1. Understanding the drivers of species coexistence is essential in ecology. Niche and fitness differences (i.e. how species limit themselves compared to others and species' differences in competitive ability, respectively) permit studying the consequences of species interactions. Yet, the multitude of methods to compute niche and fitness differences hampers cross-community comparisons. Such shortcoming leaves a gap in our understanding of the natural drivers of species coexistence and whether niche or/and fitness differences capture them.2. Here, we standardised niche and fitness differences across 953 species pairs to investigate species coexistence across ecological groups and methodological settings (experimental setup, natural co-occurrence, population model used and growth method). Using data gathered from 29 empirical papers, we asked whether large niche differences, small fitness differences or both explain predicted coexistence. Moreover, we performed an automated clustering algorithm to understand whether different underlying mechanisms drive species interactions. Finally, we tested whether any ecological or/and methodological settings drive these clusters.3. Species pairs predicted to coexist have larger niche differences but not smaller fitness differences than species pairs predicted not to coexist. Also, species pairs group into two clear clusters along the niche difference axis: those predicted to coexist and those that are not. Surprisingly, ecological or methodological settings do not drive these clusters. 4. Synthesis. Overall, our results show that species coexistence is mainly influenced by mechanisms acting on niche differences, highlighting the importance of sustaining mechanisms that promote niche differences to maintain species coexistence. In addition, our results provide evidence that communities predicted to coexist differ from those that are not in ways that transcend their ecological grouping.

Theory posits that the persistence of species in ecological communities is shaped by their interactions within and across trophic levels. However, we lack empirical evaluations of how the structure, strength and sign of these interactions drive the potential to coexist in diverse multi-trophic communities. Here we model community feasibility domains, a theoretically-informed measure of coexistence probability, from empirical data on communities comprising more than 50 species for three trophic guilds (plants, pollinators, and herbivores). Although feasibility domains vary depending on the number of trophic guilds considered, we show that higher network connectance leads to lower coexistence opportunities. Moreover, empirical estimations of the feasibility domains were higher with respect to random network structures but lower than a mean-field approach, suggesting that observed interaction structures tend to maximize coexistence within its imposed limits. Our results stress the importance of incorporating empirically-informed interaction structures within and across guilds to better understand how species coexist in diverse multi-trophic communities.

Understanding how species interactions affect community composition is an important objective in ecology. Yet, the multitude of methods to study coexistence has hampered cross-community comparisons. Here, we standardized niche and fitness differences across 1018 species pairs to compare the processes driving composition and outcomes, among four community types (annual plant, perennial plant, phytoplankton, and bacteria/yeast). First, we show that niche differences are more important drivers of coexistence than fitness differences. Second, in all community types negative frequency dependence is the most frequent process. Finally, the outcome of species interactions differs among community types. Coexistence was the most frequent outcome for perennial plants and phytoplankton, while competitive exclusion was the most prevalent outcome in annual plants and bacteria/yeasts. Overall, our results show that niche and fitness differences can be used as a common currency that allow cross community comparisons to understand species coexistence.

Theory posits that the persistence of species in ecological communities is shaped by their interactions within and across trophic guilds. However, we lack empirical evaluations of how the structure, strength and sign of biotic interactions drive the potential to coexist in diverse multi‐trophic communities. Here, we model community feasibility domains, a theoretically informed measure of multi‐species coexistence probability, from grassland communities comprising more than 45 species on average from three trophic guilds (plants, pollinators and herbivores). Contrary to our hypothesis, increasing community complexity, measured either as the number of guilds or community richness, did not decrease community feasibility. Rather, we observed that high degrees of species self‐regulation and niche partitioning allow for maintaining larger levels of community feasibility and higher species persistence in more diverse communities. Our results show that biotic interactions within and across guilds are not random in nature and both structures significantly contribute to maintaining multi‐trophic diversity.