Artificial light at night (ALAN) has been spreading rapidly globally, disrupting animal physiology, behaviour and associated ecosystem processes. However, impacts on soil-dwelling animals that are nocturnally active aboveground remain underexplored. Here, we examined these for the earthworm Lumbricus terrestris L., an ecosystem engineer that frequently surfaces at night. We recorded four types of L. terrestris nighttime surface behaviour, including overall surface activity, and three finer categories: risk exploration before surfacing, foraging and over-surface exploration. One experiment (controlled-temperature-room-based) tested these behavioural responses to seven ALAN levels, whilst another (field-based) investigated whether behavioural responses can consequently affect litter removal and soil respiration. In the controlled-temperature room, compared to darkness, L. terrestris significantly decreased their overall nighttime foraging at ALAN levels of 10 lx and above, with these negative ALAN effect sizes increasing with light intensity. With more risk exploration before surfacing, L. terrestris still showed greatly reduced foraging activity at the 10 lx ALAN level in the field. However, such altered behaviour did not cause clear patterns in either litter removal or soil respiration. Our results confirm that 10 lx ALAN (or potentially lower) is effective in disrupting L. terrestris nighttime surface behaviour, but this may have limited impacts on short-term C cycling.

Electricity generation is a major contributor to environmental impacts. However, a holistic yet detailed understanding of the cumulative environmental consequences of China's current electricity system, the world's largest, is still lacking. Using spatially explicit life cycle assessment, this study analysed the magnitude and global spatial distribution of a wide range of environmental footprints of China's total electricity supply from six main power technologies (coal, gas, wind, solar, nuclear and hydropower). Greenhouse Gas Emissions, Particulate Matter Formation, Freshwater Eutrophication, Mineral Resource Use and Land Transformation were found to be 5.5 Gt CO2 eq, 1.4 Mt PM2.5 eq, 1.8 kt PO4 P-lim eq, 6.2 Mt mineral deprived and 387 km2 arable land eq, respectively. Coal contributed most to four impact categories, accounting for 93 % of Greenhouse Gas Emissions, 95 % of Particulate Matter Formation, 63 % of Freshwater Eutrophication and 50 % of Land Transformation. In contrast, wind contributed most (58 %) to Mineral Resource Use and hydropower contributed 40 % of Land Transformation. The spatial distribution suggests that 99 % of Greenhouse Gas Emissions and 96 % of Particulate Matter Formation were within China while 58 % of Land Transformation of coal and 63 % of Freshwater Eutrophication of solar were widely distributed globally outside of China. These findings suggest that local, national and international policymakers should integrate full life cycle environmental footprints of power systems and their spatial distribution into decision making and establish strategies that can more effectively mitigate the impacts or avoid impact shifting across different countries, sectors and impact categories.

Humanity is urbanizing, with vast implications on natural systems. To date, most research on urban biodiversity has centered on temperate biomes. Conversely, drylands, collectively the largest terrestrial global biome, remain understudied. Here, we synthesize key mechanistic differences of urbanization's impacts on biodiversity across these biomes. Irrigation shapes dryland urban ecology, and can lead to greener, sometimes more biodiverse, landscapes than local wildlands. These green urban patches in drylands often have a different species composition, including many non-native and human-commensal species. Socioeconomic factors - locally and globally - can mediate how biomes shape urban biodiversity patterns through the effects of irrigation, greening, and invasive species. We advocate for more research in low-income dryland cities, and for implementing biome-specific, scientifically grounded management and policies.

Numbers of Earth Observation (EO) satellites have increased exponentially over the past decade, fuelled by a shift towards constellation models that promise to deliver data at finer spatial, temporal and spectral resolutions compared to the past. The result is the now >1000 EO satellites in orbit, a population that is rapidly increasing because of a booming private-sector interest in space imaging. Flowing from this, EO data volumes have mushroomed in recent years, and data processing has migrated to the cloud, with scientists leveraging tools such as Google Earth Engine for information retrieval. Whilst considerable attention has been given to the launch and in-orbit environmental impacts of satellites (e.g. rocket emissions and space-junk risks), specific environmental impacts from EO missions (data infrastructures and cloud computation); have so far escaped critical scrutiny. It is urgent that the environmental science community address this gap, so that the environmental good of EO can withstand scrutiny.Data centres consume high quantities of water and energy and they may be situated in sensitive geographical situations far away from both users and launchpads (i.e. a transboundary environmental concern). There are also hidden impacts in the carbon-intensive processes of computer component manufacture, impacting places and communities far from the site of EO information retrieval. We scope the broad suite of transboundary environmental impacts that EO generates. Related to the data aspect of the EO life-cycle, we quantify the current volume of global EO data holdings (> 800 PB currently, increasing by 100 PB / year). Mapping the distribution of datasets across different data centre providers, our work shows high redundancy of datasets, with collections from NASA and ESA replicated across many data centres globally. Storage of this data volume generates annual CO2 equivalent emissions summing to >4000 tonnes/year. We quantify the environmental cost of performing EO functions on the cloud compared to desktop machines, using Google Earth Engine as an exemplar, scaling emissions using the ‘Earth Engine Compute Unit’. We show how large-scale analyses executed within GEE rapidly scale to produce the equivalent emissions of a single ticket on an economy flight ticket from London-Paris. Executing these processes on the cloud takes seconds, and these estimates do not account for emissions from microprocessor manufacture, nor do they account for users running processes multiple times (e.g. during code development). A major blind-spot is that the geography of GEE data centres is hidden from users, with no choice given to users about where GEE processes are executed. It is important that EO providers become more transparent about the location-specific impacts of EO work, and provide tools for measuring the environmental cost of cloud computation. Furthermore, the EO community as one which is concerned with the fate of Earth’s environment must now urgently and critically consider the broad suite of EO data life-cycle impacts that lie (a) beyond the launchpad, and (b) on Earth rather than in space; taking action to minimise and mitigate them. This is important particularly because EO data will long outlive the satellites that provided them.

Experiencing nature offers numerous health and well-being benefits, particularly for urban residents. Although the benefits of visiting natural environments are well documented, less is known about the health effects of experiencing nature without going outdoors-in particular, viewing it through building windows. This meta-analysis synthesizes findings from 28 studies encompassing 104 results to examine the relationship between window views of nature and human health. Improvements were reported across various physiological, psychological, and physical health measures, with most studies focused on psychological outcomes. The meta-analytic results indicate consistently positive effects, with particularly strong benefits in studies using physiological health measures and focusing on nature in urban settings. Although some publication bias was detected, correcting for it did not change the overall conclusions. These findings highlight the potential of integrating nature views into built environments as a practical strategy for enhancing public health, particularly in urban areas.

Fieldwork-based research and education in ecology are under multiple threats and are progressively declining. We call for greater attention to this ongoing loss of direct field experience within the ecology community, as it could have widespread consequences for science and education, ultimately hindering efforts to address the ongoing biodiversity crisis.

Biodiversity renewal activities are causing major changes to landscapes and ecological assemblages in some areas. Initiatives are inherently intertwined with local people and communities, who can be drivers, inhibitors and beneficiaries of renewal efforts. It is therefore critical to understand how biodiversity renewal impacts people's pro‐nature attitudes and behaviours, health and well‐being. Research to date has established that exposure to nature is linked to health and well‐being, as well as to pro‐environmental behaviours. However, most studies have been cross‐sectional, hindering causal inference, or have focused on attitudes and behaviours relating to the environment in general, rather than on the impacts of biodiversity or environmental improvement efforts. Relatively little is known about how people's interactions with nature vary, or which components contribute to pro‐nature attitudes and behaviours, health, or well‐being over time. Here we introduce the Renewing Biodiversity Longitudinal Survey (ReBLS), a pioneering new longitudinal panel study exploring people's pro‐nature attitudes and behaviours, health and well‐being and whether these are affected by processes of environmental change and the renewal of biodiversity (both actual and perceived). This will be one of the first attempts to track changes in environmental responses, attitudes and behaviours over time within individuals. The survey will involve a national sample of approximately 18,000 adults from across England. The panel will be invited to complete the survey once a year for 3 years initially. We will link the longitudinal survey data with highly localised spatial information about the environment where participants live, including land cover, habitats and species distributions. We will measure participants' exposure to biodiversity renewal using several approaches, including self‐reported awareness of and direct and indirect involvement in biodiversity renewal activities, as well as a spatial assessment based on an audit of renewal activities within England. The ReBLS survey will advance understanding of whether, and how, biodiversity renewal affects pro‐nature attitudes and behaviours, health and well‐being. More generally, it will produce data with broad applications for both academics working on topics relating to people and nature and for practitioners making strategic decisions around biodiversity renewal, land management and public health. Read the free Plain Language Summary for this article on the Journal blog.

Nature conservation is increasingly focused on recovering depleted populations and ecosystems. The United Nations General Assembly has proclaimed 2021-2030 the UN Decade on Ecosystem Restoration, and global commitments to ecosystem restoration in response to biodiversity, climate, and sustainable development targets are now considerable, with over 100 nations committed to halting and reversing forest loss and land degradation by 2030. The impacts of these resources on nature recovery will depend on how actions are identified and implemented. Systematic conservation planning has historically been used to prioritize areas for protection but has shown great potential to guide nature recovery actions that are underpinned by principles of spatial conservation planning. In the present article, we advocate for systematic conservation planning to target resources for nature recovery and show how well-established systematic conservation planning frameworks can be developed appropriately, particularly by integrating models for forecasting ecological, social, and economic conditions with spatial prioritization methods designed to target nature recovery resources.

Imprecise language can weaken understanding of human–nature relationships. Widespread use of the term “exposure” to describe nature’s health impacts treats diverse experiences as uniform “doses” like chemical compounds. Through a narrative review of how “exposure” emerged and spread in nature–health research, we show that the term is relatively recent and has proliferated despite key limitations. “Exposure” accurately applies only in contexts where nature provides quantifiable doses (e.g., airborne microbes, biogenic compounds) that are consumed with relatively consistent effects. We identify three major problems with broader use of the term: benefits depending on attention or moderated by perception; benefits arising from behavioral affordances; and human–nature relationships being reciprocal. To improve precision, we offer a framework of ten measurement constructs, each with clear definitions, measurement approaches, and appropriate usage contexts. This shift in language will support both human wellbeing and planetary health by acknowledging our interdependence with nature.

Pathways to sustainability require a broader and fuller representation of the multiple values of nature in policy and practice. In this People and Nature special feature entitled ‘The Multiple Values of Nature’, researchers interpreted all three key words differently: multiple, values and nature. The articles also engaged variously with concepts, theory, practice and data. In the face of this diversity, some see a burgeoning field and others see a mess. In this editorial, we characterize the diversity of these contributions and consider whether the field is poised to become mainstream. Specifically, we ask what might be limiting its efforts to unsettle the dominance of economic valuation. Like the broader field, the articles engage little with theory, and only one paper engaged with a theory of value (the dominant ‘utility theory’, rejecting a component of it). All articles thus seemed dissatisfied or disengaged with existing theories of value; this suggests that popular theories of value cannot properly account for the diversity of ways that people value and relate to nature. Perhaps there is a fundamental lack in how we understand value in any context (not just nature). As this fledgling field matures, we argue that building theory is key. Specifically, there is a need to articulate a theory of value to accommodate the multiple values of nature, which relates the various concepts to empirics, and which serves as a foundation to guide practice. To facilitate this theory development, we outline a set of ways that a new theory of value would need to differ from the dominant economic (utility) theory of value in order to explain what is known about the multiple values of nature. Whether by illustrating and enlivening an existing alternative theory of value or by inspiring a new theory, perhaps this fledgling field of the multiple values of nature is poised to disrupt much broader understandings of what matters to people and why. Read the free Plain Language Summary for this article on the Journal blog.

A decade after our initial publication predicting that lightweight drones would revolutionize spatial ecology, drone technology has become firmly established in ecological studies. In the present article, we explore the key developments in ecological drone science since 2013, considering plant and animal ecology, imaging and nonimaging workflows, advances in data processing and operational ethics. Focusing on inexpensive, lightweight drones equipped with various sensors, we offer a critical evaluation of drone futures for ecologists, arguing that this could deliver opportunities for volumetric ecology to take flight. We discuss the potential future uses of drones in aerobiology and in understory and underground ecological studies and debate the future of multirobot cooperation from an ecological standpoint. We call on ecologists to engage critically with drone technology in this next phase of development.

AimSpatial sampling bias (SSB) is a feature of opportunistically sampled species records. Species distribution models (SDMs) built using these data (i.e. presence-background models) can produce biased predictions of suitability across geographic space, confounding species occurrence with the distribution of sampling effort. A wide range of SSB correction methods have been developed but simulations suggest effects on predictive performance are highly variable. Here, we aim to identify the SSB correction methods that have the highest likelihood of improving true predictive performance and evaluation strategies that provide a reliable indicator of model performance when independent test data are unavailable.LocationGlobal, simulation.Time PeriodCurrent, simulation.MethodsA meta-analysis was used to evaluate the performance of SSB correction methods in studies where there were direct comparisons between corrected and uncorrected SDMs. A simulation model was then developed to test evaluation strategies against a known truth using four common SSB correction methods.ResultsEffect sizes from published studies suggest some support for small positive effects of SSB correction on predictive performance when assessed using independent test data, but this was not evident using internal cross-validation and no single method stood out as consistently effective. Simulations support these findings and show that evaluation using internal test data was generally a poor indicator of the true effect of SSB correction. Methods that adjust models relative to a known driver of SSB produced the largest performance gains, but were also the most inconsistent.Main ConclusionsCorrecting SSB in presence-background SDMs without independent test data to evaluate the effect on model performance requires careful implementation. We recommend clearer documentation of SSB correction effects on SDMs, presenting results from models with and without correction, evaluating effects of different assumptions of SSB implementation on predictions, as well as greater efforts to collect independent test datasets to validate model predictions.

People have unique sets of direct sensory interactions with wild species, which change through their days, weeks, seasons, and lifetimes. Despite having important influences on their health and well-being and their attitudes towards nature, these personalized ecologies remain surprisingly little studied and are poorly understood. However, much can be inferred about personalized ecologies by considering them from first principles (largely macroecological), alongside insights from research into the design and effectiveness of biodiversity monitoring programmes, knowledge of how animals respond to people, and studies of human biology and demography. Here I first review how three major sets of drivers, opportunity, capability and motivation, shape people's personalized ecologies. Second, I then explore the implications of these mechanisms for how more passively and more actively practical improvements can be made in people's personalized ecologies. Particularly in light of the declines in the richness of these ecologies that are being experienced in much of the world (the so-called 'extinction of experience'), and the significant consequences, marked improvement in many people's interactions and experiences with nature may be key to the future of biodiversity. People have unique sets of direct sensory interactions with wild species, which change through their days, weeks, seasons and lifetimes. Despite having important influences on their health and wellbeing and their attitudes toward nature, these personalised ecologies remain surprisingly little studied and are poorly understood. However, much can be inferred about personalised ecologies by considering them from first principles (largely macroecological), alongside insights from research into the design and effectiveness of biodiversity monitoring programs, knowledge of how animals respond to people, and studies of human biology and demography. Here I first review how three major sets of drivers, opportunity, capability and motivation, shape people's personalised ecologies. Second, I then explore the implications of these mechanisms for how more passively and more actively practical improvements can be made in people's personalised ecologies. image

Earth Observation (EO) satellites have transformed understanding of the state and trajectories of Earth’s environment. Recent mushrooming of EO satellites and of resultant data that are stored, distributed and processed, often on the cloud, generate widespread environmental impacts that demand urgent consideration, particularly given that EO data outlive EO satellites.

Only a few diurnal animals, such as bumblebees, extend their activity into the time around sunrise and sunset when illumination levels are low. Low light impairs viewing conditions and increases sensory costs, but whether diurnal insects use low light as a cue to make behavioural decisions is uncertain. To investigate how they decide to initiate foraging at these times of day, we observed bumblebee nest-departure behaviours inside a flight net, under naturally changing light conditions. In brighter light bees did not attempt to return to the nest and departed with minimal delay, as expected. In low light the probability of non-departures increased, as a small number of bees attempted to return after spending time on the departure platform. Additionally, in lower illumination bees spent more time on the platform before flying away, up to 68 s. Our results suggest that bees may assess light conditions once outside the colony to inform the decision to depart. These findings give novel insights into how behavioural decisions are made at the start and the end of a foraging day in diurnal animals when the limits of their vision impose additional costs on foraging efficiency.