Winfried Voigt

Bottom-up effects of plant diversity on multitrophic interactions in a biodiversity experiment

Biodiversity is rapidly declining, and this may negatively affect ecosystem processes, including economically important ecosystem services. Previous studies have shown that biodiversity has positive effects on organisms and processes across trophic levels. However, only a few studies have so far incorporated an explicit food-web perspective. In an eight-year biodiversity experiment, we studied an unprecedented range of above- and below-ground organisms and multitrophic interactions. A multitrophic data set originating from a single long-term experiment allows mechanistic insights that would not be gained from meta-analysis of different experiments. Here we show that plant diversity effects dampen with increasing trophic level and degree of omnivory. This was true both for abundance and species richness of organisms. Furthermore, we present comprehensive above-ground/below-ground biodiversity food webs. Both above ground and below ground, herbivores responded more strongly to changes in plant diversity than did carnivores or omnivores. Density and richness of carnivorous taxa was independent of vegetation structure. Below-ground responses to plant diversity were consistently weaker than above-ground responses. Responses to increasing plant diversity were generally positive, but were negative for biological invasion, pathogen infestation and hyperparasitism. Our results suggest that plant diversity has strong bottom-up effects on multitrophic interaction networks, with particularly strong effects on lower trophic levels. Effects on higher trophic levels are indirectly mediated through bottom-up trophic cascades.

TROPHIC LEVELS ARE DIFFERENTIALLY SENSITIVE TO CLIMATE

Predicting the response of communities to climate change is a major challenge for ecology. Communities may well not respond as entities but be disrupted, particularly if trophic levels respond differently, but as yet there is no evidence for differential responses from natural systems. We therefore analyzed unusually detailed plant and animal data collected over 20 years from two grassland communities to determine whether functional group climate sensitivity differed between trophic levels. We found that sensitivity increases significantly with increasing trophic level. This differential sensitivity would lead to community destabilization under climate change, not simple geographical shifts, and consequently must be incorporated in predictive ecological climate models.

Global decomposition experiment shows soil animal impacts on decomposition are climate-dependent

Climate and litter quality are primary drivers of terrestrial decomposition and, based on evidence from multisite experiments at regional and global scales, are universally factored into global decomposition models. In contrast, soil animals are considered key regulators of decomposition at local scales but their role at larger scales is unresolved. Soil animals are consequently excluded from global models of organic mineralization processes. Incomplete assessment of the roles of soil animals stems from the difficulties of manipulating invertebrate animals experimentally across large geographic gradients. This is compounded by deficient or inconsistent taxonomy. We report a global decomposition experiment to assess the importance of soil animals in C mineralization, in which a common grass litter substrate was exposed to natural decomposition in either control or reduced animal treatments across 30 sites distributed from 43°S to 68°N on six continents. Animals in the mesofaunal size range were recovered from the litter by Tullgren extraction and identified to common specifications, mostly at the ordinal level. The design of the trials enabled faunal contribution to be evaluated against abiotic parameters between sites. Soil animals increase decomposition rates in temperate and wet tropical climates, but have neutral effects where temperature or moisture constrain biological activity. Our findings highlight that faunal influences on decomposition are dependent on prevailing climatic conditions. We conclude that (1) inclusion of soil animals will improve the predictive capabilities of region- or biome-scale decomposition models, (2) soil animal influences on decomposition are important at the regional scale when attempting to predict global change scenarios, and (3) the statistical relationship between decomposition rates and climate, at the global scale, is robust against changes in soil faunal abundance and diversity.

Defoliation and patchy nutrient return drive grazing effects on plant and soil properties in a dairy cow pasture

Large herbivores can influence plant and soil properties in grassland ecosystems, but especially for belowground biota and processes, the mechanisms that explain these effects are not fully understood. Here, we examine the capability of three grazing mechanisms - plant defoliation, dung and urine return, and physical presence of animals (causing trampling and excreta return in patches) - to explain grazing effects in Phleum pratense-F estuca pratensis dairy cow pasture in Finland. Comparison of control plots and plots grazed by cows showed that grazing maintained original plant-community structure, decreased shoot mass and root N and P concentrations, increased shoot N and P concentrations, and had an inconsistent effect on root mass. Among soil fauna, grazing increased the abundance of fungivorous nematodes and Aporrectodea earthworms and decreased the abundance of detritivorous enchytraeids and Lumbricus earthworms. Grazing also increased soil density and pH but did not affect average soil inorganic-N concentration. To reveal the mechanisms behind these effects, we analyzed results from mowed plots and plots that were both mowed and treated with a dung and urine mixture. This comparison revealed that grazing effects on plant attributes were almost entirely explained by defoliation, with only one partly explained by excreta return. Among belowground attributes, however, the mechanisms were more mixed, with effects explained by defoliation, patchy excreta return, and cow trampling. Average soil inorganic-N concentration was not affected by grazing because it was simultaneously decreased by defoliation and increased by cow presence. Presence of cows created great spatial heterogeneity in soil N availability and abundance of fungivorous nematodes. A greenhouse trial revealed a grazing-induced soil feedback on plant growth, which was explained by patchiness in N availability rather than changes in soil biota. Our results show that grazing effects on plant attributes can be satisfactorily predicted using the effects of defoliation, whereas those on soil fauna and soil N availability need understanding of other mechanisms as well. The results indicate that defoliation-induced changes in plant ecophysiology and the great spatial variation in N availability created by grazers are the two key mechanisms through which large herbivores can control grassland ecosystems.

Diversity Promotes Temporal Stability across Levels of Ecosystem Organization in Experimental Grasslands

The diversity–stability hypothesis states that current losses of biodiversity can impair the ability of an ecosystem to dampen the effect of environmental perturbations on its functioning. Using data from a long-term and comprehensive biodiversity experiment, we quantified the temporal stability of 42 variables characterizing twelve ecological functions in managed grassland plots varying in plant species richness. We demonstrate that diversity increases stability i) across trophic levels (producer, consumer), ii) at both the system (community, ecosystem) and the component levels (population, functional group, phylogenetic clade), and iii) primarily for aboveground rather than belowground processes. Temporal synchronization across studied variables was mostly unaffected with increasing species richness. This study provides the strongest empirical support so far that diversity promotes stability across different ecological functions and levels of ecosystem organization in grasslands.

Distributional (in) congruence of Biodiversity-Ecosystem Functioning

The majority of research on biodiversity–ecosystem functioning in laboratories has concentrated on a few traits, but there is increasing evidence from the field that functional diversity controls ecosystem functioning more often than does species number. Given the importance of traits as predictors of niche complementarity and community structures, we (1) examine how the diversity sensu lato of forest trees, freshwater fishes and soil invertebrates might support ecosystem functioning and (2) discuss the relevance of productive biota for monophyletic assemblages (taxocenes). In terrestrial ecosystems, correlating traits to abiotic factors is complicated by the appropriate choice of body-size distributions. Angiosperm and gymnosperm trees, for example, show metabolic incongruences in their respiration rates despite their pronounced macroecological scaling. Scaling heterotrophic organisms within their monophyletic assemblages seems more difficult than scaling autotrophs: in contrast to the generally observed decline of mass-specific metabolic rates with body mass within metazoans, soil organisms such as protozoans show opposite mass-specific trends. At the community level, the resource demand of metazoans shapes multitrophic interactions. Hence, population densities and their food web relationships reflect functional diversity, but the influence of biodiversity on stability and ecosystem functioning remains less clear. We focused on fishes in 18 riverine food webs, where the ratio of primary versus secondary extinctions (hereafter, ‘extinction partitioning’) summarizes the responses of fish communities to primary species loss (deletions) and its consequences. Based on extinction partitioning, our high-diversity food webs were just as (or even more) vulnerable to extinctions as low-diversity food webs. Our analysis allows us to assess consequences of the relocation or removal of fish species and to help with decision-making in sustainable river management. The study highlights that the topology of food webs (and not simply taxonomic diversity) plays a greater role in stabilizing the food web and enhancing ecological services than is currently acknowledged.

Complexity of multitrophic interactions in a grassland ecosystem depends on plant species diversity

1. We studied the theoretical prediction that a loss of plant species richness has a strong impact on community interactions among all trophic levels and tested whether decreased plant species diversity results in a less complex structure and reduced interactions in ecological networks. 2. Using plant species-specific biomass and arthropod abundance data from experimental grassland plots (Jena Experiment), we constructed multitrophic functional group interaction webs to compare communities based on 4 and 16 plant species. 427 insect and spider species were classified into 13 functional groups. These functional groups represent the nodes of ecological networks. Direct and indirect interactions among them were assessed using partial Mantel tests. Interaction web complexity was quantified using three measures of network structure: connectance, interaction diversity and interaction strength. 3. Compared with high plant diversity plots, interaction webs based on low plant diversity plots showed reduced complexity in terms of total connectance, interaction diversity and mean interaction strength. Plant diversity effects obviously cascade up the food web and modify interactions across all trophic levels. The strongest effects occurred in interactions between adjacent trophic levels (i.e. predominantly trophic interactions), while significant interactions among plant and carnivore functional groups, as well as horizontal interactions (i.e. interactions between functional groups of the same trophic level), showed rather inconsistent responses and were generally rarer. 4. Reduced interaction diversity has the potential to decrease and destabilize ecosystem processes. Therefore, we conclude that the loss of basal producer species leads to more simple structured, less and more loosely connected species assemblages, which in turn are very likely to decrease ecosystem functioning, community robustness and tolerance to disturbance. Our results suggest that the functioning of the entire ecological community is critically linked to the diversity of its component plants species.

Networking our way to better ecosystem service provision

The ecosystem services (EcoS) concept is being used increasingly to attach values to natural systems and the multiple benefits they provide to human societies. Ecosystem processes or functions only become EcoS if they are shown to have social and/or economic value. This should assure an explicit connection between the natural and social sciences, but EcoS approaches have been criticized for retaining little natural science. Preserving the natural, ecological science context within EcoS research is challenging because the multiple disciplines involved have very different traditions and vocabularies (common-language challenge) and span many organizational levels and temporal and spatial scales (scale challenge) that define the relevant interacting entities (interaction challenge). We propose a network-based approach to transcend these discipline challenges and place the natural science context at the heart of EcoS research.

Whole-plant trait spectra of North American woody plant species reflect fundamental ecological strategies

The adaptation of plant species to their biotic and abiotic environment is manifested in their traits. Suites of correlated functional traits may reflect fundamental tradeoffs and general plant strategies and hence represent trait spectra along which plant species can vary according to their respective strategies. However, the functional interpretation of these trait spectra requires the inspection of their relation to plant performance. We employed principle coordinate analysis (PCoA) to quantify fundamental whole-plant trait spectra based on 23 traits for 305 North American woody species that span boreal to subtropical climates. We related the major axes of PCoA to five measures of plant performance (i.e., growth rate, and tolerance to drought, shade, water-logging and fire) for all species and separately for gymnosperms and angiosperms. Across all species a unified gymnosperm-angiosperm trait spectrum (wood density, seed mass, rooting habit) is identified, which is correlated with drought tolerance. Apart from this, leaf type and specific leaf area (SLA) strongly separate gymnosperms from angiosperms. For gymnosperms, one trait spectrum emerges (seed mass, rooting habit), which is positively correlated with drought tolerance and inversely with shade tolerance, reflecting a tradeoff between these two strategies due to opposing trait characteristics. Angiosperms are functionally more diverse. The trait spectra related to drought tolerance and shade tolerance are decoupled and three distinct strategies emerge: high drought tolerance (low SLA, dense wood, heavy seeds, taproot), high shade tolerance (high SLA, shallow roots, high toxicity, opposite arranged leaves), and fast growth/stress intolerance (large maximum heights, soft wood, light seeds, high seed spread rate). In summary, our approach reveals that complex suits of traits and potential tradeoffs underlie fundamental performance strategies in forests. Studies relying on small sets of plant traits may not be able to reveal such underlying strategies.

A spatiotemporal analysis of landscape change using an integrated Markov chain and cellular automata models

Spatially land-cover models are necessary for sustainable land-cover planning. The expansion of human-built land involves the destruction of forests, meadows and farmlands as well as conversion of these areas to urban and industrial areas which will result in significant effects on ecosystems. Monitoring the process of these changes and planning for sustainable use of land can be successfully achieved by using the remote sensing multi-temporal data, spatial criteria and predictor models. In this study, land-cover change analysis and modeling was performed for our study area in central Germany. An integrated Cellular Automata–Markov Chain land change model was carried out to simulate the future landscape change during the period of 2020–2050. The predictive power of the model was successfully evaluated using Kappa indices. As a consequence, land change model predicts very well a continuing downward trend in grassland, farmland and forest areas, as well as a growing tendency in built-up areas. Hence, if the current trends of change continue regardless of the actions of sustainable development, drastic natural area decline will ensue. The results of this study can help local authorities to better understanding the current situation and possible future conditions as well as adopt appropriate strategies for management of land-cover. In this case, they can create a balance between urban development and environmental protection.