Ecosystem context and historical contingency in apex predator recoveries

Abstract

Habitat loss, overexploitation, and numerous other stressors have caused global declines in apex predators. This "trophic downgrading" has generated widespread concern because of the fundamental role that apex predators can play in ecosystem functioning, disease regulation, and biodiversity maintenance. In attempts to combat declines, managers have conducted reintroductions, imposed stricter harvest regulations, and implemented protected areas. We suggest that full recovery of viable apex predator populations is currently the exception rather than the rule. We argue that, in addition to well-known considerations, such as continued exploitation and slow life histories, there are several underappreciated factors that complicate predator recoveries. These factors include three challenges. First, a priori identification of the suite of trophic interactions, such as resource limitation and competition that will influence recovery can be difficult. Second, defining and accomplishing predator recovery in the context of a dynamic ecosystem requires an appreciation of the timing of recovery, which can determine the relative density of apex predators and other predators and therefore affect competitive outcomes. Third, successful recovery programs require designing adaptive sequences of management strategies that embrace key environmental and species interactions as they emerge. Consideration of recent research on food web modules, alternative stable states, and community assembly offer important insights for predator recovery efforts and restoration ecology more generally. Foremost among these is the importance of a social-ecological perspective in facilitating a long-lasting predator restoration while avoiding unintended consequences.

Keywords: Restoration; apex predator; competition; food chain; hysteresis; intraguild predation; recovery.

Fig. 1. Three-species community modules: Food chain, exploitative competition, and IGP.

These modules are generic descriptions of common configurations of predator-prey interactions in the natural world (left), each of which corresponds to a predator recovery example (center) that has followed a restoration trajectory corresponding to the module (right).

Fig. 2. Module shape alters how an apex predator’s abundance will respond to the restoration of basal resources, as indicated by the contrast of low (solid lines) and high (dashed lines) resource carrying capacities (red lines, apex predator resource-only state; blue lines, three-species coexistence state).

When ω has intermediate values, increases in resource productivity benefit the apex predator’s abundance to the detriment of the mesopredator because the mesopredator’s competetive advantage becomes superseded by the predation pressure that it experiences from the apex predator. (A and B) A continuous gradient of predator’s prey preference (ω) (A) and discrete measures of apex predator equilibrium density for characteristic models, including exploitative competition, IGP, and a food chain (B). For additional model details, see fig. S1 (baseline parameters here are as follows: ω = 0.5, r = 1, e = 0.1, a = 1, and α = 3).

Fig. 3. Module shape alters how apex predator density will respond to the culling of mesopredators, as indicated by the contrast of low (solid lines) and high (dashed lines) mesopredator mortality rates.

Culling will increase apex predator recovery success when competition is strong. In most cases, culling rates must be sufficiently high such that only the apex predator and the resource persist (red). In contrast, culling will negatively affect the apex predator’s density across most of the range of apex predator prey preference values (ω), when three-species coexistence is desired (blue). Culling of mesopredators only benefits the apex predator when competition is strong but sufficiently weak so as not to cause competitive exclusion (inset). (A) A gradient of predator’s prey preference. (B) Discrete measures of apex predator equilibrium density for discrete models: exploitative competition, IGP, and food chain. NA, not applicable.

Fig. 4. Priority effects occur when final equilibrium population sizes are dependent on initial population sizes, even though all other parameter values (that is, environmental conditions) remain unchanged.

Such priority effects occur in the IGP module when competition between the apex predators and the mesopredators is strongest, illustrated here with two simulations that differ only in the initial abundance of the apex predator. (A) The dynamics illustrate the scenario where the apex predator’s initial population size (green, P₀ > 0.1) is sufficient to affect the extinction of the mesopredator (blue, N₀ = 0.01). (B) In contrast, the dynamics illustrate a scenario where the apex predator’s initial population size (P₀ < 0.1) is insufficient to avoid extinction due to exclusion by the mesopredator (N₀ = 0.01) (that is, a failed restoration). Parameters are as in Figs. 2 and 3 but with ω = 0.225 reflecting an IGP module in which exploitative competition is strong.

Fig. 5. Time-varying modules of riparian corridors along small streams within the northern range of the Greater Yellowstone Ecosystem from the 1920s to present.

Northern-range riparian areas have exhibited (at least) three different major types of communities since 1920. Before wolf extinctions (1920s), riparian areas included wolves, elk, beavers, and willows. Following wolf extinctions (1930s to 1990s), these areas were reduced to just elk and willow. Most recently (1990 to present), wolf reintroductions have produced a system with wolves, elk, and willow but few beavers. Qualitatively, these different modules exhibit fundamentally different dynamics, exemplify temporal variability in a single system’s characteristic module, and meet different ecological and social services. [Illustration by Shannon Hennessey, Oregon State University].