Ecosystem processes at the watershed scale: Extending optimality theory from plot to catchment

The adjustment of local vegetation conditions to limiting soil water by either maximizing productivity or minimizing water stress has been an area of central interest in ecohydrology since Eagleson's classic study. This work has typically been limited to consider one-dimensional exchange and cycling within patches and has not incorporated the effects of lateral redistribution of soil moisture, coupled ecosystem carbon and nitrogen cycling, and vegetation allocation processes along topographic gradients. We extend this theory to the hillslope and catchment scale, with in situ and downslope feedbacks between water, carbon and nutrient cycling within a fully transient, distributed model. We explore whether ecosystem patches linked along hydrologic flow paths as a catena evolve to form an emergent pattern optimized to local climate and topographic conditions. Lateral hydrologic connectivity of a small catchment is calibrated with streamflow data and further tested with measured soil moisture patterns. Then, the spatial gradient of vegetation density within a small catchment estimated with fine-resolution satellite imagery and field measurements is evaluated with simulated vegetation growth patterns from different root depth and allocation strategies as a function of hillslope position. This is also supported by the correspondence of modeled and field measured spatial patterns of root depths and catchment-level aboveground vegetation productivity. We test whether the simulated spatial pattern of vegetation corresponds to measured canopy patterns and an optimal state relative to a set of ecosystem processes, defined as maximizing ecosystem productivity and water use efficiency at the catchment scale. Optimal carbon uptake ranges show effective compromises between multiple resources (water, light, and nutrients), modulated by vegetation allocation dynamics along hillslope gradient.