A convexity-constrained parameterization of the random effects generalized partial credit model.

An alternative closed-form expression for the marginal joint probability distribution of item scores under the random effects generalized partial credit model is presented. The closed-form expression involves a cumulant generating function and is therefore subjected to convexity constraints. As a consequence, complicated moment inequalities are taken into account in maximum likelihood estimation of the parameters of the model, so that the estimation solution is always proper.

Optimal phenology of life history events in : exit from diapause in relation to interannual variation in spring bloom timing and predation.

Respiration of lipids by copepods during diapause (overwintering dormancy) contributes to ocean carbon sequestration via the seasonal lipid pump (SLP). Parameterizing this flux in predictive models requires a mechanistic understanding of how life history adaptation in copepods shapes their timing of exit from diapause. We investigate the optimal phenology of in the Norwegian Sea using an individual-based model in which diapause exit is represented as a trait characterized by phenotypic mean and variance.

Do DOM quality and origin affect the uptake and accumulation of a lipid-soluble contaminant in a filter feeding ascidian species (Ciona) that can target small particle size classes?

The widely reported increase of terrestrial dissolved organic matter (terrDOM) in northern latitude coastal areas ("coastal darkening") can impact contaminant dynamics in affected systems. One potential impact is based on differences in chemical adsorption processes of the molecularly larger terrDOM compared to marine DOM (marDOM) that leads to increased emulsification of lipophilic contaminants with terrDOM. Filter feeders filter large amounts of water and DOM daily and thus are directly exposed to associated contaminants through both respiration and feeding activity.

Climate change vulnerability of Arctic char across Scandinavia.

Climate change is anticipated to cause species to shift their ranges upward and poleward, yet space for tracking suitable habitat conditions may be limited for range-restricted species at the highest elevations and latitudes of the globe. Consequently, range-restricted species inhabiting Arctic freshwater ecosystems, where global warming is most pronounced, face the challenge of coping with changing abiotic and biotic conditions or risk extinction. Here, we use an extensive fish community and environmental dataset for 1762 lakes sampled across Scandinavia (mid-1990s) to evaluate the climate vulnerability of Arctic char (Salvelinus alpinus), the world's most cold-adapted and northernly distributed freshwater fish.

Phytoplankton biomass in northern lakes reveals a complex response to global change.

Global change may introduce fundamental alterations in phytoplankton biomass and community structure that can alter the productivity of northern lakes. In this study, we utilized Swedish and Finnish monitoring data from lakes that are spatially (135 lakes) and temporally (1995-2019, 110 lakes) extensive to assess how phytoplankton biomass (PB) of dominant phytoplankton groups related to changes in water temperature, pH and key nutrients [total phosphorus (TP), total nitrogen (TN), total organic carbon (TOC), iron (Fe)] along spatial (Fennoscandia) and temporal (25 years) gradients. Using a machine learning approach, we found that TP was the most important determinant of total PB and biomass of a specific species of Raphidophyceae - Gonyostomum semen - and Cyanobacteria (both typically with adverse impacts on food-webs and water quality) in spatial analyses, while Fe and pH were second in importance for G.