Sustainable Forest Management for Optimizing Multispecies Wildlife Habitat: A Coastal Douglas‐fir Example

Abstract

Wildlife species viability optimization models are developed to convert a given set of initial forest conditions, through a combination of natural growth and management treatments, to a forest system which addresses the joint habitat needs of multispecies populations over time. A linear model of forest cover and wildlife populations is used to form a system of forest management control variables for wildlife habitat modification. The paper examines two objective functions coupled to this system for optimizing sustainable joint species viability. The first maximizes the product of periodic joint viabilities over all time periods, focusing management resources on long‐term equilibria, with less emphasis on conversion strategy. The second iteratively maximizes the minimum periodic joint viability over all time periods. This focuses management resources on the most limiting time periods, typically the conversion phase periods. Both objective functions resulted in either point or cyclic equilibria, with cycle lengths equal to minimum forest treatment ages. A third objective, based on maximizing the minimum individual species periodic viability is used to examine single species emphasis. Examples are developed through a case study of 92 vertebrate species found in coastal Douglas‐fir stands of northwestern California.

Extinction risk in cloud forest fragments under climate change and habitat loss

“…However, the dynamic nature of threats, including climate change and land-use change, makes it imperative to include explicit measures of persistence, such as the risk of extinction (Hof & Raphael, 1993;Bevers et al, 1995;Williams & Araujo, 2002;Nicholson & Possingham, 2006), not just implicit measures such as the percentage of a range secured within protected areas. However, the dynamic nature of threats, including climate change and land-use change, makes it imperative to include explicit measures of persistence, such as the risk of extinction (Hof & Raphael, 1993;Bevers et al, 1995;Williams & Araujo, 2002;Nicholson & Possingham, 2006), not just implicit measures such as the percentage of a range secured within protected areas.…”

Alternative targets and economic efficiency of selecting protected areas for biodiversity conservation in boreal forest

“…Church et al (1996) proposed an additive objective function for assigning weights to species. Hof and Raphael (1993) used quite a similar approach as us regarding the species abundance in the context of timber scheduling problem (see also Bevers et al 1995). Moreover, they presented a multiplicative objective function (joint viability) instead of additive form.…”

Where and how to manage: Optimal selection of conservation actions for multiple species.

“…Optimization tools such as the one presented in this paper can aid in more efficient and effective allocation of the available budgets for conservation (Pressey et al 1997;Cowling et al 2003). Earlier studies on multi-action planning (Hof et al 1994;Bevers et al 1995;Holzkämper et al 2006) did not consider action cost in the optimization. Cost of actions can however differ widely, and conservation budgets are typically tight.…”

“…In this case decision is required on which action to apply to which site, such that the benefit for all species is maximized for the given budget. To quantify the effect that each of the restoration actions would have on the species, we use the concept of a benefit function (Hof and Raphael 1993;Bevers et al 1995;Arponen et al 2005Arponen et al , 2007Cabeza and Moilanen 2006). A benefit function f j [R j (X)] is an increasing function of the representation of species j R j (X), which specifies how the conservation value of a network (set of sites X) changes when the species' representation level changes (Figure 1; see Table 1 for a list of symbols used).…”

“…Second, complex trade-offs between species can occur, as the best action for one species could be suboptimal for another species (Van Teeffelen 2007). The data demands for a multi-action reserve selection problem are large as well, and these factors together may be the reason why little has been published concerning optimal multi-action conservation planning (but see Hof et al (1994) and Bevers et al (1995) for timing of forest harvest and Holzkämper et al (2006) for optimal land use planning).…”