• Energy Research

AbstractPlant–plant and plant–soil interactions can help maintain plant diversity and ecosystem functions. Changes in these interactions may underlie experimentally observed increases in biodiversity effects over time via the selection of genotypes adapted to low or high plant diversity. Little is known, however, about such community‐history effects and particularly the role of plant–soil interactions in this process. Soil‐legacy effects may occur if co‐evolved interactions with soil communities either positively or negatively modify plant biodiversity effects. We tested how plant selection and soil legacy influence biodiversity effects on productivity, and whether such effects increase the resistance of the communities to invasion by weeds. We used two plant selection treatments: parental plants growing in monoculture or in mixture over 8 yr in a grassland biodiversity experiment in the field, which we term monoculture types and mixture types. The two soil‐legacy treatments used in this study were neutral soil inoculated with live or sterilized soil inocula collected from the same plots in the biodiversity experiment. For each of the four factorial combinations, seedlings of eight species were grown in monocultures or four‐species mixtures in pots in an experimental garden over 15 weeks. Soil legacy (live inoculum) strongly increased biodiversity complementarity effects for communities of mixture types, and to a significantly weaker extent for communities of monoculture types. This may be attributed to negative plant–soil feedbacks suffered by mixture types in monocultures, whereas monoculture types had positive plant–soil feedbacks, in both monocultures and mixtures. Monocultures of mixture types were most strongly invaded by weeds, presumably due to increased pathogen susceptibility, reduced biomass, and altered plant–soil interactions of mixture types. These results show that biodiversity effects in experimental grassland communities can be modified by the evolution of positive vs. negative plant–soil feedbacks of plant monoculture vs. mixture types.

The consequences of plant species loss are rarely assessed in a multi-trophic context and especially effects on life-history traits of organisms at higher trophic levels have remained largely unstudied. We used a grassland biodiversity experiment and measured the effects of two components of plant diversity, plant species richness and the presence of nitrogen-fixing legumes, on several life-history traits of naturally colonizing aphids and their primary and secondary parasitoids in the field. We found that, irrespective of aphid species identity, the proportion of winged aphid morphs decreased with increasing plant species richness, which was correlated with decreasing host plant biomass. Similarly, emergence proportions of parasitoids decreased with increasing plant species richness. Both, emergence proportions and proportions of female parasitoids were lower in plots with legumes, where host plants had increased nitrogen concentrations. This effect of legume presence could indicate that aphids were better defended against parasitoids in high-nitrogen environments. Body mass of emerged individuals of the two most abundant primary parasitoid species was, however, higher in plots with legumes, suggesting that once parasitoids could overcome aphid defenses, they could profit from larger or more nutritious hosts. Our study demonstrates that cascading effects of plant species loss on higher trophic levels such as aphids, parasitoids and secondary parasitoids begin with changed life-history traits of these insects. Thus, life-history traits of organisms at higher trophic levels may be useful indicators of bottom-up effects of plant diversity on the biodiversity of consumers.

AbstractCurrent climate change is disrupting biotic interactions and eroding biodiversity worldwide. However, species sensitive to aridity, high temperatures, and climate variability might find shelter in microclimatic refuges, such as leaf rolls built by arthropods. To explore how the importance of leaf shelters for terrestrial arthropods changes with latitude, elevation, and climate, we conducted a distributed experiment comparing arthropods in leaf rolls versus control leaves across 52 sites along an 11,790 km latitudinal gradient. We then probed the impact of short‐ versus long‐term climatic impacts on roll use, by comparing the relative impact of conditions during the experiment versus average, baseline conditions at the site. Leaf shelters supported larger organisms and higher arthropod biomass and species diversity than non‐rolled control leaves. However, the magnitude of the leaf rolls’ effect differed between long‐ and short‐term climate conditions, metrics (species richness, biomass, and body size), and trophic groups (predators vs. herbivores). The effect of leaf rolls on predator richness was influenced only by baseline climate, increasing in magnitude in regions experiencing increased long‐term aridity, regardless of latitude, elevation, and weather during the experiment. This suggests that shelter use by predators may be innate, and thus, driven by natural selection. In contrast, the effect of leaf rolls on predator biomass and predator body size decreased with increasing temperature, and increased with increasing precipitation, respectively, during the experiment. The magnitude of shelter usage by herbivores increased with the abundance of predators and decreased with increasing temperature during the experiment. Taken together, these results highlight that leaf roll use may have both proximal and ultimate causes. Projected increases in climate variability and aridity are, therefore, likely to increase the importance of biotic refugia in mitigating the effects of climate change on species persistence.

Local habitat size has been shown to influence colonization and extinction processes of species in patchy environments. However, species differ in body size, mobility, and trophic level, and may not respond in the same way to habitat size. Thus far, we have a limited understanding of how habitat size influences the structure of multitrophic communities and to what extent the effects may be generalizable over a broad geographic range. Here, we used water‐filled bromeliads of different sizes as a natural model system to examine the effects of habitat size on the trophic structure of their inhabiting invertebrate communities. We collected composition and biomass data from 651 bromeliad communities from eight sites across Central and South America differing in environmental conditions, species pools, and the presence of large‐bodied odonate predators. We found that trophic structure in the communities changed dramatically with changes in habitat (bromeliad) size. Detritivore : resource ratios showed a consistent negative relationship with habitat size across sites. In contrast, changes in predator : detritivore (prey) ratios depended on the presence of odonates as dominant predators in the regional pool. At sites without odonates, predator : detritivore biomass ratios decreased with increasing habitat size. At sites with odonates, we found odonates to be more frequently present in large than in small bromeliads, and predator : detritivore biomass ratios increased with increasing habitat size to the point where some trophic pyramids became inverted. Our results show that the distribution of biomass amongst food‐web levels depends strongly on habitat size, largely irrespective of geographic differences in environmental conditions or detritivore species compositions. However, the presence of large‐bodied predators in the regional species pool may fundamentally alter this relationship between habitat size and trophic structure. We conclude that taking into account the response and multitrophic effects of dominant, mobile species may be critical when predicting changes in community structure along a habitat‐size gradient.

Alpine lakes support unique communities which may respond with great sensitivity to climate change. To understand the drivers of benthic macroinvertebrate community structure, samples were collected in the littoral of 28 lakes within Hohe Tauern National Park, Austria. Sampling took place from early July to early August 2018 between altitudes of 2,000 and 2,700 m a.s.l. The extent of habitat types in the lake littoral was estimated. Habitat types were classified into sediment (maximum grain size of 2 mm), small rocks (up to 20 cm x 15 cm x 5 cm), and large boulders/sheer rock faces. The extent of rocky habitats was calculated as the sum of areas covered by small rocks and boulders/sheer rock faces. A total area of 1 m² was sampled in each lake, using a hand net with a sharp frame (25 cm in width) and 500 µm mesh-size. Mixed samples were taken, covering each habitat type proportional to its extent in the lake (100% corresponding to 1 m²). For habitats covering up to 10% of the lake, a standardized area of 0.1 m² was sampled. In sediment, the uppermost 5 cm of the ground were scooped into the net by sweeping it swiftly through the sediment. When sampling large boulders or rock faces, a metal spatula was used to scrape macroinvertebrates off the surface and collect them in the net. Macroinvertebrates were brushed off small rocks using a toothbrush over water-filled trays. The dimensions of those small rocks were measured, and total surface area was calculated, assuming a suitable geometric form (ellipsoid or cuboid). Samples were presorted in the field and preserved in 4% formalin. After 3-4 weeks, all samples were rinsed in tap water and transferred to 70% ethanol for further storage. Identification was performed using a stereomicroscope (OLYMPUS SZX16, 11.2x-184x) to the lowest taxon possible. Lake size was determined by aerial photograph in Google Earth Pro. To do so, the outlines of the lakes were traced, and the area of the polygon then calculated. Physical and chemical water parameters were measured with a multi-parameter sonde (EXO2 YSI) (for lakes 1-18 from a boat, otherwise from a rock or by wading into the lake): water temperature (°C), dissolved oxygen (% saturation), conductivity (µS/m), pH, nitrate (mg/l), turbidity (FNU), blue-green algae phycocyanin (µg/l) and chlorophyll-a (µg/l). Maximum depth (m) was measured with a sonar by rowing up to 10 transects across lakes. Maximum depth was not measured for lakes 19-28. Two data loggers had been planted per lake in lakes 1-18 in the previous year and were recovered in 2018. Data loggers measured water temperature at about half a meter depth in six-hour intervals over an entire year. Ice-free days were deduced from available logger data, assuming an ice-cover at water temperatures below 2 °C (daily maximum temperature). Additionally, zoo- and phytoplankton samples were taken from the first 18 lakes. Zooplankton was sampled with vertical tows from the hypolimnion to the surface in deeper lakes, and with oblique tows in shallow lakes using a 29 cm diameter net with a 30 µm mesh size. Samples were then fixed in sucrose-formalin and counted under an Olympus SZX16 stereomicroscope equipped with a 0.7 – 11.5 zoom objective. Phytoplankton samples from lakes 1-18 were taken with a 1.2 L water sampler from the middle of the epilimnion, and when one was present, also from the deep chlorophyll maximum. Samples were fixed with Lugol's iodine and counted in sampling chambers with a Nikon TE2000 inverted microscope using a 20x objective.

This data set contains measures of energy-use efficiency, energy flow, and energy storage in units of dry biomass that quantify the multitrophic ecosystem functioning realized in grassland ecosystems of differing plant diversity. Given are both the measures integrated over whole ecosystems (total network measures) as well as the energy dynamics associated with individual ecosystem compartments including the entire biological community and detrital compartments across the above- and belowground parts of the ecosystem.Data presented here is from the Main Experiment plots of a large grassland biodiversity experiment (the Jena Experiment, see further details below). In the main experiment, 82 grassland plots of 20 x 20 m were established from a pool of 60 species belonging to four functional groups (grasses, legumes, tall and small herbs). In May 2002, varying numbers of plant species from this species pool were sown into the plots to create a gradient of plant species richness (1, 2, 4, 8, 16 and 60 species) and functional richness (1, 2, 3, 4 functional groups). Study plots are grouped in four blocks in parallel to the river in order to account for any effect of a gradient in abiotic soil properties. Each block contains an equal number of plots of each plant species richness and plant functional group richness level. Plots were maintained in general by bi-annual weeding and mowing. Since 2010, plot size was reduced to 5.5 x 6 m and plots were weeded three times per year.Trophic-network models were constructed for 80 of the experimental plots, and represent the ecosystem energy budget in the currency of dry-mass (g m-2 for standing stocks and g m-2 d-1 for flows). All trophic networks have the same topology, but they differ in the estimated size of the standing stock biomass of individual compartments (g m-2) and flows among the compartments (g m-2 d-1). Each trophic network contains twelve ecosystem compartments representing distinct trophic groups of the above- and belowground parts of the ecosystem (i.e., plants, soil microbial community, and above- and belowground herbivores, carnivores, omnivores, decomposers, all represented by invertebrate macro- and mesofauna) and detrital pools (i.e., surface litter and soil organic matter). Vertebrates were not considered in our study due to limitations of data availability and because the impact of resident vertebrates in our experimental system is expected to be minimal. Larger grazing vertebrates were excluded by a fence around the field site, though there was some occasional grazing by voles.Compartments are connected by 41 flows. Flows (fluxes) constitute 30 internal flows within the system, namely feeding (herbivory, predation, decomposition), excretion, mortality, and mechanical transformation of surface litter due to bioturbation plus eleven 11 external flows, i.e. one input (flows entering the system, namely carbon uptake by plants) and ten output flows (flows leaving the system, namely respiration losses). The ecosystem inflow (a flow entering the system) and outflows (flows leaving the system) represent carbon uptake and respiration losses, respectively. In the case of consumer groups, the food consumed (compartment-wide input flow) is further split into excretion (not assimilated organic material that is returned to detrital pools in the form of fecesfaeces) and assimilated organic material, which is further split into respiration (energy lost out of the system to the environment) and biomass production, which is further consumed by higher trophic levels due to predation or returned to detrital pools in the form of mortality (natural mortality or prey residues). In case of detrital pools (i.e. surface litter and soil organic matter), the input flows are in the form of excretion and mortality from the biota compartments, and output flows are in the form of feeding by decomposers and soil microorganisms (i.e. decomposition). Surface litter and soil organic matter are connected by flows in the form of burrowing (mechanical transportation) of organic material from the surface to the soil by soil fauna. Organism immigration and emigration are not considered in our study due to limited data availability.Flows were quantified using resource processing rates (i.e. the feeding rates at which material is taken from a source) multiplied with the standing biomass of the respective source compartment. To approximate resource processing rates, different approaches were used: (i) experimental measurements (namely the aboveground decomposition, fauna burial activity (bioturbation), microbial respiration, and aboveground herbivory and predation rates); (ii) allometric equations scaled by individual body mass, environmental temperature and phylogenetic group (for the above- and belowground fauna respiration rates and plant respiration); (iii) assimilation rates scaled by diet type (for quantification of belowground fauna excretion and natural mortality); (iv) literature-based rates scaled by biomass of trophic groups (for microbial mortality); and (v) mass-balance assumptions (carbon uptake, plant and aboveground fauna mortality, belowground decomposition, belowground herbivory, and belowground predation). Mass-balance assumption means that the flows are calculated assuming that resource inputs into the compartment (i.e. feeding) balance the rate at which material is lost (i.e. the sum of through excretion, respiration, predation, and natural death). We used constrained nonlinear multivariable optimization to perturb the initial flow rates estimated from the various sources. We assigned confidence ratings for each flow rate, reflecting the quality of empirical data it is based on. We then used the 'fmincon' function from Matlab's optimization toolbox, which utilizes the standard Moore-Penrose pseudoinverse approach to achieve a balanced steady state ecological network model that best reflects the collected field data. Measured data used to parameterize the trophic network models were collected mostly in the year 2010.Network-wide measures that quantify proxies for different aspects of multitrophic ecosystem functioning were calculated for each experimental plot using the 'enaR' package in R. In particular, total energy flow was measured as the sum of all flows through each ecosystem compartment. Flow uniformity was calculated as the ratio of the mean of summed flows through each individual ecosystem compartment divided by the standard deviation of these means. Total-network standing biomass was determined as the sum of standing biomass across all ecosystem compartments. Community maintenance costs were calculated as the ratio of community-wide respiration related to community-wide biomass. Supplement to: Buzhdygan, Oksana Y; Meyer, Sebastian Tobias; Weisser, Wolfgang W; Eisenhauer, Nico; Ebeling, Anne; Borrett, Stuart R; Buchmann, Nina; Cortois, Roeland; De Deyn, Gerlinde B; de Kroon, Hans; Gleixner, Gerd; Hertzog, Lionel R; Hines, Jes; Lange, Markus; Mommer, Liesje; Ravenek, Janneke; Scherber, Christoph; Scherer-Lorenzen, Michael; Scheu, Stefan; Schmid, Bernhard; Steinauer, Katja; Strecker, Tanja; Tietjen, Britta; Vogel, Anja; Weigelt, Alexandra; Petermann, Jana S (2020): Biodiversity increases multitrophic energy use efficiency, flow and storage in grasslands. Nature Ecology & Evolution Most of the data used to parameterize these trophic networks were collected in 2010.A diagram depicting the conceptual trophic-network model developed to describe multitrophic ecosystem functioning can be found in the paper (REF to the NEE paper). This paper also shows the relationship between the individual flows and compartment sizes as well as the network-wide measures with plant species richness. Further sensitivity analyses for the influence of including the highest diversity level are also provided in the paper.