Transitions of social-ecological subsistence systems in the Arctic

Transitions of social-ecological systems (SES) expose governance systems to new challenges. This is particularly so in the Arctic where resource systems are increasingly subjected to global warming, industrial development and globalization which subsequently alter the local SES dynamics. Based on common-pool resource theory, we developed a dynamic conceptual model explaining how exogenous drivers might alter a traditional subsistence system from a provisioning to an appropriation actions situation. In a provisioning action situation the resource users do not control the resource level but adapt to the fluctuating availability of resources, and the collective challenge revolve around securing the subsistence in the community. An increased harvest pressure enabled by exogenous drivers could transform the SES to an appropriation action situation where the collective challenge has changed to avoid overuse of a common-pool resource. The model was used as a focal lens to investigate the premises for broad-scale transitions of subsistence-oriented SESs in Arctic Alaska, Canada and Greenland. We synthesized data from documents, official statistics and grey and scientific literature to explore the different components of our model. Our synthesis suggests that the traditional Arctic subsistence SESs mostly comply with a provisioning action situation. Despite population growth and available technology; urbanization, increased wage labor and importation of food have reduced the resource demand, and we find no evidence for a broad-scale transition to an appropriation action situation throughout the Western Arctic. However, appropriation challenges have emerged in some cases either as a consequence of commercialization of the resource or by severely reduced resource stocks due to various exogenous drivers. Future transitions of SESs could be triggered by the emergence of commercial local food markets and Arctic warming. In particular, Arctic warming is an intensifying exogenous driver that is threatening many important Arctic wildlife resources inflicting increased appropriation challenges to the governance of local harvest.Ye

Scale-dependent response diversity of seabirds to prey in the North Sea

Functional response diversity is defined as the diversity of responses to environmental change among species that contribute to the same ecosystem function. Because different ecological processes dominate on different spatial and temporal scales, response diversity is likely to be scale dependent. Using three extensive data sets on seabirds, pelagic fish, and zooplankton, we investigate the strength and diversity in the response of seabirds to prey in the North Sea over three scales of ecological organization. Two-stage analyses were used to partition the variance in the abundance of predators and prey among the different scales of investigation: variation from year to year, variation among habitats, and variation on the local patch scale. On the year-to-year scale, we found a strong and synchronous response of seabirds to the abundance of prey, resulting in low response diversity. Conversely, as different seabird species were found in habitats dominated by different prey species, we found a high diversity in the response of seabirds to prey on the habitat scale. Finally, on the local patch scale, seabirds were organized in multispecies patches. These patches were weakly associated with patches of prey, resulting in a weak response strength and a low response diversity. We suggest that ecological similarities among seabird species resulted in low response diversity on the year-to-year scale. On the habitat scale, we suggest that high response diversity was due to interspecific competition and niche segregation among seabird species. On the local patch scale, we suggest that facilitation with respect to the detection and accessibility of prey patches resulted in overlapping distribution of seabirds but weak associations with prey. The observed scale dependencies in response strength and diversity have implications for how the seabird community will respond to different environmental disturbances

Taking movement data to new depths : Inferring prey availability and patch profitability from seabird foraging behavior

Funded byNatural Environment Research Council. Grant Number: NE/K007440/1 and Marine Scotland Science and Seabird Tracking and Research (STAR) Project led by the Royal Society for the Protection of Birds (RSPB)Peer reviewedPublisher PD

Estimation and simulation of foraging trips in land-based marine predators

The behavior of colony-based marine predators is the focus of much research globally. Large telemetry and tracking data sets have been collected for this group of animals, and are accompanied by many empirical studies that seek to segment tracks in some useful way, as well as theoretical studies of optimal foraging strategies. However, relatively few studies have detailed statistical methods for inferring behaviors in central place foraging trips. In this paper we describe an approach based on hidden Markov models, which splits foraging trips into segments labeled as “outbound”, “search”, “forage”, and “inbound”. By structuring the hidden Markov model transition matrix appropriately, the model naturally handles the sequence of behaviors within a foraging trip. Additionally, by structuring the model in this way, we are able to develop realistic simulations from the fitted model. We demonstrate our approach on data from southern elephant seals (Mirounga leonina) tagged on Kerguelen Island in the Southern Ocean. We discuss the differences between our 4-state model and the widely used 2-state model, and the advantages and disadvantages of employing a more complex model

Identifying a cross-cohort circulating microRNA signature for Lung Cancer prediction using Random Forests

Lungekreft er en sykdom hvor tidlig diagnose er spesielt viktig for pasientoverlevelse. Screeningteknikker som brukes i dag fokuserer ofte på pasienter i risikogrupper fordi de er invasive, kostbare og har lav spesifisitet. MikroRNA er små ikke-kodende RNA som sirkulerer i blod og har potensial som ikke-invasive biomarkører for en rekke ulike sykdommer. Disse små RNA-ene har viktige regulatoriske funskjoner i planter, virus og dyr, og det har blitt bevist at disse er differensielt uttrykt i mange ulike krefttyper, inkludert lungekreft. Nylige fremskritt innen sekvenseringsteknologi har muliggjort kvantifisering og identifisering av mikroRNA på massiv-parallel skala. Ved å sekvensere blodprøvene til pasienter for mikroRNA og deretter sammenstille disse dataene med deres prognostiske og diagnostiske utfall, kan man trene veiledete maskinlæringsmodeller som kan skille lungekreftspasienter fra kontroller ved å kun bruke mikroRNA som er uttrykt i pasientenes blodprøver. Denne type data fra fire europeiske longitudinelle kohorter, en diagnostisk og tre prediagnostiske, ble i denne studien brukt til å trene en slik modell som kan predikere lungekreft på tvers av kohorter og dermed brukes til diagnoseformål. Random forest er en maskinlæringsmetode som er spesielt velegnet til å modellere komplekse mikroRNA-ekspresjonsprofiler og som samtidig muligjør en grad av tolkbarhet i modellene: de viktigste mikroRNA-ene for prediksjoner kan hentes direkte ut fra modellen. Dette prosjektet er av en utforskende art: flere ulike eksperimenter ble gjennomført vedrørende ekstrahering av de mest interessante forklaringsvariablene og samplingmetodene. Hovedresultatet ble en random forest modell trent på en linærtransformert versjon av de prediagnostiske kohortene som kunne predikere lungekreft i den diagnostiske kohorten med relativt god spesifisitet og sensitivitet. De viktigste mikroRNA-ene fra denne modellen ble deretter videre analysert for deres rolle i biologiske og regulatoriske gennettverk, og disse gennettverkene viste seg å korrelere med kreftrelaterte nettverk. Videre arbeid og mer avanserte statistiske metoder er likevel nødvendig for å kunne modellere lungekreft i de prediagnostiske kohortene. Modeller som skiller diagnoser fra kontroller i disse kohortene vil være i stand til å predikere lungekreft opptil flere år før diagnosen blir satt med klassiske metoder, og denne typen modell vil være svært verdifull i medisinsk praksis.Lung cancer is a disease in which early diagnosis is of particular importance for patient survival. Current screening techniques are focused on at-risk populations because of their invasiveness, cost, and low specificity. MicroRNAs are small non-coding RNAs circulating in blood that hold potential as non-invasive biomarkers for many different diseases. These small RNAs have important regulatory functions in plants, viruses, and animals and have been proven to be differentially expressed in a wide range of human cancers - including lung cancer. Recent advances in sequencing technology has opened up for the identification and quantification of microRNA at massively parallel scales. By sequencing the microRNAs present in a patient's blood sample and pairing these with their diagnostic and prognostic outcomes, one could train supervised machine learning models that distinguish cancer patients from controls using only the microRNAs that are expressed in their blood samples. Using data of this kind from four European longitudinal cohort studies, three prediagnostic and one diagnostic, this study aimed to train such a model to create a cross-cohort lung cancer predictor that might be useful as a diagnostic tool. Random forests were found to be well suited for this task, as they can model the complex biological nature of the microRNA expression profiles while also adding a layer of interpretability; the most important features for doing predictions can be extracted directly from the model. This project is of an exploratory nature, and as such, many different experiments for feature extraction and sampling were carried out. The main finding was a random forest model that when trained on linearly transformed prediagnostic training data could predict lung cancer in a separate diagnostic cohort with fair specificity and sensitivity. This model's top microRNAs were then further analysed for their role in biological and regulatory gene pathways, and these were found to be cancer related. Further work and more advanced statistical methods are needed to model lung cancer in the prediagnostic cohorts. Models that perform well on the prediagnostic cohorts would be capable of predicting lung cancer years before current diagnostic techniques, and this kind of model would be highly valuable in medical practice

Nomenclatural checklist for Acromegalomma species (Annelida, Sabellidae), a nomen novum replacement for the junior homonym Megalomma Johansson, 1926

Este artículo contiene 20 páginas.Acromegalomma, nomen novum, is introduced as a replacement name for the polychaete genus Megalomma Johansson, 1926 (Annelida, Sabellidae), preoccupied by Megalomma Westwood, 1842 (Insecta, Coleoptera, Carabidae). The historical background of the homonymy and a full list with 36 new combinations in the new genus are included, while two species are considered as species inquirenda.This work was financially supported by the European Community's Seventh Framework Programme (FP7/2007-2013), through the Assemble Grant Agreement no. 227799-ASSEMBLE to the project “Biodiversity of Annelida Polychaeta in the Ria Formosa coastal lagoon: a baseline study”, awarded to J.G. and developed at the CCMAR, University of Algarve (Faro, Portugal).Peer reviewe

Extracurricular Entrepreneurship and Enterprise Education: What, How, Why, for Whom, and When?

publishedVersio

Global coordination and standardisation in marine biodiversity through the World Register of Marine Species (WoRMS) and related databases

The World Register of Marine Species is an over 90% complete open-access inventory of all marine species names. Here we illustrate the scale of the problems with species names, synonyms, and their classification, and describe how WoRMS publishes online quality assured information on marine species.Within WoRMS, over 100 global, 12 regional and 4 thematic species databases are integrated with a common taxonomy. Over 240 editors from 133 institutions and 31 countries manage the content. To avoid duplication of effort, content is exchanged with 10 external databases. At present WoRMS contains 460,000 taxonomic names (from Kingdom to subspecies), 368,000 species level combinations of which 215,000 are currently accepted marine species names, and 26,000 related but non-marine species. Associated information includes 150,000 literature sources, 20,000 images, and locations of 44,000 specimens. Usage has grown linearly since its launch in 2007, with about 600,000 unique visitors to the website in 2011, and at least 90 organisations from 12 countries using WoRMS for their data management.By providing easy access to expert-validated content, WoRMS improves quality control in the use of species names, with consequent benefits to taxonomy, ecology, conservation and marine biodiversity research and management. The service manages information on species names that would otherwise be overly costly for individuals, and thus minimises errors in the application of nomenclature standards. WoRMS' content is expanding to include host-parasite relationships, additional literature sources, locations of specimens, images, distribution range, ecological, and biological data. Species are being categorised as introduced (alien, invasive), of conservation importance, and on other attributes. These developments have a multiplier effect on its potential as a resource for biodiversity research and management. As a consequence of WoRMS, we are witnessing improved communication within the scientific community, and anticipate increased taxonomic efficiency and quality control in marine biodiversity research and management

Macrofaunal ecology of sedimented hydrothermal vents in the Bransfield Strait, Antarctica

Sediment-hosted hydrothermal vents, where hot, mineral-rich water flows through sediment, are poorly understood globally, both in their distribution and the ecology of individual vent fields. We explored macrofaunal community ecology at a sediment-hosted hydrothermal vent in the Southern Ocean. This is the first such study of these ecosystems outside of the Pacific and the furthest south (62˚S) of any vent system studied. Sedimentary fauna were sampled at four sites in the Bransfield Strait (Southern Ocean), with the aim of contrasting community structure between vent and non-vent sites. Geochemical data were used to create and test a novel proxy index to quantify the degree of hydrothermal influence and its influence on deep-sea biota. Macrofaunal communities were clearly distinct between vent and non-vent sites, and diversity, richness and density declined towards maximum hydrothermal activity. This variation is in contrast to observations from similar systems in the Pacific and demonstrates the influence of factors other than chemosynthetic primary productivity in structuring infauna at deep-sea vent communities. Vent endemic fauna had limited abundance and were represented by a single siboglinid species at hydrothermally active areas, meaning that that the majority of local biota were those also found in other areas. Several taxa occupied all sampling stations but there were large differences in their relative abundances, suggesting communities were structured by niche variation rather than dispersal ability

Sphaerodoridae (Annelida: Polychaeta) from the Bellingshausen Sea (Antarctica) with the description of two new species

The examination of polychaete collections obtained during the Spanish Bentart 2006expedition to the Bellingshausen Sea (Antarctica) revealed the presence of several sphaerodorid species. In this work, species belonging to the genera Sphaerodorum Örsted, 1843, Ephesiella Chamberlin, 1919, Clavodorum Hartman and Fauchald, 1971 and Sphaerephesia Fauchald, 1972 are reported including two new species belonging to Sphaerodorum and Sphaerephesia, respectively. A specimen identified as Ephesiella sp. might also represent a new species but, due to its poor state of preservation, a formal description is not possible yet. Furthermore, Sphaerodoropsis polypapillata Hartmann-Schröder and Rosenfeldt, 1988 is transferred to the genus Clavodorum Hartman and Fauchald, 1971 after examination of the type series and specimens obtained from the Bellingshausen Sea.Comisión Interministerial de Ciencia y Tecnología; REN 2001-1074/ANTComisión Interministerial de Ciencia y Tecnología; CGL2004-0185