Exploring the Frequency and Distribution of Ecological Non-monotonicity in Associations among Ecosystem Constituents

Abstract

Complex links between biotic and abiotic constituents are fundamental for the functioning of ecosystems. Although non-monotonic interactions and associations are known to increase the stability, diversity, and productivity of ecosystems, they are frequently ignored by community-level standard statistical approaches. Using the copula-based dependence measure qad, capable of quantifying the directed and asymmetric dependence between variables for all forms of (functional) relationships, we determined the proportion of non-monotonic associations between different constituents of an ecosystem (plants, bacteria, fungi, and environmental parameters). Here, we show that up to 59% of all statistically significant associations are non-monotonic. Further, we show that pairwise associations between plants, bacteria, fungi, and environmental parameters are specifically characterized by their strength and degree of monotonicity, for example, microbe–microbe associations are on average stronger than and differ in degree of non-monotonicity from plant–microbe associations. Considering directed and non-monotonic associations, we extended the concept of ecosystem coupling providing more complete insights into the internal order of ecosystems. Our results emphasize the importance of ecological non-monotonicity in characterizing and understanding ecosystem patterns and processes.

Adding experimental precision to the realism of field observations: Plant communities structure bacterial communities in a glacier forefield

“…Bacterial communities are shaped by dispersal, the environment, and interactions among bacteria and between bacteria and other organisms (Cordero & Datta, 2016; Hanusch et al, 2023; Knelman et al, 2012; Nemergut et al, 2013; Yuan et al, 2016). Our experimental procedures excluded dispersal and homogenised the environmental conditions as well as the initial bacterial communities, which largely determines microbial interactions potentially occurring within the experimental microcosms.…”