A derivative-free optimisation method for global ocean biogeochemical models

The skill of global ocean biogeochemical models, and the earth system models in which they are embedded, can be improved by systematic calibration of the parameter values against observations. However, such tuning is seldom undertaken as these models are computationally very expensive. Here we investigate the performance of DFO-LS, a local, derivative-free optimisation algorithm which has been designed for computationally expensive models with irregular model–data misfit landscapes typical of biogeochemical models. We use DFO-LS to calibrate six parameters of a relatively complex global ocean biogeochemical model (MOPS) against synthetic dissolved oxygen, phosphate and nitrate “observations” from a reference run of the same model with a known parameter configuration. The performance of DFO-LS is compared with that of CMA-ES, another derivative-free algorithm that was applied in a previous study to the same model in one of the first successful attempts at calibrating a global model of this complexity. We find that DFO-LS successfully recovers five of the six parameters in approximately 40 evaluations of the misfit function (each one requiring a 3000-year run of MOPS to equilibrium), while CMA-ES needs over 1200 evaluations. Moreover, DFO-LS reached a “baseline” misfit, defined by observational noise, in just 11–14 evaluations, whereas CMA-ES required approximately 340 evaluations. We also find that the performance of DFO-LS is not significantly affected by observational sparsity, however fewer parameters were successfully optimised in the presence of observational uncertainty. The results presented here suggest that DFO-LS is sufficiently inexpensive and robust to apply to the calibration of complex, global ocean biogeochemical models

Influence of GEOTRACES data distribution and misfit function choice on objective parameter retrieval in a marine zinc cycle model

Biogeochemical model behaviour for micronutrients is typically hard to constrain because of the sparsity of observational data, the difficulty of determining parameters in situ, and uncertainties in observations and models. Here, we assess the influence of data distribution, model uncertainty, and the misfit function on objective parameter optimisation in a model of the oceanic cycle of zinc (Zn), an essential micronutrient for marine phytoplankton with a long whole-ocean residence time. We aim to investigate whether observational constraints are sufficient for reconstruction of biogeochemical model behaviour, given that the Zn data coverage provided by the GEOTRACES Intermediate Data Product 2017 is sparse. Furthermore, we aim to assess how optimisation results are affected by the choice of the misfit function and by confounding factors such as analytical uncertainty in the data or biases in the model related to either seasonal variability or the larger-scale circulation. The model framework applied herein combines a marine Zn cycling model with a state-of-the-art estimation of distribution algorithm (Covariance Matrix Adaption Evolution Strategy, CMA-ES) to optimise the model towards synthetic data in an ensemble of 26 optimisations. Provided with a target field that can be perfectly reproduced by the model, optimisation retrieves parameter values perfectly regardless of data coverage. As differences between the model and the system underlying the target field increase, the choice of the misfit function can greatly impact optimisation results, while limitation of data coverage is in most cases of subordinate significance. In cases where optimisation to full or limited data coverage produces relatively distinct model behaviours, we find that applying a misfit metric that compensates for differences in data coverage between ocean basins considerably improves agreement between optimisation results obtained with the two data situations

New insights into Neolithic milk consumption through proteomic analysis of dental calculus

There has long been debate over the origins of dairy consumption within European populations. Whilst it was previously assumed that lactase persistence (LP) was under positive selection following the advent of agriculture, recent genetic studies of prehistoric human remains have revealed LP may have only emerged in Europe in the last 4000 years. These findings stand in contrast to organic residue analysis of Neolithic pottery indicating the utilisation of dairy products, and zooarchaeological mortality profiles consistent with dairying herds at Neolithic sites. The recent discovery of the milk protein β-lactoglobulin (BLG) within human dental calculus presents a new method via which to explore dairy product consumption in the archaeological past. Here, we apply shotgun proteomic analysis to dental calculus samples from three British Neolithic sites, revealing the earliest identification of BLG in human dental calculus to date. The presence of BLG peptides in individuals who are unlikely to possess LP provides new insight into dairying in the British Neolithic, suggesting the potential processing of milk by Neolithic populations to reduce the lactose content of dairy products

Archaeological bone lipids as palaeodietary markers

Rationale Stable isotope analysis of archaeological and fossil bone samples can provide important insights into past environments, ecologies and diets. Previous studies have focused on stable carbon and nitrogen isotopes in bone collagen, or carbon isotopes in bone mineral (bioapatite). Carbon isotope analysis of lipids from archaeological bone has received much less attention, partly due to the lack of suitable methodologies allowing sufficient recovery of compounds for structural and isotopic characterisation. Here we show that lipids can be easily and reliably recovered from archaeological bone using a modified protocol, and that these provide complementary dietary information to other bone components. Methods Human and animal bones were obtained from a variety of archaeological contexts. Lipids were sequentially extracted using solvent extraction (dichloromethane/methanol), followed by acidified methanol extraction (methanol/H2SO4). The lipids were then analysed by gas chromatography/mass spectrometry (GC/MS) and gas chromatography/combustion/isotope ratio mass spectrometry (GC/C/IRMS). Results Appreciable amounts of endogenous lipid were recovered from archaeological bone. Importantly, a comparison between compound-specific and bulk collagen isotopic data shows that archaeological bone lipids reflect dietary input and can be used to distinguish between marine and terrestrial consumers, as well as between C3 and C4 plant consumers. Furthermore, the presence of essential fatty acids directly incorporated from diet to bone may provide additional palaeodietary information. Conclusions Our findings suggest that archaeological bone lipids are a hitherto untapped resource of dietary information that offer additional insights to those gained from other isotopic analyses of bone

Pathways and timescales of Southern Ocean hydrothermal iron and manganese transport

Scarcity of iron and manganese limits the efficiency of the biological carbon pump over large areas of the Southern Ocean. The importance of hydrothermal vents as a source of these micronutrients to the euphotic zone of the Southern Ocean is debated. Here we present full depth profiles of dissolved and total dissolvable trace metals in the remote eastern Pacific sector of the Southern Ocean (55–60° S, 89.1° W), providing evidence of enrichment of iron and manganese at depths of 2000–4000 m. These enhanced micronutrient concentrations were co-located with 3He enrichment, an indicator of hydrothermal fluid originating from ocean ridges. Modelled water trajectories revealed the understudied South East Pacific Rise and the Pacific Antarctic Ridge as likely source regions. Additionally, the trajectories demonstrate pathways for these Southern Ocean hydrothermal ridge-derived trace metals to reach the Southern Ocean surface mixed layer within two decades, potentially supporting a regular supply of micronutrients to fuel Southern Ocean primary production

Ancient chicken remains reveal the origins of virulence in Marek’s disease virus

The pronounced growth in livestock populations since the 1950s has altered the epidemiological and evolutionary trajectory of their associated pathogens. For example, Marek’s disease virus (MDV), which causes lymphoid tumors in chickens, has experienced a marked increase in virulence over the past century. Today, MDV infections kill >90% of unvaccinated birds, and controlling it costs more than US$1 billion annually. By sequencing MDV genomes derived from archeological chickens, we demonstrate that it has been circulating for at least 1000 years. We functionally tested the Meq oncogene, one of 49 viral genes positively selected in modern strains, demonstrating that ancient MDV was likely incapable of driving tumor formation. Our results demonstrate the power of ancient DNA approaches to trace the molecular basis of virulence in economically relevant pathogens

Ancient genomes indicate population replacement in Early Neolithic Britain

The roles of migration, admixture and acculturation in the European transition to farming have been debated for over 100 years. Genome-wide ancient DNA studies indicate predominantly Aegean ancestry for continental Neolithic farmers, but also variable admixture with local Mesolithic hunter-gatherers. Neolithic cultures first appear in Britain circa 4000 bc, a millennium after they appeared in adjacent areas of continental Europe. The pattern and process of this delayed British Neolithic transition remain unclear. We assembled genome-wide data from 6 Mesolithic and 67 Neolithic individuals found in Britain, dating 8500–2500 bc. Our analyses reveal persistent genetic affinities between Mesolithic British and Western European hunter-gatherers. We find overwhelming support for agriculture being introduced to Britain by incoming continental farmers, with small, geographically structured levels of hunter-gatherer ancestry. Unlike other European Neolithic populations, we detect no resurgence of hunter-gatherer ancestry at any time during the Neolithic in Britain. Genetic affinities with Iberian Neolithic individuals indicate that British Neolithic people were mostly descended from Aegean farmers who followed the Mediterranean route of dispersal. We also infer considerable variation in pigmentation levels in Europe by circa 6000 bc

A time-resolved proteomic and prognostic map of COVID-19.

COVID-19 is highly variable in its clinical presentation, ranging from asymptomatic infection to severe organ damage and death. We characterized the time-dependent progression of the disease in 139 COVID-19 inpatients by measuring 86 accredited diagnostic parameters, such as blood cell counts and enzyme activities, as well as untargeted plasma proteomes at 687 sampling points. We report an initial spike in a systemic inflammatory response, which is gradually alleviated and followed by a protein signature indicative of tissue repair, metabolic reconstitution, and immunomodulation. We identify prognostic marker signatures for devising risk-adapted treatment strategies and use machine learning to classify therapeutic needs. We show that the machine learning models based on the proteome are transferable to an independent cohort. Our study presents a map linking routinely used clinical diagnostic parameters to plasma proteomes and their dynamics in an infectious disease

A time-resolved proteomic and prognostic map of COVID-19

COVID-19 is highly variable in its clinical presentation, ranging from asymptomatic infection to severe organ damage and death. We characterized the time-dependent progression of the disease in 139 COVID-19 inpatients by measuring 86 accredited diagnostic parameters, such as blood cell counts and enzyme activities, as well as untargeted plasma proteomes at 687 sampling points. We report an initial spike in a systemic inflammatory response, which is gradually alleviated and followed by a protein signature indicative of tissue repair, metabolic reconstitution, and immunomodulation. We identify prognostic marker signatures for devising risk-adapted treatment strategies and use machine learning to classify therapeutic needs. We show that the machine learning models based on the proteome are transferable to an independent cohort. Our study presents a map linking routinely used clinical diagnostic parameters to plasma proteomes and their dynamics in an infectious disease

Ancient chicken remains reveal the origins of virulence in Marek’s 2 disease virus

The dramatic growth in livestock populations since the 1950s has altered the epidemiological and evolutionary trajectory of their associated pathogens. For example, Marek’s disease virus (MDV), which causes lymphoid tumors in chickens, has experienced a marked increase in virulence over the last century. Today, MDV infections kill >90% of unvaccinated birds and controlling it costs >US$1bn annually. By sequencing MDV genomes derived from archeological chickens, we demonstrate that it has been circulating for at least 1000 years. We functionally tested the Meq oncogene, one of 49 viral genes positively selected in modern strains, demonstrating that ancient MDV was likely incapable of driving tumor formation. Our results demonstrate the power of ancient DNA approaches to trace the molecular basis of virulence in economically relevant pathogens