Provenance and Family Variation in Biomass Potential of Loblolly Pine in the Piedmont of North Carolina

Considerable genetic differences in loblolly pine (Pinus taeda L.) exist for growth, stem form, and wood quality traits that influence biomass/biofuel production. By planting genetically superior trees with desirable biomass/biofuel traits, it is possible to substantially increase the amount of biomass and potential sawtimber trees produced from plantations. Ten of the fastest growing loblolly pine families from two provenances, Atlantic Coastal Plain and Piedmont, were tested for their biomass potential in North Carolina on a Piedmont site. At this northern Piedmont site at age six years, there were no provenance differences for biomass production or for trees with sawtimber potential. Variation in volume and sawtimber potential was significant at the family level. For biomass plantations, risks can be mitigated because of shorter rotation length, allowing for a higher-risk seed lot to capture greater gains in terms of volume. For a longer-rotation sawtimber stand, a more conservative family deployment strategy should be considered to maintain stem quality at the end of the rotation. Understanding the different seed source families and harvest regimes is essential to ensure profitable returns from pine plantations. Study Implications Landowners in the southeastern United States have more choices than ever before regarding the choice of genetic stock of loblolly pine seedlings they plant, and the family selection should reflect the stand management objectives with regard to growth, stem form, and wood quality traits. In a biomass/biofuel production regime, planting families from nonlocal seed sources for increased growth can potentially increase the amount of biomass and sawtimber produced from the plantation, although risks such as increased susceptibility to winter storm damage must be considered. For biomass plantations, with shorter rotation lengths, risks can be reduced allowing for a higher-risk genotype to capture the greater gains in volume. For a sawtimber stand, genotype selections should be more conservative to ensure stem quality at the end of the rotation. Understanding different genotypes and harvest regimes is essential to maximize profit from plantations.

Modelling harvest of Asian elephants Elephas maximus on the basis of faulty assumptions promotes inappropriate management solutions

A ratio-based logistic model developed to assess elephant harvest rates, based on a study at Nagarhole Tiger Reserve in India, was recommended as a management tool to control human–elephant conflict through culling. Considering this reserve among others violates an assumption of the logistic model: isolation. Nevertheless, assuming this violation was irrelevant, we re-evaluated the model, with minor modifications, for the neighbouring Mudumalai Tiger Reserve, where we used data from 13 elephant Elephas maximus population surveys to derive bootstrapped sets of population ratios, and mortality records. We generated arrays of harvest regimes and examined which ratio outputs were closest to the bootstrapped ratios. Our results indicated that (1) model outputs corresponded best with the Mudumalai population structure when harvest regimes were extreme and unlikely, (2) there were significant differences in population structure and harvest regimes between Nagarhole and Mudumalai, and (3) only 49% of adult male deaths predicted by model outputs were recorded in official governmental records. The model provides significantly different results among reserves, which invalidates it as a tool to predict change across the entire elephant population. Variability in survey data and inaccuracies in transition probabilities are sufficiently large to warrant caution when using them as a basis for deterministic modelling. Official mortality databases provide a weak means of validation because poaching incidents are poorly recorded. We conclude that the model should be based on validated transition probabilities and encompass the entire regional population.