Canadian Forest Service Publications

Protecting wildlife habitat in managed forest landscapes—How can network connectivity models help? Yemshanov, D., Haight, R.G., Rempel, R., Liu, N., Koch, F.H., Natural Resource Modeling. (2021) 34:12286.

Year: 2021

Issued by: Great Lakes Forestry Centre

Catalog ID: 40485

Language: English

Availability: PDF (download)

Available from the Journal's Web site.
DOI: 10.1111/nrm.12286

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Plain Language Summary

Industrial forestry in boreal regions increases fragmentation and may decrease the viability of some wildlife populations, particularly the woodland caribou, Rangifer tarandus caribou. Caribou protection often calls for changes in forestry practices, which may increase the cost and reduce the available timber supply. We present a linear programming model that assesses the trade‐off between habitat protection and harvesting objectives by combining harvest scheduling and optimal habitat connectivity problems. We formulate the habitat connectivity model as a network flow problem that maximizes the amount of habitat connected over a desired time span in a forested landscape, while the forestry objective maximizes net undiscounted revenues from timber harvest subject to even harvest flow and environmental sustainability constraints. We applied the approach to explore the trade‐off between caribou habitat protection and harvesting goals in the Armstrong‐Whitesand Forest, Ontario, Canada, a boreal forest area with prime caribou habitat. Our model also incorporates Dynamic Caribou Harvesting Scheduling (DCHS), a harvest policy currently in a place in Ontario that aims to balance the forest management and caribou protection goals in northern boreal regions. In our study area, the implementation of DCHS appears to have relatively minor impact on timber supply cost. By comparison, maximizing the protection of caribou habitat would lead to a noticeable increase of the mill gate timber cost by $3.3 m−3 on average, while enabling habitat protection in an additional 5.0%–9.5% of the range area. Our model is generalizable and can be adapted for assessing habitat recovery and harvest goals in other regions.