Description: 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.

Description: 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.

Description: 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.

Description: Concern about the functional consequences of unprecedented loss in biodiversity has prompted biodiversity–ecosystem functioning (BEF) research to become one of the most active fields of ecological research in the past 25 years. Hundreds of experiments have manipulated biodiversity as an independent variable and found compelling support that the functioning of ecosystems increases with the diversity of their ecological communities. This research has also identified some of the mechanisms underlying BEF relationships, some context-dependencies of the strength of relationships, as well as implications for various ecosystem services that humankind depends upon. In this chapter, we argue that a multitrophic perspective of biotic interactions in random and non-random biodiversity change scenarios is key to advance future BEF research and to address some of its most important remaining challenges. We discuss that the study and the quantification of multitrophic interactions in space and time facilitates scaling up from small-scale biodiversity manipulations and ecosystem function assessments to management-relevant spatial scales across ecosystem boundaries. We specifically consider multitrophic conceptual frameworks to understand and predict the context-dependency of BEF relationships. Moreover, we highlight the importance of the eco-evolutionary underpinnings of multitrophic BEF relationships. We outline that FAIR data (meeting the standards of findability, accessibility, interoperability, and reusability) and reproducible processing will be key to advance this field of research by making it more integrative. Finally, we show how these BEF insights may be implemented for ecosystem management, society, and policy. Given that human well-being critically depends on the multiple services provided by diverse, multitrophic communities, integrating the approaches of evolutionary ecology, community ecology, and ecosystem ecology in future BEF research will be key to refine conservation targets and develop sustainable management strategies.

Description: The research of a generation of ecologists was catalysed by the recognition that the number and identity of species in communities influences the functioning of ecosystems. The relationship between biodiversity and ecosystem functioning (BEF) is most often examined by controlling species richness and randomising community composition. In natural systems, biodiversity changes are often part of a bigger community assembly dynamic. Therefore, focusing on community assembly and the functioning of ecosystems (CAFE), by integrating both species richness and composition through species gains, losses and changes in abundance, will better reveal how community changes affect ecosystem function. We synthesise the BEF and CAFE perspectives using an ecological application of the Price equation, which partitions the contributions of richness and composition to function. Using empirical examples, we show how the CAFE approach reveals important contributions of composition to function. These examples show how changes in species richness and composition driven by environmental perturbations can work in concert or antagonistically to influence ecosystem function. Considering how communities change in an integrative fashion, rather than focusing on one axis of community structure at a time, will improve our ability to anticipate and predict changes in ecosystem function.

Description: The increasing amount of plastic littered into the sea may provide a new substratum for benthic organisms. These marine fouling communities on plastic have not received much scientific attention. We present, to our knowledge, the first comprehensive analysis of their macroscopic community composition, their primary production and the polymer degradation comparing conventional polyethylene (PE) and a biodegradable starch-based plastic blend in coastal benthic and pelagic habitats in the Mediterranean Sea. The biomass of the fouling layer increased significantly over time and all samples became heavy enough to sink to the seafloor. The fouling communities, consisting of 21 families, were distinct between habitats, but not between polymer types. Positive primary production was measured in the pelagic, but not in the benthic habitat, suggesting that large accumulations of floating plastic could pose a source of oxygen for local ecosystems, as well as a carbon sink. Contrary to PE, the biodegradable plastic showed a significant loss of tensile strength and disintegrated over time in both habitats. These results indicate that in the marine environment, biodegradable polymers may disintegrate at higher rates than conventional polymers. This should be considered for the development of new materials, environmental risk assessment and waste management strategies.