The need for sound ecological science has escalated alongside the rise of the information age and “big data” across all sectors of society. Big data generally refer to massive volumes of data not readily handled by the usual data tools and practices and present unprecedented opportunities for advancing science and informing resource management through data‐intensive approaches. The era of big data need not be propelled only by “big science” – the term used to describe large‐scale efforts that have had mixed success in the individual‐driven culture of ecology. Collectively, ecologists already have big data to bolster the scientific effort – a large volume of distributed, high‐value information – but many simply fail to contribute. We encourage ecologists to join the larger scientific community in global initiatives to address major scientific and societal problems by bringing their distributed data to the table and harnessing its collective power. The scientists who contribute such information will be at the forefront of socially relevant science – but will they be ecologists?

Variation in length and asymmetry of wing primary feathers can arise from a breakdown of developmental homeostasis, feather abrasion and incomplete growth durin...

The scale and magnitude of complex and pressing environmental issues lend urgency to the need for integrative and reproducible analysis and synthesis, facilitated by data-intensive research approaches. However, the recent pace of technological change has been such that appropriate skills to accomplish data-intensive research are lacking among environmental scientists, who more than ever need greater access to training and mentorship in computational skills. Here, we provide a roadmap for raising data competencies of current and next-generation environmental researchers by describing the concepts and skills needed for effectively engaging with the heterogeneous, distributed, and rapidly growing volumes of available data. We articulate five key skills: (1) data management and processing, (2) analysis, (3) software skills for science, (4) visualization, and (5) communication methods for collaboration and dissemination. We provide an overview of the current suite of training initiatives available to environmental scientists and models for closing the skill-transfer gap.

The peer review model is one of the most important tools used in science to assess the relative merit of research. We manipulated a published article to reflect one of the following four author designations: female, male, initial, and no name provided. This article was then reviewed by referees of both genders at various stages of scientific training. Name changing did not influence acceptance rates or quality ratings. Undergraduate referees were less critical than graduate students or postdoctoral researchers, independent of gender. However, female postdoctoral researchers were the most critical referees: Their rejection rates were the highest and quality ratings the lowest, regardless of the author name provided. Contrary to previous reports in the literature, there was no evidence of same-gender preferences. This study strongly suggests that female postgraduate biologists may apply different expectations to peer review. © 2009 by American Institute of Biological Sciences. All rights reserved