Hierarkkinen Bayes-malli osoittaa Arktisten merinisäkkäiden levinneisyyksien muutokset

Kehitimme menetelmän erilaisten avointen aineistojen, kuten julkaistujen artikkelien ja tietokantojen, käyttämiseen analysoidaksemme arktisten merinisäkkäiden levinneisyyksiä. Menetelmän avulla arvioimme ympäristön vaikutusta lajien levinneisyydelle sekä levinneisyyksien mahdollisia muutoksia havaittujen ympäristömuutosten seurauksena. Tutkimus toteutettiin Karan Merellä, joka on yksi arktisista reunameristä. Etsimme avoimista aineistosta havaintotietoja jääkarhuista (Ursus maritimus), mursuista (Odobenus rosmarus rosmarus) ja norpista (Phoca hispida). Paikansimme havainnot ja analysoimme lajien esiintymistiheytta Poissonin pisteprosessimallilla. Vaihtelevan laatuinen aineisto ei sisältänyt tietoa lähdetutkimusten havaintoprosessista, minkä vuoksi pystyimme mallintamaan ainoastaan lajien esiintymistiheyden suhteessa tuntemattomaan havaintointensiteettiin. Selitimme lajien suhteellista esiintymistiheyttä ympäristömuuttujilla ja satunnaismuuttujilla, joista jälkimmäiset kuvastavat esiintymistiheyden satunnaisvaihtelua ajassa ja tilassa sekä suhteessa satunnaiseen havainnointi-intensiteettiin. Jääkarhujen esiintymistiheyttä selitimme myös norppien ennustetulla esiintymistiheydellä jääkarhujen havaintopisteissä. Merijään tiheys ja havaintojen etäisyys rannikosta olivat tärkeimpiä selittäviä ympäristömuuttujia jokaisen lajin kohdalla. Hylkeiden esiintymistiheys oli tärkein muuttuja selittämään jääkarhujen esiintymistiheyttä. Merijään tiheyden heikkeneminen 17-vuotisen tutkimusjakson aikana vaikutti lajien esiintymistiheyksiin siten, että mursujen ja jääkarhujen tiheys pysyi vakaana tai heikkeni hieman, kun taas norppien tiheys laski itäisellä ja kasvoi läntisellä Karan Merellä. Pisteprosessimalli on vakaa menetelmä lajien levinneisyyksien arvioimiseen perustuen vaihtelevan laatuisiin havaintoihin. Menetelmä tarjoaa sijainnista riippumattomasti luotettavaa tietoa ekosysteemeistä ja tarjoaa työkaluja suojelutoimintaan arktisella. Tuloksemme osoittivat, että yksinkertaisessa ravintoverkossa saalistajalajin levinneisyys selittyy paremmin saalislajien levinneisyydellä kuin ympäristömuuttujilla. Heikkenevä merijää on ilmeinen syy merinisäkkäiden levinneisyyksien muutoksiin arktisella alueella.Aim Our aim involved developing a method to analyse spatiotemporal distributions of Arctic marine mammals (AMMs) using heterogeneous open source data, such as scientific papers and open repositories. Another aim was to quantitatively estimate the effects of environmental covariates on AMMs’ distributions and to analyse whether their distributions have shifted along with environmental changes. Location Arctic shelf area. The Kara Sea. Methods Our literature search focused on survey data regarding polar bears (Ursus maritimus), Atlantic walruses (Odobenus rosmarus rosmarus) and ringed seals (Phoca hispida). We mapped the data on a grid and built a hierarchical Poisson point process model to analyse species’ densities. The heterogeneous data lacked information on survey intensity and we could model only the relative density of each species. We explained relative densities with environmental covariates and random effects reflecting excess spatiotemporal variation and the unknown, varying sampling effort. The relative density of polar bears was explained also by the relative density of seals. Results The most important covariates explaining AMMs’ relative densities were ice concentration and distance to the coast, and regarding polar bears, also the relative density of seals. The results suggest that due to the decrease in the average ice concentration, the relative densities of polar bears and walruses slightly decreased or stayed constant during the 17‐year‐long study period, whereas seals shifted their distribution from the Eastern to the Western Kara Sea. Main conclusions Point process modelling is a robust methodology to estimate distributions from heterogeneous observations, providing spatially explicit information about ecosystems and thus serves advances for conservation efforts in the Arctic. In a simple trophic system, a distribution model of a top predator benefits from utilizing prey species’ distributions compared to a solely environmental model. The decreasing ice cover seems to have led to changes in AMMs’ distributions in the marginal Arctic region.Peer reviewe

Hydrographic responses to regional covariates across the Kara Sea

The Kara Sea is a shelf sea in the Arctic Ocean which has a strong spatiotemporal hydrographic variation driven by river discharge, air pressure and sea ice. There is a lack of information about the local scale effects of environmental variables to surface hydrography in different regions of the Kara Sea. We use a hierarchical spatially varying coefficient model to study the monthly variation of sea surface temperature (SST) and salinity (SSS) in the Kara Sea between years 1980 and 2000. The model allows us to study the effect of climatic (arctic oscillation index, AO) and seasonal (river discharge and ice concentration) environmental covariates on SST and SSS. The results show that the hydrographical response to environmental covariates vary considerably between different regions of the Kara Sea. River discharge decreases SSS in the shallow shelf area and has a neutral effect in the northern Kara Sea. The responses of SST to AO and river discharge vary in south-north direction. Ice concentration has the most constant effect across Kara Sea. We estimated also the average SST and SSS in the Kara Sea in 1980-2000. The average August SST over the Kara Sea in 1995-2000 was higher than the respective average in 1980-1984 with 99.9 % probability as SSS decreased with 77 % probability. We found a support that the winter season AO has an impact on the summer season hydrographical conditions, and decadal temporal trends may be related to the varying level of winter season AO index.Peer reviewe

A framework for space-efficient read clustering in metagenomic samples

Background: A metagenomic sample is a set of DNA fragments, randomly extracted from multiple cells in an environment, belonging to distinct, often unknown species. Unsupervised metagenomic clustering aims at partitioning a metagenomic sample into sets that approximate taxonomic units, without using reference genomes. Since samples are large and steadily growing, space-efficient clustering algorithms are strongly needed. Results: We design and implement a space-efficient algorithmic framework that solves a number of core primitives in unsupervised metagenomic clustering using just the bidirectional Burrows-Wheeler index and a union-find data structure on the set of reads. When run on a sample of total length n, with m reads of maximum length l each, on an alphabet of total size sigma, our algorithms take O(n(t + log sigma)) time and just 2n + o(n) + O(max{l sigma log n, K logm}) bits of space in addition to the index and to the union-find data structure, where K is a measure of the redundancy of the sample and t is the query time of the union-find data structure. Conclusions: Our experimental results show that our algorithms are practical, they can exploit multiple cores by a parallel traversal of the suffix-link tree, and they are competitive both in space and in time with the state of the art.Peer reviewe

Exposing changing phenology of fish larvae by modeling climate effects on temporal early life-stage shifts

Changing environmental conditions are influencing the seasonal timing in life history events of organisms. Such shifts in phenology are often linked to increasing temperatures that stimulate faster developments or earlier arrivals. This phenomenon has been demonstrated in terrestrial and aquatic realms, but data and knowledge are limited on how early life stages of fish are affected over long-term and broad environmental scales. Here, we analyze 2 decades (1974-1996) of size class-specific Baltic herring Clupea harengus membras L. larval data along the whole coast of Finland to expose shifts in phenology linked to changes in environmental covariates. We use a novel Bayesian hierarchical spatio-temporal hurdle model that describes larval occurrence and abundance with separate processes. Abundances are modeled with the Ricker population growth model that enables us to predict size-specific larvae groups in relation to the environment while accounting for population density dependence. We quantify shifts in phenology at multiple life stages, based on first appearances of smallest larvae (15 mm) appearing earlier than they have done historically. Our results show a strong signal in shifting phenology of the larvae toward an earlier development of 7.7 d per decade. Increasing temperature had a positive effect on the earlier development of larger larvae. Additionally, we highlight that the survival of larvae becomes more density dependent as their size increases. Our modeling framework can reveal phenological shifts of early life stages in relation to environmental change for survey data that do not necessarily cover the onset of reproduction.Peer reviewe

Spatial confounding in Bayesian species distribution modeling

1) Species distribution models (SDMs) are currently the main tools to derive species niche estimates and spatially explicit predictions for species geographical distribution. However, unobserved environmental conditions and ecological processes may confound the model estimates if they have direct impact on the species and, at the same time, they are correlated with the observed environmental covariates. This, so-called spatial confounding, is a general property of spatial models and it has not been studied in the context of SDMs before. 2) We examine how the estimation accuracy of SDMs depends on the type of spatial confounding. We construct two simulation studies where we alter spatial structures of the observed and unobserved covariates and the level of dependence between them. We fit generalized linear models with and without spatial random effects applying Bayesian inference and recording the bias induced to model estimates by spatial confounding. After this we examine spatial confounding also with real vegetation data from northern Norway. 3) Our results show that model estimates for coarse scale covariates, such as climate covariates, are likely to be biased if a species distribution depends also on an unobserved covariate operating on a finer spatial scale. Pushing higher probability for a relatively weak and smoothly varying spatial random effect compared to the observed covariates improved the model's estimation accuracy. The improvement was independent of the actual spatial structure of the unobserved covariate. 4) Our study addresses the major factors of spatial confounding in SDMs and provides a list of recommendations for pre-inference assessment of spatial confounding and for inference-based methods to decrease the chance of biased model estimates.Peer reviewe

Impacts of oil spills on Arctic marine ecosystems: A quantitative and probabilistic risk assessment perspective

Oil spills resulting from maritime accidents pose a poorly understood risk to the Arctic environment. We propose a novel probabilistic method to quantitatively assess these risks. Our method accounts for spatiotemporally varying population distributions, the spreading of oil, and seasonally varying species-specific exposure potential and sensitivity to oil. It quantifies risk with explicit uncertainty estimates, enables one to compare risks over large geographic areas, and produces information on a meaningful scale for decision-making. We demonstrate the method by assessing the short-term risks oil spills pose to polar bears, ringed seals, and walrus in the Kara Sea, the western part of the Northern Sea Route. The risks differ considerably between species, spatial locations, and seasons. Our results support current aspirations to ban heavy fuel oil in the Arctic but show that we should not underestimate the risks of lighter oils either, as these oils can pollute larger areas than heavier ones. Our results also highlight the importance of spatially explicit season-specific oil spill risk assessment in the Arctic and that environmental variability and the lack of data are a major source of uncertainty related to the oil spill impacts.Peer reviewe

Removal of Pyrrhotite from High-Sulphur Tailings Utilising Non-Oxidative H2SO4 Leaching

Tailings are a residual material stream produced in the mineral processing of ores. They may contain a major sulphide content that increases the risk of acid rock drainage (ARD) but may also host valuable metals. Tank bioleaching is a technically viable method to treat sulphide tailings. However, a significant pyrrhotite content may cause increased acid and oxidant consumption and result in longer retention times in a bioleaching process. In this work, non-oxidative H2SO4 leaching of pyrrhotite is studied for high-sulphur tailings, both as a pre-treatment method and to consider the recovery possibilities of Fe and S. Continuous mode validation tests, conducted at 90 °C, pH 1.0 and 106 min retention time, resulted in a complete pyrrhotite dissolution with 427 kg/t acid consumption (as 95% H2SO4). Unwanted dissolution of Ni and Zn was taking place with a leaching yield of 21.5% and 13.5%, respectively, while Co and Cu dissolution was negligible. The continuous mode tests signalled that by shortening the retention time, Ni dissolution could be dramatically decreased. The non-oxidative pyrrhotite leaching produced a H2S-rich gas stream, which could be utilised in later metals’ recovery processes after bioleaching to precipitate (CoNi)S, ZnS and CuS products. The non-oxidative pyrrhotite leaching also produced a FeSO4 solution, with approximately 20 g/L of Fe

Työeläkkeiden rahoitusselvitys

Raportissa tarkastellaan TyEL-eläkkeiden rahoitusta ja TyEL-yhtiöiden asiakashyvityksiä. Raportissa kuvataan TyEL:n rahoitusympäristön muutoksia ja rahoitussäännöksiä. Keskeiset pitkän aikavälin rakenteelliset haasteet ovat matala syntyvyys sekä matala korkotaso. Raportissa arvioidaan laskelmien avulla erilaisia rahastointivaihtoehtoja. Lisäksi selvitetään mahdollisuuksia lisätä TyEL-yhtöiden asiakashyvitysten läpinäkyvyyttä. Raportin toimeksianto sisältyy työmarkkinoiden keskusjärjestöjen kesällä 2019 tekemään sopimukseen