Abstract: Good management models and good models for understanding biology differ in basic philosophy. Management models must facilitate management decisions despite large amounts of uncertainty about the managed populations. Such models must be based on parameters that can be estimated readily, must explicitly account for uncertainty, and should be simple to understand and implement. In contrast, biological models are designed to elucidate the workings of biology and should not be constrained by management concerns. We illustrate the need to incorporate uncertainty in management models by reviewing the inadequacy of using standard biological models to manage marine mammals in the United States. Past management was based on a simple model that, although it may have represented population dynamics adequately, failed as a management tool because the parameter that triggered management action was extremely difficult to estimate for the majority of populations. Uncertainty in parameter estimation resulted in few conservation actions. We describe a recently adopted management scheme that incorporates uncertainty and its resulting implementation. The approach used in this simple management scheme, which was tested by using simulation models, incorporates uncertainty and mandates monitoring abundance and human-caused mortality. Although the entire scheme may be suitable for application to some terrestrial and marine problems, two features are broadly applicable: the incorporation of uncertainty through simulations of management and the use of quantitative management criteria to translate verbal objectives into levels of acceptable risk. 相似文献
Adaptive cluster sampling (ACS) is an efficient sampling design for estimating parameters of rare and clustered populations.
It is widely used in ecological research. The modified Hansen-Hurwitz (HH) and Horvitz-Thompson (HT) estimators based on small
samples under ACS have often highly skewed distributions. In such situations, confidence intervals based on traditional normal
approximation can lead to unsatisfactory results, with poor coverage properties. Christman and Pontius (Biometrics 56:503–510,
2000) showed that bootstrap percentile methods are appropriate for constructing confidence intervals from the HH estimator.
But Perez and Pontius (J Stat Comput Simul 76:755–764, 2006) showed that bootstrap confidence intervals from the HT estimator
are even worse than the normal approximation confidence intervals. In this article, we consider two pseudo empirical likelihood
functions under the ACS design. One leads to the HH estimator and the other leads to a HT type estimator known as the Hájek
estimator. Based on these two empirical likelihood functions, we derive confidence intervals for the population mean. Using
a simulation study, we show that the confidence intervals obtained from the first EL function perform as good as the bootstrap
confidence intervals from the HH estimator but the confidence intervals obtained from the second EL function perform much
better than the bootstrap confidence intervals from the HT estimator, in terms of coverage rate. 相似文献
Large body size confers a competitive advantage in animal contests but does not always determine the outcome. Here we explore
the trade-off between short-term achievement of high social status and longer-term life history costs in animals which vary
in competitive ability. Using laboratory mice, Mus musculus, as a model system, we show that small competitors can initially maintain dominance over larger males by increasing investment
in olfactory status signalling (scent-marking), but only at the cost of reduced growth rate and body size. As a result they
become more vulnerable to dominance reversals later in life. Our results also provide the first empirical information about
life history costs of olfactory status signals.
Received: 15 December 1999 / Revised: 6 June 2000 / Accepted: 24 June 2000 相似文献
Plants contain substances that inhibit corrosion. Here we review biomass-based corrosion inhibitors from plant leaves, nuts, and fruit peels, after treatment with acids, bases or saline solutions. The mechanism of corrosion inhibition involves a monolayer coverage, according to isotherm and Langmuir models. Plant extract-based corrosion inhibitors contain heteroatoms whose electrons pair in the p-electron level in multiple bonds and the vacant d-orbitals of iron. Corrosion inhibition under marine conditions involves various chemical interactions between metals and dissolved ionic components.