Priors for the Bayesian star paradox

We show that the Bayesian star paradox, first proved mathematically by Steel and Matsen for a specific class of prior distributions, occurs in a wider context including less regular, possibly discontinuous, prior distributions.     

On the relationship between content, ancestor, and ancestry in phylogenetic nomenclature

In this paper I draw attention to the concepts of content and ancestry in phylogenetic nomenclature. I argue that these concepts are tightly linked and that they cannot be separated as suggested by Bryant and Cantino [Biol. Rev. 77 (2002) 39] in their recent response to a critique of phylogenetic nomenclature. In addition, I argue that the basic assumption in phylogenetic nomenclature that a taxon name always refers to the same ancestor or ancestry is questionable.     

Island properties dominate species traits in determining plant colonizations in an archipelago system

The extrinsic determinants hypothesis emphasizes the essential role of environmental heterogeneity in species’ colonization. Consequently, high resident species diversity can increase community susceptibility to colonizations because good habitats may support more species that are functionally similar to colonizers. On the other hand, colonization success is also likely to depend on species traits. We tested the relative importance of environmental characteristics and species traits in determining colonization success using census data of 587 vascular plant species collected about 70 yr apart from 471 islands in the archipelago of SW Finland. More specifically, we explored potential new colonization as a function of island properties (e.g. location, area, habitat diversity, number of resident species per unit area), species traits (e.g. plant height, life-form, dispersal vector, Ellenberg indicator values, association with human impact), and species’ historical distributions (number of inhabited islands, nearest occurrence). Island properties and species’ historical distributions were more effective than plant traits in explaining colonization outcomes. Contrary to the extrinsic determinants hypothesis, colonization success was neither associated with resident species diversity nor habitat diversity per se, although colonization was lowest on sparsely vegetated islands. Our findings lead us to propose that while plant traits related to dispersal and establishment may enhance colonization, predictions of plant colonizations primarily require understanding of habitat properties and species’ historical distributions.     

Don't judge a cell by its cover: heterogeneity within early lymphoid progenitors

B‐cell differentiation is one of the most recognized examples of the progressive lineage commitment that is distinctive for stem cell systems. However, the characteristics of the stage just before a cell becomes restricted to the B‐cell lineage are less understood. Using single‐cell RNA sequencing technology, Rolink and colleagues are able to define the cellular heterogeneity at this step and challenge our understanding of developmental trajectories in early B‐lymphoid development (Alberti‐Servera et al, 2017 ).     

Considering Future Potential Regarding Structural Diversity in Selection of Forest Reserves

A rich structural diversity in forests promotes biodiversity. Forests are dynamic and therefore it is crucial to consider future structural potential when selecting reserves, to make robust conservation decisions. We analyzed forests in boreal Sweden based on 17,599 National Forest Inventory (NFI) plots with the main aim to understand how effectiveness of reserves depends on the time dimension in the selection process, specifically by considering future structural diversity. In the study both the economic value and future values of 15 structural variables were simulated during a 100 year period. To get a net present structural value (NPSV), a single value covering both current and future values, we used four discounting alternatives: (1) only considering present values, (2) giving equal importance to values in each of the 100 years within the planning horizon, (3) applying an annual discount rate considering the risk that values could be lost, and (4) only considering the values in year 100. The four alternatives were evaluated in a reserve selection model under budget-constrained and area-constrained selections. When selecting young forests higher structural richness could be reached at a quarter of the cost over almost twice the area in a budget-constrained selection compared to an area-constrained selection. Our results point to the importance of considering future structural diversity in the selection of forest reserves and not as is done currently to base the selection on existing values. Targeting future values increases structural diversity and implies a relatively lower cost. Further, our results show that a re-orientation from old to young forests would imply savings while offering a more extensive reserve network with high structural qualities in the future. However, caution must be raised against a drastic reorientation of the current old-forest strategy since remnants of ancient forests will need to be prioritized due to their role for disturbance-sensitive species.     

Predictors of Weight Change in Middle‐aged and Old Men

Objective: Studies on weight change and mortality have yielded inconclusive results. This 10‐year prospective study was undertaken to improve understanding of factors affecting weight change. Research Methods and Procedures: The subjects were 1143 men, aged 36 to 88 years (mean, 53.3 years) at entry. A questionnaire was filled in at entry and at the end of the follow‐up with queries on weight, height, weight at the age of 20, physician‐diagnosed diseases, smoking, alcohol use, dietary habits, leisure physical activity, occupation, present occupational activity, living conditions (living alone or cohabiting), and former athletic status. Further information on morbidity was obtained from selected national registers. Factors predicting weight change during the study were identified by stepwise linear multiple regression analysis. Results: The mean 10‐year weight change was 0.8 (range, ?29 to +24) kg. Age at entry (β‐coefficient, ?0.17, SE 0.02), weight at entry (β, ?0.03, SE 0.01), diabetes at entry (β, ?3.55, SE 1.02), diabetes diagnosed after entry (β, ?3.94, SE 0.96), malignant cancer (β, ?1.60, SE 0.70), being a smoker (β, ?1.59, SE 0.48), and increased physical activity (β, ?1.27, SE 0.54) were significantly (p < 0.05) associated with weight loss in the final model. The model explained 13% of the variance of weight change. Discussion: The results emphasize the complexity of weight change. Some factors associated with weight change are apparently negatively, and some positively, associated with health. This could explain the equivocal findings on weight change and mortality in the literature.