Advances in Statistical Ecology: New Methods and Software

Statistics has been arguably one of the hottest scientific fields in the last ten years, with implications in many aspects of technology. Presumably, the most significant aspect of this recent trend has been the surge of the data analytics revolution, or in other words, the recognition that data had become ubiquitous and that efficient techniques for storage, sharing and analysis would be key to the improvement of many aspects of our everyday life. This triggered an explosion in the sizes of communities of statistics users and developers, with important positive feedbacks such as the proliferation of data-oriented programs and web contents.
Ecology has been no stranger to this process and the aim of this Research Topic is to contribute to the review and rapid dissemination of recent statistical methods in the field. In doing so, it will strive to be doubly inclusive. First, we invite contributions relevant to the study of any biotic and abiotic processes involved in the interaction between living organisms and their environment. Second, we encourage not only the submission of novel data analytics methods (including statistical models and machine learning techniques), but also articles describing original applications of existing methods and descriptions of new computer resources, including programs, user interfaces, infrastructures for data sharing, and more generally any data science resource contributing to reproducible research in ecology. Submission of review articles on related topics is also welcome.

Keywords: statistical models, machine learning, algorithms, computer programs, reproducible research

Important Note: All contributions to this Research Topic must be within the scope of the section and journal to which they are submitted, as defined in their mission statements. Frontiers reserves the right to guide an out-of-scope manuscript to a more suitable section or journal at any stage of peer review.