Effective management of ecological resilience – are we there yet?

1. Ecological resilience is developing into a credible paradigm for policy development and environmental management for preserving natural capital in a rapidly changing world. However, resilience emerges from complex interactions, limiting the translation of theory into practice. 2. Main limitations include the following: (i) difficulty in quantification and detection of changes in ecological resilience, (ii) a lack of empirical evidence to support preventative or proactive management and (iii) difficulties in managing processes operating across socio-ecological systems that vary in space and time. 3. We highlight recent research with the potential to address these limitations including new and/or improved indicators of resilience and tools to assess scale as a driver of resilience. 4. Synthesis and applications. Effective resilience-based management must be adaptive in nature. To support this, we propose an operational model using resilience-based iterative management actions operating across scales

A cookbook for using model diagnostics in integrated stock assessments

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Sequential multiplex PCR assay for determining capsular serotypes of colonizing S. pneumoniae

Asymptomatic nasopharyngeal carriage represents an important biological marker for monitoring pneumococcal serotype distribution and evaluating vaccine effects. Serotype determination by conventional method (Quellung reaction) is technically and financially challenging. On the contrary, PCR-based serotyping represents a simple, economic and promising alternative method.Evaluation StudiesJournal ArticleResearch Support, Non-U.S. Gov'tSCOPUS: ar.jinfo:eu-repo/semantics/publishe

Assessing climate change impacts on the water quality of Scottish standing waters

The aim of this project was to assess the key evidence available to improve understanding of climate change impacts on the water quality of Scottish standing waters. Recommendations were made on changes needed to adapt water policy and monitoring networks as part of Scotland’s response to the climate crisis

Nutrient and microbial water quality of the upper Ganga river, India: identification of pollution sources

The Ganga River is facing mounting environmental pressures due to rapidly increasing human population, urbanisation, industrialisation and agricultural intensification, resulting in worsening water quality, ecological status and impacts on human health. A combined inorganic chemical, algal and bacterial survey (using flow cytometry and 16S rRNA gene sequencing) along the upper and middle Ganga (from the Himalayan foothills to Kanpur) was conducted under pre-monsoon conditions. The upper Ganga had total phosphorus (TP) and total dissolved nitrogen concentrations of less than 100 μg l−1 and 1.0 mg l−1, but water quality declined at Kannauj (TP = 420 μg l−1) due to major nutrient pollution inputs from human-impacted tributaries (principally the Ramganga and Kali Rivers). The phosphorus and nitrogen loads in these two tributaries and the Yamuna were dominated by soluble reactive phosphorus and ammonium, with high bacterial loads and large numbers of taxa indicative of pathogen and faecal organisms, strongly suggesting sewage pollution sources. The high nutrient concentrations, low flows, warm water and high solar radiation resulted in major algal blooms in the Kali and Ramganga, which greatly impacted the Ganga. Microbial communities were dominated by members of the Phylum Proteobacteria, Bacteriodetes and Cyanobacteria, with communities showing a clear upstream to downstream transition in community composition. To improve the water quality of the middle Ganga, and decrease ecological and human health risks, future mitigation must reduce urban wastewater inputs in the urbanised tributaries of the Ramganga, Kali and Yamuna Rivers

Genomic, Pathway Network, and Immunologic Features Distinguishing Squamous Carcinomas

This integrated, multiplatform PanCancer Atlas study co-mapped and identified distinguishing molecular features of squamous cell carcinomas (SCCs) from five sites associated with smokin

Storm impacts on phytoplankton community dynamics in lakes

In many regions across the globe, extreme weather events such as storms have increased in frequency, intensity, and duration due to climate change. Ecological theory predicts that such extreme events should have large impacts on ecosystem structure and function. High winds and precipitation associated with storms can affect lakes via short-term runoff events from watersheds and physical mixing of the water column. In addition, lakes connected to rivers and streams will also experience flushing due to high flow rates. Although we have a well-developed understanding of how wind and precipitation events can alter lake physical processes and some aspects of biogeochemical cycling, our mechanistic understanding of the emergent responses of phytoplankton communities is poor. Here we provide a comprehensive synthesis that identifies how storms interact with lake and watershed attributes and their antecedent conditions to generate changes in lake physical and chemical environments. Such changes can restructure phytoplankton communities and their dynamics, as well as result in altered ecological function (e.g., carbon, nutrient and energy cycling) in the short- and long-term. We summarize the current understanding of storm-induced phytoplankton dynamics, identify knowledge gaps with a systematic review of the literature, and suggest future research directions across a gradient of lake types and environmental conditions.Peer reviewe

Pan-Cancer Analysis of lncRNA Regulation Supports Their Targeting of Cancer Genes in Each Tumor Context

Long noncoding RNAs (lncRNAs) are commonly dys-regulated in tumors, but only a handful are known toplay pathophysiological roles in cancer. We inferredlncRNAs that dysregulate cancer pathways, onco-genes, and tumor suppressors (cancer genes) bymodeling their effects on the activity of transcriptionfactors, RNA-binding proteins, and microRNAs in5,185 TCGA tumors and 1,019 ENCODE assays.Our predictions included hundreds of candidateonco- and tumor-suppressor lncRNAs (cancerlncRNAs) whose somatic alterations account for thedysregulation of dozens of cancer genes and path-ways in each of 14 tumor contexts. To demonstrateproof of concept, we showed that perturbations tar-geting OIP5-AS1 (an inferred tumor suppressor) andTUG1 and WT1-AS (inferred onco-lncRNAs) dysre-gulated cancer genes and altered proliferation ofbreast and gynecologic cancer cells. Our analysis in-dicates that, although most lncRNAs are dysregu-lated in a tumor-specific manner, some, includingOIP5-AS1, TUG1, NEAT1, MEG3, and TSIX, synergis-tically dysregulate cancer pathways in multiple tumorcontexts

Spatial Organization and Molecular Correlation of Tumor-Infiltrating Lymphocytes Using Deep Learning on Pathology Images

Beyond sample curation and basic pathologic characterization, the digitized H&E-stained images of TCGA samples remain underutilized. To highlight this resource, we present mappings of tumorinfiltrating lymphocytes (TILs) based on H&E images from 13 TCGA tumor types. These TIL maps are derived through computational staining using a convolutional neural network trained to classify patches of images. Affinity propagation revealed local spatial structure in TIL patterns and correlation with overall survival. TIL map structural patterns were grouped using standard histopathological parameters. These patterns are enriched in particular T cell subpopulations derived from molecular measures. TIL densities and spatial structure were differentially enriched among tumor types, immune subtypes, and tumor molecular subtypes, implying that spatial infiltrate state could reflect particular tumor cell aberration states. Obtaining spatial lymphocytic patterns linked to the rich genomic characterization of TCGA samples demonstrates one use for the TCGA image archives with insights into the tumor-immune microenvironment