codes and data for "Network-informed analysis of a multivariate trait-space reveals optimal trait selection"

Trait-based analyses have shown great potential to advance our understanding of terrestrial ecosystem processes and functions. However, challenges remain in adequately synthesising a multidimensional and covarying trait space. Here, we develop a trait reduction procedure based on network analysis of a global trait dataset that covers 27 traits across 262 ecoregions. By applying constraints on previous optimal reduced network in which traits were incrementally added or removed, we established consistent network series. Then, the most cost-efficient trait sets are allowing to identify to represent full trait space when an acquisition cost can be attributed to each trait.<b> </b>We found that that the reduced trait sets properly represented the three main dimensions of full trait space in hydrological safety, leaf economic strategy, and plant reproduction and competition. Then a parsimonious trade-off can also be achieved by selecting a 16-trait network which costs only 42.1% of the full suite of the 27 traits. Our approach can help in revealing important trade-offs and in selecting key traits, thus will potentially enhancing our understanding on the main trade-off dimensions of the multivariate trait space and facilitating trait-based research practically.