Malte Jochum

and 6 more

Global change alters ecological communities with consequences for ecosystem processes. Such processes and functions are a central aspect of ecological research and vital to understanding and mitigating the consequences of global change, but also those of other drivers of change in organism communities. In this context, the concept of energy flux through trophic networks integrates food-web theory and biodiversity-ecosystem functioning theory and connects biodiversity to multitrophic ecosystem functioning. As such, the energy flux approach is a strikingly effective tool to answer central questions in ecology and global-change research. This might seem straight forward, given that the theoretical background and software to efficiently calculate energy flux are readily available. However, the implementation of such calculations is not always straight forward, especially for those who are new to the topic and not familiar with concepts central to this line of research, such as food-web theory or metabolic theory. To facilitate wider use of energy flux in ecological research, we thus provide a guide to adopting energy-flux calculations for people new to the method, struggling with its implementation, or simply looking for background reading, important resources, and standard solutions to the problems everyone faces when starting to quantify energy fluxes for their community data. First, we introduce energy flux and its use in community and ecosystem ecology. Then, we provide a comprehensive explanation of the single steps towards calculating energy flux for community data. Finally, we discuss remaining challenges and exciting research frontiers for future energy-flux research.

Josephine Grenzer

and 5 more

1. Plant-soil feedback (PSF) has gained attention as a mechanism promoting plant growth and coexistence. However, because most PSF research has measured monoculture growth in greenhouse conditions, field-based PSF experiments remain an important frontier for PSF research. 2. Using a four-year, factorial field experiment in Jena, Germany, we measured the growth of nine grassland species on soils conditioned by each of the target species (i.e., PSF). Plant community models were parameterized with or without these PSF effects, and model predictions were compared to plant biomass production in new and existing diversity-productivity experiments. 3. Plants created soils that changed subsequent plant biomass by 36%. However, because they were both positive and negative, the net PSF effect was 14% less growth on ‘home’ than ‘away’ soils. At the species level, seven of nine species realized non-neutral PSFs, but the two dominant species grew only 2% less on home than away soils. At the species*soil type level, 31 of 72 PSFs differed from zero. 4. In current and pre-existing diversity-productivity experiments, nine-species plant communities produced 37 to 29% more biomass than monocultures due primarily to selection effects. Null and PSF models predicted 29 to 28% more biomass for polycultures than monocultures, again due primarily to selection effects. 5. Synthesis: In field conditions, PSFs were large enough to be expected to cause roughly 14% overyielding due to complementarity, however, in plant communities overyielding was caused by selections effects, not complementarity effects. Further, large positive and large negative PSFs were associated with subdominant species, suggesting there may be selective pressure for plants to create neutral PSF. Broadly, results highlighted the importance of testing PSF effects in communities because there are several ways in which PSFs may be more or less important to plant growth in communities than suggested from simple PSF values.