Climate change impacts on tree species, forest properties, and ecosystem services

– Swiss forests experience strong impacts under the CH2011 scenarios, partly even for the low greenhouse gas scenario RCP3PD. Negative impacts prevail in low-elevation forests, whereas mostly positive impacts are expected in high-elevation forests. – Major changes in the distribution of the two most important tree species, Norway spruce and European beech, are expected. Growth conditions for spruce improve in a broad range of scenarios at presently cool high-elevation sites with plentiful precipitation, but in the case of strong warming (A1B and A2) spruce and beech are at risk in large parts of the Swiss Plateau. – High elevation forests that are temperature-limited will show little change in species composition but an increase in biomass. In contrast, forests at low elevations in warm-dry inner-Alpine valleys are sensitive to even moderate warming and may no longer sustain current biomass and species. – Timber production potential, carbon storage, and protection from avalanches and rockfall react differently to climate change, with an overall tendency to deteriorate at low elevations, and improve at high elevations. – Climate change will affect forests also indirectly, e.g., by increasing the risk of infestation by spruce bark beetles, which will profit from an extended flight period and will produce more generations per year.

Expected impact of applying new 2013 AHA/ACC cholesterol guidelines criteria on the recommended lipid target achievement after acute coronary syndromes.

BACKGROUND 2013 AHA/ACC guidelines on the treatment of cholesterol advised to tailor high-intensity statin after ACS, while previous ATP-III recommended titration of statin to reach low-density lipoprotein cholesterol (LDL-C) targets. We simulated the impact of this change of paradigm on the achievement of recommended targets. METHODS Among a prospective cohort study of consecutive patients hospitalized for ACS from 2009 to 2012 at four Swiss university hospitals, we analyzed 1602 patients who survived one year after recruitment. Targets based on the previous guidelines approach was defined as (1) achievement of LDL-C target < 1.8 mmol/l, (2) reduction of LDL-C ≥ 50% or (3) intensification of statin in patients who did not reach LDL-C targets. Targets based on the 2013 AHA/ACC guidelines approach was defined as the maximization of statin therapy at high-intensity in patients aged ≤75 years and moderate- or high-intensity statin in patients >75 years. RESULTS 1578 (99%) patients were prescribed statin at discharge, with 1120 (70%) at high-intensity. 1507 patients (94%) reported taking statin at one year, with 909 (57%) at high-intensity. Among 482 patients discharged with sub-maximal statin, intensification of statin was only observed in 109 patients (23%). 773 (47%) patients reached the previous LDL-C targets, while 1014 (63%) reached the 2013 AHA/ACC guidelines targetsone year after ACS (p value < 0.001). CONCLUSION The application of the new 2013 AHA/ACC guidelines criteria would substantially increase the proportion of patients achieving recommended lipid targets one year after ACS. Clinical trial number, NCT01075868.

Expected Shortfall is jointly elicitable with Value at Risk - Implications for backtesting

In this note, we comment on the relevance of elicitability for backtesting risk measure estimates. In particular, we propose the use of Diebold-Mariano tests, and show how they can be implemented for Expected Shortfall (ES), based on the recent result of Fissler and Ziegel (2015) that ES is jointly elicitable with Value at Risk.

Differentiating the Multipoint Expected Improvement for Optimal Batch Design

This work deals with parallel optimization of expensive objective functions which are modelled as sample realizations of Gaussian processes. The study is formalized as a Bayesian optimization problem, or continuous multi-armed bandit problem, where a batch of q > 0 arms is pulled in parallel at each iteration. Several algorithms have been developed for choosing batches by trading off exploitation and exploration. As of today, the maximum Expected Improvement (EI) and Upper Confidence Bound (UCB) selection rules appear as the most prominent approaches for batch selection. Here, we build upon recent work on the multipoint Expected Improvement criterion, for which an analytic expansion relying on Tallis’ formula was recently established. The computational burden of this selection rule being still an issue in application, we derive a closed-form expression for the gradient of the multipoint Expected Improvement, which aims at facilitating its maximization using gradient-based ascent algorithms. Substantial computational savings are shown in application. In addition, our algorithms are tested numerically and compared to state-of-the-art UCB-based batchsequential algorithms. Combining starting designs relying on UCB with gradient-based EI local optimization finally appears as a sound option for batch design in distributed Gaussian Process optimization.

How Much am I Expected to Pay for my Parents‘ Firm? An Institutional Logics Perspective on Family Discounts

Recent evidence suggests that successors do not simply inherit their parents’ firm, but have to pay a certain price. Building on institutional logics literature, we explore successors’ family discount expectations, defined as the rebate expected from parents in comparison to nonfamily buyers when assuming control of the firm. We find that family cohesion increases discount expectations, while successors’ fear of failure and family equity stake in the firm decrease discount expectations. Higher education in business or economics weakens These effects. On average, in our study comprised of 16 countries, successors expect a 57% family discount.