Reassessment of red list status of european amphibians

Peer reviewe

A family of process-based models to simulate landscape use by multiple taxa

Context: Land-use change is a key driver of biodiversity loss. Models that accurately predict how biodiversity might be affected by land-use changes are urgently needed, to help avoid further negative impacts and inform landscape-scale restoration projects. To be effective, such models must balance model realism with computational tractability and must represent the different habitat and connectivity requirements of multiple species. Objectives: We explored the extent to which process-based modelling might fulfil this role, examining feasibility for different taxa and potential for informing real-world decision-making. Methods: We developed a family of process-based models (*4pop) that simulate landscape use by birds, bats, reptiles and amphibians, derived from the well-established poll4pop model (designed to simulate bee populations). Given landcover data, the models predict spatially-explicit relative abundance by simulating optimal home-range foraging, reproduction, dispersal of offspring and mortality. The models were co-developed by researchers, conservation NGOs and volunteer surveyors, parameterised using literature data and expert opinion, and validated against observational datasets collected across Great Britain. Results: The models were able to simulate habitat specialists, generalists, and species requiring access to multiple habitats for different types of resources (e.g. breeding vs foraging). We identified model refinements required for some taxa and considerations for modelling further species/groups. Conclusions: We suggest process-based models that integrate multiple forms of knowledge can assist biodiversity-inclusive decision-making by predicting habitat use throughout the year, expanding the range of species that can be modelled, and enabling decision-makers to better account for landscape context and habitat configuration effects on population persistence

New genetic loci link adipose and insulin biology to body fat distribution.

Body fat distribution is a heritable trait and a well-established predictor of adverse metabolic outcomes, independent of overall adiposity. To increase our understanding of the genetic basis of body fat distribution and its molecular links to cardiometabolic traits, here we conduct genome-wide association meta-analyses of traits related to waist and hip circumferences in up to 224,459 individuals. We identify 49 loci (33 new) associated with waist-to-hip ratio adjusted for body mass index (BMI), and an additional 19 loci newly associated with related waist and hip circumference measures (P < 5 × 10(-8)). In total, 20 of the 49 waist-to-hip ratio adjusted for BMI loci show significant sexual dimorphism, 19 of which display a stronger effect in women. The identified loci were enriched for genes expressed in adipose tissue and for putative regulatory elements in adipocytes. Pathway analyses implicated adipogenesis, angiogenesis, transcriptional regulation and insulin resistance as processes affecting fat distribution, providing insight into potential pathophysiological mechanisms

Agricultural Management and Climatic Change Are the Major Drivers of Biodiversity Change in the UK

Action to reduce anthropogenic impact on the environment and species within it will be most effective when targeted towards activities that have the greatest impact on biodiversity. To do this effectively we need to better understand the relative importance of different activities and how they drive changes in species’ populations. Here, we present a novel, flexible framework that reviews evidence for the relative importance of these drivers of change and uses it to explain recent alterations in species’ populations. We review drivers of change across four hundred species sampled from a broad range of taxonomic groups in the UK. We found that species’ population change (~1970–2012) has been most strongly impacted by intensive management of agricultural land and by climatic change. The impact of the former was primarily deleterious, whereas the impact of climatic change to date has been more mixed. Findings were similar across the three major taxonomic groups assessed (insects, vascular plants and vertebrates). In general, the way a habitat was managed had a greater impact than changes in its extent, which accords with the relatively small changes in the areas occupied by different habitats during our study period, compared to substantial changes in habitat management. Of the drivers classified as conservation measures, low-intensity management of agricultural land and habitat creation had the greatest impact. Our framework could be used to assess the relative importance of drivers at a range of scales to better inform our policy and management decisions. Furthermore, by scoring the quality of evidence, this framework helps us identify research gaps and needs

Developing models to estimate the occurrence in the English countryside of Great Crested Newts, a protected species under the Habitats Directive

The great crested newt is a European Protected Species (EPS) with a widespread distribution within Great Britain. This results in the species frequently coming into conflict with development. Consequently, decision-makers in local government and licensing authorities face complex issues when it comes to reconciling development and conservation. New approaches are therefore needed to ensure that conservation decisions are based upon the best available science. The project set out to evaluate new potential approaches to these issues using three work packages: (1) Develop, test and compare species distribution models (SDMs) for great crested newts; (2) Building on these models, develop a methodology for assessing the impact of a plan or project on the local conservation status of great crested newts; and (3) End-user testing to assess model applications and fitness for purpose. Defra commissioned the project with additional funding from Natural Resources Wales, and together with Natural England and JNCC, also provided guidance. GLM models developed using eDNA presence-absence data for a small area of Kent provided a good prediction of the county-wide distribution of the species. GLM models developed for Cheshire and Lincolnshire using eDNA data yielded weaker models. Equally, the Kent model did not reliably fit Cheshire and Lancashire, suggesting that the predictor variables vary geographically. Maxent and ensemble models yielded good fits to county-wide distributions but poor fits to the localised eDNA data in all three counties. These models may have utility at a broad scale, but cannot account for absences at a local scale. Equally, some important variables at a local scale cannot be obtained through GIS layers and need to be obtained through field surveys. Constructing models for different scales therefore requires different modelling tools and different types of predictor variables. Maxent models of the national distribution of great crested newts in England gave predictions that were broadly consistent with current knowledge and can be used to calculate potential areas of occupancy. A framework for assigning and measuring Favourable Reference Values (FRVs) for great crested newts at different scales was developed using both an ‘equilibrium’ (=’no net change’) approach and FRVs set using baseline data according to other criteria. These principles were combined with SDMs and connectivity analysis of five case studies. The case studies combine both real and hypothetical data, and illustrate how a modelling approach can be used to identify important areas of newt habitat, identify connectivity between ponds, predict potential impacts of development, and design and evaluate mitigation measures. Three end-user consultation exercises showed that there was considerable interest and enthusiasm for the development and application of SDMs across a range of applications and stakeholders. Concerns were expressed over the quality and quantity of data available for modelling using current data-flow systems; the predictive power of models; and the potential for model outputs to be misused. Challenges that need to be addressed include training, expertise and building capacity, enhancing the regulatory framework for protected species, and the improvement and centralisation of data management systems. Species Distribution Models (SDMs) provide an objective and evidence-based tool for use within decision-making processes involving great crested newts. They have the potential to identify priority areas for conservation, target survey effort, assess the impacts of development, and assign Favourable Reference Values for the species. However, great crested newt records and habitat data are currently dispersed across multiple recording systems and vary in quality and quantity. A well-integrated data management system is required if SDMs are to make the best use of available information

Species considerations in the design of biodiversity offset schemes in England

On 16th September 2013, twelve ecologists met to evaluate how species can be given consideration in biodiversity offsets in the English context. They noted that while the type, area and distinctiveness of vegetation cover (‘habitat’) within a proposed development site is sometimes a useful basis for assessing likely impacts on individual species, this is not always the case. If biodiversity offsetting is to contribute towards a goal of ‘no net loss’ of biodiversity, assessment of the impacts of a development must take into account the abundance of individual species in the wider landscape within which it is situated. An assessment process should be initiated to identify Species of Principal Importance for which habitat is not a suitable proxy to their presence or absence. This process would be based on the wealth of existing ecological evidence and methods available in England, including habitat suitability assessments and models. There is a need to designate a set of approaches to offsetting for impacts on each species requiring special consideration in biodiversity offsets. It is recommended that a central on-line repository of know-how for establishing species populations is created for use as a guide to the long-term viability of plans for offsets for species

First combined studies on Lorentz Invariance Violation from observations of astrophysical sources

International audienceImaging Atmospheric Cherenkov Telescopes study the highest energy (up to tens of TeV) photon emission coming from nearby and distant astrophysical sources, thus providing valuable results from searches for Lorentz Invariance Violation (LIV) effects. Highly variable, energetic and distant sources such as Pulsars and AGNs are the best targets for the Time-of-Flight LIV studies. However, the limited number of observations of AGN flares or of high-energy pulsed emission greatly restricts the potential of such studies, especially any potential LIV effects as a function of redshift. To address these issues, an inter-experiment working group has been established by the three major collaborations taking data with Imaging Atmospheric Cherenkov Telescopes (H.E.S.S., MAGIC and VERITAS) with the aim to increase sensitivity to any effects of LIV, together with an improved control of systematic uncertainties, by sharing data samples and developing joint analysis methods. This will allow an increase in the number of available sources and to perform a sensitive search for redshift dependencies. This presentation reviews the first combined maximum likelihood method analyses using simulations of published source observations done in the past with H.E.S.S., MAGIC and VERITAS. The results from analyses based on combined maximum likelihood methods, the strategies to deal with data from different types of sources and instruments, as well as future plans will be presented

Robust constraints on Lorentz Invariance Violation from H.E.S.S., MAGIC and VERITAS data combination

International audienceGamma-Ray bursts, flaring active galactic nuclei and pulsars are distant and energetic astrophysical sources, detected up to tens of TeV with Imaging Atmospheric Cherenkov Telescopes (IACTs). Due to their high variability, they are the most suitable sources for energy-dependent time-delay searches related to Lorentz Invariance Violation (LIV) predicted by some Quantum Gravity (QG) models. However, these studies require large datasets. A working group between the three major IACTs ground experiments - H.E.S.S., MAGIC and VERITAS - has been formed to address this issue and combine for the first time all the relevant data collected by the three experiments in a joint analysis.This proceeding will review the new standard combination method. The likelihood technique used to deal with data from different source types and instruments will be presented, as well as the way systematic uncertainties are taken into account. The method has been developed and tested using simulations based on published source observations from the three experiments. From these simulations, the performance of the method will be assessed and new light will be shed on time delays dependencies with redshift