The translation of genetic gains into economic gains is important for evaluating the impact of using genetically improved forest reproductive material (FRM) in the forest sector. However, few studies based on European forests have been published to date. Here, we analyse the stand-level wood production and financial performance of planting genetically improved FRM in even-aged planted forests focusing on four European case studies with advanced breeding programme material and different management contexts: Scots pine (Pinus sylvestris L.) in southern Finland, central Sweden and central France, and maritime pine (Pinus pinaster Ait.) in southwestern France. The growth of improved stands was simulated using species-specific growth models by incorporating two levels of expected genetic gains (present and next generations of seed orchards, varying from 7 to 40 per cent depending on the breeding programme) into the estimated mean annual volume increment over a rotation (m3 ha−1 yr−1). For each level of genetic gain, we tested the plantation of improved FRM managed with two silvicultural scenarios (maintaining the standard baseline rotation and thinning regime vs shorter rotation through the earlier achievement of the recommended felling criteria) in comparison with the plantation of the reference unimproved material (absence of genetic gain) managed according to the standard silvicultural regime. The use of improved FRM resulted in a larger financial performance in terms of soil expectation value (SEV € ha−1, discount rate 3 per cent) than planting unimproved reference material in all case studies and silvicultural scenarios for different wood price contexts (SEV gain from +20 to +190 per cent depending on the genetic and silvicultural context). The challenges associated with the economic assessment of realized gains from genetically improved FRM are discussed. We argue that silvicultural guidelines should be adapted to the use of improved FRM in order to gain better financial performance and flexible silvicultural response of planted forests to future environmental and socio-economic changes.
Variability in functional traits (FT) is increasingly used to understand the mechanisms behind tree species interactions and ecosystem functioning. In order to explore how FT differ due to interactions between tree species and its influence on stand productivity and other ecological processes, we examined the effects of tree species composition on the intra-specific variability of four widely measured FT: specific leaf area (SLA), leaf nitrogen content (NC), leaf angle (AL), and stomatal conductance (gs) response to vapor pressure deficit. This study focused on three major central European tree species: European beech (F. sylvatica L.), Sessile oak (Q. petraea Liebl.), and Norway spruce (P. abies Karst.). Each species was examined in monoculture and 2-species mixtures in the 13-year-old tree biodiversity experiment BIOTREE-Kaltenborn. Trait distributions and linear mixed models were used to analyze the effect of species mixing, tree size and stand variables on the intra-specific FT variability. A significant effect of branch height on most traits and species indicated a vertical gradient of foliar trait frequently related to light availability. Beech and oak showed a high overall trait variability and sensitivity to species mixing and stand basal area, while the trait variability of spruce was limited. Greater shifts in trait distributions due to mixing were found in SLA for oak and NC for beech. Thus intra-specific variability of key leaf traits was already influenced at this young development stage by inter-specific interactions. Finally, we used the 3-PG process-based forest growth model to show that the measured intra-specific variability on single FT values could influence stand productivity, light absorption and transpiration, although the net effect depends on the considered trait and the species composition of the mixture. The results of this study can help to better understand the effects of inter-specific competition on intra-specific FT variability, which has implications for the parameterization of process-based forest growth models and our understanding of ecosystem functioning.
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