• Energy Research

AbstractGlobal change encompasses many co‐occurring anthropogenic drivers, which can act synergistically or antagonistically on ecological systems. Predicting how different global change drivers simultaneously contribute to observed biodiversity change is a key challenge for ecology and conservation. However, we lack the mechanistic understanding of how multiple global change drivers influence the vital rates of multiple interacting species. We propose that reaction norms, the relationships between a driver and vital rates like growth, mortality, and consumption, provide insights to the underlying mechanisms of community responses to multiple drivers. Understanding how multiple drivers interact to affect demographic rates using a reaction‐norm perspective can improve our ability to make predictions of interactions at higher levels of organization—that is, community and food web. Building on the framework of consumer–resource interactions and widely studied thermal performance curves, we illustrate how joint driver impacts can be scaled up from the population to the community level. A simple proof‐of‐concept model demonstrates how reaction norms of vital rates predict the prevalence of driver interactions at the community level. A literature search suggests that our proposed approach is not yet used in multiple driver research. We outline how realistic response surfaces (i.e., multidimensional reaction norms) can be inferred by parametric and nonparametric approaches. Response surfaces have the potential to strengthen our understanding of how multiple drivers affect communities as well as improve our ability to predict when interactive effects emerge, two of the major challenges of ecology today.

The present study was conducted at the Jena Experiment field site from 2011 to 2015. The 48 experimental plant communities included twelve monocultures (of which one was removed from all analyses because it was planted with the wrong species), twelve 2-species mixtures, twelve 4-species mixtures and twelve 8-species mixtures. We used two community-evolution treatments (plant histories); plants with eight years of co-selection history in different plant communities in the Jena Experiment (communities of co-selected plants) and plants without such co-selection history (naïve communities). Community-level plant productivity was measured each year from 2012 to 2015 by collecting species-specific aboveground biomass twice per year in May and August. There are a total of seven harvests included in this dataset. We harvested plant material 3 cm aboveground from a 50 x 20 cm area in the centre of each half-quadrat, sorted it into species, dried it at 70°C and weighed the dry biomass. We also include a datafile with the stability metrics presented in the paper, such as resistance, recovery, and resilience to the flood, population stability and temporal stability.

NOTE for reproducibility of our resultsFor all our analyses, we removed three plots from the original design (in all cases both split-split plots containing new/old communities)B1A12, quadrat with Org soilThis 8-species mixture had to be excluded because of missing data and the data not accurately representing the plant community.B2A05Festuca pratense monoculture had to be exlucded because the wrong species was planted.B2A15Onobrychis viciifolia monoculture had to be excluded because it was such an extreme outlier and the data did not accurately represent the community.

NOTE for reproducibility of our resultsFor all our analyses, we removed three plots from the original design (in all cases both split-split plots containing new/old communities)B1A12, quadrat with Org soilThis 8-species mixture had to be excluded because of missing data and the data not accurately representing the plant community.B2A05Festuca pratense monoculture had to be exlucded because the wrong species was planted.B2A15Onobrychis viciifolia monoculture had to be excluded because it was such an extreme outlier and the data did not accurately represent the community.

Summary Afforestation projects using species mixtures are expected to better support ecosystem services than monoculture plantations. While grassland studies have shown natural selection favoring high‐performance genotypes in species‐rich communities, this has not been explored in forests. We used seed‐family identity (known maternity) to represent genetic identity and investigated how this affected the biomass accumulation (i.e. growth) of individual trees (n = 13 435) along a species richness gradient (1–16 species) and over stand age (9 yr) in a forest biodiversity experiment. We found that among the eight species tested, different seed families responded differently to species richness, some of them growing relatively better in low‐diversity plots and others in high‐diversity plots. Furthermore, within‐species growth variation increased with species richness and stand age, while between‐species variation decreased with stand age. These results indicate that seed families within species and their reaction norms along the species richness gradient vary considerably and thus can explain a substantial proportion of the overall variation in tree growth. Our findings suggest that the growth and associated ecosystem services of species‐rich mixtures in afforestation projects can be optimized by artificially selecting seed families with high mixture performance in biodiversity experiments.

AbstractUnderstanding factors that maintain ecosystem stability is critical in the face of environmental change. Experiments simulating species loss from grassland have shown that losing biodiversity decreases ecosystem stability. However, as the originally sown experimental communities with reduced biodiversity develop, plant evolutionary processes or the assembly of interacting soil organisms may allow ecosystems to increase stability over time. We explored such effects in a long‐term grassland biodiversity experiment with plant communities with either a history of co‐occurrence (selected communities) or no such history (naïve communities) over a 4‐yr period in which a major flood disturbance occurred. Comparing communities of identical species composition, we found that selected communities had temporally more stable biomass than naïve communities, especially at low species richness. Furthermore, selected communities showed greater biomass recovery after flooding, resulting in more stable post‐flood productivity. In contrast to a previous study, the positive diversity–stability relationship was maintained after the flooding. Our results were consistent across three soil treatments simulating the presence or absence of co‐selected microbial communities. We suggest that prolonged exposure of plant populations to a particular community context and abiotic site conditions can increase ecosystem temporal stability and resilience due to short‐term evolution. A history of co‐occurrence can in part compensate for species loss, as can high plant diversity in part compensate for the missing opportunity of such adaptive adjustments.