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Developing effective management strategies is essential to conservation biology. Population models and sensitivity analyses on model parameters have provided a means to quantitatively compare different management strategies, allowing managers to objectively assess the resulting impacts. Inference from traditional sensitivity analyses (i.e., eigenvalue sensitivity methods) is only valid for a population at its stable age distribution, while more recent methods have relaxed this assumption and instead focused on transient population dynamics. However, very few case studies, especially in long-lived vertebrates where transient dynamics are potentially most relevant, have applied these transient sensitivity methods and compared them to eigenvalue sensitivity methods. We use bison (Bison bison) at Badlands National Park as a case study to demonstrate the benefits of transient methods in a practical management scenario involving culling strategies. Using an age and stage-structured population model that incorporates culling decisions, we find that culling strategies over short time-scales (e.g., 1–5 years) are driven largely by the standing population distribution. However, over longer time-scales (e.g., 25 years), culling strategies are governed by reproductive output. In addition, after 25 years, the strategies predicted by transient methods qualitatively coincide with those predicted by traditional eigenvalue sensitivity. Thus, transient sensitivity analyses provide managers with information over multiple time-scales in contrast to the long time-scales associated with eigenvalue sensitivity analyses. This flexibility is ideal for adaptive management schemes and allows managers to balance short-term goals with long-term viability.
Buhnerkempe, Michael; Burch, Nathanial; Hamilton, Sarah J.; Byrne, Kerry M.; Childers, Eddie; Holfelder, Kirstin A.; McManus, Lindsay; Pyne, Matthew I.; Schroeder, Greg; and Doherty, Paul F., "The Utility of Transient Sensitivity for Wildlife Management and Conservation: Bison as a Case Study" (2011). Mathematics, Statistics and Computer Science Faculty Research and Publications. 467.
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