Citizen science can improve conservation science, natural resource management, and environmental protection

Citizen science has advanced science for hundreds of years, contributed to many peer-reviewed articles, and informed land management decisions and policies across the United States. Over the last 10 years, citizen science has grown immensely in the United States and many other countries. Here, we show how citizen science is a powerful tool for tackling many of the challenges faced in the field of conservation biology. We describe the two interwoven paths bywhich citizen science can improve conservation efforts, natural resource management, and environmental protection. The first path includes building scientific knowledge, while the other path involves informing policy and encouraging public action. We explore how citizen science is currently used and describe the investments needed to create a citizen science program. We find that: 1. Citizen science already contributes substantially to many domains of science, including conservation, natural resource, and environmental science. Citizen science informs natural resource management, environmental protection, and policymaking and fosters public input and engagement. 2. Many types of projects can benefit fromcitizen science, but one must be careful tomatch the needs for science and public involvement with the right type of citizen science project and the right method of public participation. 3. Citizen science is a rigorous process of scientific discovery, indistinguishable from conventional science apart from the participation of volunteers.When properly designed, carried out, and evaluated, citizen science can provide sound science, efficiently generate high-quality data, and help solve problems

Internet of Things for Sustainable Forestry

Forests and grasslands play an important role in water and air purification, prevention of the soil erosion, and in provision of habitat to wildlife. Internet of Things has a tremendous potential to play a vital role in the forest ecosystem management and stability. The conservation of species and habitats, timber production, prevention of forest soil degradation, forest fire prediction, mitigation, and control can be attained through forest management using Internet of Things. The use and adoption of IoT in forest ecosystem management is challenging due to many factors. Vast geographical areas and limited resources in terms of budget and equipment are some of the limiting factors. In digital forestry, IoT deployment offers effective operations, control, and forecasts for soil erosion, fires, and undesirable depositions. In this chapter, IoT sensing and communication applications are presented for digital forestry systems. Different IoT systems for digital forest monitoring applications are also discussed

Supervised versus unsupervised categorization: Two sides of the same coin?

Supervised and unsupervised categorization have been studied in separate research traditions. A handful of studies have attempted to explore a possible convergence between the two. The present research builds on these studies, by comparing the unsupervised categorization results of Pothos et al. (submitted; 2008) with the results from two procedures of supervised categorization. In two experiments, we tested 375 participants with nine different stimulus sets, and examined the relation between ease of learning of a classification, memory for a classification, and spontaneous preference for a classification. After taking into account the role of the number of category labels (clusters) in supervised learning, we found the three variables to be closely associated with each other. Our results provide encouragement for researchers seeking unified theoretical explanations for supervised and unsupervised categorization, but raise a range of challenging theoretical questions

Microbial ligand costimulation drives neutrophilic steroid-refractory asthma

Funding: The authors thank the Wellcome Trust (102705) and the Universities of Aberdeen and Cape Town for funding. This research was also supported, in part, by National Institutes of Health GM53522 and GM083016 to DLW. KF and BNL are funded by the Fonds Wetenschappelijk Onderzoek, BNL is the recipient of an European Research Commission consolidator grant and participates in the European Union FP7 programs EUBIOPRED and MedALL. The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.Peer reviewedPublisher PD