Modelling the effect of belowground herbivory on grassland diversity

While shoot herbivores reduce, root herbivores increase nutrient enrichment's impact on diversity in a grassland model

Nutrient enrichment is widespread throughout grassland systems and expected to increase during the Anthropocene. Trophic interactions, like aboveground herbivory, have been shown to mitigate its effect on plant diversity. Belowground herbivory may also impact these habitats' response to nutrient enrichment, but its influence is much less understood, and likely to depend on factors such as the herbivores' preference for dominant species and the symmetry of belowground competition. If preferential toward the dominant, fastest growing species, root herbivores may reduce these species' relative fitness and support diversity during nutrient enrichment. However, as plant competition belowground is commonly considered to be symmetric, root herbivores may be less impactful than shoot herbivores because they do not reduce any competitive asymmetry between the dominant and subordinate plants. To better understand this system, we used an established, two-layer, grassland community model to run a full-factorially designed simulation experiment, crossing the complete removal of aboveground herbivores and belowground herbivores with nutrient enrichment. After 100 yr of simulation, we analyzed communities' diversity, competition on the individual level, as well as their resistance and recovery. The model reproduced both observed general effects of nutrient enrichment in grasslands and the short-term trends of specific experiments. We found that belowground herbivores exacerbate the negative influence of nutrient enrichment on Shannon diversity within our model grasslands, while aboveground herbivores mitigate its effect. Indeed, data on individuals' above- and belowground resource uptake reveals that root herbivory reduces resource limitation belowground. As with nutrient enrichment, this shifts competition aboveground. Since shoot competition is asymmetric, with larger, taller individuals gathering disproportionate resources compared to their smaller, shorter counterparts, this shift promotes the exclusion of the smallest species. While increasing the root herbivores' preferences toward dominant species lessens their negative impact, at best they are only mildly advantageous, and they do very little reduce the negative consequences of nutrient enrichment. Because our model's belowground competition is symmetric, we hypothesize that root herbivores may be beneficial when root competition is asymmetric. Future research into belowground herbivory should account for the nature of competition belowground to better understand the herbivores' true influence.

Simulation of herbicide impacts on a plant community: comparing model predictions of the plant community model IBC-grass to empirical data

BACKGROUND

Semi-natural plant communities such as field boundaries play an important ecological role in agricultural landscapes, e.g., provision of refuge for plant and other species, food web support or habitat connectivity. To prevent undesired effects of herbicide applications on these communities and their structure, the registration and application are regulated by risk assessment schemes in many industrialized countries. Standardized individual-level greenhouse experiments are conducted on a selection of crop and wild plant species to characterize the effects of herbicide loads potentially reaching off-field areas on non-target plants. Uncertainties regarding the protectiveness of such approaches to risk assessment might be addressed by assessment factors that are often under discussion. As an alternative approach, plant community models can be used to predict potential effects on plant communities of interest based on extrapolation of the individual-level effects measured in the standardized greenhouse experiments. In this study, we analyzed the reliability and adequacy of the plant community model IBC-grass (individual-based plant community model for grasslands) by comparing model predictions with empirically measured effects at the plant community level.

RESULTS

We showed that the effects predicted by the model IBC-grass were in accordance with the empirical data. Based on the species-specific dose responses (calculated from empirical effects in monocultures measured 4 weeks after application), the model was able to realistically predict short-term herbicide impacts on communities when compared to empirical data.

CONCLUSION

The results presented in this study demonstrate an approach how the current standard greenhouse experiments-measuring herbicide impacts on individual-level-can be coupled with the model IBC-grass to estimate effects on plant community level. In this way, it can be used as a tool in ecological risk assessment.

Novel model coupling approach for resilience analysis of coastal plant communities

Resilience is a major research focus covering a wide range of topics from biodiversity conservation to ecosystem (service) management. Model simulations can assess the resilience of, for example, plant species, measured as the return time to conditions prior to a disturbance. This requires process-based models (PBM) that implement relevant processes such as regeneration and reproduction and thus successfully reproduce transient dynamics after disturbances. Such models are often complex and thus limited to either short-term or small-scale applications, whereas many research questions require species predictions across larger spatial and temporal scales. We suggest a framework to couple a PBM and a statistical species distribution model (SDM), which transfers the results of a resilience analysis by the PBM to SDM predictions. The resulting hybrid model combines the advantages of both approaches: the convenient applicability of SDMs and the relevant process detail of PBMs in abrupt environmental change situations. First, we simulate dynamic responses of species communities to a disturbance event with a PBM. We aggregate the response behavior in two resilience metrics: return time and amplitude of the response peak. These metrics are then used to complement long-term SDM projections with dynamic short-term responses to disturbance. To illustrate our framework, we investigate the effect of abrupt short-term groundwater level and salinity changes on coastal vegetation at the German Baltic Sea. We found two example species to be largely resilient, and, consequently, modifications of SDM predictions consisted mostly of smoothing out peaks in the occurrence probability that were not confirmed by the PBM. Discrepancies between SDM- and PBM-predicted species responses were caused by community dynamics simulated in the PBM and absent from the SDM. Although demonstrated with boosted regression trees (SDM) and an existing individual-based model, IBC-grass (PBM), our flexible framework can easily be applied to other PBM and SDM types, as well as other definitions of short-term disturbances or long-term trends of environmental change. Thus, our framework allows accounting for biological feedbacks in the response to short- and long-term environmental changes as a major advancement in predictive vegetation modeling.

Potential impact of effects on reproductive attributes induced by herbicides on a plant community

Current herbicide risk assessment guidelines for nontarget terrestrial plants require testing effects on young, vulnerable life stages (i.e., seedling emergence [and subsequent growth] and vegetative vigor [growth and dry wt]) but not directly on the reproduction of plants. However, the European Food Safety Authority (EFSA) has proposed that effects on reproduction might be considered when evaluating the potential effects on plants. We adapted the plant community model for grassland (IBC-grass) to give insight into the current debate on the sensitivity of reproductive versus vegetative endpoints in ecological risk assessment. In an extensive sensitivity analysis of this model, we compared plant attributes potentially affected by herbicides and the consequences for long-term plant population dynamics and plant diversity. This evaluation was implemented by reducing reproductive as well as vegetative endpoints by certain percentages (e.g., 10-90%) as a theoretical assumption. Plant mortality and seed sterility (i.e., inability of seeds to germinate) were the most sensitive attributes. Our results indicated that effects on seed production at off-field exposure rates must be very strong to have an impact on the risk assessment. Otherwise, effects on seed production are compensated for by the soil seed bank. The present study highlights the usefulness of community level modeling studies to support regulators in their decisions on the appropriate risk assessment endpoints and provides confidence in their assessments. Environ Toxicol Chem 2018;37:1707-1722. © 2018 SETAC.

Community-Weighted Mean Plant Traits Predict Small Scale Distribution of Insect Root Herbivore Abundance

Small scale distribution of insect root herbivores may promote plant species diversity by creating patches of different herbivore pressure. However, determinants of small scale distribution of insect root herbivores, and impact of land use intensity on their small scale distribution are largely unknown. We sampled insect root herbivores and measured vegetation parameters and soil water content along transects in grasslands of different management intensity in three regions in Germany. We calculated community-weighted mean plant traits to test whether the functional plant community composition determines the small scale distribution of insect root herbivores. To analyze spatial patterns in plant species and trait composition and insect root herbivore abundance we computed Mantel correlograms. Insect root herbivores mainly comprised click beetle (Coleoptera, Elateridae) larvae (43%) in the investigated grasslands. Total insect root herbivore numbers were positively related to community-weighted mean traits indicating high plant growth rates and biomass (specific leaf area, reproductive- and vegetative plant height), and negatively related to plant traits indicating poor tissue quality (leaf C/N ratio). Generalist Elaterid larvae, when analyzed independently, were also positively related to high plant growth rates and furthermore to root dry mass, but were not related to tissue quality. Insect root herbivore numbers were not related to plant cover, plant species richness and soil water content. Plant species composition and to a lesser extent plant trait composition displayed spatial autocorrelation, which was not influenced by land use intensity. Insect root herbivore abundance was not spatially autocorrelated. We conclude that in semi-natural grasslands with a high share of generalist insect root herbivores, insect root herbivores affiliate with large, fast growing plants, presumably because of availability of high quantities of food. Affiliation of insect root herbivores with large, fast growing plants may counteract dominance of those species, thus promoting plant diversity.