Conserving woodland caribou habitat while maintaining timber yield: a graph theory approach

Abstract

The fragmentation and loss of old-growth forest has led to the decline of many forest-dwelling species that depend on old-growth forest as habitat. Emblematic of this issue in many areas of the managed boreal forest in Canada is the threatened woodland caribou (Rangifer tarandus caribou (Gmelin, 1788)). We develop a methodology to help determine when and how timber can be harvested to best satisfy both industrial timber supply and woodland caribou habitat requirements. To start, we use least-cost paths based on graph theory to determine the configuration of woodland caribou preferred habitat patches. We then developed a heuristic procedure to schedule timber harvesting based on a trade-off between merchantable wood volume and the remaining amount of habitat and its connectivity during a planning cycle. Our heuristic can attain 84% of the potential woodland caribou habitat that would be available in the absence of harvesting at the end of a 100 year planning horizon. Interestingly, this is more than that which is attained by the current plan (50%) and a harvesting plan that targets high volume stands (32%). Our results indicate that our heuristic procedure (i.e., an ecologically tuned optimization approach) may better direct industrial activities to improve old-growth habitat while maintaining specified timber production levels.

The functional complex network approach to foster forest resilience to global changes

“…b Territory with a good overall resilience with a good functional diversity (e.g., value of 2.3), good connectivity (26 links with many of them being strong) and a high centrality (2.94 links per dot) landscape to consider dynamic changes occurring both at the stand and landscape scales (Martensen et al 2017;Saura 2018). Simulation modelling could also be used to determine what type of silvicultural interventions should be performed and where to obtain the desirable objectives over time and over a large spectrum of possible future scenarios (Ruppert et al 2016;Aquilué 2018). As a first rule to link stand and landscape scales, managers may choose to intervene in stands and/or forest ownerships having the lowest functional diversity while prioritizing those that can positively affect most of the selected indicators at the landscape level (e.g., the two stands with an asterisk in Fig.…”

A replanning approach for maximizing woodland caribou habitat alongside timber production

“…Earlier research (Ruppert et al, 2016) found that the caribou mosaic is not optimal for joint planning of timber harvesting and caribou habitat conservation. The heuristic developed by Ruppert et al (2016) (henceforth referred to as the harvesting heuristic) outperformed the caribou mosaic plan by maintaining 79% of the maximum possible amount of caribou habitat versus the caribou mosaic which maintained 60% of the maximum possible amount of caribou habitat. The maximum possible amount of caribou habitat is defined as the amount of caribou habitat measured using a no-harvest model over the same planning horizon and forest.…”

“…The maximum possible amount of caribou habitat is defined as the amount of caribou habitat measured using a no-harvest model over the same planning horizon and forest. To achieve that outcome, Ruppert et al (2016) used a graph theory approach, where preferred habitat patches of caribou are nodes and potential movement paths for caribou are arcs connecting those nodes. Specifically, they measured caribou habitat using the Equivalent Connected Area (ECA) metric which is based upon the amount of preferred habitat patches and how well they are connected on the landscape (Saura et al, 2011).…”

“…Using this classification, potential movement paths are created using a cost surface (planning units assigned values in Table 1), whereby the potential movement of caribou or arcs are constructed to represent the least costly path between nodes (i.e., least-cost paths are a function of the distance D r a f t and additive costs of each arc along a cost surface) (Adriaensen et al 2003;Fall et al 2007). The ECA value for each forest stand is then computed based on the marginal contributions of individual patches of caribou habitat, determined from the simulation, to the overall habitat connectivity of the landscape (Ruppert et al, 2016). Finally, a heuristic harvest value of each stand is calculated, which is a weighted function of the volume of merchantable wood in the stand were it to be harvested and the decrease in suitable habitat that might result were that to happen.…”

“…We utilize this caribou value for forest stands and advance the research of Ruppert et al (2016) by developing an optimization framework that allows one to identify timber harvest schedules that provide a higher ECA value for the landscape than their harvesting heuristic while meeting the same timber harvest targets. We accomplish this by replacing the harvesting heuristic with a linear programming (LP) optimization model (Dantzig, 1963), and running that model repeatedly within a replanning framework.…”