Jaco-Pierre van der Merwe.
Pine plantation Recent high-resolution climate modelling research has revealed that the suitability of key pine species for plantation forestry will shift dramatically by 2060. The lead author, Dr Jaco-Pierre van der Merwe of York Timbers, says these findings are crucial for everyone invested in the future of forests to enable pre-emptive tree breeding and the introduction of new forest species to mitigate climate change.
Pine plantation forests in South Africa are grown in 20- to 30-year cycles, depending on the required final product. Van der Merwe and a cohort of nine forestry specialists from York Timbers, the Institute for Commercial Forestry Research, and universities argue that it is imperative to anticipate future growing conditions to ensure species selection with optimal growth potential.
The challenge is that existing global and regional climate models (GCMs and RCMs) are too coarse for precision forestry applications, and the researchers wanted to develop improved, high-resolution climate projections that incorporate local terrain and microclimatic variations.
In November 2025, Volume 37 of the Journal of Forestry Research published a seminal article by Dr Jaco-Pierre van der Merwe of York Timbers. The title of the paper is: “High-resolution climate downscaling using terrain features and global circulation models: applications for species suitability in the management of plantation forestry.”
The Department of Science, Technology and Innovation (DSTI) and Forestry South Africa (FSA) supported the project.
The context
South Africa’s plantation forestry sector, primarily located in Mpumalanga, is a significant contributor to the economy, employing around 92,000 people and producing 15 million m³ of roundwood annually.
The sector relies heavily on introduced pine species, notably Pinus elliottii, P. taeda, P. patula, and the hybrid P. patula × P. tecunumanii. These species are matched to sites with climates similar to their native habitats to optimise growth and survival. However, South Africa is a water-scarce country, and climate change is introducing new uncertainties regarding the future viability of these species.
Data and modelling
The researchers referenced climate and terrain data across Mpumalanga and developed models that incorporate climate model outputs and terrain features to predict the mean annual maximum temperature (MAT-max), minimum temperature (MAT-min), and median annual precipitation (MAP-median).
Read more – https://www.woodbizafrica.co.za/november-december-2025-issue-54/26/