Complexity-functioning relationships differ across different environmental conditions.

Habitat complexity is widely considered an important determinant of biodiversity, and enhancing complexity can play a key role in restoring degraded habitats. However, the effects of habitat complexity on ecosystem functioning - as opposed to biodiversity and community structure - are relatively poorly understood for artificial habitats, which dominate many coastlines. With Greening of Grey Infrastructure (GGI) approaches, or eco-engineering, increasingly being applied around the globe, it is important to understand the effects that modifying habitat complexity has on both biodiversity and ecological functioning in these highly modified habitats.

The invasive seaweed Asparagopsis taxiformis erodes the habitat structure and biodiversity of native algal forests in the Mediterranean Sea.

Invasive seaweeds are listed among the most relevant threats to marine ecosystems worldwide. Biodiversity hotspots, such as the Mediterranean Sea, are facing multiple invasions and are expected to be severely affected by the introduction of new non-native seaweeds in the near future. In this study, we evaluated the consequences of the shift from the native Ericaria brachycarpa to the invasive Asparagopsis taxiformis habitat on the shallow rocky shores of Favignana Island (Egadi Islands, MPA, Sicily, Italy).

The invasive Asparagopsis taxiformis hosts a low diverse and less trophic structured molluscan assemblage compared with the native Ericaria brachycarpa.

Invasive seaweeds threaten biodiversity and socio-economics values of worldwide marine ecosystems. Understanding to what extent invasive seaweeds can modify local biodiversity is one of the main priorities in conservation ecology. We compared the molluscan assemblage of the invasive Asparagopsis taxiformis with that of the native Ericaria brachycarpa and explore if variation in the molluscan assemblage diversity was related to the substrate attributes (biomass, and thallus, canopy, and interstitial volumes) of the algae.

Forecasting national and regional level intensive care unit bed demand during COVID-19: The case of Italy.

Given the pressure on healthcare authorities to assess whether hospital capacity allows properly responding to outbreaks such as COVID-19, there is a need for simple, data-driven methods that may provide accurate forecasts of hospital bed demand. This study applies growth models to forecast the demand for Intensive Care Unit admissions in Italy during COVID-19. We show that, with only some mild assumptions on the functional form and using short time-series, the model fits past data well and can accurately forecast demand fourteen days ahead (the mean absolute percentage error (MAPE) of the cumulative fourteen days forecasts is 7.

Care Appropriateness and Health Productivity Evolution: A Non-Parametric Analysis of the Italian Regional Health Systems.

Background: There has been increasing interest in measuring the productive performance of healthcare services since the mid-1980s.

Objective: By applying bootstrapped data envelopment analysis across the 20 Italian Regional Health Systems (RHSs) for the period 2008-2012, we employed a two-stage procedure to investigate the relationship between care appropriateness and productivity evolution in public hospital services.

Methods: In the first stage, we estimated the Malmquist index and decomposed this overall measure of productivity into efficiency and technological change.

Healthcare reform in Italy: an analysis of efficiency based on nonparametric methods.

Over the past twenty years, important changes in the Italian health system have led to different approaches in organizing, delivering and financing health services throughout the country's regions. In this paper, we assess the impacts that such changes have had on health efficiency. The analysis performed here is in two stages.