By Byron K. Williams
Analysis and administration of Animal Populations bargains with the procedures keen on making proficient judgements in regards to the administration of animal populations. It covers the modeling of inhabitants responses to administration activities, the estimation of amounts wanted within the modeling attempt, and the applying of those estimates and versions to the advance of sound administration judgements. The booklet synthesizes and integrates in one quantity the equipment linked to those subject matters, as they practice to ecological evaluate and conservation of animal populations.
- Integrates inhabitants modeling, parameter estimation and decision-theoretic techniques to administration in one, cohesive framework
- Provides authoritative, cutting-edge descriptions of quantitative techniques to modeling, estimation and decision-making
- Emphasizes the function of mathematical modeling within the behavior of technological know-how and management
- Utilizes a unifying organic context, constant mathematical notation, and diverse organic examples
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Example Consider a wildlife species that is exposed annually to sport hunting. A traditional concern in game management is the effect of harvest on future population status, and in particular the effect of harvest on annual survival. Two competing hypotheses have been identified: 1. The hypothesis of additive mortality asserts that harvest is additive to other forms of mortality such as disease and predation. Under this hypothesis the annual mortality rate increases approximately linearly in response to increases in harvest rate.
Given the inconsistent uses of causation, it is not surprising that the controversy between advocates and opponents of tobacco restrictions has not been amenable to data-based resolution. Indeed, the evidence likely will continue to indicate that tobacco use is simultaneously a cause of lung cancer (in the necessary sense) and not a cause of lung cancer (in the sufficient sense). 2. 3. , destruction of Salmonella bacilli through sterilization). Scientific investigation thus involves a search for conditions that are predictive of the nonconcurrence of an effect of concern.
Under these conditions no other factor than C can cause the effect, for otherwise E presumably would be recorded in the absence of C, in violation of the requirement for co-occurrence. C is therefore recognized as the cause, and the only cause, of E under the experimental conditions. This very high standard illustrates the value (and rigor) in establishing causation through experiment and helps to explain why experimental design is a near-imperative in much of biological science. 3. S C I E N T I F I C M E T H O D S A useful context for scientific method involves scientific investigation both before and during a period when it is guided by a recognized theoretical framework.
Analysis and Management of Animal Populations by Byron K. Williams