regional CO₂ budgets.

There is more useful information in the time series of satellite-derived column-averaged carbon dioxide (XCO2) than is typically characterized. Often, the entire time series is treated at once without considering detailed features at shorter timescales, such as non-stationary changes in signal characteristics – amplitude, period, and phase. In many instances, signals are visually and analytically differentiable from other portions in a time series. Each Rise (increasing) and Fall (decreasing) segment, in the seasonal cycle is visually discernable in a graph of the time series. The Rise and Fall segments largely result from seasonal differences in terrestrial ecosystem production, which means that the segment’s signal characteristics can be used to establish observational benchmarks because the signal characteristics are driven by similar underlying processes. We developed an analytical segmentation algorithm to characterize the Rise and Fall segments in XCO2 seasonal cycles. We present the algorithm for general application of the segmentation analysis and emphasize here that the segmentation analysis is more generally applicable to cyclic time series. We demonstrate the utility of the algorithm with specific results related to the comparison between satellite- and model-derived XCO2 seasonal cycles (2009–2012) for large bioregions on the globe. We found a seasonal amplitude gradient of 0.74–0.77 ppm for every 10˚ degrees of latitude for the satellite data, with similar gradients for Rise and Fall segments. This translates to a south-north seasonal amplitude gradient of 8 ppm for XCO2, about half the gradient in seasonal amplitude based on surface site in-situ CO2 data (~ 19 ppm). The latitudinal gradients in period of the satellite-derived seasonal cycles were of opposing sign and magnitude (-9 days/10˚ latitude for Fall segments, and 10 days/10˚ latitude for Rise segments), and suggests that a specific latitude (~ 2˚ N) exists which defines an inversion point for the period asymmetry. Before (after) the point of asymmetry inversion, the periods of Rise segments are less (greater) than the periods of Fall segments; only a single model could reproduce this emergent pattern. The asymmetry in amplitude and period between Rise and Fall segments introduces a novel pattern in seasonal cycle analyses, but while we show these emergent patterns exist in the data, we are still breaking ground in applying the information for science applications. Maybe the most useful application is that the segmentation analysis allowed us to decompose the model biases into their correlated parts of biases in amplitude, period, and phase, independently for Rise and Fall segments. We offer an extended discussion on how such information on model biases and the emergent patterns in satellite-derived seasonal cycles can be used to guide future inquiry and model development.

Understanding the global carbon (C) cycle is of crucial importance to map current and future climate dynamics relative to global environmental change. A full characterization of C cycling requires detailed information on spatiotemporal patterns of surface-atmosphere fluxes. However, relevant C cycle observations are highly variable in their coverage and reporting standards. Especially problematic is the lack of integration of the carbon dioxide (CO2) exchange of the ocean, inland freshwaters and the land surface with the atmosphere. Here we adopt a data-driven approach to synthesize a wide range of observation-based spatially explicit surface-atmosphere CO2 fluxes from 2001 to 2010, to identify the state of today's observational opportunities and data limitations. The considered fluxes include net exchange of open oceans, continental shelves, estuaries, rivers, and lakes, as well as CO2 fluxes related to net ecosystem productivity, fire emissions, loss of tropical aboveground C, harvested wood and crops, as well as fossil fuel and cement emissions. Spatially explicit CO2 fluxes are obtained through geostatistical and/or remote-sensing-based upscaling, thereby minimizing biophysical or biogeochemical assumptions encoded in process-based models. We estimate a bottom-up net C exchange (NCE) between the surface (land, ocean, and coastal areas) and the atmosphere. Though we provide also global estimates, the primary goal of this study is to identify key uncertainties and observational shortcomings that need to be prioritized in the expansion of in situ observatories. Uncertainties for NCE and its components are derived using resampling. In many regions, our NCE estimates agree well with independent estimates from other sources such as process-based models and atmospheric inversions. This holds for Europe (mean±1 SD: 0.8±0.1PgCyr-1, positive numbers are sources to the atmosphere), Russia (0.1±0.4PgCyr-1), East Asia (1.6±0.3PgCyr-1), South Asia (0.3±0.1PgCyr-1), Australia (0.2±0.3PgCyr-1), and most of the Ocean regions. Our NCE estimates give a likely too large CO2 sink in tropical areas such as the Amazon, Congo, and Indonesia. Overall, and because of the overestimated CO2 uptake in tropical lands, our global bottom-up NCE amounts to a net sink of -5.4±2.0PgCyr-1. By contrast, the accurately measured mean atmospheric growth rate of CO2 over 2001-2010 indicates that the true value of NCE is a net CO2 source of 4.3±0.1PgCyr-1. This mismatch of nearly 10PgCyr-1 highlights observational gaps and limitations of data-driven models in tropical lands, but also in North America. Our uncertainty assessment provides the basis for setting priority regions where to increase carbon observations in the future. High on the priority list are tropical land regions, which suffer from a lack of in situ observations. Second, extensive pCO2 data are missing in the Southern Ocean. Third, we lack observations that could enable seasonal estimates of shelf, estuary, and inland water-atmosphere C exchange. Our consistent derivation of data uncertainties could serve as prior knowledge in multicriteria optimization such as the Carbon Cycle Data Assimilation System (CCDAS) and atmospheric inversions, without over- or under-stating bottom-up data credibility. In the future, NCE estimates of carbon sinks could be aggregated at national scale to compare with the official national inventories of CO2 fluxes in the land use, land use change, and forestry sector, upon which future emission reductions are proposed., SCOPUS: re.j, info:eu-repo/semantics/published

Understanding the global carbon (C) cycle is of crucial importance to map current and future climate dynamics relative to global environmental change. A full characterization of C cycling requires detailed information on spatiotemporal patterns of surface–atmosphere fluxes. However, relevant C cycle observations are highly variable in their coverage and reporting standards. Especially problematic is the lack of integration of the carbon dioxide (CO2) exchange of the ocean, inland freshwaters and the land surface with the atmosphere. Here we adopt a data-driven approach to synthesize a wide range of observation-based spatially explicit surface–atmosphere CO2 fluxes from 2001 to 2010, to identify the state of today's observational opportunities and data limitations. The considered fluxes include net exchange of open oceans, continental shelves, estuaries, rivers, and lakes, as well as CO2 fluxes related to net ecosystem productivity, fire emissions, loss of tropical aboveground C, harvested wood and crops, as well as fossil fuel and cement emissions. Spatially explicit CO2 fluxes are obtained through geostatistical and/or remote-sensing-based upscaling, thereby minimizing biophysical or biogeochemical assumptions encoded in process-based models. We estimate a bottom-up net C exchange (NCE) between the surface (land, ocean, and coastal areas) and the atmosphere. Though we provide also global estimates, the primary goal of this study is to identify key uncertainties and observational shortcomings that need to be prioritized in the expansion of in situ observatories. Uncertainties for NCE and its components are derived using resampling. In many regions, our NCE estimates agree well with independent estimates from other sources such as process-based models and atmospheric inversions. This holds for Europe (mean ± 1 SD: 0.8 ± 0.1 PgC yr−1, positive numbers are sources to the atmosphere), Russia (0.1 ± 0.4 PgC yr−1), East Asia (1.6 ± 0.3 PgC yr−1), South Asia (0.3 ± 0.1 PgC yr−1), Australia (0.2 ± 0.3 PgC yr−1), and most of the Ocean regions. Our NCE estimates give a likely too large CO2 sink in tropical areas such as the Amazon, Congo, and Indonesia. Overall, and because of the overestimated CO2 uptake in tropical lands, our global bottom-up NCE amounts to a net sink of −5.4 ± 2.0 PgC yr−1. By contrast, the accurately measured mean atmospheric growth rate of CO2 over 2001–2010 indicates that the true value of NCE is a net CO2 source of 4.3 ± 0.1 PgC yr−1. This mismatch of nearly 10 PgC yr−1 highlights observational gaps and limitations of data-driven models in tropical lands, but also in North America. Our uncertainty assessment provides the basis for setting priority regions where to increase carbon observations in the future. High on the priority list are tropical land regions, which suffer from a lack of in situ observations. Second, extensive pCO2 data are missing in the Southern Ocean. Third, we lack observations that could enable seasonal estimates of shelf, estuary, and inland water–atmosphere C exchange. Our consistent derivation of data uncertainties could serve as prior knowledge in multicriteria optimization such as the Carbon Cycle Data Assimilation System (CCDAS) and atmospheric inversions, without over- or under-stating bottom-up data credibility. In the future, NCE estimates of carbon sinks could be aggregated at national scale to compare with the official national inventories of CO2 fluxes in the land use, land use change, and forestry sector, upon which future emission reductions are proposed., Biogeosciences, 14 (15), ISSN:1726-4170

Objetivo: Validar la histerosonografía para el diagnóstico de patologías endometriales en mujeres con hemorragia uterina anormal en comparación con histopatología en la consulta externa del Hospital José Carrasco Arteaga. Cuenca 2010-2012. Material y métodos: El estudio incluyo 250 pacientes con hemorragia uterina anormal valoradas por el especialista y remitidas para valoración por imagenología. Se realizó pruebas de Histerosonografía y análisis de histopatología a todas las pacientes. Se obtuvieron valores de sensibilidad, especificidad, valores predictivos positivos y negativos y razones de verosimilitud. Resultados: La media de edad fue de 48,69 años de edad; la media de edad de presentación de menarquía fue de 12,89 años mientras que la media de edad para la presentación de menopausia fue de 44,17 años; la hemorragia anormal de mayor presentación fue la hipermenorrea con el 36,4%. Mediante la técnica histerosonográfica el principal diagnóstico encontrado fue el pólipo endometrial con el 26,8%.Mientras que mediante la histopatología la hiperplasia endometrial fue el principal diagnóstico con un 24,8%. La sensibilidad de la histerosonografía para diagnóstico de patologías uterinas fue de 90.08% (IC: 83.31 – 94.40) y la especificidad del 94.79 %(65.85 – 82.10) Conclusiones: La histerosonografía presentó una alta sensibilidad y especificidad para el diagnóstico de pólipos endometriales, hiperplasia endometrial y endometrio normal. Descriptores: HISTEROSONOGRAFIA, HISTOPATOLOGIA, PATOLOGIA/CLASIFICACION, SENSIBILIDAD Y ESPECIFICIDAD, HOSPITAL JOSE CARRASCO ARTEAGA DEL INSTITUTO ECUATORIANO DE SEGURIDAD SOCIAL. Objective: To validate hysterosonography for diagnosing endometrial pathology in women with abnormal uterine bleeding compared with histopathology Hospital outpatient José Carrasco Arteaga, from October 2010 to complete the sample. Methods: 250 patients with abnormaluterine bleeding valuated by the specialist and dispatched to imagenology valuation. There were performed hysterosonography and histopathology analysis to all patients. Sensitivity, specificity, predictive positive values and negative values were calculated. Results: The study sample had the following gynecological characteristics: the mean age was 48.69 years old, the average age of onset of menarche was 12.89 years while the average age for menopause presentation was 44.17 years, and abnormal bleeding occurred most frequently were hypermenorrhea with 36.4 %. Hysterosonography revealed polyps as the main pathology founded (26.8%). Meanwhile the histopathology revealed hyperplasia endometrial as the main diagnostic (24.8%). Hysterosonography sensitivity to diagnose endometrial pathologies were 90.08% (83.31 – 94.40) and the specificity 94.79% (IC: 65.85 – 82.10 Conclusions: Hysterosonography showed high sensitivity and specificity for the diagnosis of endometrial polyps, endometrial hyperplasia and normal endometrium. KEYWORDS: HYSTEROSONOGRAPHY, HISTOPATHOLOGY, PATHOLOGY / CLASSIFICATION, SENSITIVITY AND SPECIFICITY, HOSPITAL JOSE CARRASCO ARTEAGA ECUADORIAN SOCIAL SECURITY INSTITUTE. Especialista en Imagenología Cuenca

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.