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The climate impact of carbon capture and storage depends on how much CO2 is stored underground, yet databases of industrial-scale projects report capture capacity as a measure of project size. We review publicly available sources to estimate the amount of CO2 that has been stored by facilities since 1996. We organize these sources into three categories corresponding to the associated degree of assurance: (1) legal assurance, (2) quality assurance through auditing, and (3) no assurance. Data were found for 20 facilities, with an aggregate capture capacity of 36 Mt of CO2 year–1. Combining data from all categories, we estimate that 29 Mt of CO2 was geologically stored in 2019 and there was cumulative storage of 197 Mt over the period of 1996–2020. These are climate relevant scales commensurate with recent cumulative and ongoing emissions impacts of renewables in some markets, e.g., solar photovoltaics in the United States. The widely used capture capacity is in aggregate 19–30% higher than storage rates and is not a good proxy for estimating storage volumes. However, the discrepancy is project-specific and not always a reflection of project performance. This work provides a snapshot of storage amounts and highlights the need for uniform reporting on capture and storage rates with quality assurance.

Estimates of economic implications of climate policy are important inputs into policy-making. Despite care to contextualize quantitative assessments of mitigation costs, one strong view outside academic climate economics is that achieving Paris Agreement goals implies sizable macroeconomic losses. Here, we argue that this notion results from unwarranted simplification or omission of the complexities of quantifying mitigation costs, which generates ambiguity in communication and interpretation. We synthesize key factors influencing mitigation cost estimates to guide interpretation of estimates, for example from the Intergovernmental Panel on Climate Change, and suggest ways to improve the underlying models. We propose alternatives for the scenario design framework, the framing of mitigation costs and the methods used to derive them, to better inform public debate and policy.

The environmental impacts of food are currently at unsustainable levels. Consumers undoubtedly play a central role in reducing the impacts of the food system to more sustainable levels via dietary changes and food waste reduction. Mathematical optimisation is one approach to identifying less environmentally impactful dietary patterns. A limited number of studies, however, have assessed whether impact reductions offered by optimised diets are enough to remain within planetary boundaries (i.e. attain ‘absolute’ environmental sustainability). Using UK food consumption as a case study, here we employ linear programming to identify nutritionally adequate diets that meet sociocultural acceptability criteria whilst minimising (a) environmental impact transgressions of their allocated share of the safe operating space (SoSOS) for nine planetary boundaries (PBs), (b) cost, or (c) deviation from the current diet. We show that the current diet is unsustainable as it transgresses six or seven PBs, depending on the SoSOS allocation principle. Optimising for minimum SoSOS transgressions yields diets offering significant impact reductions (66 - 95% reduction across all PBs) compared to the current average dietary pattern, but whether they completely mitigate SoSOS transgressions depends on the sharing principle adopted to assign the SoSOS to national food consumption. Additionally, by comparing least-cost and least-transgression solutions, we find a trade-off between cost and environmental sustainability indicating that more sustainable dietary patterns are not currently incentivised by the relative prices of food items in the UK. Our work demonstrates the value in embedding ‘absolute’ sustainability in diet optimisation so that solutions inherently provide a more clear-cut understanding of their broad implications on the environment., Sustainable Production and Consumption, 28, ISSN:2352-5509

1. Understanding the role of different species in the transmission of multi-host pathogens, such as rabies virus, is vital for effective control strategies. Across most of sub-Saharan Africa domestic dogs Canis familiaris are considered the reservoir for rabies, but the role of wildlife has been long debated. Here we explore the multi-host transmission dynamics of rabies across south-east Tanzania. 2. Between January 2011 and July 2019, data on probable rabies cases were collected in the regions of Lindi and Mtwara. Hospital records of animal-bite patients presenting to healthcare facilities were used as sentinels for animal contact tracing. The timing, location and species of probable rabid animals were used to reconstruct transmission trees to infer who infected whom and the relative frequencies of within- and between-species transmission. 3. During the study, 688 probable human rabies exposures were identified, resulting in 47 deaths. Of these exposures, 389 were from domestic dogs (56.5%) and 262 from jackals (38.1%). Over the same period, 549 probable animal rabies cases were traced: 303 in domestic dogs (55.2%) and 221 in jackals (40.3%), with the remainder in domestic cats and other wildlife species. 4. Although dog-to-dog transmission was most commonly inferred (40.5% of transmission events), a third of inferred events involved wildlife-to-wildlife transmission (32.6%), and evidence suggested some sustained transmission chains within jackal populations. 5. A steady decline in probable rabies cases in both humans and animals coincided with the implementation of widespread domestic dog vaccination during the first 6 years of the study. Following the lapse of this program, dog rabies cases began to increase in one of the northernmost districts. 6. Synthesis and applications. In south-east Tanzania, despite a relatively high incidence of rabies in wildlife and evidence of wildlife-to-wildlife transmission, domestic dogs remain essential to the reservoir of infection. Continued dog vaccination alongside improved surveillance would allow a fuller understanding of the role of wildlife in maintaining transmission in this area. Nonetheless, dog vaccination clearly suppressed rabies in both domestic dog and wildlife populations, reducing both public health and conservation risks and, if sustained, has potential to eliminate rabies from this region.

Spatial turnover of biological communities is determined by both dispersal and environmental constraints. However, we lack quantitative predictions about how these factors interact and influence turnover across genealogical scales. In this study, we have implemented a predictive framework based on approximate Bayesian computation (ABC) to quantify the signature of dispersal and environmental constraints in community turnover. First, we simulated the distribution of haplotypes, intra-specific lineages and species in biological communities under different strengths of dispersal and environmental constraints. Our simulations show that spatial turnover rate is invariant across genealogical scales when dispersal limitation determines the species ranges. However, when environmental constraint limits species ranges, spatial turnover rates vary across genealogical scales. These simulations were used in an ABC framework to quantify the role of dispersal and environmental constraints in 16 empirical biological communities sampled from local to continental scales, including several groups of insects (both aquatic and terrestrial), molluscs and bats. In seven datasets, the observed genealogical invariance of spatial turnover, assessed with distance–decay curves, suggests a dispersal-limited scenario. In the remaining datasets, the variance in distance–decay curves across genealogical scales was best explained by various combinations of dispersal and environmental constraints. Our study illustrates how modelling spatial turnover at multiple genealogical scales (species and intraspecific lineages) provides relevant insights into the relative role of dispersal and environmental constraints in community turnover., his research was supported by the Spanish Ministerio de Ciencia e Innovación and the European Regional Development Fund (ERDF) through grants CGL2016-76637-P and PID2020-112935GB-I000. DP and MA receive support from the Xunta de Galicia. MBA and MA acknowledge support from Ministerio de Ciencia, Innovación y Universidades through the grants PGC2018-099363-B-I00 and RYC-2015-18241, respectively.

Brood diseases and pesticides can reduce the survival of bee larvae, reduce bee populations, and negatively influence ecosystem biodiversity. However, major gaps persist in our knowledge regarding the routes and implications of co-exposure to these stressors in managed and wild bee brood. In this review, we evaluate the likelihood for co-exposure to brood pathogen and pesticide stressors by examining the routes of potential co-exposure and the possibility for pollen and nectar contaminated with pathogens and pesticides to become integrated into brood food. Furthermore, we highlight ways in which pesticides may increase brood disease morbidity directly, through manipulating host immunity, and indirectly through disrupting microbial communities in the guts of larvae, or compromising brood care provided by adult bees. Lastly, we quantify the brood research bias towards Apis species and discuss the implications the bias has on brood disease and pesticide risk assessment in wild bee communities. We advise that future studies should place a higher emphasis on evaluating bee brood afflictions and their interactions with commonly encountered stressors, especially in wild bee species.

Reliable and accurate biodiversity census methods are essential for monitoring ecosystem health and assessing potential ecological impacts of future development projects. Although metabarcoding is increasingly used to study biodiversity across ecological research, morphology‐based identification remains the preferred approach for marine ecological impact assessments. Comparing metabarcoding to morphology‐based protocols currently used by ecological surveyors is essential to determine whether this DNA‐based approach is suitable for the long‐term monitoring of marine ecosystems. We compared metabarcoding and morphology‐based approaches for the analysis of invertebrates in low diversity intertidal marine sediment samples. We used a recently developed bioinformatics pipeline and two taxonomic assignment methods to resolve and assign amplicon sequence variants (ASVs) from Illumina amplicon data. We analysed the community composition recovered by both methods and tested the effects, on the levels of diversity detected by the metabarcoding method, of sieving samples prior to DNA extraction. Metabarcoding of the mitochondrial marker cytochrome c oxidase I (COI) gene recovers the presence of more taxonomic groups than the morphological approach. We found that sieving samples results in lower alpha diversity detected and suggests a community composition that differs significantly from that suggested by un‐sieved samples in our metabarcoding analysis. We found that whilst metabarcoding and morphological approaches detected similar numbers of species, they are unable to identify the same set of species across samples. Synthesis and Applications We show that metabarcoding using the cytochrome c oxidase I (COI) marker provides a more holistic, community‐based, analysis of benthic invertebrate diversity than a traditional morphological approach. We also highlight current gaps in reference databases and bioinformatic pipelines for the identification of intertidal benthic invertebrates that need to be addressed before metabarcoding can replace traditional methods. Ultimately, with these limitations taken into consideration, resolving community‐wide diversity patterns with metabarcoding could improve the management of non‐protected marine habitats in the U.K.

Neutral theory proposes that some macroscopic biodiversity patterns can be explained in terms of drift, speciation and immigration, without invoking niches. There are many different varieties of neutral model, all assuming that the fitness of an individual is unrelated to its species identity. Variants that are spatially explicit provide a means for making quantitative predictions about spatial biodiversity patterns. We present software packages that make spatially explicit neutral simulations straightforward and efficient. The packages allow the user to customize both dispersal and landscape structure in a wide variety of ways. We provide a Python package pycoalescence and a functionally equivalent R package rcoalescence. In both packages, the core routines are written in C++ and make use of coalescence methods to optimize performance. We explain the technical details of the packages and give examples for their application, with a particular focus on two scenarios of ecological and evolutionary interest: a landscape with habitat fragmentation, and an archipelago of islands. Spatially explicit neutral models represent an important tool in ecology for understanding the processes of biodiversity generation and predicting outcomes at large scales. The effort required to implement these complex spatially explicit simulations efficiently has thus far been a barrier to entry. Our packages increase the accessibility of these models and encourage further investigation of the primary mechanisms underpinning biodiversity.

Polycystic ovary syndrome (PCOS) is the most common endocrine disorder among women of reproductive age with reproductive, metabolic and endocrine implications. While the exact pathophysiological mechanisms of the syndrome are unknown, its heterogeneity suggests a multifactorial causal background. In the last two decades, numerous environmental chemicals, including Bisphenol-A (BPA) that is used in the synthesis of polycarbonate plastics, have been proposed as potential contributors to the aetiology of PCOS. This review provides a holistic overview of the available data regarding the possible relation of PCOS with BPA exposure. We have included a total number of 24 studies. Eleven human case-control and 13 animal studies provided data regarding this potential relation. Accumulating evidence suggests that a correlation between high levels of BPA and the presence of PCOS may exist. Contradicting results from human and animal studies, however, render it difficult to conclude on the exact role of BPA in the pathogenesis of PCOS. BPA may constitute a consequence of the syndrome rather than a cause, but further research is still needed to clarify this. Continued efforts to study the early origins of PCOS, using prospective-designed studies, are required to identify the exact effect of BPA on women with PCOS.

Technological breakthroughs and policy measures targeting energy efficiency and clean energy alone will not suffice to deliver Paris Agreement-compliant greenhouse gas emissions trajectories in the next decades. Strong cases have recently been made for acknowledging the decarbonisation potential lying in transforming linear economic models into closed-loop industrial ecosystems and in shifting lifestyle patterns towards this direction. This perspective highlights the research capacity needed to inform on the role and potential of the circular economy for climate change mitigation and to enhance the scientific capabilities to quantitatively explore their synergies and trade-offs. This begins with establishing conceptual and methodological bridges amongst the relevant and currently fragmented research communities, thereby allowing an interdisciplinary integration and assessment of circularity, decarbonisation, and sustainable development. Following similar calls for science in support of climate action, a transdisciplinary scientific agenda is needed to co-create the goals and scientific processes underpinning the transition pathways towards a circular, net-zero economy with representatives from policy, industry, and civil society. Here, it is argued that such integration of disciplines, methods, and communities can then lead to new and/or structurally enhanced quantitative systems models that better represent critical industrial value chains, consumption patterns, and mitigation technologies. This will be a crucial advancement towards assessing the material implications of, and the contribution of enhanced circularity performance to, mitigation pathways that are compatible with the temperature goals of the Paris Agreement and the transition to a circular economy. © 2021 The Authors This work was supported by the H2020 European Commis- sion projects “PARIS REINFORCE”(Grant Agreement No. 820846), “LOCOMOTION”(Grant Agreement No. 821105), “NDC ASPECTS”(Grant Agreement No. 101003866), and “newTRENDS”(Grant Agreement No. 893311); the European Research Council (ERC) project “FINEPRINT”(Grant Agreement No. 725525); the Hel- lenic Foundation for Research and Innovation (HFRI) and General Secretariat for Research and Technology (GSRT) project “ATOM”(Grant Agreement No. HFRI-FM17–2566); the Spanish Ministry of Science, Innovation, and Universities projects RTI2018–099858- A-I00 and RTI2018–093352-B-I00; the María de Maeztu excel- lence accreditation 2018–2022 (Ref. MDM-2017–0714), funded by MCIN/AEI/10.13039/50110 0 011033; and by the Basque Government through the BERC 2018–2021 program and BIDERATU project (KK- 2021/0 0 050, ELKARTEK programme 2021). The sole responsibility for the content of this paper lies with the authors; the paper does not necessarily reflect the opinions of the European Commission, the Basque Government, or the Spanish Government.

Copyright © 2021 The Author(s). The pace to achieving a sustainable plastics economy remains noticeably slow due to a lack of understanding on the role and importance of stakeholder dynamics in the plastic packaging system. This study aims to unpack and assess the role of stakeholders in improving plastics recycling rates and circularity in the UK, using polyethylene terephthalate (PET) drinks bottles value chain as a case study. Via the theoretical lens of stakeholder theory we identify and group the stakeholders involved in the PET drinks bottles value chain, and integrate this in the Complex Value Optimisation for Resource Recovery (CVORR) systems thinking approach to make sense of, and analyse, stakeholders complex interactions. Results highlight that even though, external stakeholders (e.g. NGOs, trade associations) engage on different levels and scales in promoting circularity in the PET bottles value chain, there is strong drive in incentivising production and consumption processes driven by the significant lobbying power of internal stakeholders operating upstream of the PET bottles value chain (i.e. producers and brand owners). This lobbying power, which arises from the well-established market of PET bottles in the UK, and its support by financial institutions, it strongly influences national and local government policies and decision-making processes. Meanwhile, the waste management processes are short-sighted, being unable to gain improved momentum and increasing the PET bottles recycling rates. This dynamic conceals, and somewhat retains, the prevailing resistance in removing the infrastructural, regulatory and technological lock-ins. The development of an interdisciplinary collaboration between internal and external stakeholders is paramount to sustainably managing PET drinks bottles in the UK and achieving a transition to a sustainable circular plastics economy. Fostering closer collaboration between all stakeholders involved in the system, can aid the development of new value networks and support new policy interventions that can improve circularity in the plastic packaging sector. Brunel University London as part of the Brunel Research Initiative & Enterprise Fund (BRIEF) award No.11683100, in the context of ‘Closing the Plastic Food Packaging Loop’ project, and generously supported by the Oxford Martin School, University of Oxford.

Habitat fragmentation has become one of the largest areas of research in conservation biology. Empirical studies into habitat fragmentation impacts typically measure ecological responses to metrics describing fragmentation processes, for example ‘distance to the nearest forest edge’, ‘forest fragment area’ and ‘landscape habitat amount’. However, these studies often fail to sample across representative ranges of fragmentation metrics characterising the study region. They therefore lack the data to account for correlation among multiple fragmentation metrics and for spatial autocorrelation among sample sites, which reduces the strength of derived predictive models. Here, we draw on approaches used in the mining and soil science industry to develop standardised and repeatable protocols for designing optimised sampling schemes of biodiversity in fragmented landscapes that meet three criteria: the distance between sample sites is maximised to reduce spatial autocorrelation, the full range of values of the metrics of interest are sampled and the confounding effects of correlated metrics are minimised. We show that our computational methods can optimise the placement of sample sites in fragmented landscapes to minimise, and in some cases to entirely avoid, over- or under-sampling of fragmentation metrics. Our method is flexible enough to cater for any continuous (e.g. maps of percentage tree cover) or categorical (e.g. habitat and land use types) fragmentation metric, and to simultaneously handle combinations of multiple fragmentation metrics and habitat types. We implement our methods as open-source code which includes options to mask invalid or inaccessible regions, update designs to adapt to unforeseen constraints in the field and suggest optimal numbers of sample sites for given design criteria. Using a case study landscape, we demonstrate how the approach improves on manually generated sampling designs. We also show that the methods are flexible enough to be applied to landscape studies beyond the field of habitat fragmentation. We introduce our package as a novel research tool that is able to streamline the experimental design process for biodiversity sampling and monitoring at landscape scales, leading to improved data quality and representativeness.

Does competition influence patterns of coexistence between closely related taxa? Here we address this question by analyzing patterns of range overlap between related species of birds (‘sister pairs’) co‐occurring on a tropical elevational gradient. We explicitly contrast the behavioral dimension of interspecific competition (interference competition) with similarity in resource acquisition traits (exploitative competition). Specifically, we ask whether elevational range overlap in 118 sister pairs that live along the Manu Transect in southeastern Peru is predicted by proxies for competition (intraspecific territorial behavior) or niche divergence (beak divergence and divergence times, an estimate of evolutionary age). We find that close relatives that defend year‐round territories tend to live in non‐overlapping elevational distributions, while close relatives that do not defend territories tend to broadly overlap in elevational distribution. In contrast, neither beak divergence nor evolutionary age was associated with patterns of range limitation. We interpret these findings as evidence that behavioral interactions – particularly direct territorial aggression – can be important in setting elevational range limits and preventing coexistence of closely related species, though this depends upon the extent to which intraspecific territorial behavior can be extended to territorial interactions between species. Our results suggest that interference competition can be an important driver of species range limits in diverse assemblages, and thus highlight the importance of considering behavioral dimensions of the niche in macroecological studies.

1. Estimating population abundance is a key objective of surveillance programmes, particularly for vector species of public health interest. For mosquitos, which are vectors of human pathogens, established methods to measure absolute population abundance such as mark‐release‐recapture are difficult to implement and usually spatially limited. Typically, regional monitoring schemes assess species relative abundance (counting captured individuals) to prioritize control efforts and study species distribution. However, assessing absolute abundance is crucial when the focus is on pathogen transmission by contacts between vectors and hosts. Here, we applied the N‐mixture model approach to estimate mosquito abundance from standard monitoring data. 2. We extended the N‐mixture model approach in a Bayesian framework by considering a beta‐binomial distribution for the detection process. We ran a simulation study to explore model performance under a low detection probability, a time‐varying population and different sets of independent variables. 3. When informative priors were used and the model was well specified, estimates by N‐mixture model well correlated (>0.9) with synthetic data and had a mean absolute deviation of about 20%. Correlation decreased and biased increased with uninformative priors or model misspecification. 4. When fed with field monitoring data to estimate the absolute abundance of the mosquito arbovirus vector Aedes albopictus within the metropolitan city of Rome (Italy), the N‐mixture model showed higher population size in residential neighbourhoods than in large green areas and revealed that traps located adjacent to vegetated sites have a higher probability of capturing mosquitoes. 5. Synthesis and applications. Our results show that, if supported by a good knowledge of the target species biology and by informative priors (e.g. from previous studies of capture rates), the N‐mixture model represents a valuable tool to exploit field monitoring data to estimate absolute abundance of disease vectors and to assess vector‐related health risk on a wide spatial and temporal scale. For mosquitoes specifically, it is also valuable to invest in increased efficiency of trapping devices to improve estimates of absolute abundance from the models.

Purpose This study aims to assess gender-based differences on farmers’ perception of impacts and vulnerability to climate change and the implementation of adaptation strategies in the Pra River Basin of Ghana, while also providing lessons for other Sub-Saharan nations and regions with similar conditions. Design/methodology/approach The study used semi-structured interviews and questionnaires to collect data from 344 farmers, 64 participants in focus group discussions and 6 agriculture extension officers (key informants) from 10 districts in the Pra River Basin of Ghana. Findings Results showed several differences in how climate change is perceived and tackled by male and female genders. In the perception of male farmers, for example, they were found to be more vulnerable to increased temperature, and changes in rainfall and growing season, whereas female farmers on average were considered to be less resilient to floods and droughts for different reasons. Moreover, floods posed higher risks to farming than other climate change impacts. Gender roles had a significant correlation with the type of adaptation strategies practised. Men adopted agrochemicals more often than women, as an adaptation strategy. Research limitations/implications Gender-differentiated interventions should be incorporated in the national climate change action plan for sustainable development in a rain-fed agricultural economy such as Ghana. The study recommends several actions to promote gender equity in the assessed region. Originality/value This research assessed the gender differentials in climate trends, impact, vulnerability and adaptation based on primary data collected between April and May 2019 and compared the results with climate data in the basin for the period 1991–2014. It is an empirical study focused on primary data analysis obtained in loco by authors, involving approximately 400 participants.

1. Effective conservation decisions rely on accurate survey data, but methods can be resource‐intensive and risk false negative results. Presence of the threatened hazel dormouse (England, UK) is typically confirmed by looking for its nest in survey tubes, over a 6‐month period. As an alternative, environmental DNA (eDNA) surveys have proven benefits in efficiency and accuracy for other taxa, but generally rely on the extraction and amplification of DNA from water, soil or sediment, which are not yet dependable samples for rare terrestrial mammals like the hazel dormouse. 2. At a known occupancy site, paper‐lined survey tubes were used to capture a DNA sample. Like other species of rodent, the hazel dormouse excretes urine freely, and this was highlighted by ultraviolet torch, swabbed from the paper, extracted and hazel dormouse eDNA amplified by quantitative polymerase chain reaction (qPCR). 3. Hazel dormouse presence was confirmed in this way in three out of 50 tubes within 8 days. Detection by conventional nest survey occurred on day 63 when a hazel dormouse nest was found in a single survey tube. We calculate that amplification of eDNA left behind in tubes increased survey efficiency here at least 12‐fold. 4. Synthesis and applications. In this study we demonstrate that eDNA swabbed from a clean substrate placed in survey apparatus can significantly hasten the detection of a rare species. This method has the potential to broaden the application of eDNA to other terrestrial vertebrates, including surveys at large spatiotemporal scales. Beyond presence/absence, the non‐invasive DNA sample could also offer insights into sex ratio, abundance, behaviour and population genetics.

Achieving multi-million-hectare commitments from countries around the world to restore degraded lands in resilient and sustainable ways requires, among other things, huge volumes of tree planting material. Seed systems encompassing all forest reproductive material (e.g., seeds, cuttings, stakes, and wildings), are key to ensuring that sufficient planting material with a diverse range of suitable species, adapted to local conditions and capable of persisting under a changing climate, is available for restoration projects. The ideal structure of a seed system integrates five components: seed selection and innovation, seed harvesting and production, market access, supply and demand, quality control, and an enabling environment. We propose 15 indicators to evaluate these key components and trial them by assessing national seed systems in 7 Latin American countries. We conclude that the indicators enable a straightforward assessment of the strengths and weaknesses of national seed systems, thus assisting governments to identify key areas for improvement and opportunities for horizontal learning., Diversity, 13 (8), ISSN:1424-2818

Assessing global progress on human adaptation to climate change is an urgent priority. Although the literature on adaptation to climate change is rapidly expanding, little is known about the actual extent of implementation. We systematically screened >48,000 articles using machine learning methods and a global network of 126 researchers. Our synthesis of the resulting 1,682 articles presents a systematic and comprehensive global stocktake of implemented human adaptation to climate change. Documented adaptations were largely fragmented, local and incremental, with limited evidence of transformational adaptation and negligible evidence of risk reduction outcomes. We identify eight priorities for global adaptation research: assess the effectiveness of adaptation responses, enhance the understanding of limits to adaptation, enable individuals and civil society to adapt, include missing places, scholars and scholarship, understand private sector responses, improve methods for synthesizing different forms of evidence, assess the adaptation at different temperature thresholds, and improve the inclusion of timescale and the dynamics of responses. Determining progress in adaptation to climate change is challenging, yet critical as climate change impacts increase. A stocktake of the scientific literature on implemented adaptation now shows that adaptation is mostly fragmented and incremental, with evidence lacking for its impact on reducing risk.

Active travel (walking or cycling for transport) is considered the most sustainable form of personal transport. Yet its net effects on mobility-related CO2 emissions are complex and underresearched. Here we collected travel activity data in seven European cities and derived life cycle CO2 emissions across modes and purposes. Daily mobility-related life cycle CO2 emissions were 3.2 kgCO(2) per person, with car travel contributing 70% and cycling 1%. Cyclists had 84% lower life cycle CO2 emissions than non-cyclists. Life cycle CO2 emissions decreased by 14% per additional cycling trip and decreased by 62% for each avoided car trip. An average person who `shifted travel modes' from car to bike decreased life cycle CO2 emissions by 3.2 kgCO(2)/day. Promoting active travel should be a cornerstone of strategies to meet net zero carbon targets, particularly in urban areas, while also improving public health and quality of urban life. This work was supported by the European project Physical Activity through Sustainable Transportation Approaches (PASTA). PASTA (http://www.pastaproject.eu/) was a four-year project funded by the European Union's Seventh Framework Program (EU FP7) under European Commission - Grant Agreement No. 602624. CB is also supported by UK Research and Innovation (UKRI) under the Centre for Research on Energy Demand Solutions (CREDS, Grant agreement number EP/R035288/1). ED is also supported by a postdoctoral scholarship from FWO - Research Foundation Flanders. ML held a joint PASTA/VITO PhD scholarship. SS is supported by the Martin Filko Scholarship from the Ministry of Education in Slovakia. Brand, C (corresponding author), Univ Oxford, Transport Studies Unit, South Parks Rd, Oxford OX, christian.brand@ouce.ox.ac.uk

The extent to which the ongoing decline in Arctic sea ice affects mid-latitude climate has received great attention and polarised opinions. The basic issue is whether the inter-annual variability in Arctic sea ice is the cause of, or the response to, variability in mid-latitude atmospheric circulation. A recent paper by Mori et al. (M19) claims to have reconciled previous conflicting studies by showing that a consistent mid-latitude climate response to inter-annual sea-ice anomalies can be identified in both the ERA-Interim reanalysis, taken as observations, and in an ensemble of atmosphere-only (AMIP) climate model simulations. We here demonstrate that such a conclusion cannot be drawn, due to issues with the interpretation of the maximum covariance analysis performed. After applying the M19 approach to the output from a simple statistical model, we conclude that a predominant atmospheric forcing of the sea-ice variability, rather than the converse, is the most plausible explanation of the results presented in M19.

Bioaerosol exposure has been linked to adverse respiratory conditions. Intensive farming and composting facilities are important anthropogenic sources of bioaerosols. We aimed to characterise populations living close to intensive farming and composting facilities. We also infer whether the public are becoming more concerned about anthropogenic bioaerosol emissions, using reports of air pollution related incidents attributed to facilities. We mapped the location of 1,257 intensive farming and 310 composting facilities in England in relation to the resident population and its characteristics (sex and age), area characteristics (deprivation proxy and rural/urban classification) and school locations stratified by pre-defined distance bands from these bioaerosol sources. We also calculated the average number of air pollution related incidents per year per facility. We found that more than 16% of the population and 15% of schools are located within 4,828 m of an intensive farming facility or 4,000 m of a composting facility; few people (0.01 %) live very close to these sites and tend to be older people. Close to composting facilities, populations are more likely to be urban and more deprived. The number of incidents were attributed to a small proportion of facilities; population characteristics around these facilities were similar. Results indicate that populations living near composting facilities (particularly>250 to ⩽ 4,000 m) are mostly located in urban areas (80%–88% of the population), which supports the need for more community health studies to be conducted. Results could also be used to inform risk management strategies at facilities with higher numbers of incidents.

Many scholars have recently looked to adaptive management and adaptive governance as new approaches to implement green infrastructure. Much of the recent scholarship, however, that argues for combining the three concepts of adaptive management, adaptive governance, and green infrastructure is either theoretical, at early planning stages, or based on relatively small experiments. Since green infrastructure is now being implemented in a number of cities at large spatial scales, this paper examines how and whether combining these theories helps to solve anticipated problems compared to earlier work on environmental governance and political implementation. The city of Philadelphia has become known as a national and international leader in using green infrastructure for stormwater management. This paper therefore analyses Philadelphia’s early experiences in the period from 2009 to 2015 as a test at urban scale of the usefulness of theories of adaptive management and adaptive governance in implementing green infrastructure. The city of Philadelphia found itself rapidly changing its implementation approach multiple times in response to political pressure. The city’s changing responses illustrate challenges in implementing environmental policies among actors with differing levels of political power, economic interests, and participation. This paper describes the rapid changes in programs using mixed methods and data sources including quantitative analysis of the city’s billing and program data, qualitative interpretation of media and public documents, and subsequent interviews with city officials. Understanding how and why Philadelphia rapidly changed its approach will be interesting to policymakers and advocates in other cities who also intend to implement green infrastructure at urban scale. Accepted version

Many ecological economists advocate the need to evolve beyond capitalism if we want to flourish as a society as well as respect the safe boundaries of our planet. While becoming clearer of the shape and underlying value-structure of such a new system, we also need to think about how we can motivate people to take part in such a major social transition. This paper tackles this question by critically evaluating the underlying hedonistic-normative assumptions of current mainstream models for pro-environmental behaviours (PEB). In a self-determination theory perspective on human motivation and well-being, the paper proposes a 2-pathway model of PEB that integrates a relational pathway for environmental motivation. Based on insights from neurobiology and psychology, this paper advances current PEB theories and lays the groundwork for a new category of environmental interventions: experiential strategies. Thus, the 2-pathway model provides important theoretical insights into the link between mindfulness and sustainable lifestyles, as well as the interface between environmental behaviours and well-being. By recognising and investing in the relational capacities of individuals, we might be able to promote a society that prioritises self-actualisation over self-interest.

Automated monitoring approaches offer an avenue to deep, large-scale insight into how ecosystems respond to human pressures. Since sensor technology and data analyses are often treated independantly, there are no open-source examples of end-to-end, real-time ecological monitoring networks.Here, we present the complete implementation of an autonomous acoustic monitoring network deployed in the tropical rainforests of Borneo. Real-time audio is uploaded remotely from the field, indexed by a central database, and delivered via an API to a public-facing website.We provide the open-source code and design of our monitoring devices, the central web2py database and the ReactJS website. Furthermore, we demonstrate an extension of this infrastructure to deliver real-time analyses of the eco-acoustic data.By detailing a fully functional, open-source, and extensively tested design, our work will accelerate the rate at which fully autonomous monitoring networks mature from technological curiosities, and towards genuinely impactful tools in ecology.

Madagascar is one of the most biodiverse countries in Africa, due to its level of endemism and species diversity. However, the pressure of human activities threatens the last patches of natural vegetation in the country and conservation decisions are undertaken with limited data availability. In this study, we use free online datasets to generate distribution models of 1539 endemic trees and prioritise for conservation and restoration considering threat, alongside conservation value and cost. Threats considered include illegal logging, forest degradation and agriculture or slash and burns activities. We found that the areas with the highest potential concentration of species are along the north and south-east of the country where more than 400 tree species can be found. Most scenarios identify a common conservation and restoration priority area along the north east of the country. Our findings guide managers, conservation organizations or governments in decisions about where to invest their limited conservation resources.

International audience; Classical biomonitoring techniques have focused primarily on measures linked to various biodiversity metrics and indicator species. Next-generation biomonitoring (NGB) describes a suite of tools and approaches that allow the examination of a broader spectrum of organizational levels-from genes to entire ecosystems. Here, we frame 10 key questions that we envisage will drive the field of NGB over the next decade. While not exhaustive, this list covers most of the key challenges facing NGB, and provides the basis of the next steps for research and implementation in this field. These questions have been grouped into current- and outlook-related categories, corresponding to the organization of this paper.

Biodiversity loss is a critical sustainability issue, and companies are beginning to seek ways to assess their biodiversity performance. Initiatives to date have developed biodiversity indicators for specific business contexts (e.g., spatial scales-from site, to product, to regional, or corporate scales); however, many are not widely translatable across different contexts making it challenging for businesses seeking indicators to manage their biodiversity performance. By synthesising the steps of common conservation and business decision-making systems, we propose a framework to support more comprehensive development of quantitative biodiversity indicators, for a range of business contexts. The framework integrates experience from existing tried-and-tested conservation frameworks. We illustrate how our framework offers a pathway for businesses to assess their biodiversity performance and demonstrate responsible management by mitigating and reversing their biodiversity impacts and sustaining their dependencies, enabling them to demonstrate their contribution to emerging global biodiversity targets (e.g., Convention on Biological Diversity post-2020 targets)., Business Strategy and the Environment, 29 (8), ISSN:0964-4733, ISSN:1099-0836

This study investigated the ability of monochromatic ultraviolet (UV) light at 254 nm applied at typical drinking water disinfection doses to damage the antibiotic-resistant genes mph(A), sul1, tet-A, and bla-Tem1 in waterborne bacteria. UV sensitivity rank was bla-TEM1 > tet-A > sul1 > mph(A), which is consistent with predictions of a previously presented genomic-based UV sensitivity model. It is the first time that predictions of the relative UV sensitivity of antibiotic resistance genes have been validated with experimental data and suggest that such modeling is useful for determining the UV sensitivity of other genes in waterborne microorganisms.

Biogeography is an implicit and fundamental component of almost every dimension of modern biology, from natural selection and speciation to invasive species and biodiversity management. However, biogeography has rarely been integrated into human or veterinary medicine nor routinely leveraged for global health management. Here we review the theory and application of biogeography to the research and management of human infectious diseases, an integration we refer to as ‘pathogeography’. Pathogeography represents a promising framework for understanding and decomposing the spatial distributions, diversity patterns and emergence risks of human infectious diseases into interpretable components of dynamic socio‐ecological systems. Analytical tools from biogeography are already helping to improve our understanding of individual infectious disease distributions and the processes that shape them in space and time. At higher levels of organization, biogeographical studies of diseases are rarer but increasing, improving our ability to describe and explain patterns that emerge at the level of disease communities (e.g., co‐occurrence, diversity patterns, biogeographic regionalisation). Even in a highly globalized world most human infectious diseases remain constrained in their geographic distributions by ecological barriers to the dispersal or establishment of their causal pathogens, reservoir hosts and/or vectors. These same processes underpin the spatial arrangement of other taxa, such as mammalian biodiversity, providing a strong empirical ‘prior’ with which to assess the potential distributions of infectious diseases when data on their occurrence is unavailable or limited. In the absence of quality data, generalized biogeographic patterns could provide the earliest (and in some cases the only) insights into the potential distributions of many poorly known or emerging, or as‐yet‐unknown, infectious disease risks. Encouraging more community ecologists and biogeographers to collaborate with health professionals (and vice versa) has the potential to improve our understanding of infectious disease systems and identify novel management strategies to improve local, global and planetary health.

Information on the distribution and abundance of the forest elephant Loxodonta cyclotis is needed to allocate limited resources appropriately and set conservation goals for the species. However, monitoring at large scales in forest habitats is complicated, expensive and time consuming. We investigated the potential of applying interview-based occupancy analysis as a tool for the rapid assessment of the distribution and relative abundance of forest elephants in eastern Cameroon. Using single-season occupancy models, we explored the covariates that affect forest elephant occupancy and detectability, and identified spatial and temporal patterns in population change and occupancy. Quantitative and qualitative socio-demographic data offer additional depth and understanding, placing the occupancy analysis in context and providing valuable information to guide conservation action. Detectability of forest elephants has decreased since 2008, which is consistent with the decline in perceived abundance in occupied sites. Forest elephants occupy areas outside protected areas and outside the known elephant range defined by IUCN. Critical conservation attention is required to assess forest elephant populations and the threats they face in these poorly understood areas. Interview-based occupancy analysis is a reliable and suitable method for a rapid assessment of forest elephant occupancy on a large scale, as a complement to, or the first stage in, a monitoring process.

Given forecast aviation growth, many airports are predicted to reach capacity and require expansion. However, pressure to meet air quality regulations emphasises the importance of efficient ground-level aircraft activities to facilitate growth. Operational strategies such as reducing engine thrust setting at takeoff can reduce fuel consumption and pollutant emissions; however, quantification of the benefits and consistency of its use have been limited by data restrictions. Using 3,336 high-resolution flight data records, this paper analyses the impact of reduced thrust takeoff at London Heathrow. Results indicate that using reduced thrust takeoff reduces fuel consumption, nitrogen oxides (NOX) and black carbon (BC) emissions by 1.0-23.2%, 10.7-47.7%, and 49.0-71.7% respectively, depending on aircraft-engine combinations relative to 100% thrust takeoff. Variability in thrust settings for the same aircraft-engine combination and dependence on takeoff weight (TOW) is quantified. Consequently, aircraft-engine specific optimum takeoff thrust settings that minimise fuel consumption and pollutant emissions for different aircraft TOWs are presented. Further reductions of 1.9%, 5.8% and 6.5% for fuel consumption, NOX and BC emissions could be achieved, equating to reductions of approximately 0.4%, 3.5% and 3.3% in total ground level fuel consumption, NOX and BC emissions. These results quantify the contribution that reduced thrust operations offer towards achieving industry environmental targets and air quality compliance, and imply that the current implementation of reduced thrust takeoff at Heathrow is near optimal, considering operational and safety constraints.

Lakes and ponds cover only about 4% of the Earth’s non-glaciated surface1, yet they represent disproportionately large sources of methane and carbon dioxide2, 3, 4. Indeed, very small ponds (for example

Benchmarks to guide countries in ratcheting-up ambition, climate finance, and support in an equitable manner are critical but not yet determined in the context of the Paris Agreement1. We identify global cost-optimal mitigation scenarios consistent with the Paris Agreement goals and allocate their emissions dynamically to countries according to five equity approaches. At the national level, China's Nationally Determined Contribution (NDC) is weaker than any of the five equity approaches, India's and the USA's NDC are aligned with two, and the EU's with three. Most developing countries’ conditional (Intended) NDCs (INDCs) are more ambitious than the average of the five equity approaches under the 2 °C goal. If the G8 and China adopt the average of the five approaches, the gap between conditional INDCs and 2 °C-consistent pathways could be closed. For an equitable, cost-optimal achievement of the 1.5 °C target, emissions in 2030 are 21% lower (relative to 2010) than for 2 °C for the G8 and China combined, and 39% lower for remaining countries. Equitably limiting warming to 1.5 °C rather than 2 °C requires that individual countries achieve mitigation milestones, such as peaking or reaching net-zero emissions, around a decade earlier.

Future emissions scenarios for the IPCC Sixth Assessment Report should explore the carbon budget space in a systematic manner, which would be robust to the updates of latest climate science, so that policy implications can be adequately assessed.

Elevated CO2 (eCO(2)) experiments provide critical information to quantify the effects of rising CO2 on vegetation 1-6 . Many eCO(2) experiments suggest that nutrient limitations modulate the local magnitude of the eCO(2) effect on plant biomass(1,3,5), but the global extent of these limitations has not been empirically quantified, complicating projections of the capacity of plants to take up CO27,9. Here, we present a data-driven global quantification of the eCO(2) effect on biomass based on 138 eCO(2) experiments. The strength of CO2 fertilization is primarily driven by nitrogen (N) in similar to 65% of global vegetation and by phosphorus (P) in similar to 25% of global vegetation, with N- or P-limitation modulated by mycorrhizal association. Our approach suggests that CO2 levels expected by 2100 can potentially enhance plant biomass by 12 +/- 3% above current values, equivalent to 59 +/- 13 PgC. The globalscale response to eCO(2) we derive from experiments is similar to past changes in greenness(9) and bio-mass(10) with rising CO2, suggesting that CO2 will continue to stimulate plant biomass in the future despite the constraining effect of soil nutrients. Our research reconciles conflicting evidence on CO2 fertilization across scales and provides an empirical estimate of the biomass sensitivity to eCO(2) that may help to constrain climate projections.

As the circular economy (CE) concept gains growing popularity among consumers and producers, small‐ and medium‐sized enterprises (SMEs) increasingly look for ways to reorganize their offering and operations to integrate into the CE. This study examines the impact of (a) circular eco‐innovations and (b) external funding available for CE activities on the growth of European SMEs using a data set of 5,100 SMEs across 28 European countries in 2016. Findings reveal that a significant threshold investment (i.e., higher than 10% of revenues) into circular eco‐innovations is required for SMEs to benefit from investing into the CE. Moreover, the majority of circular eco‐innovations fail to boost the growth rates of SMEs, with the exception of investments into eco‐design innovations. Although traditional forms of debt and grant finance targeted to CE activities are found to have no or negative impact on the growth of SMEs, equity finance (i.e., angel and venture capital investments) contributes positively to their growth. The study offers insights into the lower levels of SME engagement in the CE as well as policy implications for improving engagement.

1. Climate change is a world-wide threat to biodiversity and ecosystem structure, functioning and services. To understand the underlying drivers and mechanisms, and to predict the consequences for nature and people, we urgently need better understanding of the direction and magnitude of climate change impacts across the soil–plant–atmosphere continuum. An increasing number of climate change studies are creating new opportunities for meaningful and high-quality generalizations and improved process understanding. However, significant challenges exist related to data availability and/or compatibility across studies, compromising opportunities for data re-use, synthesis and upscaling. Many of these challenges relate to a lack of an established ‘best practice’ for measuring key impacts and responses. This restrains our current understanding of complex processes and mechanisms in terrestrial ecosystems related to climate change. 2. To overcome these challenges, we collected best-practice methods emerging from major ecological research networks and experiments, as synthesized by 115 experts from across a wide range of scientific disciplines. Our handbook contains guidance on the selection of response variables for different purposes, protocols for standardized measurements of 66 such response variables and advice on data management. Specifically, we recommend a minimum subset of variables that should be collected in all climate change studies to allow data re-use and synthesis, and give guidance on additional variables critical for different types of synthesis and upscaling. The goal of this community effort is to facilitate awareness of the importance and broader application of standardized methods to promote data re-use, availability, compatibility and transparency. We envision improved research practices that will increase returns on investments in individual research projects, facilitate second-order research outputs and create opportunities for collaboration across scientific communities. Ultimately, this should significantly improve the quality and impact of the science, which is required to fulfil society's best practice, coordinated experiments, data management and documentation, ecosystem, experimental macroecology, methodology, open science, vegetation This is an open access article under the terms of the Creative Commons Attribution License, which permits use, distribution and reproduction in any medium, provided the original work is properly cited. © 2019 The Authors. Methods in Ecology and Evolution published by John Wiley & Sons Ltd on behalf of British Ecological Society.

Despite consensus in the literature that regulation, technology-push and market-pull drive eco-innovation (EI), evidence remains limited on the diverse firm capabilities needed to boost EI. Building on the natural-resource-based-view (NRBV) of the firm and the EI literature, this paper posits that firms need to renew and realign their capabilities, and ultimately develop distinctive sustainability-oriented capabilities, in order to meet the rapidly changing regulatory, technology, and market demands. Results of the analysis, based on a survey of UK firms, reveal that eco-innovations are more likely to arise when firms: (a) build capabilities on voluntary self-regulation (i.e. executive driven EMS and CSR) because such organisational capabilities allow them to address increasing regulatory pressures; (b) invest in environmental research and development (i.e. eco-R&D)- instead of generic research and development- because it provides them with the relevant and specific technological capabilities to tackle technology shifts towards sustainability; and (c) develop capabilities in green market sensing as such capabilities allow them to address green consumption needs.

One of the most important goals in current fisheries management is to maintain or restore stocks above levels that can produce the maximum sustainable yield (MSY). However, it may not be feasible to achieve MSY simultaneously for multiple species because of trade-offs that result from interactions between species, mixed fisheries and the multiple objectives of stakeholders. The premise in this study is that MSY is a concept that needs adaptation, not wholesale replacement. The approach chosen to identify trade-offs and stakeholder preferences involved a process of consulting and discussing options with stakeholders as well as scenario modelling with bio-economic and multi-species models. It is difficult to intuitively anticipate the consequences of complex trade-offs and it is also complicated to address them from a political point of view. However, scenario modelling showed that the current approach of treating each stock separately and ignoring trade-offs may result in unacceptable ecosystem, economic or social effects in North Sea fisheries. Setting FMSY as a management target without any flexibility for compromises may lead to disappointment for some of the stakeholders. To treat FMSY no longer as a point estimate but rather as a “Pretty Good Yield” within sustainable ranges was seen as a promising way forward to avoid unacceptable outcomes when trying to fish all stocks simultaneously at FMSY. This study gives insights on how inclusive governance can help to reach consensus in difficult political processes, and how science can be used to make informed decisions inside a multi-dimensional trade-off space.

Discussions on a long-term global goal to limit climate change, in the form of an upper limit to warming, were only partially resolved at the United Nations Framework Convention on Climate Change negotiations in Paris, 2015. Such a political agreement must be informed by scientific knowledge. One way to communicate the costs and benefits of policies is through a mapping that systematically explores the consequences of different choices. Such a multi-disciplinary effort based on the analysis of a set of scenarios helped structure the IPCC AR5 Synthesis Report. This Perspective summarizes this approach, reviews its strengths and limitations, and discusses how decision-makers can use its results in practice. It also identifies research needs that can facilitate integrated analysis of climate change and help better inform policy-makers and the public.

Data centres account for 1% of total global electricity demand but this may grow to between 15-30% of electricity consumption in some countries by 2030. The majority of this growth is attributed to cloud computing, particularly the larg-est “hyperscale” vendors. IT emissions previously accounted for under the Greenhouse Gas Protocol Scope 1 and Scope 2 move to Scope 3 when outsourced to the cloud. However, the data needed to complete those calculations is not available from cloud vendors. Further, since Scope 3 emissions tend to be reported only voluntarily and the emissions are aggregated into the global emissions reporting by the large cloud vendors, this can result in emissions being hidden when they are moved to the cloud.

Forest ecosystems are rich in biodiversity and provide valuable ecosystem services, but are declining worldwide. Malus niedzwetzkyana, an Endangered wild relative of domesticated apples, is an important component of the walnut–fruit forests of Central Asia. Its iconic pink blossom and genetic properties give it special cultural and scientific significance, but livestock grazing and firewood collection threaten its survival. The conservation of the species and its native forest ecosystem is critical and urgent. This study provides information on the ecology and population of M. niedzwetzkyana and the threats affecting its habitat, improving our understanding of its distribution and proposing measures to reduce threats. We collected ecological data and assessed population structure and threats at four forest sites in southern Kyrgyzstan. We mapped 149 individuals, creating the largest known dataset for this species. We developed species distribution models for M. niedzwetzkyana to identify climatically suitable regions and potential areas for restoration. Sary-Chelek Biosphere Reserve contained the largest expanse of pristine forest and the most stable M. niedzwetzkyana population, followed by Kara-Alma Forestry Unit. Forests in the Gava Forestry Unit and Dashman Reserve were most extensively damaged by humans and livestock. The wild apple's favoured habitat was south-west facing slopes with a gradient < 30° and a relatively open canopy. Overall, the study population was vulnerable to extinction with limited regeneration potential. We recommend short-term population enhancement through planting projects and increased protection of individuals in pristine sites. Community-based conservation initiatives should be prioritized in extensively damaged sites, and larger-scale reforestation of these forests needs to be considered.

Viruses, such as dengue, Zika, yellow fever and chikungunya, depend on mosquitoes for transmission. Their epidemics typically present periodic patterns, linked to the underlying mosquito population dynamics, which are known to be driven by natural climate fluctuations. Understanding how climate dictates the timing and potential of viral transmission is essential for preparedness of public health systems and design of control strategies. While various alternative approaches have been proposed to estimate local transmission potential of such viruses, few open-source, ready to use and freely available software tools exist.We developed theIntrodução: Os vírus da dengue, Zika, febre amarela e chikungunya mantém‐se em ciclos de transmissão entre humanos e mosquitos. As epidemias desses vírus apresentam padrões oscilatórios periódicos de carácter universal, que refletem flutuações no número total de mosquitos presentes, por sua vez influenciadas por flutuações climáticas naturais que afetam o ciclo de vida do mosquito. O conhecimento de como o clima resulta em janelas de oportunidade favorável à transmissão desses vírus é essencial para o planeamento de ações de saúde pública, como campanhas de prevenção, alocação de recursos em sistemas de saúde e ações de controlo do mosquito. Enquanto que vários métodos que estimam o potencial desses vírus segundo dados climáticos tȇm sido publicados em anos recentes, ferramentas de software grátis e open‐source são praticamente inexistentes. Resultados: Nós desenvolvemos o Mosquito‐borne Viral Suitability Estimator (MVSE), um pacote de software para o sistema de programação R. MVSE estima o index P, uma nova medida informada por dados climáticos, baseada na equação do número reprodutivo básico (R0) de um modelo dinâmico. A expressão do R0 usada considera informação a priori para parâmetros humanos, virais e entomológicos, assim como séries temporais de temperatura e humidade. Assim sendo, o index P pode ser calculado para qualquer hospedeiro e vírus de interesse em qualquer região do globo para qual dados climáticos estão disponíveis. Conclusões: Neste manuscrito, a teoria, o suporte empírico e a interpretação biológica do novo index P são introduzidas e discutidas. Usando exemplos reais em múltiplos contextos epidemiológicos da América do Sul e Central, nós demonstramos também as funcionalidades básicas do MVSE e o seu potencial para fins académicos e educacionais.

Understanding temporal change and long-term persistence of species and communities is vital if we are to accurately assess the relative values of human-modified habitats for biodiversity. Despite a large literature and emerging consensus demonstrating a high conservation value of selectively logged tropical rainforests, few studies have taken a long-term perspective. We resampled small mammals (≤ 1 kg) in a heavily logged landscape in Sabah, Borneo between 2011 and 2016 to investigate temporal patterns of species-level changes in population density. We found that small mammal population density in heavily logged forest was highly variable among years, consistent with patterns previously observed in unlogged forest, and uncovered evidence suggesting that one species is potentially declining towards local extinction. Across nine species, population densities varied almost sevenfold during our 6-year study period, highlighting the extremely dynamic nature of small mammal communities in this ecosystem. Strictly terrestrial murid species tended to exhibit strong temporal dynamics, whereas semi-arboreal foraging species such as treeshrews had more stable dynamics. We found no relationships between population density and fruit/seed mass, and therefore no evidence that our patterns represent responses to inter-annual mast fruiting of the dominant canopy dipterocarp trees. This may be due to the removal of most of the canopy during logging, and hence the dipterocarp seed resource, although it possibly also reflects spatiotemporal limitations of our data. Our results underline the importance of understanding long-term variability in animal communities before developing conservation and management recommendations for human-altered ecosystems.

The rates of species and trait diversification vary across the Tree-of-Life and over time. Whereas species richness and clade age generally are decoupled, the correlation of accumulated trait diversity of clades (trait disparity) with clade age remains poorly explored. Total trait disparity may be coupled with clade age if the growth of disparity (disparification) within and across clades is continuous with time in an additive niche expansion process (linear-cumulative model), or alternatively if the rate of trait disparification varies over time and decreases as ecological space becomes gradually saturated (disparity-dependent model). Using a clock-calibrated phylogenetic tree for 143 freshwater macroinvertebrate families and richness and trait databases covering > 6400 species, we measured trait disparity in 18 independent clades that successively transitioned to freshwater ecosystems and analyzed its relation with clade age. We found a positive correlation between clade age and total disparity within clades, but no relationship for most individual traits. Traits unique to freshwater lifestyle were highly variable within older clades, while disparity in younger clades shifted towards partially terrestrial lifestyles and saline tolerance to occupy habitats previously inaccessible or underutilized. These results argue that constraints from incumbent lineages limit trait disparity in younger clades that evolved for filling unoccupied regions of the trait space, which suggests that trait disparification may follow a disparity-dependent model. Overall, we provide an empirical pattern that reveals the potential of the disparity-dependent model for understanding fundamental processes shaping trait dynamics across the Tree-of-Life., This research received support from grant CGL2007‐60163/BOS funded by the Spanish Ministry of Education and Science/FEDER (Fondo Europeo de Desarrollo Regional). NB acknowledges the BioFresh EU funded project Biodiversity of Freshwater Ecosystems: Status, Trends, Pressures, and Conservation Priorities (7th FWP contract no. 226874). Further funding support was provided by a Beatriu de Pinós postdoctoral fellowship (BP‐DGR‐2011) to CM by the Agència de Gestió d'Ajuts Universitarisi de Recerca, Generalitat de Catalunya.

The Paris Agreement—which is aimed at holding global warming well below 2 °C while pursuing efforts to limit it below 1.5 °C—has initiated a bottom-up process of iteratively updating nationally determined contributions to reach these long-term goals. Achieving these goals implies a tight limit on cumulative net CO2 emissions, of which residual CO2 emissions from fossil fuels are the greatest impediment. Here, using an ensemble of seven integrated assessment models (IAMs), we explore the determinants of these residual emissions, focusing on sector-level contributions. Even when strengthened pre-2030 mitigation action is combined with very stringent long-term policies, cumulative residual CO2 emissions from fossil fuels remain at 850–1,150 GtCO2 during 2016–2100, despite carbon prices of US$130–420 per tCO2 by 2030. Thus, 640–950 GtCO2 removal is required for a likely chance of limiting end-of-century warming to 1.5 °C. In the absence of strengthened pre-2030 pledges, long-term CO2 commitments are increased by 160–330 GtCO2, further jeopardizing achievement of the 1.5 °C goal and increasing dependence on CO2 removal.

1. In managing various threats to biodiversity, it is important to prioritize multiple management actions and the levels of effort to apply. However, a spatial conservation prioritization framework that integrates these key aspects, and can be generalized, is still missing. Moreover, assessing the robustness of prioritization frameworks to uncertainty in species responses to management is critical to avoid misallocation of limited resources. Yet, the impact of information uncertainty on prioritization of management effort remains unknown. 2. We present an approach for prioritizing alternative levels of conservation management effort to multiple actions, based on the ecological responses of species to management. We estimated species responses through a structured email‐based expert elicitation process, where we also captured the uncertainty in individual experts' assessments. We identified priority locations and associated level of management of effort of four actions to abate threats to freshwater‐dependent fauna, using a northern Australia case study, and quantified sensitivity of the proposed solution to uncertainty in the answers of each individual expert. 3. Achievement of conservation targets for freshwater‐dependent fauna in the Daly River catchment would require 9.4 million AU$ per year, for a total of approximately 189 million AU$ investment over 20 years. We suggest that this could be best achieved through a mix of aerial shooting of buffalos and pigs, riparian fencing and chemical spraying of weeds, applied at varying levels of management effort in key areas of the catchment. 4. Uncertainty in experts' estimation of species responses to threats causes 60% of the species to achieve 80% of their conservation targets, which was consistent across target levels. 5. Synthesis and applications . Our prioritization approach facilitates the planning of conservation management at fine spatial scales and is applicable to terrestrial, freshwater and marine realms. Plan implementation may require policy instruments ranging from landowner stewardship agreements, market‐based mechanisms and low‐intensity land use management schemes, to regulation of commercial activities within portions of marine protected areas. However, assessing plan sensitivity to uncertainty in species response to management and finding ways of dealing with it in the prioritization rather than ignoring it, as often done, remains vital for effective achievement of conservation objectives. This study was conducted with the support of funding from the Australian Research Council (discovery grant no. DP120103353 to S.L., M.J.K. and J.C. and DECRA grant no. DE130100565 to S.L.), the Australian Government's National Environmental Research Program (M.J.K., V.H. and S. L.) and support by Griffith University and the Spanish Government (Ramon y Cajal contract RYC‐2013‐13979 to V.H.).

The lack of clarity in the objectives of the Common Fisheries Policy (CFP) must be addressed to create a more efficient balance across diverse ecological, economic and social dimensions. Particularly economic and social objectives present at an overarching level must be made explicit and addressed in lower level management measures, in order to link them to biological objectives and allow policy to build a balance across types of objectives. Selecting clear objectives is essential, particularly for policy impact assessment. The aim of this paper is to demonstrate how more specific high level objectives to managing fisheries can be derived from stakeholders. The paper first reviews the definition of objectives, from a historical and conceptual perspective. Secondly, it discusses the issues of manageability and acceptability, and finally describes an articulation of the high level objectives derived from extensive stakeholder consultations at European and regional level. The results from workshops at the European level to identify objectives were further examined at regional level for the Baltic and North Seas in additional individual consultations. The German case addresses two seas (Baltic and North Seas), has a complex governance structure (due to federalism) and significant roles for the three types of actors (industry, government and environmental NGOs). The analysis suggests that establishing higher level sustainability objectives within the CFP can help diverse interest groups to develop a consensus on management actions to meet complex social goals.

1. Biodiversity conservation strategies increasingly target maintaining evolutionary history and the resilience of ecosystem function, not just species richness (SR). This has led to the emergence of two metrics commonly proposed as tools for decision making: phylogenetic diversity (PD) and functional diversity (FD). Yet the extent to which they are interchangeable remains poorly understood. 2. We explore shifts in and relationships between FD and PD of bird communities across a disturbance gradient in Borneo, from old-growth tropical forest to oil palm plantation. 3. We show a marked decline in PD, and an increase in phylogenetic mean nearest taxon distance (MNTD) from forest to oil palm, in line with declining SR across the gradient. However, phylogenetic mean pairwise distance (MPD) is constrained by forest logging more than by conversion to oil palm, taking account of SR. 4. The decline in FD across the gradient is less severe than in PD, with all metrics indicating relatively high trait diversity in oil palm despite low SR, although functional redundancy is much reduced. Accounting for SR, levels of functional over- or under-dispersion of bird communities are strongly coupled to habitat disturbance level rather than to any equivalent phylogenetic metric. 5. Policy Implications. We suggest that while phylogenetic diversity (PD) is an improvement on species richness as a proxy for functional diversity (FD), conservation decisions based on PD alone cannot reliably safeguard maximal FD. Thus, PD and FD are related but still complementary. Priority setting exercises should use these metrics in combination to identify conservation targets.

Objective Bicycle use for commuting is being encouraged not only to address physical inactivity, but also vehicular congestion, air pollution and climate change. The current study aimed to ascertain the urban environmental correlates and determinants of bicycle use for commuting (bicycle commuting) among the working or studying population in Barcelona, Spain. Methods Adults ( n = 769; 52% females) recruited whilst commuting within Barcelona (Spain) responded to a comprehensive telephone survey concerning their travel behaviour. Based upon responses collected from June 2011 to May 2012, participants were categorised into four groups: frequent bicyclists, infrequent bicyclists, willing non-bicyclists, and unwilling non-bicyclists. The determinants of frequency and willingness (propensity) to commute by bicycle were assessed by multinomial logistic regression models adjusted for potential confounders and covariates. Results The number of public bicycle stations surrounding the home address and amount of greenness surrounding the work/study address were significant positive determinants of bicycle commuting propensity. On the other hand, the number of public transport stations surrounding the home address and elevation of the work/study address were significant negative determinants of bicycle commuting propensity. Individual age, education level, gender, nationality, physical activity level and commute distance significantly affected this propensity. Conclusion Greater availability of public bicycle stations and higher levels of urban greenness may increase bicycle use by adults commuting within a city such as Barcelona, Spain. Electrically-assisted public bicycles may address the challenge of elevation, making this system a more competitive mode against traditional motorised public transport.