• Energy Research

(Uploaded by Plazi for the Bat Literature Project) No abstract provided.

AbstractBiodiversity experiments revealed that plant diversity loss can decrease ecosystem functions across trophic levels. To address why such biodiversity-function relationships strengthen over time, we established experimental mesocosms replicating a gradient in plant species richness across treatments of shared versus non-shared history of (1) the plant community and (2) the soil fauna community. After 4 months, we assessed the multitrophic functioning of soil fauna via biomass stocks and energy fluxes across the food webs. We find that soil community history significantly enhanced belowground multitrophic function via changes in biomass stocks and community-average body masses across the food webs. However, variation in plant diversity and plant community history had unclear effects. Our findings underscore the importance of long-term community assembly processes for soil fauna-driven ecosystem function, with species richness and short-term plant adaptations playing a minimal role. Disturbances that disrupt soil community stability may hinder fauna-driven ecosystem functions, while recovery may require several years.

Darwin's classic image of an “entangled bank” of interdependencies among species has long suggested that it is difficult to predict how the loss of one species affects the abundance of others. We show that for dynamical models of realistically structured ecological networks in which pair-wise consumer-resource interactions allometrically scale to the ¾ power—as suggested by metabolic theory—the effect of losing one species on another can be predicted well by simple functions of variables easily observed in nature. By systematically removing individual species from 600 networks ranging from 10–30 species, we analyzed how the strength of 254,032 possible pair-wise species interactions depended on 90 stochastically varied species, link, and network attributes. We found that the interaction strength between a pair of species is predicted well by simple functions of the two species' biomasses and the body mass of the species removed. On average, prediction accuracy increases with network size, suggesting that greater web complexity simplifies predicting interaction strengths. Applied to field data, our model successfully predicts interactions dominated by trophic effects and illuminates the sign and magnitude of important nontrophic interactions.

Few models concern how environmental variables such as temperature affect community structure. Here, we develop a model of how temperature affects food web connectance, a powerful driver of population dynamics and community structure. We use the Arrhenius equation to add temperature dependence of foraging traits to an existing model of food web structure. The model predicts potentially large temperature effects on connectance. Temperature-sensitive food webs exhibit slopes of up to 0.01 units of connectance per 1°C change in temperature. This corresponds to changes in diet breadth of one resource item per 2°C (assuming a food web containing 50 species). Less sensitive food webs exhibit slopes down to 0.0005, which corresponds to about one resource item per 40°C. Relative sizes of the activation energies of attack rate and handling time determine whether warming increases or decreases connectance. Differences in temperature sensitivity are explained by differences between empirical food webs in the body size distributions of organisms. We conclude that models of temperature effects on community structure and dynamics urgently require considerable development, and also more and better empirical data to parameterize and test them.

AbstractWarming and eutrophication are two of the most important global change stressors for natural ecosystems, but their interaction is poorly understood. We used a dynamic model of complex, size‐structured food webs to assess interactive effects on diversity and network structure. We found antagonistic impacts: Warming increases diversity in eutrophic systems and decreases it in oligotrophic systems. These effects interact with the community size structure: Communities of similarly sized species such as parasitoid–host systems are stabilized by warming and destabilized by eutrophication, whereas the diversity of size‐structured predator–prey networks decreases strongly with warming, but decreases only weakly with eutrophication. Nonrandom extinction risks for generalists and specialists lead to higher connectance in networks without size structure and lower connectance in size‐structured communities. Overall, our results unravel interactive impacts of warming and eutrophication and suggest that size structure may serve as an important proxy for predicting the community sensitivity to these global change stressors.

Ecological communities consist of small abundant and large non‐abundant species. The energetic equivalence rule is an often‐observed pattern that could be explained by equal energy usage among abundant small organisms and non‐abundant large organisms. To generate this pattern, metabolism (as an indicator of individual energy use) and abundance have to scale inversely with body mass, and cancel each other out. In contrast, the pattern referred to as biomass equivalence states that the biomass of all species in an area should be constant across the body‐mass range. In this study, we investigated forest soil communities with respect to metabolism, abundance, population energy use, and biomass. We focused on four land‐use types in three different landscape blocks (Biodiversity Exploratories). The soil samples contained 870 species across 12 phylogenetic groups. Our results indicated positive sublinear metabolic scaling and negative sublinear abundance scaling with species body mass. The relationships varied mainly due to differences among phylogenetic groups or feeding types, and only marginally due to land‐use type. However, these scaling relationships were not exactly inverse to each other, resulting in increasing population energy use and biomass with increasing body mass for most combinations of phylogenetic group or feeding type with land‐use type. Thus, our results are mostly inconsistent with the classic perception of energetic equivalence, and reject the biomass equivalence hypothesis while documenting a specific and nonrandom pattern of how abundance, energy use, and biomass are distributed across size classes. However, these patterns are consistent with two alternative predictions: the resource‐thinning hypothesis, which states that abundance decreases with trophic level, and the allometric degree hypothesis, which states that population energy use should increase with population average body mass, due to correlations with the number of links of consumers and resources. Overall, our results suggest that a synthesis of food web structures with metabolic theory may be most promising for predicting natural patterns of abundance, biomass, and energy use.

AbstractEarthworms are an important soil taxon as ecosystem engineers, providing a variety of crucial ecosystem functions and services. Little is known about their diversity and distribution at large spatial scales, despite the availability of considerable amounts of local-scale data. Earthworm diversity data, obtained from the primary literature or provided directly by authors, were collated with information on site locations, including coordinates, habitat cover, and soil properties. Datasets were required, at a minimum, to include abundance or biomass of earthworms at a site. Where possible, site-level species lists were included, as well as the abundance and biomass of individual species and ecological groups. This global dataset contains 10,840 sites, with 184 species, from 60 countries and all continents except Antarctica. The data were obtained from 182 published articles, published between 1973 and 2017, and 17 unpublished datasets. Amalgamating data into a single global database will assist researchers in investigating and answering a wide variety of pressing questions, for example, jointly assessing aboveground and belowground biodiversity distributions and drivers of biodiversity change.