Estimating Density Dependence, Environmental Variance, and Long-Term Selection on a Stage-Structured Life History

A method for analyzing long-term demographic data on density-dependent stage-structured populations in a stochastic environment is derived to facilitate comparison of populations and species with different life histories. We assume that a weighted sum of stage abundances, N, exerts density dependence on stage-specific vital rates of survival and reproduction and that N has a small or moderate coefficient of variation. The dynamics of N are approximated as a univariate stochastic process governed by three key parameters: the density-independent growth rate, the net density dependence, and environmental variance in the life history. We show how to estimate the relative weighs of stages in N and the key parameters. Life history evolution represents a stochastic maximization of a simple function of the key parameters. The long-term selection gradient on the life history can be expressed as a vector of sensitivities of this function with respect to density-independent, density-dependent, and stochastic components of the vital rates. To illustrate the method, we analyze 38 years of demographic data on a great tit population, estimating the key parameters, which accurately predict the observed mean, coefficient of variation, and fluctuation rate of N; we also evaluate the long-term selection gradient on the life history.</p

Linear MIM-Width of Trees

We provide an $O(n \log n)$ algorithm computing the linear maximum induced matching width of a tree and an optimal layout.Comment: 19 pages, 7 figures, full version of WG19 paper of same nam

Assessing the Influence of Salmon Farming through Total Lipids, Fatty Acids, and Trace Elements in the Liver and Muscle of Wild Saithe Pollachius virens

Saithe Pollachius virens are attracted to uneaten salmon feed underneath cages at open-cage salmon farms in Norway. The aggregated Saithe have modified their feeding habits as they have switched from wild prey to uneaten food pellets, which could lead to physiological and biochemical changes in the Saithe. Variations in profiles of total lipids, fatty acids, and trace elements in Saithe liver and muscle were measured to evaluate the influence of fish feed from salmon farms on wild Saithe populations. Farm-aggregated Saithe had higher fat content in liver tissues than did individuals captured more than 25 km away from farms, but no clear differences were found in muscle tissues. High proportions of fatty acids of terrestrial origin, such as oleic, linoleic, and linolenic acids, in liver and muscle tissues of farm-aggregated Saithe reflected the presence of wild Saithe at farms. Accordingly, low proportions of arachidonic, eicosapentaenoic, and docosahexaenoic acids in Saithe tissues mirrored the feeding activity at farms. Variations in specific trace element signatures among fish groups also revealed the farming influence on wild Saithe. High levels of Fe, As, Se, Zn, and B in liver, but also As, B, Li, Hg, and Sr in muscle of Saithe captured away from farms indicated the absence of feeding at farms.This study was part of the project “Evaluation of actions to promote sustainable coexistence between salmon culture and coastal fisheries – ProCoEx” funded by The Norwegian Seafood Research Fund (FHF). The study was also supported by the Norwegian Research Council through the EcoCoast project

Evaluering av utprøving av digital hjemmeoppfølging: Delrapport II

Med støtte fra Helsedirektoratet prøver seks lokale prosjekter i kommunal regi ut digital hjemmeoppfølging av personer med kronisk sykdom. Utprøvingen gjennomføres i perioden 2018-2021 som en del av Nasjonalt velferdsteknologiprogram. Formålet med utprøvingen er å få tilstrekkelig kunnskap om digital hjemmeoppfølging til å gi nasjonale anbefalinger om implementering av tiltaket. Utprøvingen evalueres av forskere fra Universitetet i Oslo, Oslo Economics og Nasjonal senter for distriksmedisin. I denne delrapporten beskriver vi erfaringer med og effekter av digital hjemmeoppfølging til og med høsten 2020

Variable strength of forest stand attributes and weather conditions on the questing activity of Ixodes ricinus ticks over years in managed forests

Given the ever-increasing human impact through land use and climate change on the environment, we crucially need to achieve a better understanding of those factors that influence the questing activity of ixodid ticks, a major disease-transmitting vector in temperate forests. We investigated variation in the relative questing nymph densities of Ixodes ricinus in differently managed forest types for three years (2008–2010) in SW Germany by drag sampling. We used a hierarchical Bayesian modeling approach to examine the relative effects of habitat and weather and to consider possible nested structures of habitat and climate forces. The questing activity of nymphs was considerably larger in young forest successional stages of thicket compared with pole wood and timber stages. Questing nymph density increased markedly with milder winter temperatures. Generally, the relative strength of the various environmental forces on questing nymph density differed across years. In particular, winter temperature had a negative effect on tick activity across sites in 2008 in contrast to the overall effect of temperature across years. Our results suggest that forest management practices have important impacts on questing nymph density. Variable weather conditions, however, might override the effects of forest management practices on the fluctuations and dynamics of tick populations and activity over years, in particular, the preceding winter temperatures. Therefore, robust predictions and the detection of possible interactions and nested structures of habitat and climate forces can only be quantified through the collection of long-term data. Such data are particularly important with regard to future scenarios of forest management and climate warming

Emergent global patterns of ecosystem structure and function from a mechanistic general ecosystem model

Anthropogenic activities are causing widespread degradation of ecosystems worldwide, threatening the ecosystem services upon which all human life depends. Improved understanding of this degradation is urgently needed to improve avoidance and mitigation measures. One tool to assist these efforts is predictive models of ecosystem structure and function that are mechanistic: based on fundamental ecological principles. Here we present the first mechanistic General Ecosystem Model (GEM) of ecosystem structure and function that is both global and applies in all terrestrial and marine environments. Functional forms and parameter values were derived from the theoretical and empirical literature where possible. Simulations of the fate of all organisms with body masses between 10 µg and 150,000 kg (a range of 14 orders of magnitude) across the globe led to emergent properties at individual (e.g., growth rate), community (e.g., biomass turnover rates), ecosystem (e.g., trophic pyramids), and macroecological scales (e.g., global patterns of trophic structure) that are in general agreement with current data and theory. These properties emerged from our encoding of the biology of, and interactions among, individual organisms without any direct constraints on the properties themselves. Our results indicate that ecologists have gathered sufficient information to begin to build realistic, global, and mechanistic models of ecosystems, capable of predicting a diverse range of ecosystem properties and their response to human pressures