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Planting three billion trees to capture carbon and seeking measures to reverse pollinator decline are two key pledges of the EU Biodiversity Strategy for 2030. Although planting trees could be adequate to restore biodiversity in degraded landscapes and mitigate anthropogenic carbon emissions, it can also negatively impact biodiversity of naturally treeless habitats. To explore whether these two pledges might conflict, we focused on the European dry heathland, a treeless habitat frequent in the southwestern Iberian Peninsula, where it is locally known as herriza. The herriza stands out by its high plant biodiversity and profuse flowering that supports a wide range of insect pollinators. Yet, the herriza has been heavily afforested with pine trees until the onset of the 21st century. This fact provides a unique natural experiment to assess how the afforestation of a treeless habitat affects its flower abundance and associated pollinator diversity. We conducted a two-year field study of the diversity and abundance of flowers and pollinators in five selected sites, each consisting of two adjacent plots of open and afforested herriza. Afforested herriza plots consistently showed lower diversity and abundance of flowers and, likely subsequent, lower diversity and abundance of insect pollinators than open herriza plots. Results highlight the negative impact of afforestation of a treeless habitat on its flowering pattern and associated insect pollinator guild. They thus suggest seeking alternatives to afforesting naturally treeless habitats in order to avoid conflicts between carbon sequestration and pollinator conservation. Data (.csv) pol:Raw pollinator data, ordered by sampling year (cycle 1 or 2), season (autumn, winter, early spring, late spring, summer), site (Marrufo, Buenas Noches, Montecoche, Montero, Fates), date , subplot (H: Open herriza, P: Afforested herriza), transect (1-4), taxonomic categories (order, family, genus, species) and abundances. flor:Raw flower data, ordered bysampling year (cycle 1 or 2), season (autumn, winter, early spring, late spring, summer), site (Marrufo, Buenas Noches, Montecoche, Montero, Fates), date , subplot (H: Open herriza, P: Afforested herriza), meter, transect (1-4) and flower species. d:Data prepared with the richness and abundance of flowers and pollinators in each of the transects. Sorted by site, season, subplot, year of sampling, and transect. Script R script with the main results.

Historical contingency, such as the order of species arrival, can modify competitive outcomes via niche modification or preemption. However, how these mechanisms ultimately modify stabilising niche and average fitness differences remains largely unknown. By experimentally assembling two congeneric spider mite species feeding on tomato plants during two generations, we show that order of arrival affects species’ competitive ability and changes the outcome of competition. Contrary to expectations, order of arrival did not cause positive frequency dependent priority effects. Instead, coexistence was predicted when the inferior competitor (Tetranychus urticae) arrived first. In that case, T. urticae colonised the preferred feeding stratum (leaves) of T. evansi leading to spatial niche preemption, which equalised fitness and reduced niche differences, driving community assembly to a close-to-neutrality scenario. Our study demonstrates how the order of species arrival and the spatial context of competitive interactions can jointly determine whether species can coexist.

Adaptation to novel environments have been documented at the population, phenotype and genotype level. However, the ecological consequences of this process are often ignored. For example, recent evolutionary history in different environments is expected to lead to increased growth rates and competitive abilities. These traits have been identified as key ingredients underlying species coexistence, which suggests that adaptation to new environments may shape species coexistence patterns. However, this hypothesis remains untested.To tackle this issue, we performed experimental evolution of two herbivorous spider mite species (Tetranychus urticaeandT. evansi) feeding on tomato plants grown under high or low cadmium concentrations. We combined phenotypic analyses with structural stability theory to show that both the cadmium environment and evolution in it changed the coexistence patterns of the two species by increasing niche differences. In fact, the presence of cadmium reduced interspecific competition and led to facilitation between the two herbivores, entailing stable coexistence independently of the previous evolutionary history. Evolution in the cadmium environment also reduced interspecific competition in the ancestral environment, producing stable coexistence. These results show that evolution in a new environment, even in absence of interspecific competitors, affects long-term species coexistence. Importantly, it highlights that biotic interactions (within or between populations) should be accounted for when describing adaptation to novel environments.

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 intra- and interspecific 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) andPulicaria 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 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.

SummaryGenetic diversity affects evolutionary trajectories but their ultimate effects on ecological interactions and community dynamics remains poorly understood. It has been hypothesized that phenotypic novelties produced by ploidy and heterozygosity modify the ecological interactions between novel genotypes and more ancient locally adapted ones, and therefore, their opportunities to coexist.We performed a greenhouse competition experiment with three taxa of theErysimum incanumspecies complex differing in ploidy (2x, 4x and 6x) and heterozygosity (high and low). This experiment allows us to parameterize a population model to test the effect of genetic diversity on modulating the ecological forces that determine the outcome of competition, niche and fitness differences.Depending on whether ploidy variation and the level of heterozygosity made interspecific competition greater or smaller than intraspecific competition, we predicted either priority effects or coexistence. Such competitive outcome differences were explained by the phenotypic expression in the number of stalks (plant size surrogate) with genotypes under priority effects showing more stalks.Altogether, our results show that non-polyploid plants can coexist with polyploids contravening theoretical expectations of polyploidy dominance under stable conditions. However, historical contingency such as order of arrival promotes priority effects when adaptive phenotypic optimums strongly compete for space.

In structured populations, persistence under environmental change may be particularly threatened when abiotic factors simultaneously negatively affect survival and reproduction of several life cycle stages, as opposed to a single stage. Such effects can then be exacerbated when species interactions generate reciprocal feedbacks between the demographic rates of the different species. Despite the importance of such demographic feedbacks, forecasts that account for them are limited as individual-based data on interacting species are perceived to be essential for such mechanistic forecasting—but are rarely available. Here, we first review the current shortcomings in assessing demographic feedbacks in population and community dynamics. We then present an overview of advances in statistical tools that provide an opportunity to leverage population-level data on abundances of multiple species to infer stage-specific demography. Lastly, we showcase a state-of-the-art Bayesian method to infer and project stage-specific survival and reproduction for several interacting species in a Mediterranean shrub community. This case study shows that climate change threatens populations most strongly by changing the interaction effects of conspecific and heterospecific neighbours on both juvenile and adult survival. Thus, the repurposing of multi-species abundance data for mechanistic forecasting can substantially improve our understanding of emerging threats on biodiversity.

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 persistence (i.e. long-term viability) 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 solved 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 seven years in a Mediterranean grassland. Our approach, which is designed to be applied to any ecological system regardless of the number of species and type of interactions, shows that is possible to obtain both mechanistic and predictive information of ecological persistence for individual species and entire communities, providing a clear link for a stronger integration of theoretical and empirical research.

5 figuras.- 1 tabla.- This article is in Press, Journal Pre-proof, Climate change is a fundamental process affecting terrestrial ecosystems. However, there is relatively little knowledge about its impacts on soil communities, with a large degree of uncertainty regarding their resistance to predicted alterations in temperature and, particularly, precipitation. Moreover, most studies exploring the response of soil biota to predicted rainfall reduction have focused on mesic environments and soil microbes, which limit our ability to find general patterns across ecosystems and soil organisms. In this study, we analysed the impact of predicted climate change scenarios of rainfall reduction on soil food webs of Mediterranean water-limited forests using nematodes as bioindicators. We took advantage of replicated rainfall exclusion infrastructures (30% exclusion) established in Quercus forests of southern Spain in 2016 (2-year exclusion) and of southern France in 2003 (15-year exclusion) to explore the sensitivity of the soil food web to predicted reductions at short- and long-term scales. Rainfall reduction had large negative short-term effects on nematode abundance, particularly of lower trophic groups (bacterivores and fungivores). Rainfall reduction had also consistent short- and long-term impacts on community composition (decrease of fungivores, marginal increase of omnivores) and nematode-based indicators of soil food web structure (higher maturity and structure index, lower prey:predator ratio). These results can be considered indicative of a low resistance of the soil food web to rainfall reductions predicted by climate change. Overall, our findings demonstrate the sensitivity of water-limited forests to further reductions in soil water availability, which might substantially alter their soil communities and likely affect the many ecosystem processes that they control., This study was funded by the MICINN projects INTERCAPA (CGL2014-56739-R) and MICROFUN (RTI2018-094394-B-I00). P.H. was supported by a FPI-MICINN grant. L.M. was supported by the fellowship IV2 from VI-PPIT (Univ. Sevilla) and the project PID2019-108288RA-I00 (MINECO). OG acknowledges financial support provided by the Spanish Ministry of Economy and Competitiveness (MINECO) and by the European Social Fund through the Ramón y Cajal Program (RYC-2017-23666). Puéchabon is supported by the OSU OREME (UMS 3282) and the French national research infrastructure ANAEE-France (ANR-11-INBS-0001).

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’.

Increases in land use intensity (LUI) reduce species richness. However, we have a poor understanding of how underlying coexistence mechanisms are altered by land use and whether diversity loss occurs due to changes in plant-plant interactions (competition and facilitation) or in species intrinsic growth rates. We expect that LUI could reduce stabilizing niche differences and the indirect interactions that promote coexistence (e.g., intransitivity), while increasing competitive inequalities between species. To test the importance of these different processes, we use 8-yr time series from 150 grasslands differing in LUI to evaluate the role of direct and indirect interactions in promoting coexistence between 50 plant species. We show that LUI reduces the number of coexisting species mostly by causing a non-linear reduction in niche differences, rather than by enhancing competitive inequalities. However, surprisingly, niche differences remained important in stabilizing coexistence between those species remaining at high LUI. Indirect interactions were generally less important than direct ones, and played a moderate role in promoting coexistence in smaller assemblages of species at intermediate LUI. Our models could accurately reproduce the decline in diversity seen with LUI, indicating that our time series approach captures the important interactions between species. By analyzing land use effects through recent advances in structural stability applied to community ecology we provide a more mechanistic understanding of its effects. Our results highlight the importance of identifying the niche differences that are lost with increasing LUI, to better predict and manage effects of land use on biodiversity.Significant statementHuman land use is a major threat to grassland biodiversity. Grasslands with high rates of fertilization, grazing and mowing, contain many fewer plant species. Knowing the underlying causes is necessary for a better management of biodiversity. Here we apply ecological theory to spatiotemporal data on changes in plant abundance in managed grasslands in central Europe. We show that the observed decline in diversity can be explained by how interactions among plant species change with increases in land use intensity. In particular, intensive land use removes the stabilizing effect of self-limiting processes that buffer species against extinction as well as limit competitive dominance. Therefore, actions to promote these stabilizing dynamics among interacting species seem key to restore plant diversity.

Understanding whether land use intensification causes regime shifts is of key importance for management, particularly if these shifts are associated with thresholds separating different ecosystem states and with hysteretic dynamics. Here we use a unique, long-term grassland database to identify thresholds in the response of 16 ecosystem functions and the diversities of 21 taxa to land use intensity. We show that aboveground diversity (5 of 10 taxa), shoot biomass and soil N retention showed threshold responses to land use intensity, i.e., abrupt changes between extensively and intensively managed grasslands. Time-series analysis revealed that ecosystem functions showed hysteresis around the threshold, while diversity did not. Shifting back to the functioning seen in extensively managed grasslands may therefore require larger reductions in land use intensity than shifting to the high intensity state. Identifying such thresholds along land use gradients is critical to prevent ecosystem degradation and conserve biodiversity and ecosystem functions.

Modern coexistence theory (MCT) holds the potential to study the ability of species to avoid extinction (i.e. to persist) across community types but is rarely applied beyond pairs of competing species. Here, we show that this limitation can be overcome by mapping species according to their niche ((Formula presented.)) and fitness differences ((Formula presented.)). This application provides three main benefits to study processes of multispecies persistence across trophic levels. First, (Formula presented.) mapping introduces a novel categorization of species and communities according to the high-level processes at play: frequency dependence (negative or positive), the occurrence of positive species interactions (facilitation and mutualism) and whether persistence is possible without the presence of other species because of trophic interactions, such as herbivory or predation. Therefore, this mapping can be seen as a toolbox to describe how species persistence depends on species interactions. Second, (Formula presented.) mapping facilitates studying how species persistence responds to environmental changes that shift intrinsic growth rates and the strength and sign of species interactions. Third, (Formula presented.) mapping has the potential to foster synthesis across community types because it can accommodate co-occurrence of positive, negative and neutral interactions between species. We, therefore, argue that (Formula presented.) mapping can promote collaboration across sub-fields, as it provides a common concept to link disparate ecological communities.

Predicting species coexistence can be difficult often because underlying assembly processes are unknown and data are limited. However, accurate predictions are needed for design and forecasting problems in biodiversity conservation, climate change, invasion ecology, restoration ecology, and synthetic ecology. Here we describe an approach (Learning Outcomes Via Experiments; LOVE) where a limited set of experiments are conducted and multiple community outcomes measured (richness, composition, and abundance), from which a model is trained to predict outcomes for arbitrary experiments. Across seven taxonomically datasets, LOVE predicts test outcomes with low error when trained on ∼100 randomly-selected experiments. LOVE can then prioritize experiments for tasks like maximizing outcome richness or total abundance, or minimizing abundances of unwanted species. LOVE complements existing mechanism-first approaches to prediction and shows that rapid screening of communities for desirable properties may become possible.Author summaryPredicting which species will or will not coexist with each other is a central challenge for ecology. Success would allow experimental assembly of communities with desirable properties (e.g. high biodiversity). Mechanistic approaches to this problem run into data and theory limitations, as well as vast combinatorial complexity. Here we instead show to predict and prioritize coexistence without needing to identify or quantify any ecological mechanisms, based on statistical learning from randomly-selected experiments. The approach may help us to discover and then assemble ecological communities with desirable properties.

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'. ISSN:0962-8436 ISSN:1471-2970 ISSN:0080-4622

Contemporary studies of species coexistence are underpinned by deterministic models that assume that competing species have continuous (i.e., noninteger) densities, live in infinitely large landscapes, and coexist over infinite time horizons. By contrast, in nature, species are composed of discrete individuals subject to demographic stochasticity and occur in habitats of finite size where extinctions occur in finite time. One consequence of these discrepancies is that metrics of species' coexistence derived from deterministic theory may be unreliable predictors of the duration of species coexistence in nature. These coexistence metrics include invasion growth rates and niche and fitness differences, which are now commonly applied in theoretical and empirical studies of species coexistence. In this study, we tested the efficacy of deterministic coexistence metrics on the duration of species coexistence in a finite world. We introduce new theoretical and computational methods to estimate coexistence times in stochastic counterparts of classic deterministic models of competition. Importantly, we parameterized this model using experimental field data for 90 pairwise combinations of 18 species of annual plants, allowing us to derive biologically informed estimates of coexistence times for a natural system. Strikingly, we found that for species expected to deterministically coexist, community sizes containing only 10 individuals had predicted coexistence times of more than 1000 years. We also found that invasion growth rates explained 60% of the variation in intrinsic coexistence times, reinforcing their general usefulness in studies of coexistence. However, only by integrating information on both invasion growth rates and species' equilibrium population sizes could most (99%) of the variation in species coexistence times be explained. This integration was achieved with demographically uncoupled single-species models solely determined by the invasion growth rates and equilibrium population sizes. Moreover, because of a complex relationship between niche overlap/fitness differences and equilibrium population sizes, increasing niche overlap and increasing fitness differences did not always result in decreasing coexistence times, as deterministic theory would predict. Nevertheless, our results tend to support the informed use of deterministic theory for understanding the duration of species' coexistence while highlighting the need to incorporate information on species' equilibrium population sizes in addition to invasion growth rates.

Restoration ecology commonly seeks to re-establish species of interest in degraded habitats. Despite a rich understanding of how succession influences re-establishment, there are several outstanding questions that remain unaddressed: are short-term abundances sufficient to determine long-term re-establishment success, and what factors contribute to unpredictable restorations outcomes? In other words, when restoration fails, is it because the restored habitat is substandard, because of strong competition with invasive species, or alternatively due to changing environmental conditions that would equally impact established populations? Here, we re-purpose tools developed from modern coexistence theory to address these questions, and apply them to an effort to restore the endangered Contra Costa goldfields (Lasthenia conjugens) in constructed ("restored") California vernal pools. Using 16 years of data, we construct a population model of L. conjugens, a species of conservation concern due primarily to habitat loss and invasion of exotic grasses. We show that initial, short-term appearances of restoration success from population abundances is misleading, as year-to-year fluctuations cause long-term population growth rates to fall below zero. The failure of constructed pools is driven by lower maximum growth rates compared with reference ("natural") pools, coupled with a stronger negative sensitivity to annual fluctuations in abiotic conditions that yield decreased maximum growth rates. Nonetheless, our modeling shows that fluctuations in competition (mainly with exotic grasses) benefit L. conjugens through periods of competitive release, especially in constructed pools of intermediate pool depth. We therefore show how reductions in invasives and seed addition in pools of particular depths could change the outcome of restoration for L. conjugens. By applying a largely theoretical framework to the urgent goal of ecological restoration, our study provides a blueprint for predicting restoration success, and identifies future actions to reverse species loss. Funding Agencies|Air Force Center for Environmental Excellence; US Fish and Wildlife Service; CH2M Hill; NSF LTREB grants [DEB-0744520, DEB-1257385]; USDA NIFA Predoctoral Fellowship [2021-67034-35111]; Swedish Research Council (Vetenskapsradet) [2017-05245]; Spanish Ministry of Economy and Competitiveness (MINECO); European Social Fund through the Ramon y Cajal Program [RYC2017-23666]

Modelling species interactions in diverse communities traditionally requires a prohibitively large number of species-interaction coefficients, especially when considering environmental dependence of parameters. We implemented Bayesian variable selection via sparsity-inducing priors on non-linear species abundance models to determine which species interactions should be retained and which can be represented as an average heterospecific interaction term, reducing the number of model parameters. We evaluated model performance using simulated communities, computing out-of-sample predictive accuracy and parameter recovery across different input sample sizes. We applied our method to a diverse empirical community, allowing us to disentangle the direct role of environmental gradients on species intrinsic growth rates from indirect effects via competitive interactions. We also identified a few neighbouring species from the diverse community that had non-generic interactions with our focal species. This sparse modelling approach facilitates exploration of species interactions in diverse communities while maintaining a manageable number of parameters. Funding Agencies|NSF EPSCoRNational Science Foundation (NSF)NSF - Office of the Director (OD) [EPS-2019528]; Australian Research CouncilAustralian Research Council [DP140100574]; VetenskapsradetSwedish Research Council [2017-05245]; European Social FundEuropean Social Fund (ESF) [RYC-2017-23666]; Ministerio de Economia y CompetitividadSpanish Government; Deutsches Zentrum fur integrative Biodiversitatsforschung Halle-Jena-Leipzig [FZT 118, 02548816]

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. Author summary Prediction is challenging but recently developed Machine Learning techniques allow to dramatically improve prediction accuracy in several domains. However, these tools are often of little application in ecology due to the hardship of gathering information on the needed explanatory variables, which often comprise not only physical variables such as temperature or soil nutrients, but also information about the complex network of species interactions that modulate species abundances. Here we present a two-step sequential modelling framework that overcomes these constraints. We first infer potential species abundances by training models just with easily obtained abiotic variables and then use this outcome to fine-tune the prediction of the realized species abundances when taking into account the rest of the predicted species in the community. Overall, our results show a promising way forward for fine scale prediction in ecology., O.G. acknowledges support provided by the Ministerio de Ciencia, Innovacion y Universidades (RYC-2017-23666). O.G. and I.B. acknowledge financial support provided by the Secretaria de Estado de Investigacion, Desarrollo e Innovacion (CGL2017-92436-EXP, SIMPLEX and RTI2018-098888-A-I00, MeDiNaS). J.G. acknowledges financial support provided by the Ministerio de Ciencia, Innovacion y Universidades (PGC2018-093854-B-I00). The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.

Theory posits that the persistence of species in ecological communities is shaped by their interactions within and across trophic levels. However, we lack empirical evaluations of how the structure, strength and sign of these interactions drive the potential to coexist in diverse multi-trophic communities. Here we model community feasibility domains, a theoretically-informed measure of coexistence probability, from empirical data on communities comprising more than 50 species for three trophic guilds (plants, pollinators, and herbivores). Although feasibility domains vary depending on the number of trophic guilds considered, we show that higher network connectance leads to lower coexistence opportunities. Moreover, empirical estimations of the feasibility domains were higher with respect to random network structures but lower than a mean-field approach, suggesting that observed interaction structures tend to maximize coexistence within its imposed limits. Our results stress the importance of incorporating empirically-informed interaction structures within and across guilds to better understand how species coexist in diverse multi-trophic communities.

To avoid extinction, every species must be able to exploit available resources at least as well as the other species in its community. All else being equal, theory predicts that the more distinct the niches of such co-occurring and competing species, the more species that can persist in the long run. However, both theoretical and experimental studies define a priori the nature and number of resources over which species compete. It therefore remains unclear whether or not species in empirically realistic contexts are actually exploiting all or some of the niches available to them. Here we provide a mathematical solution to this long-standing problem. Specifically, we show how to use the interactions between sets of co-occurring plant species to quantify their implied “niche dimensionality”: the effective number of resources over which those species appear to be competing. We then apply this approach to quantify the niche dimensionality of 12 plant assemblages distributed across the globe. Contrary to conventional wisdom, we found that the niche dimensionality in these systems was much lower than the number of competing species. However, two high-resolution experiments also show that changes in the local environment induce a reshuffling of plant’s competitive roles and hence act to increase the assemblages’ effective niche dimensionality. Our results therefore indicate that homogeneous environments are unlikely to be able to maintain high diversity and also shows how environmental variation impacts species’ niches and hence their opportunities for long-term survival.

Cadiz Bay is a shallow mesotidal lagoon with extensive populations of the seagrass Cymodocea nodosa at intertidal and shallow subtidal elevations. This work aims to understand the mechanisms behind the resilience of this species to gradual sea level rise by studying its acclimation capacity to depth along the shallow littoral, and therefore, to gradual variations in the light environment. To address this objective, these populations have been monitored seasonally over a 10 year period, representing the longest seasonal database available in the literature for this species. The monitoring included populations at 0.4, − 0.08 and − 0.5 m LAT. The results show that C. nodosa has a strong seasonality for demographic and shoot dynamic properties – with longer shoots and larger growth in summer (high temperature) than in winter (low temperature), but also some losses. Moreover, shoots have different leaf morphometry depending on depth, with small and dense shoots in the intertidal areas (0.4 m) and sparse large shoots in the subtidal ones (− 0.08 and 0.5 m). These differences in morphometry and shoot dynamic properties, combined with the differences in shoot density, explain the lack of differences in meadow production balance (i.e. meadow growth – meadow losses) between the intertidal (0.4 m) and the deepest population (− 0.5 m), supporting the long term resilience of Cymodocea nodosa in Cadiz Bay. This study contributes to the understanding of the mechanisms behind seagrass stability and resilience, which is particularly important towards predicting the effects of climate change on these key coastal ecosystems, and also highlights the value of continuous long-term monitoring efforts to evaluate seagrass trajectories. info:eu-repo/semantics/publishedVersion

Historical contingency, such as the order of species arrival, can modify competitive outcomes via niche modification or preemption. However how these mechanisms ultimately modify stabilising niche and average fitness differences remains largely unknown. By experimentally assembling two congeneric spider mite species feeding on tomato plants during two generations, we show that order of arrival interacts with species’ competitive ability to determine competitive outcomes. Contrary to expectations, we did not observe that order of arrival cause priority effects. In fact, coexistence was predicted when the inferior competitor (Tetranychus urticae) arrived first. In that case, T. urticae colonized the preferred feeding stratum (leaves) of T. evansi leading to spatial niche preemption, which equalized fitness but also increased niche differences, driving community assembly to a close-to-neutrality scenario. Our study demonstrates how the spatial context of competitive interactions interact with species competitive ability to influence the effect of order of arrival on species coexistence.

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, MINECO (RYC-2017-23666) RTI2018-098888-A-I00, MICINN (RTI2018-098888-A-I00)

Pollination plays a central role both in the maintenance of biodiversity and in crop production. However, habitat loss, pesticides, invasive species, and larger environmental fluctuations are contributing to a dramatic decline of numerous pollinators world-wide. This has increased the need for interventions to protect the composition, functioning, and dynamics of pollinator communities. Yet, how to make these interventions successful at the system level remains extremely challenging due to the complex nature of species interactions and the various unknown or unmeasured confounding ecological factors. Here, we propose that this knowledge can be derived by following a probabilistic causal analysis of pollinator communities. This analysis implies the inference of interventional expectations from the integration of observational and synthetic data. We propose that such synthetic data can be generated using theoretical models that can enable the tractability and scalability of unseen confounding ecological factors affecting the behavior of pollinator communities. We discuss a road map for how this probabilistic causal analysis can be accomplished to increase our system-level causative knowledge of natural communities.

QUESTION: Do invasions by alien plant species with contrasting trait profiles (Arctotheca calendula, Carpobrotus spp., Conyza bonariensis and Opuntia dillenii) change the functional and phylogenetic structure of coastal plant communities? LOCATION: Atlantic coastal habitats in Huelva (Spain). METHODS: We identified species diversity and composition in 220 paired (invaded and non‐invaded) plots along the coast (440 plots in total). We measured nine functional traits for every native and invader species, namely, specific leaf area (SLA), specific root length (SRL), leaf and root dry mass content (LDMC and RDMC) and carbon isotope fraction (δ¹³C). We calculated, at the plot scale, community means (CMs) for each trait, functional richness, Faith's phylogenetic diversity and functional and phylogenetic mean pairwise dissimilarities. RESULTS: Three out the four species showed rather extreme trait values compared to the native flora with greater impact on invaded communities. In plots invaded by A. calendula the values of the native communities of SLA and SRL increased, while LDMC, RDMC and δ¹³C decreased showing CMs more similar to its functional profile. Besides, these plots showed lower functional and phylogenetic diversity in the native component of the community. In plots invaded by Carpobrotus spp. and O. dillenii the CMs values for LDMC and δ¹³C increased, but have little effect on the functional and phylogenetic structure of the native communities, while no differences were observed for the communities invaded by C. bonariensis (the most functionally similar to the native species). CONCLUSIONS: Our study highlights that inferring community assembly rules from the exploration of functional and phylogenetic differences between invaded and non‐invaded plots is not straightforward. By considering invaders with different functional profiles, we have shown that species with different mechanisms of invasion have contrasting impacts on the community. Consequently, the effect of plant invaders differs depending on their functional distinction from the recipient community, rather than their phylogenetic origin.

La acción COST NNEXT ha financiado el coste para publicar este artículo en abierto, por lo que aparece en la web de la revista como acceso abierto: https://onlinelibrary.wiley.com/doi/full/10.1111/brv.12511, Non-native tree (NNT) species have been transported worldwide to create or enhance services that are fundamental for human well-being, such as timber provision, erosion control or ornamental value; yet NNTs can also produce undesired effects, such as fire proneness or pollen allergenicity. Despite the variety of effects that NNTs have on multiple ecosystem services, a global quantitative assessment of their costs and benefits is still lacking. Such information is critical for decision-making, management and sustainable exploitation of NNTs. We present here a global assessment of NNT effects on the three main categories of ecosystem services, including regulating (RES), provisioning (PES) and cultural services (CES), and on an ecosystem disservice (EDS), i.e. pollen allergenicity. By searching the scientific literature, country forestry reports, and social media, we compiled a global data set of 1683 case studies from over 125 NNT species, covering 44 countries, all continents but Antarctica, and seven biomes. Using different meta-analysis techniques, we found that, while NNTs increase most RES (e.g. climate regulation, soil erosion control, fertility and formation), they decrease PES (e.g. NNTs contribute less than native trees to global timber provision). Also, they have different effects on CES (e.g. increase aesthetic values but decrease scientific interest), and no effect on the EDS considered. NNT effects on each ecosystem (dis)service showed a strong context dependency, varying across NNT types, biomes and socio-economic conditions. For instance, some RES are increased more by NNTs able to fix atmospheric nitrogen, and when the ecosystem is located in low-latitude biomes; some CES are increased more by NNTs in less-wealthy countries or in countries with higher gross domestic products. The effects of NNTs on several ecosystem (dis)services exhibited some synergies (e.g. among soil fertility, soil formation and climate regulation or between aesthetic values and pollen allergenicity), but also trade-offs (e.g. between fire regulation and soil erosion control). Our analyses provide a quantitative understanding of the complex synergies, trade-offs and context dependencies involved for the effects of NNTs that is essential for attaining a sustained provision of ecosystem services., Ministerio de Ciencia y Competitividad, Comunidad de Madrid

Plant-pollinator networks are a widely used tool to understand the dynamics of such ecological communities. However, while most mutualistic networks have been defined at the species level, ecological processes, such as pollination, take place at the individual level. This recognition has led to the development of individual plant-level networks, yet current approaches only account for individuals of a single plant species due to conceptual and mathematical limitations. Here, we introduce a mechanistic multilayer framework based on the frequency of insect visits to plant individuals belonging to different species. It is designed to depict from the network structure the potential conspecific and heterospecific pollen flows among plant individuals. Pollen transfer is modeled as a transport-like system, where pollen grains are represented as random-walkers that diffuse on an ensemble of bipartite layers of conspecific plants and their floral visitors that are coupled through shared visitors. With this physical conceptualization, we investigate how the number of developed seeds of plant individuals is affected by the multilayer structure (network-level), as well as by their local network properties (motif- and node-level). We apply this multiscale analysis to a dataset of nine plant-pollinator networks from a Mediterranean grassland. At the network-level we show a highly modular structure, with insect visitors effectively connecting individuals of the same and different plant species. Interestingly, the network structure is critical for modulating individual plant reproduction for the three most attractive species. In particular, the motif-level, represented by the number of homospecific and heterospecific motifs, is the best descriptor of plant reproductive success, as it integrates local heterospecific and conspecific interactions. We provide a simple, but robust set of metrics to scale down network ecology to functioning properties at the individual level, where most ecological processes take place, hence moving forward the description and interpretation of multitrophic communities across scales.

Direct 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.

7 figuras.- 1 tablas.- referencias.- Data and associated code to reproduce the results are stored in Figshare (https://figshare.com/s/6ad186835f2ce6527ffa). Data is currently under embargo and it will be released upon publication. Nonetheless, data can be available under reviewer request if needed., Litter decomposition is a fundamental process for nutrient cycling and C fluxes between terrestrial ecosystems and the atmosphere. Multiple factors such as environmental conditions, litter quality, and decomposer organisms are known to influence this ecological process in direct and indirect ways. However, it remains poorly understood to what extent this entangled bank of complex interactions can be disrupted by several global change drivers such as climate change and invasive species. Here we report main findings from a litter decomposition experiment conducted in a natural mixed forest invaded by Phytophthora cinnamomi, an exotic oomycete well-known for causing tree disease and forest decline. In two Mediterranean forest types (namely woodland and closed forest), we first built a rainfall exclusion infrastructure to reduce natural precipitation by 30 %. Then, we followed the spatial variation in C and N leaf litter dynamics as well as the abundance of the exotic oomycete P. cinnamomi during 18 months under both control and rainfall exclusion conditions using a litter bag methodology with different mesh sizes to further evaluate the indirect role of mesofauna abundance and diversity in litter C and N temporal dynamics. Significant reductions in soil moisture produced by the experimental rainfall exclusion increased directly C litter loss with time, and indirectly via increases in overall mesofauna abundance and changes in the ratio between predators and decomposers. N litter dynamics were in contrast modulated mainly by initial litter quality. Surprisingly, P. cinnamomi abundance did not correlate with variation in initial litter quality as previously suggested, but we found that the exotic oomycete was negatively correlated with both decomposer and predator abundances. These results suggest it might participate indirectly in litter decomposition dynamics through the biotic soil component. Synthesis: Contrary to expected, our results show that a moderate but realistic rainfall reduction can accelerate the litter decomposition process. It also points out to litter fauna as a key component modulating the indirect impacts of global change drivers on litter decomposition., This study was funded by the MICINN projects INTERCAPA (CGL2014-56739-R) and MICROFUN (RTI2018-094394-B-I00). PH was supported by a FPI-MICINN grant. LM was supported by the fellowship IV2 from VI-PPIT (Univ. Sevilla) and the project PID2019-108288RA-I00 (MINECO). OG acknowledges financial support provided by the Spanish Ministry of Economy and Competitiveness (MINECO) and by the European Social Fund through the Ramón y Cajal Program (RYC-2017-23666)

Urban parks and gardens provide cultural and aesthetic services critical for human well-being. Yet, they represent one of the main reasons for the intentional introduction of ornamental species, some of which can escape and establish in natural ecosystems. Besides aesthetic reasons, climate and socioeconomic factors can also modulate which species are planted in urban parks. Here, we evaluate the relationship between traits of 486 ornamental woody species from 46 Spanish urban parks and climatic and socioeconomic variables. We specifically assessed how plant traits, climatic, and socioeconomic factors are related to the proportion of non-native species and, among them, to the proportion of established non-native species in Spain. Overall, we found clear associations between species traits and climatic variables. Most notably, parks with warmer winters have more plant species with conspicuous flowers, whereas parks with colder winters and a more continental climate have more species with higher tolerances to cold and shade. Most of the species recorded in our study are non-native (82 %). Higher proportions of non-native species in urban parks were positively associated with towns with large size homes and inhabitants with higher median age but negatively related to parks with species with a higher hardiness-zone range. Moreover, a greater proportion of non-native species that can establish in the natural ecosystems was found in parks with lower continentality conditions. Our results show that Spanish urban parks have an overwhelming proportion of non-native woody species, some of which have the potential to establish, and that the variation in their proportions can be explained by climatic, and socioeconomic factors.

The growing demand for timber and the boom in massive tree-planting programs could mean the spreading of mismanaged tree plantations worldwide. Here, we apply the concept of ecological intensification to forestry systems as a viable biodiversity-focused strategy that could be critical to develop productive, yet sustainable, tree plantations. Tree plantations can be highly productive if tree species are properly combined to complement their ecological functions. Simultaneously considering soil biodiversity and animal-mediated biocontrol will be critical to minimize the reliance on external inputs. Integrating genetic, functional, and demographic diversity across heterogeneous landscapes should improve resilience under climate change. Designing ecologically intensified plantations will mean breaking the timber productivity versus conservation dichotomy and assuring the maintenance of key ecosystem services at safe levels.

Climate and competition interact to affect species' performance, such as growth and survival, and help determine species distributions and coexistence. However, it is unclear how climatic conditions modulate frequency-dependent performance, that is, how performance changes as a species becomes locally rare or common. This is critical because declines in performance as a species becomes more common (negative frequency dependence) is a signature of niche differences among species that stabilize coexistence, whereas positive frequency dependence leads to priority effects and hampers species coexistence. Here, we used dendrochronology and hierarchical models to test whether frequency-dependent growth of sugar pine (Pinus lambertiana) depends on climatic conditions. We found that growth rates were strongly dependent on annual precipitation, but no frequency dependence was evident across all years. However, there was a strong interaction between precipitation and frequency dependence, revealing stabilizing niche differences in dry years but positive frequency dependence in wet years. These differences emerged because of precipitation-driven changes in the direction and strength of both con- and heterospecific competition. Overall, these results show how stabilizing and destabilizing effects can be temporally dynamic for long-lived species and interact with climate variation.

9 páginas.-- 2 figuras.-- 4 tablas.-- 70 referencias.-- Material suplementario.-- Vaz, Ana S. et al..., Limitations in the assessment of cultural ecosystem services through quantifiable approaches have constrained our knowledge of how these services can be altered by drivers of global change, such as non-native tree species. Here, we address this caveat by evaluating the effects of non-native tree species, in comparison to native ones, on several categories of cultural services, i.e., recreation and ecotourism, aesthetics, inspiration, and cultural heritage. We propose an indicator-based approach that includes the use of a meta-analysis statistics, the odds ratio, to evaluate photographic, internet and catalogue data, and to infer on the effects of non-native trees on cultural services. We apply our approach to the Iberian Peninsula, exploring potential environmental and socio-economic predictors of non-native tree effects across NUTS-2 administrative regions. Overall, non-native tree effects differed among categories of cultural services and varied with the data type. Non-native trees increased recreation and ecotourism services, when considering data from official tourism entities, but not from nature route users. Data from inventories of urban parks and catalogues of ornamental plant dealers suggested that non-native trees decreased aesthetics services, particularly in Spain, but not in Portugal. Non-native trees also increased cultural heritage services, but no significant effects were observed on inspiration services. Overall, non-native trees showed higher increases in cultural services across regions with lower levels of development (in terms of income, employment and education) and life satisfaction. We suggest that management should emphasise awareness on non-native trees, including the risks involved in promoting the expansion of potentially invasive species. Efforts to raise awareness should prioritise official tourism entities and ornamental plant dealers, with a special focus on less developed regions. Our proposed approach represents a pioneer assessment of the relations between non-native trees and cultural ecosystem services, supporting strategic management in Iberia. The focus on widely available data sources enables reproducibility and application in assessments worldwide, Funding: A. S. Vaz was supported by the FSE/MEC and FCT (PhD grant PD/BD/52600/2014); J.R. Vicente by POPH/FSE and FCT (Post-Doc grant SFRH/BPD/84044/2012); O. Godoy by EUH2020 research and innovation program (Marie Sklodowska-Curie grant agreement No 661118-BioFUNC); Á. Bayon by Plan Estatal I+D+i (Spain) and ESF through a pre-doctoral contract. This work was supported by the FPS COST ActionFP1403 NNEXT: Non-native tree species for European forests − experiences, risks and opportunities, and TD1209 AlienChallenge: European Information System for Alien Species; and by the IMPLANTIN project (CGL2015-65346-R) of the Ministerio de Economía y Competitividad of Spain, and the REMEDINAL3-CM MAE-2719 network (Comunidad de Madrid).

Recent developments in modern coexistence theory (MCT) have advanced our understanding of how species interactions among themselves and with the environment influence community dynamics. Although the formulation of MCT is mathematically clear, its application to empirical cases is still challenging, which precludes its adoption by a large range of ecologists and evolutionary biologists interested in broad questions related to community assembly and the maintenance of species diversity. We developed cxr, an r package that provides a complete toolbox for calculating species vital rates and interaction parameters, from which the user can obtain estimates of coexistence outcomes based on stabilizing niche differences and average fitness differences. Our aim is to offer a highly versatile package to accommodate different research needs. This means that the user can define population models, use different optimization algorithms and include the effect of external covariates on species interactions, which may include environmental variables (e.g. temperature, precipitation, salinity) and biotic controls (e.g. predation, pollination, mycorrhizae). To illustrate the functionality and versatility of cxr, we provide a complete set of population dynamic models and a dataset from a highly diverse grassland community. By building bridges between MCT formulation and its implementation, we provide tools to obtain a deeper mechanistic understanding of how species interactions determine basic patterns such as species abundances and dominance, which are core information for many applied fields, such as conservation, restoration and invasion biology. Finally, the package is not limited taxonomically to any particular group. The application of tools derived from MCT to a wide range of different systems can create feedbacks between empirical and theoretical studies in a way that stimulates a better understanding of the processes maintaining biodiversity.

With ongoing biodiversity loss, it is important to understand how the mechanisms that promote coexistence relate to those that increase functioning in diverse communities. Both coexistence and biodiversity functioning research have unified their mechanisms into two classes. However, despite seeming similarities, theory suggests that coexistence and biodiversity mechanisms do not necessarily map onto each other, yet direct empirical evidence for this prediction is lacking. We coupled field-parameterized models of competition between 10 plants with a biodiversity-functioning experiment measuring biomass production, litter decomposition, and soil nutrient content under contrasting environmental conditions. We related biodiversity mechanisms (complementarity and selection effects), to coexistence mechanisms (niche and fitness differences). As predicted by theory, complementarity effects were positively correlated with niche differences and differences in selection effects were correlated with fitness differences. However, we also found that niche differences contributed to selection effects and fitness differences to complementarity effects. Despite this complexity more stably coexisting communities (i.e. those in which niche differences offset fitness differences) produced more biomass, particularly under drought. This relationship was weaker for litter decomposition rates and soil nutrient acquisition, showing that the mechanisms promoting plant coexistence may differ from those promoting high levels of functions that are less directly related to plant performance. We provide the first empirical evidence that the mechanisms promoting stable coexistence correlate with those driving high biomass production. These findings establish a link between stable coexistence and functioning, which could allow better predictions of how diversity loss induced by global change translates to changes in ecosystem function.

12 paginas.-- 1 figuras.-- 4 tablas.-- 59 referencias.-- Additional Supporting Information may be found in the online version of this article http://dx.doi.org/10.1111/geb.12511