APSIM Symposium – Keynotes

The draft program is provided here.  Please be aware that timing may change.

The APSIM Symposium is focusing on 3 areas:

1. Whole Farm, Crop and Livestock Modelling

2. Cutting Edge Software and Tools

3. Genotype, Environment, Management (GxExM)

There are 4 keynote presentations for each of the above sessions as well as one on Advances in APSIM Software.  These abstract for the keynotes are below:

Session 1 – Challenges and opportunities for farm and livestock modelling – what’s in APSIM and what is on the way

Val Snow, AgResearch

About five years ago Snow et al. (2014) outlined some of the challenges and opportunities for modelling grazed systems and whole farms (as opposed to individual paddocks). These features include: (i) plant systems that are biologically diverse so interactions between plant species must be considered; (ii) economic return requires the inclusion of the animal as an additional trophic level; (iii) interaction between the grazing animal and the pasture is complex, influenced by the environment, plant species and animal behaviour and this creates feedbacks that can result in vicious cycles; (iv) animals spatially transfer substantial amounts of nutrients both randomly and systematically and this creates or exacerbates soil variability; and (v) whole farm management is both more complex and more important to system function in grazed compared to arable systems and it is harder to capture in simulation models. Since then there have been advances in APSIM that assist in addressing modelling these complex systems – some of these are in release or are currently under development. This presentation will outline these new developments and discuss the outstanding needs and requirements.

Snow, V.O., Rotz, C.A., Moore, A.D., Martin-Clouaire, R., Johnson, I.R., Hutchings, N.J., Eckard, R.J., 2014. The challenges – and some solutions – to process-based modelling of grazed agricultural systems. Environmental Modelling & Software 62, 420-436.


Session 2 – Genotype, Environment, Management (GxExM)

On the nature of crop models (and modellers) needed to advance crop adaptation and improvement (GxExM)

Graeme Hammer, University of Queensland

Modelling and simulation provide an avenue to advance crop adaptation and improvement. Serious play with dynamic crop growth and development models (CGM) enables one to explore consequences of potential agronomic and breeding interventions in design of crops for production systems. Using simplified mathematical representations of the interacting biological and environmental components of the dynamic soil–plant–environment system, CGM can reliably predict trajectories of crop attributes through the crop life cycle, i.e. the emergent phenotype. Environmental (E), genetic (G), and management (M) influences, and hence their dynamic interactions (GxExM), can be incorporated via the nature and coefficients of the response and control equations in the model and aspects of its initialization.   Here, I will consider examples of applications relevant to agronomy and breeding. The potential to use CGM to advance such applications to crop adaptation and improvement requires a “credible” model that is fit for purpose along with informed users that are aware of the biological underpinning and functional dynamics of the CGM (Hammer et al. 2019). Here I will discuss these concepts in relation to the need to progress rigour and transparency in the effective future use of CGM technology.

Hammer, G., Messina, C., Wu, A., and Cooper, M. (2019) Biological reality and parsimony in crop models – why we need both in crop improvement! In Silico Plants 2019: diz010. doi: 10.1093/insilicoplants/diz010


Session 3 – Cutting Edge Software and Tools

Lifecycle model development

Jeremy Whish, CSIRO

About 5 years ago Whish et al. 2015 described a method of including population models within APSIM Classic for the modelling of weed seed banks, pathogens and diseases by linking with DYMEX. To further expand the systems capability of APSIM NextGen a lifecycle development framework has been created to seamlessly build lifecycle models of seed banks, pathogens and diseases within APSIM. This framework takes advantage of PMF architecture to interact with different APSIM models. Generic coupling points have been identified and these will be included within all NextGen models to facilitate dynamic interactions between pest populations and crops.

Whish, J.P.M., Herrmann, N.I., White, N.A., Moore, A.D., Kriticos, D.J., 2015. Integrating pest population models with biophysical crop models to better represent the farming system. Environmental Modelling & Software 72, 418–425. doi:10.1016/j.envsoft.2014.10.010



Session 4 – Advances in APSIM Software

Dean Holzworth, CSIRO

Since 2014, the APSIM Initiative has been building a new generation of APSIM, migrating models and functionality as required from APSIM 7.10 to a modern software framework. APSIM Next Generation has been officially released and can now, in some situations, be used for project work.

This talk presents the reasons for creating APSIM Next Generation, discusses what functionality is available within APSIM Next Generation and what models are available. Also presented will be a discussion on what will happen with the existing version of APSIM 7.10.

Holzworth, Dean, N. I. Huth, J. Fainges, H. Brown, E. Zurcher, R. Cichota, S. Verrall, N. I. Herrmann, B. Zheng, and V. Snow. “APSIM Next Generation: Overcoming Challenges in Modernising a Farming Systems Model.” Environmental Modelling & Software 103 (May 1, 2018): 43–51. https://doi.org/10.1016/j.envsoft.2018.02.002.