Ideas and perspectives: how coupled is the vegetation to the boundary layer?

Understanding the sensitivity of transpiration to stomatal conductance is critical to simulating the water cycle. This sensitivity is a function of the degree of coupling between the vegetation and the atmosphere and is commonly expressed by the decoupling factor. The degree of coupling assumed by models varies considerably and has previously been shown to be a major cause of model disagreement when simulating changes in transpiration in response to elevated CO2. The degree of coupling also offers us insight into how different vegetation types control transpiration fluxes, which is fundamental to our understanding of land–atmosphere interactions. To explore this issue, we combined an extensive literature summary from 41 studies with estimates of the decoupling coefficient estimated from FLUXNET data. We found some notable departures from the values previously reported in single-site studies. There was large variability in estimated decoupling coefficients (range 0.05–0.51) for evergreen needleleaf forests. This is a result that was broadly supported by our literature review but contrasts with the early literature which suggests that evergreen needleleaf forests are generally well coupled. Estimates from FLUXNET indicated that evergreen broadleaved forests were the most tightly coupled, differing from our literature review and instead suggesting that it was evergreen needleleaf forests. We also found that the assumption that grasses would be strongly decoupled (due to vegetation stature) was only true for high precipitation sites. These results were robust to assumptions about aerodynamic conductance and, to a lesser extent, energy balance closure. Thus, these data form a benchmarking metric against which to test model assumptions about coupling. Our results identify a clear need to improve the quantification of the processes involved in scaling from the leaf to the whole ecosystem. Progress could be made with targeted measurement campaigns at flux sites and greater site characteristic information across the FLUXNET network.