Optimizing Water–Carbon Coupling Through a Trait-Based Framework Integrating WCCI and Dual-Filter CATS Model

Ecological restoration in degraded landscapes requires understanding the factors driving ecosystem function. We ask the central question: Do microtopography and plant functional traits control water-carbon coupling efficiency (WCCI) in mining-affected grasslands? We developed a novel, decoupled WCCI metric balancing water-use efficiency (1/SLA) and carbon-stock potential (Height + Foliage Cover). We hypothesized that (1) microhabitats with severe environmental filters (e.g., drought, erosion) would exhibit the lowest WCCI, and (2) this function could be optimized by assembling species that balance these two distinct trait strategies. Our objectives were to: (i) quantify the new WCCI across five microhabitat zones (A–E); (ii) assess how soil filters shape existing community functions; and (iii) identify optimized, zone-specific species assemblages using a dual-filter CATS model that maximizes WCCI. Results show significant variability in WCCI. The most degraded zones, A (arid) and B (high erosion), exhibited the lowest functional performance (mean WCCI = 0.029 and 0.078), supporting our first hypothesis. The dual-filter CATS model, constrained by abiotic targets (Tolerance = 10%) and a diversity cap (Max Abundance = 30%), successfully generated distinct, functionally tailored species assemblages for each zone. For instance, the optimized community for arid Zone A included the drought-adapted grass Stipa capillata (15.9%), while the resource-rich Zone D was recommended Medicago lupulina (12.7%). Conclusion: These findings confirm that a “one-size-fits-all” approach is insufficient. We demonstrate the necessity of a trait-based, microhabitat-specific framework to move beyond taxonomic mimicry and truly optimize biogeochemical functions in restoration.