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The local abiotic and environmental conditions of a grass‐based farming system may influence the agricultural benefits of mixtures in comparison to pure stands. We investigated the effects of species identities and interactions between grass, legume, and herb species on dry matter yield and sward digestibility and explored how contrasting environments may affect these relationships. We established experimental plots across 11 mixtures and 4 monocultures of perennial ryegrass (Lolium perenne L.), chicory (Cichorium intybus L.), white clover (Trifolium repens L.), and red clover (Trifolium pratense L.) established at two seeding densities in two sites Brody and Szelejewo (Poland) and managed them over a 3‐year period. The two sites were close geographically and had similar climates, but differed in soil types (Luvisols and Cambisols, respectively). We confirmed that the annual DM yields were generally higher on Cambisols soil as compared to Luvisols soil; both individual species effects and species interaction strengths differed across the two contrasting environments. The predicted annual DM yield for the 4‐species mixtures in general gave comparable or higher yields compared to monocultures across the 3 years, with the mixtures giving around 10%–30% higher yields than the weighted average of the monocultures of the constituent species. Analysing the transgressive overyielding it turned out that there was no significant difference between the 4‐species mixtures and best performing monoculture. The benefits of species diversity in our study was greater on less productive site because we found larger overyielding of the 4‐species sward on the Luvisols soil than on the Cambisols soil. Additionally, the effect of mixtures composed by 4‐species increased the yield stability compared to monocultures in the 3‐year period of our study, particularly on Cambisols soil. Sward digestibility applied to average values did not differ much between sites with mixtures performing similarly to monocultures. The reason for that could have been the dynamics of sward botanical composition during study years shifted towards increased perennial ryegrass and decreased proportions of chicory in the sward as well as the observed phenomenon that the species in mixed swards progressed to successive growth stages more slowly than in pure sowing. [ABSTRACT FROM AUTHOR]

Background: Agricultural yields have increased continuously over the last few decades. However, a focus solely on production can harm the environment. Diversification of agriculture has been suggested to increase production and sustainability. Biodiversity experiments showed positive effects on ecosystems and productivity. However, application of these results to intensively managed grasslands has been questioned due to differences in plant species and management regimes. Research on whether diversity can benefit multifunctionality, that is, an integrated index of multiple ecosystem functions, under intensive management, is still scarce. Methods: To address this, we manipulated plant species richness from one to six species spanning three functional groups (legumes, herbs, and grasses) in intensively managed multispecies grassland leys and examined seven ecosystem functions. Results: We found that multifunctionality increased with functional group and species richness. Legume+herb mixtures showed high multifunctionality, while grass monocultures and mixtures with high proportions of grasses had low multifunctionality. Different plant species and plant communities drove different ecosystem functions. Legumes and herbs improved productivity and water availability, while grasses enhanced invasion resistance. These results indicate that multifunctionality and individual ecosystem functions can be promoted through targeted combinations of plants with complementary ecological traits. Conclusions: Plant diversity can improve multifunctionality also under intensive management, potentially benefitting agroeconomics and sustainability. [ABSTRACT FROM AUTHOR]

Biodiversity and ecosystem function (BEF) studies aim to understand how ecosystems respond to a gradient of species diversity. Generalised Diversity‐Interactions (DI) models are suitable for analysing the BEF relationship. These models relate an ecosystem function response of a community to the identity of the species in the community, their evenness (proportions) and interactions. The number of species in the community (richness) is included implicitly in a DI model.It is common in BEF studies to model an ecosystem function as a function of richness; while this can uncover trends in the BEF relationship, by definition, species diversity is broader than richness alone, and important patterns in the BEF relationship may remain hidden. Here, we introduce the DImodels R package for implementing DI models. We show how richness is mathematically equivalent to a simplified DI model under certain conditions, and illustrate how using the DI multidimensional definition of species diversity can provide deeper insight to the BEF relationship compared to traditional approaches.Using DI models can lead to considerably improved model fit over other methods; it does this by incorporating variation due to the multiple facets of species diversity. Predicting from a DI model is not limited to the study design points, the model can interpolate or extrapolate to predict for any species composition and proportions (assuming there is sufficient coverage of this space in the study design).Expressing the BEF relationship as a function of richness alone can be useful to capture overall trends. However, collapsing the multiple dimensions of species diversity to a single dimension (such as richness) can result in valuable ecological information being lost. DI modelling provides a framework to test the multiple components of species diversity in the BEF relationship. It facilitates uncovering a deeper ecological understanding of the BEF relationship and can lead to enhanced inference. The open‐source DImodels R package provides a user‐friendly way to implement this modelling approach. [ABSTRACT FROM AUTHOR]

There is a global requirement to improve the environmental sustainability of intensively managed grassland monocultures that rely on high rates of nitrogen fertiliser, which is associated with negative environmental impacts. Multi‐species grass–legume mixtures are a promising tool for stimulating both productivity and sustainability in intensively managed grasslands, but questions remain about the benefit of increasing the diversity of plant functional groups.We established a plot‐scale experiment that manipulated the diversity of plant communities from a six‐species pool comprising three functional groups: grasses, legumes and herbs (two species each). Communities were grown as monocultures, or mixtures of two to six species, following a simplex design. This allowed us to quantify species' identity effects and functional group interaction effects. To investigate the impact of severe weather events, main plots were split and two levels of water supply, 'rainfed' and a 2‐month experimental drought, were applied. Mineral nitrogen fertiliser was applied at 150 kg ha−1 year−1, and a Lolium perenne monoculture received 300 kg ha−1 year−1 (300N) as a highly fertilised comparison. Annual above‐ground biomass was measured for 2 years.We found a strong positive effect on yield due to functional group interactions. Multi‐species communities with three functional groups yielded more than the best‐performing monoculture over a large range of different relative abundances of the three functional groups. The highest diversity community outperformed the 300N L. perenne under rainfed conditions.Although species' monoculture yields were generally reduced by the experimental drought, the interaction effects were not affected by drought and remained sufficiently large for the six‐species mixture under drought to have similar yields to both the best‐performing monoculture and the 300N L. perenne under rainfed conditions.Synthesis and applications. Plant diversity can result in higher yields, mitigate the yield risks associated with extreme weather events and displace fertiliser inputs and their embedded greenhouse gas emissions. Multi‐species swards offer a practical, farm‐scale management action to enhance the sustainability of intensive grassland production. [ABSTRACT FROM AUTHOR]

Fluctuations in population abundances are often correlated through time across multiple locations, a phenomenon known as spatial synchrony. Spatial synchrony can exhibit complex spatial structures, termed 'geographies of synchrony', that can reveal mechanisms underlying population fluctuations. However, most studies have focused on spatial extents of 10s to 100s of kilometres, making it unclear how synchrony concepts and approaches should apply to dynamics at finer spatial scales.We used network analyses, multiple regression on similarity matrices, and wavelet coherence analyses to examine micro‐scale synchrony and geographies of synchrony, over distances up to 30 m, in a serpentine grassland plant community.We found that species' populations exhibited a geography of synchrony even over such short distances. Often, well‐synchronized populations were geographically separate, a spatial structure that was shaped mainly by gopher disturbance and dispersal limitation, and to a lesser extent by relationships with other plant species. Precipitation was a significant driver of site‐ and community‐wide temporal dynamics. Gopher disturbance appeared to drive synchrony on 2‐ to 6‐year timescales, and we detected coherent fluctuations among pairs of focal plant taxa.Synthesis. Micro‐geographies of synchrony are an intriguing phenomenon that may also help us better understand community dynamics. Additionally, the related geographies of synchrony and coherent temporal dynamics among some species pairs indicate that incorporating interspecific interactions can improve understanding of population spatial synchrony. [ABSTRACT FROM AUTHOR]

Biodiversity and Ecosystem Function analyses aim to explain how individual species and their interactions affect ecosystem function. With this study, we asked in what ways do species interact, are these interactions affected by species planting pattern, and are initial (planted) proportions or previous year (realized) proportions a better reference point for characterizing grassland diversity effects?We addressed these questions with experimental communities compiled from a pool of 16 tallgrass prairie species. We planted all species in monocultures and mixtures that varied in their species richness, evenness, and spatial pattern. We recorded species‐specific biomass production over three growing seasons and fitted Diversity‐Interactions (DI) models to annual plot biomass yields.In the establishment season, all species interacted equally to form the diversity effect. In years 2 and 3, each species contributed a unique additive coefficient to its interaction with every other species to form the diversity effect. These interactions were affected by Helianthus maximiliani and the species planting pattern. Models based on species planted proportions better‐fit annual plot yield than models based on species previous contributions to plot biomass.Outcomes suggest that efforts to plant tallgrass prairies to maximize diversity effects should focus on the specific species present and in what arrangement they are planted. Furthermore, for particularly diverse grasslands, the effort of collecting annual species biomass data may not be necessary when quantifying diversity effects with DI models. [ABSTRACT FROM AUTHOR]

Uncovering the roles of biotic interactions in assembling and maintaining species‐rich communities remains a major challenge in ecology. In plant communities, interactions between individuals of different species are expected to generate positive or negative spatial interspecific associations over short distances. Recent studies using individual‐based point pattern datasets have concluded that (a) detectable interspecific interactions are generally rare, but (b) are most common in communities with fewer species; and (c) the most abundant species tend to have the highest frequency of interactions. However, it is unclear how the detection of spatial interactions may change with the abundances of each species, or the scale and intensity of interactions. We ask if statistical power is sufficient to explain all three key results.We use a simple two‐species model, assuming no habitat associations, and where the abundances, scale and intensity of interactions are controlled to simulate point pattern data. In combination with an approximation to the variance of the spatial summary statistics that we sample, we investigate the power of current spatial point pattern methods to correctly reject the null model of pairwise species independence.We show the power to detect interactions is positively related to both the abundances of the species tested, and the intensity and scale of interactions, but negatively related to imbalance in abundances. Differences in detection power in combination with the abundance distributions found in natural communities are sufficient to explain all the three key empirical results, even if all pairwise interactions are identical. Critically, many hundreds of individuals of both species may be required to detect even intense interactions, implying current abundance thresholds for including species in the analyses are too low.Synthesis. The widespread failure to reject the null model of spatial interspecific independence could be due to low power of the tests rather than any key biological process. Since we do not model habitat associations, our results represent a first step in quantifying sample sizes required to make strong statements about the role of biotic interactions in diverse plant communities. However, power should be factored into analyses and considered when designing empirical studies. Current methods for detecting plant–plant interactions from spatial data are very data hungry, possibly requiring hundreds of individuals of each species to be mapped before even strong interspecific interactions can be detected. With the knowledge of population abundances and the spatial scale of neighbourhood interactions, our approximation generates the statistical power of these tests for a range of interaction strengths. [ABSTRACT FROM AUTHOR]

It is now commonplace for community ecologists to infer assembly processes from the evolutionary relatedness of co‐occurring species. Such inferences, however, have typically depended on assembly theories that assume competitive equilibrium and that are species based. In reality, all natural communities are dynamic, particularly during the course of succession, and the ecological interactions which drive phylogenetic community structure actually occur among neighbouring individuals rather than species.To bridge this gap between theory and reality, we examine how colonisation, competition, and consequent replacement of individuals translate into phylogenetic community structure by using an individual‐based model. The model we use assumes a trade‐off between competition and colonisation abilities and that the points where species fall on the trade‐off curve are phylogenetically conserved.We find that the phylogenetic alpha diversity of a given community will be equal to or greater than the null expectation generated by randomly drawing individuals from communities at the same time step (i.e. phylogenetic overdispersion). This pattern results from the combination of interspecific differences in colonisation ability and neighbourhood competition that lead to individuals being regularly distributed in two‐dimensional space.We also show that phylogenetic beta diversity increases with increasing temporal differences between two communities. However, when this positive relationship is analysed only among the communities at close time steps, it becomes insignificant as they approach competitive equilibrium. We find similar patterns for functional alpha and beta diversity when phylogeny is replaced with functional traits.Synthesis. Though questions concerning community assembly have often been spatially framed, our model shows that the span of the time frame can also affect, or even reverse, inferences about assembly processes. Our model also implies that a shift in the frame of reference from species to individuals brings a new perspective to community assembly. Careful consideration of non‐equilibrium and individual‐level aspects provides better insights into the consequences of the evolutionary and functional similarities of individuals on community assembly. Using individual‐based models, we show that a shift in the frame of reference from species to individuals brings a new perspective to community assembly. We also find that the selected span of time frame can affect, or even reverse, inferences about assembly processes. Careful consideration of non‐equilibrium and individual‐level aspects provides better insights into the consequences of the evolutionary and functional similarities of individuals on community assembly. [ABSTRACT FROM AUTHOR]

ABSTRACT: Typical weather in Ireland provides conditions favourable for sustaining grass growth throughout most of the year. This affords grass based farming a significant economic advantage due to the low input costs associated with grass production. To optimize the productivity of grass based systems, farmers must manage the resource over short time scales. While research has been conducted into developing predictive grass growth models for Ireland to support on‐farm decision making, short term weather forecasts have not yet been incorporated into these models. To assess their potential for use in predictive grass growth models, deterministic forecasts from the European Centre for Medium‐Range Weather Forecasts (ECMWF) were verified for lead times up to 10 days using observations from 25 Irish weather stations. Forecasts of air temperature variables were generally precise at all lead times, particularly up to 7 days. Verification of ECMWF soil temperature forecasts is limited, but here they were shown to be accurate at all depths and most precise at greater depths such as 50 cm. Rainfall forecasts performed well up to approximately 5 days. Seven bias correction techniques were assessed to minimize systematic biases in the forecasts. Based on the root mean squared error values, no large improvement was identified for rainfall forecasts on equivalent ECMWF forecasts, but the optimum bias corrections improved air and soil temperature forecasts greatly. Overall, the results demonstrated that forecasts predict observations accurately up to approximately a week in advance and therefore could prove valuable in grass growth prediction at farm level in Ireland. [ABSTRACT FROM AUTHOR]

Abstract: Grassland diversity can support sustainable intensification of grassland production through increased yields, reduced inputs and limited weed invasion. We report the effects of diversity on weed suppression from 3 years of a 31‐site continental‐scale field experiment. At each site, 15 grassland communities comprising four monocultures and 11 four‐species mixtures based on a wide range of species' proportions were sown at two densities and managed by cutting. Forage species were selected according to two crossed functional traits, “method of nitrogen acquisition” and “pattern of temporal development”. Across sites, years and sown densities, annual weed biomass in mixtures and monocultures was 0.5 and 2.0 t  DM ha−1 (7% and 33% of total biomass respectively). Over 95% of mixtures had weed biomass lower than the average of monocultures, and in two‐thirds of cases, lower than in the most suppressive monoculture (transgressive suppression). Suppression was significantly transgressive for 58% of site‐years. Transgressive suppression by mixtures was maintained across years, independent of site productivity. Based on models, average weed biomass in mixture over the whole experiment was 52% less (95% confidence interval: 30%–75%) than in the most suppressive monoculture. Transgressive suppression of weed biomass was significant at each year across all mixtures and for each mixture. Weed biomass was consistently low across all mixtures and years and was in some cases significantly but not largely different from that in the equiproportional mixture. The average variability (standard deviation) of annual weed biomass within a site was much lower for mixtures (0.42) than for monocultures (1.77). Synthesis and applications. Weed invasion can be diminished through a combination of forage species selected for complementarity and persistence traits in systems designed to reduce reliance on fertiliser nitrogen. In this study, effects of diversity on weed suppression were consistently strong across mixtures varying widely in species' proportions and over time. The level of weed biomass did not vary greatly across mixtures varying widely in proportions of sown species. These diversity benefits in intensively managed grasslands are relevant for the sustainable intensification of agriculture and, importantly, are achievable through practical farm‐scale actions. [ABSTRACT FROM AUTHOR]

Perineal granulation tissue affects 2.7% of vaginal deliveries. Associated with nulliparity and instrumental delivery, it causes pain and delays recovery for new mothers. [ABSTRACT FROM AUTHOR]

Increased species diversity promotes ecosystem function; however, the dynamics of multi-species grassland systems over time and their role in sustaining higher yields generated by increased diversity are still poorly understood. We investigated the development of species' relative abundances in grassland mixtures over 3 years to identify drivers of diversity change and their links to yield diversity effects., A continental-scale field experiment was conducted at 31 sites using 11 different four-species mixtures each sown at two seed abundances. The four species consisted of two grasses and two legumes, of which one was fast establishing and the other temporally persistent. We modelled the dynamics of the four-species mixtures, and tested associations with diversity effects on yield., We found that species' dynamics were primarily driven by differences in the relative growth rates ( RGRs) of competing species, and secondarily by density dependence and climate. The temporally persistent grass species typically had the highest RGRs and hence became dominant over time. Density dependence sometimes induced stabilising processes on the dominant species and inhibited shifts to monoculture. Legumes persisted at most sites at low or medium abundances and persistence was improved at sites with higher annual minimum temperature., Significant diversity effects were present at the majority of sites in all years and the strength of diversity effects was improved with higher legume abundance in the previous year. Observed diversity effects, when legumes had declined, may be due to (i) important effects of legumes even at low abundance, (ii) interaction between the two grass species or (iii) a store of N because of previous presence of legumes., Synthesis. Alongside major compositional changes driven by RGR differences, diversity effects were observed at most sites, albeit at reduced strength as legumes declined. This evidence strongly supports the sowing of multi-species mixtures that include legumes over the long-standing practice of sowing grass monocultures. Careful and strategic selection of the identity of the species used in mixtures is suggested to facilitate the maintenance of species diversity and especially persistence of legumes over time, and to preserve the strength of yield increases associated with diversity. [ABSTRACT FROM AUTHOR]

Understanding the biodiversity and ecosystem function relationship can be challenging in species-rich ecosystems. Traditionally, species richness has been relied on heavily to explain changes in ecosystem function across diversity gradients. Diversity-Interactions models can test how ecosystem function is affected by species identity, species interactions, and evenness, in addition to richness. However, in a species-rich system, there may be too many species interactions to allow estimation of each coefficient, and if all interaction coefficients are estimable, they may be devoid of any sensible biological meaning. Parsimonious descriptions using constraints among interaction coefficients have been developed but important variability may still remain unexplained. Here, we extend Diversity-Interactions models to describe the effects of diversity on ecosystem function using a combination of fixed coefficients and random effects. Our approach provides improved standard errors for testing fixed coefficients and incorporates lack-of-fit tests for diversity effects. We illustrate our methods using data from a grassland and a microbial experiment. Our framework considerably reduces the complexities associated with understanding how species interactions contribute to ecosystem function in species-rich ecosystems. [ABSTRACT FROM AUTHOR]

Biodiversity is declining world-wide with detrimental effects on ecosystems. However, we lack a quantitative understanding of the shape of the relationship between microbial biodiversity and ecosystem function ( BEF). This limits our understanding of how microbial diversity depletion can impact key functions for human well-being, including pollutant detoxification., Three independent microcosm experiments were conducted to evaluate the direction (i.e. positive, negative or null) and the shape of the relationships between bacterial diversity and both broad (i.e. microbial respiration) and specialized (i.e. toxin degradation) functions in five Australian and two UK freshwater ecosystems using next-generation sequencing platforms., Reduced bacterial diversity, even after accounting for biomass, caused a decrease in broad (i.e. cumulative microbial respiration) and specialized (biodegradation of two important toxins) functions in all cases. Unlike the positive but decelerating BEF relationship observed most frequently in plants and animals, most evaluated functional measurements were related to bacterial diversity in a non-redundant fashion (e.g. exponentially and/or linearly)., Synthesis. Our results suggest that there is a lack of functional redundancy in the relationship between bacterial diversity and ecosystem functioning; thus, the consequences of declining microbial diversity on ecosystem functioning and human welfare have likely been considerably underestimated. [ABSTRACT FROM AUTHOR]

We investigate the consequences of global warming scenarios in Quebec forests using an inhomogeneous Markov chain model. This allows us to unify predictions from climate change models and mechanistic models of forest disturbance and growth and allows predicting the potential impacts of climate change on Quebec forests. The model predicts changes in fire rate in Quebec hardwood forests as well as possible growth enhancements due to increasing [ABSTRACT FROM AUTHOR]

A central issue of community ecology is finding rules that explain the composition and abundance of coexisting species. Nowadays two main processes, environmental filtering and limiting similarity, are thought to play the main roles in structuring communities. Their relative importance under different environmental conditions, however, is still not properly clarified., We studied the strength and the effect of environmental filtering (causing convergence) and limiting similarity (causing divergence) in 137 sample plots along an extremely long environmental gradient ranging from open sand grasslands to highly productive marshes, using a trait-based approach. The main environmental gradient (i.e. productivity) was characterized by the Normalized Difference Vegetation Index, an indicator of above-ground live biomass. Cover of the plant species was estimated visually. Values of 11 plant traits were collected from field measurements and data bases. Mean and dispersion of the trait values of the plots were quantified by community-weighted means and Rao's quadratic entropy. Trait convergence and divergence were tested by randomization tests, followed by the study of changes in effect size along the productivity gradient by fitting generalized additive mixed models ( GAMM)., For vegetative traits we found mainly convergence, indicating the filtering effect of environmental constraints, while traits related to regeneration showed divergence., The strength of convergence in vegetative traits generally decreased as productivity grew, indicating that while under harsh conditions environmental constraints strongly limit the possible trait values, under more benign conditions various water and nutrient use strategies are adaptable. At high productivity, the strength of divergence in regenerative traits decreased. Since the larger diversity of vegetative traits found here reduces competition, the importance of diverse reproductive strategy is probably lower., Synthesis. Our results partly support the stress-dominance hypothesis, but reveal that assembly rules are more complex. The relative importance of environmental filtering and limiting similarity depends on the trait and on the environmental conditions of the habitat. Traits related to resource use are generally limited by environmental filtering, and this restriction is weakening as conditions become more favourable, while traits related to regeneration are constrained by limiting similarity and are more diverse under harsh conditions. [ABSTRACT FROM AUTHOR]

Spatial processes have a major influence on the stability of species interaction networks and their resilience to environmental fluctuations. Here, we combine field observations and a dynamic model to understand how spatial processes may affect a network composed of the flowering plant Antirrhinum majus, its cohort of pollinators, and a specialist seed-predator and its parasitoid., The interactions taking place within this system were investigated by determining the fate of flowers and fruits on flowering and fruiting stems at 16 study sites. We then used this information to estimate spatial and temporal variation in the pollination rate, parasitism rate and hyperparasitism rate., We found that the plants were pollinator-limited, with relatively variable fruit-to-flower ratios across sites. On almost all sites, plants were both parasitized and hyperparasitized, at a low to moderate rate., Comparing our field observations with a tritrophic Nicholson-Bailey model, we found that empirical data are not always consistent with the conditions for local tritrophic persistence. This suggests that other mechanisms such as random disturbances and recolonizations (patch dynamics) or inter-site migration through metacommunity dynamics (source-sink dynamics) play a role in this system. Model simulations showed that dispersal could contribute to increasing tritrophic persistence in this system, and that source-sink structure, not just environmental stochasticity, may cause the observed pattern of spatial variation., Synthesis. We defined and measured metrics related to species interactions and densities. This led us to suggest that the functioning of the A. majus metacommunity is more consistent with source-sink than patch metacommunity dynamics, highlighting the extent to which dispersal explains the persistence of the system. [ABSTRACT FROM AUTHOR]

Most ecosystems provide multiple services, thus the impact of biodiversity losses on ecosystem functions may be considerably underestimated by studies that only address single functions. We propose a multivariate modelling framework for quantifying the relationship between biodiversity and multiple ecosystem functions (multifunctionality). Our framework consolidates the strengths of previous approaches to analysing ecosystem multifunctionality and contributes several advances. It simultaneously assesses the drivers of multifunctionality, such as species relative abundances, richness, evenness and other manipulated treatments. It also tests the relative importance of these drivers across functions, incorporates correlations among functions and identifies conditions where all functions perform well and where trade-offs occur among functions. We illustrate our framework using data from three ecosystem functions (sown biomass, weed suppression and nitrogen yield) in a four-species grassland experiment. We found high variability in performance across the functions in monocultures, but as community diversity increased, performance increased and variability across functions decreased. [ABSTRACT FROM AUTHOR]

Density- and distance-dependent ( DDD) mechanisms are important determinants of plant reproductive success ( PRS). Different components of sequential PRS can operate either in the same or in different directions and thus reinforce or neutralize each other, and they may also operate at different spatial scales. Thus, spatially explicit approaches are needed to detect such complex DDD effects across multiple PRS components and spatial scales., To reveal DDD effects of different components of early PRS of the Iberian pear ( Pyrus bourgaeana) sampled over three consecutive years, we used marked point pattern analysis. Our special interest is to identify conflicting processes that regulate populations at different spatial scales, for example whether DDD on fruit initiation and on fruit development acted in opposite directions. To evaluate the significance of observed mark correlation functions based on empirical data (e.g. fruiting success), we compared them to expectations given by spatially explicit null models., Diverse DDD processes affected several aspects of PRS in a variable extent over the three seasons. First, fruit initiation was higher for individuals with more neighbours at small distances (i.e. up to 40 m). However, P. bourgaeana fruit development decreased with increasing number of nearby neighbours, but these effects cancelled for overall fruit set that did not show DDD effects. Secondly, the absolute number of fruits produced (crop sizes) by trees showed positive density dependence in 2011 and 2012 but not in 2013. Finally, the total number of seeds produced did not show DDD effects, indicating that conflicting demographic processes can disrupt the initial spatial pattern of tree investment in reproduction., Synthesis. Understanding complex spatial effects of DDD processes requires dissection of component processes to attain the complete picture since contrasting DDD processes may be hidden behind a single cumulative measure of reproductive success. The combination of novel and classic mark correlation functions used here constitutes a powerful spatially explicit tool that can be broadly applied to unravel conflicting mechanisms of DDD regulating the persistence of sessile organisms at a range of spatial scales. Our findings help to explain why some authors failed to find expected DDD of PRS and highlight the importance of detailed multiyear field studies on plant reproductive success. [ABSTRACT FROM AUTHOR]

A coordinated continental-scale field experiment across 31 sites was used to compare the biomass yield of monocultures and four species mixtures associated with intensively managed agricultural grassland systems. To increase complementarity in resource use, each of the four species in the experimental design represented a distinct functional type derived from two levels of each of two functional traits, nitrogen acquisition ( N2-fixing legume or nonfixing grass) crossed with temporal development (fast-establishing or temporally persistent). Relative abundances of the four functional types in mixtures were systematically varied at sowing to vary the evenness of the same four species in mixture communities at each site and sown at two levels of seed density., Across multiple years, the total yield (including weed biomass) of the mixtures exceeded that of the average monoculture in >97% of comparisons. It also exceeded that of the best monoculture (transgressive overyielding) in about 60% of sites, with a mean yield ratio of mixture to best-performing monoculture of 1·07 across all sites. Analyses based on yield of sown species only (excluding weed biomass) demonstrated considerably greater transgressive overyielding (significant at about 70% of sites, ratio of mixture to best-performing monoculture = 1·18)., Mixtures maintained a resistance to weed invasion over at least 3 years. In mixtures, median values indicate <4% of weed biomass in total yield, whereas the median percentage of weeds in monocultures increased from 15% in year 1 to 32% in year 3., Within each year, there was a highly significant relationship ( P < 0·0001) between sward evenness and the diversity effect (excess of mixture performance over that predicted from the monoculture performances of component species). At lower evenness values, increases in community evenness resulted in an increased diversity effect, but the diversity effect was not significantly different from the maximum diversity effect across a wide range of higher evenness values. The latter indicates the robustness of the diversity effect to changes in species' relative abundances., Across sites with three complete years of data (24 of the 31 sites), the effect of interactions between the fast-establishing and temporal persistent trait levels of temporal development was highly significant and comparable in magnitude to effects of interactions between N2-fixing and nonfixing trait levels of nitrogen acquisition., Synthesis and applications. The design of grassland mixtures is relevant to farm-level strategies to achieve sustainable intensification. Experimental evidence indicated significant yield benefits of four species agronomic mixtures which yielded more than the highest-yielding monoculture at most sites. The results are relevant for agricultural practice and show how grassland mixtures can be designed to improve resource complementarity, increase yields and reduce weed invasion. The yield benefits were robust to considerable changes in the relative proportions of the four species, which is extremely useful for practical management of grassland swards. [ABSTRACT FROM AUTHOR]

The development of models of the relationship between biodiversity and ecosystem function ( BEF) has advanced rapidly over the last 20 years, incorporating insights gained through extensive experimental work. We propose Generalised Diversity- Interactions models that include many of the features of existing models and have several novel features. Generalised Diversity- Interactions models characterise the contribution of two species to ecosystem function as being proportional to the product of their relative abundances raised to the power of a coefficient θ., A value of θ < 1 corresponds to a stronger than expected contribution of species' pairs to ecosystem functioning, particularly at low relative abundance of species., Varying the value of θ has profound consequences for community-level properties of BEF relationships, including: (i) saturation properties of the BEF relationship; (ii) the stability of ecosystem function across communities; (iii) the likelihood of transgressive overyielding., For low values of θ, loss of species can have a much greater impact on ecosystem functioning than loss of community evenness., Generalised Diversity- Interactions models serve to unify the modelling of BEF relationships as they include several other current models as special cases., Generalised Diversity- Interactions models were applied to seven data sets and three functions: total biomass (five grassland experiments), community respiration (one bacterial experiment) and nitrate leaching (one earthworm experiment). They described all the nonrandom structure in the data in six experiments, and most of it in the seventh experiment and so fit as well or better than competing BEF models for these data. They were significantly better than Diversity-Interactions models in five experiments., Synthesis. We show that Generalized Diversity- Interactions models quantitatively integrate several methods that separately address effects of species richness, evenness and composition on ecosystem function. They describe empirical data at least as well as alternative models and improve the ability to quantitatively test among several theoretical and practical hypotheses about the effects of biodiversity levels on ecosystem function. They improve our understanding of important aspects of the relationship between biodiversity (evenness and richness) and ecosystem function ( BEF), which include saturation, effects of species loss, the stability of ecosystem function and the incidence of transgressive overyielding. [ABSTRACT FROM AUTHOR]

Biodiversity is an important determinant of primary productivity in experimental ecosystems. We combine two streams of research on understanding the effects of biodiversity on ecosystem function: quantifying phylogenetic diversity as a predictor of biodiversity effects in species-rich systems and the contribution of pairwise interspecific interactions to ecosystem function. We developed a statistical model that partitions the effect of biodiversity into effects due to community phylogenetic diversity and other community properties (e.g., average pairwise interaction, between- and within-functional-group effects, and so forth). The model provides phylogenetically based species-level explanations of differences in ecosystem response for communities with differing species composition. In two well-known grassland experiments, the model approach provides a parsimonious description of the effects of diversity as being due to the joint effect of the average pairwise statistical interaction and to community phylogenetic diversity. Effects associated with functional groupings of species in communities are largely explained by community phylogenetic diversity. The model approach quantifies a direct link between a measure of the evolutionary diversity of species and their interactive contribution to ecosystem function. It proves a useful tool in developing a mechanistic understanding of variation in ecosystem function. [ABSTRACT FROM AUTHOR]

Productive grasslands in temperate regions have relied strongly on low plant diversity with high management intensity and fertiliser inputs. Increasing plant diversity can provide high yields of digestible forage for livestock production with lower environmental impacts, and thus represents a diversity‐dependent nature‐based solution that can deliver multiple ecosystem functions. Sharing lessons from the design of managed, productive grassland communities, we address the following questions: how can we identify combinations of plant species that best deliver a selected function or multiple functions? and; when is community composition more important than species richness? We describe approaches that separate plant diversity into its underlying components: species richness, composition and relative abundance. Disentangling these three components facilitates a more nuanced understanding of how diversity can contribute to the design of diversity‐dependent nature‐based solutions. [ABSTRACT FROM AUTHOR]

Intensively managed grasslands are globally prominent ecosystems. We investigated whether experimental increases in plant diversity in intensively managed grassland communities can increase their resource use efficiency. This work consisted of a coordinated, continental-scale 33-site experiment. The core design was 30 plots, representing 15 grassland communities at two seeding densities. The 15 communities comprised four monocultures (two grasses and two legumes) and 11 four-species mixtures that varied in the relative abundance of the four species at sowing. There were 1028 plots in the core experiment, with another 572 plots sown for additional treatments. Sites followed a protocol and employed the same experimental methods with certain plot management factors, such as seeding rates and number of cuts, determined by local practice. The four species used at a site depended on geographical location, but the species were chosen according to four functional traits: a fast-establishing grass, a slow-establishing persistent grass, a fast-establishing legume, and a slow-establishing persistent legume. As the objective was to maximize yield for intensive grassland production, the species chosen were all highyielding agronomic species. The data set contains species-specific biomass measurements (yield per species and of weeds) for all harvests for up to four years at 33 sites. Samples of harvested vegetation were also analyzed for forage quality at 26 sites. These data should be of interest to ecologists studying relationships between diversity and ecosystem function and to agronomists interested in sustainable intensification. The large spatial scale of the sites provides opportunity for analyses across spatial (and temporal) scales. The database can also complement existing databases and meta-analyses on biodiversityecosystem function relationships in natural communities by focusing on those same relationships within intensively managed agricultural grasslands. [ABSTRACT FROM AUTHOR]