Region-wide temporal and spatial variation in Caribbean reef architecture: is coral cover the whole story?

The architectural complexity of coral reefs is largely generated by reef-building corals, yet the effects of current regional-scale declines in coral cover on reef complexity are poorly understood. In particular, both the extent to which declines in coral cover lead to declines in complexity and the length of time it takes for reefs to collapse following coral mortality are unknown. Here we assess the extent of temporal and spatial covariation between coral cover and reef architectural complexity using a Caribbean-wide dataset of temporally replicated estimates spanning four decades. Both coral cover and architectural complexity have declined rapidly over time, with little evidence of a time-lag. However, annual rates of change in coral cover and complexity do not covary, and levels of complexity vary greatly among reefs with similar coral cover. These findings suggest that the stressors influencing Caribbean reefs are sufficiently severe and widespread to produce similar regional-scale declines in coral cover and reef complexity, even though reef architectural complexity is not a direct function of coral cover at local scales. Given that architectural complexity is not a simple function of coral cover, it is important that conservation monitoring and restoration give due consideration to both architecture and coral cover. This will help ensure that the ecosystem services supported by architectural complexity, such as nutrient recycling, dissipation of wave energy, fish production and diversity, are maintained and enhanced

Model-based Boosting in R: A Hands-on Tutorial Using the R Package mboost

We provide a detailed hands-on tutorial for the R add-on package mboost. The package implements boosting for optimizing general risk functions utilizing component-wise (penalized) least squares estimates as base-learners for fitting various kinds of generalized linear and generalized additive models to potentially high-dimensional data. We give a theoretical background and demonstrate how mboost can be used to fit interpretable models of different complexity. As an example we use mboost to predict the body fat based on anthropometric measurements throughout the tutorial

Assessing internal changes in the future structure of dry-hot compound events: the case of the Pyrenees

Impacts upon vulnerable areas such as mountain ranges may become greater under a future scenario of adverse climatic conditions. In this sense, the concurrence of long dry spells and extremely hot temperatures can induce environmental risks such as wildfires, crop yield losses or other problems, the consequences of which could be much more serious than if these events were to occur separately in time (e.g. only long dry spells). The present study attempts to address recent and future changes in the following dimensions: duration (D), magnitude (M) and extreme magnitude (EM) of compound dry-hot events in the Pyrenees. The analysis focuses upon changes in the extremely long dry spells and extremely high temperatures that occur within these dry periods in order to estimate whether the internal structure of the compound event underwent a change in the observed period (1981-2015) and whether it will change in the future (2006-2100) under intermediate (RCP4.5, where RCP is representative concentration pathway) and high (RCP8.5) emission scenarios. To this end, we quantified the changes in the temporal trends of such events, as well as changes in the bivariate probability density functions for the main Pyrenean regions. The results showed that to date the risk of the compound event has increased by only one dimension - magnitude (including extreme magnitude) - during the last few decades. In relation to the future, increase in risk was found to be associated with an increase in both the magnitude and the duration (extremely long dry spells) of the compound event throughout the Pyrenees during the spring under RCP8.5 and in the northernmost part of this mountain range during summer under this same scenario