Biodiversity and pollination benefits trade off against profit in an intensive farming system.

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.

Pollinator-assisted plant phenotyping, selection, and breeding for crop resilience to abiotic stresses.

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.

Multitrophic Higher-Order Interactions Modulate Species Persistence.

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.

Experimental evidence of the importance of multitrophic structure for species persistence.

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.

Intraspecific variation in species interactions promotes the feasibility of mutualistic assemblages.

Patterns of resource use observed at the species level emerge from the way individuals exploit the range of available resources. Hence, accounting for interindividual differences in resource use, such as pollinator use by plants, is essential to advance our understanding of community assembly and persistence. By using finely resolved data on plant-pollinator interactions, we evaluated how interindividual plant variation in pollinator use scales up to affect community structure and dynamics. All co-occurring plant species comprised specialists interacting with proper subsets of pollinators that visited generalists, and differences in interaction patterns were driven by among-individual trait variation. Furthermore, the nested structure and feasibility of plant-pollinator communities were maximised at higher levels of interindividual plant variation in traits and pollinator use. Our study sheds light on how pervasive properties of community structure arise from individual-level processes and contributes to elucidate the importance of preserving intraspecific variation in traits and resource use within populations.

Structural asymmetry in biotic interactions as a tool to understand and predict ecological persistence.

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.

Non-random interactions within and across guilds shape the potential to coexist in multi-trophic ecological communities.

Theory posits that the persistence of species in ecological communities is shaped by their interactions within and across trophic guilds. However, we lack empirical evaluations of how the structure, strength and sign of biotic interactions drive the potential to coexist in diverse multi-trophic communities. Here, we model community feasibility domains, a theoretically informed measure of multi-species coexistence probability, from grassland communities comprising more than 45 species on average from three trophic guilds (plants, pollinators and herbivores). Contrary to our hypothesis, increasing community complexity, measured either as the number of guilds or community richness, did not decrease community feasibility. Rather, we observed that high degrees of species self-regulation and niche partitioning allow for maintaining larger levels of community feasibility and higher species persistence in more diverse communities. Our results show that biotic interactions within and across guilds are not random in nature and both structures significantly contribute to maintaining multi-trophic diversity.

The non-random assembly of network motifs in plant-pollinator networks.

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.

Brain size predicts bees' tolerance to urban environments.

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.

Characterization Factors to Assess Land Use Impacts on Pollinator Abundance in Life Cycle Assessment.

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.

Fine scale prediction of ecological community composition using a two-step sequential Machine Learning ensemble.

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.

Species-habitat networks elucidate landscape effects on habitat specialisation of natural enemies and pollinators.

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.

Identifying "Useful" Fitness Models: Balancing the Benefits of Added Complexity with Realistic Data Requirements in Models of Individual Plant Fitness.

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.

Innovation in solitary bees is driven by exploration, shyness and activity levels.

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.

Interaction between warming and landscape foraging resource availability on solitary bee reproduction.

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.

Multiple stressors interact to impair the performance of bumblebee Bombus terrestris colonies.

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.

Los abejorros están constantemente expuestos a una amplia gama de agentes estresantes bióticos y abióticos de los que deben defenderse para sobrevivir. Los patógenos y los pesticidas son importantes factores estresantes que influyen en la salud de los abejorros, tanto cuando actúan solos como en combinación. Para tener un mejor conocimiento sobre la salud de los abejorros, debemos investigar cómo interactúan estos factores estresantes, pero los estudios experimentales hasta la fecha generalmente se centran en estudiar solo uno o dos factores. El objetivo de nuestro estudio es evaluar cómo los efectos combinados de cuatro importantes factores estresantes (el parásito intestinal Nosema ceranae, el insecticida neonicotinoide tiametoxam, el insecticida piretroide cipermetrina y el fungicida EBI tebuconazol) interactúan para afectar a los abejorros a nivel individual y de colonia. Establecimos siete grupos de tratamiento de colonias de abejorros que expusimos a diferentes combinaciones de estos factores estresantes durante dos semanas en condiciones de laboratorio, y posteriormente se colocaron en el campo durante siete semanas, para evaluar el efecto de los tratamientos sobre la prevalencia de N. ceranae en abejorros inoculados, los niveles de expresión de genes relacionados con la inmunidad y la desintoxicación, la recolección de alimentos, el aumento de peso, el número de obreras y machos, y la producción de cría de obreras, machos y reinas. La exposición a mezclas de pesticidas redujo la recolección de alimentos por parte de los abejorros. Todos los genes relacionados con la inmunidad se sobre-expresaron en los abejorros inoculados con N. ceranae cuando no habían estado expuestos a mezclas de pesticidas, y los abejorros expuestos al fungicida y al piretroide presentaron menos probabilidades de tener N. ceranae. La exposición combinada a la mezcla de tres pesticidas y N. ceranae redujo el crecimiento de la colonia de abejorros y todos los tratamientos tuvieron efectos perjudiciales en la producción de crías. Los grupos expuestos al insecticida neonicotinoide produjeron entre un 40 y un 76% menos de reinas que las colonias control. Nuestros hallazgos muestran que la exposición a combinaciones de factores estresantes con los que los abejorros entran frecuentemente en contacto tiene efectos perjudiciales sobre la salud y el rendimiento de la colonia y, por lo tanto, podría tener un impacto a nivel poblacional. Estos resultados también tienen importantes implicaciones para las prácticas y políticas actuales de evaluación de riesgos y uso de plaguicidas, ya que las combinaciones probadas aquí se aplican con frecuencia simultáneamente en el campo. Comprender las interacciones entre los diferentes factores de estrés es fundamental para mejorar nuestra capacidad de gestión de las poblaciones de abejas y así garantizar los servicios de polinización en el futuro.

Feeding specialization and longer generation time are associated with relatively larger brains in bees.

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.

The interplay of landscape composition and configuration: new pathways to manage functional biodiversity and agroecosystem services across Europe.

Managing agricultural landscapes to support biodiversity and ecosystem services is a key aim of a sustainable agriculture. However, how the spatial arrangement of crop fields and other habitats in landscapes impacts arthropods and their functions is poorly known. Synthesising data from 49 studies (1515 landscapes) across Europe, we examined effects of landscape composition (% habitats) and configuration (edge density) on arthropods in fields and their margins, pest control, pollination and yields. Configuration effects interacted with the proportions of crop and non-crop habitats, and species' dietary, dispersal and overwintering traits led to contrasting responses to landscape variables. Overall, however, in landscapes with high edge density, 70% of pollinator and 44% of natural enemy species reached highest abundances and pollination and pest control improved 1.7- and 1.4-fold respectively. Arable-dominated landscapes with high edge densities achieved high yields. This suggests that enhancing edge density in European agroecosystems can promote functional biodiversity and yield-enhancing ecosystem services.

Non-bee insects are important contributors to global crop pollination.

Wild and managed bees are well documented as effective pollinators of global crops of economic importance. However, the contributions by pollinators other than bees have been little explored despite their potential to contribute to crop production and stability in the face of environmental change. Non-bee pollinators include flies, beetles, moths, butterflies, wasps, ants, birds, and bats, among others. Here we focus on non-bee insects and synthesize 39 field studies from five continents that directly measured the crop pollination services provided by non-bees, honey bees, and other bees to compare the relative contributions of these taxa. Non-bees performed 25-50% of the total number of flower visits. Although non-bees were less effective pollinators than bees per flower visit, they made more visits; thus these two factors compensated for each other, resulting in pollination services rendered by non-bees that were similar to those provided by bees. In the subset of studies that measured fruit set, fruit set increased with non-bee insect visits independently of bee visitation rates, indicating that non-bee insects provide a unique benefit that is not provided by bees. We also show that non-bee insects are not as reliant as bees on the presence of remnant natural or seminatural habitat in the surrounding landscape. These results strongly suggest that non-bee insect pollinators play a significant role in global crop production and respond differently than bees to landscape structure, probably making their crop pollination services more robust to changes in land use. Non-bee insects provide a valuable service and provide potential insurance against bee population declines.

Opposing effects of floral visitors and soil conditions on the determinants of competitive outcomes maintain species diversity in heterogeneous landscapes.

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.