Multidimensional responses of grassland stability to eutrophication.

Eutrophication usually impacts grassland biodiversity, community composition, and biomass production, but its impact on the stability of these community aspects is unclear. One challenge is that stability has many facets that can be tightly correlated (low dimensionality) or highly disparate (high dimensionality). Using standardized experiments in 55 grassland sites from a globally distributed experiment (NutNet), we quantify the effects of nutrient addition on five facets of stability (temporal invariability, resistance during dry and wet growing seasons, recovery after dry and wet growing seasons), measured on three community aspects (aboveground biomass, community composition, and species richness). Nutrient addition reduces the temporal invariability and resistance of species richness and community composition during dry and wet growing seasons, but does not affect those of biomass. Different stability measures are largely uncorrelated under both ambient and eutrophic conditions, indicating consistently high dimensionality. Harnessing the dimensionality of ecological stability provides insights for predicting grassland responses to global environmental change.

Within-individual leaf trait variation increases with phenotypic integration in a subtropical tree diversity experiment.

Covariation of plant functional traits, that is, phenotypic integration, might constrain their variability. This was observed for inter- and intraspecific variation, but there is no evidence of a relationship between phenotypic integration and the functional variation within single plants (within-individual trait variation; WTV), which could be key to understand the extent of WTV in contexts like plant-plant interactions. We studied the relationship between WTV and phenotypic integration in c. 500 trees of 21 species in planted forest patches varying in species richness in subtropical China. Using visible and near-infrared spectroscopy (Vis-NIRS), we measured nine leaf morphological and chemical traits. For each tree, we assessed metrics of single and multitrait variation to assess WTV, and we used plant trait network properties based on trait correlations to quantify phenotypic integration. Against expectations, strong phenotypic integration within a tree led to greater variation across leaves. Not only this was true for single traits, but also the dispersion in a tree's multitrait hypervolume was positively associated with tree's phenotypic integration. Surprisingly, we only detected weak influence of the surrounding tree-species diversity on these relationships. Our study suggests that integrated phenotypes allow the variability of leaf phenotypes within the organism and supports that phenotypic integration prevents maladaptive variation.

Herbivory and nutrients shape grassland soil seed banks.

Anthropogenic nutrient enrichment and shifts in herbivory can lead to dramatic changes in the composition and diversity of aboveground plant communities. In turn, this can alter seed banks in the soil, which are cryptic reservoirs of plant diversity. Here, we use data from seven Nutrient Network grassland sites on four continents, encompassing a range of climatic and environmental conditions, to test the joint effects of fertilization and aboveground mammalian herbivory on seed banks and on the similarity between aboveground plant communities and seed banks. We find that fertilization decreases plant species richness and diversity in seed banks, and homogenizes composition between aboveground and seed bank communities. Fertilization increases seed bank abundance especially in the presence of herbivores, while this effect is smaller in the absence of herbivores. Our findings highlight that nutrient enrichment can weaken a diversity maintaining mechanism in grasslands, and that herbivory needs to be considered when assessing nutrient enrichment effects on seed bank abundance.

Restoration ecology through the lens of coexistence theory.

Advances in restoration ecology are needed to guide ecological restoration in a variable and changing world. Coexistence theory provides a framework for how variability in environmental conditions and species interactions affects species success. Here, we conceptually link coexistence theory and restoration ecology. First, including low-density growth rates (LDGRs), a classic metric of coexistence, can improve abundance-based restoration goals, because abundances are sensitive to initial treatments and ongoing variability. Second, growth-rate partitioning, developed to identify coexistence mechanisms, can improve restoration practice by informing site selection and indicating necessary interventions (e.g., site amelioration or competitor removal). Finally, coexistence methods can improve restoration assessment, because initial growth rates indicate trajectories, average growth rates measure success, and growth partitioning highlights interventions needed in future.

Light competition drives herbivore and nutrient effects on plant diversity.

Enrichment of nutrients and loss of herbivores are assumed to cause a loss of plant diversity in grassland ecosystems because they increase plant cover, which leads to a decrease of light in the understory1-3. Empirical tests of the role of competition for light in natural systems are based on indirect evidence, and have been a topic of debate for the last 40 years. Here we show that experimentally restoring light to understory plants in a natural grassland mitigates the loss of plant diversity that is caused by either nutrient enrichment or the absence of mammalian herbivores. The initial effect of light addition on restoring diversity under fertilization was transitory and outweighed by the greater effect of herbivory on light levels, indicating that herbivory is a major factor that controls diversity, partly through light. Our results provide direct experimental evidence, in a natural system, that competition for light is a key mechanism that contributes to the loss of biodiversity after cessation of mammalian herbivory. Our findings also show that the effects of herbivores can outpace the effects of fertilization on competition for light. Management practices that target maintaining grazing by native or domestic herbivores could therefore have applications in protecting biodiversity in grassland ecosystems, because they alleviate competition for light in the understory.

Linking changes in species composition and biomass in a globally distributed grassland experiment.

Global change drivers, such as anthropogenic nutrient inputs, are increasing globally. Nutrient deposition simultaneously alters plant biodiversity, species composition and ecosystem processes like aboveground biomass production. These changes are underpinned by species extinction, colonisation and shifting relative abundance. Here, we use the Price equation to quantify and link the contributions of species that are lost, gained or that persist to change in aboveground biomass in 59 experimental grassland sites. Under ambient (control) conditions, compositional and biomass turnover was high, and losses (i.e. local extinctions) were balanced by gains (i.e. colonisation). Under fertilisation, the decline in species richness resulted from increased species loss and decreases in species gained. Biomass increase under fertilisation resulted mostly from species that persist and to a lesser extent from species gained. Drivers of ecological change can interact relatively independently with diversity, composition and ecosystem processes and functions such as aboveground biomass due to the individual contributions of species lost, gained or persisting.

The potential of multispectral imaging flow cytometry for environmental monitoring.

Environmental monitoring involves the quantification of microscopic cells and particles such as algae, plant cells, pollen, or fungal spores. Traditional methods using conventional microscopy require expert knowledge, are time-intensive and not well-suited for automated high throughput. Multispectral imaging flow cytometry (MIFC) allows measurement of up to 5000 particles per second from a fluid suspension and can simultaneously capture up to 12 images of every single particle for brightfield and different spectral ranges, with up to 60x magnification. The high throughput of MIFC has high potential for increasing the amount and accuracy of environmental monitoring, such as for plant-pollinator interactions, fossil samples, air, water or food quality that currently rely on manual microscopic methods. Automated recognition of particles and cells is also possible, when MIFC is combined with deep-learning computational techniques. Furthermore, various fluorescence dyes can be used to stain specific parts of the cell to highlight physiological and chemical features including: vitality of pollen or algae, allergen content of individual pollen, surface chemical composition (carbohydrate coating) of cells, DNA- or enzyme-activity staining. Here, we outline the great potential for MIFC in environmental research for a variety of research fields and focal organisms. In addition, we provide best practice recommendations.

Temporal rarity is a better predictor of local extinction risk than spatial rarity.

Spatial rarity is often used to predict extinction risk, but rarity can also occur temporally. Perhaps more relevant in the context of global change is whether a species is core to a community (persistent) or transient (intermittently present), with transient species often susceptible to human activities that reduce niche space. Using 5-12 yr of data on 1,447 plant species from 49 grasslands on five continents, we show that local abundance and species persistence under ambient conditions are both effective predictors of local extinction risk following experimental exclusion of grazers or addition of nutrients; persistence was a more powerful predictor than local abundance. While perturbations increased the risk of exclusion for low persistence and abundance species, transient but abundant species were also highly likely to be excluded from a perturbed plot relative to ambient conditions. Moreover, low persistence and low abundance species that were not excluded from perturbed plots tended to have a modest increase in abundance following perturbance. Last, even core species with high abundances had large decreases in persistence and increased losses in perturbed plots, threatening the long-term stability of these grasslands. Our results demonstrate that expanding the concept of rarity to include temporal dynamics, in addition to local abundance, more effectively predicts extinction risk in response to environmental change than either rarity axis predicts alone.

Responses of plant diversity to precipitation change are strongest at local spatial scales and in drylands.

Mitigating and adapting to climate change requires an understanding of the magnitude and nature by which climate change will influence the diversity of plants across the world's ecosystems. Experiments can causally link precipitation change to plant diversity change, however, these experiments vary in their methods and in the diversity metrics reported, making synthesis elusive. Here, we explicitly account for a number of potentially confounding variables, including spatial grain, treatment magnitude and direction and background climatic conditions, to synthesize data across 72 precipitation manipulation experiments. We find that the effects of treatments with higher magnitude of precipitation manipulation on plant diversity are strongest at the smallest spatial scale, and in drier environments. Our synthesis emphasizes that quantifying differential responses of ecosystems requires explicit consideration of spatial grain and the magnitude of experimental manipulation. Given that diversity provides essential ecosystem services, especially in dry and semi-dry areas, our finding that these dry ecosystems are particular sensitive to projected changes in precipitation has important implications for their conservation and management.

Community change can buffer chronic nitrogen impacts, but multiple nutrients tip the scale.

Anthropogenic nitrogen (N) inputs are causing large changes in ecosystems worldwide. Many previous studies have examined the impact of N on terrestrial ecosystems; however, most have added N at rates that are much higher than predicted future deposition rates. Here, we present the results from a gradient of experimental N addition (0-10 g·N·m-2 ) in a temperate grassland. After a decade of N addition, we found that all levels of N addition changed plant functional group composition, likely indicating altered function for plant communities exposed to 10 yr of N inputs. However, N addition only had weak impacts on species composition and this functional group shift was not driven by any particular species, suggesting high levels of functional redundancy among grasslands species. Adding other nutrients (P, K, and micronutrients) in combination with N caused substantially greater changes in the relative abundance of species and functional groups. Together, these results suggest that compositional change within functional groups may buffer grasslands from impacts of N deposition, but concurrent eutrophication with other elements will likely lead to substantial changes in plant composition and biomass.

Beyond nitrogen: phosphorus - estimating the minimum niche dimensionality for resource competition between phytoplankton.

The niche dimensionality required for coexistence is often discussed in terms of the number of limiting resources. N and P limitation are benchmarks for studying phytoplankton interactions. However, it is generally agreed that limitation by small numbers of resources cannot explain the high phytoplankton diversity observed in nature. Here, we parameterised resource competition models using experimental data for six phytoplankton species grown in monoculture with nine potential limiting resources. We tested predicted species biomass from these models against observations in two-species experimental mixtures. Uptake rates were similar across species, following the classic Redfield ratio. Model accuracy levelled out at around three to five resources suggesting the minimum dimensionality of this system. The models included the resources Fe, Mg, Na and S. Models including only N and P always performed poorly. These results suggest that high-dimensional information about resource limitation despite stoichiometric constraints may be needed to accurately predict community assembly.

Phylogenetic and metabolic diversity have contrasting effects on the ecological functioning of bacterial communities.

Quantifying the relative contributions of microbial species to ecosystem functioning is challenging, because of the distinct mechanisms associated with microbial phylogenetic and metabolic diversity. We constructed bacterial communities with different diversity traits and employed exoenzyme activities (EEAs) and carbon acquisition potential (CAP) from substrates as proxies of bacterial functioning to test the independent effects of these two aspects of biodiversity. We expected that metabolic diversity, but not phylogenetic diversity would be associated with greater ecological function. Phylogenetically relatedness should intensify species interactions and coexistence, therefore amplifying the influence of metabolic diversity. We examined the effects of each diversity treatment using linear models, while controlling for the other, and found that phylogenetic diversity strongly influenced community functioning, positively and negatively. Metabolic diversity, however, exhibited negative or non-significant relationships with community functioning. When controlling for different substrates, EEAs increased along with phylogenetic diversity but decreased with metabolic diversity. The strength of diversity effects was related to substrate chemistry and the molecular mechanisms associated with each substrate's degradation. EEAs of phylogenetically similar groups were strongly affected by within-genus interactions. These results highlight the unique flexibility of microbial metabolic functions that must be considered in further ecological theory development.

Increasing effects of chronic nutrient enrichment on plant diversity loss and ecosystem productivity over time.

Human activities are enriching many of Earth's ecosystems with biologically limiting mineral nutrients such as nitrogen (N) and phosphorus (P). In grasslands, this enrichment generally reduces plant diversity and increases productivity. The widely demonstrated positive effect of diversity on productivity suggests a potential negative feedback, whereby nutrient-induced declines in diversity reduce the initial gains in productivity arising from nutrient enrichment. In addition, plant productivity and diversity can be inhibited by accumulations of dead biomass, which may be altered by nutrient enrichment. Over longer time frames, nutrient addition may increase soil fertility by increasing soil organic matter and nutrient pools. We examined the effects of 5-11 yr of nutrient addition at 47 grasslands in 12 countries. Nutrient enrichment increased aboveground live biomass and reduced plant diversity at nearly all sites, and these effects became stronger over time. We did not find evidence that nutrient-induced losses of diversity reduced the positive effects of nutrients on biomass; however, nutrient effects on live biomass increased more slowly at sites where litter was also increasing, regardless of plant diversity. This work suggests that short-term experiments may underestimate the long-term nutrient enrichment effects on global grassland ecosystems.

gauseR: Simple methods for fitting Lotka-Volterra models describing Gause's "Struggle for Existence".

Point 1: The ecological models of Alfred J. Lotka and Vito Volterra have had an enormous impact on ecology over the past century. Some of the earliest-and clearest-experimental tests of these models were famously conducted by Georgy Gause in the 1930s. Although well known, the data from these experiments are not widely available and are often difficult to analyze using standard statistical and computational tools. Point 2: Here, we introduce the gauseR package, a collection of tools for fitting Lotka-Volterra models to time series data of one or more species. The package includes several methods for parameter estimation and optimization, and includes 42 datasets from Gause's species interaction experiments and related work. Additionally, we include with this paper a short blog post discussing the historical importance of these data and models, and an R vignette with a walk-through introducing the package methods. The package is available for download at github.com/adamtclark/gauseR. Point 3: To demonstrate the package, we apply it to several classic experimental studies from Gause, as well as two other well-known datasets on multi-trophic dynamics on Isle Royale, and in spatially structured mite populations. In almost all cases, models fit observations closely and fitted parameter values make ecological sense. Point 4: Taken together, we hope that the methods, data, and analyses that we present here provide a simple and user-friendly way to interact with complex ecological data. We are optimistic that these methods will be especially useful to students and educators who are studying ecological dynamics, as well as researchers who would like a fast tool for basic analyses.

Resource-enhancing global changes drive a whole-ecosystem shift to faster cycling but decrease diversity.

Many global changes take the form of resource enhancements that have potential to transform multiple aspects of ecosystems from slower to faster cycling, including a suite of both above- and belowground variables. We developed a novel analytic approach to measure integrated ecosystem responses to resource-enhancing global changes, and how such whole ecosystem slow-to-fast transitions are linked to diversity and exotic invasions in real-world ecosystems. We asked how 5-yr experimental rainfall and nutrient enhancements in a natural grassland system affected 16 ecosystem functions, pools, and stoichiometry variables considered to indicate slow vs. fast cycling. We combined these metrics into a novel index we termed "slow-fast multifunctionality" and assessed its relationship to plant community diversity and exotic plant dominance. Nutrient and rainfall addition interacted to affect average slow-fast multifunctionality. Nutrient addition alone pushed the system toward faster cycling, but this effect weakened with the joint addition of rainfall and nutrients. Variables associated with soil nutrient pools and cycling most strongly contributed to this antagonistic interaction. Nutrient and water addition together, respectively, had additive or synergistic effects on plant trait composition and productivity, demonstrating divergence of above- and belowground ecosystem responses. Our novel metric of faster cycling was strongly associated with decreased plant species richness and increased exotic species dominance. These results demonstrate the breadth of interacting community and ecosystem changes that ensue when resource limitation is relaxed.

Thresholds for ecological responses to global change do not emerge from empirical data.

To understand ecosystem responses to anthropogenic global change, a prevailing framework is the definition of threshold levels of pressure, above which response magnitudes and their variances increase disproportionately. However, we lack systematic quantitative evidence as to whether empirical data allow definition of such thresholds. Here, we summarize 36 meta-analyses measuring more than 4,600 global change impacts on natural communities. We find that threshold transgressions were rarely detectable, either within or across meta-analyses. Instead, ecological responses were characterized mostly by progressively increasing magnitude and variance when pressure increased. Sensitivity analyses with modelled data revealed that minor variances in the response are sufficient to preclude the detection of thresholds from data, even if they are present. The simulations reinforced our contention that global change biology needs to abandon the general expectation that system properties allow defining thresholds as a way to manage nature under global change. Rather, highly variable responses, even under weak pressures, suggest that 'safe-operating spaces' are unlikely to be quantifiable.

Author Correction: Leaf nutrients, not specific leaf area, are consistent indicators of elevated nutrient inputs.

An amendment to this paper has been published and can be accessed via a link at the top of the paper.

Integrating the underlying structure of stochasticity into community ecology.

Stochasticity is a core component of ecology, as it underlies key processes that structure and create variability in nature. Despite its fundamental importance in ecological systems, the concept is often treated as synonymous with unpredictability in community ecology, and studies tend to focus on single forms of stochasticity rather than taking a more holistic view. This has led to multiple narratives for how stochasticity mediates community dynamics. Here, we present a framework that describes how different forms of stochasticity (notably demographic and environmental stochasticity) combine to provide underlying and predictable structure in diverse communities. This framework builds on the deep ecological understanding of stochastic processes acting at individual and population levels and in modules of a few interacting species. We support our framework with a mathematical model that we use to synthesize key literature, demonstrating that stochasticity is more than simple uncertainty. Rather, stochasticity has profound and predictable effects on community dynamics that are critical for understanding how diversity is maintained. We propose next steps that ecologists might use to explore the role of stochasticity for structuring communities in theoretical and empirical systems, and thereby enhance our understanding of community dynamics.

Understanding plant communities of the future requires filling knowledge gaps.

In their response to our letter, De Boek et al. (2019) and Muller, Ballhausen, Lakovic, and Rillig (2019) argue that our conclusion that we need more realistic climate change experiments is too "gloomy" and that we need a plurality of experiments including extremes and multifactorial approaches. We agree that a diversity of experimental approaches is required in order to anticipate the consequences for plant communities of alternative future environmental conditions. However, we argue that "realistic" experiments are underrepresented in the portfolio of previous experiments, and are urgently needed to understand how species communities of the future will look like and how they will function. This article is a response to Muller et al., 26, e4-e5 and De Boeck et al., 26, e6-e7.