# Asynchronous Responses of Plants, Soils, and Microbes to Snow Cover Change Across Terrestrial Ecosystems: A Global Meta-Analysis

## TL;DR

This study finds that plants, soils, and microbes respond differently to changes in snow cover, leading to ecosystem-level asynchrony.

## Contribution

The study provides the first global meta-analysis showing asynchrony in ecosystem components' responses to snow cover change.

## Key findings

- Snow removal strongly reduces soil water content and microbial diversity.
- Snow addition has smaller or variable effects across ecosystem components.
- Responses of plants and soil organisms often mismatch, indicating ecosystem decoupling.

## Abstract

Snow cover, as a critical component of the global climate system, strongly influences ecological processes in cold and temperate regions. However, how different ecosystem components—plants, soils, and microbes—respond to snow cover change remains poorly understood, especially in terms of their coordination. Here, we conducted a global meta-analysis of 1986 single and 1047 paired observations from snow manipulation experiments across diverse terrestrial ecosystems. Our results showed that snow removal generally reduced SWC and microbial diversity, whereas snow addition exerted smaller or more variable influences across ecosystem components. Among all variables, the effect of snow cover change on soil water content was most pronounced, whereas its impacts on other factors were generally weak. Notably, the direction and magnitude of responses often differed among ecosystem components exposed to the same treatments. Pairwise comparisons revealed frequent mismatches between plant and soil organism responses, indicating substantial ecosystem-level decoupling across biomes. These findings support the ecosystem asynchrony hypothesis and highlight the need for integrated approaches that link aboveground and belowground processes. Our study improves the understanding of ecosystem stability under changing snow regimes and provides insights for predicting future terrestrial responses to global climate change.