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In 1972, the National Institute for Occupational Safety and Health developed an 85 A-weighted decibel recommended exposure level to reduce the risk of hearing loss from occupational noise exposure. When research showed that smoking caused cancer, heart disease, and other health problems, doctors and the public health community spoke out, leading to the first Surgeon General's report on smoking and health, decreased smoking rates, and, eventually, a largely smoke-free environment, with dramatic reductions in morbidity and mortality.

How do you successfully engage an audience in a citizen-science project? The processes developed by eBird (www.ebird.org), a fast-growing web-based tool that now gathers millions of bird observations per month, offers a model.

Extreme weather events are increasing in frequency and intensity as a result of modern climate change. During winter, species may be especially vulnerable to extreme weather as they are surviving on scarce resources and living at the edge of their thermal limits. We compiled data from eBird, a global citizen science initiative, to examine how 41 eastern North American birds shifted their occurrence and abundance patterns immediately following two recent extreme weather events each affecting > 2 million km2, the intrusion of a polar vortex and a winter heat wave. eBird data is continuously collected at high spatiotemporal resolution across large spatial extents, allowing us to compare species' responses immediately before and after these extreme events with trends in other winters across geographic scales. Overall, we found that birds responded differently to each extreme weather event. Bird occurrence rates did not change following the polar vortex, but where species occurred, population density was temporarily reduced, suggesting reductions in number of individuals driven by decreases in behavioral activity or temporary movement out of the area. However, birds demonstrated widespread increases in occurrence and increases in density and number of individuals where they occurred for at least 20 days after the heat wave, hinting at longer‐term range changes. Smaller‐bodied, warm‐adapted passerines tended to be most sensitive to extreme weather and responded most negatively to the polar vortex and most positively to the heat wave, while larger‐bodied, cold‐adapted waterbirds expressed only mild responses to either event. Thus, certain species may be exceptionally sensitive to extreme weather events while others are less sensitive. As climate change progresses and climatic variability increases, researchers and managers must better quantify the broad‐scale sensitivity of different species to multiple types of extreme weather events.

Limited knowledge of the distribution, abundance, and habitat associations of migratory species hinders effective conservation actions. We use Neotropical migratory birds as a model group to compare approaches to prioritize land conservation needed to support ≥30% of the global abundances of 117 species. Specifically, we compare scenarios from spatial optimization models to achieve conservation targets by: 1) area requirements for conserving >30% abundance of each species for each week of the year independently vs. combined; 2) including vs. ignoring spatial clustering of species abundance; and 3) incorporating vs. avoiding human-dominated landscapes. Solutions integrating information across the year require 56% less area than those integrating weekly abundances, with additional reductions when shared-use landscapes are included. Although incorporating spatial population structure requires more area, geographical representation among priority sites improves substantially. These findings illustrate that globally-sourced citizen science data can elucidate key trade-offs among opportunity costs and spatiotemporal representation of conservation efforts. Conservation decisions to protect land used by migratory birds rely on understanding species’ dynamic habitat associations. Here the authors identify conservation scenarios needed to maintain >30% of the abundances of 117 migratory birds across the Americas, considering spatial and temporal patterns of species abundance.

Migration is a common strategy used by birds that breed in seasonal environments. Selection for greater migration efficiency is likely to be stronger for terrestrial species whose migration strategies require non-stop transoceanic crossings. If multiple species use the same transoceanic flyway, then we expect the migration strategies of these species to converge geographically towards the most optimal solution. We test this by examining population-level migration trajectories within the Western Hemisphere for 118 migratory species using occurrence information from eBird. Geographical convergence of migration strategies was evident within specific terrestrial regions where geomorphological features such as mountains or isthmuses constrained overland migration. Convergence was also evident for transoceanic migrants that crossed the Gulf of Mexico or Atlantic Ocean. Here, annual population-level movements were characterized by clockwise looped trajectories, which resulted in faster but more circuitous journeys in the spring and more direct journeys in the autumn. These findings suggest that the unique constraints and requirements associated with transoceanic migration have promoted the spatial convergence of migration strategies. The combination of seasonal atmospheric and environmental conditions that has facilitated the use of similar broad-scale migration strategies may be especially prone to disruption under climate and land-use change.

Large‐scale monitoring of seasonal animal movement is integral to science, conservation and outreach. However, gathering representative movement data across entire species ranges is frequently intractable. Citizen science databases collect millions of animal observations throughout the year, but it is challenging to infer individual movement behaviour solely from observational data. We present BirdFlow, a probabilistic modelling framework that draws on citizen science data from the eBird database to model the population flows of migratory birds. We apply the model to 11 species of North American birds, using GPS and satellite tracking data to tune and evaluate model performance. We show that BirdFlow models can accurately infer individual seasonal movement behaviour directly from eBird relative abundance estimates. Supplementing the model with a sample of tracking data from wild birds improves performance. Researchers can extract a number of behavioural inferences from model results, including migration routes, timing, connectivity and forecasts. The BirdFlow framework has the potential to advance migration ecology research, boost insights gained from direct tracking studies and serve a number of applied functions in conservation, disease surveillance, aviation and public outreach.

Volunteers are increasingly being recruited into citizen science projects to collect observations for scientific studies. An additional goal of these projects is to engage and educate these volunteers. Thus, there are few barriers to participation resulting in volunteer observers with varying ability to complete the project's tasks. To improve the quality of a citizen science project's outcomes it would be useful to account for inter-observer variation, and to assess the rarely tested presumption that participating in a citizen science projects results in volunteers becoming better observers. Here we present a method for indexing observer variability based on the data routinely submitted by observers participating in the citizen science project eBird, a broad-scale monitoring project in which observers collect and submit lists of the bird species observed while birding. Our method for indexing observer variability uses species accumulation curves, lines that describe how the total number of species reported increase with increasing time spent in collecting observations. We find that differences in species accumulation curves among observers equates to higher rates of species accumulation, particularly for harder-to-identify species, and reveals increased species accumulation rates with continued participation. We suggest that these properties of our analysis provide a measure of observer skill, and that the potential to derive post-hoc data-derived measurements of participant ability should be more widely explored by analysts of data from citizen science projects. We see the potential for inferential results from analyses of citizen science data to be improved by accounting for observer skill.

The accurate repair of DNA double-strand breaks (DSBs), highly toxic DNA lesions, is crucial for genome integrity and is tightly regulated during the cell cycle. In mitosis, cells inactivate DSB repair in favor of a tethering mechanism that stabilizes broken chromosomes until they are repaired in the subsequent cell cycle phases. How this is achieved mechanistically is not yet understood, but the adaptor protein TOPBP1 is critically implicated in this process. Here, we identify CIP2A as a TOPBP1-interacting protein that regulates TOPBP1 localization specifically in mitosis. Cells lacking CIP2A display increased radio-sensitivity, micronuclei formation and chromosomal instability. CIP2A is actively exported from the cell nucleus in interphase but, upon nuclear envelope breakdown at the onset of mitosis, gains access to chromatin where it forms a complex with MDC1 and TOPBP1 to promote TOPBP1 recruitment to sites of mitotic DSBs. Collectively, our data uncover CIP2A-TOPBP1 as a mitosis-specific genome maintenance complex. In this work, CIP2A is discovered as a TOPBP1-interacting protein that regulates TOPBP1 localization specifically in mitosis. Cells lacking CIP2A display increased radio-sensitivity, micronuclei formation and chromosomal instability.