Advances in Silviculture of Intensively Managed Plantations

Purpose of Review Intensive management of forest plantations has evolved significantly in recent decades because of advances in our understanding of environmental and silvicultural effects on forest productivity combined with improvements in information technologies. Our paper summarizes concepts that provide a basis for making strategic and operational silvicultural decisions that insure sustainability when applying intensive management of forest plantations. In addition, we include new information in areas where there are knowledge gaps in forest plantation management. Recent Findings Intensive management of forest plantations increasingly incorporates large-scale precision silviculture to estimate silvicultural, biotic, and abiotic effects on site-specific forest productivity. Remote sensing measurements combined with strategically located ground information provide spatial modeling tools needed for this type of silviculture. Long-term field experiments, which are a part of this methodology, provide a mechanistic understanding of environmental and silvicultural effects on forest production that is required for the models driving silvicultural decisions. The focus on maximizing production will challenge scientific efforts to alleviate concerns about intensive land use and to provide solutions for water use conflicts while maintaining long-term productivity and sustainability. Future work will need to develop a better understanding of genetic x environment x silvicultural (G x E x S) interactions to improve productivity and simultaneously provide improved ecosystem services. Summary New silviculture technology combines remote sensing information with ground data to model resource availability and limitations to forest productivity. Understanding G x E x S permits successful implementation of these new silvicultural technologies. An improved understanding of G x E x S will provide practical tools that may be incorporated into our scientific and technical models while providing robust economic sustainability.