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The economic impact of optimising radiata pine stand density

The-economic-impact-of-optimising-radiata-pine-stand-density

Optimising radiata pine stand density could increase the net value of New Zealand’s plantation estate by $1.7B.
 
Scion scientists have used the productivity indices Site Index (SI) and 300 Index (I300) to develop a model that predicts the optimum final crop stand density (Sopt) for a standard structural grade regime. Using this model they were able to develop productivity maps, or surfaces of Sopt covering the whole country. 
 
The average predicted Sopt for growing structural grade logs across New Zealand was found to be 614 stems per hectare. As the current final stand density for structural grade regimes averages around 500 stems per hectare there is definite scope for increasing the volume of high-value log products. 
 
Most recently, the researchers have run a series of simulations to check the accuracy of the model’s Sopt predictions, and to look at the potential economic gains of optimising stand density.
 
Net value per hectare, internal rate of return (IRR) and net present value (NPV) were all found to increase linearly as stand density approached Sopt; beyond Sopt values increased very slowly or plateaued.
 
Increasing stand density to Sopt will result in gains in gross and net value of around $5,200 and $2,320 per hectare and a 0.44% increase in IRR. The potential gains for the entire plantation estate are $3.8B (gross) and $1.7B (net), which, when discounted, are equal to $349M and $156M in 2017.
 
Forest owners and managers can use the developed model with input parameters that reflect their specific situation to plan targeted operations to optimise stand density and maximise the value of their crop. 

Watt, M. S., Kimberley, M. O., Dash, J. P., Harrison, D., Monge, J. J., & Dowling, L. (2017). 

The economic impact of optimising final stand density for structural saw log production on the value of the New Zealand plantation estate. Forest Ecology and Management, 406, 361-369.

https://doi.org/10.1016/j.foreco.2017.07.044

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