International audience | By disrupting nocturnal landscapes worldwide, light pollution caused by Artificial Light At Night (ALAN) is recognized as a major threat to biodiversity. As even low light intensities might affect some taxa, concerns are arising about biological responses to widespread low light levels. We used data from a French citizen science bat monitoring program (1894 full-nights monitored on 1055 sites) to explore the landscape-scale effects of light on an open-space-foraging bat species, the Serotine bat (Eptesicus serotinus). We assessed this species' abundance and timing of night-time activity (median time of activity) at foraging sites. ALAN, and to a lesser extent moonlight, reduced E. serotinus abundance. ALAN delayed activity, and this delay was amplified during overcast nights. On the contrary, where there was no ALAN, the higher the cloud cover, the earlier the activity occurred. Cloud cover likely darkened the night sky in rural locations, whereas it amplified skyglow in light-polluted places, increasing ALAN effects on bats. Interestingly, moonlight also delayed activity but this effect was weakened where there was ALAN. Our study shows that even fine variations of light levels could affect the spatiotemporal distribution of a common species usually considered to be “light tolerant”, with potential cascading effects on individual fitness and population dynamics. It stresses how urgent it is to preserve and restore dark areas to protect biodiversity from light pollution while working on light intensity and directivity where ALAN is needed.

International audience | By disrupting nocturnal landscapes worldwide, light pollution caused by Artificial Light At Night (ALAN) is recognized as a major threat to biodiversity. As even low light intensities might affect some taxa, concerns are arising about biological responses to widespread low light levels. We used data from a French citizen science bat monitoring program (1894 full-nights monitored on 1055 sites) to explore the landscape-scale effects of light on an open-space-foraging bat species, the Serotine bat (Eptesicus serotinus). We assessed this species' abundance and timing of night-time activity (median time of activity) at foraging sites. ALAN, and to a lesser extent moonlight, reduced E. serotinus abundance. ALAN delayed activity, and this delay was amplified during overcast nights. On the contrary, where there was no ALAN, the higher the cloud cover, the earlier the activity occurred. Cloud cover likely darkened the night sky in rural locations, whereas it amplified skyglow in light-polluted places, increasing ALAN effects on bats. Interestingly, moonlight also delayed activity but this effect was weakened where there was ALAN. Our study shows that even fine variations of light levels could affect the spatiotemporal distribution of a common species usually considered to be “light tolerant”, with potential cascading effects on individual fitness and population dynamics. It stresses how urgent it is to preserve and restore dark areas to protect biodiversity from light pollution while working on light intensity and directivity where ALAN is needed.

Marine Protected Areas (MPAs) are designated to enable the management of damaging activities within a discrete spatial area, and can be effective at reducing the associated impacts, including habitat loss and over-exploitation. Such sites, however, may be exposed to the potential impacts from broader scale pressures, such as anthropogenic litter, due to its diffuse nature and lack of constraint by legislative and/or political boundaries. Plastic, a large component of litter, is of particular concern, due to increasing evidence of its potential to cause ecological and socio-economic damage. The presence of sensitive marine features may mean that some MPAs are at greater potential risk from the impacts of plastic pollution than some non-protected sites. Understanding the abundance, distribution and composition of litter along coastlines is important for designing and implementing effective management strategies. Gathering such data, however, can be expensive and time-consuming but litter survey programmes that enlist citizen scientists are often able to resolve many of the logistical or financial constraints. Here, we examine data collected over 25-years (1994–2018), by Marine Conservation Society volunteers, for spatial patterns in relation to the English MPA network, with the aim of highlighting key sources of litter and identifying management priority areas. We found that MPAs in southeast (Kent) and southwest (Cornwall and Devon) England have the highest densities of shore-based litter. Plastic is the main material constituent and public littering the most common identifiable source. Items attributed to fishing activities were most prevalent in southwest MPAs and sewage related debris was highest in MPAs near large rivers and estuaries, indicating localised accumulation. When comparing inside and outside of MPAs, we found no difference in litter density, demonstrating the need for wider policy intervention at local, national and international scales to reduce the amount of litter.

Pollution of coastal and marine environments by mismanaged anthropogenic debris is a global threat requiring complex, multilateral solutions and mitigation strategies. International efforts to catalogue and quantify the density, extent and nature of mismanaged waste have not yet assessed the heterogeneity of debris between nearby areas. Better understanding of how debris types and density can be used as a proxy between regions and between land and seafloor habitats at a global scale can aid in developing cost effective and representative debris monitoring systems. Using volunteer collected clean-up and survey data, we compared the proportion and density of both total debris and specific items across 19,428 coastal land and seafloor sites from International Coastal Cleanups and Dive Against Debris surveys, from 86 countries between 2011 and 2018. We show that although some items common on land are also common on the seafloor, there is an overall global mismatch between debris types and densities on land and the seafloor from nearby areas. Correlations in land/seafloor debris type/density occurred primarily for items which entangle and/or sink, including fishing line, plastic bags, glass and polyethylene terephthalate (PET) bottles. Minimal similarity between land and seafloor surveys occurs for items which float or degrade. We suggest that to accurately evaluate local debris density, land and seafloor surveys are required to gain a holistic understanding. When detailed information on debris type, relative concentration, and likely source and transport are assessed, more cost effective and efficient policy interventions can be designed and implemented from local through to global scales.

Rivers are an important source of marine anthropogenic litter, but the particular origins of riverine litter itself have not been well established. Here we used a citizen science approach where schoolchildren examined litter at riversides and identified possible sources at over 250 sampling spots along large and small rivers in Germany, during autumn 2016 and spring 2017. Litter densities have an overall median of 0.14, interquartile range 0–0.57 items m−2 and an overall average (±standard deviation) of 0.54 ± 1.20 litter items m−2. Litter quantities differed only little by sampling year. The principal litter types found were plastics and cigarette butts (31% and 20%, respectively), followed by glass, paper, and metal items, indicating recreational visitors as the principal litter source. At many sites (85%), accumulations of litter, consisting principally of cigarettes and food packaging, have been found. At almost all sampling sites (89%), litter potentially hazardous to human health has been observed, including broken glass, sharp metal objects, used personal hygiene articles and items containing chemicals. In the search for litter sources, the schoolchildren identified mainly people who use the rivers as recreational areas (in contrast to residents living in the vicinity, illegal dumping, or the river itself depositing litter from upstream sources). These results indicate the urgent need for better education and policy measures in order to protect riparian environments and reduce input of riverine litter to the marine environment.

Air pollution exposure characterization has been shaped by many constraints. These include technologies that lead to insufficient coverage across space and/or time in order to characterize individual or community-level exposures with sufficient accuracy and precision. However, there is now capacity for continuous monitoring of many air pollutants using comparatively inexpensive, real-time sensors. Crucial questions remain regarding whether or not these sensors perform adequately for various potential end uses and whether performance varies over time or across ambient conditions. Performance scrutiny of sensors via lab- and field-testing and calibration across their lifetime is necessary for interpretation of data, and has important implications for end users including cost effectiveness and ease of use. We developed a comparatively lower-cost, portable, in-home air sampling platform and a guiding development and maintenance workflow that achieved our goal of characterizing some key indoor pollutants with high sensitivity and reasonable accuracy. Here we describe the process of selecting, validating, calibrating, and maintaining our platform – the Environmental Multi-pollutant Monitoring Assembly (EMMA) – over the course of our study to-date. We highlight necessary resources and consider implications for communities or researchers interested in developing such platforms, focusing on PM₂.₅, NO, and NO₂ sensors. Our findings emphasize that lower-cost sensors should be deployed with caution, given financial and resource costs that greatly exceed sensor costs, but that selected community objectives could be supported at lesser cost and community-based participatory research strategies could be used for more wide-ranging goals.

Citizen science is having increasing influence on environmental monitoring as its advantages are becoming recognised. However methodologies are often simplified to make them accessible to citizen scientists. We tested whether a recent citizen science survey (the OPAL Air Survey) could detect trends in lichen community composition over transects away from roads. We hypothesised that the abundance of nitrophilic lichens would decrease with distance from the road, while that of nitrophobic lichens would increase. The hypothesised changes were detected along strong pollution gradients, but not where the road source was relatively weak, or background pollution relatively high. We conclude that the simplified OPAL methodology can detect large contrasts in nitrogenous pollution, but it may not be able to detect more subtle changes in pollution exposure. Similar studies are needed in conjunction with the ever-growing body of citizen science work to ensure that the limitations of these methods are fully understood.

Monitoring beach plastic contamination across space and time is necessary for understanding its sources and ecological effects, and for guiding mitigation. This is logistically and financially challenging, especially for microplastics. Citizen science represents an option for sampling accessible sites to support long term monitoring, but challenges persist around data validation. Here we test a simple citizen science methodology to monitor visible microplastic contamination on sandy beaches using a standard quadrat unit (50 cm × 50 cm x 5 cm depth) sieved to 1 mm, to support the analysis of microplastic on two islands within the marine protected area of the Galápagos Archipelago, Ecuador (San Cristóbal and Santa Cruz islands). High school and university students undertook supervised sampling of two beaches in 2019–2020 collecting over 7000 particles. A sub-sample of the suspected microplastics collected (n = 2,213, ∼30% total) were analysed using FTIR spectrometry, confirming 93% of particles >1 mm visually identified by students were microplastics or rubber, validating this method as a crowd-sourced indicator for microplastic contamination. These data provide important insights into the plastic contamination of Galápagos, revealing plastic abundances of 0–2524 particles m⁻² over the two beaches (the highest reported in Galápagos). Strong accumulation gradients were measured parallel to the waterline at Punta Pitt (San Cristobal island) and perpendicular to the waterline at Tortuga Bay (Santa Cruz island), where four-fold higher concentrations were recorded at the sea turtle nesting habitat on the back-beach dune. No significant seasonal trends were measured during one year. These results demonstrate the value of citizen science in filling spatiotemporal knowledge gaps of beach contamination to support intervention design and conservation.

China is the largest plastic consumer in the world. Despite its plastic waste import ban in 2017, this populous economy inevitably generates a large amount of waste, including plastic waste, a considerable part of which has become marine litter. Data from the 2018 National Coastal Cleanup and Monitoring Project, the largest beach litter monitoring activities using the citizen science approach in China, have been retrieved and analyzed to understand spatial patterns, composition, and original usage of marine litter. Within this project, 24 beaches were surveyed every two months. As a result, the mean density was 3.85 ± 5.39 items m⁻², much higher than that reported by previous studies in China. There were great differences in the spatial distribution of litter. The highest densities appeared in the runoff-affected area of the Yangtze River, which was another difference from previous studies. Low-density, easy-to-transport foamed plastics were the major contributor to marine litter in these areas. Along China’s coast, approximately 90% of litter was from land-based sources, and over half of that originated from domestic sources. Including foamed plastic products, plastic litter with low recycling value dominated. Both natural and human factors influencing the spatiotemporal distribution and composition of litter are discussed. Socioeconomic factors, such as the lifestyle and consumption levels of citizens and local waste management systems, are possible explanations for the low-value characteristic of marine litter. The deviation between previous data and citizen science data in this study may be caused by many factors. Based on the discussion on these factors, some suggestions for citizen science research in China are also put forward.

Volunteer cleanup operations collect large datasets on anthropogenic litter that are seldom analyzed. Here we assess the influence of land use in both near-stream and watershed scale source domains on anthropogenic litter concentration (standing stock, kg km−1) in riparian zones of Iowa, USA. We utilized riparian litter concentration data on four classes of anthropogenic litter (metal, recyclable, garbage, and tires) from volunteer cleanup operations. Anthropogenic litter data were tested for correlation with near-stream and watershed scale land uses (developed, road density, agricultural, and open lands). Road density (road length/area) and developed land use (% area) were significantly correlated to anthropogenic litter, but agricultural (% area) and open lands (% area) were not. Metal objects correlated to near-stream road density (r = 0.79, p = 0.02), while garbage and recyclable materials correlated to watershed scale road density (r = 0.69, p = 0.06 and r = 0.71, p = 0.05 respectively). These differences in the important spatial scales of land use may be related to differences in transport characteristics of anthropogenic litter. Larger, denser metal objects may be transported more slowly through the watershed/channelized system and thus, dependent on more proximal sources, whereas smaller, less dense garbage and recyclable material are likely transported more rapidly, resulting in concentrations that depend more on watershed scale supply. We developed a linear regression model that used near-stream road density and the total amount of observed litter to predict an average anthropogenic litter density of 188 kg km−1 and a standing stock of 946 t in all Iowa streams (>4th Strahler order). The techniques employed in this study can be applied to other professional and volunteer litter datasets to develop prevention and cleanup efforts, inform investigations of process, and assess management actions.