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Process and measurement errors of population size: their mutual effects on precision and bias of estimates for demographic parameters

机译：人口规模的过程和测量误差：它们对人口参数估计值的准确性和偏差的相互影响

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摘要

Knowing the parameters of population growth and regulation is fundamental for answering many ecological questions and the successful implementation of conservation strategies. Moreover, detecting a population trend is often a legal obligation. Yet, inherent process and measurement errors aggravate the ability to estimate these parameters from population time-series. We use numerical simulations to explore how the lengths of the time-series, process and measurement error influence estimates of demographic parameters. We first generate time-series of population sizes with given demographic parameters for density-dependent stochastic population growth, but assume that these population sizes are estimated with measurement errors. We then fit parameters for population growth, habitat capacity, total error and long-term trends to the ‘measured’ time-series data using non-linear regression. The length of the time-series and measurement error introduce a substantial bias in the estimates for population growth rate and to a lesser degree on estimates for habitat capacity, while process error has little effect on parameter bias. The total error term of the statistical model is dominated by process error as long as the latter is larger than the measurement error. A decline in population size is difficult to document as soon as either error becomes moderate, trends are not very pronounced, and time-series are short (<10–15 seasons). Detecting an annual decline of 1% within 6-year reporting periods, as required for the European Union for the species of Community Interest, appears unachievable.
机译：了解人口增长和调控的参数是回答许多生态问题和成功实施保护战略的基础。此外，检测人口趋势通常是法律义务。但是，固有的过程和测量误差会加剧从总体时间序列估算这些参数的能力。我们使用数值模拟来探索时间序列的长度，过程和测量误差如何影响人口统计参数的估计。我们首先使用给定的人口统计参数生成人口规模的时间序列，以进行依赖于密度的随机人口增长，但是假设这些人口规模是通过测量误差估算的。然后，我们使用非线性回归将人口增长，栖息地容量，总误差和长期趋势的参数拟合到“测得”的时间序列数据中。时间序列的长度和测量误差在人口增长率的估计中引入了很大的偏差，而对栖息地容量的估计则引入了较小的偏差，而过程误差对参数偏差的影响很小。只要过程误差大于测量误差，统计模型的总误差项就由过程误差决定。只要其中一个误差变得中等，趋势不是很明显并且时间序列很短（<10-15个季节），就很难记录人口数量的减少。按照欧盟对共同体利益物种的要求，在6年报告期内无法检测到每年1％的下降。

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