Abstract
Global climate is changing due to increasing anthropogenic emissions of greenhouse gases. Forest managers need growth and yield models that can be used to predict future forest dynamics during the transition period of present-day forests under a changing climatic regime. In this study, we developed a forest growth and yield model that can be used to predict individual-tree growth under current and projected future climatic conditions. The model was constructed by integrating historical tree growth records with predictions from an ecological process-based model using neural networks. The new model predicts basal area (BA) and volume growth for individual trees in pure or mixed species forests. For model development, tree-growth data under current climatic conditions were obtained using over 3000 permanent sample plots from the Province of Nova Scotia, Canada. Data to reflect tree growth under a changing climatic regime were projected with JABOWA-3 (an ecological process-based model). Model validation with designated data produced model efficiencies of 0.82 and 0.89 in predicting individual-tree BA and volume growth. Model efficiency is a relative index of model performance, where 1 indicates an ideal fit, while values lower than zero means the predictions are no better than the average of the observations. Overall mean prediction error (BIAS) of basal area and volume growth predictions was nominal (i.e., for BA: -0.0177 cm2 5-year-1 and volume: 0.0008 m3 5-year-1). Model variability described by root mean squared error (RMSE) in basal area prediction was 40.53 cm2 5-year-1 and 0.0393 m3 5-year-1 in volume prediction. The new modelling approach has potential to reduce uncertainties in growth and yield predictions under different climate change scenarios. This novel approach provides an avenue for forest managers to generate required information for the management of forests in transitional periods of climate change. Artificial intelligence technology has substantial potential in forest modelling.
Highlights
Climate change has become an important issue of the 21st century
A process-based gap model (i.e., JABOWA-3) was used to project tree growth under three climate-change scenarios [29]. This model simulates tree growth based on key assumptions: i.e. (1) trees grow at a maximum rate under optimal conditions, which is influenced by maximum tree age, diameter, and height; (2) tree growth is controlled by biotic and abiotic factors such as inter-tree competition, temperature, and soil water and nutrient content
BIAS is calculated from denormalised data using eq (6); basal area (BA) increment; volume increment (m3 5year-1). doi:10.1371/journal.pone.0132066.t003
Summary
Climate change has become an important issue of the 21st century. Climate change will modify treegrowing environments by altering site conditions, such as soil water content, atmospheric humidity, soil and air temperatures, and the length of growing seasons. The forest industry is expected to be the most affected by climate change, compared to other resource-based industries. This is because normal harvesting rotations for timber range from 50 to 100 years for most tree species and present-day forests are expected to experience a period of transition from current to future growing conditions over the 100 years. Forests provide important socioeconomic and ecological services, and existing forests cannot be replaced quickly over the short term to accommodate the anticipated changes in tree-growing environment. Existing forests need to be managed during this period of transition with well-informed management plans that account for the effects of climate change
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