Dispersal kernels of butterflies: Power-law functions are invariant to marking frequency
Dispersal kernels of butterflies: Power-law functions are invariant to marking frequency
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DOI：
10.1016/j.baae.2006.06.005
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发表时间：
2007-01-01
影响因子：
3.8
通讯作者：
Konvicka, Martin
中科院分区：
文献类型：
--
作者：
Fric, Zdenek;Konvicka, Martin
尽管最近发展了复杂的扩散模型，但简单的基于回归的模型在估计动物远距离移动的频率方面仍然有用。由于逆幂函数IPF(ln i=ln C-m ln D)而不是负指数函数NEF(ln i=ln a-k D)表现出自相似的性质，它应该对标记-再捕获研究中投入的努力的变化具有鲁棒性。我们使用了三组蝴蝶(鳞翅目)的运动数据来说明这一点：EuPhydryas aurinia，2002年(由IPF更好地拟合)，E.aurinia，2003年(由NEF更好地拟合)和Parnassius Mnemase(由NEF更好地拟合)。通过动物数量、标记天数和标记努力的模拟减少，我们发现IPF在不改变基于简化数据的回归参数的情况下经受住了标记频率的严重下降。相反，根据简化数据拟合的近场效应参数变化很大，与基于未简化数据的函数不同。由于IPF的强大性能，可以在相对较小的实地工作中获得可靠的扩散估计，这可能有助于快速和有效地比较物种、地点和种群之间的运动模式。(C)2006年Gesellschaft皮草Okologie。由Elsevier GmbH出版。版权所有。
Despite recent developments of sophisticated dispersal modelling, simple regression-based models remain useful for estimating frequencies of tong-distance movements of animals. Since the inverse power function, IPF (ln I = ln C-m ln D), but not the negative exponential function, NEF (ln I = ln a-k D), exhibits the property of self-similarity, it should be robust against variation in effort invested into mark-recapture studies. We illustrate this using three data sets on movements of butterflies (Lepidoptera): Euphydryas aurinia, year 2002 (better fitted by IPF), E. aurinia, year 2003 (better fitted by NEF) and Parnassius mnemosyne (better fitted by NEF). By simulated reductions of numbers of animals, numbers of marking days, and marking effort, we show that IPF withstands severe decline in marking frequency without a change of parameters of regressions based on reduced data. In contrast, parameters of NEFs fitted to the reduced data widely varied and differed from functions based on unreduced data. Owing to the robust performance of IPF, reliable dispersal estimates may be obtained at relatively small field effort, which may facilitate quick and efficient comparisons of movement patterns among species, Locations and populations. (C) 2006 Gesellschaft fur Okologie. Published by Elsevier GmbH. All rights reserved.