Variation in Volume Production Through Clonal Deployment: Results From a Simulation Model to Minimize Risk for Both a Currently Known and Unknown Future Pest

Abstract

A simulation model was developed to examine optimum patterns of deploying selected clones in the hypothetical situations of both a currently known pest and an unknown future pest. We modelled the interactions between Sitka spruce (Picea sitchensis (Bong.) Carr.), an economically important forest tree in British Columbia and the northwestern U.S., and the spruce terminal weevil (Pissodes strobi (Peck)), a major pest in western spruces. The model is combined with the Province of British Columbia's Tree and Stand Simulator (TASS) model to drive individual tree growth and stand establishment and development.Two clonal-sampling strategies are examined: a randomly drawn set of genotypes or clones, to depict the potential consequences of a new (e.g., exotic) or a previously unimportant natural pest attacking a 'random' set of genotypes, and a 'fixed' set of clones, emulating a 'commercial' or known set of clones for growth and resistance mechanisms. Simulations use a range of numbers of genotypes or clones (2, 6, 18 and 30), and three deployment patterns (a random mixture of ramets, single-clone blocks, and a mosaic of smaller clonal blocks), in one and five hectare (Ha) stands. Total merchantable timber volume on a per Ha basis at harvest age 80 is used to compare the various combinations and schemes.With both random and fixed chosen sets of clones, the random planting pattern (i.e., random mixture of ramets from the clonal set) produced the most volume. Eighteen randomly chosen clones generally produced more volume, than 2, 6 and 30 clones, but differences among 6, 18 and 30 clones were small in most cases, irrespective of planting pattern. For fixed clones, the use of more resistant clones with higher growth potential produced more volume; however, pure clonal blocks of the best clone were not better than a mixture of that clone and an inferior one. Reducing the effects of insect activity and attack on trees, by lowering the average annual temperature in the model, or turning off all insect 'activity', increased merchantable volume but did not change the optimum number of clones (~18) or deployment pattern (random mixture). Forestry agencies can weigh these findings against economic advantages of block plantings of similar genotypes, in the choice of an appropriate number of clones and a deployment strategy.

Evaluation of genetic variation of attack and resistance in lodgepole pine in the early stages of a mountain pine beetle outbreak

“…Particular mechanisms that may be operating in this subset of families are of course unknown at this point, but clearly there is differential exclusion of bark beetles among these genotypes and these variations are likely to be due to some type of response to visual or olfactory bark cues (Shepherd 1966;Strom et al 1999). In a different population and test of lodgepole pine (but with parents from the same general provenances' areas assessed in this study), Yanchuk (1986) estimated the genetic correlation between bark thickness and height growth to be −0.18 (SE=0.24), but 0.63 (SE= 0.20) for diameter. Therefore, some of the taller growing families may tend to have thinner bark or some other antixenosis characteristics related to differential success of colonization attempts.…”

“…Most of the parent-tree collections were made from local sources in the PG LO; however, parents from several provenances or populations outside the PG LO are included in the test, as these have proven well in provenance tests in the PG LO and similar climates (Rehfeldt et al 1999). Population and quantitative genetic variations in other attributes have been reported previously for similar populations and tests of lodgepole pine from this area, for traits such as height growth, stem rusts and pitch moth, and wood properties (Wu and Ying 1997;Xie and Ying 1996;Yanchuk 1986;Ying and Liang 1994), so the quantitative genetics for lodgepole pine populations in this geographic area of BC are well documented. Height (HT) at age 10 was the last height measure made on this trial, so we used this measure of growth potential to look at relationships between differential attack and growth.…”

Genetic diversity and forest reproductive material - from seed source selection to planting

“…This number with level of risk similar to forest established by seedlings, ranges from seven (Libby 1982) to 30 unrelated clones (Libby & Ahuja 1993). More recent researches confirmed these recommendations (Bishir & Roberds 1999, Yanchuk et al 2006. For slow-growing species, a larger number of clones must be used.…”

“…For the establishment of SO in Finland the minimum number of clones is 30 (Koski 1980) and in Sweden the proposed number is 20 clones (Lindgren & Prescher 2005). Concerning the number of clones to include in the establishment of SO, different recommendations are made by a number of authors: more than 20 clones (Johnson & Lipow 2002), no more than 30 (Yanchuk et al 2006) or 40 (Bishir & Roberds 1999), between 30 to 40 (Roberds & Bishir 1997), more than 40 (Koski 2000). However, not all clones should be represented with an equal number of ramets (Lindgren 1974, Lindgren & Matheson 1986, Hodge & White 1993).…”

A comparative evaluation of the application of somatic embryogenesis, rooting of cuttings, and organogenesis of conifers

“…The level of risk is unlikely to be reduced if the number of clones exceeds 30-40 (Bishir and Roberds 1999). Another model suggests that approximately 18 genotypes are optimal under many conditions and that, for merchantable volume, no more than 30 clones are needed for risk protection and near-optimal timber yield (Yanchuck et al 2006). This model also indicates that planting blocks with a mixture of clones has advantages over planting a mosaic of blocks, with each block containing a different single superior clone.…”