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首页> 外文学位 >Predicting Impacts on Balsam Fir due to Hemlock Looper and Balsam Fir Sawfly Defoliation for a Decision Support System.
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Predicting Impacts on Balsam Fir due to Hemlock Looper and Balsam Fir Sawfly Defoliation for a Decision Support System.

机译：预测由于Hemlock Looper和Balsam Fir锯齿落叶对决策支持系统的影响而对Balsam冷杉造成的影响。

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摘要

Some of Canada's major insect pests periodically attack balsam fir (Abies balsamea (L.) Mill.) with results that are economically catastrophic. It is a preferred host for severely damaging defoliators like spruce budworm (Choristoneura fumiferana Clem.), balsam fir sawfly (Neodiprion abietis Harris) and hemlock looper ( Lambdina fiscellaria fiscellaria Guen.). Though much is known about spruce budworm defoliation and its related impacts, very little information existed about the remaining two species which differ in their feeding behavior. This dissertation quantifies and compares defoliation and impacts on host trees at the tree, stand and forest level due to the three insects. The quantified information was used to build and implement decision support system (DSS), allowing discussion of key policy alternatives for reducing impacts on Forest Management District 15, Newfoundland.;Firstly, cumulative defoliation due to balsam fir sawfly and hemlock looper was estimated from defoliation per age class of foliage and compared to aerial defoliation surveys. Knowing the importance of defoliation prediction in pest management, a Bayesian Network model was proposed that improved and automated defoliation prediction for balsam fir sawfly. Key component of DSS, i.e., empirical relationships between defoliation and impacts (growth and mortality) were quantified from permanent sample plot data and dendrochronology. Following the existing spruce budworm DSS framework, STAMAN stand growth model was used to grow stands with and without defoliation thus calculating % stand volume losses and timber volume loss across a forest landbase.;It was estimated that defoliation caused by balsam fir sawfly from 1996-2008 has caused maximum total operable softwood growing stock and softwood harvest volume reductions of 26% and 31%, respectively. In contrast, defoliation caused by hemlock looper in the same period caused a maximum 3% reduction in softwood harvest levels. Hemlock looper was found to produce maximum impacts followed by balsam fir sawfly and spruce budworm. Due to long-term legacy effects on stand yields and delayed recovery, harvest volume reductions may occur for up to 50 years after outbreak collapse. Re-optimization of harvest schedules can be used to calculate new even-flow long term harvest levels and reduce impacts at the forest scale. Best management option for reducing damage depends on type, severity and extent of insect damage, but consists of a combination of thoughtful, well planned biological insecticide protection as well as forest management approach through harvest level reductions, harvest rescheduling and salvage.
机译：加拿大的一些主要害虫定期袭击香脂冷杉（Abies balsamea（L.）Mill。），其结果在经济上是灾难性的。它是严重破坏落叶者的首选寄主，例如云杉芽虫（Choristoneura fumiferana Clem。），香脂杉木锯蝇（Neodiprion abietis Harris）和铁杉弯钩（Lambdina fiscellaria fiscellaria Guen）。尽管人们对云杉芽虫的脱叶及其相关影响知之甚少，但关于其余两种物种的摄食行为不同的信息很少。本文对这三种昆虫在树木，林分和森林水平上的落叶和对寄主树的影响进行了量化和比较。量化的信息用于建立和实施决策支持系统（DSS），从而可以讨论减少对纽芬兰的森林管理区15影响的关键政策替代方案。首先，从脱脂中估计出香脂木锯蝇和铁杉弯钩造成的累积脱叶。每个年龄段的叶子，并与空中落叶调查进行比较。知道了落叶预测在害虫管理中的重要性，提出了贝叶斯网络模型，该模型改进了香脂冷杉锯蝇的改进的自动落叶预测。 DSS的关键组成部分，即落叶和影响（增长和死亡率）之间的经验关系是根据永久性地块数据和树木年代学来量化的。根据现有的云杉bud虫DSS框架，使用STAMAN林分生长模型来种植有无落叶的林分，从而计算出整个森林陆基的林分体积损失和木材体积损失的百分比。;据估计，从1996- 2008年，可操作的针叶木种植总量和针叶木采伐量的最大总量分别减少了26％和31％。相反，在同一时期，铁杉弯弯造成的落叶使针叶木采伐量最多降低了3％。发现铁杉弯钩产生最大的影响，其次是香脂杉木锯蝇和云杉芽虫。由于对林木单产的长期遗留影响和恢复的延迟，暴发暴发后长达50年的收成可能会减少。重新优化采伐时间表可用于计算新的平均流量长期采伐水平，并减少对森林规模的影响。减少损害的最佳管理方案取决于昆虫损害的类型，严重性和程度，但包括周到的，计划周密的生物杀虫剂保护以及通过降低收获水平，重新安排收获和进行挽救的森林管理方法的结合。

著录项

  • 作者

    Iqbal, Javed.;

  • 作者单位

    University of New Brunswick (Canada).;

  • 授予单位 University of New Brunswick (Canada).;
  • 学科 Agriculture Forestry and Wildlife.
  • 学位 Ph.D.
  • 年度 2011
  • 页码 229 p.
  • 总页数 229
  • 原文格式 PDF
  • 正文语种 eng
  • 中图分类
  • 关键词

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