Universality of Cherenkov Light in EAS

The reconstruction of cosmic-ray-induced extensive air showers with a non-imaging Cherenkov detector array requires knowledge of the Cherenkov yield of any given air shower for a given set of shower parameters. Although air showers develop in a stochastic cascade, certain characteristics of the particles in the shower have been shown to come from universal probability distributions, a property known as shower universality. Both the energy and the angular distributions of charged particles within a shower have been parameterized. One can use these distributions to calculate the Cherenkov photon yield as an angular distribution from the Cherenkov cones of charged particles at various stages of shower development. This Cherenkov photon yield can then be tabulated for use in the reconstruction of air showers. In this work, we develop the calculation of both the Cherenkov angular distribution and Cherenkov yield per shower particle, and show how a look-up table was constructed to capture the relevant features of these distributions for general use. We compare the results of our calculations with the results of full, particle-stack, Monte Carlo simulation of the Cherenkov light produced in extensive air showers using CORSIKA-IACT. We make comparisons of both the lateral distribution of the Cherenkov photon flux amongst several detectors and of the arrival-time distribution of the Cherenkov photons in a single detector

Multi-species population indices for sets of species including rare, disappearing or newly occurring species

NI is funded by Natural Environment Research Council award NE/R016429/1 as part of the UK-SCAPE programme delivering National Capability.Multi-species indices (MSI) are widely used as ecological indicators and as instruments to inform environmental policies. Many of these indices combine species-specific estimates of relative population sizes using the geometric mean. Because the geometric mean is not defined when values of zero occur, usually only commoner species are included in MSIs and zero values are replaced by a small non-zero value. The latter can exhibit an arbitrary influence on the geometric mean MSI. Here, we show how the compound Poisson and the negative binomial model can be used in such cases to obtain an MSI that has similar features to the geometric mean, including weighting halving and doubling of a species’ population equally. In contrast to the geometric mean, these two statistical models can handle zero values in population sizes and thus accommodate newly occurring and temporarily or permanently disappearing species in the MSI. We compare the MSIs obtained by the two statistical models with the geometric mean MSI and measure sensitivity to changes in evenness and to population trends in rare and abundant species. Additionally, we outline sources of uncertainty and discuss how to measure them. We found that, in contrast to the geometric mean and the negative binomial MSI, the compound Poisson MSI is less sensitive to changes in evenness when total abundance is constant. Further, we found that the compound Poisson model can be influenced more than the other two methods by trends of species showing a low interannual variance. The negative binomial MSI is less sensitive to trends in rare species compared with the other two methods, and similarly sensitive to trends in abundant species as the geometric mean. While the two new MSIs have the advantage that they are not arbitrarily influenced by rare, newly appearing and disappearing species, both do not weight all species equally. We recommend replacing the geometric mean MSI with either compound Poisson or negative binomial when there are species with a population size of zero in some years having a strong influence on the geometric mean MSI. Further, we recommend providing additional information alongside the MSIs. For example, it is particularly important to give an evenness index in addition to the compound Poisson MSI and to indicate the number of disappearing and newly occurring species alongside the negative binomial MSI.Publisher PDFPeer reviewe

A generic method for estimating and smoothing multispecies biodiversity indices using intermittent data

Biodiversity indicators summarise extensive, complex ecological data sets and are important in influencing government policy. Component data consist of time-varying indices for each of a number of different species. However, current biodiversity indicators suffer from multiple statistical shortcomings. We describe a state-space formulation for new multispecies biodiversity indicators, based on rates of change in the abundance or occupancy probability of the contributing individual species. The formulation is flexible and applicable to different taxa. It possesses several advantages, including the ability to accommodate the sporadic unavailability of data, incorporate variation in the estimation precision of the individual species’ indices when appropriate, and allow the direct incorporation of smoothing over time. Furthermore, model fitting is straightforward in Bayesian and classical implementations, the latter adopting either efficient Hidden Markov modelling or the Kalman filter. Conveniently, the same algorithms can be adopted for cases based on abundance or occupancy data—only the subsequent interpretation differs. The procedure removes the need for bootstrapping which can be prohibitive. We recommend which of two alternatives to use when taxa are fully or partially sampled. The performance of the new approach is demonstrated on simulated data, and through application to three diverse national UK data sets on butterflies, bats and dragonflies. We see that uncritical incorporation of index standard errors should be avoided

Neutrino propagation in the Earth and emerging charged leptons with nuPyProp\texttt{nuPyProp}

Ultra-high-energy neutrinos serve as messengers of some of the highest energy astrophysical environments. Given that neutrinos are neutral and only interact via weak interactions, neutrinos can emerge from sources, traverse astronomical distances, and point back to their origins. Their weak interactions require large target volumes for neutrino detection. Using the Earth as a neutrino converter, terrestrial, sub-orbital, and satellite-based instruments are able to detect signals of neutrino-induced extensive air showers. In this paper, we describe the software code $\texttt{nuPyProp}$ that simulates tau neutrino and muon neutrino interactions in the Earth and predicts the spectrum of the $\tau$-lepton and muons that emerge. The $\texttt{nuPyProp}$ outputs are lookup tables of charged lepton exit probabilities and energies that can be used directly or as inputs to the $\texttt{nuSpaceSim}$ code designed to simulate optical and radio signals from extensive air showers induced by the emerging charged leptons. We describe the inputs to the code, demonstrate its flexibility and show selected results for $\tau$-lepton and muon exit probabilities and energy distributions. The $\texttt{nuPyProp}$ code is open source, available on github.Comment: 42 pages, 21 figures, code available at https://github.com/NuSpaceSim/nupypro

The Effects of Restoring Logged Tropical Forests on Avian Phylogenetic and Functional Diversity.

Selective logging is the most prevalent land-use change in the tropics. Despite the resulting degradation of forest structure, selectively logged forests still harbour a substantial amount of biodiversity leading to suggestions that their protection is the next best alternative to conserving primary, old-growth forests. Restoring carbon stocks under Reducing Emissions from Deforestation and Forest Degradation (REDD+) schemes is a potential method for obtaining funding to protect logged forests, via enrichment planting and liberation cutting of vines. This study investigates the impacts of restoring logged forests in Borneo on avian phylogenetic diversity-the total evolutionary history shared across all species within a community-and on functional diversity, with important implications for the protection of evolutionarily unique species and the provision of many ecosystem services. Overall and understorey avifaunal communities were studied using point count and mist-netting surveys, respectively. Restoration caused a significant loss in phylogenetic diversity and MPD (mean pairwise distance) leaving an overall bird community of less total evolutionary history and more closely related species compared to unlogged forests, while the understorey bird community had MNTD (mean nearest taxon distance) that returned towards the lower levels found in a primary forest, indicating more closely related species pairs. The overall bird community experienced a significant loss of functional strategies and species with more specialized traits in restored forests compared to that of unlogged forests, which led to functional clustering in the community. Restoration also led to a reduction in functional richness and thus niches occupied in the understorey bird community compared to unlogged forests. While there are additional benefits of restoration for forest regeneration, carbon sequestration, future timber harvests, and potentially reduced threat of forest conversion, this must be weighed against the apparent loss of phylogenetic and functional diversity from unlogged forest levels, making the biodiversity-friendliness of carbon sequestration schemes questionable under future REDD+ agreements. To reduce perverse biodiversity outcomes, it is important to focus restoration only on the most degraded areas or at reduced intensity where breaks between regimes are incorporated. This article is protected by copyright. All rights reserved

Winners and losers over 35 years of dragonfly and damselfly distributional change in Germany

Aim: Recent studies suggest insect declines in parts of Europe; however, the generality of these trends across different taxa and regions remains unclear. Standardized data are not available to assess large-scale, long-term changes for most insect groups but opportunistic citizen science data are widespread for some. Here, we took advantage of citizen science data to investigate distributional changes of Odonata. Location: Germany. Methods: We compiled over 1 million occurrence records from different regional databases. We used occupancy-detection models to account for imperfect detection and estimate annual distributions for each species during 1980–2016 within 5 × 5 km quadrants. We also compiled data on species attributes that were hypothesized to affect species’ sensitivity to different drivers and related them to the changes in species’ distributions. We further developed a novel approach to cluster groups of species with similar patterns of distributional change to represent multispecies indicators. Results: More species increased (45%) than decreased (29%) or remained stable (26%) in their distribution (i.e. number of occupied quadrants). Species showing increases were generally warm-adapted species and/or running water species, while species showing decreases were cold-adapted species using standing water habitats such as bogs. Time series clustering defined five main patterns of change—each associated with a specific combination of species attributes, and confirming the key roles of species’ temperature and habitat preferences. Overall, our analysis predicted that mean quadrant-level species richness has increased over most of the time period. Main conclusions: Trends in Odonata provide mixed news—improved water quality, coupled with positive impacts of climate change, could explain the positive trends of many species. At the same time, declining species point to conservation challenges associated with habitat loss and degradation. Our study demonstrates the great value of citizen science and the work of natural history societies for assessing large-scale distributional change

Distance sampling and the challenge of monitoring butterfly populations

1. Abundance indices generated by the UK Butterfly Monitoring Scheme (UKBMS) have been influential in informing our understanding of environmental change and highlighting UK conservation priorities. Here, we critically evaluate the standard ‘Pollard Walk’ methodology employed by the UKBMS. 2. We consider the systematic sampling biases among different butterfly species and biotopes using distance sampling. We collected over 5000 observations on 17 species using distance sampling at 13 study sites in England and Wales. We fitted detection functions to explore variation in detectability among species and sites. 3. Our results suggest that around one-third of individual butterflies in the Pollard Walk box were missed. However, detectability varies markedly among species and sites. We provide the first species-specific estimates of detectability for converting Pollard Walk data into population densities. A few species show no drop off in detectability and most require only a modest correction factor, but for the least detectable species, we estimate that 3/4 of individuals are not recorded. 4. Much of the variation among sites is explained by substantially higher detectability among sites in England than in Wales, which had different recorders. Biological traits have only limited explanatory power in distinguishing detectable vs undetectable species. 5. The variation in detectability is small compared with the variation in true abundance, such that population density estimates from the Pollard Walk are highly correlated with those derived from distance sampling. 6. These results are used to evaluate the robustness of the Pollard Walk for comparisons of abundance across species, across sites and over time. UKBMS data provide a good reflection of relative abundance for most species and of large-scale trends in abundance. We also consider the practicalities of applying distance sampling to butterfly monitoring in general. Distance sampling is a valuable tool for quantifying bias and imprecision and has a role in surveying species of conservation concern, but is not viable as a wholesale replacement for simpler methods for large-scale monitoring of multispecies butterfly communities by volunteer recorders

Multi-species population indices for sets of species including rare, disappearing or newly occurring species

Multi-species indices (MSI) are widely used as ecological indicators and as instruments to inform environmental policies. Many of these indices combine species-specific estimates of relative population sizes using the geometric mean. Because the geometric mean is not defined when values of zero occur, usually only commoner species are included in MSIs and zero values are replaced by a small non-zero value. The latter can exhibit an arbitrary influence on the geometric mean MSI. Here, we show how the compound Poisson and the negative binomial model can be used in such cases to obtain an MSI that has similar features to the geometric mean, including weighting halving and doubling of a species’ population equally. In contrast to the geometric mean, these two statistical models can handle zero values in population sizes and thus accommodate newly occurring and temporarily or permanently disappearing species in the MSI. We compare the MSIs obtained by the two statistical models with the geometric mean MSI and measure sensitivity to changes in evenness and to population trends in rare and abundant species. Additionally, we outline sources of uncertainty and discuss how to measure them. We found that, in contrast to the geometric mean and the negative binomial MSI, the compound Poisson MSI is less sensitive to changes in evenness when total abundance is constant. Further, we found that the compound Poisson model can be influenced more than the other two methods by trends of species showing a low interannual variance. The negative binomial MSI is less sensitive to trends in rare species compared with the other two methods, and similarly sensitive to trends in abundant species as the geometric mean. While the two new MSIs have the advantage that they are not arbitrarily influenced by rare, newly appearing and disappearing species, both do not weight all species equally. We recommend replacing the geometric mean MSI with either compound Poisson or negative binomial when there are species with a population size of zero in some years having a strong influence on the geometric mean MSI. Further, we recommend providing additional information alongside the MSIs. For example, it is particularly important to give an evenness index in addition to the compound Poisson MSI and to indicate the number of disappearing and newly occurring species alongside the negative binomial MSI