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

尽管在过去二十年中，加拿大在采取更全面的可持续森林管理方法方面取得了相当大的进展，但加拿大土地管理者需要更好的工具来有效地管理北方景观，以实现从木材生产力到生态系统功能和生物多样性等一系列价值。新的造林方法，例如可变保留采伐，正日益被接受为实现以生态为基础的可持续森林管理目标的一种方法。尽管如此，关于这些做法的影响，我们还有很多需要了解的，更重要的是，我们如何在景观上最佳地部署它们，以支持自然生物多样性，同时最大限度地提高潜在的森林生产力。

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.