How biocrusts form self-organized patterns and potentially influence dryland ecosystem functioning

A research team led by Prof. Li Yuqiang from the Northwest Institute of Eco-Environment and Resources (NIEER) of the Chinese Academy of Sciences has uncovered the mechanisms behind the formation of self-organized Turing patterns in biocrusts. This self-organizing ability of biocrusts has significant implications for ecosystem functions and the resilience of dryland ecosystems. Their findings were published in the Proceedings of the National Academy of Sciences on July 21.

Biocrusts, which consist of organisms such as lichens and mosses, play a vital role in dryland ecosystems. Their spatial distribution, which often exhibits Turing patterns, is fundamental to the functioning of these ecosystems. However, the mechanisms underlying the formation of these patterns and their ecological significance remain unclear.

To address this knowledge gap, the researchers conducted field observations across different successional stages of biocrusts in Shapotou, northern China, and employed a probabilistic cellular automaton model to investigate the self-organized spatial patterns of biocrust patches.

They discovered that the dynamics of biocrusts in drylands are regulated by spatial and temporal scale-dependent feedbacks, ultimately leading to the formation of self-organized Turing patterns.

Specifically, short-range positive feedbacks initially promote the development of patches, characterized by a heavy-tailed patch size distribution. As patches grow, long-range negative feedbacks due to resource constraints curtail further expansion, leading to a characteristic patch scale in patch size distribution and regular Turing patterns.

A further finding is that field measurements of biocrust performance at the center and edge of patches of varying sizes across succession stages further verify the asynchronous nature of scale-dependent feedbacks.

Understanding the self-organization processes within biocrust communities can provide valuable insights into the connections between spatial patterns and ecosystem functionality. This knowledge may also help predict how biocrusts and dryland ecosystems will respond to environmental changes.