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How sea level rise (SLR) alters carbon (C) dynamics in tidal salt marsh soils is unresolved. Changes in hydrodynamics could influence organo-mineral associations, influencing dissolved organic carbon (DOC) fluxes. As SLR increases the duration of inundation, we hypothesize that lateral DOC export will increase due to reductive dissolution of C-bearing iron (Fe) oxides, destabilizing soil C stocks and influencing greenhouse gas emissions. To test this, soil cores (0–8 cm depth) were collected from the high marsh of a temperate salt marsh that currently experiences changes in water level and soil redox oscillation due to spring-neap tides. Mesocosms experimentally simulated SLR by continuously inundating high marsh soils and were compared to mesocosms with Control conditions, where the water level oscillated on a spring-neap cycle. Porewater DOC, lateral DOC, and porewater reduced Fe (Fe2+) concentrations were significantly higher in SLR treatments (1.7 ± 0.5 mM, 0.63 ± 0.14 mM, and 0.15 ± 0.11 mM, respectively) than Control treatments (1.2 ± 0.35 mM, 0.56 ± 0.15 mM, and 0.08 ± 01 mM, respectively Solid phase analysis with Fe extended X-ray absorption fine-structure spectroscopy further revealed that SLR led to > 3 times less Fe oxide-C coprecipitates than Control conditions In addition, the overall global warming potential (GWP) decreased under SLR due to suppressed CO2 emissions. Our data suggest that SLR may increase lateral C export of current C stocks by dissolving C-bearing Fe oxides but decrease the overall GWP from emissions of soil trace gases. These findings have implications for understanding the fate of SOC dynamics under future SLR scenarios. [ABSTRACT FROM AUTHOR]

Background and Aim: Canine vector-borne diseases represent an important issue for the welfare and health of animals, but also have great zoonotic potential. These diseases are caused by bacteria, nematodes such as filariae, and other parasites such as Leishmania spp. Given the difficulty in differentiating common microfilariae in dogs by microscopy and serological methods, molecular techniques such as polymerase chain reaction (PCR) and sequencing should be valuable for reaching a reliable diagnosis. This study aimed to use microscopy and PCR to identify the microfilarial species in dogs from Valle del Cauca, Colombia, and a possible association with Leishmania infantum parasites. Materials and Methods: This study was conducted on 270 dogs from Pradera and Florida municipalities. Microfilariae were detected in dogs by optical microscopy and amplification with 5.8S-ITS2-28S. Species identification was achieved through the amplification of the gene cytochrome oxidase I (COX1). Results: Microscopic detection of microfilariae was possible in 4.81% (13/270) of the dogs. In addition, by PCR of COX1 and Sanger sequencing of ITS2, Acanthocheilonema reconditum was identified as the circulating microfilarial species in 12 dogs, coinfecting with the species L. infantum (Leishmania donovani complex). Conclusion: To the best of our knowledge, this is the first report on A. reconditum and L. infantum mixed infection in dogs in Colombia, particularly in the Valle del Cauca. [ABSTRACT FROM AUTHOR]

Field-measured soil respiration (RS , the soil-to-atmosphere CO2 flux) observations were compiled into a global soil respiration database (SRDB) a decade ago, a resource that has been widely used by the biogeochemistry community to advance our understanding of RS dynamics. Novel carbon cycle science questions require updated and augmented global information with better interoperability among datasets. Here, we restructured and updated the global RS database to version SRDB-V5. The updated version has all previous fields revised for consistency and simplicity, and it has several new fields to include ancillary information (e.g., RS measurement time, collar insertion depth, collar area). The new SRDB-V5 includes published papers through 2017 (800 independent studies), where total observations increased from 6633 in SRDB-V4 to 10 366 in SRDB-V5. The SRDB-V5 features more RS data published in the Russian and Chinese scientific literature and has an improved global spatio-temporal coverage and improved global climate space representation. We also restructured the database so that it has stronger interoperability with other datasets related to carbon cycle science. For instance, linking SRDB-V5 with an hourly timescale global soil respiration database (HGRsD) and a community database for continuous soil respiration (COSORE) enables researchers to explore new questions. The updated SRDB-V5 aims to be a data framework for the scientific community to share seasonal to annual field RS measurements, and it provides opportunities for the biogeochemistry community to better understand the spatial and temporal variability in RS , its components, and the overall carbon cycle. The database can be downloaded at https://github.com/bpbond/srdb and will be made available in the Oak Ridge National Laboratory's Distributed Active Archive Center (ORNL DAAC). All data and code to reproduce the results in this study can be found at 10.5281/zenodo.3876443 (Jian and Bond-Lamberty, 2020). [ABSTRACT FROM AUTHOR]

A data-driven method is presented for improving sampling designs from times series (1D approach) or spatial arrays (2D approach) of digital information. We present the autocorrelated conditioned Latin Hypercube Sampling (acLHS). This method combines a conditioned Latin Hypercube (cLHS) to obtain a representative sample of the joint probability distribution function and an autocorrelation model to reproduce the spatial or temporal dependency function (i.e., temporal or spatial variability). The acLHS method was tested with two case studies using data of soil CO 2 efflux (i.e., the CO 2 flux from soils to the atmosphere known as soil respiration) that are useful for carbon cycle science. First, we used data representing a time series (1D approach), and then spatial data (2D approach) across the conterminous United States (CONUS). Results show that acLHS was more efficient than other sampling methods (i.e., fixed sampling, cLHS) as it better reproduced the joint probability distribution and the temporal or spatial variability of the variable of interest. Finally, we use a Bernstein copula-based stochastic co-simulation method (BCSCS) and demonstrated that the acLHS reduces modeling prediction errors compared with other methods. The acLHS is a flexible method that can be applied to any variable of interest as a time series (1D approach) or as a spatial format (2D approach). • A geostatistical sampling method to improve representativeness of samples. • Implementation works for time series (1D) and spatial information (2D). • The method improves accuracy and precision for prediction purposes. [ABSTRACT FROM AUTHOR]

Field-measured soil respiration (RS, the soil-to-atmosphere CO2 flux) observations were compiled into a global soil respiration database (SRDB) a decade ago, a resource that has been widely used by the biogeochemistry community to advance our understanding of RS dynamics. Novel carbon cycle sciences questions require updated and augmented global information with better interoperability among datasets. Here, we restructured and updated the global RS database to version SRDB-V5. The updated version has all previous fields revised for consistency and simplicity, and it has several new fields to include ancillary information (e.g., RS measurement time, collar insertion depth, collar area). The new SRDB-V5 includes published papers through 2017 (800 independent studies) where total observations increased from 6633 in SRDB-V4 to 10366 in SRDB-V5. The SRDB-V5 features more RS data published in Russian and Chinese scientific literature, has an improved global spatio-temporal coverage, and improved global climate-space representation. We also restructured the database so that it has stronger interoperability with other datasets related to carbon-cycle science. For instance, linking SRDB-V5 with an hourly timescale global soil respiration database (HGRsD) and an open community database for continuous soil respiration and other chamber flux data (COSORE) enables researchers to explore new questions. The updated SRDB-V5 aims to be a data framework for the scientific community to share seasonal to annual field RS measurements, and it provides opportunities for the biogeochemistry community to better understand the spatial and temporal variability of RS, its components, and the overall carbon cycle. The database can be downloaded at https://github.com/bpbond/srdb and ORNL DAAC [Submitted]. All data and code to reproduce the results in this study can be found at: Jian, Jinshi, Bond-Lamberty, Ben. (2020). jinshijian/ESSD: SRDB-V5 first release (Version v1.0.0) [Data set]. Zenodo. http://doi.org/10.5281/zenodo.3876443. [ABSTRACT FROM AUTHOR]

Although the application of agro-industrial effluents on soil is an important practice of environmental management in the industry, this practice can cause impacts on soil microbiology due to the nutrient load and other components present in this waste. Thus, the objective of this study was to evaluate and select relevant articles, involving studies of factors that may influence the amount of biomass in the soil, comparing methodology and progress in studies with this theme. For this, articles indexed in three electronic databases were used: Web of Science, Scopus and Scielo. From these databases, 18 articles related to the topic were selected, all published between 2005 and 2018. For the total of selected scientific studies, 11 have methodologies related to the scope of the study and 7 reinforce the theoretical basis in the elaboration and complementation of the study. It was observed that the main articles were published in the English language, mainly in studies related to the Scopus and Web of Science bases and the most recurrent methods were titrimetric and spectrophotogrammetric methods. It is also concluded that the majority of the studies analyzed relate to microbial biomass alteration of the soil under influence of effluent disposal, as well as a variation of these communities as a function of soil cover. [ABSTRACT FROM AUTHOR]

Annual soil moisture estimates are useful to characterize trends in the climate system, in the capacity of soils to retain water and for predicting land and atmosphere interactions. The main source of soil moisture spatial information across large areas (e.g., continents) is satellite-based microwave remote sensing. However, satellite soil moisture datasets have coarse spatial resolution (e.g., 25–50 km grids); and large areas from regional-to-global scales have spatial information gaps. We provide an alternative approach to predict soil moisture spatial patterns (and associated uncertainty) with higher spatial resolution across areas where no information is otherwise available. This approach relies on geomorphometry derived terrain parameters and machine learning models to improve the statistical accuracy and the spatial resolution (from 27km to 1km grids) of satellite soil moisture information across the conterminous United States on an annual basis (1991–2016). We derived 15 primary and secondary terrain parameters from a digital elevation model. We trained a machine learning algorithm (i.e., kernel weighted nearest neighbors) for each year. Terrain parameters were used as predictors and annual satellite soil moisture estimates were used to train the models. The explained variance for all models-years was >70% (10-fold cross-validation). The 1km soil moisture grids (compared to the original satellite soil moisture estimates) had higher correlations (improving from r2 = 0.1 to r2 = 0.46) and lower bias (improving from 0.062 to 0.057 m3/m3) with field soil moisture observations from the North American Soil Moisture Database (n = 668 locations with available data between 1991–2013; 0-5cm depth). We conclude that the fusion of geomorphometry methods and satellite soil moisture estimates is useful to increase the spatial resolution and accuracy of satellite-derived soil moisture. This approach can be applied to other satellite-derived soil moisture estimates and regions across the world. [ABSTRACT FROM AUTHOR]

• Proximal remote sensing tools can be used for estimating gross primary productivity. • The most relevant electromagnetic regions were ∼550 nm and ∼710 nm. • Daily gross primary productivity was related to Plant Senescence Reflectance Index (PSRI) and the Greenness Index (GCC). • Sun Induced Fluorescence (SIF) was not a good predictor for GPP. Salt marshes are highly productive ecosystems relevant for Blue Carbon assessments, but information for estimating gross primary productivity (GPP) from proximal remote sensing (PRS) is limited. Temperate salt marshes have seasonal canopy structure and metabolism changes, defining different canopy phenological phases, GPP rates, and spectral reflectance. We combined multi-annual PRS data (i.e., PhenoCam, discrete hyperspectral measurements, and automated spectral reflectance sensors) with GPP derived from eddy covariance. We tested the performance of empirical models to predict GPP from 12 common vegetation indices (VIs; e.g., NDVI, EVI, PSRI, GCC), Sun-Induced Fluorescence (SIF), and reflectance from different areas of the electromagnetic spectrum (i.e., VIS-IR, RedEdge, IR, and SIF) across the annual cycle and canopy phenological phases (i.e., Greenup, Maturity, Senescence, and Dormancy). Plant Senescence Reflectance Index (PSRI) from hyperspectral data and the Greenness Index (GCC) from PhenoCam, showed the strongest relationship with daily GPP across the annual cycle and within phenological phases (r2=0.30–0.92). Information from the visible-infrared electromagnetic region (VIS-IR) coupled with a partial least square approach (PLSR) showed the highest data-model agreement with GPP, mainly because of its relevance to respond to physiological and structural changes in the canopy, compared with indices (e.g., GCC) that particularly react to changes in the greenness of the canopy. The most relevant electromagnetic regions to model GPP were ∼550 nm and ∼710 nm. Canopy phenological phases impose challenges for modeling GPP with VIs and the PLSR approach, particularly during Maturity, Senescence, and Dormancy. As more eddy covariance sites are established in salt marshes, the application of PRS can be widely tested. Our results highlight the potential to use canopy reflectance from the visible spectrum region for modeling annual GPP in salt marshes as an example of advances within the AmeriFlux network. [ABSTRACT FROM AUTHOR]

This article carries out an academic exercise around the public policy for primary and secondary education that has been implemented by the Republic for over 200 years. It focuses on the variables of objectives, coverage and quality, which are examined from primary and secondary government sources and public figures interested in the subject. Under such policy, education was intended to reach the largest possible number of people and to be solid, relevant, and in tune with the cultural, social and ideological dynamics that characterized a liberal, democratic nation entering capitalism. The explanation for all this historical path is divided into three parts. The first one deals with the independence period between 1810-1821, highlighting the enormous effort made by enlightened Criollos to organize the foundations of an educational system amid the political instability of the time. The second part takes place between the enactment of a law on August 6, 1821 and Decree 429 of January 20, 1893, conceived from the search for the appropriate structural formula to build a useful quality education. The third and last part covers the 20th century, from Law 39 of 1903 until the promulgation of Law 115 of 1994 and its effects to this day. [ABSTRACT FROM AUTHOR]

Tree stems exchange carbon dioxide, methane, and nitrous oxide with the atmosphere. The biophysical mechanisms controlling these fluxes are not fully understood, and consequently are not included in process-based models. We highlight advances and opportunities that will allow quantification of the role of these plant structures in the local-to-global balance of greenhouse gases (GHGs). [ABSTRACT FROM AUTHOR]

Forest soils are an important component of CO2 and CH4 fluxes at the global scale, but the magnitude of these fluxes varies greatly in space and time within a landscape. Understanding the spatial and temporal distributions of these fluxes across complex landscapes remains a major challenge for researchers and land managers alike. We investigated the spatiotemporal variability of soil-atmosphere CO2 and CH4 fluxes and the relationships of these fluxes to chemical and physical soil properties distributed across a topographically-heterogeneous landscape. Soil CO2 and CH4 fluxes were measured along with soil temperature, moisture, bulk density, texture, carbon, sorption capacity, and dissolved organic matter quality over 2 years along hillslope transects spanning valley bottom, transition zone, and upland landscape positions in a temperate forest watershed. Transition zone soil CO2 efflux was 54-160% higher than low-lying valley bottoms, and 15-54% higher than uplands. Net seasonal CH4 uptake was 58-150% higher in transition zone soils than in uplands, while valley bottoms were occasionally large net sources (up to 19 nmol CH4 m−2 s−1). Soil CO2 efflux and net CH4 uptake were both positively associated with seasonal temperature, and were highest in soils with relatively high carbon and clay content, and relatively low bulk density, moisture, and sorption capacity. We concluded that: (1) transition zone soils act as landscape hotspots for net CH4 uptake in addition to CO2 efflux, and (2) that this spatial distribution is more consistent across seasons for net CH4 uptake than for CO2 efflux. [ABSTRACT FROM AUTHOR]

Incorporation of silica-rich rice husk residue into flooded paddy soil decreases arsenic uptake by rice. However, the impact of this practice on soil greenhouse gas (GHG) emissions and elemental cycling is unresolved particularly as amended soils experience recurrent flooding and drying cycles. We evaluated the impact of pre-incubated silica-rich rice residue incorporation to soils on pore water chemistry and soil GHG fluxes (i.e., CO 2 , CH 4 , N 2 O) over a flooding and drying cycle typical of flooded rice cultivation. Soils pre-incubated with rice husk had 4-fold higher pore water Si than control and 2-fold higher than soils pre-incubated with rice straw, whereas the pore water As and Fe concentrations in soils amended with pre-incubated straw and husk were unexpectedly similar (maximum ~ 0.85 μM and ~ 450 μM levels, respectively). Pre-incubation of residues did not affect Si but did affect the pore water levels of As and Fe compared to previous studies using fresh residues where straw amended soils had higher As and Fe in pore water. The global warming potential (GWP) of soil GHG emissions decreased in the order straw (612 ± 76 g CO 2 -eq m − 2 ) > husk (367 ± 42 g CO 2 -eq m − 2 ) > ashed husk = ashed straw (251 ± 26 and 278 ± 28 g CO 2 -eq m − 2 ) > control (186 ± 23 g CO 2 -eq m − 2 ). The GWP increase due to pre-incubated straw amendment was due to: a) larger N 2 O fluxes during re-flooding; b) smaller contributions from larger CH 4 fluxes during flooded periods; and c) higher CH 4 and CO 2 fluxes at the onset of drainage. In contrast, the GWP of the husk amendment was dominated by CO 2 and CH 4 emissions during flooded and drainage periods, while ashed amendments increased CO 2 emissions particularly during drainage. This experiment shows that ashed residues and husk addition minimizes GWP of flooded soils and enhances pore water Si compared to straw addition even after pre-incubation. [ABSTRACT FROM AUTHOR]

There is an increasing need for approaches to determine reference emission levels and implement policies to address the objectives of Reducing Emissions from Deforestation and Forest Degradation, plus improving forest management, carbon stock enhancement and conservation (REDD+). Important aspects of approaching emissions reductions include coordination and sharing of technology, data, protocols and experiences within and among countries to maximize resources and apply knowledge to build robust monitoring, reporting and verification (MRV) systems. We propose that enhancing the multiple facets of interoperability could facilitate implementation of REDD+ programs and actions. For this case, interoperability is a collective effort with the ultimate goal of sharing and using information to produce knowledge and apply knowledge gained, by removing conceptual, technological, organizational and cultural barriers. These efforts must come from various actors and institutions, including government ministries/agencies, scientific community, landowners, civil society groups and businesses. Here, we review the case of Mexico as an example of evolving interoperability in developing countries, and highlight challenges and opportunities for implementation of REDD+. Country-specific actions toward a higher degree of interoperability can be complex, expensive and even risky. These efforts provide leadership opportunities and will facilitate science–policy integration for implementation of REDD+, particularly in developing counties. [ABSTRACT FROM AUTHOR]

The present article outlines certain observations to consider when embarking on the exercise of an empirical-historical research that leads to the knowledge of the process of elaboration of cultural identity, in the dimension of the social identity that makes a professional group look like and be seen as something unique and cohesive, exercise organized in four sections, the first of them of historiographic nature and the other three of strict conceptual order. On the first of them, it is addressed the dilemma of delimiting the space in which the object of study moves; in relation to the other three, it was decided to relate the research with the following concepts: modernization, profession and social identity; topics whose articulation will depend on the analysis of the events, milestones and dynamics of the annotated period. [ABSTRACT FROM AUTHOR]

In this paper, we present an explanation for the problem of the abstract versions of Peter Wason‘s four-card selection task: modest subjects‘ results when they are confronted with these tasks. Our explanation poses that individuals do not comprehend the task rule as a conditional sentence, but as a biconditional one, causing that subjects do not choose the correct cards. Santamaría presented an objection for any approach that suggests a biconditional interpretation in the task selection. In this work, we discuss this objection based on the apparent primacy of a logical rule in human reasoning: modus ponens. Additionally, we present a study based on Socratic dialogue seminars with a tutorial style, developed by us, to check whether our explanation is viable or not, and discuss the results achieved. [ABSTRACT FROM AUTHOR]

This article aims to reflect on the general trajectory followed by the public and private discourse that identified factors both internal and external that came together in the absence of an elementary/secondary education of high quality between the formation of the Gran Colombia and the end of the period of conservative rule in 1930. It describes and analyzes the unidimensionality of the public discourse in the nineteenth century, focusing on the anachronistic permanence of the method of rote learning in classrooms, compared to the multidimensionality of the private speech of the twentieth century, when variables of medical and economic nature were rescued to explain the roots of this phenomenon. [ABSTRACT FROM AUTHOR]

Essential fatty acids should be included in the diet to ensure adequate fish growth. Despite the great number of studies on fatty acid nutrition of fish, there are still several unknowns. The aim of the present study was to investigate fatty acid nutrition of jundiá, a Latin American freshwater catfish. Four diets were formulated containing (i) coconut oil (−C, negative control), (ii) coconut oil + high-docosahexaenoic-acid-fish oil (+C, positive control) and coconut + sunflower + linseed oils at different ratios, producing either (iii) a diet rich in linoleic acid ( LA) (High LA) or 4) a diet low in LA (Low LA). All diets contained significant amounts of saturated fatty acids (at least 57.5% total fatty acids in High LA) and monounsaturated fatty acids (at least 19.1% total fatty acids in −C). Diets were fed to jundiá fingerlings (1.5 g) for 70 days; growth, body composition and liver histology were evaluated. The −C diet, without essential fatty acids, promoted significantly lower fish growth, body fat accumulation and hepatic lipidosis. Fish fed High LA and Low LA diets presented similar growth as fish fed +C diet. These findings suggest that diet formulations for jundiá catfish fingerlings can include only plant oils without negative effect on growth, survival, body composition, fish health or parameters of feed utilization (ingestion rate and protein utilization). [ABSTRACT FROM AUTHOR]

Some land and ocean processes are related through connections (and synoptic-scale teleconnections) to the atmosphere. Synoptic-scale atmospheric (El Niño/Southern Oscillation [ENSO], Pacific Decadal Oscillation [PDO], and North Atlantic Oscillation [NAO]) decadal cycles are known to influence the global terrestrial carbon cycle. Potentially, smaller scale land-ocean connections influenced by coastal upwelling (changes in sea surface temperature) may be important for local-to-regional water-limited ecosystems where plants may benefit from air moisture transported from the ocean to terrestrial ecosystems. Here we use satellite-derived observations to test potential connections between changes in sea surface temperature (SST) in regions with strong coastal upwelling and terrestrial gross primary production (GPP) across the Baja California Peninsula. This region is characterized by an arid/semiarid climate along the southern California Current. We found that SST was correlated with the fraction of photosynthetic active radiation (fPAR; as a proxy for GPP) with lags ranging from 0 to 5 months. In contrast ENSO was not as strongly related with fPAR as SST in these coastal ecosystems. Our results show the importance of local-scale changes in SST during upwelling events, to explain the variability in GPP in coastal, water-limited ecosystems. The response of GPP to SST was spatially-dependent: colder SST in the northern areas increased GPP (likely by influencing fog formation), while warmer SST at the southern areas was associated to higher GPP (as SST is in phase with precipitation patterns). Interannual trends in fPAR are also spatially variable along the Baja California Peninsula with increasing secular trends in subtropical regions, decreasing trends in the most arid region, and no trend in the semi-arid regions. These findings suggest that studies and ecosystem process based models should consider the lateral influence of local-scale ocean processes that could influence coastal ecosystem productivity. [ABSTRACT FROM AUTHOR]

Soil CO2 efflux is the primary source of CO2 emissions from terrestrial ecosystems to the atmosphere. The rates of this flux vary in time and space producing hot moments (sudden temporal high fluxes) and hot spots (spatially defined high fluxes), but these high reaction rates are rarely studied in conjunction with each other. We studied temporal and spatial variation of soil CO2 efflux in a water-limited Mediterranean ecosystem in Baja California, Mexico. Soil CO2 efflux increased 522% during a hot moment after rewetting of soils following dry summer months. Monthly precipitation was the primary driver of the seasonal trend of soil CO2 efflux (including the hot moment) and through changes in soil volumetric water content (VWC) it influenced the relationship between CO2 efflux and soil temperature. Geostatistical analyses showed that the spatial dependence of soil CO2 efflux changed between two contrasting seasons (dry and wet). During the dry season high soil VWC was associated with high soil CO2 efflux, and during the wet season the emergence of a hot spot of soil CO2 efflux was associated with higher root biomass and leaf area index. These results suggest that sampling designs should accommodate for changes in spatial dependence of measured variables. The spatio-temporal relationships identified in this study are arguably different from temperate ecosystems where the majority of soil CO2 efflux research has been done. This study provides evidence of the complexity of the mechanisms controlling the spatio-temporal variability of soil CO2 efflux in water-limited ecosystems. [ABSTRACT FROM AUTHOR]

Keywords: carbon fluxes; heterogeneity; net ecosystem carbon balance; remote sensing; soil carbon EN carbon fluxes heterogeneity net ecosystem carbon balance remote sensing soil carbon 579 582 4 07/10/20 20131201 NES 131201 Proper implementation of reducing emissions from deforestation and forest degradation, plus improving forest management, carbon stock enhancement and conservation (REDD+) requires addressing challenges related to social, technological, ecological and economical issues [[1]]. Deforestation and changes in land use (e.g., changes from forest to agriculture) are relatively easy to detect by analyzing structural and spectral reflectance changes [7]; however, identifying and quantifying forest degradation (i.e., long-term lowering of biomass density within a forest) still remains challenging [[2], [6]]. In addition, forest degradation is potentially related to a nonregulated extraction of forest products (e.g., timber and firewood/charcoal), shifting cultivation, cattle grazing within the forest and low-intensity fires. [Extracted from the article]

High ground-level ozone concentrations are typical of Mediterranean climates. Plant exposure to this oxidant is known to reduce carbon assimilation. Ozone damage has been traditionally measured through manipulative experiments that do not consider long-term exposure and propagate large uncertainty by up-scaling leaf-level observations to ecosystem-level interpretations. We analyzed long-term continuous measurements (>9 site-years at 30 min resolution) of environmental and eco-physiological parameters at three Mediterranean ecosystems: (i) forest site dominated by Pinus ponderosa in the Sierra Mountains in California, USA; (ii) forest site composed of a mixture of Quercus spp. and P. pinea in the Tyrrhenian sea coast near Rome, Italy; and (iii) orchard site of Citrus sinensis cultivated in the California Central Valley, USA. We hypothesized that higher levels of ozone concentration in the atmosphere result in a decrease in carbon assimilation by trees under field conditions. This hypothesis was tested using time series analysis such as wavelet coherence and spectral Granger causality, and complemented with multivariate linear and nonlinear statistical analyses. We found that reduction in carbon assimilation was more related to stomatal ozone deposition than to ozone concentration. The negative effects of ozone occurred within a day of exposure/uptake. Decoupling between carbon assimilation and stomatal aperture increased with the amount of ozone pollution. Up to 12-19% of the carbon assimilation reduction in P. ponderosa and in the Citrus plantation was explained by higher stomatal ozone deposition. In contrast, the Italian site did not show reductions in gross primary productivity either by ozone concentration or stomatal ozone deposition, mainly due to the lower ozone concentrations in the periurban site over the shorter period of investigation. These results highlight the importance of plant adaptation/sensitivity under field conditions, and the importance of continuous long-term measurements to explain ozone damage to real-world forests and calculate metrics for ozone-risk assessment. [ABSTRACT FROM AUTHOR]

Water availability is the dominant control of global terrestrial primary productivity with concurrent effects on evapotranspiration and ecosystem respiration, especially in water-limited ecosystems. Process-oriented ecosystem models are critical tools for understanding land-atmosphere exchanges and for up-scaling this information to regional and global scales. Thus, it is important to understand how ecosystem models simulate ecosystem fluxes under changing weather conditions. Here, we applied both time-series analysis and meta-analysis techniques to study how five ecosystem process-oriented models-simulated gross primary production (GPP), ecosystem respiration (Reco), and evapotranspiration (ET). Ecosystem fluxes were simulated for 3 years at a daily time step from four evergreen and three deciduous Mediterranean oak woodlands (21 site-year measurements; 105 site-year-simulations). Mediterranean ecosystems are important test-beds for studying the interannual dynamics of soil moisture on ecosystem mass and energy exchange as they experience cool, wet winters with hot, dry summers and are typically subject to drought. Results show data-model disagreements at multiple temporal scales for GPP, Reco, and ET at both plant functional types. Overall there was a systematic underestimation of the temporal variation of Reco at both plant functional types at temporal scales between weeks and months, and an overestimation at the yearly scale. Modeled Reco was systematically overestimated during drought for all sites, but daily GPP was systematically underestimated only for deciduous sites during drought. In contrast, daily estimates of ET showed good data-model agreement even during drought conditions. This meta-analysis brings attention to the importance of drought conditions for modeling purposes in representing forest dynamics in water-limited ecosystems. [ABSTRACT FROM AUTHOR]

The aim of the present article is to identify and explain continuities and discontinuities of educational public policy from different conservative governments which were ruling the country during the last three decades of century XX. Furthermore, requirements and directives given and applied by national party over the regeneration period, in particular of the former, the deepening of practical sense in education and their religious character, and from the latter, the exploitation around a renewed spirit of identity and national unity of citizen and democratic inclusion. [ABSTRACT FROM AUTHOR]

Climate models suggest that extreme rainfall events will become more common with increased atmospheric warming. Consequently, changes in the size and frequency of rainfall will influence biophysical drivers that regulate the strength and timing of soil CO2 efflux - a major source of terrestrial carbon flux. We used a rainfall manipulation experiment during the summer monsoon season ( July- September) to vary both the size and frequency of precipitation in an arid grassland 2 years before and 2 years after a lightning-caused wildfire. Soil CO2 efflux rates were always higher under increased rainfall event size than under increased rainfall event frequency, or ambient precipitation. Although fire reduced soil CO2 efflux rates by nearly 70%, the overall responses to rainfall variability were consistent before and after the fire. The overall sensitivity of soil CO2 efflux to temperature ( Q10) converged to 1.4, but this value differed somewhat among treatments especially before the fire. Changes in rainfall patterns resulted in differences in the periodicity of soil CO2 efflux with strong signals at 1, 8, and 30 days. Increased rainfall event size enhanced the synchrony between photosynthetically active radiation and soil CO2 efflux over the growing season before and after fire, suggesting a change in the temporal availability of substrate pools that regulate the temporal dynamics and magnitude of soil CO2 efflux. We conclude that arid grasslands are capable of rapidly increasing and maintaining high soil CO2 efflux rates in response to increased rainfall event size more than increased rainfall event frequency both before and after a fire. Therefore, the amount and pattern of multiple rain pulses over the growing season are crucial for understanding CO2 dynamics in burned and unburned water-limited ecosystems. [ABSTRACT FROM AUTHOR]

Summary [ABSTRACT FROM AUTHOR]

Soil respiration, the flux of CO from the soil to the atmosphere represents a major flux in the global carbon cycle. Our ability to predict this flux remains limited because of multiple controlling mechanisms that interact over different temporal and spatial scales. However, new advances in measurement and analyses present an opportunity for the scientific community to improve the understanding of the mechanisms that regulate soil respiration. In this paper, we address several recent advancements in soil respiration research from experimental measurements and data analysis to new considerations for model-data integration. We focus on the links between the soil-plant-atmosphere continuum at short (i.e., diel) and medium (i.e., seasonal-years) temporal scales. First, we bring attention to the importance of identifying sources of soil CO production and highlight the application of automated soil respiration measurements and isotope approaches. Second, we discuss the need of quality assurance and quality control for applications in time series analysis. Third, we review perspectives about emergent ideas for modeling development and model-data integration for soil respiration research. Finally, we call for stronger interactions between modelers and experimentalists as a way to improve our understanding of soil respiration and overall terrestrial carbon cycling. [ABSTRACT FROM AUTHOR]

Soils play a critical role in the global carbon cycle, yet the biophysical factors regulating soil CO2 dynamics remain unclear. We combined high-frequency in situ observations of fine roots and ectomycorrhizal (EM) fungi with data from multiple soil sensor arrays to examine the biophysical interactions influencing soil CO2 production for one year in a mixed conifer forest. Using structural equation modeling we constructed a hypothesized model to test for causal interactions among environmental factors, biotic factors, and soil CO2 dynamics throughout the soil profile. According to our model, seasonal variation in CO2 production was significantly influenced by EM rhizomorph production, soil temperature, and soil moisture. Fine root production, on the other hand, did not appear to significantly influence soil CO2 production. The relationship between EM rhizomorph production and soil CO2 production was also supported by a zero temporal lag between these two measurements in a cross-correlation analysis. In contrast, CO2 production increased before fine root production suggesting that these two measurements were decoupled in time. Results from this study highlight the need to better understand differences in carbon allocation between plant roots and EM fungi to improve our predictions of soil carbon dynamics under global climate change. [ABSTRACT FROM AUTHOR]

Ecosystem processes are influenced by weather and climatic perturbations at multiple temporal scales with a large range of amplitudes and phases. Technological advances of automated biometeorological measurements provide the opportunity to apply spectral methods on continuous time series to identify differences in amplitudes and phases and relationships with weather variation. Here we used wavelet coherence analysis to study the temporal covariance between soil CO2 production and soil temperature, soil moisture, and photosynthetically active radiation (PAR). Continuous (hourly average) data were acquired over 2 years among three vegetation types in a semiarid mixed temperate forest. We showed that soil temperature and soil moisture influence soil CO2 production differently at multiple periods (e.g. hours, days, weeks, months, years), especially after rain pulse events. Our results provide information about the periodicity of soil CO2 production among vegetation types, and provide insights about processes controlling CO2 production through the study of phase relationships between two time series (e.g. soil CO2 production and PAR). We tested the performance of empirical models of soil CO2 production using the continuous wavelet transform. These models, built around soil temperature and moisture, failed at multiple periods across the measured dates, suggesting that empirical models should include other factors that regulate soil CO2 production at different temporal scales. Our results add a new dimension for the analysis of continuous time series of biometeorological measurements and model testing, which will prove useful for analysis of increasing sensor data obtained by environmental networks. [ABSTRACT FROM AUTHOR]

• Here, we explore how interannual variations in environmental factors (i.e. temperature, precipitation and light) influence CO2 fluxes (gross primary production and ecosystem respiration) in terrestrial ecosystems classified by vegetation type and the mycorrhizal type of dominant plants (arbuscular mycorrhizal (AM) or ectomycorrhizal (EM)). • We combined 236 site-year measurements of terrestrial ecosystem CO2 fluxes and environmental factors from 50 eddy-covariance flux tower sites with information about climate, vegetation type and dominant plant species. • Across large geographical distances, interannual variations in ecosystem CO2 fluxes for EM-dominated sites were primarily controlled by interannual variations in mean annual temperature. By contrast, interannual variations in ecosystem CO2 fluxes at AM-dominated sites were primarily controlled by interannual variations in precipitation. • This study represents the first large-scale assessment of terrestrial CO2 fluxes in multiple vegetation types classified according to dominant mycorrhizal association. Our results support and complement the hypothesis that bioclimatic conditions influence the distribution of AM and EM systems across large geographical distances, which leads to important differences in the major climatic factors controlling ecosystem CO2 fluxes. [ABSTRACT FROM AUTHOR]

To better understand how management and restoration practices influence the response of terrestrial ecosystems to large-scale disturbances, it is critical to study above- and belowground effects. In this study, we examined the immediate effect of a major hurricane on aboveground forest structure, arbuscular mycorrhizae (AM) and belowground carbon pools in experimentally thinned plots in a tropical forest. The hurricane occurred five years after a thinning treatment, when thinned plots had similar aboveground carbon stocks but different forest structure compared to control plots. Thinned plots had more large diameter (>10 cm) trees compared to the control plots, which were characterized by a higher density of small diameter (<10 cm) trees. Despite pre-hurricane differences in forest structure, there were no significant differences between treatments in changes of canopy openness or number of affected trees following the hurricane. Thinned plots had larger belowground carbon pools than the controls plots before the hurricane, and these differences remained after the hurricane despite rapid decomposition of organic matter rich in nitrogen. There were no pre-hurricane differences in AM fungal spores or total AM root colonization. The hurricane reduced AM sporulation by nearly 50% in both treatments, yet we observed a significant increase in AM root colonization after the hurricane with greater AM colonization in the thinned plots. Hurricanes have well-known visible aboveground effects, but here we showed that less visible belowground effects are influenced by forest management and may play an important role in forest recovery. [ABSTRACT FROM AUTHOR]

• In this study, we explore how a hurricane disturbance influenced carbon allocation for the production of new fine roots. • Before and after a hurricane, we measured the age of carbon (time since fixation from the atmosphere) in fine root structural tissues using natural abundance radiocarbon (14C) measured by accelerator mass spectrometry. Roots were sampled from five seasonally dry tropical forests ranging in age from 6 yr to a mature forest. • Structural carbon in combined live + dead roots picked from soil cores sampled 1 month before the hurricane had mean ages ranging from 4 to 11 yr, whereas live roots alone had ages of 1–2 yr. Structural carbon in new live fine roots produced over a period lasting from 3 wk before the hurricane to 2 months after the event had mean ages of between 2 and 10 yr. • Contrary to expectations, our results showed that plants allocate long-lived storage carbon pools to the production of new fine roots after canopy defoliation and root mortality. The age of the carbon allocated for new roots increased with forest age and forest above-ground biomass, suggesting an adaptation of plants to survive and recover from severe disturbances. [ABSTRACT FROM AUTHOR]

We establish the existence of two weak coupling regime effective dynamics for an open quantum system of repeated interactions (vanishing strength and individual interaction duration, respectively). This generalizes known results (Attal and Joye in J. Stat. Phys. 126:1241–1283, ) in that the von Neumann algebras describing the system and the chain element may not be of finite type. Then (but now assuming that the small system is of finite type), we prove that both effective dynamics capture the long-term behavior of the system: existence of a unique asymptotic state for them implies the same property for the respective exact dynamics—provided that the perturbation parameter is sufficiently small. The zero-th order term in a power series expansion in the perturbation parameter of such an asymptotic state is given by the asymptotic state of the effective dynamics. We conclude by working out the case in which the small system and the chain element are spins. [ABSTRACT FROM AUTHOR]

• Characterization of spatial and temporal variation of soil respiration coupled with fine root and rhizomorph dynamics is necessary to understand the mechanisms that regulate soil respiration. • A dense wireless network array of soil CO2 sensors in combination with minirhizotron tubes was used to continuously measure soil respiration over 1 yr in a mixed conifer forest in California, USA, in two adjacent areas with different vegetation types: an area with woody vegetation (Wv) and an area with scattered herbaceous vegetation (Hv). • Annual soil respiration rates and the lengths of fine roots and rhizomorphs were greater at Wv than at Hv. Soil respiration was positively correlated with fine roots and rhizomorphs at Wv but only with fine roots at Hv. Diel and seasonal soil respiration patterns were decoupled with soil temperature at Wv but not at Hv. When decoupled, higher soil respiration rates were observed at increasing temperatures, demonstrating a hysteresis effect. The diel hysteresis at Wv was explained by including the temperature-dependent component of soil respiration and the variation dependent on photosynthetically active radiation. • The results show that vegetation type and fine root and rhizomorph dynamics influence soil respiration in addition to changes in light, temperature and moisture. [ABSTRACT FROM AUTHOR]

The jundiá ( Rhamdia quelen) is a siluriform with great potential for aquaculture in South America. Fish oil is a raw material in diets for fish. However, the fisheries that provide fish oil have reached their limit of sustainability. Thus, the use of alternative sources for this ingredient is primordial. The aim of this study was to evaluate the performance and body composition of the jundiá fed with different sources of the vegetable oils. Jundiá (1.0±0.2 g) were fed for 31 days with five isonitrogenous (37%) and isoenergetic (19 kJ g−1) diets, in which the following oils were added: 50 g kg−1 corn oil (CO), 50 g kg−1 fish oil (FO), 50 g kg−1 linseed oil (LO), 33.4 g kg−1 fish oil and 16.7 g kg−1 linseed oil (1/3LO), 16.7 g kg−1 fish oil and 33.4 g kg−1 linseed oil (2/3LO). The performance did not show differences between treatments. The final fatty acid profile and n-3/n-6 ratio of the fish were highly influenced by the diet. Fish-fed diets with linseed and/or fish oil showed superior n-3/n-6 ratios to the minimal recommended by the World Health Organization; whereas fish fed diets with corn oil showed an inferior value. Albeit in the present study the commercial size of fish was not attained, these results show a clear tendency. The desaturation/elongation capacity was evidenced, in this species, for the first time. Linseed oil can be utilized as a substitute for fish oil in diets of jundiá without affecting their performance and for producing good-quality fish. However, more studies are necessary to confirm these results for commercial size. [ABSTRACT FROM AUTHOR]

Seasonally dry tropical forests (SDTF) are a widely distributed vegetation type in the tropics, characterized by seasonal rainfall with several months of drought when they are subject to fire. This study is one of the first attempts to quantify above- and belowground biomass (AGB and BGB) and above- and belowground carbon (AGC and BGC) pools to calculate their recovery after fire, using a chronosequence approach (six forests that ranged form 1 to 29 years after fire and mature forest). We quantified AGB and AGC pools of trees, lianas, palms, and seedlings, and BGB and BGC pools (Oi, Oe, Oa soil horizons, and fine roots). Total AGC ranged from 0.05 to nearly 72 Mg C ha−1, BGC from 21.6 to nearly 85 Mg C ha−1, and total ecosystem carbon from 21.7 to 153.5 Mg C ha−1; all these pools increased with forest age. Nearly 50% of the total ecosystem carbon was stored in the Oa horizon of mature forests, and up to 90% was stored in the Oa-horizon of early successional SDTF stands. The soils were shallow with a depth of <20 cm at the study site. To recover values similar to mature forests, BGC and BGB required <19 years with accumulation rates greater than 20 Mg C ha−1 yr−1, while AGB required 80 years with accumulation rates nearly 2.5 Mg C ha−1 yr−1. Total ecosystem biomass and carbon required 70 and 50 years, respectively, to recover values similar to mature forests. When belowground pools are not included in the calculation of total ecosystem biomass or carbon recovery, we estimated an overestimation of 10 and 30 years, respectively. [ABSTRACT FROM AUTHOR]

Soil organisms undertake every major ecosystem process, from primary production to decomposition to carbon sequestration, and those processes they catalyze have a bearing on the management of issues from agriculture to global climate change. Nonetheless, until recently, research to measure the dynamics of microscopic organisms living belowground has largely been limited to infrequent field sampling and laboratory extrapolation. Now, however, new sensor technologies can measure and monitor soil organisms and processes at rapid and continuous temporal scales. In this article, we describe these technologies and how they can be arrayed for an integrated view of soil dynamics. [ABSTRACT FROM AUTHOR]

Acetylene reduction assay (ARA) was applied to determine the rate of nitrogen fixation by cyanoprokaryotes in a wetland in El Eden Ecological Reserve. The data obtained throughout a hydrological cycle showed both an increase of fixed nitrogen during wet periods and an important amount of nitrogen rate produced by non-heterocytic filamentous and colonial blue-green algae. The results support the importance of the contribution of algae to nutrient balance in the wetland ecosystem. [ABSTRACT FROM AUTHOR]

• Plant phenological phases influence NEE and CH 4 exchange • CO 2 and CH 4 emissions during senescence and dormancy overshadowed annual carbon uptakes • Light availability partially explained NEE variability • Lower water table level increased ecosystem-scale CH 4 emissions • This temperate tidal salt marsh was a net source of carbon to the atmosphere Salt marshes are large carbon reservoirs as part of blue carbon ecosystems. Unfortunately, there is limited information about the net ecosystem (NEE) and methane (CH 4) exchange between salt marshes and the atmosphere to fully understand their carbon dynamics. We tested the influence of biophysical drivers by plant phenological phases (i.e., Greenup, Maturity, Senescence and Dormancy) on NEE and CH 4 exchange in a grass-dominated temperate tidal salt marsh. We used three years of data derived from eddy covariance, PhenoCam (to measure vegetation phenology), and ancillary meteorological and water/soil variables. Overall, NEE showed significant differences among all phenological phases (p < 0.05), while CH 4 exchange had significant differences among all phases except for Greenup and Dormancy. Net CO 2 uptake was higher across Maturity (-61 g C-CO 2 m2), while CO 2 emissions were higher during Dormancy (182 g C-CO 2 m2). The lower but constant CO 2 emissions during Dormancy overshadowed the CO 2 uptake during the growing season and contributed to >72% of the annual CO 2 emissions in this ecosystem. Net CH 4 emissions were higher during Maturity (3.7 g C-CH 4 m2) and Senescence (4.2 g C-CH 4 m2). Photosynthetically active radiation (PAR) substantially influenced (r2 > 0.57) daytime NEE across phenological phases, but a combination of variables including water table level (WTL), water temperature and atmospheric pressure were relevant to explain CH 4 exchange. The study site was an overall net carbon source to the atmosphere with annual emissions of 13-201 g C-CO 2 m−2yr−1 and 8.5-15.2 g C-CH 4 m−2yr−1. Our findings provide insights on: a) the role of plant phenological phases on ecosystem-scale CO 2 and CH 4 fluxes; b) challenges for modeling ecosystem-scale CO 2 and CH 4 fluxes in salt marshes; and c) the potential net loss of carbon to the atmosphere that should be considered for carbon management and accounting in these ecosystems. [ABSTRACT FROM AUTHOR]

Objective: To investigate the effect of pre and postnatal exposure to a glyphosate-based herbicide on glucose metabolism and liver histology in adult F1 mice offspring. Methods: Female mice (C57Bl/6) received 0.5% of glyphosate (Roundup Original DI®) in drinking water or purified water (Glyphosate Group and Control Group respectively) during pregnancy and lactation. Offspring (F1) were submitted to glucose and insulin tolerance tests and euthanized on postnatal day 150. Body and plasma parameters, and liver histology were analyzed. Results: Exposure to glyphosate reduced maternal body weight gain during pregnancy and lactation, with no impacts on litter size. Pre and postnatal exposure to glyphosate did not affect body parameters but increased glucose tolerance on postnatal day 60. In spite of glucose tolerance normalization by postnatal day 143, this effect was associated with higher insulin sensitivity relative to mice in the Control-F1 Group. Mice in the Glyphosate-F1 Group had mild and moderate lobular inflammation in the liver. Conclusion: Maternal exposure to glyphosate affected insulin sensitivity and caused hepatic inflammation in adult F1 mice offspring. [ABSTRACT FROM AUTHOR]

Piscirickettsia salmonis is the pathogen that most affects the salmon industry in Chile. Large quantities of antibiotics have been used to control it. In search of alternatives, we have developed [Cu(NN1)2]ClO4 where NN1 = 6-((quinolin-2-ylmethylene)amino)-2H-chromen-2-one. The antibacterial capacity of [Cu(NN1)2]ClO4 was determined. Subsequently, the effect of the administration of [Cu(NN1)2]ClO4 on the growth of S. salar, modulation of the immune system and the intestinal microbiota was studied. Finally, the ability to protect against a challenge with P. salmonis was evaluated. The results obtained showed that the compound has an MIC between 15 and 33.9 μg/mL in four isolates. On the other hand, the compound did not affect the growth of the fish; however, an increase in the transcript levels of IFN-γ, IL-12, IL-1β, CD4, lysozyme and perforin was observed in fish treated with 40 μg/g of fish. Furthermore, modulation of the intestinal microbiota was observed, increasing the genera of beneficial bacteria such as Lactobacillus and Bacillus as well as potential pathogens such as Vibrio and Piscirickettsia. Finally, the treatment increased survival in fish challenged with P. salmonis by more than 60%. These results demonstrate that the compound is capable of protecting fish against P. salmonis, probably by modulating the immune system and the composition of the intestinal microbiota. [ABSTRACT FROM AUTHOR]

• The seasonal climatology Flux Footprint Areas (FFAs) of the TDF were evaluated. • Seasonality, biophysical characteristics, and ENSO were the most influential factors on climatological FFAs in the TDF. • The effects of La Niña phases on seasonal FFAs were the largest for the TDF sites. • FFA in the TDF is sensitive to changes in forest canopy height. Tropical Dry Forest (TDF) is a distinctive ecosystem characterized by distinct seasonal changes, primarily composed of deciduous trees adapted to endure prolonged drought periods. Obtaining ecosystem-scale flux measurements using the Eddy Covariance (EC) technique is crucial for comprehending the spatiotemporal dynamics of interactions between the land and the atmosphere. It is imperative to have information about the variability in the contribution source area of the Flux Footprint Area (FFA) to assess the impact of changing microclimate variables on the EC FFA. In this study, we describe and evaluate the influence of various phases of the El Niño Southern Oscillation (ENSO) on the spatial and temporal climatology of FFA at three EC sites within the TDF of the Santa Rosa National Park-Environmental Super Site (SRNP-EMSS). Our analysis covered the period from 2014 to 2021 on a seasonal scale and employed a 2D model. Our findings indicate that: a) seasonal climatology FFAs exhibit variation across locations and over time due to factors such as forest canopy height, site topography, wind direction, and atmospheric stability conditions; b) FFAs are smaller during dry seasons compared to wet seasons; and c) multiple ENSO phases (cold, neutral, and warm) significantly affect the seasonal climatology of FFAs. Notably, during the moderate La Niña phase (2020/2021), the mean FFA size was 4.20 km2, which was 23.80% larger than the mean FFA during the intense El Niño phase (2015/2016) at 3.20 km2. Additionally, during La Niña phases, FFAs were more asymmetrically distributed around the EC tower compared to El Niño phases, with mean symmetric indices of 0.35 and 0.29, respectively. Finally, the overlap among the three EC climatology FFAs during La Niña phases was 35% greater than that during the El Niño phases. Our study highlights how variations in FFAs can significantly impact intra-annual flux estimates. [ABSTRACT FROM AUTHOR]

Tidal salt marshes produce and emit CH4. Therefore, it is critical to understand the biogeochemical controls that regulate CH4 spatial and temporal dynamics in wetlands. The prevailing paradigm assumes that acetoclastic methanogenesis is the dominant pathway for CH4 production, and higher salinity concentrations inhibit CH4 production in salt marshes. Recent evidence shows that CH4 is produced within salt marshes via methylotrophic methanogenesis, a process not inhibited by sulfate reduction. To further explore this conundrum, we performed measurements of soil–atmosphere CH4 and CO2 fluxes coupled with depth profiles of soil CH4 and CO2 pore water gas concentrations, stable and radioisotopes, pore water chemistry, and microbial community composition to assess CH4 production and fate within a temperate tidal salt marsh. We found unexpectedly high CH4 concentrations up to 145,000 μmol mol−1 positively correlated with S2− (salinity range: 6.6–14.5 ppt). Despite large CH4 production within the soil, soil–atmosphere CH4 fluxes were low but with higher emissions and extreme variability during plant senescence (84.3 ± 684.4 nmol m−2 s−1). CH4 and CO2 within the soil pore water were produced from young carbon, with most Δ14C‐CH4 and Δ14C‐CO2 values at or above modern. We found evidence that CH4 within soils was produced by methylotrophic and hydrogenotrophic methanogenesis. Several pathways exist after CH4 is produced, including diffusion into the atmosphere, CH4 oxidation, and lateral export to adjacent tidal creeks; the latter being the most likely dominant flux. Our findings demonstrate that CH4 production and fluxes are biogeochemically heterogeneous, with multiple processes and pathways that can co‐occur and vary in importance over the year. This study highlights the potential for high CH4 production, the need to understand the underlying biogeochemical controls, and the challenges of evaluating CH4 budgets and blue carbon in salt marshes. [ABSTRACT FROM AUTHOR]

Soil moisture is key for quantifying soil-atmosphere interactions. We provide a soil moisture pattern recognition framework to increase the spatial resolution and fill gaps of the ESA-CCI (European Space Agency-Climate Change Initiative v4.5) soil moisture dataset, which contains more than 40 years of satellite soil moisture global grids with a spatial resolution of ~27 km. We use terrain parameters coupled with bioclimatic and soil type information to predict the finer-grained satellite soil moisture. We assess the impact of terrain parameters on the prediction accuracy by cross-validating the pattern recognition of soil moisture with and without the support of bioclimatic and soil type information. The outcome is a new dataset of gap-free global mean annual soil moisture and uncertainty for 28 years (1991-2018) across 15 km grids. We use independent in situ records from the International Soil Moisture Network (ISMN, n = 13376) and in situ precipitation records (n = 4909) only for evaluating the new dataset. Cross-validated correlation between observed and predicted soil moisture values varies from r = 0.69 to r = 0.87 with root mean squared errors (RMSE, m3/m3) around 0.03 and 0.04. Our soil moisture predictions improve: (a) the correlation with the ISMN (when compared with the original ESA-CCI dataset) from r = 0.30 (RMSE = 0.09, ubRMSE = 0.37) to r = 0.66 (RMSE = 0.05, ubRMSE = 0.18); and (b) the correlation with local precipitation records across boreal (from r = < 0.3 up r = 0.49) or tropical areas (from r = < 0.3 to r = 0.46) which are currently poorly represented in the ISMN. Temporal trends show a decline of global annual soil moisture using: (a) data from the ISMN (-1.5 [-1.8, -1.24] %, (b) associated locations from the original ESA-CCI dataset (-0.87 [-1.54, -0.17] %), (c) associated locations from predictions based on terrain parameters (-0.85 [-1.01, -0.49] %), and (d) associated locations from predictions including bioclimatic and soil type information (-0.68 [-0.91, -0.45] %). We provide a new soil moisture dataset that has no gaps and a finer resolution together with validation methods and a modeling approach that can be applied worldwide (Guevara, et al., 2020, https://doi.org/10.4211/hs.9f981ae4e68b4f529cdd7a5c9013e27e). [ABSTRACT FROM AUTHOR]

Tidal salt marsh ecosystems store copious amounts of carbon (C) within sediments. In order to predict how these C stores may be affected by environmental change, it is critical to assess current CO 2 and CH 4 production and efflux from these ecosystems. Production and efflux of these greenhouse gases (GHGs) are governed by coupled geochemical, hydrological, physical and biological processes in sediments that are sensitive to local conditions, which can result in large spatial and temporal heterogeneity of GHGs dynamics within the ecosystem. To understand how the drivers of GHGs dynamics vary across salt marsh ecosystems, we coupled solid-phase geochemistry to measurements of porewater chemistry (to ∼1 m), CO 2 and CH 4 production in sediments and efflux to the atmosphere in a temperate tidal salt marsh for over one year to capture seasonal patterns within two vegetation zones of the marsh landscape that have distinct biogeochemical and hydrologic conditions: Tall Spartina (TS) and Short Spartina (SS). The SS vegetation zone experienced nearly constant inundation, low redox values (−200 to 200 mV), porewater pH 6–7 that did not vary with depth or time, an enrichment of pyrite and goethite with depth and up to 3 mM porewater sulfide. In contrast, the TS vegetation zone on the natural levee proximal to a tidal channel experienced large water level oscillations due to spring-neap tides that resulted in variable but higher redox values (0–700 mV), porewater pH 6–7 at depth but surface (0–3 cm) as low as 4 in the spring, an enrichment of ferrihydrite and a depletion of pyrite at ∼30 cm, and up to 0.8 mM ferrous Fe in porewater. At 50–56 cm, solid phase analyses (STXM-NEXAFS) revealed differential C speciation between the two vegetation zones, with stronger C-Fe spatial association at TS and stronger C-Ca co-association at SS despite both having similar soil pH of 3–4. These results suggest that soil pH may not be strongly predictive of C-mineral control in flooded marsh sediments. Both vegetation zones showed consistent CO 2 and CH 4 emissions from sediments to the atmosphere throughout the study period with TS having ∼60% higher median CO 2 and SS having ∼55% higher median CH 4 efflux. Using depth profiling, unexpectedly high concentrations of CO 2 (>200 μM) and CH 4 (>200 μM) were observed at depths 50–75 cm at both zones that were higher for SS in these sulfate-rich (up to 17 mM) sediments, which suggests methylotrophic methanogenesis occurs deep within the profile of salt marsh sediments away from the tidal channel. Moreover, if we extrapolate our median depth values of CH 4 and CO 2 to the 5.3 Mha of global salt marshes, this could account for a conservative estimate of ∼70 Gg of unaccounted C stored in gaseous form (i.e., CH 4 and CO 2) in marsh sediments, which should be considered when attempting to understand the current patterns and future responses of carbon dynamics from these ecosystems. [ABSTRACT FROM AUTHOR]

Autumn canopy phenological transitions are increasing in length as a consequence of climate change. Here, we assess how well hyperspectral indices in the visible and near-infrared (NIR) wavelengths predict nitrogen (N) concentrations in lower-canopy leaves in the autumn phenological transition as they are generally understudied in leaf trait research. Using a Bayesian framework, we tested how well published indices are able to predict N concentrations in Fagus grandifolia Ehrh., Liriodendron tulipifera L., and Betula lenta L. from mid-summer through senescence, and how related the indices are to autumn phenological change. No indices were able to determine a trend in differences in N in mid-summer leaves. Indices that included wavelengths in the green and NIR ranges were the first indices able to detect a trend and had among the highest correlations with N concentration in both the last green collection and the senescing collection. Models were unique when indices were fit to data from different phenophases. Indices that focused on only the red edge (i.e., the sharp increase in reflectance between the red and NIR wavelengths) had the strongest explanatory power across the autumn phenological transition, but had less explanatory power for individual collections. These indices, as well as those that have been correlated with chlorophyll (CCI) and carotenoids (PRI), were the strongest descriptors of autumn progression. This study provides insights on challenges and capabilities to monitor a leaf's N concentration throughout and across canopy senescence. [ABSTRACT FROM AUTHOR]

Soil moisture is key for quantifying soil-atmosphere interactions and the ESA-CCI (European Space Agency Climate Change Initiative) provides historical (> 30 years) satellite soil moisture gridded data at the global scale. We evaluate an alternative approach to increase the spatial resolution of the original ESA-CCI soil moisture measurements from 27 km to 15 km grids by coupling machine learning (ML) algorithms with information from digital terrain analysis at the global scale. We modeled mean annual ESA-CCI soil moisture values across 26 years of available data (1991–2016) using a ML based kernel method and multiple terrain parameters (e.g., slope, wetness index) as prediction factors. We used ground information from the International Soil Moisture Network (ISMN, n = 13376) for evaluating soil moisture predictions. We provide gap-free mean annual soil moisture predictions, which increase by nearly 50 % the spatial resolution of ESA-CCI soil moisture product. Our predictions showed a statistical accuracy varying 0.69–0.87 % and 0.04 m³/m³ of cross-validated explained variance and root mean squared error (RMSE). We found no significant differences between the ESA-CCI and our predictions, but we found discrepancy between multiple evaluation metrics (e.g., bias vs efficiency) comparing the ESA-CCI with the ISMN. We found a negative bias (−0.01 to −0.08 m³/m³) between the values of ISMN when comparing with the ESA-CCI and our predictions across the analyzed years. A temporal analysis, using a robust trend detection strategy (i.e., Theil-Sen estimator), suggests a decline of soil moisture at the global scale that is consistent in both gridded datasets and field measurements of soil moisture varying from −0.7[−0.77, −0.62] % in the ESA-CCI product, −0.9[−1.01, −0.8] % in the downscaled predictions, and −1.6 [−1.7, −1.5] % in the ISMN. [ABSTRACT FROM AUTHOR]