Effects of Roads and Traffic on Wildlife Populations and Landscape Function Road Ecology is Moving toward Larger Scales

Road ecology has developed into a significant branch of ecology with steady growth in the number of refereed journal articles, books, conferences, symposia, and “best practice” guidelines being produced each year. The main objective of this special issue of Ecology and Society is to highlight the need for studies that document the population, community, and ecosystem-level effects of roads and traffic by publishing studies that document these effects. It became apparent when compiling this special issue that there is a paucity of studies that explicitly examined higher order effects of roads and traffic. No papers on landscape function or ecosystem-level effects were submitted, despite being highlighted as a priority for publication. The 17 papers in this issue, from Australia, Canada, the Netherlands, and USA, all deal to some extent with either population or community-level effects of roads and traffic. Nevertheless, many higher order effects remain unquantified, and must become the focus of future studies because the complexity and interactions among the effects of roads and traffic are large and potentially unexpected. An analysis of these complex interrelations requires systematic research, and it is necessary to further establish collaborative links between ecologists and transportation agencies. Many road agencies have “environmental sustainability” as one of their goals and the only way to achieve such goals is for them to support and foster long-term and credible scientific research. The current situation, with numerous small-scale projects being undertaken independently of each other, cannot provide the information required to quantify and mitigate the negative effects of roads and traffic on higher levels. The future of road ecology research will be best enhanced when multiple road projects in different states or countries are combined and studied as part of integrated, well-replicated research projects

Study of Z → llγ decays at √s = 8 TeV with the ATLAS detector

This paper presents a study of Z → llγ decays with the ATLAS detector at the Large Hadron Collider. The analysis uses a proton–proton data sample corresponding to an integrated luminosity of 20.2 fb−1 collected at a centre-ofmass energy √s = 8 TeV. Integrated fiducial cross-sections together with normalised differential fiducial cross-sections, sensitive to the kinematics of final-state QED radiation, are obtained. The results are found to be in agreement with stateof-the-art predictions for final-state QED radiation. First measurements of Z → llγ γ decays are also reported

Constraints on spin-0 dark matter mediators and invisible Higgs decays using ATLAS 13 TeV pp collision data with two top quarks and missing transverse momentum in the final state

This paper presents a statistical combination of searches targeting final states with two top quarks and invisible particles, characterised by the presence of zero, one or two leptons, at least one jet originating from a b-quark and missing transverse momentum. The analyses are searches for phenomena beyond the Standard Model consistent with the direct production of dark matter in pp collisions at the LHC, using 139 fb−1 of data collected with the ATLAS detector at a centre-of-mass energy of 13 TeV. The results are interpreted in terms of simplified dark matter models with a spin-0 scalar or pseudoscalar mediator particle. In addition, the results are interpreted in terms of upper limits on the Higgs boson invisible branching ratio, where the Higgs boson is produced according to the Standard Model in association with a pair of top quarks. For scalar (pseudoscalar) dark matter models, with all couplings set to unity, the statistical combination extends the mass range excluded by the best of the individual channels by 50 (25) GeV, excluding mediator masses up to 370 GeV. In addition, the statistical combination improves the expected coupling exclusion reach by 14% (24%), assuming a scalar (pseudoscalar) mediator mass of 10 GeV. An upper limit on the Higgs boson invisible branching ratio of 0.38 (0.30+0.13−0.09) is observed (expected) at 95% confidence level

Deep generative models for fast photon shower simulation in ATLAS

The need for large-scale production of highly accurate simulated event samples for the extensive physics programme of the ATLAS experiment at the Large Hadron Collider motivates the development of new simulation techniques. Building on the recent success of deep learning algorithms, variational autoencoders and generative adversarial networks are investigated for modelling the response of the central region of the ATLAS electromagnetic calorimeter to photons of various energies. The properties of synthesised showers are compared with showers from a full detector simulation using geant4. Both variational autoencoders and generative adversarial networks are capable of quickly simulating electromagnetic showers with correct total energies and stochasticity, though the modelling of some shower shape distributions requires more refinement. This feasibility study demonstrates the potential of using such algorithms for ATLAS fast calorimeter simulation in the future and shows a possible way to complement current simulation techniques

Search for doubly charged Higgs boson production in multi-lepton final states using 139 fb−1 of proton–proton collisions at s√ = 13 TeV with the ATLAS detector

A search for pair production of doubly charged Higgs bosons (H±± ), each decaying into a pair of prompt, isolated, and highly energetic leptons with the same electric charge, is presented. The search uses a proton–proton collision data sample at a centre-of-mass energy of 13 TeV corresponding to an integrated luminosity of 139 fb−1 recorded by the ATLAS detector during Run 2 of the Large Hadron Collider (LHC). This analysis focuses on same-charge leptonic decays, H±±→ℓ±ℓ′± where ℓ,ℓ′=e,μ,τ, in two-, three-, and four-lepton channels, but only considers final states which include electrons or muons. No evidence of a signal is observed. Corresponding upper limits on the production cross-section of a doubly charged Higgs boson are derived, as a function of its mass m(H±±), at 95% confidence level. Assuming that the branching ratios to each of the possible leptonic final states are equal, B(H±±→e±e±)=B(H±±→e±μ±)=B(H±±→μ±μ±)=B(H±±→e±τ±)=B(H±±→μ±τ±)=B(H±±→τ±τ±)=1/6, the observed (expected) lower limit on the mass of a doubly charged Higgs boson is 1080 GeV (1065 GeV) within the left-right symmetric type-II seesaw model, which is the strongest limit to date produced by the ATLAS Collaboration. Additionally, this paper provides the first direct test of the Zee–Babu neutrino mass model at the LHC, yielding an observed (expected) lower limit of m(H±±) = 900 GeV (880 GeV)

Effects of road fencing on population persistence

Roads affect animal populations in three adverse ways. They act as barriers to movement, enhance mortality due to collisions with vehicles, and reduce the amount and quality of habitat. Putting fences along roads removes the problem of road mortality but increases the barrier effect. We studied this trade-off through a stochastic, spatially explicit, individual-based model of population dynamics. We investigated the conditions under which fences reduce the impact of roads on population persistence. Our results showed that a fence may or may not reduce the effect of the road on population persistence, depending on the degree of road avoidance by the animal and the probability that an animal that enters the road is killed by a vehicle. Our model predicted a lower value of traffic mortality below which a fence was always harmful and an upper value of traffic mortality above which a fence was always beneficial. Between these two values the suitability offences depended on the degree of road avoidance. Fences were more likely to be beneficial the lower the degree of road avoidance and the higher the probability of an animal being killed on the road. We recommend the use offences when traffic is so high that animals almost never succeed in their attempts to cross the road or the population of the species of concern is declining and high traffic mortality is known to contribute to the decline. We discourage the use offences when population size is stable or increasing or if the animals need access to resources on both sides of the road, unless fences are used in combination with wildlife crossing structures. In many cases, the use offences may be beneficial as an interim measure until more permanent measures are implemented

Guidelines for Evaluating the Effectiveness of Road Mitigation Measures

Wildlife crossing structures - underpasses and overpasses - have been constructed around the world and are used by many species of wildlife to safely cross roads and other linear infrastructures. However, there is still much to learn about their effectiveness at contributing to the preservation of biodiversity. How many and what kinds of structures do we need to reach the goals of mitigation? Without clear insights into the effectiveness of wildlife crossing structures, we run the risk of losing wildlife populations (or even species) and wasting money. The evaluation of the effectiveness of mitigation requires a good experimental design and should be incorporated into road planning

Dispersal distance of mammals is proportional to home range size

We tested the prediction that home range area and dispersal distance in mammals are related when considered independently of body size. Regression of log-transformed data demonstrated that more variance in maximum dispersal distance could be explained by home range area (74%) than could be explained by body size (50%). The relationship between maximum dispersal distance and home range size was isometric (slope = 1) when the square root of home range area (i.e., linear dimension of home range) was used. Thus, maximum dispersal distance was related to home range size by a single constant of 40. A linear relationship remained between these two variables after the effects of body size were removed (F = 31.6, df = 1, 32, P = 3.2 × 10 -6 R 2 = 0.50). A similar isometric relationship with home range size was found for median dispersal distance (related by a multiple of 7). This isometric relationship between dispersal distance and home range size was tested using a second data source: maximum movements made by mammals after translocation, which also was linearly related to home range area (F = 94.5, df = 1, 23, P = 1.3 × 10 -9, R 2 = 0.81). The slope and intercept of this relationship were not different from those of the relationship between maximum dispersal distance and home range area. We suggest that the vagility of mammals affected both home range size and dispersal distance (or movement after translocation) independently of body size, such that these movements could be predicted by home range area better than by body size alone. The resulting isometric relationship between dispersal distance and home range size has potential as a useful scaling rule for ecological practitioners

Good science and experimentation are needed in road ecology

Scientifically rigorous research that produces accurate information is required to identify and mitigate the negative impacts of roads and traffic on wildlife, communities and ecosystems. The current approach to road planning and construction is not conducive to doing good science or incorporating explicit learning in the road development process. This typically result in inadequate information about road impacts, and poor-quality monitoring that rarely answers relevent questions about mitigation effectiveness, often leads to equivocal outcomes and does not improve "best practice" as it potentially could and should. With some improvements and more experiments with roads and mitigation measures, the planning, design, construction and management of roads and road impacts could be significantly enhanced

The Rauischholzhausen agenda for road ecology

Despite the documented negative effects of roads on wildlife, ecological research on road effects has had comparatively little influence on road planning decisions. We argue that road research would have a larger impact if researchers carefully considered the relevance of the research questions addressed and the inferential strength of the studies undertaken. At a workshop at the German castle of Rauischholzhausen we identified five particularly relevant questions, which we suggest provide the framework for a research agenda for road ecology: (1) Under what circumstances do roads affect population persistence? (2) What is the relative importance of road effects vs. other effects on population persistence? (3) Under what circumstances can road effects be mitigated? (4) What is the relative importance of the different mechanisms by which roads affect population persistence? (5) Under what circumstances do road networks affect population persistence at the landscape scale? We recommend experimental designs that maximize inferential strength, given existing constraints, and we provide hypothetical examples of such experiments for each of the five research questions. In general, manipulative experiments have higher inferential strength than do nonmanipulative experiments, and full before-after-control-impact designs are preferable to before-after or control-impact designs. Finally, we argue that both scientists and planners must be aware of the limits to inferential strength that exist for a given research question in a given situation. In particular, when the maximum inferential strength of any feasible design is low, decision makers must not demand stronger evidence before incorporating research results into the planning process, even though the level of uncertainty may be hig