Nitrogen cycle impacts on CO2 fertilisation and climate forcing of land carbon stores

Anthropogenic fossil fuel burning increases atmospheric carbon dioxide (CO2) concentration, which is adjusting the climate system. The direct impact of rising CO2 levels and climate feedback alters the terrestrial carbon stores. Land stores are presently increasing, offsetting a substantial fraction of CO2 emissions. Less understood is how this human-induced carbon cycle perturbation interacts with other terrestrial biogeochemical cycles. These connections require quantification, as they may eventually suppress land fertilisation, and so fewer emissions are allowed to follow any prescribed future global warming pathway. Using the new Joint UK Land Environment Simulator-CN large-scale land model, which contributed to Coupled Model Intercomparison Project Phase 6 as the land component of the UK Earth System Model v1 climate model, we focus on how the introduction of the simulated terrestrial nitrogen (N) cycle modulates the expected evolution of vegetation and soil carbon pools. We find that the N-cycle suppresses, by approximately one-third, any future gains by the global soil pool when compared to calculations without that cycle. There is also a decrease in the vegetation carbon gain, although this is much smaller. Factorial simulations illustrate that N suppression tracks direct CO2 rise rather than climate change. The finding that this CO2-related effect predominantly influences soil carbon rather than vegetation carbon, we explain by different balances between changing carbon uptake levels and residence times. Finally, we discuss how this new generation of land models may gain further from emerging point knowledge held by the detailed ecological modelling community

Machine learning and artificial intelligence to aid climate change research and preparedness

Climate change challenges societal functioning, likely requiring considerable adaptation to cope with future altered weather patterns. Machine learning (ML) algorithms have advanced dramatically, triggering breakthroughs in other research sectors, and recently suggested as aiding climate analysis (Reichstein et al 2019 Nature 566 195–204, Schneider et al 2017 Geophys. Res. Lett. 44 12396–417). Although a considerable number of isolated Earth System features have been analysed with ML techniques, more generic application to understand better the full climate system has not occurred. For instance, ML may aid teleconnection identification, where complex feedbacks make characterisation difficult from direct equation analysis or visualisation of measurements and Earth System model (ESM) diagnostics. Artificial intelligence (AI) can then build on discovered climate connections to provide enhanced warnings of approaching weather features, including extreme events. While ESM development is of paramount importance, we suggest a parallel emphasis on utilising ML and AI to understand and capitalise far more on existing data and simulations

The Diagnostic and Prognostic Accuracy of Five Markers of Serious Bacterial Infection in Malawian Children with Signs of Severe Infection

Early recognition and prompt and appropriate antibiotic treatment can significantly reduce mortality from serious bacterial infections (SBI). The aim of this study was to evaluate the utility of five markers of infection: C-reactive protein (CRP), procalcitonin (PCT), soluble triggering receptor expressed on myeloid cells-1 (sTREM-1), CD163 and high mobility group box-1 (HMGB1), as markers of SBI in severely ill Malawian children.Children presenting with a signs of meningitis (n = 282) or pneumonia (n = 95), were prospectively recruited. Plasma samples were taken on admission for CRP, PCT, sTREM-1 CD163 and HMGB1 and the performance characteristics of each test to diagnose SBI and to predict mortality were determined. Of 377 children, 279 (74%) had SBI and 83 (22%) died. Plasma CRP, PCT, CD163 and HMGB1 and were higher in HIV-infected children than in HIV-uninfected children (p<0.01). In HIV-infected children, CRP and PCT were higher in children with SBI compared to those with no detectable bacterial infection (p<0.0005), and PCT and CD163 were higher in non-survivors (p = 0.001, p = 0.05 respectively). In HIV-uninfected children, CRP and PCT were also higher in children with SBI compared to those with no detectable bacterial infection (p<0.0005), and CD163 was higher in non-survivors (p = 0.05). The best predictors of SBI were CRP and PCT, and areas under the curve (AUCs) were 0.81 (95% CI 0.73–0.89) and 0.86 (95% CI 0.79–0.92) respectively. The best marker for predicting death was PCT, AUC 0.61 (95% CI 0.50–0.71).Admission PCT and CRP are useful markers of invasive bacterial infection in severely ill African children. The study of these markers using rapid tests in a less selected cohort would be important in this setting

Ecotoxicity of microplastics to freshwater biota: Considering exposure and hazard across trophic levels

In contrast to marine ecosystems, the toxicity impact of microplastics in freshwater environments is poorly understood. This contribution reviews the literature on the range of effects of microplastics across and between trophic levels within the freshwater environment, including biofilms, macrophytes, phytoplankton, invertebrates, fish and amphibians. While there is supporting evidence for toxicity in some species e.g. growth reduction for photoautotrophs, increased mortality for some invertebrates, genetic changes in amphibians, and cell internalization of microplastics and nanoplastics in fish; other studies show that it is uncertain whether microplastics can have detrimental long-term impacts on ecosystems. Some taxa have yet to be studied e.g. benthic diatoms, while only 12% of publications on microplastics in freshwater, demonstrate trophic transfer in foodwebs. The fact that just 2% of publications focus on microplastics colonized by biofilms is hugely concerning given the cascading detrimental effects this could have on freshwater ecosystem function. Multiple additional stressors including environmental change (temperature rises and invasive species) and contaminants of anthropogenic origin (antibiotics, metals, pesticides and endocrine disruptors) will likely exacerbate negative interactions between microplastics and freshwater organisms, with potentially significant damaging consequences to freshwater ecosystems and foodwebs

Stability in Ecosystem Functioning across a Climatic Threshold and Contrasting Forest Regimes

Classical ecological theory predicts that changes in the availability of essential resources such as nitrogen should lead to changes in plant community composition due to differences in species-specific nutrient requirements. What remains unknown, however, is the extent to which climate change will alter the relationship between plant communities and the nitrogen cycle. During intervals of climate change, do changes in nitrogen cycling lead to vegetation change or do changes in community composition alter the nitrogen dynamics? We used long-term ecological data to determine the role of nitrogen availability in changes of forest species composition under a rapidly changing climate during the early Holocene (16k to 8k cal. yrs. BP). A statistical computational analysis of ecological data spanning 8,000 years showed that secondary succession from a coniferous to deciduous forest occurred independently of changes in the nitrogen cycle. As oak replaced pine under a warming climate, nitrogen cycling rates increased. Interestingly, the mechanism by which the species interacted with nitrogen remained stable across this threshold change in climate and in the dominant tree species. This suggests that changes in tree population density over successional time scales are not driven by nitrogen availability. Thus, current models of forest succession that incorporate the effects of available nitrogen may be over-estimating tree population responses to changes in this resource, which may result in biased predictions of future forest dynamics under climate warming

Shrub growth and expansion in the Arctic tundra: an assessment of controlling factors using an evidence-based approach

Woody shrubs have increased in biomass and expanded into new areas throughout the Pan-Arctic tundra biome in recent decades, which has been linked to a biome-wide observed increase in productivity. Experimental, observational, and socio-ecological research suggests that air temperature—and to a lesser degree precipitation—trends have been the predominant drivers of this change. However, a progressive decoupling of these drivers from Arctic vegetation productivity has been reported, and since 2010, vegetation productivity has also been declining. We created a protocol to (a) identify the suite of controls that may be operating on shrub growth and expansion, and (b) characterise the evidence base for controls on Arctic shrub growth and expansion. We found evidence for a suite of 23 proximal controls that operate directly on shrub growth and expansion; the evidence base focused predominantly on just four controls (air temperature, soil moisture, herbivory, and snow dynamics). 65% of evidence was generated in the warmest tundra climes, while 24% was from only one of 28 floristic sectors. Temporal limitations beyond 10 years existed for most controls, while the use of space-for-time approaches was high, with 14% of the evidence derived via experimental approaches. The findings suggest the current evidence base is not sufficiently robust or comprehensive at present to answer key questions of Pan-Arctic shrub change. We suggest future directions that could strengthen the evidence, and lead to an understanding of the key mechanisms driving changes in Arctic shrub environments

PCR Improves Diagnostic Yield from Lung Aspiration in Malawian Children with Radiologically Confirmed Pneumonia

Accurate data on childhood pneumonia aetiology are essential especially from regions where mortality is high, in order to inform case-management guidelines and the potential of prevention strategies such as bacterial conjugate vaccines. Yield from blood culture is low, but lung aspirate culture provides a higher diagnostic yield. We aimed to determine if diagnostic yield could be increased further by polymerase chain reaction (PCR) detection of bacteria (Streptococcus pneumoniae and Haemophilus influenzae b) and viruses in lung aspirate fluid.A total of 95 children with radiological focal, lobar or segmental consolidation had lung aspirate performed and sent for bacterial culture and for PCR for detection of bacteria, viruses and Pneumocystis jirovecii. In children with a pneumococcal aetiology, pneumococcal bacterial loads were calculated in blood and lung aspirate fluid.Blood culture identified a bacterial pathogen in only 8 patients (8%). With the addition of PCR on lung aspirate samples, causative pathogens (bacterial, viral, pneumocystis) were identified singly or as co-infections in 59 children (62%). The commonest bacterial organism was S.pneumoniae (41%), followed by H. influenzae b (6%), and the commonest virus identified was adenovirus (16%), followed by human bocavirus (HBoV) (4%), either as single or co-infection.In a select group of African children, lung aspirate PCR significantly improves diagnostic yield. Our study confirms a major role of S.pneumoniae and viruses in the aetiology of childhood pneumonia in Africa

Genome-Wide Association Study in BRCA1 Mutation Carriers Identifies Novel Loci Associated with Breast and Ovarian Cancer Risk

BRCA1-associated breast and ovarian cancer risks can be modified by common genetic variants. To identify further cancer risk-modifying loci, we performed a multi-stage GWAS of 11,705 BRCA1 carriers (of whom 5,920 were diagnosed with breast and 1,839 were diagnosed with ovarian cancer), with a further replication in an additional sample of 2,646 BRCA1 carriers. We identified a novel breast cancer risk modifier locus at 1q32 for BRCA1 carriers (rs2290854, P = 2.7×10-8, HR = 1.14, 95% CI: 1.09-1.20). In addition, we identified two novel ovarian cancer risk modifier loci: 17q21.31 (rs17631303, P = 1.4×10-8, HR = 1.27, 95% CI: 1.17-1.38) and 4q32.3 (rs4691139, P = 3.4×10-8, HR = 1.20, 95% CI: 1.17-1.38). The 4q32.3 locus was not associated with ovarian cancer risk in the general population or BRCA2 carriers, suggesting a BRCA1-specific associat