The avian scavenger crisis: Looming extinctions, trophic cascades, and loss of critical ecosystem functions

There is no author summary for this article yet. Authors can add summaries to their articles on ScienceOpen to make them more accessible to a non-specialist audience.

Abstract

Related collections

Most cited references 42

Record: found
Abstract: found
Article: not found

An introduction to recursive partitioning: rationale, application, and characteristics of classification and regression trees, bagging, and random forests.

Carolin Strobl, James Malley, Gerhard Tutz (2009)

Recursive partitioning methods have become popular and widely used tools for nonparametric regression and classification in many scientific fields. Especially random forests, which can deal with large numbers of predictor variables even in the presence of complex interactions, have been applied successfully in genetics, clinical medicine, and bioinformatics within the past few years. High-dimensional problems are common not only in genetics, but also in some areas of psychological research, where only a few subjects can be measured because of time or cost constraints, yet a large amount of data is generated for each subject. Random forests have been shown to achieve a high prediction accuracy in such applications and to provide descriptive variable importance measures reflecting the impact of each variable in both main effects and interactions. The aim of this work is to introduce the principles of the standard recursive partitioning methods as well as recent methodological improvements, to illustrate their usage for low and high-dimensional data exploration, but also to point out limitations of the methods and potential pitfalls in their practical application. Application of the methods is illustrated with freely available implementations in the R system for statistical computing. (c) 2009 APA, all rights reserved.

0 comments Cited 607 times – based on 0 reviews      Review now

Bookmark

Record: found
Abstract: found
Article: not found

Multiple causes of high extinction risk in large mammal species.

Marcel Cardillo, Georgina Mace, Kate E. Jones … (2005)

Many large animal species have a high risk of extinction. This is usually thought to result simply from the way that species traits associated with vulnerability, such as low reproductive rates, scale with body size. In a broad-scale analysis of extinction risk in mammals, we find two additional patterns in the size selectivity of extinction risk. First, impacts of both intrinsic and environmental factors increase sharply above a threshold body mass around 3 kilograms. Second, whereas extinction risk in smaller species is driven by environmental factors, in larger species it is driven by a combination of environmental factors and intrinsic traits. Thus, the disadvantages of large size are greater than generally recognized, and future loss of large mammal biodiversity could be far more rapid than expected.