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Mapping in situ eddy covariance measurements of terrestrial land–atmosphere fluxes to the globe is a key method for diagnosing the Earth system from a data-driven perspective. We describe the first global products (called X-BASE) from a newly implemented upscaling framework, FLUXCOM-X, representing an advancement from the previous generation of FLUXCOM products in terms of flexibility and technical capabilities. The X-BASE products are comprised of estimates of CO2 net ecosystem exchange (NEE), gross primary productivity (GPP), evapotranspiration (ET), and for the first time a novel, fully data-driven global transpiration product (ETT), at high spatial (0.05°) and temporal (hourly) resolution. X-BASE estimates the global NEE at −5.75 ± 0.33 Pg C yr−1 for the period 2001–2020, showing a much higher consistency with independent atmospheric carbon cycle constraints compared to the previous versions of FLUXCOM. The improvement of global NEE was likely only possible thanks to the international effort to increase the precision and consistency of eddy covariance collection and processing pipelines, as well as to the extension of the measurements to more site years resulting in a wider coverage of bioclimatic conditions. However, X-BASE global net ecosystem exchange shows a very low interannual variability, which is common to state-of-the-art data-driven flux products and remains a scientific challenge. With 125 ± 2.1 Pg C yr−1 for the same period, X-BASE GPP is slightly higher than previous FLUXCOM estimates, mostly in temperate and boreal areas. X-BASE evapotranspiration amounts to 74.7×103 ± 0.9×103 km3 globally for the years 2001–2020 but exceeds precipitation in many dry areas, likely indicating overestimation in these regions. On average 57 % of evapotranspiration is estimated to be transpiration, in good agreement with isotope-based approaches, but higher than estimates from many land surface models. Despite considerable improvements to the previous upscaling products, many further opportunities for development exist. Pathways of exploration include methodological choices in the selection and processing of eddy covariance and satellite observations, their ingestion into the framework, and the configuration of machine learning methods. For this, the new FLUXCOM-X framework was specifically designed to have the necessary flexibility to experiment, diagnose, and converge to more accurate global flux estimates.

In the previous article, we defined the scholarship of teaching and learning (SoTL) and the scholarship of practice (SoP) and identified characteristics and qualities related to these topics. In this article, we provide examples of scholars who have conducted a SoTL project related to student affairs. Each of these entries describes the project and gives us insights into why scholars choose to engage in this work and the impact of their work on teaching and learning.

Surface radiometer data from Ross Island, Antarctica, collected during the austral summer 2015–2016 by the US Department of Energy Atmospheric Radiation Measurement (ARM) program West Antarctic Radiation Experiment (AWARE), are used to evaluate how shortwave and longwave irradiance respond to changing cloud properties as governed by contrasting meteorological regimes. Shortwave atmospheric transmittance is derived from pyranometer measurements, and cloud conservative-scattering optical depth is derived from filter radiometer measurements at 870 nm. With onshore flow associated with marine air masses, clouds contain mostly liquid water. With southerly flow over the Transantarctic Mountains, orographic forcing induces substantial cloud ice water content. These ice and mixed-phase clouds attenuate more surface shortwave irradiance than the maritime-influenced clouds and also emit less longwave irradiance due to colder cloud base temperature. These detected irradiance changes are in a range that can mean onset or inhibition of surface melt over ice shelves. This study demonstrates how basic and relatively low-cost broadband and filter radiometers can be used to detect subtle climatological influences of contrasting cloud microphysical properties at very remote locations.

Abstract Background In the choroid plexus and pituitary gland, vasculature is known to have a permeable, fenestrated phenotype which allows for the free passage of molecules in contrast to the blood brain barrier observed in the rest of the CNS. The endothelium of these compartments, along with secretory, neural-lineage cells (choroid epithelium and pituitary endocrine cells) have been studied in detail, but less attention has been given to the perivascular mesenchymal cells of these compartments. Methods The Hic1 CreERT2 Rosa26 LSL−TdTomato mouse model was used in conjunction with a Pdgfra H2B−EGFP mouse model to examine mesenchymal cells, which can be subdivided into Pdgfra+ fibroblasts and Pdgfra− pericytes within the choroid plexus (CP) and pituitary gland (PG), by histological, immunofluorescence staining and single-cell RNA-sequencing analyses. Results We found that both CP and PG possess substantial populations of distinct Hic1+ mesenchymal cells, including an abundance of Pdgfra+ fibroblasts. Within the pituitary, we identified distinct subpopulations of Hic1+ fibroblasts in the glandular anterior pituitary and the neurosecretory posterior pituitary. We also identified multiple distinct markers of CP, PG, and the meningeal mesenchymal compartment, including alkaline phosphatase, indole-n-methyltransferase and CD34. Conclusions Novel, distinct subpopulations of mesenchymal cells can be found in permeable vascular interfaces, including the CP, PG, and meninges, and make distinct contributions to both organs through the production of structural proteins, enzymes, transporters, and trophic molecules.

We report results from simultaneous experiments conducted in late 2022 in Belarus, Estonia, Kazakhstan, Russia and Ukraine. The experiments focus on fact-checking misinformation supportive of Russia in the Russia-Ukraine War. Meta-analysis makes clear that fact-checking misinformation reduces belief in pro-Kremlin false claims. Effects of fact-checks are not uniform across countries; our meta-analytic estimate is reliant on belief accuracy increases observed in Russia and Ukraine. While fact-checks improve belief accuracy, they do not change respondents' attitudes about which side to support in the War. War does not render individuals hopelessly vulnerable to misinformation-but fact-checking misinformation is unlikely to change their views toward the conflict.

Abstract Colorectal cancer (CRC) is the third most common cancer worldwide. Screening programs allow early diagnosis and have improved the clinical management of this disease. Aberrant DNA methylation is increasingly being explored as potential biomarkers for many types of cancers. In this study we investigate the methylation of ten target genes in 105 CRC and paired normal adjacent colonic tissue samples using a MethylLight droplet digital PCR (ML-ddPCR) assay. Receiver operator characteristic (ROC) curves were used to determine the diagnostic performance of all target genes individually and in combination. All 515 different combinations of genes showed significantly higher levels of methylation in CRC tissue. The combination of multiple target genes into a single test generally resulted in greater diagnostic accuracy when compared to single target genes. Our data confirms that ML-ddPCR is able to reliably detect significant differences in DNA methylation between CRC tissue and normal adjacent colonic tissue in a specific selection of target genes.

Earth's drylands are home to more than two billion people, provide key ecosystem services, and exert a large influence on the trends and variability in Earth's carbon cycle. However, modeling dryland carbon and water fluxes with remote sensing suffers from unique challenges not typically encountered in mesic systems, particularly in capturing soil moisture stress. Here, we develop and evaluate an approach for the joint modeling of dryland gross primary production (GPP), net ecosystem exchange (NEE), and evapotranspiration (ET) in the western United States (US) using a suite of AmeriFlux eddy covariance sites spanning major functional types and aridity regimes. We use artificial neural networks (ANNs) to predict dryland ecosystem fluxes by fusing optical vegetation indices, multitemporal thermal observations, and microwave soil moisture and temperature retrievals from the Soil Moisture Active Passive (SMAP) sensor. Our new dryland ANN (DrylANNd) carbon and water flux model explains more than 70 % of monthly variance in GPP and ET, improving upon existing MODIS GPP and ET estimates at most dryland eddy covariance sites. DrylANNd predictions of NEE were considerably worse than its predictions of GPP and ET likely because soil and plant respiratory processes are largely invisible to satellite sensors. Optical vegetation indices, particularly the normalized difference vegetation index (NDVI) and near-infrared reflectance of vegetation (NIRv), were generally the most important variables contributing to model skill. However, daytime and nighttime land surface temperatures and SMAP soil moisture and soil temperature also contributed to model skill, with SMAP especially improving model predictions of shrubland, grassland, and savanna fluxes and land surface temperatures improving predictions in evergreen needleleaf forests. Our results show that a combination of optical vegetation indices and thermal infrared and microwave observations can substantially improve estimates of carbon and water fluxes in drylands, potentially providing the means to better monitor vegetation function and ecosystem services in these important regions that are undergoing rapid hydroclimatic change.

Mesenchymal progenitors (MPs) are fundamental to tissue development and regeneration, however, their embryonic origin is unclear. Single cell-omics coupled with lineage tracing reveal a unique somite-derived MP hierarchy in limb morphogenesis.

Summary: The musculoskeletal system relies on the integration of multiple components with diverse physical properties, such as striated muscle, tendon, and bone, that enable locomotion and structural stability. This relies on the emergence of specialized, but poorly characterized, interfaces between these various elements during embryonic development. Within the appendicular skeleton, we show that a subset of mesenchymal progenitors (MPs), identified by Hic1, do not contribute to the primary cartilaginous anlagen but represent the MP population, whose progeny directly contribute to the interfaces that connect bone to tendon (entheses), tendon to muscle (myotendinous junctions), and the associated superstructures. Furthermore, deletion of Hic1 leads to skeletal defects reflective of deficient muscle-bone coupling and, consequently, perturbation of ambulation. Collectively, these findings show that Hic1 identifies a unique MP population that contributes to a secondary wave of bone sculpting critical to skeletal morphogenesis.

Abstract Background Over 120 million mice and rats are used annually in research, conventionally housed in shoebox-sized cages that restrict natural behaviours (e.g. nesting and burrowing). This can reduce physical fitness, impair thermoregulation and reduce welfare (e.g. inducing abnormal stereotypic behaviours). In humans, chronic stress has biological costs, increasing disease risks and potentially shortening life. Using a pre-registered protocol ( https://atrium.lib.uoguelph.ca/xmlui/handle/10214/17955 ), this meta-analysis therefore tested the hypothesis that, compared to rodents in ‘enriched’ housing that better meets their needs, conventional housing increases stress-related morbidity and all-cause mortality. Results Comprehensive searches (via Ovid, CABI, Web of Science, Proquest and SCOPUS on May 24 2020) yielded 10,094 publications. Screening for inclusion criteria (published in English, using mice or rats and providing ‘enrichments’ in long-term housing) yielded 214 studies (within 165 articles, using 6495 animals: 59.1% mice; 68.2% male; 31.8% isolation-housed), and data on all-cause mortality plus five experimentally induced stress-sensitive diseases: anxiety, cancer, cardiovascular disease, depression and stroke. The Systematic Review Center for Laboratory animal Experimentation (SYRCLE) tool assessed individual studies’ risks of bias. Random-effects meta-analyses supported the hypothesis: conventional housing significantly exacerbated disease severity with medium to large effect sizes: cancer (SMD = 0.71, 95% CI = 0.54–0.88); cardiovascular disease (SMD = 0.72, 95% CI = 0.35–1.09); stroke (SMD = 0.87, 95% CI = 0.59–1.15); signs of anxiety (SMD = 0.91, 95% CI = 0.56–1.25); signs of depression (SMD = 1.24, 95% CI = 0.98–1.49). It also increased mortality rates (hazard ratio = 1.48, 95% CI = 1.25–1.74; relative median survival = 0.91, 95% CI = 0.89–0.94). Meta-regressions indicated that such housing effects were ubiquitous across species and sexes, but could not identify the most impactful improvements to conventional housing. Data variability (assessed via coefficient of variation) was also not increased by ‘enriched’ housing. Conclusions Conventional housing appears sufficiently distressing to compromise rodent health, raising ethical concerns. Results also add to previous work to show that research rodents are typically CRAMPED (cold, rotund, abnormal, male-biased, poorly surviving, enclosed and distressed), raising questions about the validity and generalisability of the data they generate. This research was funded by NSERC, Canada.

We use reanalysis data and satellite remote sensing of cloud properties to examine how meteorological conditions alter the surface energy balance to cause surface melt that is detectable in satellite passive microwave imagery over West Antarctica. This analysis can detect each of the three primary mechanisms for inducing surface melt at a specific location: thermal blanketing involving sensible heat flux and/or longwave heating by optically thick cloud cover, all-wave radiative enhancement by optically thin cloud cover, and föhn winds. We examine case studies over Pine Island and Thwaites glaciers, which are of interest for ice shelf and ice sheet stability, and over Siple Dome, which is more readily accessible for field work. During January 2015 over Siple Dome we identified a melt event whose origin is an all-wave radiative enhancement by optically thin clouds. During December 2011 over Pine Island and Thwaites glaciers, we identified a melt event caused mainly by thermal blanketing from optically thick clouds. Over Siple Dome, those same 2011 synoptic conditions yielded a thermal-blanketing-driven melt event that was initiated by an impulse of sensible heat flux and then prolonged by cloud longwave heating. The December 2011 synoptic conditions also generated föhn winds at a location on the Ross Ice Shelf adjacent to the Transantarctic Mountains, and we analyze this case with additional support from automatic weather station data. In contrast, a late-summer thermal blanketing period over Pine Island and Thwaites glaciers during February 2013 showed surface melt initiated by cloud longwave heating and then prolonged by enhanced sensible heat flux. One limitation thus far with this type of analysis involves uncertainties in the cloud optical properties. Nevertheless, with improvements this type of analysis can enable quantitative prediction of atmospheric stress on the vulnerable Antarctic ice shelves in a steadily warming climate.

Plant activity in semi-arid ecosystems is largely controlled by pulses of precipitation, making them particularly vulnerable to increased aridity that is expected with climate change. Simple bucket-model hydrology schemes in land surface models (LSMs) have had limited ability in accurately capturing semi-arid water stores and fluxes. Recent, more complex, LSM hydrology models have not been widely evaluated against semi-arid ecosystem in situ data. We hypothesize that the failure of older LSM versions to represent evapotranspiration, ET, in arid lands is because simple bucket models do not capture realistic fluctuations in upper-layer soil moisture. We therefore predict that including a discretized soil hydrology scheme based on a mechanistic description of moisture diffusion will result in an improvement in model ET when compared to data because the temporal variability of upper-layer soil moisture content better corresponds to that of precipitation inputs. To test this prediction, we compared ORCHIDEE LSM simulations from (1) a simple conceptual 2-layer bucket scheme with fixed hydraulic parameters and (2) an 11-layer discretized mechanistic scheme of moisture diffusion in unsaturated soil based on Richards equations, against daily and monthly soil moisture and ET observations, together with data-derived estimates of transpiration / evapotranspiration, T∕ET, ratios, from six semi-arid grass, shrub, and forest sites in the south-western USA. The 11-layer scheme also has modified calculations of surface runoff, water limitation, and resistance to bare soil evaporation, E, to be compatible with the more complex hydrology configuration. To diagnose remaining discrepancies in the 11-layer model, we tested two further configurations: (i) the addition of a term that captures bare soil evaporation resistance to dry soil; and (ii) reduced bare soil fractional vegetation cover. We found that the more mechanistic 11-layer model results in a better representation of the daily and monthly ET observations. We show that, as predicted, this is because of improved simulation of soil moisture in the upper layers of soil (top ∼ 10 cm). Some discrepancies between observed and modelled soil moisture and ET may allow us to prioritize future model development and the collection of additional data. Biases in winter and spring soil moisture at the forest sites could be explained by inaccurate soil moisture data during periods of soil freezing and/or underestimated snow forcing data. Although ET is generally well captured by the 11-layer model, modelled T∕ET ratios were generally lower than estimated values across all sites, particularly during the monsoon season. Adding a soil resistance term generally decreased simulated bare soil evaporation, E, and increased soil moisture content, thus increasing transpiration, T, and reducing the negative bias between modelled and estimated monsoon T∕ET ratios. This negative bias could also be accounted for at the low-elevation sites by decreasing the model bare soil fraction, thus increasing the amount of transpiring leaf area. However, adding the bare soil resistance term and decreasing the bare soil fraction both degraded the model fit to ET observations. Furthermore, remaining discrepancies in the timing of the transition from minimum T∕ET ratios during the hot, dry May–June period to high values at the start of the monsoon in July–August may also point towards incorrect modelling of leaf phenology and vegetation growth in response to monsoon rains. We conclude that a discretized soil hydrology scheme and associated developments improve estimates of ET by allowing the modelled upper-layer soil moisture to more closely match the pulse precipitation dynamics of these semi-arid ecosystems; however, the partitioning of T from E is not solved by this modification alone.

The authors present large sample studies showing substantial relationships between measures of embodiment (the rubber hand illusion and mirror synaesthesia) and trait imaginative suggestibility in the hypnotic context. These measures of striking experiential change may therefore be confounded by suggestion effects.

Abstract Background Health, healthcare, and healthcare system problems within the developing world are well recognised. eHealth, the use of Information and Communications Technologies (ICT) for health, is frequently suggested as one means by which to ameliorate such problems. However, to identify and implement the most appropriate ehealth solutions requires development of a thoughtful and broadly evidence-informed strategy. Most published strategies focus on health informatics solutions, neglecting the potential for other aspects of ehealth (telehealth, telemedicine, elearning, and ecommerce). This study examined the setting in Botswana to determine the need for a telemedicine-specific strategy. Methods A situational assessment of ehealth activities in Botswana was performed through a scoping review of the scientific and grey literature using specified search terms to July 2018; an interview with an official from the major mhealth stakeholder; and benchtop review of policies and other relevant Government documents including the country’s current draft eHealth Strategy. Results Thirty-nine papers were reviewed. Various ehealth technologies have been applied within Botswana. These include Skype for educational activities, instant messaging (WhatsApp for telepathology; SMS for transmission of laboratory test results, patient appointment reminders, and invoicing and bill payment), and robotics for dermatopathology. In addition health informatics technologies have been used for surveillance, monitoring, and access to information by healthcare workers. The number of distinct health information systems has been reduced from 37 to 12, and 9 discrete EMRs remain active within the public health institutions. Many infrastructural issues were identified. A critical assessment of the current draft ehealth strategy document for Botswana showed limitations. Many telemedicine services have been introduced over the years (addressing cervical cancer screening, teledermatology, teleradiology, oral medicine and eye screening), but only one project was confirmed to be active and being scaled up with the intervention of the Government. Conclusions Botswana’s draft ‘ehealth’ strategy will not, in and of itself, nurture innovative growth in the application of telemedicine initiatives, which currently are fragmented and stalled. This lack of focus is preventing telemedicine’s recognised potential from being leveraged. A specific Telemedicine Strategy, aligned with and supportive of the pre-existing ehealth strategy, would provide the necessary focus, stimulus, and guidance.

Evaporation (E) and transpiration (T) respond differently to ongoing changes in climate, atmospheric composition, and land use. It is difficult to partition ecosystem-scale evapotranspiration (ET) measurements into E and T, which makes it difficult to validate satellite data and land surface models. Here, we review current progress in partitioning E and T and provide a prospectus for how to improve theory and observations going forward. Recent advancements in analytical techniques create new opportunities for partitioning E and T at the ecosystem scale, but their assumptions have yet to be fully tested. For example, many approaches to partition E and T rely on the notion that plant canopy conductance and ecosystem water use efficiency exhibit optimal responses to atmospheric vapor pressure deficit (D). We use observations from 240 eddy covariance flux towers to demonstrate that optimal ecosystem response to D is a reasonable assumption, in agreement with recent studies, but more analysis is necessary to determine the conditions for which this assumption holds. Another critical assumption for many partitioning approaches is that ET can be approximated as T during ideal transpiring conditions, which has been challenged by observational studies. We demonstrate that T can exceed 95 % of ET from certain ecosystems, but other ecosystems do not appear to reach this value, which suggests that this assumption is ecosystem-dependent with implications for partitioning. It is important to further improve approaches for partitioning E and T, yet few multi-method comparisons have been undertaken to date. Advances in our understanding of carbon–water coupling at the stomatal, leaf, and canopy level open new perspectives on how to quantify T via its strong coupling with photosynthesis. Photosynthesis can be constrained at the ecosystem and global scales with emerging data sources including solar-induced fluorescence, carbonyl sulfide flux measurements, thermography, and more. Such comparisons would improve our mechanistic understanding of ecosystem water fluxes and provide the observations necessary to validate remote sensing algorithms and land surface models to understand the changing global water cycle.

A limitation of the Met Office operational data assimilation scheme is that surface-sensitive infrared satellite sounding channels cannot be used during daytime periods where numerical weather prediction (NWP) model background land surface temperature (LST) biases are greater than 2 K in magnitude. The Met Office Unified Model (UM) has a significant cold LST bias in semi-arid regions when compared with satellite observations; a range of UM configurations were assessed with different model resolutions, land surface cover datasets and bare soil parameterisations. UM LST biases were evaluated at global resolution and in a limited area model (LAM) at a 2.2 km resolution over the SALSTICE (Semi-Arid Land Surface Temperature and IASI Calibration Experiment) experimental domain in south-eastern Arizona. This validation is in conjunction with eddy-covariance flux tower measurements. LST biases in the Global Atmosphere/Land 3.1 (GA/L3.1) configuration were largest in the mid-morning with respect to Moderate Resolution Imaging Spectroradiometer (MODIS) Terra (-13.6±2.8 K at the Kendall Grassland site). The diurnal cycle of LST in Global Atmosphere/Land 6.1 (GA/L6.1) showed a significant improvement relative to GA/L3.1 with the cold LST biases reduced to -1.4±2.7 K and -3.6±3.0 K for Terra and Aqua overpasses, respectively. The higher-resolution LAM showed added value over the global configurations. The spatial distribution of the LST biases relative to MODIS and the modelled bare soil cover fraction were found to be moderately correlated (0.61±0.08) during the daytime, which suggests that regions of cold LST bias are associated with low bare soil cover fraction. Coefficients of correlation with the shrub surface fractions followed the same trend as the bare soil cover fraction, although with a less significant correlation (0.36±0.09), and indicated that the sparse vegetation canopies in south-eastern Arizona are not well represented in UM ancillary datasets. The x component of the orographic slope was positively correlated with the LST bias (0.41±0.05 for MODIS Aqua) and identified that regions of cold model LST bias are found on easterly slopes, and regions of warm model LST bias are found on westerly slopes. An overestimate in the modelled turbulent heat and moisture fluxes at the eddy-covariance flux sites was found to be coincident with an underestimate in the ground heat flux.

Abstract Backgound Economic evaluations of interventions to prevent healthcare-associated infections in the United States rarely take the societal perspective and thus ignore the potential benefits of morbidity and mortality risk reductions. Using new Department of Health and Human Services guidelines for regulatory impact analysis, we developed a cost-benefit analyses of a national multifaceted, in-hospital Clostridioides difficile infection prevention program (including staffing an antibiotic stewardship program) that incorporated value of statistical life estimates to obtain economic values associated with morbidity and mortality risk reductions. Methods We used a net present value model to assess costs and benefits associated with antibiotic stewardship programs. Model inputs included treatment costs, intervention costs, healthcare-associated Clostridioides difficile infection cases, attributable deaths, and the value of statistical life which was used to estimate the economic value of morbidity and mortality risk reductions. Results From 2015 to 2020, total net benefits of the intervention to the healthcare system range from $300 million to $7.6 billion when values for morbidity and mortality risk reductions are ignored. Including these values, the net social benefits of the intervention range from $21 billion to $624 billion with the annualized net benefit of $25.5 billion under our most likely outcome scenario. Conclusions Incorporating the economic value of morbidity and mortality risk reductions in economic evaluations of healthcare-associated infections will significantly increase the benefits resulting from prevention.

The Countryside Survey (CS) of Great Britain (GB) provides a unique and statistically robust series of datasets, consisting of an extensive set of repeated ecological measurements at a national scale, covering a time span of 29 years. CS was first undertaken in 1978 to provide a baseline for ecological and land use change monitoring in the rural environment of GB, following a stratified random design, based on 1 km squares. Originally, eight random 1 km squares were drawn from each of 32 environmental classes, thus comprising 256 sample squares in the 1978 survey. The number of these sites increased to 382 in 1984, 506 in 1990, 569 in 1998 and 591 in 2007. Detailed information regarding vegetation types and land use was mapped in all five surveys, allowing reporting by defined standard habitat classifications. Additionally, point and linear landscape features (such as trees and hedgerows) are available from all surveys after 1978. From these stratified, randomly located sample squares, information can be converted into national estimates, with associated error terms. Other data, relating to soils, freshwater and vegetation, were also sampled on analogous dates. However, the present paper describes only the surveys of landscape features and habitats. The resulting datasets provide a unique, comprehensive, quantitative ecological coverage of extent and change in these features in GB. Basic results are presented and their implications discussed. However, much opportunity for further analyses remains. Data from each of the survey years are available via the following DOIs: Landscape area data 1978: https://doi.org/10.5285/86c017ba-dc62-46f0-ad13-c862bf31740e, 1984: https://doi.org/10.5285/b656bb43-448d-4b2c-aade-7993aa243ea3, 1990: https://doi.org/10.5285/94f664e5-10f2-4655-bfe6-44d745f5dca7, 1998: https://doi.org/10.5285/1e050028-5c55-42f4-a0ea-c895d827b824, and 2007: https://doi.org/10.5285/bf189c57-61eb-4339-a7b3-d2e81fdde28d; Landscape linear feature data 1984: https://doi.org/10.5285/a3f5665c-94b2-4c46-909e-a98be97857e5, 1990: https://doi.org/10.5285/311daad4-bc8c-485a-bc8a-e0d054889219, 1998: https://doi.org/10.5285/8aaf6f8c-c245-46bb-8a2a-f0db012b2643 and 2007: https://doi.org/10.5285/e1d31245-4c0a-4dee-b36c-b23f1a697f88, Landscape point feature data 1984: https://doi.org/10.5285/124b872e-036e-4dd3-8316-476b5f42c16e, 1990: https://doi.org/10.5285/1481bc63-80d7-4d18-bcba-8804aa0a9e1b, 1998: https://doi.org/10.5285/ed10944f-40c8-4913-b3f5-13c8e844e153 and 2007: https://doi.org/10.5285/55dc5fd7-d3f7-4440-b8a7-7187f8b0550b.

Extreme climatic events, such as droughts and heat stress, induce anomalies in ecosystem–atmosphere CO2 fluxes, such as gross primary production (GPP) and ecosystem respiration (Reco), and, hence, can change the net ecosystem carbon balance. However, despite our increasing understanding of the underlying mechanisms, the magnitudes of the impacts of different types of extremes on GPP and Reco within and between ecosystems remain poorly predicted. Here we aim to identify the major factors controlling the amplitude of extreme-event impacts on GPP, Reco, and the resulting net ecosystem production (NEP). We focus on the impacts of heat and drought and their combination. We identified hydrometeorological extreme events in consistently downscaled water availability and temperature measurements over a 30-year time period. We then used FLUXNET eddy covariance flux measurements to estimate the CO2 flux anomalies during these extreme events across dominant vegetation types and climate zones. Overall, our results indicate that short-term heat extremes increased respiration more strongly than they downregulated GPP, resulting in a moderate reduction in the ecosystem's carbon sink potential. In the absence of heat stress, droughts tended to have smaller and similarly dampening effects on both GPP and Reco and, hence, often resulted in neutral NEP responses. The combination of drought and heat typically led to a strong decrease in GPP, whereas heat and drought impacts on respiration partially offset each other. Taken together, compound heat and drought events led to the strongest C sink reduction compared to any single-factor extreme. A key insight of this paper, however, is that duration matters most: for heat stress during droughts, the magnitude of impacts systematically increased with duration, whereas under heat stress without drought, the response of Reco over time turned from an initial increase to a downregulation after about 2 weeks. This confirms earlier theories that not only the magnitude but also the duration of an extreme event determines its impact. Our study corroborates the results of several local site-level case studies but as a novelty generalizes these findings on the global scale. Specifically, we find that the different response functions of the two antipodal land–atmosphere fluxes GPP and Reco can also result in increasing NEP during certain extreme conditions. Apparently counterintuitive findings of this kind bear great potential for scrutinizing the mechanisms implemented in state-of-the-art terrestrial biosphere models and provide a benchmark for future model development and testing.

Abstract Dietary docosahexaenoic acid (DHA, 22:6n-3) not only increases blood and tissue levels of DHA, but also eicosapentaenoic acid (EPA, 20:5n-3). It is generally believed that this increase is due to DHA retroconversion to EPA, however, a slower conversion of α-linolenic acid (ALA, 18:3n-3) derived EPA to downstream metabolic products (i.e. slower turnover of EPA) is equally plausible. In this study, 21-day old Long Evans rats were weaned onto an ALA only or DHA + ALA diet for 12 weeks. Afterwards, livers were collected and the natural abundance 13C-enrichment was determined by compound specific isotope analysis (CSIA) of liver EPA by isotope ratio mass-spectrometry and compared to dietary ALA and DHA 13C-enrichment. Isotopic signatures (per mil, ‰) for liver EPA were not different (p > 0.05) between the ALA only diet (−25.89 ± 0.39 ‰, mean ± SEM) and the DHA + ALA diet (−26.26 ± 0.40 ‰), suggesting the relative contribution from dietary ALA and DHA to liver EPA did not change. However, with DHA feeding estimates of absolute EPA contribution from ALA increased 4.4-fold (147 ± 22 to 788 ± 153 nmol/g) compared to 3.2-fold from DHA (91 ± 14 to 382 ± 13 nmol/g), respectively. In conclusion, CSIA of liver EPA in rats following 12-weeks of dietary DHA suggests that retroconversion of DHA to EPA is a relatively small contributor to increases in EPA, and that this increase in EPA is largely coming from elongation/desaturation of ALA.

Much adaptive evolutionary change is underlain by mutational variation in regions of the genome that regulate gene expression rather than in the coding regions of the genes themselves. An understanding of the role of gene expression variation in facilitating local adaptation will be aided by an understanding of underlying regulatory networks. Here, we characterize the genetic architecture of gene expression variation in the threespine stickleback (Gasterosteus aculeatus), an important model in the study of adaptive evolution. We collected transcriptomic and genomic data from 60 half-sib families using an expression microarray and genotyping-by-sequencing, and located expression quantitative trait loci (eQTL) underlying the variation in gene expression in liver tissue using an interval mapping approach. We identified eQTL for several thousand expression traits. Expression was influenced by polymorphism in both cis- and trans-regulatory regions. Trans-eQTL clustered into hotspots. We did not identify master transcriptional regulators in hotspot locations: rather, the presence of hotspots may be driven by complex interactions between multiple transcription factors. One observed hotspot colocated with a QTL recently found to underlie salinity tolerance in the threespine stickleback. However, most other observed hotspots did not colocate with regions of the genome known to be involved in adaptive divergence between marine and freshwater habitats.

Effects of hydraulic redistribution (HR) on hydrological, biogeochemical, and ecological processes have been demonstrated in the field, but the current generation of standard earth system models does not include a representation of HR. Though recent studies have examined the effect of incorporating HR into land surface models, few (if any) have done cross-site comparisons for contrasting climate regimes and multiple vegetation types via the integration of measurement and modeling. Here, we incorporated the HR scheme of Ryel et al. (2002) into the NCAR Community Land Model Version 4.5 (CLM4.5), and examined the ability of the resulting hybrid model to capture the magnitude of HR flux and/or soil moisture dynamics from which HR can be directly inferred, to assess the impact of HR on land surface water and energy budgets, and to explore how the impact may depend on climate regimes and vegetation conditions. Eight AmeriFlux sites with contrasting climate regimes and multiple vegetation types were studied, including the Wind River Crane site in Washington State, the Santa Rita Mesquite savanna site in southern Arizona, and six sites along the Southern California Climate Gradient. HR flux, evapotranspiration (ET), and soil moisture were properly simulated in the present study, even in the face of various uncertainties. Our cross-ecosystem comparison showed that the timing, magnitude, and direction (upward or downward) of HR vary across ecosystems, and incorporation of HR into CLM4.5 improved the model-measurement matches of evapotranspiration, Bowen ratio, and soil moisture particularly during dry seasons. Our results also reveal that HR has important hydrological impact in ecosystems that have a pronounced dry season but are not overall so dry that sparse vegetation and very low soil moisture limit HR.