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Biodiversity is declining rapidly. The most important causes of biodiversity loss are climate change, land- and sea-use change, invasive alien species, pollution, and overexploitation of natural resources. This unprecedented deterioration of the biosphere has profound and far-reaching consequences for insects, who play many important roles within ecosystems, including pollination and decomposition. Declines in the abundance and distribution of insects threaten these essential ecosystem functions. While there is no doubt that urgent and immediate measures are needed to address biodiversity loss and climate change, monitoring of insects is a priority to underpin and inform ongoing conservation action. Citizen science has emerged as an important tool for monitoring insects. In this primer, we explain the application of citizen science for monitoring insects and emerging approaches using digital technologies.

•1. Woodland cover in Britain has increased over the past century and is set to increase further through woodland creation schemes aiming to tackle climate change. Nonetheless, the wider repercussions of increasing woodland cover for species, especially invertebrates, have not been comprehensively assessed. •2. Here, we quantified the woodland associations of 2762 invertebrate species in Britain across 21 broad taxon groups using species occurrence records collected by specialist recording societies. We then related the strength of species' woodland associations to published estimates of their long-term national distribution trends between 1970 and 2015. •3. Across all taxa, 29% of species were positively associated with broadleaf woodland cover, whereas 27% of species were negatively associated. There was a slight tendency for species associated with broadleaf woodland to have more positive long-term distribution trends, but the effect had little explanatory power. For 15% of species, we detected a non-monotonic association with broadleaf woodland cover, such that their occurrence peaked at intermediate levels of cover. Intermediate-cover species had more positive long-term distribution trends than species with monotonic positive or negative woodland associations. •4. Our findings suggest that woodland invertebrates have not consistently increased, despite the increases in woodland cover. While some caution is warranted owing to our use of heterogeneous occurrence records, the considerable variation in distribution trends of woodland-associated species could be explained by the high diversity of woodland species and ways in which they use woodland habitat. Woodland creation, or increasing tree cover in general, could have idiosyncratic impacts on species, depending on how new woodlands are created and managed.

Bioblitzes are a popular approach to engage people and collect biodiversity data. Despite this, few studies have actually evaluated the multiple outcomes of bioblitz activities. We used a systematic review, an analysis of data from more than 1000 bioblitzes, and a detailed analysis of one specific bioblitz to inform our inquiry. We evaluated five possible bioblitz outcomes, which were creating a species inventory, engaging people in biological recording, enhancing learning about nature, discovering a species new to an area, and promoting an organization. We conclude that bioblitzes are diverse but overall effective at their aims and have advantages over unstructured biodiversity recording. We demonstrate for the first time that bioblitzes increase the recording activity of the participants for several months after the event. In addition, we provide evidence that bioblitzes are effective at bringing people and organizations together to build communities of professionals and amateurs, critical for conserving and protecting biodiversity.

•1. The current biodiversity crisis, extinction of experience of nature and rising concern about people's well-being and mental health require us to understand the benefits of activities supporting people's engagement with nature. •2. We ran a 1-week randomised controlled experiment to test the impact of nature-focussed activities on people's connectedness to nature and well-being. This project, called ‘Nature Up Close and Personal: A Wellbeing Experiment’ recruited 500 people who completed the pre- and post-participation surveys which included seven psychometric outcome measures. •3. People were randomly assigned to one of six groups. Those in non-control groups were asked to take part in one 10-min activity five times over 8 days; this could be done in any place with nature near to them. The activities were as follows: two different citizen science activities, a nature-noticing activity (asking people to note three good things in nature: 3GTiN) or a combination of citizen science and 3GTiN. •4. Citizen science, 3GTiN and the combination of the two had significant positive effects on nature connectedness, happiness, sense of worthwhile life and satisfaction with life. 3GTiN (alone and in combination with citizen science) had significant positive effects on pro-nature conservation behaviours. •5. All activities engaged the pathways to nature connectedness. Compared to 3GTiN, people doing citizen science scored lower at engaging with nature through their senses, and feeling calm or joyful, but higher for feeling that they made a difference. The combined activity engaged the pathways to nature connectedness at least as strongly as the highest scoring of citizen science or 3GTiN individually. This shows the potential to intentionally design citizen science to enhance the pathways to nature connectedness. Nature-based citizen science is more than just a way to gather environmental data: it benefits well-being and nature connectedness of participants, and (when in combin

• Purpose of the Review: One of the major threats to tree health, and hence the resilience of forests and their provision of ecosystem services, is new and emerging pests. Therefore, forest health monitoring is of major importance to detect invasive, emerging and native pest outbreaks. This is usually done by foresters and forest health experts, but can also be complemented by citizen scientists. Here, we review the use of citizen science for detection and monitoring, as well as for hypothesis-driven research and evaluation of control measures as part of forest pest surveillance and research. We then examine its limitations and opportunities and make recommendations on the use of citizen science for forest pest monitoring. • Recent Findings: The main opportunities of citizen scientists for forest health are early warning, early detection of new pests, monitoring of impact of outbreaks and scientific research. Each domain has its own limitations, opportunities and recommendations to follow, as well as their own public engagement strategies. The development of new technologies provides many opportunities to involve citizen scientists in forest pest monitoring. To enhance the benefits of citizen scientists’ inclusion in monitoring, it is important that they are involved in the cocreation of activities. • Summary: Future monitoring and research may benefit from tailor-made citizen science projects to facilitate successful monitoring by citizen scientists and expand their practice to countries where the forest health sector is less developed. In this sense, citizen scientists can help understand and detect outbreaks of new pests and avoid problems in the future.

In November 2020, a meeting was held to explore what citizen science practitioners can gain from understanding engagement, marketing, and volunteer motivations in order to benefit recruitment and retention in environmental citizen science. This report summarises the lessons learned from considering the role of people as participants within citizen science; although we note that this is only one and, for some, a contested view of participants. Marketing and motivation studies highlighted the importance of knowing more about participants. Framing and user experience experts showed how to convert knowledge into tailored approaches that enhance engagement and retention. Other fields, including the world of commerce, have potential lessons for citizen science practitioners, especially those involved in top-down, mass participatory projects that require high levels of engagement.

Social–ecological networks (SENs) represent the complex relationships between ecological and social systems and are a useful tool for analyzing and managing ecosystem services. However,mainstreaming the application of SENs in ecosystem service research has been hindered by a lack of clarity about how tomatch research questions to ecosystem service conceptualizations in SEN (i.e., as nodes, links, attributes, or emergent properties). Building from different disciplines, we propose a typology to represent ecosystem service in SENs and identify opportunities and challenges of using SENs in ecosystem service research. Our typology provides guidance for this growing field to improve research design and increase the breadth of questions that can be addressed with SEN to understand human–nature interdependencies in a changing world.

The increasing pace of climate change is an existential threat to farming continuity and biodiversity. Agricultural innovation is running too slowly but could be accelerated by a change in the agroecological narrative. A farmer-led agroecology prioritising farming continuity for biodiversity would speed up innovation and better serve science and society.

Early detection is important for the management of invasive alien species. In the last decade citizen science has become an important source of such data. Here, we used opportunistic records from the “LIFE ARTEMIS” citizen science project, in which people submitted records from places where they observed tree pests, to understand the distribution of a rapidly-spreading forest pest: the oak lace bug (Corythucha arcuata) in Slovenia. These citizen science records were not distributed randomly. We constructed a species distribution model for C. arcuata that accounted for the biased distribution of citizen science by using the records of other tree pests and diseases from the same project as pseudo-absences (so-called constrained pseudo-absences), and compared this to a model with pseudo-absences selected randomly from across Slovenia. We found that the constrained pseudo-absence model showed that C. arcuata was more likely to be found in east, in places with more oak trees and at lower elevations, and also closer to highways and railways, indicating introduction and dispersal by accidental human transport. The outputs from the model with random pseudo-absences were broadly similar, although estimates from this model tended to be higher and less precise, and some factors that were significant (proximity to minor roads and human settlements) were artefacts of recorder bias, showing the importance of taking the distribution of recording into account wherever possible. The finding that C. arcuata is more likely to be found near highways allows us to design advice for where future citizen science should be directed for efficient early detection.

1. Ecological networks are valuable for ecosystem analysis but their use is often limited by a lack of data because many types of ecological interaction, for example, predation, are short-lived and difficult to observe or detect. While there are different methods for inferring the presence of interactions, they have rarely been used to predict the interaction strengths that are required to construct weighted, or quantitative, ecological networks. 2. Here, we develop a trait-based approach suitable for inferring weighted networks, that is, with varying interaction strengths. We developed the method for seed-feeding carabid ground beetles (Coleoptera: Carabidae) although the principles can be applied to other species and types of interaction. 3. Using existing literature data from experimental seed-feeding trials, we predicted a per-individual interaction cost index based on carabid and seed size. This was scaled up to the population level to create inferred weighted networks using the abundance of carabids and seeds from empirical samples and energetic intake rates of carabids from the literature. From these weighted networks, we also derived a novel measure of expected predation pressure per seed type per network. 4. This method was applied to existing ecological survey data from 255 arable fields with carabid data from pitfall traps and plant seeds from seed rain traps. Analysis of these inferred networks led to testable hypotheses about how network structure and predation pressure varied among fields. 5. Inferred networks are valuable because (a) they provide null models for the structuring of food webs to test against empirical species interaction data, for example, DNA analysis of carabid gut regurgitates and (b) they allow weighted networks to be constructed whenever we can estimate interactions between species and have ecological census data available. This permits ecological network analysis even at times and in places when interactions were not directly asse

Reported declines in insect populations have sparked global concern, with artificial light at night (ALAN) identified as a potential contributing factor. Despite strong evidence that lighting disrupts a range of insect behaviors, the empirical evidence that ALAN diminishes wild insect abundance is limited. Using a matched-pairs design, we found that street lighting strongly reduced moth caterpillar abundance compared with unlit sites (47% reduction in hedgerows and 33% reduction in grass margins) and affected caterpillar development. A separate experiment in habitats with no history of lighting revealed that ALAN disrupted the feeding behavior of nocturnal caterpillars. Negative impacts were more pronounced under white light-emitting diode (LED) street lights compared to conventional yellow sodium lamps. This indicates that ALAN and the ongoing shift toward white LEDs (i.e., narrow- to broad-spectrum lighting) will have substantial consequences for insect populations and ecosystem processes.

We believe that approaches to landscape modification should explicitly include farmers, given their understanding of landscape management practices, and consider climate change, so that the landscapes are designed for future environmental conditions. Climate change is an existential threat to farmers and current patterns of arable agriculture, leading to increases in the variability of agricultural productivity and crop failure. The performance of many of the crops that are currently highly productive will decline significantly and the geographical envelopes within which these crops can be grown are expected to shift northwards in Europe. Farmers will likely be faced with a choice: either leave farming or modify the crops that are grown, adopting new cultivars or species able to be cultivated profitably under future climatic conditions. We hypothesised that farmers do not adopt new crops or cultivars individually but use crops within sequences, called rotations, which are agronomically well understood. We know from past research that changes to rotations will lead to changes in biodiversity and the ecosystem services furnished by farmland, both within a field and at landscape scales. Here, we show how we might: use farmer knowledge of crop agronomy to propose future crop rotations in the light of climate change predictions; model these crop rotations to estimate likely effects on economy, biodiversity and ecosystem services; and validate these predictions through empirical study in regions where the rotations are already used. A workflow of co-development would have the benefit of generating practical rotations built on farmer knowledge and demonstrate empirically the predicted economic and ecological effects, markedly increasing the likely credibility of the results for farmers. Such a methodology has the potential to transform future sustainable agricultural landscapes.

1. The night‐time environment is increasingly being lit, often by broad‐spectrum lighting, and there is growing evidence that artificial light at night (ALAN) has consequences for ecosystems, potentially contributing to declines in insect populations. 2. Moths are species‐rich, sensitive to ALAN, and have undergone declines in Europe, making them the ideal group for investigating the impacts of light pollution on nocturnal insects more broadly. Here, we take a life cycle approach to review the impacts of ALAN on moths, drawing on a range of disciplines including ecology, physiology, and applied entomology. 3. We find evidence of diverse impacts across most life stages and key behaviours. Many studies have examined flight‐to‐light behaviour in adults and our meta‐analysis found that mercury vapour, metal halide, and compact fluorescent bulbs induce this more than LED and sodium lamps. However, we found that ALAN can also disrupt reproduction, larval development, and pupal diapause, with likely negative impacts on individual fitness, and that moths can be indirectly affected via hostplants and predators. These findings indicate that ALAN could also affect day‐flying insects through impacts on earlier life stages. 4. Overall, we found strong evidence for effects of artificial light on moth behaviour and physiology, but little rigorous, direct evidence that this scales up to impacts on populations. Crucially, there is a need to determine the potential contribution of ALAN to insect declines, relative to other drivers of change. In the meantime, we recommend precautionary strategies to mitigate possible negative effects of ALAN on insect populations.

The early detection of tree health pests and disease is an important component of biosecurity to protect the aesthetic, recreational and economic importance of trees, woodlands and forestry. Citizen science is valuable in supporting the early detection of tree pests and diseases. Different stakeholders (government, business, society and individual) will vary in their opinion of the balance between costs and benefits of early detection and consequent management, partly because many costs are local whereas benefits are felt at larger scales. This can create clashes in motivations of those involved in citizen science, thus leading to ethical dilemmas about what is good and responsible conduct for the use of citizen science. We draw on our experience of tree health citizen science to exemplify five dilemmas. These dilemmas arise because: the consequences of detection may locally be severe (e.g. the destruction of trees); knowledge of these impacts could lead to refusal to make citizen science reports; citizen science reports can be made freely, but can be costly to respond to; participants may expect solutions even if these are not possible; and early detection is (by definition) a rare event. Effective engagement and dialogue across stakeholders, including public stakeholders, is important to properly address these issues. This is vital to ensure the public’s long-term support for and trust in the use of citizen science for the early detection of tree pests and diseases.

Around the world volunteers and non-professionals collect data as part of environmental citizen science projects, collecting wildlife observations, measures of water quality and much more. However, where projects allow flexibility in how, where, and when data are collected there will be variation in the behaviour of participants which results in biases in the datasets collected. We develop a method to quantify this behavioural variation, describing the key drivers and providing a tool to account for biases in models that use these data. We used a suite of metrics to describe the temporal and spatial behaviour of participants, as well as variation in the data they collected. These were applied to 5,268 users of the iRecord Butterflies mobile phone app, a multi-species environmental citizen science project. In contrast to previous studies, after removing transient participants (those active on few days and who contribute few records), we do not find evidence of clustering of participants; instead, participants fall along four continuous axes that describe variation in participants’ behaviour: recording intensity, spatial extent, recording potential and rarity recording. Our results support a move away from labelling participants as belonging to one behavioural group or another in favour of placing them along axes of participant behaviour that better represent the continuous variation between individuals. Understanding participant behaviour could support better use of the data, by accounting for biases in the data collection process.

Conservationists increasingly use unstructured observational data, such as citizen science records or ranger patrol observations, to guide decision making. These datasets are often large and relatively cheap to collect, and they have enormous potential. However, the resulting data are generally “messy,” and their use can incur considerable costs, some of which are hidden. We present an overview of the opportunities and limitations associated with messy data by explaining how the preferences, skills, and incentives of data collectors affect the quality of the information they contain and the investment required to unlock their potential. Drawing widely from across the sciences, we break down elements of the observation process in order to highlight likely sources of bias and error while emphasizing the importance of cross-disciplinary collaboration. We propose a framework for appraising messy data to guide those engaging with these types of dataset and make them work for conservation and broader sustainability applications.

1. Wildfires drive global biodiversity patterns and affect plant–pollinator interactions, and are expected to become more frequent and severe under climate change. Post‐fire plant communities often have increased floral abundance and diversity, but the effects of wildfires on the ecological process of pollination are poorly understood. Nocturnal moths are globally important pollinators, but no previous study has examined the effects of wildfire on nocturnal pollination interactions. 2. We investigated the effects of wildfire on nocturnal pollen‐transport networks. We analysed the abundance and species richness of moths and flowers, and the structure of these networks, at three burned and three unburned sites in Portugal for two years, starting eight months after a large fire. 3. Nocturnal pollen‐transport networks had lower complexity and robustness following the fire than at nearby unburned sites. Overall, 70% of individual moths carried pollen, and moths were found to be transporting pollen from 83% of the flower species present. Burned sites had significantly more abundant flowers, but less abundant and species‐rich moths. Individual moths transported more pollen in summer at burned sites, but less in winter; however, total pollen transport by the moth assemblage at burned sites was just 20% of that at unburned sites. Interaction turnover between burned and unburned networks was high. 4. Negative effects of fire upon moths will likely permeate to other taxa through loss of mutualisms. Therefore, if wildfires become more frequent under climate change, community resilience may be eroded. Understanding the responses of ecological networks to wildfire can inform management that promotes resilience and facilitates whole‐ecosystem conservation.

1. Moths are globally relevant as pollinators but nocturnal pollination remains poorly understood. Plant–pollinator interaction networks are traditionally constructed using either flower‐visitor observations or pollen‐transport detection using microscopy. Recent studies have shown the potential of DNA metabarcoding for detecting and identifying pollen‐transport interactions. However, no study has directly compared the realised observations of pollen‐transport networks between DNA metabarcoding and conventional light microscopy. 2. Using matched samples of nocturnal moths, we constructed pollen‐transport networks using two methods: light microscopy and DNA metabarcoding. Focussing on the feeding mouthparts of moths, we developed and provide reproducible methods for merging DNA metabarcoding and ecological network analysis to better understand species interactions. 3. DNA metabarcoding detected pollen on more individual moths, and detected multiple pollen types on more individuals than microscopy, although the average number of pollen types per individual was unchanged. However, after aggregating individuals of each species, metabarcoding detected more interactions per moth species. Pollen‐transport network metrics differed between methods because of variation in the ability of each to detect multiple pollen types per moth and to separate morphologically similar or related pollen. We detected unexpected but plausible moth–plant interactions with metabarcoding, revealing new detail about nocturnal pollination systems. 4. The nocturnal pollination networks observed using metabarcoding and microscopy were similar yet distinct, with implications for network ecologists. Comparisons between networks constructed using metabarcoding and traditional methods should therefore be treated with caution. Nevertheless, the potential applications of metabarcoding for studying plant–pollinator interaction networks are encouraging, especially when investigating understudied pollinators

Artificial light at night (ALAN) is an increasingly important driver of global change. Lighting directly affects plants, but few studies have investigated indirect effects mediated by interacting organisms. Nocturnal Lepidoptera are globally important pollinators, and pollen transport by moths is disrupted by lighting. Many street lighting systems are being replaced with novel, energy‐efficient lighting, with unknown ecological consequences. Using the wildflower Silene latifolia, we compared pollination success and quality at experimentally lit and unlit plots, testing two major changes to street lighting technology: in lamp type, from high‐pressure sodium lamps to light‐emitting diodes, and in lighting regime, from full‐night (FN) to part‐night (PN) lighting. We predicted that lighting would reduce pollination. S. latifolia was pollinated both diurnally and nocturnally. Contrary to our predictions, flowers under FN lighting had higher pollination success than flowers under either PN lighting or unlit controls, which did not significantly differ from each other. Lamp type, lighting regime, and distance from the light all significantly affected aspects of pollination quality. These results confirm that street lighting could affect plant reproduction through indirect effects mediated by nocturnal insects, and further highlight the possibility for novel lighting technologies to mitigate the effects of ALAN on ecosystems.

Global biodiversity monitoring is urgently needed across the world to assess the impacts of environmental change on biodiversity. One way to increase monitoring is through citizen science. ‘Citizen science’ is a term that we use in this chapter to describe the diverse approaches that involve people in monitoring in a voluntary capacity, thus including participatory monitoring in which people work collaboratively with scientists in developing monitoring. There is great unrealised potential for citizen science, especially in Asia and Africa. However, to fulfil this potential citizen science will need to meet local needs (for participants, communities and decision makers, including people's own use of the data and their motivations to participate) and support global needs for biodiversity monitoring (including the United Nations’ Sustainable Development Goals and the Aichi Biodiversity Targets). Activities should be feasible (for participants to provide scientifically rigorous data) and useful (for data users, from local to global scales). We use examples from across the world to demonstrate how monitoring can engage different types of participants, through different technologies, to record different variables according to different sampling approaches. Overall, these examples show how citizen science has the potential to provide a step change in our ability to monitor biodiversity—and hence respond to threats at all scales from local to global.

1. Citizen science is gaining increasing prominence as a tool for science and engagement. However, despite being a potentially valuable tool for sustainable development, citizen science has little visibility in many developing countries. 2. We undertook a collaborative prioritisation process with experts in conservation and the environment to assess the potential of environmental citizen science in East Africa, including its opportunities, benefits and barriers. This provided principles that are applicable across developing countries, particularly for large‐scale citizen science. 3. We found that there was great potential for citizen science to add to our scientific knowledge of natural resources and biodiversity trends. Many of the important benefits of citizen science were for people, as well as the environment directly. Major barriers to citizen science were mostly social and institutional, although projects should also consider access to suitable technology and language barriers. 4. Policy implications. Citizen science can provide data to support decision‐making and reporting against international targets. Participation can also provide societal benefits, informing and empowering people, thus supporting the United Nations’ Sustainable Development Goals. In developing countries, innovation is needed to further develop culturally relevant citizen science that benefits participants and end users. This should be supported through regional networks of stakeholders for sharing best practice.

Understanding spatial variation in the structure and stability of plant–pollinator networks, and their relationship with anthropogenic drivers, is key for maintaining pollination services and mitigating declines. Constructing sufficient networks to examine patterns over large spatial scales remains challenging. Using biological records (citizen science), we constructed potential plant–pollinator networks at 10 km resolution across Great Britain, comprising all potential interactions inferred from recorded floral visitation and species co‐occurrence. We calculated network metrics (species richness, connectance, pollinator and plant generality) and adapted existing methods to assess robustness to sequences of simulated plant extinctions across multiple networks. We found positive relationships between agricultural land cover and both pollinator generality and robustness to extinctions under several extinction scenarios. Increased robustness was attributable to changes in plant community composition (fewer extinction‐prone species) and network structure (increased pollinator generality). Thus, traits enabling persistence in highly agricultural landscapes can confer robustness to potential future perturbations on plant–pollinator networks.

Analysis of ecological networks is a valuable approach to understanding the vulnerability of systems to disturbance. The tolerance of ecological networks to coextinctions, resulting from sequences of primary extinctions (here termed “knockout extinction models”, in contrast with other dynamic approaches), is a widely used tool for modeling network “robustness”. Currently, there is an emphasis to increase biological realism in these models, but less attention has been given to the effect of model choices and network structure on robustness measures. Here, we present a suite of knockout extinction models for bipartite ecological networks (specifically plant–pollinator networks) that can all be analyzed on the same terms, enabling us to test the effects of extinction rules, interaction weights, and network structure on robustness. We include two simple ecologically plausible models of propagating extinctions, one new and one adapted from existing models. All models can be used with weighted or binary interaction data. We found that the choice of extinction rules impacts robustness; our two propagating models produce opposing effects in all tests on observed plant–pollinator networks. Adding weights to the interactions tends to amplify the opposing effects and increase the variation in robustness. Variation in robustness is a key feature of these extinction models and is driven by the structural heterogeneity of nodes (specifically, the skewness of the plant degree distribution) in the network. Our analysis therefore reveals the mechanisms and fundamental network properties that drive observed trends in robustness.

The aim of the project is to support the development of the JNCC Terrestrial Surveillance Schemes and to undertake analysis that cuts across the schemes. It is important that this development and analysis is set in the context of the needs of public sector bodies. Therefore, in the first year of the TSDA project, it was valuable to undertake an assessment of the needs for biodiversity evidence in the CNCBs and related public-sector bodies. Specifically, the aims for this assessment were to ensure that there was a clear understanding of the needs of public environmental bodies and to provide evidence of that understanding.

The immune state of wild animals is largely unknown. Knowing this and what affects it is important in understanding how infection and disease affects wild animals. The immune state of wild animals is also important in understanding the biology of their pathogens, which is directly relevant to explaining pathogen spillover among species, including to humans. The paucity of knowledge about wild animals' immune state is in stark contrast to our exquisitely detailed understanding of the immunobiology of laboratory animals. Making an immune response is costly, and many factors (such as age, sex, infection status, and body condition) have individually been shown to constrain or promote immune responses. But, whether or not these factors affect immune responses and immune state in wild animals, their relative importance, and how they interact (or do not) are unknown. Here, we have investigated the immune ecology of wild house mice—the same species as the laboratory mouse—as an example of a wild mammal, characterising their adaptive humoral, adaptive cellular, and innate immune state. Firstly, we show how immune variation is structured among mouse populations, finding that there can be extensive immune discordance among neighbouring populations. Secondly, we identify the principal factors that underlie the immunological differences among mice, showing that body condition promotes and age constrains individuals’ immune state, while factors such as microparasite infection and season are comparatively unimportant. By applying a multifactorial analysis to an immune system-wide analysis, our results bring a new and unified understanding of the immunobiology of a wild mammal.

Citizen science—the involvement of volunteers in data collection, analysis and interpretation—simultaneously supports research and public engagement with science, and its profile is rapidly rising. Citizen science represents a diverse range of approaches, but until now this diversity has not been quantitatively explored. We conducted a systematic internet search and discovered 509 environmental and ecological citizen science projects. We scored each project for 32 attributes based on publicly obtainable information and used multiple factor analysis to summarise this variation to assess citizen science approaches. We found that projects varied according to their methodological approach from ‘mass participation’ (e.g. easy participation by anyone anywhere) to ‘systematic monitoring’ (e.g. trained volunteers repeatedly sampling at specific locations). They also varied in complexity from approaches that are ‘simple’ to those that are ‘elaborate’ (e.g. provide lots of support to gather rich, detailed datasets). There was a separate cluster of entirely computer-based projects but, in general, we found that the range of citizen science projects in ecology and the environment showed continuous variation and cannot be neatly categorised into distinct types of activity. While the diversity of projects begun in each time period (pre 1990, 1990–99, 2000–09 and 2010–13) has not increased, we found that projects tended to have become increasingly different from each other as time progressed (possibly due to changing opportunities, including technological innovation). Most projects were still active so consequently we found that the overall diversity of active projects (available for participation) increased as time progressed. Overall, understanding the landscape of citizen science in ecology and the environment (and its change over time) is valuable because it informs the comparative evaluation of the ‘success’ of different citizen science approaches. Comparative evaluation prov

Invasive alien species, including pests and diseases of plants and animals, are a major cause of biodiversity change and may impact upon human well-being and the economy. If new, potentially invasive, taxa arrive then it is most cost-effective to respond as early in their establishment as possible. Information to support this can be gained from volunteers, i.e. via citizen science. However, it is vital to develop ways of quantifying volunteer recorder effort to assess its contribution to the detection of rare events, such as the arrival of invasive alien species. We considered the potential to detect adult oak processionary moths (Thaumetopoea processionea) by amateur naturalists recording moths at light traps. We calculated detection rates from the Netherlands, where T. processionea is widely established and poses a risk to tree health and human health, and applied these to the spatial pattern of moth recording effort in the UK. The probability of recording T. processionea in the Netherlands varied across provinces from 0.05–2.4% per species of macro-moth recorded on a list of species (so equalling 1–52% for a list of 30 species). Applying these rates to the pattern of moth recording in the UK: T. processionea could be detected (detection > 0%), if it were present, in 69% and 4.7% of 10 km and 1 km squares, respectively. However, in most squares detection probability is low (< 1% of 1 km squares have annual detection probability of > 10%). Our study provides a means to objectively assess the use of citizen science as a monitoring tool in the detection of rare events, e.g. the arrival of invasive alien species, occurrence of rare species and natural colonisation.

Agricultural intensification is a leading cause of global biodiversity loss, which can reduce the provisioning of ecosystem services in managed ecosystems. Organic farming and plant diversification are farm management schemes that may mitigate potential ecological harm by increasing species richness and boosting related ecosystem services to agroecosystems. What remains unclear is the extent to which farm management schemes affect biodiversity components other than species richness, and whether impacts differ across spatial scales and landscape contexts. Using a global metadataset, we quantified the effects of organic farming and plant diversification on abundance, local diversity (communities within fields), and regional diversity (communities across fields) of arthropod pollinators, predators, herbivores, and detritivores. Both organic farming and higher in-field plant diversity enhanced arthropod abundance, particularly for rare taxa. This resulted in increased richness but decreased evenness. While these responses were stronger at local relative to regional scales, richness and abundance increased at both scales, and richness on farms embedded in complex relative to simple landscapes. Overall, both organic farming and in-field plant diversification exerted the strongest effects on pollinators and predators, suggesting these management schemes can facilitate ecosystem service providers without augmenting herbivore (pest) populations. Our results suggest that organic farming and plant diversification promote diverse arthropod metacommunities that may provide temporal and spatial stability of ecosystem service provisioning. Conserving diverse plant and arthropod communities in farming systems therefore requires sustainable practices that operate both within fields and across landscapes.

Ecological systems comprise of individuals and species interacting with each other and their environment, and these interactions combine to form complex networks. The maintenance of biodiversity and many ecosystem functions depend upon these ecological interactions. Humans, their crops and livestock can also be considered as part of these networks of interactions making network analysis valuable for considering the resilience of ecosystem services, i.e., the benefits we gain from nature. Networks are visually appealing and visualisation can attract attention and inform, both to communicate overall messages and provide comparisons between networks. There are many different approaches and layouts for visualising networks, but there is little research to help guide best practice. Ultimately though, best practice should be to ensure that messages are supported by evidence and clearly communicated with reference to the competence of the audience. Given the appeal of visualisations and the importance of networks in communicating the interdependence of species (including humans), ecological networks and their visualisation can be used to support excellent public engagement and can be used to enhance the value of citizen science, in which people actively contribute to scientific research. Network approaches could also be valuable for engagement with decision-makers and stakeholders, including their application to complex socio-economic systems, especially where co-production of network visualisations could provide evidence-based overviews of data. In summary, ecological networks and their visualisation are an important tool for scientific inquiry, communication and engagement with even greater potential than has currently been realised.

Pollination and herbivory networks have mainly been studied separately, highlighting their distinct structural characteristics and the related processes and dynamics. However, most plants interact with both pollinators and herbivores, and there is evidence that both types of interaction affect each other. Here we investigated the way plants connect these mutualistic and antagonistic networks together, and the consequences for community stability. Using an empirical data set, we show that the way plants connect pollination and herbivory networks is not random and promotes community stability. Analyses of the structure of binary and quantitative networks show different results: the plants’ generalism with regard to pollinators is positively correlated to their generalism with regard to herbivores when considering binary interactions, but not when considering quantitative interactions. We also show that plants that share the same pollinators do not share the same herbivores. However, the way plants connect pollination and herbivory networks promotes stability for both binary and quantitative networks. Our results highlight the relevance of considering the diversity of interaction types in ecological communities, and stress the need to better quantify the costs and benefits of interactions, as well as to develop new metrics characterizing the way different interaction types are combined within ecological networks.

1. Significant advances in both mathematical and molecular approaches in ecology offer unprecedented opportunities to describe and understand ecosystem functioning. Ecological networks describe interactions between species, the underlying structure of communities and the function and stability of ecosystems. They provide the ability to assess the robustness of complex ecological communities to species loss, as well as a novel way of guiding restoration. However, empirically quantifying the interactions between entire communities remains a significant challenge. 2. Concomitantly, advances in DNA sequencing technologies are resolving previously intractable questions in functional and taxonomic biodiversity and provide enormous potential to determine hitherto difficult to observe species interactions. Combining DNA metabarcoding approaches with ecological network analysis presents important new opportunities for understanding large-scale ecological and evolutionary processes, as well as providing powerful tools for building ecosystems that are resilient to environmental change. 3. We propose a novel ‘nested tagging’ metabarcoding approach for the rapid construction of large, phylogenetically structured species-interaction networks. Taking tree–insect–parasitoid ecological networks as an illustration, we show how measures of network robustness, constructed using DNA metabarcoding, can be used to determine the consequences of tree species loss within forests, and forest habitat loss within wider landscapes. By determining which species and habitats are important to network integrity, we propose new directions for forest management. 4. Merging metabarcoding with ecological network analysis provides a revolutionary opportunity to construct some of the largest, phylogenetically structured species-interaction networks to date, providing new ways to: (i) monitor biodiversity and ecosystem functioning; (ii) assess the robustness of interacting communities to species loss; and

Background: Recently there has been increasing focus on monitoring pollinating insects, due to concerns about their declines, and interest in the role of volunteers in monitoring pollinators, particularly bumblebees, via citizen science. Methodology/Principal Findings: The Big Bumblebee Discovery was a one-year citizen science project run by a partnership of EDF Energy, the British Science Association and the Centre for Ecology & Hydrology which sought to assess the influence of the landscape at multiple scales on the diversity and abundance of bumblebees. Timed counts of bumblebees ( Bombus spp.; identified to six colour groups) visiting focal plants of lavender (Lavendula spp.) were carried out by about 13 000 primary school children (7 – 11 years old) from over 400 schools across the UK. 3948 reports were received totalling 26 868 bumblebees. We found that while the wider landscape type had no significant effect on reported bumblebee abundance, the local proximity to flowers had a significant effect (fewer bumblebees where other flowers were reported to be > 5m away from the focal plant). However, the rate of mis-identifcation, revealed by photographs uploaded by participants and a photo-based quiz, was high. Conclusions/Significance: Our citizen science results support recent research on the importance of local floral resources on pollinator abundance. Timed counts of insects visiting a lure plant is potentially an effective approach for standardised pollinator monitoring, engaging a large number of participants with a simple protocol. However, the relatively high rate of mis-identifications (compared to reports from previous pollinator citizen science projects) highlights the importance of investing in resources to train volunteers. Also, to be a scientifically valid method for enquiry, citizen science data needs to be sufficiently high quality, so receiving supporting evidence (such as photographs) would allow this to be tested and for records to be verified.

People have been recording wildlife for centuries and the resulting datasets lead to important scientific research. The Biological Records Centre (BRC), established in 1964, is a national focus for terrestrial and freshwater species recording in the United Kingdom (UK). BRC works with the voluntary recording community (i.e. a mutualistic symbiosis) through support of national recording schemes (i.e. ‘citizen science’, but unlike most citizen science it is volunteer led) and adds value to the data through analysis and reporting. Biological recording represents a diverse range of activities, involving an estimated 70 000 people annually in the UK, from expert volunteers undertaking systematic monitoring to mass participation recording. It is an invaluable monitoring tool because the datasets are long term, have large geographic extent and are taxonomically diverse (85 taxonomic groups). It supports a diverse range of outputs, e.g. atlases showing national distributions (12 127 species from over 40 taxonomic groups) and quantified trends (1636 species). BRC pioneers the use of technology for data capture (online portals and smartphone apps) and verification (including automated verification) through customisable, inter-operable database systems to facilitate efficient data flow. We are confident that biological recording has a bright future with benefits for people, science, and nature.

1. Ecological resilience is developing into a credible paradigm for policy development and environmental management for preserving natural capital in a rapidly changing world. However, resilience emerges from complex interactions, limiting the translation of theory into practice. 2. Main limitations include the following: (i) difficulty in quantification and detection of changes in ecological resilience, (ii) a lack of empirical evidence to support preventative or proactive management and (iii) difficulties in managing processes operating across socio-ecological systems that vary in space and time. 3. We highlight recent research with the potential to address these limitations including new and/or improved indicators of resilience and tools to assess scale as a driver of resilience. 4. Synthesis and applications. Effective resilience-based management must be adaptive in nature. To support this, we propose an operational model using resilience-based iterative management actions operating across scales.