Current Projects

On going: Remote sensing of habitat conditions

I'm working with Karel and Tom at CSIRO Environment to add temporal dynamics to HCAS. 

On going: Plant nitrogen stable isotope ratio as an indicator of change in plant conditions

Remote sensing gives many structure related vegetation indicators. Rarely do we get functional and compositional indicators, which are important aspects of ecosystem. Using ground-based observation and Landsat, I derived a nitrogen isotope from spectra observations for the past for decades. 

I'm working no publishing it but a preprint is already available. 

Past: Modelling fuel load under future climate 

A biophysics-aware machine learning (ML) was used to construct models with climatic, edaphic and topographic predictors that predict fuel patterns at fine spatial resolution. We hope to use this novel framework to bet combine past observations and our current knowledge of plant responses to climate change to make projection of fuel load under future climate. 

The results are now in a publication in Journal of Applied Ecology.

Past: Predicting grassland phenology

I'm currently developing a generalisable ecophysiological modelling framework that incorporates physiological processes and traits to predict the dynamics of grassland productivity across Australian landscapes. It involves in finding relationships between rainfall, plant physiological processes and associated functional traits. Model validation will use data inputs from in situ phenocams and satellite derived EVI across landscapes. 

Details in a paper in Agriculture and Forestry Meteorology. 

Past project: Predict LAI

I tested the concept of ecohydrological equilibrium (i.e., long-term equilibrium LAI is determined by water availability) for its predictions in Australia.  The predicted LAI values and the response to Ca both compared well to those of satellite-derived data.  These results indicate that Lequ could be an useful alternative to satellite-derived data to terrestrial vegetation models to guild foliage carbon allocation.   

Publication on this project now in JAMES. 

And try this Shiny app  to see how it works or this link for the code. 

Past project: Stomatal conductance and photosynthesis model at high VPD

VPD is projected to increase in the future, accompanying the rising Ca.  It is thus important to test whether stomatal conductance (gs) models capture the response of gs at high VPD .  Here, I evaluated: (i) the empirical and optimal gs models (Leuning, Medlyn), which assume gs is related directly to VPD ; (ii) the Tuzet model, which follows the hydraulic limitation hypothesis; and (iii) the non-stomatal limitation in which photosynthetic capacity decreases with increasing VPD .  The findings suggested that models need to incorporate non-stomatal limitation to accurate simulate of gs and photosynthesis at high VPD 

A publication of the findings is in Tree Physiology. 

Past project: MAESPA simulation of EucFACE

The aim of this project is to determine the baseline and the response of carbon and water fluxes in the Eucalyptus Free-Air-Carbon-Enrichment site (EucFACE).  We parametrized a process-based model with in situ physiological and quantified the carbon and water fluxes under ambient and elevated Ca.  We also conducted a attribution analysis to explore the influence of changes in plant physiology.  Our findings suggested the Ca response in the evergreen woodland being much lower than the change of Ca potentially and modified by plant physiology. 

The code for this project is fully aviabible through bitbucket. 

The paper is publised in Biogeosciences.