Optimizing stand management involving the effect of genetic gain: preliminary results for Scots pine in Finland

Abstract

A solid starting point for assessing tree-improvement programs would be to determine the effect of genetic gain in economic terms at stand level. This paper presents a stand-level optimization analysis of the use of improved seed material in reforestation from the perspective of forest owners. We used a genetic algorithm to study the effects of optimized stand management on the bare land value (BLV) for both genetically improved and unimproved reforestation material, with increase in BLV (ΔBLV > 0) representing the deployment benefit over the standard tree-improvement program. The stand-level optimization analysis was applied to a case representative of economic and climatic circumstances in Finland. The results show that the absolute increase in the BLV is distinctly higher in southern Finland than in central Finland, let alone northern Finland, regardless of the interest rate (3% or 4%) or genetic gain (3% or 15%). Sensitivity analyses revealed that market-related risks need to be taken into account carefully. Our tentative results provide new insight on the financial incentives for using genetically improved seed material in Scots pine (Pinus sylvestris L.) stand establishment under varying climatic conditions, but the subject merits further investigation — with greater detail and a more systematic data structure.