Intensive silviculture and competition theory: linking practice and science

集约化造林（IS）可以解决目前加拿大工业林业和支持它的陆地基础面临的一些挑战。这些挑战包括商业纤维的短期过度使用，对更多受保护空间的要求以及对包括高质量木材在内的各种产品的需求。IS的处方是基于对北方森林系统竞争性质的假设。首先，大部分场地资源可以有效地用于作物树木（竞争性排斥），一些物种混合更好地分配了可用资源（竞争性生产）。我们的项目调查了两个假设，将解决这些假设，并为开发更有效的信息系统干预措施提供指导。我们将在安大略省西北部和东北部使用四个已建立的试验，在林分发展的三个关键阶段-建立（5年），树冠闭合（20年）和成熟（超过100年）。新的实地和实验室工作将补充历史数据集，以更好地估计地上和地下参数，包括根结构和分层。DNA条形码将用于鉴定根和真菌组织。测量和基于过程的数据将为新的树级模型提供基础，该模型将与树高和/或树冠尺寸相联系。我们的私营部门合作伙伴Tembec公司和森林研究伙伴关系需要这样一个模型来预测IS战略对目标物种和其他关键生态系统参数（如土壤有机质、养分矿化率、树木层生产力）的影响。我们的公共部门合作伙伴，安大略森林研究所和加拿大林务局，要求这一科学为森林管理政策的制定提供信息。我们所有的合作伙伴都将全面参与数据的收集、模型的开发、研究生的监督/指导和其他HQP。

Intensive silviculture (IS) may resolve some of the challenges currently facing industrial forestry and the landbase that supports it in Canada. These challenges include a short-term over- commitment of commercial fibre, calls for more protected spaces and demand for an increasing variety of products, including high quality wood. IS prescriptions are based on assumptions about the nature of competition in boreal forest systems. First, that the majority of site resources can be effectively directed to crop trees (competitive exclusion) and that some species mixtures better partition the resources available (competitive production). Our project investigates two hypotheses that will address these assumptions and provide guidance for the development of more effective IS interventions. We will use a series of four established trials, in northwestern and northeastern Ontario, at three critical stages of stand development - establishment (5 years), crown closure (20 years) and mature (over 100 years). Historical datasets will be supplemented by new field and laboratory work to capture better estimates of above- and below-ground parameters including root structure and stratification. DNA bar coding will be used to identify root and fungal tissues. Mensurational and process-based data will provide the basis for a new tree-level model that will be linked to tree height and/or crown dimension. Our private sector partners, Tembec Inc and the Forest Research Partnership, require such a model to predict the effects of IS strategies on target species and other key ecosystem parameters (e.g. soil organic matter, nutrient mineralization rates, tree layer productivity). Our public sector partners, Ontario Forest Research Institute and the Canadian Forest Service, require this science to inform the development of forest management policy. All our partners will participate fully in the collection of data, the development of the model and the supervision/mentoring of graduate students and other HQP.