Mapping species distributions: A comparison of skilled naturalist and lay citizen science recording

To assess the ability of traditional biological recording schemes and lay citizen science approaches to gather data on species distributions and changes therein, we examined bumblebee records from the UK’s national repository (National Biodiversity Network) and from BeeWatch. The two recording approaches revealed similar relative abundances of bumblebee species but different geographical distributions. For the widespread common carder (Bombus pascuorum), traditional recording scheme data were patchy, both spatially and temporally, reflecting active record centre rather than species distribution. Lay citizen science records displayed more extensive geographic coverage, reflecting human population density, thus offering better opportunities to account for recording effort. For the rapidly spreading tree bumblebee (Bombus hypnorum), both recording approaches revealed similar distributions due to a dedicated mapping project which overcame the patchy nature of naturalist records. We recommend, where possible, complementing skilled naturalist recording with lay citizen science programmes to obtain a nation-wide capability, and stress the need for timely uploading of data to the national repository

Citizen science: a new approach to advance ecology, education, and conservation

Citizen science has a long history in the ecological sciences and has made substantial contributions to science, education, and society. Developments in information technology during the last few decades have created new opportunities for citizen science to engage ever larger audiences of volunteers to help address some of ecology’s most pressing issues, such as global environmental change. Using online tools, volunteers can find projects that match their interests and learn the skills and protocols required to develop questions, collect data, submit data, and help process and analyze data online. Citizen science has become increasingly important for its ability to engage large numbers of volunteers to generate observations at scales or resolutions unattainable by individual researchers. As a coupled natural and human approach, citizen science can also help researchers access local knowledge and implement conservation projects that might be impossible otherwise. In Japan, however, the value of citizen science to science and society is still underappreciated. Here we present case studies of citizen science in Japan, the United States, and the United Kingdom, and describe how citizen science is used to tackle key questions in ecology and conservation, including spatial and macro-ecology, management of threatened and invasive species, and monitoring of biodiversity. We also discuss the importance of data quality, volunteer recruitment, program evaluation, and the integration of science and human systems in citizen science projects. Finally, we outline some of the primary challenges facing citizen science and its future.Dr. Janis L. Dickinson was the keynote speaker at the international symposium at the 61th annual meeting of the Ecological Society of Japan. We appreciate the Ministry of Education, Culture, Sports, Science and Technology in Japan for providing grant to Hiromi Kobori (25282044). Tatsuya Amano is financially supported by the European Commission’s Marie Curie International Incoming Fellowship Programme (PIIF-GA-2011- 303221). The findings and conclusions in this report are those of the authors and do not necessarily represent the views of the funding agencies or the Department of the Interior or the US Government.This is the final version of the article. It was first available from Springer via http://dx.doi.org/10.1007/s11284-015-1314-

Tomislav Durbešić (1928.-2001.). Iz Tomove bilježnice

We use a recent study on the effects of neonicotinoids on bees as a concrete example to reinforce the advice of OEPP/EPPO (2010) that strong inference is impossible if there is no true replication and that analyses based on pseudoreplication are invalid.PostprintPeer reviewe

Broad-Scale Patterns of Late Jurassic Dinosaur Paleoecology

There have been numerous studies on dinosaur biogeographic distribution patterns. However, these distribution data have not yet been applied to ecological questions. Ecological studies of dinosaurs have tended to focus on reconstructing individual taxa, usually through comparisons to modern analogs. Fewer studies have sought to determine if the ecological structure of fossil assemblages is preserved and, if so, how dinosaur communities varied. Climate is a major component driving differences between communities. If the ecological structure of a fossil locality is preserved, we expect that dinosaur assemblages from similar environments will share a similar ecological structure.This study applies Ecological Structure Analysis (ESA) to a dataset of 100+ dinosaur taxa arranged into twelve composite fossil assemblages from around the world. Each assemblage was assigned a climate zone (biome) based on its location. Dinosaur taxa were placed into ecomorphological categories. The proportion of each category creates an ecological profile for the assemblage, which were compared using cluster and principal components analyses. Assemblages grouped according to biome, with most coming from arid or semi-arid/seasonal climates. Differences between assemblages are tied to the proportion of large high-browsing vs. small ground-foraging herbivores, which separates arid from semi-arid and moister environments, respectively. However, the effects of historical, taphonomic, and other environmental factors are still evident.This study is the first to show that the general ecological structure of Late Jurassic dinosaur assemblages is preserved at large scales and can be assessed quantitatively. Despite a broad similarity of climatic conditions, a degree of ecological variation is observed between assemblages, from arid to moist. Taxonomic differences between Asia and the other regions demonstrate at least one case of ecosystem convergence. The proportion of different ecomorphs, which reflects the prevailing climatic and environmental conditions present during fossil deposition, may therefore be used to differentiate Late Jurassic dinosaur fossil assemblages. This method is broadly applicable to different taxa and times, allowing one to address questions of evolutionary, biogeographic, and climatic importance

The evolution of Müllerian mimicry

It is now 130 years since Fritz Müller proposed an evolutionary explanation for the close similarity of co-existing unpalatable prey species, a phenomenon now known as Müllerian mimicry. Müller’s hypothesis was that unpalatable species evolve a similar appearance to reduce the mortality involved in training predators to avoid them, and he backed up his arguments with a mathematical model in which predators attack a fixed number (n) of each distinct unpalatable type in a given season before avoiding them. Here, I review what has since been discovered about Müllerian mimicry and consider in particular its relationship to other forms of mimicry. Müller’s specific model of associative learning involving a “fixed n” in a given season has not been supported, and several experiments now suggest that two distinct unpalatable prey types may be just as easy to learn to avoid as one. Nevertheless, Müller’s general insight that novel unpalatable forms have higher mortality than common unpalatable forms as a result of predation has been well supported by field experiments. From its inception, there has been a heated debate over the nature of the relationship between Müllerian co-mimics that differ in their level of defence. There is now a growing awareness that this relationship can be mediated by many factors, including synergistic effects between co-mimics that differ in their mode of defence, rates of generalisation among warning signals and concomitant changes in prey density as mimicry evolves. I highlight areas for future enquiry, including the possibility of Müllerian mimicry systems based on profitability rather than unprofitability and the co-evolution of defence

Supernova neutrino burst detection with the Deep Underground Neutrino Experiment

The Deep Underground Neutrino Experiment (DUNE), a 40-kton underground liquid argon time projection chamber experiment, will be sensitive to the electron-neutrino flavor component of the burst of neutrinos expected from the next Galactic core-collapse supernova. Such an observation will bring unique insight into the astrophysics of core collapse as well as into the properties of neutrinos. The general capabilities of DUNE for neutrino detection in the relevant few- to few-tens-of-MeV neutrino energy range will be described. As an example, DUNE's ability to constrain the νe spectral parameters of the neutrino burst will be considered

Neutrino interaction classification with a convolutional neural network in the DUNE far detector

The Deep Underground Neutrino Experiment is a next-generation neutrino oscillation experiment that aims to measure CP-violation in the neutrino sector as part of a wider physics program. A deep learning approach based on a convolutional neural network has been developed to provide highly efficient and pure selections of electron neutrino and muon neutrino charged-current interactions. The electron neutrino (antineutrino) selection efficiency peaks at 90% (94%) and exceeds 85% (90%) for reconstructed neutrino energies between 2–5 GeV. The muon neutrino (antineutrino) event selection is found to have a maximum efficiency of 96% (97%) and exceeds 90% (95%) efficiency for reconstructed neutrino energies above 2 GeV. When considering all electron neutrino and antineutrino interactions as signal, a selection purity of 90% is achieved. These event selections are critical to maximize the sensitivity of the experiment to CP-violating effects

Experiment simulation configurations approximating DUNE TDR

The Deep Underground Neutrino Experiment (DUNE) is a next-generation long-baseline neutrino oscillation experiment consisting of a high-power, broadband neutrino beam, a highly capable near detector located on site at Fermilab, in Batavia, Illinois, and a massive liquid argon time projection chamber (LArTPC) far detector located at the 4850L of Sanford Underground Research Facility in Lead, South Dakota. The long-baseline physics sensitivity calculations presented in the DUNE Physics TDR, and in a related physics paper, rely upon simulation of the neutrino beam line, simulation of neutrino interactions in the near and far detectors, fully automated event reconstruction and neutrino classification, and detailed implementation of systematic uncertainties. The purpose of this posting is to provide a simplified summary of the simulations that went into this analysis to the community, in order to facilitate phenomenological studies of long-baseline oscillation at DUNE. Simulated neutrino flux files and a GLoBES configuration describing the far detector reconstruction and selection performance are included as ancillary files to this posting. A simple analysis using these configurations in GLoBES produces sensitivity that is similar, but not identical, to the official DUNE sensitivity. DUNE welcomes those interested in performing phenomenological work as members of the collaboration, but also recognizes the benefit of making these configurations readily available to the wider community