This study investigated the basic biology as well as vital statistics of the Sakura shrimp, Sergia lucens in the southwestern coast of Taiwan. The research includes length-weight relationship, spawning season, sex ratio and Von Bertalanffy equation. All sample had found partly grown eggs. The greatest spawn in January and July. It is possible that one population in the fishing area. Analysis of Covariance(ANCOVA) on the relationship between length and weight shows that male and female has the similar growth rate; but male shrimp appeared to be heavier than female for about 0.0217 g. There are more female than male in fishing area, and the ratio increase toward large size group. The growth rate of Sergia lucens is allometric. Result from morphometric study as well as fluctuation in GSI shows that the Sergested shrimp of the southwestern Taiwan can be classified as belonging to one single population but with the possible existence of two spawning subgroups. Analysis on length frequency distribution computer package, FiSAT, showed that total mortality and natural mortality was equal to 7.86 and 5.02, respectively.

Statistical age-structured models are widely used in fisheries stock assessment. These models have been become increasingly complex over recent decades, allowing them to incorporate a larger variety of fisheries data. These typically include information regarding annual fishery yields, indices of abundance and catch composition data, which reflect the distribution of ages in the harvested population each year. In some fisheries, age composition can be determined annually through the examination of annuli on hard parts, such as otoliths or scales. These methods are, however, costly, time consuming and require a relatively high level of expertise on the part of data collectors. Alternatively, length frequency distributions within the annual catch are relatively simple and inexpensive to acquire, and can be employed to extrapolate age structure given that some information regarding age length relationships in the population is known. This type of data is therefore critical for many age-structured fisheries models. Length frequency data are compiled from length measurements of a sub-sample of the commercial catch. Even when they derive from a relatively large sample size, however, these data depend on a number of biological, economic and logistical factors. In some fisheries, for example, larger, more valuable fish may be separated from the overall catch and sold quickly, before port samplers have chance to gather sub-samples (Burns et al. 1983). This can reduce the relative frequency of large individuals in length frequency data. Alternatively, fish may become stratified in holding bins or storage containers according to size, due to their slippery texture and body shape (Hilborn and Walters 1992). With smaller, shorter individuals falling to the bottom where they are less likely to be picked up and measured, length frequency data may contain a disproportionately high frequency of large fish. This study used simulations to examine the impact of these two types of bias in length frequency data on a statistical age-structured model. The model, which was similar to those used in stock assessments for black sea bass (Centropristis striata) and gag (Mycteroperca microlepis) in the southeastern United States, produced erroneous population estimates when given biased data. Length frequency data that contained too many small fish caused stock status estimates to became overly pessimistic, indicating that populations were more heavily depleted than was actually the case. This type of bias supported overly conservative management measures, which posed an unnecessary cost to fishermen. Conversely, when the data included too many large fish, estimates of stock status were overly optimistic, and supported management actions that did not effectively protect the stock from overfishing. These results indicate that the quantity of length frequency data alone does not protect against bias when using complex age-structured models. The likelihood and magnitude of bias in these must also be examined in order to determine whether results are likely to be biased. For a given fishery, it is therefore critical that potential sources of bias in length frequency data be thoroughly inspected, and that the modeling approach used to assess the stock be appropriate based on the availability and accuracy of the data. / Master of Science

This study investigated the distribution, growth and reproduction of splendid ponyfish (Leiognathus splendens), the most dominant fish species in the catches of demersal trawls, along the coastal waters off southwestern Taiwan. Samples were collected once every 1-2 month (7-8 times per year), from January 2001 to January 2004 at seven stations, including Fangliao, Linbian, Dapeng Bay, Linyuan, Jhongjhou, Zuoying and Jiading, in southwestern Taiwan. The results showed that the distribution of L. splendens had significant differences among seasons, sites and water depths. The monthly mean abundance peaked in April, July and December, whereas lowest in January. L. splendens appeared in the north of Jhonhjhou only in the period from June to November. Based on their occurrence, the ponyfish could be separated into south and north groups at Linyuan. The south group can be further divided into inshore and offshore subgroups. The south group was more abundant than the north group. The size of L. splendens ranged from 15.32 mm to 121.01 mm (TL¡×total length), with an asymptotic length (L¡Û) of 128.20 mm and a catabolic growth coefficient (K) of 0.16(on a yearly basis). The ova diameter raged from 101.01 to 966.37 um with a peak between 500 and 600 um. The reproductive characteristic of L. splendens postulated as an asynchrouous spawner, who may spawn from March to May at Dapeng Bay and Linbian. The sex ratio (female/male) was less than 0.5 in total samples, and their first maturity length (L50) for female and male were 72.93 mm and 68.22 mm respectively. The distribution of L. splendens is associated with hydrology, season and ocean current. Higher abundance is normally coincided with low salinity, density, oxygen dissolution, and high water temperature and high value of Cpar (corrected irradiance-photosynthetically available radiation). The SCSW (South China Sea Water) and SCSSW(South China Sea Surface Water) with high temperature and low salinity flowing northward into the Taiwan Strait during the southwest monsoon season of May-September may deeply influence the northward distribution of the fish. Bigger fish and mature female capture during the spawning season from March to May, besides, smaller fish (TL¡Õ 20 mm) abundance on April, July and October. Additionally, the rainfall and nutrient wash away from onshore by typhoons, are the factors increase catches of L. splendens in the coastal waters of southwestern Taiwan.

This thesis is about the demography of the tunicate Styela clava, a species of some notoriety because of its invasiveness and impacts in many parts of the world. Species assemblages have continuously changed throughout evolutionary history, but the rate of today’s anthropogenically facilitated dispersal is unparalleled in history. Non-indigenous species (NIS) are now considered one of the most important risks to native biodiversity. NIS become invasive by becoming both widespread and locally dominant. This requires that a species becomes established, spreads locally, and increases in abundance. In the early stages of invasion, its demography and life history characteristics are of crucial importance. In New Zealand, Styela has established populations in several places, but none of these populations has yet reached the high densities found in other countries. In Lyttelton Port, where this study was located, Styela was first noticed in 2005. It therefore presented an ideal situation to study an invasive species in its early stages of establishment and provided a potentially good model for understanding how invasive species get local traction and spread from initial infestation points. Therefore, I set out to determine demographic features of Styela to understand the numbers game of population dynamics. This study used empirical data on growth rates, size-frequencies through time, and size and age to maturity to test several models, including von Bertalanffy, Logistic dose-response, Ricker and power models of individual growth. The most useful proved to be the von Bertalanffy model. Styela individuals shrink frequently, so average growth rates were often quite low, even though some individuals reached 160 mm or more in total length. Mortality was greatest in summer, presumably after reproduction, and lowest in winter. Fewer than 5% of individuals survived 12 months, and most or all of these died soon afterwards. Populations were, therefore, essentially annual. Recruitment was difficult to determine because of the cryptic nature of small juveniles. However, size-frequency, abundance and mortality data indicated that recruitment most likely occurred in early spring (late-October), and then again in late summer, with growth to maturity (at c. 50 mm total length) within < 5 months. Several manipulative experiments showed that Styela did not readily capitalise on provision of free space but the other non-native ascidian, Ciona intestinalis, rapidly recruited. Transplants of Styela were greatly affected by C. intestinalis, which overgrew them, similar to a localised replacement of Styela by Ciona seen overseas. Lefkovitch modelling was used to test whether Styela had an “Achilles heel” in its life history, whereby managed removal could impact future populations. This showed that under several scenarios intervention would most likely be ineffectual. Overall, this study showed that the original populations in Lyttelton Port are either static or in decline, somewhat contrary to original expectations. Nevertheless, it appears that these small populations may be acting as stepping stones for spread of this species outside of the port.

No description available.