The problem with delineating narrow criteria for citizen science

No abstract available.http://www.pnas.org2020-01-30hj2019Forestry and Agricultural Biotechnology Institute (FABI

SNAPSHOT USA 2019 : a coordinated national camera trap survey of the United States

This article is protected by copyright. All rights reserved.With the accelerating pace of global change, it is imperative that we obtain rapid inventories of the status and distribution of wildlife for ecological inferences and conservation planning. To address this challenge, we launched the SNAPSHOT USA project, a collaborative survey of terrestrial wildlife populations using camera traps across the United States. For our first annual survey, we compiled data across all 50 states during a 14-week period (17 August - 24 November of 2019). We sampled wildlife at 1509 camera trap sites from 110 camera trap arrays covering 12 different ecoregions across four development zones. This effort resulted in 166,036 unique detections of 83 species of mammals and 17 species of birds. All images were processed through the Smithsonian's eMammal camera trap data repository and included an expert review phase to ensure taxonomic accuracy of data, resulting in each picture being reviewed at least twice. The results represent a timely and standardized camera trap survey of the USA. All of the 2019 survey data are made available herein. We are currently repeating surveys in fall 2020, opening up the opportunity to other institutions and cooperators to expand coverage of all the urban-wild gradients and ecophysiographic regions of the country. Future data will be available as the database is updated at eMammal.si.edu/snapshot-usa, as well as future data paper submissions. These data will be useful for local and macroecological research including the examination of community assembly, effects of environmental and anthropogenic landscape variables, effects of fragmentation and extinction debt dynamics, as well as species-specific population dynamics and conservation action plans. There are no copyright restrictions; please cite this paper when using the data for publication.Publisher PDFPeer reviewe

Mammal responses to global changes in human activity vary by trophic group and landscape

Wildlife must adapt to human presence to survive in the Anthropocene, so it is critical to understand species responses to humans in different contexts. We used camera trapping as a lens to view mammal responses to changes in human activity during the COVID-19 pandemic. Across 163 species sampled in 102 projects around the world, changes in the amount and timing of animal activity varied widely. Under higher human activity, mammals were less active in undeveloped areas but unexpectedly more active in developed areas while exhibiting greater nocturnality. Carnivores were most sensitive, showing the strongest decreases in activity and greatest increases in nocturnality. Wildlife managers must consider how habituation and uneven sensitivity across species may cause fundamental differences in human–wildlife interactions along gradients of human influence.Peer reviewe

Teaching R in the Undergraduate Ecology Classroom: Approaches, Lessons Learned, and Recommendations

Learning ecology requires training in data management and analysis. Because of its transparent and flexible nature, R is increasingly used for data management and analysis in the field of ecology. Consequently, job postings targeting candidates with a bachelor\u27s degree and a required knowledge of R have increased over the past ten years. In this paper, we begin by presenting data from the last ten years demonstrating the increase in the use of R, an open-source programming environment, in ecology and its prevalence as a required skill in job descriptions. We then discuss our experiences teaching undergraduates R in two advanced ecology classes using different approaches. One approach, in a course with a field laboratory, focused on collecting, cleaning, and preparing data for analysis. The other approach, in a course without a field laboratory, focused on analyzing existing datasets and applying the results to content discussed in the lecture portion of the course. Our experiences determined that each approach had strengths and weaknesses. We recommend that above all, instructors of ecology and related subjects should be encouraged to include R in their coursework. Furthermore, instructors should be aware of the following: Learning R is a separate skill from learning statistics; writing R assignments is a significant time commitment for course preparation; and there is a tradeoff between teaching R and teaching content. Determining how one\u27s course fits into the curriculum and identifying resources outside of the classroom for students’ continued practice will ensure that R training is successful and will extend beyond a one-semester course