Network-based characterization of temperature effects on the structural organization of productive Italian grasslands

Alpine grasslands are highly sensitive to temperature, one of the main drivers of plant physiological processes and species distributions. However, little is known about how thermal gradients shape the organisation of plant functional traits. Traditional approaches typically consider single traits or pairwise correlations, which can overlook the interactions among multiple traits that support ecosystem functioning. Here, we combine field measurements with Network Analysis to investigate how temperature influences the structural organisation of grassland traits. We collected 18 plant and environmental traits across three alpine grasslands in northern Italy along an altitudinal gradient, serving as a natural proxy for temperature variation. Using Plant Trait Networks (PTNs), we quantified patterns of trait connectivity, community structure, and the relative importance of individual traits. Our results indicate that increasing altitude, and the associated shift toward harsher environmental conditions and lower temperatures, leads to lower network connectivity, fewer trait interdependencies, and reduced centrality of individual traits. Communities of strongly associated traits become smaller and more fragmented, reflecting a loss of coordinated trait organisation under colder conditions. These findings demonstrate that temperature strongly affects the structural cohesion and functional integration of grassland traits. By applying Network science to functional ecology, this study provides new insights into climate impacts on vegetation and highlights the potential of PTNs to evaluate ecosystem resilience under environmental change.