Scale-Dependent Heterogeneity Drives Microbial Insurance in Phyllosphere Algal-Bacterial Networks during Lake Eutrophication.

The algal-bacterial symbiotic communities within the submerged macrophyte phyllosphere exhibit significant potential for lake restoration. However, their response mechanisms to environmental heterogeneity remain unclear, as traditional experiments or models typically overlook the complexity of cross-kingdom microbial networks. To address this, we established a cross-scale framework that integrates controlled mesocosm experiments with field lake surveys across trophic gradients. Using multilevel network analysis, we found that increased environmental heterogeneity promoted stochastic assembly and niche differentiation within phyllosphere communities. This enhanced the functional metabolic complementarity of algal-bacterial networks, thereby strengthening the ecosystem resilience. These findings challenge the traditional view that homogeneous environments favor microbial functional redundancy. Notably, machine learning models trained on experimental data showed high predictive accuracy but exhibited systematic biases when applied to natural lakes, highlighting the scale-dependent complexity of in situ microbial networks. Our study identifies heterogeneity-driven microbial insurance as a critical stabilizing mechanism and advocates for incorporating this ecological complexity into cross-scale restoration strategies.