著者
草光 紀子 一恩 英二 中野 光議 上田 哲行
出版者
日本雨水資源化システム学会
雑誌
Journal of Rainwater Catchment Systems (ISSN:13438646)
巻号頁・発行日
vol.23, no.1, pp.27-34, 2017 (Released:2019-08-06)
参考文献数
29

Aquatic fauna found in 21 man-made biotopes that were established in agricultural and rural development projects in rural areas in Ishikawa Prefecture, Japan, were surveyed. A total of 117 species were captured or observed, including nine species of amphibians, 14 species of fish, 75 species of aquatic insects, ten species of crustaceans, and nine species of mussels and snails. Mostly aquatic insects made up the 38 species of odonates found. In addition, 24 coleopteran species and ten hemipteran species were discovered in the biotopes. The Red Data Book of Japan lists Rana nigromaculata, Cipangopaludina chinensis laeta, and Oryzias latipes latipes as endangered species, and these species were captured in 18, eight, and six out of 21 biotopes, respectively. In addition, two nonindigenous invasive species, Procambarus clarkii and Rana catesbeiana, were captured in 11 and six biotopes, respectively. The numbers of species varied greatly among biotopes, ranging from four to 59, suggesting that the effect of biotope on biodiversity was not uniform.
著者
Elizaphan Otieno Ndede Koichi Unami Masayuki Fujihara
出版者
Japan Rainwater Catchment Systems Association
雑誌
Journal of Rainwater Catchment Systems (ISSN:13438646)
巻号頁・発行日
vol.24, no.1, pp.33-36, 2018 (Released:2019-08-06)
参考文献数
14

Fish is one of the most important primary sources of animal protein for human consumption globally. Fish harvesting strategy in artificial fish ponds is important to fish-farmers who practice commercial aquaculture under uncertainties of market prices. Robust optimization was developed to solve uncertain optimization problems by considering the uncertain data to be existing in an uncertainty set. In this study, we consider that growth models for market price of fish with volatility are given and then analyze harvesting policy for fish in the framework of discrete robust optimization. Demonstrative optimization is performed using a robust counterpart optimization technique, which involves numerical solution of nonlinear algebraic equations systems, with hypothetical model parameters. With discrete harvesting stages in the time domain, the robust optimal harvesting policy under presence of volatility is prescribed as a partial harvesting strategy.