An exposure-effect approach for evaluating ecosystem-wide risks from human activities

Ecosystem-based management (EBM) is promoted as the solution for sustainable use. An ecosystem-wide assessment methodology is therefore required. In this paper, we present an approach to assess the risk to ecosystem components from human activities common to marine and coastal ecosystems. We build on: (i) a linkage framework that describes how human activities can impact the ecosystem through pressures, and (ii) a qualitative expert judgement assessment of impact chains describing the exposure and sensitivity of ecological components to those activities. Using case study examples applied at European regional sea scale, we evaluate the risk of an adverse ecological impact from current human activities to a suite of ecological components and, once impacted, the time required for recovery to pre-impact conditions should those activities subside. Grouping impact chains by sectors, pressure type, or ecological components enabled impact risks and recovery times to be identified, supporting resource managers in their efforts to prioritize threats for management, identify most at-risk components, and generate time frames for ecosystem recovery

Discovery of blood transcriptomic markers for depression in animal models and pilot validation in subjects with early-onset major depression

Early-onset major depressive disorder (MDD) is a serious and prevalent psychiatric illness in adolescents and young adults. Current treatments are not optimally effective. Biological markers of early-onset MDD could increase diagnostic specificity, but no such biomarker exists. Our innovative approach to biomarker discovery for early-onset MDD combined results from genome-wide transcriptomic profiles in the blood of two animal models of depression, representing the genetic and the environmental, stress-related, etiology of MDD. We carried out unbiased analyses of this combined set of 26 candidate blood transcriptomic markers in a sample of 15–19-year-old subjects with MDD (N=14) and subjects with no disorder (ND, N=14). A panel of 11 blood markers differentiated participants with early-onset MDD from the ND group. Additionally, a separate but partially overlapping panel of 18 transcripts distinguished subjects with MDD with or without comorbid anxiety. Four transcripts, discovered from the chronic stress animal model, correlated with maltreatment scores in youths. These pilot data suggest that our approach can lead to clinically valid diagnostic panels of blood transcripts for early-onset MDD, which could reduce diagnostic heterogeneity in this population and has the potential to advance individualized treatment strategies

Comorbid mental disorders in substance users from a single catchment area - a clinical study

<p>Abstract</p> <p>Background</p> <p>The optimal treatment of patients with substance use disorders (SUDs) requires an awareness of their comorbid mental disorders and vice versa. The prevalence of comorbidity in first-time-admitted SUD patients has been insufficiently studied. Diagnosing comorbidity in substance users is complicated by symptom overlap, symptom fluctuations, and the limitations of the assessment methods. The aim of this study was to diagnose all mental disorders in substance users living in a single catchment area, without any history of treatment for addiction or psychiatric disorders, admitted consecutively to the specialist health services. The prevalence of substance-induced versus substance-independent disorders according to the Diagnostic and Statistical Manual of Mental Disorders, Fourth Edition (DSM-IV), in SUD patients will be described.</p> <p>Methods</p> <p>First-time consecutively admitted patients from a single catchment area, aged 16 years or older, admitted to addiction clinics or departments of psychiatry as outpatients or inpatients will be screened for substance-related problems using the Alcohol Use Disorder Identification Test and the Drug Use Disorder Identification Test. All patients with scores above the cutoff value will be asked to participate in the study. The patients included will be diagnosed for SUD and other axis I disorders by a psychiatrist using the Psychiatric Research Interview for Substance and Mental Disorders. This interview was designed for the diagnosis of primary and substance-induced disorders in substance users. Personality disorders will be assessed according to the Structured Clinical Interview for DSM-IV axis II disorders. The Symptom Checklist-90-Revised, the Inventory of Depressive Symptoms, the Montgomery Asberg Depression Rating Scale, the Young Mania Rating Scale, and the Angst Hypomania Check List will be used for additional diagnostic assessments. The sociodemographic data will be recorded with the Stanley Foundation's Network Entry Questionnaire. Biochemical assessments will reveal somatic diseases that may contribute to the patient's symptoms.</p> <p>Discussion</p> <p>This study is unique because the material represents a complete sample of first-time-admitted treatment seekers with SUD from a single catchment area. Earlier studies have not focused on first-time-admitted patients, so chronically ill patients, may have been overrepresented in those samples. This study will contribute new knowledge about mental disorders in first-time-admitted SUD patients.</p

How to measure the economic impacts of changes in growth, feed efficiency and survival in aquaculture

In this article we introduce a variety of bio-economic models that can be used to calculate the economic benefits associated with improved productivity in aquaculture. In the aquaculture industry, three important biological productivity factors are growth, survival and feed efficiency. The profitability of improving productivity factors, especially growth, is highly dependent upon the cost factor structure, production system, its constraints and other factors within the supply chain. Therefore we present a number of different bio-economical models that can be used to robustly assess the economic impacts in different production environments. These models are introduced with case examples across a range of aquaculture species and production systems. We calculate changes in profitability through a reduction in production costs and any potential increases in product price premiums via the use of weight dependent unit profit as the outcome in cost-benefit analysis, so that results may be expanded to cover different volumes

Optimising sampling frequency for monitoring heterotrophic protists in a marine ecosystem

Heterotrophic protists are essential components of the marine ecosystem, yet they are often excluded from monitoring programmes. With limited resources, monitoring strategies need to be optimised considering both scientific knowledge and available resources. In doing so, it is crucial to understand how sampling frequency affects the value of the data. We analysed 11 years of weekly heterotrophic protist time-series data from Station L4 in the Western English Channel to explore how different sampling intervals impact data quality. In the L4 dataset, comprising 55 protist taxa, the reduction of sampling frequency from weekly to four times a year at specific seasons decreased the number of taxa encountered by 38% for ciliates and 29% for heterotrophic dinoflagellates while the mean annual biomass or its mean variation were not affected. Furthermore, when samples were taken only four times a year, biomass peaks of the ten most important taxa were often missed. The primary motivator for this study was furthering the development of the heterotrophic protist monitoring in temperate and subarctic marine areas, e.g. the Baltic Sea. Based on our findings, we give recommendations on sampling frequency to optimise the value of heterotrophic protist monitoring