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American Bison - Buffalo Field Campaign

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2. Determine the required scope of model.<br />

Single or multiple species?<br />

Age or stage structured?<br />

One or more population units?<br />

Spatially homogeneous or with spatial structure?<br />

What is the geographical extent?<br />

Are animal-habitat feedbacks necessary?<br />

3. Evaluate existing software and decide whether to use an<br />

existing programme or to construct a new model. Considerable<br />

time and money can be saved by using “off the shelf” software,<br />

such as RAMAS (http://www.ramas.com/software.htm),<br />

Vortex (Lacy 1993), ALEX (Possingham et al. 1992), or another<br />

modelling environment.<br />

4. Collect necessary data and estimate model parameters.<br />

This can be a huge step. Data will be needed to estimate mean<br />

vital rates and realistic estimates of variance. Ecosystem or<br />

habitat models will require much additional information to<br />

determine carrying capacity and animal-ecosystem feedbacks.<br />

Most population-habitat models used for PVA will include<br />

catastrophes, estimates of variance in habitat carrying capacity,<br />

and specific assumptions on the form and process of density<br />

dependence.<br />

5. Construct, calibrate, and run the model. Evaluate model<br />

results. Considerable effort may be required to understand and<br />

comprehensively evaluate model inputs, and to understand<br />

model results. Output from a simulation exercise usually<br />

includes huge quantities of data that will need to be reduced,<br />

summarised, and presented in an understandable form.<br />

6. Package results in a digestible and understandable format.<br />

This is a vastly underappreciated problem, and it will be much<br />

easier if the model objectives were clear and concisely stated at<br />

the outset.<br />

7. Ralls et al. (Table 25.4 in Ralls et al. 2002) provide a specific<br />

checklist for evaluating the quality of a PVA, and this checklist<br />

applies equally well to many additional conservation modelling<br />

exercises. They provide “yes-no” questions that focus on model<br />

objectives, model structure, data and parameter estimation,<br />

analysis of model outcomes, handling of model uncertainty,<br />

interpretation, and peer review. These criteria provide a sound<br />

framework for helping to ensure models are constructed and<br />

used in an appropriate fashion.<br />

9.8 Conclusions<br />

While many topics are addressed in this chapter, effective<br />

management of bison ultimately relies on the judicious<br />

application of common sense and good judgement. When<br />

bison have access to sufficient space and forage, and are left<br />

relatively undisturbed, they are more than fully capable of taking<br />

care of themselves. Nonetheless, most bison will not experience<br />

natural conditions that include wide-open spaces and intact<br />

predator communities, so we hope the guidelines provided will<br />

support science-based management programmes that lead<br />

to more effective conservation and restoration of bison. These<br />

guidelines focus on widespread common management issues—<br />

population management, disease, and genetic management.<br />

These guidelines and principles will ensure that key issues are<br />

addressed, and citations will help managers find more detailed<br />

information that may be necessary to accommodate specific<br />

situations.<br />

<strong>American</strong> <strong>Bison</strong>: Status Survey and Conservation Guidelines 2010 101

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