Tools for managing forest productivity and biodiversity in relation to ecosystem function in boreal mixedwood forests

管理与北方混交林生态系统功能相关的森林生产力和生物多样性的工具

• 批准号: 447251-2013
• 负责人: Macdonald, Ellen
• 金额: $ 15.99万
• 依托单位: University of Alberta
• 依托单位国家: 加拿大
• 项目类别: Strategic Projects - Group
• 财政年份: 2015
• 资助国家: 加拿大
• 起止时间: 2015-01-01 至 2016-12-31
• 项目状态: 已结题
• 来源: https://www.nserc-crsng.gc.ca/ase-oro/Details-Detailles_eng.asp?id=575286
• 关键词: Tools; managing; forest; productivity; biodiversity

Despite considerable progress over the past two decades towards a more holistic approach to sustainable forest management (SFM) Canadian land managers require better tools to effectively manage boreal landscapes for a range of values - from timber productivity, to ecosystem function and biodiversity. New silvicultural approaches, such as variable retention harvesting, are increasingly being accepted as an approach to achieve the objectives of ecologically-based SFM. Still, we have much to learn about the impacts of such practices and, more importantly, how we can optimally deploy them on the landscape in order to support natural biodiversity while maximizing potential forest-site productivity. We will explore the usefulness of data derived from a variety of remote sensing sources, which describe local site conditions, to explain/predict: 1) forest productivity, ecosystem function (soil water - carbon pools and fluxes), and biodiversity (especially, epigaeic arthropods, vascular and non-vascular plants); 2) how these respond and recover following a gradient of variable retention harvesting; and 3) any trade-offs among these often competing values. From this we will develop predictive models which can be used to improve deployment of harvesting on landscapes in an optimal way with respect to site-productivity, carbon storage and natural biodiversity. With refinement, these models can be developed for expanded application to a broader range of landscape disturbances. Our partners will gain tools to achieve a range of objectives in a mixedwood setting using predictor variables easily derived from remote sensing. We will create a knowledge base to inform forest management practices that minimize negative impacts on the forest environment - including maintaining and supporting natural biodiversity - while promoting stand regeneration, maximizing potential forest-site productivity and understanding implications for carbon management. The resulting tools will be useful to optimize deployment of harvesting across forest landscapes in a way that balances environmental costs and benefits.

尽管在过去二十年中在可持续森林管理（SFM）方面取得了相当大的进展，但加拿大土地管理人员需要更好的工具来有效地管理北方景观，以实现一系列价值-从木材生产力到生态系统功能和生物多样性。新的造林方法，如可变保留采伐，越来越被接受为实现基于生态的可持续森林管理目标的方法。尽管如此，我们仍然需要了解这些做法的影响，更重要的是，我们如何能够最佳地将它们部署在景观中，以支持自然生物多样性，同时最大限度地提高森林的生产力。 我们将探索来自各种遥感来源的数据的有用性，这些数据描述了当地的立地条件，以解释/预测：1）森林生产力，生态系统功能（土壤水-碳库和通量）和生物多样性（特别是地上节肢动物、维管和非维管植物）; 2）这些植物如何在可变保留收获梯度之后响应和恢复;以及3）在这些经常竞争的值之间的任何权衡。由此，我们将开发预测模型，这些模型可用于以最佳方式改善景观上的收获部署，包括场地生产力，碳储存和自然生物多样性。经过改进，这些模型可以扩展应用到更广泛的景观干扰。 我们的合作伙伴将获得工具，利用从遥感中很容易得出的预测变量，在混交林环境中实现一系列目标。我们将创建一个知识库，为森林管理实践提供信息，以最大限度地减少对森林环境的负面影响，包括维护和支持自然生物多样性，同时促进林分再生，最大限度地提高林地的潜在生产力，并了解碳管理的影响。由此产生的工具将有助于以平衡环境成本和效益的方式优化整个森林景观的采伐部署。