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The Arctic is changing rapidly due to the amplification of global temperature trends, causing profound impacts on the ice sheet in Greenland, glaciers, frozen ground, ecosystems, and societies. Here, we focus on impacts that atmospheric circulation causes in addition to the climate warming trends. We combine time series of glacier mass balance from temporal satellite gravimetry measurements (GRACE/GRACE-FO; 2002–2023), active layer thickness in permafrost areas from ESA’s Climate Change Initiative remote sensing and modelling product (2003–2019), and field measurements of the Circumpolar Active Layer Monitoring Network (2002–2023). Despite regional and system-related complexities, we identify robust covariations between these observations, which vary asynchronously between neighbouring regions and synchronously in regions antipodal to the North Pole. We reveal a close connection with dominant modes of atmosphere circulation, controlling about 75% of the common pan-Arctic impact variability (2002–2022), also affecting the Greenland Ice Sheet. We emphasize that it is necessary to consider such atmospheric driving patterns when projecting impacts, particularly caused by extremes, in an increasingly warmer Arctic.

Biomarkers lie at the heart of precision medicine. Surprisingly, while rapid genomic profiling is becoming ubiquitous, the development of biomarkers usually involves the application of bespoke techniques that cannot be directly applied to other datasets. There is an urgent need for a systematic methodology to create biologically-interpretable molecular models that robustly predict key phenotypes. Here we present SIMMS (Subnetwork Integration for Multi-Modal Signatures): an algorithm that fragments pathways into functional modules and uses these to predict phenotypes. We apply SIMMS to multiple data types across five diseases, and in each it reproducibly identifies known and novel subtypes, and makes superior predictions to the best bespoke approaches. To demonstrate its ability on a new dataset, we profile 33 genes/nodes of the PI3K pathway in 1734 FFPE breast tumors and create a four-subnetwork prediction model. This model out-performs a clinically-validated molecular test in an independent cohort of 1742 patients. SIMMS is generic and enables systematic data integration for robust biomarker discovery. Accurate and actionable biomarkers that integrate diverse molecular, functional and clinical information hold great promise in precision medicine. Here, the authors develop SIMMS, a method for pathway-based cross-disease biomarker discovery.

[...]the technical paper seeks to support achievement of the 2030 Agenda for Sustainable Development - specifically SDG Target 14.b: \"Provide access for smallscale artisanal fishers to marine resources and markets\"; and SDG Target 2.3: \"By 2030 double the agricultural productivity and the incomes of small-scale food producers, particularly women, indigenous peoples, family farmers, pastoralists and fishers, including through secure and equal access to land, other productive resources and inputs, knowledge, financial services, markets and opportunities for value addition and non-farm employment\". [...]FAO and all the authors wish to acknowledge the Governments of Norway and Sweden, whose generous support to the SSF Umbrella Programme made this publication possible. FT COFI Sub-Committee on Fish Trade CSF Community-supported fishery CSO Civil society organization ECOWAS Economic Community of Western African States EEZ Exclusive economic zone ETP Endangered, threatened and protected (species) FAC Fisheries Advisory Committee (Barbados) FAO Food and Agriculture Organization of the United Nations FCWC Fishery Committee for the West Central Gulf of Guinea FIP Fishery Improvement Project FIS Fishery Information System (Maldives) FishNET Fish Traders and Processors Network (FCWC) FLE Fisheries Learning Exchange FMM Flexible Multi-Partner Mechanism FODP Fisherfolk Organization Development Project (Barbados) FTP Fish Trade Project FTT FAO-Thiaroye processing technique FUI Fuel use intensity GHL Guideline harvest level GIFT Gender in Fisheries Team HCR Harvest Control Rules IFAD International Fund for Agricultural Development IPNLF International Pole and Line Foundation ITC International Trade Centre IOTC Indian Ocean Tuna Commission IUU Illegal, unreported and unregulated (fishing) KJS Kodiak Jig Seafoods MAP Alaska Sea Grant Marine Advisory Program MDPI Masyarakat dan Perikanan Indonesia MIFCO Maldives Industrial Fisheries Company MRHP Ministry of Fishery Resources (Ministere des Ressources Halieutiques et de la Peche, Madagascar) MSC Marine Stewardship Council MSY Maximum sustainable yield NEPAD New Partnership for Africa's Development NGO Non-governmental Organization NOAA National Oceanic and Atmospheric Administration NPFMC North Pacific Fishery Management Council NSGCP National Sea Grant College Program PAH Polycyclic aromatic hydrocarbons PFRS Policy Framework and Reform Strategy for Fisheries and Aquaculture in Africa PHL Post-harvest losses RASFF Rapid Alert System for Food and Feed RFMO Regional fisheries management organization SDGs Sustainable Development Goals SDM Seafood direct marketing SGEP Sea Grant Extension Program SSF Guidelines Voluntary Guidelines for Securing Sustainable Small-Scale Fisheries in the Context of Food Security and Poverty Eradication TAC Total allowable catch UNDP United Nations Development Programme UWI University of the West Indies VMS Vessel monitoring system Showcasing applied practices in value chains, post-harvest operations and trade The objective of this technical paper is to showcase applied practices and initiatives in support of enhancing small-scale fisheries value chains, post-harvest operations and trade, thus illustrating the relevant recommendations made in Chapter 7 of the SSF Guidelines. According to estimates, small-scale fisheries employ more than 90 percent of the approximately 120 million people employed in fisheries.

Biomarkers lie at the heart of precision medicine, biodiversity monitoring, agricultural pathogen detection, amongst others. Surprisingly, while rapid genomic profiling is becoming ubiquitous, the development of biomarkers almost always involves the application of bespoke techniques that cannot be directly applied to other datasets. There is an urgent need for a systematic methodology to create biologically-interpretable molecular models that robustly predict key phenotypes. We therefore created SIMMS: an algorithm that fragments pathways into functional modules and uses these to predict phenotypes. We applied SIMMS to multiple data-types across four diseases, and in each it reproducibly identified subtypes, made superior predictions to the best bespoke approaches, and identified known and novel signaling nodes. To demonstrate its ability on a new dataset, we measured 33 genes/nodes of the PIK3CA pathway in 1,734 FFPE breast tumours and created a four-subnetwork prediction model. This model significantly out-performed existing clinically-used molecular tests in an independent 1,742-patient validation cohort. SIMMS is generic and can work with any molecular data or biological network, and is freely available at: https://cran.r-project.org/web/packages/SIMMS.