Field experimental evidence that grazers mediate transition between microalgal and seagrass dominance

We tested the relative effects of nutrient loading, reduced predation, and reduced grazing on eelgrass community dynamics in Chesapeake Bay and found evidence supporting the mutualistic mesograzer model in which small invertebrate grazers control accumulation of epiphytic algae, buffer eutrophication effects, and thus facilitate seagrass dominance. Experimental reduction of crustacean grazers in the field stimulated a nearly sixfold increase in epiphytic algae, and reduced seagrass biomass by 65% compared to controls with grazers. Nutrient fertilization generally had much weaker effects, but an interaction with mesograzers was key in changing the sign of fertilization effects on the system: aboveground eelgrass biomass was reduced by fertilization under reduced grazing, but increased by fertilization under ambient grazing. When protected from predators in field cages, these mesograzers limited epiphyte blooms even with nutrient enrichment, and nutrients instead enhanced grazer secondary production. Crustacean mesograzers play a key role in maintaining macrophyte (seagrass) dominance in Chesapeake Bay, in buffering eelgrass against eutrophication, and in efficiently transferring nitrogen to higher trophic levels. Yet, these crustacean grazers are also highly sensitive to predator abundance. Reducing nutrient pollution alone is unlikely to restore seagrass meadows where alterations to food webs have reduced populations of algae-feeding mesograzers. Integration of both water quality and fishery management will be more effective in restoring and maintaining healthy coastal ecosystems

Top-down and bottom-up controls on sediment organic matter composition in an experimental seagrass ecosystem

We tested the singular and interactive effects of resource availability (light) and community composition (food chain length and herbivore species richness) on eelgrass (Zostera marina) ecosystem properties and functioning with an experimental mesocosm system. Food chain length was manipulated through the presence or absence of blue crab (Callinectes sapidus) predators, whereas grazer species richness varied across three levels (zero, two, or four crustacean species). We found important and interacting effects of bottom-up and top-down forcings on sediment organic matter (SOM) composition. Light increased eelgrass and algal biomass and sediment organic carbon and nitrogen content. Increasing grazer diversity generally decreased algal biomass and ecosystem production but interacted with food chain length (i.e., presence of predatory crabs) and light. Predators generally increased algal biomass and ecosystem production through a trophic cascade, which was stronger at high grazer diversity and under ambient light. SOM composition, determined with fatty acid (FA) biomarkers, was sensitive to all manipulated variables. Increasing grazer species richness often decreased the contributions of FAs derived from plant and algal sources, whereas increasing light had the opposite effect. Food chain length was generally a less important determinant of SOM composition than light, although predators did increase FAs representative of heterotrophic bacteria. Overall, resource availability and epibenthic community composition strongly influenced organic matter cycling, SOM composition, and the bacterial community in seagrass-bed sediments

Opinion Piece: The case for establishing a minimal medication alternative for psychosis and schizophrenia

The development of severe mental health conditions is strongly linked to our environments, particularly experiences of trauma and adversity. However treatments for severe mental health conditions are often primarily biomedical, centred around medication. For people diagnosed with schizophrenia or psychosis, this is antipsychotic medication. Although antipsychotics have been found to reduce symptoms and risk of relapse, some patients derive little benefit from these drugs, and they can lead to severe adverse effects. Subsequently, a high proportion of people do not want to take antipsychotics and request an alternative. Yet in the UK and in many countries there are currently no guidelines for stopping antipsychotics or formal treatment alternatives, despite such alternatives being available in some countries. For example, in Norway and Vermont (USA), in response to pressure from service user organisations, governments have mandated the establishment of “minimal medication” services. We examine whether everyone with a psychotic condition needs long-term antipsychotic treatment and evidence for alternative models of care. We recommend that healthcare providers should be encouraged to develop a psychosocial treatment package for people with psychosis or schizophrenia that provides a realistic possibility of minimising antipsychotic exposure

Forecasting in the light of Big Data

Predicting the future state of a system has always been a natural motivation for science and practical applications. Such a topic, beyond its obvious technical and societal relevance, is also interesting from a conceptual point of view. This owes to the fact that forecasting lends itself to two equally radical, yet opposite methodologies. A reductionist one, based on the first principles, and the naive inductivist one, based only on data. This latter view has recently gained some attention in response to the availability of unprecedented amounts of data and increasingly sophisticated algorithmic analytic techniques. The purpose of this note is to assess critically the role of big data in reshaping the key aspects of forecasting and in particular the claim that bigger data leads to better predictions. Drawing on the representative example of weather forecasts we argue that this is not generally the case. We conclude by suggesting that a clever and context-dependent compromise between modelling and quantitative analysis stands out as the best forecasting strategy, as anticipated nearly a century ago by Richardson and von Neumann

Combining density functional theory (DFT) and collision cross-section (CCS) calculations to analyze the gas-phase behaviour of small molecules and their protonation site isomers

Electrospray ion mobility-mass spectrometry (IM-MS) data show that for some small molecules, two (or even more) ions with identical sum formula and mass, but distinct drift times are observed. In spite of showing their own unique and characteristic fragmentation spectra in MS/MS, no configurational or constitutional isomers are found to be present in solution. Instead the observation and separation of such ions appears to be inherent to their gas-phase behaviour during ion mobility experiments. The origin of multiple drift times is thought to be the result of protonation site isomers ('protomers'). Although some important properties of protomers have been highlighted by other studies, correlating the experimental collision cross-sections (CCSs) with calculated values has proven to be a major difficulty. As a model, this study uses the pharmaceutical compound melphalan and a number of related molecules with alternative (gas-phase) protonation sites. Our study combines density functional theory (DFT) calculations with modified MobCal methods (e.g. nitrogen-based Trajectory Method algorithm) for the calculation of theoretical CCS values. Calculated structures can be linked to experimentally observed signals, and a strong correlation is found between the difference of the calculated dipole moments of the protomer pairs and their experimental CCS separation

A CDCL-style calculus for solving non-linear constraints

In this paper we propose a novel approach for checking satisfiability of non-linear constraints over the reals, called ksmt. The procedure is based on conflict resolution in CDCL style calculus, using a composition of symbolical and numerical methods. To deal with the non-linear components in case of conflicts we use numerically constructed restricted linearisations. This approach covers a large number of computable non-linear real functions such as polynomials, rational or trigonometrical functions and beyond. A prototypical implementation has been evaluated on several non-linear SMT-LIB examples and the results have been compared with state-of-the-art SMT solvers.Comment: 17 pages, 3 figures; accepted at FroCoS 2019; software available at <http://informatik.uni-trier.de/~brausse/ksmt/

30 days wild: development and evaluation of a large-scale nature engagement campaign to improve well-being

There is a need to increase people’s engagement with and connection to nature, both for human well-being and the conservation of nature itself. In order to suggest ways for people to engage with nature and create a wider social context to normalise nature engagement, The Wildlife Trusts developed a mass engagement campaign, 30 Days Wild. The campaign asked people to engage with nature every day for a month. 12,400 people signed up for 30 Days Wild via an online sign-up with an estimated 18,500 taking part overall, resulting in an estimated 300,000 engagements with nature by participants. Samples of those taking part were found to have sustained increases in happiness, health, connection to nature and pro-nature behaviours. With the improvement in health being predicted by the improvement in happiness, this relationship was mediated by the change in connection to nature

Vortex detection and quantum transport in mesoscopic graphene Josephson-junction arrays

We investigate mesoscopic Josephson junction arrays created by patterning superconducting disks on monolayer graphene, concentrating on the high-$T/T_c$ regime of these devices and the phenomena which contribute to the superconducting glass state in diffusive arrays. We observe features in the magnetoconductance at rational fractions of flux quanta per array unit cell, which we attribute to the formation of flux-quantized vortices. The applied fields at which the features occur are well described by Ginzburg-Landau simulations that take into account the number of unit cells in the array. We find that the mean conductance and universal conductance fluctuations are both enhanced below the critical temperature and field of the superconductor, with greater enhancement away from the graphene Dirac point.This work was financially supported by the Engineering and Physical Sciences Research Council, and an NPL/EPSRC Joint Postdoctoral Partnership (RG61493).This is the accepted manuscript. The final version is available at http://journals.aps.org/prb/abstract/10.1103/PhysRevB.91.245418

On the Considerations of Using Near Real Time Data for Space Weather Hazard Forecasting

Space weather represents a severe threat to ground-based infrastructure, satellites and communications. Accurately forecasting when such threats are likely (e.g., when we may see large induced currents) will help to mitigate the societal and financial costs. In recent years computational models have been created that can forecast hazardous intervals, however they generally use post-processed “science” solar wind data from upstream of the Earth. In this work we investigate the quality and continuity of the data that are available in Near-Real-Time (NRT) from the Advanced Composition Explorer and Deep Space Climate Observatory (DSCOVR) spacecraft. In general, the data available in NRT corresponds well with post-processed data, however there are three main areas of concern: greater short-term variability in the NRT data, occasional anomalous values and frequent data gaps. Some space weather models are able to compensate for these issues if they are also present in the data used to fit (or train) the model, while others will require extra checks to be implemented in order to produce high quality forecasts. We find that the DSCOVR NRT data are generally more continuous, though they have been available for small fraction of a solar cycle and therefore DSCOVR has experienced a limited range of solar wind conditions. We find that short gaps are the most common, and are most frequently found in the plasma data. To maximize forecast availability we suggest the implementation of limited interpolation if possible, for example, for gaps of 5 min or less, which could increase the fraction of valid input data considerably