https://scholars.lib.ntu.edu.tw/handle/123456789/378471
標題: | An alternative kernel-based method for estimating copepod growth rates from multimodal biomass distributions in artificial cohort experiments | 作者: | Lin, K.-Y. Sastri, A.R. CHIH-HAO HSIEH |
關鍵字: | Artificial cohort method; Copepod community; Metabolic theory of ecology; Multimodal distribution | 公開日期: | 2013 | 卷: | 52 | 期: | 1 | 來源出版物: | Zoological Studies | 摘要: | Background: Elucidating copepod growth and production rates is important in understanding the trophic role of copepods in marine systems. One of the most commonly used field methods for measuring copepod growth rates is the artificial cohort method. Results: An 'artificial cohort' is established by limiting the incubated animals to relatively narrow size ranges or developmental stages. Thus, one can measure the change in body weight (BW; attributed to body growth) between the start and conclusion of incubation by following the shift in the biomass distribution. The critical issue here is determining how to describe the biomass distribution before and after incubation in a mathematically concise manner. Traditionally, the mean value of the biomass distribution is used as the representative BW, which assumes that the biomass distribution follows a unimodal distribution. However, in practice, the complex composition of copepod communities can commonly yield observations of multimodal distributions. To overcome this difficulty, we suggest that the representative BW of copepod communities be estimated by multiple-peak consideration instead of using the average value. Specifically, we used a kernel-based approach to determine peak values; as such, only BW values associated with a high frequency were used to determine the representative BW. Conclusions: Through a comparison of different methods, we show that the multiple-peak consideration yielded a higher proportion of realistic growth rate values. In addition, we noted that growth rates estimated with the multiple-peak method were more closely aligned with predictions based on the metabolic theory of ecology. © 2013 Lin et al. |
URI: | http://www.scopus.com/inward/record.url?eid=2-s2.0-84899825225&partnerID=MN8TOARS http://scholars.lib.ntu.edu.tw/handle/123456789/378471 |
DOI: | 10.1186/1810-522X-52-14 |
顯示於: | 海洋研究所 |
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