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Reading tea leaves worldwide: decoupled drivers of initial litter decomposition mass-loss rate and stabilisation
Get PDFThe breakdown of plant material fuels soil functioning and biodiversity. Currently, process understanding of global decomposition patterns and the drivers of such patterns are hampered by the lack of coherent large-scale datasets. We buried 36,000 individual litterbags (tea bags) worldwide and found an overall negative correlation between initial mass-loss rates and stabilization factors of plant-derived carbon, using the Tea Bag Index (TBI). The stabilization factor quantifies the degree to which easy-to-degrade components accumulate during early-stage decomposition (e.g. by environmental limitations). However, agriculture and an interaction between moisture and temperature led to a decoupling between initial mass-loss rates and stabilization, notably in colder locations. Using TBI improved mass-loss estimates of natural litter compared to models that ignored stabilization. Ignoring the transformation of dead plant material to more recalcitrant substances during early-stage decomposition, and the environmental control of this transformation, could overestimate carbon losses during early decomposition in carbon cycle models
Observational assessment of changes in Earth's energy imbalance since 2000
Get PDFSatellite observations from the Clouds and the Earth's Radiant Energy System show that Earth’s energy imbalance has doubled from 0.5 ± 0.2 Wm−2 during the first 10 years of this century to 1.0 ± 0.2 Wm−2 during the past decade. The increase is the result of a 0.9 ± 0.3 Wm−2 increase absorbed solar radiation (ASR) that is partially offset by a 0.4 ± 0.25 Wm−2 increase in outgoing longwave radiation (OLR). Despite marked differences in ASR and OLR trends during the hiatus (2000–2010), transition-to-El Niño (2010–2016) and post-El Niño (2016–2022) periods, trends in net top-of-atmosphere flux (NET) remain within 0.1 Wm−2 per decade of one another, implying a steady acceleration of climate warming. Northern and southern hemisphere trends in NET are consistent to 0.06 ± 0.31 Wm−2 per decade due to a compensation between weak ASR and OLR hemispheric trend differences of opposite sign. We find that large decreases in stratocumulus and middle clouds over the sub-tropics and decreases in low and middle clouds at mid-latitudes are the primary reasons for increasing ASR trends in the northern hemisphere (NH). These changes are especially large over the eastern and northern Pacific Ocean, and coincide with large increases in sea-surface temperature (SST). The decrease in cloud fraction and higher SSTs over the NH sub-tropics lead to a significant increase in OLR from cloud-free regions, which partially compensate for the NH ASR increase. Decreases in middle cloud reflection and a weaker reduction in low-cloud reflection account for the increase in ASR in the southern hemisphere, while OLR changes are weak. Changes in cloud cover in response to SST increases imply a feedback to climate change yet a contribution from radiative forcing or internal variability cannot be ruled out
Medium amplitude field susceptometry (MAFS) for magnetic nanoparticles
Get PDFThe linear dynamic susceptibility is arguably the most important property to specify the magnetization dynamics of a given system. Therefore, this quantity has been studied in great detail and the corresponding measurements known as susceptometry are well-established. Notwithstanding its relevance, the linear susceptibility is inherently limited to describe the magnetization response to weak external fields only. Here, we suggest the framework of Medium Amplitude Field Susceptometry (MAFS) to study the non-linear response which complements the linear susceptibility and provides additional information on the magnetic properties of the system and is applicable to magnetic fields of medium amplitudes. In particular, we introduce the general third-order nonlinear susceptibility cˆ3 as a central quantity that completely specifies the lowest-order non-linear response to arbitrary time-dependent magnetic fields. We show that response functions in medium amplitude oscillatory magnetic fields and parallel superposition susceptometry are contained in cˆ3 as special cases. Also included in cˆ3 are interesting intermodulation effects when the system is probed by a superposition of oscillating magnetic fields with different frequencies. We work out the explicit form of cˆ3 for several model systems for the dynamics of magnetic nanoparticles (MNPs). We expect this unifying framework to be not only of theoretical interest, but also useful for a deeper characterization of MNP systems, giving additional information on their suitability for various applications
Adjustments to climate perturbations - mechanisms, implications, observational constraints
Get PDFSince the 5th Assessment Report of the Intergovernmental Panel on Climate Change (AR5) an extended concept of the energetic analysis of climate change including forcings, feedbacks and adjustment processes has become widely adopted. Adjustments are defined as processes that occur in response to the introduction of a climate forcing agent, but that are independent of global-mean surface temperature changes. Most considered are the adjustments that impact the Earth energy budget and strengthen or weaken the instantaneous radiative forcing due to the forcing agent. Some adjustment mechanisms also impact other aspects of climate not related to the Earth radiation budget. Since AR5 and a following description by Sherwood et al. (2015), much research on adjustments has been performed and is reviewed here. We classify the adjustment mechanisms into six main categories, and discuss methods of quantifying these adjustments in terms of their potentials, shortcomings and practicality. We furthermore describe aspects of adjustments that act beyond the energetic framework, and we propose new ideas to observe adjustments or to make use of observations to constrain their representation in models. Altogether, the problem of adjustments is now on a robust scientific footing, and better quantification and observational constraint is possible. This allows for improvements in understanding and quantifying climate change
The origins of storm Ciarán: from diabatic Rossby wave to a warm-seclusion cyclone with a sting jet
Get PDFThe evolution of Storm Ciarán was different from what is commonly attributed to windstorms affecting northwest Europe. Ciarán initially developed as a diabatic Rossby wave, driven by low-level latent-heat release and with negligible upper-tropospheric forcing. It then crossed the jet stream, intensifying explosively while developing a low-level warm seclusion and producing extreme near-surface winds, including sting jets. Ciarán is an example of an extreme windstorm following this pathway and highlights the need of a systematic assessment of its relevance in our warming climate
A computationally lightweight model for ensemble forecasting of environmental hazards: General TAMSAT-ALERT v1.2.1
Get PDFEfficient methods for predicting weather-related
hazards are crucial for the effective management of environ-
mental risk. Many environmental hazards depend on the evo-
lution of meteorological conditions over protracted periods,
requiring assessments that account for evolving conditions.
The TAMSAT-ALERT approach addresses this challenge
by combining observational monitoring with a weighted
multi-year ensemble. In this way, it enhances the utility
of existing systems by enabling users to combine multiple
streams of monitoring and meteorological forecasting data
into holistic hazard assessments. TAMSAT-ALERT forecasts
are now used in a number of regions in the Global South for
soil moisture forecasting, drought early warning and agri-
cultural decision support. The model presented here, Gen-
eral TAMSAT-ALERT, represents a significant scientific and
functional advance on previous implementations. Notably,
General TAMSAT-ALERT is applicable to any variable for
which time series data are available. In addition, function-
ality has been introduced to account for climatological non-
stationarity (for example due to climate change), large-scale
modes of variability (for example El Niño) and persistence
(for example of land-surface conditions). In this paper, we
present a full description of the model, along with case studies of its application to the prediction of central England temperature, Pakistan vegetation conditions and African precipitation
“I have never felt less protected as a Jew”: antisemitism at UK universities since 7th October 2023
Get PDFAnomaly detection using isomorphic analysis for false data injection attacks in industrial control systems
Get PDFAs the Industrial Internet-of-Things (IIoT) evolves, a growing number of industrial control systems (ICSs) are connecting to the Internet, making them more vulnerable to malicious attacks. This paper addresses the detection of false data injection (FDI) attacks, a prevalent threat to open ICSs. We introduce an innovative anomaly detection technique using isomorphic analysis to safeguard ICSs against FDI attacks. Isomorphic analysis involves comparing transmitted signals with their expected values, which are derived from mathematical models or isomorphic components. For a comprehensive defense mechanism, we incorporate three specific detectors: the control signal detector, the actuating signal detector, and the sensor reading detector. Designed to detect FDI attacks across various parts of the ICS, these detectors ensure the integrity of all transmitted signals throughout the physical control system. While the control signal detector adopts a threshold method, the other two rely on statistical approaches. If an attack is detected, the detectors can correct tampered signals before they reach downstream components, enhancing the system’s overall resilience and fault tolerance. The effectiveness of these detectors is supported by rigorous mathematical proofs. Moreover, our experimental findings further reveal the superiority of the isomorphic strategy over prior work in terms of detection rate, detection time delay, and system resilience
In vitro modelling of a typical dietary intake in restrictive anorexia nervosa results in changes to gut microbial community and metabolites
Get PDFAnorexia nervosa (AN) is a psychiatric illness with harmful physical consequences. Studies have observed differences in the faecal microbiota of patients with AN compared to healthy controls.
Diet has an impact on the gut microbiota, facilitating an altered community, such changes could impact the gut–brain axis. In this study, a three-stage gut model system that mimics the luminal microbiology of the large intestine was conducted to identify relationships between diet and gut
microbiota. A microbial medium was developed to provide nutrients more appropriate to restricting subtype AN (R-AN). The model was inoculated with faeces and samples were taken to compare differences in the microbiota and end products following the fermentation of healthy control medium (HC)
compared to R-AN medium. Then, 16S amplicon sequencing along with flow cytometry–fluorescence in situ hybridisation were used to ascertain changes in the microbiota. Gas chromatography (GC) was used to assess changes in microbial metabolites. There were reduced levels of SCFA following
the fermentation of R-AN medium. The fermentation of R-AN media led to fewer total bacteria numbers, along with less bifidobacteria and Rumincoccus proximally, but more Clostridium and Enterobacteriaceae. Nutrient-deficient medium resulted in reduced neurotransmitter-producing bacteria, reduced butyrate-producing bacteria, and increased protein-utilising bacteria, all of which could be maintaining factors in AN. The model system provides a novel tool for exploring how extreme dietary changes impact the microbiota and could therefore could be useful for assessing appropriate gut–brain targeted treatments
Towards a deeper integration of ZooMS and zooarchaeology at Paleolithic sites: current challenges and future directions
Get PDFAdvances in biomolecular methods, in particular the study of ancient proteins (paleoproteomics), have revolutionized how we can taxonomically identify archaeological bone fragments. Alongside traditional zooarchaeological assignments based on the visual inspection of morphological criteria, variations in collagen type I amino acid sequences can now be used to distinguish which animal a bone fragment belonged to. Using MALDI-ToF mass spectrometry, this method, known as Zooarchaeology by Mass Spectrometry (ZooMS), is now being applied regularly to archaeological faunal assemblages and, often at a large-scale, at Paleolithic sites. However, detailed explorations of how these ZooMS datasets can best be integrated with zooarchaeological and taphonomic data are only in their infancy. To further advance this field, we hosted a workshop at the University of Kent in 2023, bringing together both zooarchaeologists and ZooMS specialists, to showcase and discuss various ways of integrating ZooMS and zoo-archaeological data, especially within Paleolithic contexts. This special issue results from the papers presented at this workshop. In this introductory paper we reflect on the open discussion sessions that formed an essential part of the workshop. First, we discuss a series of methodological challenges; this includes the recording of zooarchaeology and taphonomy on morphologically unidentifiable bone fragments, ZooMS study design and sample selection, pre-screening and sampling, pre-treatment and collagen extraction, and the acquisition, processing, and interpretation of MALDI data. Second, we delve deeper into the interpretive potential, and the wealth of future research directions, of a full contribution of ZooMS to a range of zooarchaeological research topics. In concordance with the seven research papers in this issue, this introduction illustrates how a well-designed study, integrating zooarchaeological and taphonomic observations across both the morphological and ZooMS-identified fractions, cannot only increase the number of identifiable specimens at a site, but also provide novel insights into site formation histories, collection biases, carnivore behavior, environmental conditions, and past human subsistence, including site use, seasonality, carcass transport, prey preference, and butchery practices