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Tools to predict pollinator activity at regional scales generally rely on land cover maps, combined with human-inferred mechanistic rules and/or expert knowledge. Recently, Giménez-García et al. (2023) showed that, using large pollinator datasets, different environmental variables, and machine learning models, those predictions can be enhanced but at the cost of losing model interpretability. Here, we complement this work by exploring the potential of using advanced machine learning techniques to directly infer wild-bee visitation rates across different biomes only from land cover maps and available pollinator data while maintaining a mechanistic interpretation. In particular, we assess the ability of convolutional neural networks (CNNs), which are deep learning models, to infer mechanistic rules able to predict pollinator habitat use. At a global scale, our CNNs achieved a rank correlation coefficient of 0.44 between predictions and observations of pollinator visitation rates, doubling that of the previous human-inferred mechanistic models presented in Giménez-García et al. (2023) (0.17). Most interestingly, we show that the predictions depend on both landscape composition and configuration variables, with prediction rules being more complex than those of traditional mechanistic processes. We also demonstrate how CNNs can improve the predictions of our previous data-driven models that did not use land cover maps by creating a new model that combined the predictions of our CNN with those of our best regression model based on environmental variables, a Bayesian ridge regressor. This new ensemble model improved the overall rank correlation from 0.56 to 0.64.

Ecological intensification has been embraced with great interest by the academic sector but is still rarely taken up by farmers because monitoring the state of different ecological functions is not straightforward. Modelling tools can represent a more accessible alternative of measuring ecological functions, which could help promote their use amongst farmers and other decision-makers. In the case of crop pollination, modelling has traditionally followed either a mechanistic or a data-driven approach. Mechanistic models simulate the habitat preferences and foraging behaviour of pollinators, while data-driven models associate georeferenced variables with real observations. Here, we test these two approaches to predict pollination supply and validate these predictions using data from a newly released global dataset on pollinator visitation rates to different crops. We use one of the most extensively used models for the mechanistic approach, while for the data-driven approach, we select from among a comprehensive set of state-of-the-art machine-learning models. Moreover, we explore a mixed approach, where data-derived inputs, rather than expert assessment, inform the mechanistic model. We find that, at a global scale, machine-learning models work best, offering a rank correlation coefficient between predictions and observations of pollinator visitation rates of 0.56. In turn, the mechanistic model works moderately well at a global scale for wild bees other than bumblebees. Biomes characterized by temperate or Mediterranean forests show a better agreement between mechanistic model predictions and observations, probably due to more comprehensive ecological knowledge and therefore better parameterization of input variables for these biomes. This study highlights the challenges of transferring input variables across multiple biomes, as expected given the different composition of species in different biomes. Our results provide clear guidance on which pollination supply models perform best at different spatial scales – the first step towards bridging the stakeholder–academia gap in modelling ecosystem service delivery under ecological intensification.

Ecosystem functions such as seed production are the result of a complex interplay between competitive plant–plant interactions and mutualistic pollinator–plant interactions. In this interplay, spatial plant aggregation could work in two different directions: it could increase hetero- and conspecific competition, thus reducing seed production; but it could also attract pollinators, increasing plant fitness. To shed light on how plant spatial arrangement modulates this balance, we conducted a field study in a Mediterranean annual grassland with three focal plant species with different phenology, Chamaemelum fuscatum (early phenology), Leontodon maroccanus (middle phenology) and Pulicaria paludosa (late phenology), and a diverse guild of pollinators (flies, bees, beetles and butterflies). All three species showed spatial aggregation of conspecific individuals. Additionally, we found that the two mechanisms were working simultaneously: crowded neighborhoods reduced individual seed production via plant–plant competition, but they also made individual plants more attractive for some pollinator guilds, increasing visitation rates and plant fitness. The balance between these two forces varied depending on the focal species and the spatial scale considered. Therefore, our results indicate that mutualistic interactions do not always effectively compensate for competitive interactions in situations of spatial aggregation of flowering plants, at least in our study system. We highlight the importance of explicitly considering the spatial structure at different spatial scales of multitrophic interactions to better understand individual plant fitness and community dynamics.

La inmensa mayoría de los estudios científicos no son reproducibles: resulta muy difícil, si no imposible, trazar todo el proceso de análisis y obtención de resultados a partir de un conjunto de datos – incluso tratándose de los mismos investigadores. La trazabilidad y reproducibilidad de los resultados son sin embargo condiciones inherentes a la ciencia de calidad, y un requisito cada vez más frecuente por parte de revistas y organismos financia- dores de la investigación. Los estudios científicos reproducibles incluyen código informático capaz de recrear todos los resultados a partir de los datos originales. De esta manera el proceso de análisis queda perfectamente registrado, se reduce drásticamente el riesgo de errores, y se facilita la reutilización de código para otros análisis. Pero la ciencia reproducible no sólo acelera el progreso científico sino que también reporta múltiples beneficios para el investigador como el ahorro de tiempo y esfuerzo, o el incremento de la calidad e impacto de sus publicaciones. En este artículo explicamos en qué consiste la reproducibilidad, por qué es necesaria en ciencia, y cómo podemos hacer ciencia reproducible. Presentamos una serie de recomendaciones y herramientas para el manejo y análisis de datos, control de versiones de archivos, organización de ficheros y manejo de programas informáticos que nos permiten desarrollar flujos de trabajo reproducibles en el contexto actual de la ecología.

Pollination is a crucial ecosystem service, yet pollinator species diversity is declining as a result of factors such as climate change, habitat loss and agricultural intensification. While previous studies have often examined the extreme scenario of complete pollinator removal, showing negative impacts on plant reproductive success, we take a more realistic approach by focusing on the effects of decreasing pollinator diversity. Our global meta-analysis reveals a notable negative impact of reduced pollinator species diversity on plant reproductive success measures, such as seed set, fruit set and fruit weight. Notably, this effect varies across plant families, impacting both self-incompatible and self-compatible species. We also find that wild plant species suffer more than cultivated ones. Furthermore, the loss of invertebrate, nocturnal and wild pollinators has a more substantial impact than the loss of vertebrate, diurnal or managed pollinators. Overall, our findings consistently underscore the positive role of biodiversity in maintaining ecosystem functioning, highlighting the urgency of mitigating factors that lead to the decline in pollinator species diversity., Competing Interests: Competing interests: The authors declare no competing interests., (© 2024. The Author(s), under exclusive licence to Springer Nature Limited.)

With many species interacting in nature, determining which interactions describe community dynamics is nontrivial. By applying a computational modeling approach to an extensive field survey, we assessed the importance of interactions from plants (both inter- and intra-specific), pollinators and insect herbivores on plant performance (i.e., viable seed production). We compared the inclusion of interaction effects as aggregate guild-level terms versus terms specific to taxonomic groups. We found that a continuum from positive to negative interactions, containing mostly guild-level effects and a few strong taxonomic-specific effects, was sufficient to describe plant performance. While interactions with herbivores and intraspecific plants varied from weakly negative to weakly positive, heterospecific plants mainly promoted competition and pollinators facilitated plants. The consistency of these empirical findings over 3 years suggests that including the guild-level effects and a few taxonomic-specific groups rather than all pairwise and high-order interactions, can be sufficient for accurately describing species variation in plant performance across natural communities., (© 2025 The Author(s). Ecology Letters published by John Wiley & Sons Ltd.)

Food security is threatened by climate change, with heat and drought being the main stresses affecting crop physiology and ecosystem services, such as plant-pollinator interactions. We hypothesize that tracking and ranking pollinators' preferences for flowers under environmental pressure could be used as a marker of plant quality for agricultural breeding to increase crop stress tolerance. Despite increasing relevance of flowers as the most stress sensitive organs, phenotyping platforms aim at identifying traits of resilience by assessing the plant physiological status through remote sensing-assisted vegetative indexes, but find strong bottlenecks in quantifying flower traits and in accurate genotype-to-phenotype prediction. However, as the transport of photoassimilates from leaves (sources) to flowers (sinks) is reduced in low-resilient plants, flowers are better indicators than leaves of plant well-being. Indeed, the chemical composition and amount of pollen and nectar that flowers produce, which ultimately serve as food resources for pollinators, change in response to environmental cues. Therefore, pollinators' preferences could be used as a measure of functional source-to-sink relationships for breeding decisions. To achieve this challenging goal, we propose to develop a pollinator-assisted phenotyping and selection platform for automated quantification of Genotype × Environment × Pollinator interactions through an insect geo-positioning system. Pollinator-assisted selection can be validated by metabolic, transcriptomic, and ionomic traits, and mapping of candidate genes, linking floral and leaf traits, pollinator preferences, plant resilience, and crop productivity. This radical new approach can change the current paradigm of plant phenotyping and find new paths for crop redomestication and breeding assisted by ecological decisions., (© 2024 The Authors. The Plant Journal published by Society for Experimental Biology and John Wiley & Sons Ltd.)

Integrating biodiversity conservation into agriculture is a pressing challenge promoted by conservationists. Although biodiversity can also provide important benefits to farmers, the adoption of biodiversity-enhancing measures is lagging behind the scientific evidence. This may partially be related to the way scientists position themselves. If scientists do not convincingly communicate about the implications of their evidence, other interested stakeholders will drive the conversations. To increase societal impact, scientists must understand the complex communication environment and take an informed and strategic position. We describe the prevailing conservation and farming narratives, highlighting how the term 'biodiversity' can be used to start dialogues between parties with conflicting demands and exemplifying how scientists can build effective narratives., Competing Interests: Declaration of interests No interests are declared., (Copyright © 2024 Elsevier Ltd. All rights reserved.)

AbstractEcologists increasingly recognize that interactions between two species can be affected by the density of a third species. How these higher-order interactions (HOIs) affect species persistence remains poorly understood. To explore the effect of HOIs stemming from multiple trophic layers on a plant community composition, we experimentally built a mesocosm with three plants and three pollinator species arranged in a fully nested and modified network structure. We estimated pairwise interactions among plants and between plants and pollinators, as well as HOIs initiated by a plant or a pollinator affecting plant species pairs. Using a structuralist approach, we evaluated the consequences of the statistically supported HOIs on the persistence probability of each of the three competing plant species and their combinations. HOIs substantially redistribute the strength and sign of pairwise interactions between plant species, promoting the opportunities for multispecies communities to persist compared with a non-HOI scenario. However, the physical elimination of a plant-pollinator link in the modified network structure promotes changes in per capita pairwise interactions and HOIs, resulting in a single-species community. Our study provides empirical evidence of the joint importance of HOIs and network structure in determining species persistence within diverse communities.

Despite clear evidence that some pollinator populations are declining, our ability to predict pollinator communities prone to collapse or species at risk of local extinction is remarkably poor. Here, we develop a model grounded in the structuralist approach that allows us to draw sound predictions regarding the temporal persistence of species in mutualistic networks. Using high-resolution data from a six-year study following 12 independent plant-pollinator communities, we confirm that pollinator species with more persistent populations in the field are theoretically predicted to tolerate a larger range of environmental changes. Persistent communities are not necessarily more diverse, but are generally located in larger habitat patches, and present a distinctive combination of generalist and specialist species resulting in a more nested structure, as predicted by previous theoretical work. Hence, pollinator interactions directly inform about their ability to persist, opening the door to use theoretically informed models to predict species' fate within the ongoing global change., (© 2024. The Author(s), under exclusive licence to Springer Nature Limited.)

The rapid conversion of natural habitats to anthropogenic landscapes is threatening insect pollinators worldwide, raising concern regarding the negative consequences on their fundamental role as plant pollinators. However, not all pollinators are negatively affected by habitat conversion, as certain species find appropriate resources in anthropogenic landscapes to persist and proliferate. The reason why some species tolerate anthropogenic environments while most find them inhospitable remains poorly understood. The cognitive buffer hypothesis, widely supported in vertebrates but untested in insects, offers a potential explanation. This theory suggests that species with larger brains have enhanced behavioural plasticity, enabling them to confront and adapt to novel challenges. To investigate this hypothesis in insects, we measured brain size for 89 bee species, and evaluated their association with the degree of habitat occupancy. Our analyses revealed that bee species mainly found in urban habitats had larger brains relative to their body size than those that tend to occur in forested or agricultural habitats. Additionally, urban bees exhibited larger body sizes and, consequently, larger absolute brain sizes. Our results provide the first empirical support for the cognitive buffer hypothesis in invertebrates, suggesting that a large brain in bees could confer behavioural advantages to tolerate urban environments.

A universal feature of ecological systems is that species do not interact with others with the same sign and strength. Yet, the consequences of this asymmetry in biotic interactions for the short- and long-term persistence of individual species and entire communities remains unclear. Here, we develop a set of metrics to evaluate how asymmetric interactions among species translate to asymmetries in their individual vulnerability to extinction under changing environmental conditions. These metrics, which solve previous limitations of how to independently quantify the size from the shape of the so-called feasibility domain, provide rigorous advances to understand simultaneously why some species and communities present more opportunities to persist than others. We further demonstrate that our shape-related metrics are useful to predict short-term changes in species' relative abundances during 7 years in a Mediterranean grassland. Our approach is designed to be applied to any ecological system regardless of the number of species and type of interactions. With it, we show that is possible to obtain both mechanistic and predictive information on ecological persistence for individual species and entire communities, paving the way for a stronger integration of theoretical and empirical research., (© 2023 John Wiley & Sons Ltd.)

Agricultural expansion and intensification have boosted global food production but have come at the cost of environmental degradation and biodiversity loss. Biodiversity-friendly farming that boosts ecosystem services, such as pollination and natural pest control, is widely being advocated to maintain and improve agricultural productivity while safeguarding biodiversity. A vast body of evidence showing the agronomic benefits of enhanced ecosystem service delivery represent important incentives to adopt practices enhancing biodiversity. However, the costs of biodiversity-friendly management are rarely taken into account and may represent a major barrier impeding uptake by farmers. Whether and how biodiversity conservation, ecosystem service delivery, and farm profit can go hand in hand is unknown. Here, we quantify the ecological, agronomic, and net economic benefits of biodiversity-friendly farming in an intensive grassland-sunflower system in Southwest France. We found that reducing land-use intensity on agricultural grasslands drastically enhances flower availability and wild bee diversity, including rare species. Biodiversity-friendly management on grasslands furthermore resulted in an up to 17% higher revenue on neighboring sunflower fields through positive effects on pollination service delivery. However, the opportunity costs of reduced grassland forage yields consistently exceeded the economic benefits of enhanced sunflower pollination. Our results highlight that profitability is often a key constraint hampering adoption of biodiversity-based farming and uptake critically depends on society's willingness to pay for associated delivery of public goods such as biodiversity.

Ecological processes leave distinct structural imprints on the species interactions that shape the topology of animal-plant mutualistic networks. Detecting how direct and indirect interactions between animals and plants are organised is not trivial since they go beyond pairwise interactions, but may get blurred when considering global network descriptors. Recent work has shown that the meso-scale, the intermediate level of network complexity between the species and the global network, can capture this important information. The meso-scale describes network subgraphs representing patterns of direct and indirect interactions between a small number of species, and when these network subgraphs differ statistically from a benchmark, they are often referred to as 'network motifs'. Although motifs can capture relevant ecological information of species interactions, they remain overlooked in natural plant-pollinator networks. By exploring 60 empirical plant-pollinator networks from 18 different studies with wide geographical coverage, we show that some network subgraphs are consistently under- or over-represented, suggesting the presence of worldwide network motifs in plant-pollinator networks. In addition, we found a higher proportion of densely connected network subgraphs that, based on previous findings, could reflect that species relative abundances are the main driver shaping the structure of the meso-scale on plant-pollinator communities. Moreover, we found that distinct subgraph positions describing species ecological roles (e.g. generalisation and number of indirect interactions) are occupied by different groups of animal and plant species representing their main life-history strategies (i.e. functional groups). For instance, we found that the functional group of 'bees' was over-represented in subgraph positions with a lower number of indirect interactions in contrast to the rest of floral visitors groups. Finally, we show that the observed functional group combinations within a subgraph cannot be retrieved from their expected probabilities (i.e. joint probability distributions), indicating that plant and floral visitor associations within subgraphs are not random either. Our results highlight the presence of common network motifs in plant-pollinator communities that are formed by a non-random association of plants and floral visitors functional groups., (© 2023 The Authors. Journal of Animal Ecology © 2023 British Ecological Society.)

While wild pollinators play a key role in global food production, their assessment is currently missing from the most commonly used environmental impact assessment method, Life Cycle Assessment (LCA). This is mainly due to constraints in data availability and compatibility with LCA inventories. To target this gap, relative pollinator abundance estimates were obtained with the use of a Delphi assessment, during which 25 experts, covering 16 nationalities and 45 countries of expertise, provided scores for low, typical, and high expected abundance associated with 24 land use categories. Based on these estimates, this study presents a set of globally generic characterization factors (CFs) that allows translating land use into relative impacts to wild pollinator abundance. The associated uncertainty of the CFs is presented along with an illustrative case to demonstrate the applicability in LCA studies. The CFs based on estimates that reached consensus during the Delphi assessment are recommended as readily applicable and allow key differences among land use types to be distinguished. The resulting CFs are proposed as the first step for incorporating pollinator impacts in LCA studies, exemplifying the use of expert elicitation methods as a useful tool to fill data gaps that constrain the characterization of key environmental impacts.

Reversing biodiversity declines requires a better understanding of organismal mobility, as movement processes dictate the scale at which species interact with the environment. Previous studies have demonstrated that species foraging ranges, and therefore, habitat use increases with body size. Yet, foraging ranges are also affected by other life-history traits, such as sociality, which influence the need of and ability to detect resources. We evaluated the effect of body size and sociality on potential and realized foraging ranges using a compiled dataset of 383 measurements for 81 bee species. Potential ranges were larger than realized ranges and increased more steeply with body size. Highly eusocial species had larger realized foraging ranges than primitively eusocial or solitary taxa. We contend that potential ranges describe species movement capabilities, whereas realized ranges depict how foraging movements result from interactions between species traits and environmental conditions. Furthermore, the complex communication strategies and large colony sizes in highly eusocial species may facilitate foraging over wider areas in response to resource depletion. Our findings should contribute to a greater understanding of landscape ecology and conservation, as traits that influence movement mediate species vulnerability to habitat loss and fragmentation., (© 2022 The Authors. Ecology published by Wiley Periodicals LLC on behalf of The Ecological Society of America.)

Pollination plays a central role in both crop production and maintaining biodiversity. However, habitat loss, pesticides, invasive species and larger environmental fluctuations are contributing to a dramatic decline of pollinators worldwide. Different management solutions require knowledge of how ecological communities will respond following interventions. Yet, anticipating the response of these systems to interventions remains extremely challenging due to the unpredictable nature of ecological communities, whose nonlinear behaviour depends on the specific details of species interactions and the various unknown or unmeasured confounding factors. Here, we propose that this knowledge can be derived by following a probabilistic systems analysis rooted on non-parametric causal inference. The main outcome of this analysis is to estimate the extent to which a hypothesized cause can increase or decrease the probability that a given effect happens without making assumptions about the form of the cause-effect relationship. We discuss a road map for how this analysis can be accomplished with the aim of increasing our system-level causative knowledge of natural communities. This article is part of the theme issue 'Natural processes influencing pollinator health: from chemistry to landscapes'.

Seventy five percent of the world's food crops benefit from insect pollination. Hence, there has been increased interest in how global change drivers impact this critical ecosystem service. Because standardized data on crop pollination are rarely available, we are limited in our capacity to understand the variation in pollination benefits to crop yield, as well as to anticipate changes in this service, develop predictions, and inform management actions. Here, we present CropPol, a dynamic, open, and global database on crop pollination. It contains measurements recorded from 202 crop studies, covering 3,394 field observations, 2,552 yield measurements (i.e., berry mass, number of fruits, and fruit density [kg/ha], among others), and 47,752 insect records from 48 commercial crops distributed around the globe. CropPol comprises 32 of the 87 leading global crops and commodities that are pollinator dependent. Malus domestica is the most represented crop (32 studies), followed by Brassica napus (22 studies), Vaccinium corymbosum (13 studies), and Citrullus lanatus (12 studies). The most abundant pollinator guilds recorded are honey bees (34.22% counts), bumblebees (19.19%), flies other than Syrphidae and Bombyliidae (13.18%), other wild bees (13.13%), beetles (10.97%), Syrphidae (4.87%), and Bombyliidae (0.05%). Locations comprise 34 countries distributed among Europe (76 studies), North America (60), Latin America and the Caribbean (29), Asia (20), Oceania (10), and Africa (7). Sampling spans three decades and is concentrated on 2001-2005 (21 studies), 2006-2010 (40), 2011-2015 (88), and 2016-2020 (50). This is the most comprehensive open global data set on measurements of crop flower visitors, crop pollinators and pollination to date, and we encourage researchers to add more datasets to this database in the future. This data set is released for non-commercial use only. Credits should be given to this paper (i.e., proper citation), and the products generated with this database should be shared under the same license terms (CC BY-NC-SA)., (© 2021 The Ecological Society of America.)

Prediction is one of the last frontiers in ecology. Indeed, predicting fine-scale species composition in natural systems is a complex challenge as multiple abiotic and biotic processes operate simultaneously to determine local species abundances. On the one hand, species intrinsic performance and their tolerance limits to different abiotic pressures modulate species abundances. On the other hand, there is growing recognition that species interactions play an equally important role in limiting or promoting such abundances within ecological communities. Here, we present a joint effort between ecologists and data scientists to use data-driven models to predict species abundances using reasonably easy to obtain data. We propose a sequential data-driven modeling approach that in a first step predicts the potential species abundances based on abiotic variables, and in a second step uses these predictions to model the realized abundances once accounting for species competition. Using a curated data set over five years we predict fine-scale species abundances in a highly diverse annual plant community. Our models show a remarkable spatial predictive accuracy using only easy-to-measure variables in the field, yet such predictive power is lost when temporal dynamics are taken into account. This result suggests that predicting future abundances requires longer time series analysis to capture enough variability. In addition, we show that these data-driven models can also suggest how to improve mechanistic models by adding missing variables that affect species performance such as particular soil conditions (e.g. carbonate availability in our case). Robust models for predicting fine-scale species composition informed by the mechanistic understanding of the underlying abiotic and biotic processes can be a pivotal tool for conservation, especially given the human-induced rapid environmental changes we are experiencing. This objective can be achieved by promoting the knowledge gained with classic modelling approaches in ecology and recently developed data-driven models., Competing Interests: The authors have declared that no competing interests exist.

Invasive species can reach high abundances and dominate native environments. One of the most impressive examples of ecological invasions is the spread of the African subspecies of the honey bee throughout the Americas, starting from its introduction in a single locality in Brazil. The invasive honey bee is expected to more negatively impact bee community abundance and diversity than native dominant species, but this has not been tested previously. We developed a comprehensive and systematic bee sampling scheme, using a protocol deploying 11,520 pan traps across regions and crops for three years in Brazil. We found that invasive honey bees are now the single most dominant bee species. Such dominance has not only negative consequences for abundance and species richness of native bees but also for overall bee abundance (i.e., strong "numerical" effects of honey bees). Contrary to expectations, honey bees did not have stronger negative impacts than other native bees achieving similar levels of dominance (i.e., lack of negative "identity" effects of honey bees). These effects were markedly consistent across crop species, seasons and years, and were independent from land-use effects. Dominance could be a proxy of bee community degradation and more generally of the severity of ecological invasions., (© 2021 by the Ecological Society of America.)

Solitary bees comprise around 90% of bee species, playing an essential role in both wild and crop plant pollination. Bee populations are jeopardized by different global change pressures such as climate change and landscape transformation. However, the interactive effects of global change components have been little explored, especially for solitary bees. We conducted a factorial experiment using artificial nest-traps to analyse the combined effect of climate warming and landscape transformation on Osmia bicornis reproduction and offspring body size. The number of bee cocoons increased with temperature and flower abundance in the landscape. However, the sex ratio was biased towards males with warming, especially at low flower abundances. Male body size increased with temperature. Conversely, female body sizes showed strong interactive responses, increasing in size with high flower abundance in the landscape, but only at low temperatures. The abortion rate of larvae and parasitization were not significantly affected by neither flower abundance nor temperature. Because the body size of females in O. bicornis is key for the next generation's progeny success, our results indicate that the simultaneous exposure to a shortage of floral resources and high temperatures may have adverse direct fitness effects., (© 2021 British Ecological Society.)

The increase of species richness with area is a universal phenomenon on Earth. However, this observation contrasts with our poor understanding of how these species-area relationships (SARs) emerge from the collective effects of area, spatial heterogeneity, and local interactions. By combining a structuralist approach with five years of empirical observations in a highly-diverse Mediterranean grassland, we show that spatial heterogeneity plays a little role in the accumulation of species richness with area in our system. Instead, as we increase the sampled area more species combinations are realized, and they coexist mainly due to direct pairwise interactions rather than by changes in single-species dominance or by indirect interactions. We also identify a small set of transient species with small population sizes that are consistently found across spatial scales. These findings empirically support the importance of the architecture of species interactions together with stochastic events for driving coexistence- and species-area relationships., (© 2021. The Author(s).)

Ongoing environmental changes are affecting physical, chemical and biological soil components. Evidence of impacts of soil changes on pollinators' and seed dispersers' behaviour, fitness and density is scarce, but growing. Here, we reviewed information on such impacts and on a number of mechanisms that may explain its propagation, taking into account the full range of resources required by the large and diverse number of species of these two important functional groups. We show that while there is substantial evidence on the effects of soil nitrogen enrichment and changes in soil water content on the quality and quantity of floral and fruit resources, little is known on the effects of changes of other soil properties (e.g. soil pH, soil structure, other nutrients). Also, the few studies showing correlations between soil changes and pollinator and seed disperser foraging behaviour or fitness do not clearly identify the mechanisms that explain such correlation. Finally, most studies (including those with nitrogen and water) are local and limited to a small number of species, and it remains unclear how variable such effects are across time and geographical regions, and the strength of interactive effects between soil properties. Increasing research on this topic, taking into consideration how impacts propagate through species interaction networks, will provide essential information to predict impacts of ongoing environmental changes and help guide conservation plans that aim to minimize impacts on ecosystem functioning. This article is part of the theme issue 'The role of soils in delivering Nature's Contributions to People'.

When it comes to the brain, bigger is generally considered better in terms of cognitive performance. While this notion is supported by studies of birds and primates showing that larger brains improve learning capacity, similar evidence is surprisingly lacking for invertebrates. Although the brain of invertebrates is smaller and simpler than that of vertebrates, recent work in insects has revealed enormous variation in size across species. Here, we ask whether bee species that have larger brains also have higher learning abilities. We conducted an experiment in which field-collected individuals had to associate an unconditioned stimulus (sucrose) with a conditioned stimulus (coloured strip). We found that most species can learn to associate a colour with a reward, yet some do so better than others. These differences in learning were related to brain size: species with larger brains-both absolute and relative to body size-exhibited enhanced performance to learn the reward-colour association. Our finding highlights the functional significance of brain size in insects, filling a major gap in our understanding of brain evolution and opening new opportunities for future research., (© 2021 The Authors.)

AbstractDirect species interactions are commonly included in individual fitness models used for coexistence and local diversity modeling. Though widely considered important for such models, direct interactions alone are often insufficient for accurately predicting fitness, coexistence, or diversity outcomes. Incorporating higher-order interactions (HOIs) can lead to more accurate individual fitness models but also adds many model terms, which can quickly result in model overfitting. We explore approaches for balancing the trade-off between tractability and model accuracy that occurs when HOIs are added to individual fitness models. To do this, we compare models parameterized with data from annual plant communities in Australia and Spain, varying in the extent of information included about the focal and neighbor species. The best-performing models for both data sets were those that grouped neighbors based on origin status and life form, a grouping approach that reduced the number of model parameters substantially while retaining important ecological information about direct interactions and HOIs. Results suggest that the specific identity of focal or neighbor species is not necessary for building well-performing fitness models that include HOIs. In fact, grouping neighbors by even basic functional information seems sufficient to maximize model accuracy, an important outcome for the practical use of HOI-inclusive fitness models.

Ecological theory predicts that species interactions embedded in multitrophic networks shape the opportunities for species to persist. However, the lack of experimental support of this prediction has limited our understanding of how species interactions occurring within and across trophic levels simultaneously regulate the maintenance of biodiversity. Here, we integrate a mathematical approach and detailed experiments in plant-pollinator communities to demonstrate the need to jointly account for species interactions within and across trophic levels when estimating the ability of species to persist. Within the plant trophic level, we show that the persistence probability of plant species increases when introducing the effects of plant-pollinator interactions. Across trophic levels, we show that the persistence probabilities of both plants and pollinators exhibit idiosyncratic changes when experimentally manipulating the multitrophic structure. Importantly, these idiosyncratic effects are not recovered by traditional simulations. Our work provides tractable experimental and theoretical platforms upon which it is possible to investigate the multitrophic factors affecting species persistence in ecological communities., Competing Interests: The authors declare no competing interest.

Behavioural innovation and problem solving are widely considered to be important mechanisms by which animals respond to novel environmental challenges, including those induced by human activities. Despite their functional and ecological relevance, much of our current understanding of these processes comes from studies in vertebrates. Understanding of these processes in invertebrates has lagged behind partly because they are not perceived to have the cognitive machinery required. This perception is, however, challenged by recent evidence demonstrating sophisticated cognitive capabilities in insects despite their small brains. Here, we studied innovation, defined as the capacity to solve a new task, of a solitary bee ( Osmia cornuta ) in the laboratory by exposing naive individuals to an obstacle removal task. We also studied the underlying cognitive and non-cognitive mechanisms through a battery of experimental tests designed to measure associative learning, exploration, shyness and activity levels. We found that solitary bees can innovate, with 11 of 29 individuals (38%) being able to solve a new task consisting of lifting a lid to reach a reward. However, the propensity to innovate was uncorrelated with the measured learning capacity, but increased with exploration, boldness and activity. These results provide solid evidence that non-social insects can solve new tasks, and highlight the importance of interpreting innovation in the light of non-cognitive processes., Competing Interests: Competing interestsThe authors declare no competing or financial interests., (© 2021. Published by The Company of Biologists Ltd.)

Measuring habitat specialisation is pivotal for predicting species extinctions and for understanding consequences on ecosystem functioning. Here, we sampled pollinator and natural enemy communities in all major habitat types occurring across multiple agricultural landscapes and used species-habitat networks to determine how habitat specialisation changed along gradients in landscape composition and configuration. Although it is well known that landscape simplification often causes the replacement of specialists with generalists, our study provided evidence for intraspecific variation in habitat specialisation, highlighting how a large number of arthropod species adapted their way of selecting habitat resources depending on the landscape structure. Groups with higher diet specialisation and limited foraging flexibility appeared to have a reduced ability to respond to landscape changes, indicating that some arthropod taxa are better able than others to adapt to an increasingly broad set of resources and persist in highly impacted landscapes., (© 2020 John Wiley & Sons Ltd.)

Bumblebees are constantly exposed to a wide range of biotic and abiotic stresses which they must defend themselves against to survive. Pathogens and pesticides represent important stressors that influence bumblebee health, both when acting alone or in combination. To better understand bumblebee health, we need to investigate how these factors interact, yet experimental studies to date generally focus on only one or two stressors. The aim of this study is to evaluate how combined effects of four important stressors (the gut parasite Nosema ceranae, the neonicotinoid insecticide thiamethoxam, the pyrethroid insecticide cypermethrin and the EBI fungicide tebuconazole) interact to affect bumblebees at the individual and colony levels. We established seven treatment groups of colonies that we pulse exposed to different combinations of these stressors for 2 weeks under laboratory conditions. Colonies were subsequently placed in the field for 7 weeks to evaluate the effect of treatments on the prevalence of N. ceranae in inoculated bumblebees, expression levels of immunity and detoxification-related genes, food collection, weight gain, worker and male numbers, and production of worker brood and reproductives. Exposure to pesticide mixtures reduced food collection by bumblebees. All immunity-related genes were upregulated in the bumblebees inoculated with N. ceranae when they had not been exposed to pesticide mixtures, and bumblebees exposed to the fungicide and the pyrethroid were less likely to have N. ceranae. Combined exposure to the three-pesticide mixture and N. ceranae reduced bumblebee colony growth, and all treatments had detrimental effects on brood production. The groups exposed to the neonicotinoid insecticide produced 40%-76% fewer queens than control colonies. Our findings show that exposure to combinations of stressors that bumblebees frequently come into contact with have detrimental effects on colony health and performance and could therefore have an impact at the population level. These results also have significant implications for current practices and policies for pesticide risk assessment and use as the combinations tested here are frequently applied simultaneously in the field. Understanding the interactions between different stressors will be crucial for improving our ability to manage bee populations and for ensuring pollination services into the future., (© 2020 British Ecological Society.)

Despite their miniature brains, insects exhibit substantial variation in brain size. Although the functional significance of this variation is increasingly recognized, research on whether differences in insect brain sizes are mainly the result of constraints or selective pressures has hardly been performed. Here, we address this gap by combining prospective and retrospective phylogenetic-based analyses of brain size for a major insect group, bees (superfamily Apoidea). Using a brain dataset of 93 species from North America and Europe, we found that body size was the single best predictor of brain size in bees. However, the analyses also revealed that substantial variation in brain size remained even when adjusting for body size. We consequently asked whether such variation in relative brain size might be explained by adaptive hypotheses. We found that ecologically specialized species with single generations have larger brains-relative to their body size-than generalist or multi-generation species, but we did not find an effect of sociality on relative brain size. Phylogenetic reconstruction further supported the existence of different adaptive optima for relative brain size in lineages differing in feeding specialization and reproductive strategy. Our findings shed new light on the evolution of the insect brain, highlighting the importance of ecological pressures over social factors and suggesting that these pressures are different from those previously found to influence brain evolution in other taxa.

Agricultural intensification and associated loss of high-quality habitats are key drivers of insect pollinator declines. With the aim of decreasing the environmental impact of agriculture, the 2014 EU Common Agricultural Policy (CAP) defined a set of habitat and landscape features (Ecological Focus Areas: EFAs) farmers could select from as a requirement to receive basic farm payments. To inform the post-2020 CAP, we performed a European-scale evaluation to determine how different EFA options vary in their potential to support insect pollinators under standard and pollinator-friendly management, as well as the extent of farmer uptake.A structured Delphi elicitation process engaged 22 experts from 18 European countries to evaluate EFAs options. By considering life cycle requirements of key pollinating taxa (i.e. bumble bees, solitary bees and hoverflies), each option was evaluated for its potential to provide forage, bee nesting sites and hoverfly larval resources.EFA options varied substantially in the resources they were perceived to provide and their effectiveness varied geographically and temporally. For example, field margins provide relatively good forage throughout the season in Southern and Eastern Europe but lacked early-season forage in Northern and Western Europe. Under standard management, no single EFA option achieved high scores across resource categories and a scarcity of late season forage was perceived.Experts identified substantial opportunities to improve habitat quality by adopting pollinator-friendly management. Improving management alone was, however, unlikely to ensure that all pollinator resource requirements were met. Our analyses suggest that a combination of poor management, differences in the inherent pollinator habitat quality and uptake bias towards catch crops and nitrogen-fixing crops severely limit the potential of EFAs to support pollinators in European agricultural landscapes. Policy Implications . To conserve pollinators and help protect pollination services, our expert elicitation highlights the need to create a variety of interconnected, well-managed habitats that complement each other in the resources they offer. To achieve this the Common Agricultural Policy post-2020 should take a holistic view to implementation that integrates the different delivery vehicles aimed at protecting biodiversity (e.g. enhanced conditionality, eco-schemes and agri-environment and climate measures). To improve habitat quality we recommend an effective monitoring framework with target-orientated indicators and to facilitate the spatial targeting of options collaboration between land managers should be incentivised., (© 2020 The Authors. Journal of Applied Ecology published by John Wiley & Sons Ltd on behalf of British Ecological Society.)

We examined how plant-pollinator interactions were affected by time since habitat restoration and landscape connectivity by comparing plant-pollinator networks in restored, abandoned and continuously grazed semi-natural pastures in south-central Sweden. We measured richness of flowering plants and pollinators, and local plant-pollinator network characteristics including species composition as well as the number and identity of interactions, allowing a deeper understanding of species and interaction beta diversity. Pollinator richness and abundance were highest in restored grasslands. They successfully resembled continuously grazed grasslands. However, the turnover of interactions was extremely high among pasture categories (0.99) mainly due to high turnover of plant (0.74) and pollinator species (0.81). Among co-occurring plant and pollinator species, the turnover of interactions (0.66) was attributable mainly to differences in the number of links and to a lesser extent to species true rewiring (~0.17). Connectivity and time since restoration had no effect on the measured network properties. We show that plant-pollinator interactions can be rapidly restored even in relatively isolated grasslands. This is partly due to flexibility of most pollinators to establish interactions with the available flowering plants and relatively high species interaction rewiring, indicating that pollinators behavioural plasticity allow them to shift diets to adapt to new situations.

Human land use threatens global biodiversity and compromises multiple ecosystem functions critical to food production. Whether crop yield-related ecosystem services can be maintained by a few dominant species or rely on high richness remains unclear. Using a global database from 89 studies (with 1475 locations), we partition the relative importance of species richness, abundance, and dominance for pollination; biological pest control; and final yields in the context of ongoing land-use change. Pollinator and enemy richness directly supported ecosystem services in addition to and independent of abundance and dominance. Up to 50% of the negative effects of landscape simplification on ecosystem services was due to richness losses of service-providing organisms, with negative consequences for crop yields. Maintaining the biodiversity of ecosystem service providers is therefore vital to sustain the flow of key agroecosystem benefits to society., (Copyright © 2019 The Authors, some rights reserved; exclusive licensee American Association for the Advancement of Science. No claim to original U.S. Government Works. Distributed under a Creative Commons Attribution NonCommercial License 4.0 (CC BY-NC).)

Worldwide, anthropogenic change is causing biodiversity loss, disrupting many critical ecosystem functions. Most studies investigating the relationship between biodiversity and ecosystem functioning focus on species richness, predominantly within the context of productivity-related functions. Consequently, there is limited understanding of how other biodiversity measures, such as species evenness (the distribution of abundance among species), affect complex multitrophic functions such as pollination. We explore the effect of species evenness on the ecosystem function of pollination using a controlled experiment with selected plants and insects in flight cages. We manipulated the relative abundances of plant and pollinator species, while holding species richness, composition, dominance order, and total abundance constant. Then, we tested how numerical species evenness affected network structure and consequently, seed production, in our artificial communities. Contrary to our expectation, numerical dominance in plant communities increased complementarity in pollinator use (reduced pollinator sharing) among plant species. As predicted by theory, this increased complementarity resulted in higher seed production for the most dominant and rare plant species in our cages. Our results show that in a controlled experimental setting, numerical species evenness can alter important aspects of plant-pollinator networks and plant reproduction, irrespective of species richness, composition, and total abundance. Extending this understanding of how species evenness affects ecosystem functioning to natural systems is crucial as anthropogenic disturbances continue to alter species' abundances, likely disrupting ecosystem functions long before extinctions occur., (© 2019 by the Ecological Society of America.)

Graphics are becoming increasingly important for scientists to effectively communicate their findings to broad audiences, but most researchers lack expertise in visual media. We suggest collaboration between scientists and graphic designers as a way forward and discuss the results of a pilot project to test this type of collaboration., Competing Interests: Competing interestsThe authors declare no competing interests.

Body size is an integral functional trait that underlies pollination-related ecological processes, yet it is often impractical to measure directly. Allometric scaling laws have been used to overcome this problem. However, most existing models rely upon small sample sizes, geographically restricted sampling and have limited applicability for non-bee taxa. Allometric models that consider biogeography, phylogenetic relatedness, and intraspecific variation are urgently required to ensure greater accuracy. We measured body size as dry weight and intertegular distance (ITD) of 391 bee species (4,035 specimens) and 103 hoverfly species (399 specimens) across four biogeographic regions: Australia, Europe, North America, and South America. We updated existing models within a Bayesian mixed-model framework to test the power of ITD to predict interspecific variation in pollinator dry weight in interaction with different co-variates: phylogeny or taxonomy, sexual dimorphism, and biogeographic region. In addition, we used ordinary least squares regression to assess intraspecific dry weight ~ ITD relationships for ten bees and five hoverfly species. Including co-variates led to more robust interspecific body size predictions for both bees and hoverflies relative to models with the ITD alone. In contrast, at the intraspecific level, our results demonstrate that the ITD is an inconsistent predictor of body size for bees and hoverflies. The use of allometric scaling laws to estimate body size is more suitable for interspecific comparative analyses than assessing intraspecific variation. Collectively, these models form the basis of the dynamic R package, " pollimetry, " which provides a comprehensive resource for allometric pollination research worldwide.

[This corrects the article DOI: 10.1371/journal.pone.0151482.].

There is increasing concern about the decline of pollinators worldwide. However, despite reports that pollinator declines are widespread, data are scarce and often geographically and taxonomically biased. These biases limit robust inference about any potential pollinator crisis. Non-structured and opportunistic historical specimen collection data provide the only source of historical information which can serve as a baseline for identifying pollinator declines. Specimens historically collected and preserved in museums not only provide information on where and when species were collected, but also contain other ecological information such as species interactions and morphological traits. Here, we provide a synthesis of how researchers have used historical data to identify long-term changes in biodiversity, species abundances, morphology and pollination services. Despite recent advances, we show that information on the status and trends of most pollinators is absent. We highlight opportunities and limitations to progress the assessment of pollinator declines globally. Finally, we demonstrate different approaches to analysing museum collection data using two contrasting case studies from distinct geographical regions (New Zealand and Spain) for which long-term pollinator declines have never been assessed. There is immense potential for museum specimens to play a central role in assessing the extent of the global pollination crisis.This article is part of the theme issue 'Biological collections for understanding biodiversity in the Anthropocene'., (© 2018 The Author(s).)

Theory argues that both soil conditions and aboveground trophic interactions have equivalent potential to limit or promote plant diversity. However, it remains unexplored how they jointly modify the niche differences stabilising species coexistence and the average fitness differences driving competitive dominance. We conducted a field study in Mediterranean annual grasslands to parameterise population models of six competing plant species. Spatially explicit floral visitor assemblages and soil salinity variation were characterised for each species. Both floral visitors and soil salinity modified species population dynamics via direct changes in seed production and indirect changes in competitive responses. Although the magnitude and sign of these changes were species-specific, floral visitors promoted coexistence at neighbourhood scales, while soil salinity did so over larger scales by changing the superior competitors' identity. Our results show how below and aboveground interactions maintain diversity in heterogeneous landscapes through their opposing effects on the determinants of competitive outcomes., (© 2018 John Wiley & Sons Ltd/CNRS.)

The quest for understanding how species interactions modulate diversity has progressed by theoretical and empirical advances following niche and network theories. Yet, niche studies have been limited to describe coexistence within tropic levels despite incorporating information about multi-trophic interactions. Network approaches could address this limitation, but they have ignored the structure of species interactions within trophic levels. Here we call for the integration of niche and network theories to reach new frontiers of knowledge exploring how interactions within and across trophic levels promote species coexistence. This integration is possible due to the strong parallelisms in the historical development, ecological concepts, and associated mathematical tools of both theories. We provide a guideline to integrate this framework with observational and experimental studies., (Copyright © 2018 Elsevier Ltd. All rights reserved.)

Ecologists have shown through hundreds of experiments that ecological communities with more species produce higher levels of essential ecosystem functions such as biomass production, nutrient cycling, and pollination, but whether this finding holds in nature (that is, in large-scale and unmanipulated systems) is controversial. This knowledge gap is troubling because ecosystem services have been widely adopted as a justification for global biodiversity conservation. Here we show that, to provide crop pollination in natural systems, the number of bee species must increase by at least one order of magnitude compared with that in field experiments. This increase is driven by species turnover and its interaction with functional dominance, mechanisms that emerge only at large scales. Our results show that maintaining ecosystem services in nature requires many species, including relatively rare ones., (Copyright © 2018 The Authors, some rights reserved; exclusive licensee American Association for the Advancement of Science. No claim to original U.S. Government Works.)

During the past decades, managed honeybee stocks have increased globally. Managed honeybees are particularly used within mass-flowering crops and often spill over to adjacent natural habitats after crop blooming. Here, we uniquely show the simultaneous impact that honeybee spillover has on wild plant and animal communities in flower-rich woodlands via changes in plant-pollinator network structure that translate into a direct negative effect on the reproductive success of a dominant wild plant. Honeybee spillover leads to a re-assembly of plant-pollinator interactions through increased competition with other pollinator species. Moreover, honeybee preference for the most abundant plant species reduces its seed set, driven by high honeybee visitation rates that prevent pollen tube growth. Our study therefore calls for an adequate understanding of the trade-offs between providing pollination services to crops and the effects that managed pollinators might have on wild plants and pollinators.

Two main mechanisms may buffer ecosystem functions despite biodiversity loss. First, multiple species could share similar ecological roles, thus providing functional redundancy. Second, species may respond differently to environmental change (response diversity). However, ecosystem function would be best protected when functionally redundant species also show response diversity. This linkage has not been studied directly, so we investigated whether native and exotic pollinator species with similar traits (functional redundancy) differed in abundance (response diversity) across an agricultural intensification gradient. Exotic pollinator species contributed most positive responses, which partially stabilized overall abundance of the pollinator community. However, although some functionally redundant species exhibited response diversity, this was not consistent across functional groups and aggregate abundances within each functional group were rarely stabilized. This shows functional redundancy and response diversity do not always operate in concert. Hence, despite exotic species becoming increasingly dominant in human-modified systems, they cannot replace the functional composition of native species., (© 2017 The Author(s).)