Networking nutrients: How nutrition determines the structure of ecological networks.

Nutrients can shape ecological interactions but remain poorly integrated into ecological networks. Concepts such as nutrient-specific foraging nevertheless have the potential to expose the mechanisms structuring complex ecological systems. Nutrients also present an opportunity to predict dynamic processes, such as interaction rewiring and extinction cascades, and increase the accuracy of network analyses. Here, we propose the concept of nutritional networks. By integrating nutritional data into ecological networks, we envisage significant advances to our understanding of ecological processes from individual to ecosystem scales. We show that networks can be constructed with nutritional data to illuminate how nutrients structure ecological interactions in natural systems through an empirical example. Throughout, we identify fundamental ecological hypotheses that can be explored in a nutritional network context, alongside methods for resolving those networks. Nutrients influence the structure and complexity of ecological networks through mechanistic processes and concepts including nutritional niche differentiation, functional responses, landscape diversity, ecological invasions and ecosystem robustness. Future research on ecological networks should consider nutrients when investigating the drivers of network structure and function.

Environmental DNA as an emerging tool in botanical research.

Over the past quarter century, environmental DNA (eDNA) has been ascendant as a tool to detect, measure, and monitor biodiversity (species and communities), as a means of elucidating biological interaction networks, and as a window into understanding past patterns of biodiversity. However, only recently has the potential of eDNA been realized in the botanical world. Here we synthesize the state of eDNA applications in botanical systems with emphases on aquatic, ancient, contemporary sediment, and airborne systems, and focusing on both single-species approaches and multispecies community metabarcoding. Further, we describe how abiotic and biotic factors, taxonomic resolution, primer choice, spatiotemporal scales, and relative abundance influence the utilization and interpretation of airborne eDNA results. Lastly, we explore several areas and opportunities for further development of eDNA tools for plants, advancing our knowledge and understanding of the efficacy, utility, and cost-effectiveness, and ultimately facilitating increased adoption of eDNA analyses in botanical systems.

Detecting host-parasitoid interactions in an invasive Lepidopteran using nested tagging DNA metabarcoding.

Determining the host-parasitoid interactions and parasitism rates for invasive species entering novel environments is an important first step in assessing potential routes for biocontrol and integrated pest management. Conventional insect rearing techniques followed by taxonomic identification are widely used to obtain such data, but this can be time-consuming and prone to biases. Here, we present a next-generation sequencing approach for use in ecological studies which allows for individual-level metadata tracking of large numbers of invertebrate samples through the use of hierarchically organised molecular identification tags. We demonstrate its utility using a sample data set examining both species identity and levels of parasitism in late larval stages of the oak processionary moth (Thaumetopoea processionea-Linn. 1758), an invasive species recently established in the United Kingdom. Overall, we find that there are two main species exploiting the late larval stages of oak processionary moth in the United Kingdom with the main parasitoid (Carcelia iliaca-Ratzeburg, 1840) parasitising 45.7% of caterpillars, while a rare secondary parasitoid (Compsilura concinnata-Meigen, 1824) was also detected in 0.4% of caterpillars. Using this approach on all life stages of the oak processionary moth may demonstrate additional parasitoid diversity. We discuss the wider potential of nested tagging DNA metabarcoding for constructing large, highly resolved species interaction networks.

Climate warming alters the structure of farmland tritrophic ecological networks and reduces crop yield.

It is unclear how sustained increases in temperature and changes in precipitation, as a result of climate change, will affect crops and their interactions with agricultural weeds, insect pests and predators, due to the difficulties in quantifying changes in such complex relationships. We simulated the combined effects of increasing temperature (by an average of 1.4°C over a growing season) and applying additional rainwater (10% of the monthly mean added weekly, 40% total) using a replicated, randomized block experiment within a wheat crop. We examined how this affected the structure of 24 quantitative replicate plant-aphid-parasitoid networks constructed using DNA-based methods. Simulated climate warming affected species richness, significantly altered consumer-resource asymmetries and reduced network complexity. Increased temperature induced an aphid outbreak, but the parasitism rates of aphids by parasitoid wasps remained unchanged. It also drove changes in the crop, altering in particular the phenology of the wheat as well as its quality (i.e., fewer, lighter seeds). We discuss the importance of considering the wider impacts of climate change on interacting species across trophic levels in agroecosystems.

The dark side of street lighting: impacts on moths and evidence for the disruption of nocturnal pollen transport.

Among drivers of environmental change, artificial light at night is relatively poorly understood, yet is increasing on a global scale. The community-level effects of existing street lights on moths and their biotic interactions have not previously been studied. Using a combination of sampling methods at matched-pairs of lit and unlit sites, we found significant effects of street lighting: moth abundance at ground level was halved at lit sites, species richness was >25% lower, and flight activity at the level of the light was 70% greater. Furthermore, we found that 23% of moths carried pollen of at least 28 plant species and that there was a consequent overall reduction in pollen transport at lit sites. These findings support the disruptive impact of lights on moth activity, which is one proposed mechanism driving moth declines, and suggest that street lighting potentially impacts upon pollination by nocturnal invertebrates. We highlight the importance of considering both direct and cascading impacts of artificial light.

Pollination by nocturnal Lepidoptera, and the effects of light pollution: a review.

1. Moths (Lepidoptera) are the major nocturnal pollinators of flowers. However, their importance and contribution to the provision of pollination ecosystem services may have been under-appreciated. Evidence was identified that moths are important pollinators of a diverse range of plant species in diverse ecosystems across the world. 2. Moth populations are known to be undergoing significant declines in several European countries. Among the potential drivers of this decline is increasing light pollution. The known and possible effects of artificial night lighting upon moths were reviewed, and suggest how artificial night lighting might in turn affect the provision of pollination by moths. The need for studies of the effects of artificial night lighting upon whole communities of moths was highlighted. 3. An ecological network approach is one valuable method to consider the effects of artificial night lighting upon the provision of pollination by moths, as it provides useful insights into ecosystem functioning and stability, and may help elucidate the indirect effects of artificial light upon communities of moths and the plants they pollinate. 4. It was concluded that nocturnal pollination is an ecosystem process that may potentially be disrupted by increasing light pollution, although the nature of this disruption remains to be tested.

Molecular analysis reveals high compartmentalization in aphid-primary parasitoid networks and low parasitoid sharing between crop and noncrop habitats.

The ecosystem service of insect pest regulation by natural enemies, such as primary parasitoids, may be enhanced by the presence of uncultivated, semi-natural habitats within agro-ecosystems, although quantifying such host-parasitoid interactions is difficult. Here, we use rRNA 16S gene sequencing to assess both the level of parasitism by Aphidiinae primary parasitoids and parasitoid identity on a large sample of aphids collected in cultivated and uncultivated agricultural habitats in Western France. We used these data to construct ecological networks to assess the level of compartmentalization between aphid and parasitoid food webs of cultivated and uncultivated habitats. We evaluated the extent to which uncultivated margins provided a resource for parasitoids shared between pest and nonpest aphids. We compared the observed quantitative ecological network described by our molecular approach to an empirical qualitative network based on aphid-parasitoid interactions from traditional rearing data found in the literature. We found that the molecular network was highly compartmentalized and that parasitoid sharing is relatively rare between aphids, especially between crop and noncrop compartments. Moreover, the few cases of putative shared generalist parasitoids were questionable and could be due to the lack of discrimination of cryptic species or from intraspecific host specialization. Our results suggest that apparent competition mediated by Aphidiinae parasitoids is probably rare in agricultural areas and that the contribution of field margins as a source of these biocontrol agents is much more limited than expected. Further large-scale (spatial and temporal) studies on other crops and noncrop habitats are needed to confirm this.

The robustness of a network of ecological networks to habitat loss.

There have been considerable advances in our understanding of the tolerance of species interaction networks to sequential extinctions of plants and animals. However, communities of species exist in a mosaic of habitats, and the vulnerability of habitats to anthropogenic change varies. Here, we model the cascading effects of habitat loss, driven by plant extinctions, on the robustness of multiple animal groups. Our network is constructed from empirical observations of 11 animal groups in 12 habitats on farmland. We simulated sequential habitat removal scenarios: randomly; according to prior information; and with a genetic algorithm to identify best- and worst-case permutations of habitat loss. We identified two semi-natural habitats (waste ground and hedgerows together comprising < 5% of the total area of the farm) as disproportionately important to the integrity of the overall network. Our approach provides a new tool for network ecologists and for directing the management and restoration of multiple-habitat sites.

Mitigating the impacts of street lighting on biodiversity and ecosystem functioning.

Street lights are not only a major source of direct light pollution emissions, but stock has been transitioning to light-emitting diode (LED) technology in many parts of the world, resulting in increases in the blue part of the visible spectrum that is more harmful to biodiversity and human health. But LEDs can be modified more easily than conventional sodium lamps by adjusting their intensity, spectral output and other features of street light systems. In this Opinion piece, I provide an updated overview of street light mitigation strategies and contend that research in this area has been slow. I show how experimental lighting rigs that mimic real street lights can be used for mitigation testing, since invertebrate behaviour, abundances and interactions can respond quickly and measurably. I demonstrate how advances in network ecology that use species interaction data can provide much-needed assessments of the impacts of street lights on biodiversity and ecosystem functioning, and ultimately provide new tools and metrics for biomonitoring. I acknowledge the limitations of measuring local, short-term responses of biodiversity and identify promising avenues for collaborating with industry and government agencies in new or existing road lighting schemes, to minimize the negative long-term impacts at marginal cost. This article is part of the theme issue 'Light pollution in complex ecological systems'.

Light pollution in complex ecological systems.

Light pollution has emerged as a burgeoning area of scientific interest, receiving increasing attention in recent years. The resulting body of literature has revealed a diverse array of species-specific and context-dependent responses to artificial light at night (ALAN). Because predicting and generalizing community-level effects is difficult, our current comprehension of the ecological impacts of light pollution on complex ecological systems remains notably limited. It is critical to better understand ALAN's effects at higher levels of ecological organization in order to comprehend and mitigate the repercussions of ALAN on ecosystem functioning and stability amidst ongoing global change. This theme issue seeks to explore the effects of light pollution on complex ecological systems, by bridging various realms and scaling up from individual processes and functions to communities and networks. Through this integrated approach, this collection aims to shed light on the intricate interplay between light pollution, ecological dynamics and humans in a world increasingly impacted by anthropogenic lighting. This article is part of the theme issue 'Light pollution in complex ecological systems'.

The predator problem and PCR primers in molecular dietary analysis: Swamped or silenced; depth or breadth?

Dietary metabarcoding has vastly improved our ability to analyse the diets of animals, but it is hampered by a plethora of technical limitations including potentially reduced data output due to the disproportionate amplification of the DNA of the focal predator, here termed "the predator problem". We review the various methods commonly used to overcome this problem, from deeper sequencing to exclusion of predator DNA during PCR, and how they may interfere with increasingly common multipredator-taxon studies. We suggest that multiprimer approaches with an emphasis on achieving both depth and breadth of prey detections may overcome the issue to some extent, although multitaxon studies require further consideration, as highlighted by an empirical example. We also review several alternative methods for reducing the prevalence of predator DNA that are conceptually promising but require additional empirical examination. The predator problem is a key constraint on molecular dietary analyses but, through this synthesis, we hope to guide researchers in overcoming this in an effective and pragmatic way.

How artificial light at night may rewire ecological networks: concepts and models.

Artificial light at night (ALAN) is eroding natural light cycles and thereby changing species distributions and activity patterns. Yet little is known about how ecological interaction networks respond to this global change driver. Here, we assess the scientific basis of the current understanding of community-wide ALAN impacts. Based on current knowledge, we conceptualize and review four major pathways by which ALAN may affect ecological interaction networks by (i) impacting primary production, (ii) acting as an environmental filter affecting species survival, (iii) driving the movement and distribution of species, and (iv) changing functional roles and niches by affecting activity patterns. Using an allometric-trophic network model, we then test how a shift in temporal activity patterns for diurnal, nocturnal and crepuscular species impacts food web stability. The results indicate that diel niche shifts can severely impact community persistence by altering the temporal overlap between species, which leads to changes in interaction strengths and rewiring of networks. ALAN can thereby lead to biodiversity loss through the homogenization of temporal niches. This integrative framework aims to advance a predictive understanding of community-level and ecological-network consequences of ALAN and their cascading effects on ecosystem functioning. This article is part of the theme issue 'Light pollution in complex ecological systems'.

Experimental Climate Warming Reduces Floral Resources and Alters Insect Visitation and Wildflower Seed Set in a Cereal Agro-Ecosystem.

Declines in pollinating insects and wildflowers have been well documented in recent years. Climate change is an emerging threat to insect pollinators and their food plants, but little is known about how whole communities of interacting species will be affected or what impacts there may be on ecosystem services such as pollination. Using a novel open-air field experiment, we simulated an increase in temperature of 1.5°C and rainwater of 40% for two growing seasons to investigate how climate change may impact several within-field features of temperate arable agro-ecosystems: (1) wildflower floral resources; (2) insect visitation; (3) flower-visitor network structure; and (4) wildflower seed set. Experimental warming reduced total floral abundance by nearly 40%, and nectar volumes by over 60% for two species. The species richness of the visiting insects and flowering plants (dominated by annuals) were unaffected by warming, and while a negative impact on visitor abundance was observed, this effect appears to have been mediated by different community compositions between years. Warming increased the frequency of visits to flowers and the complexity of the flower-visitor interaction networks. Wildflower seed set was reduced in terms of seed number and/or weight in four of the five species examined. Increased rainwater did not ameliorate any of these effects. These findings demonstrate the adverse impacts that climate warming might have on annual wildflowers in arable systems and the pollinating insects that feed on them, highlighting several mechanisms that could drive changes in community composition over time. The results also reveal how cascading impacts within communities can accumulate to affect ecosystem functioning.

Birds bias offspring sex ratio in response to livestock grazing.

Livestock grazing, which has a large influence on habitat structure, is associated with the widespread decline of various bird species across the world, yet there are few experimental studies that investigate how grazing pressure influences avian reproduction. We manipulated grazing pressure using a replicated field experiment, and found that the offspring sex ratio of a common upland passerine, the meadow pipit Anthus pratensis, varied significantly between grazing treatments. The proportion of sons was lowest in the ungrazed and intensively grazed treatments and highest in treatments grazed at low intensity (by sheep, or a mixture of sheep and cattle). This response was not related to maternal body condition. These results demonstrate the sensitivity of avian reproductive biology to variation in local conditions, and support growing evidence that too much grazing, or the complete removal of livestock from upland areas, is detrimental for common breeding birds.

A dearth of data: fitting parasitoids into ecological networks.

Studying parasitoids can provide insights into global diversity estimates, climate change impacts, and agroecosystem service provision. However, this potential remains largely untapped due to a lack of data on how parasitoids interact with other organisms. Ecological networks are a useful tool for studying and exploiting the impacts of parasitoids, but their construction is hindered by the magnitude of undescribed parasitoid species, a sparse knowledge of host ranges, and an under-representation of parasitoids within DNA-barcode databases (we estimate <5% have a barcode). Here, we advocate the use of DNA metabarcoding to construct the host-parasitoid component of multilayer networks. While the incorporation of parasitoids into network-based analyses has far ranging applications, we focus on its potential for assessing ecosystem service provision within agroecosystems.

Street lighting has detrimental impacts on local insect populations.

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.

Molecular ecology as a tool for understanding pollination and other plant-insect interactions.

Advances in molecular ecology offer unprecedented opportunities to understand the ecology and evolution of insects, the complex ways in which they interact and their role in ecosystem functioning. Rapidly developing DNA sequencing technologies are resolving previously intractable questions in taxonomic and functional biodiversity and provide significant potential to determine formerly difficult to observe plant-insect interactions. We provide an overview of the state-of-the-art and critically appraise the range of molecular approaches currently available for the study of insect pollination, host-parasitoid interactions and/or wider food-web studies. Species-interaction data are increasingly being incorporated into ecological network analyses. DNA metabarcoding offers opportunities to scale-up efforts to create large, highly resolved, phylogenetically structured networks within an exciting framework to study pressing questions in ecology and evolution.

Adaptive Networks for Restoration Ecology.

The urgent need to restore biodiversity and ecosystem functioning challenges ecology as a predictive science. Restoration ecology would benefit from evolutionary principles embedded within a framework that combines adaptive network models and the phylogenetic structure of ecological interactions. Adaptive network models capture feedbacks between trait evolution, species abundances, and interactions to explain resilience and functional diversity within communities. Phylogenetically-structured network data, increasingly available via next-generation sequencing, inform constraints affecting interaction rewiring. Combined, these approaches can predict eco-evolutionary changes triggered by community manipulation practices, such as translocations and eradications of invasive species. We discuss theoretical and methodological opportunities to bridge network models and data from restoration projects and propose how this can be applied to the functional restoration of ecological interactions.