Niche and fitness differences across environmental conditions and ecosystem types

While the effects of species ecology and environmental limiting factors (ELF) on competitive interactions are relatively well-studied, the nature of the relationship between multiple ELF and species ecology is less well-understood. Here, we seek to identify the combined effects of multiple ELF and species ecology on community niche and fitness differences (NFD), which is dictated by competitive interactions, using both experimental and literature-based approaches. First, we experimentally identified how combined gradients of two ELF affect community composition, compared to their individual effects. We performed competitive experiments using communities of two phytoplankton sub-species. We described their competitive dynamics using two definitions of niche difference (ND) and fitness difference (FD). Second, using data from literature making use of any mathematical definition of NFD, we compared the type of ecological interactions of four biological systems and their respective determinants of coexistence (ND and/or FD). We computed three general definitions of NFD for pair-wise communities. Our experiment demonstrated that combined gradients of ELF interact in a complex, unpredictable fashion. However, when increasing both ELF caused an increase of ND and increased equivalence of FD, promoting coexistence. Analysing communities from literature showed that different biological systems contain different types of ecological interactions. ND was generally higher in coexisting communities and was the most common determinant of coexistence, while the importance of FD was system- and definitiondependent. Complex interactions of combined ELF gradients promote biodiversity, and the specific ecology of the species studied influences the effect of the combined gradients. Different biological systems, with different ranges of biological interactions, will therefore react differently to ELF gradients. Combined effects of ELF need to be considered alongside system-specific biological interactions, in order to accurately forecast the outcome of competition under environmental change. All results showed a qualitative difference based on the definition used, stressing the need of a general and approved framework to forecast and understand competitive interactions.