Leaf area index (LAI) is a key variable in modeling terrestrial vegetation because it has a major impact on carbon and water fluxes. However, several recent intercomparisons have shown that modeled LAI differs significantly among models and between models and satellite-derived estimates. Empirical studies show that LAI is strongly related to precipitation. This observation is predicted by the ecohydrological equilibrium theory, which provides an alternative means to predict steady state LAI. We implemented this theory in a simple optimization model. We hypothesized that, when water availability is limited, plants should adjust steady state LAI and stomatal behavior to maximize net canopy carbon export, under the constraint that canopy transpiration is a fixed fraction of total precipitation. We evaluated the predicted LAI (Lopt) for Australia against ground-based observations of LAI at 135 sites and continental-scale satellite-derived estimates. For the site-level data, the root-mean-square error of predicted Lopt was 1.07 m2 m−2, similar to the root-mean-square error of a comparison of the data against 9-year mean satellite-derived LAI (Lsat) at those sites. Continentally, Lopt had an R2 of 0.7 when compared to Lsat. The predicted Lopt increased continental-wide with rising atmospheric [CO2] over 1982–2010, which agreed with satellite-derived estimations, while the predicted stomatal behavior responded differently in dry and wet regions. Our results indicate that long-term equilibrium LAI can be successfully predicted from a simple application of ecohydrological theory. We suggest that this theory could be usefully incorporated into terrestrial vegetation models to improve their predictions of LAI.
Bibliographical noteFunding Information:
J.Y. was supported by a PhD scholarship from the Hawkesbury Institute for the Environment, Western Sydney University. Martin De Kauwe acknowledges support from the ARC Centre of Excellence for Climate Extremes (CE170100023). This research was undertaken with the assistance of resources from the National Computational Infrastructure (NCI), which is supported by the Australian Government. The model is constructed in R, and the code is fully open via the link https://bitbucket.org/Jinyan_Jim_ Yang/lai-model-perm-19jan2018/ overview. NCI website provides the climate data (http://dapds00.nci.org.au/ thredds/catalog.html) and MODIS LAI (http://remote-sensing.nci.org.au/u39/ public/html/index.shtml). Some of the ground-based LAI data were obtained through TERN AusCover (http://www. auscover.org.au). TERN is Australia’s land-based ecosystem observatory delivering data streams to enable environmental research and management (TERN, http://www.tern. org.au). TERN is a part of Australia’s National Collaborative Research Infrastructure Strategy (NCRIS, https:// www.education.gov.au/national-collaborative-research-infrastructure-strategy-ncris).
©2018. The Authors.
- ecohydrological equilibrium
- leaf area index