Tian, Y., Uchikawa, K., Ueda, Y., and Cheng, J. Comparison of fluctuations in fish communities and trophic structures of ecosystems from three currents around Japan: synchronies and differences. – ICES Journal of Marine Science, 71: . Features of three marine ecosystems affected by the Tsushima (TWC), Kuroshio (KC), and Oyashio (OC) currents were analysed based on fishery, oceanographic, and climate datasets during 1955–2010. Principal component (PC) analysis for catches of 25 indicator species showed evident decadal variation patterns with a step change in the first principal component (PC1) in the late 1980s, indicating synchronies in the dominant variation mode across the ecosystems. Step changes were also detected in the mid-1970s in PC2 and PC3 in OC, and around 1970 in PCs in KC and TWC. These indicate that the most marked change across the ecosystems occurred in the late 1980s, corresponding to the late 1980s climate regime shift, but OC also responded strongly to the mid-1970s regime shift, indicating different responses to regime shifts. The generalized additive model showed the PCs associated largely with water temperature in each region as well as climate indices, indicating the importance of regional oceanographic conditions. Ecosystem indicators such as the mean trophic level showed similarities between TWC and KC but differences with OC, indicating that trophic structures in TWC and KC were largely dependent on the mid-trophic (small pelagic species) level, while on demersal species in OC.

No abstract

Climate-induced nonlinearity in biological variability and non-stationary relationships with physical drivers are crucial to understand responses of marine organisms to climate variability. These phenomena have raised concerns in the northeastern North Pacific, but are out of the spotlight in the northwestern North Pacific in spite of potential implications for this productive system under increased climate variability. Pelagic communities in the Kuroshio ecosystem have both ecological and economic importance. However, patterns of climate-induced nonlinearity in pelagic communities are not well understood, and existence of non-stationarity in their relationships with physical drivers remains obscure. Here, we compile large numbers of climatic, oceanic and biological long-term time-series data and employ diverse statistical techniques to reveal such climate-induced nonlinearity and non-stationarity. Results show that pelagic communities in the Tsushima and Pacific areas (major areas in the Kuroshio ecosystem) had regime shifts in the late 1990s and late 1980s, respectively. Winter sea surface temperatures in the Kuroshio Current path and in the eastern part of East China Sea, which are respectively affected by the Kuroshio Current and Siberian High, correlate with dominant variability patterns in their pelagic communities. Furthermore, non-stationarity was identified with threshold years in the 1990s in the Tsushima area and in the 1980s in the Pacific area as a possible result of the declined variances in the Siberian High and Aleutian Low, respectively. Our findings provide insights on spatial differentiation of climate-induced nonlinearity and nonstationarity, which are valuable for the management of pelagic communities in the northwestern North Pacific under changing climatic conditions. K E Y W O R D S climate variability, ecological threshold, Kuroshio Current, non-stationary relationship, pelagic species, regime shift 7 3.4 Non-stationarity in community-environment relationships 7 4 DISCUSSION 9 4.1 Similarity and difference between the variability patterns 9 4.2 SST effects on pelagic communities 11 4.3 Climate effects on the SST fields 11 4.4 Climate-induced non-stationarity and its implications for fisheries management 12 ACKNOWLEDGEMENTS 13

No abstract

Liu, Y., Chen, Y., and Cheng, J. 2009. A comparative study of optimization methods and conventional methods for sampling design in fishery-independent surveys. – ICES Journal of Marine Science, 66: 1873–1882. We have introduced and evaluated a procedure, the constrained spatial simulated annealing method, for developing an optimal sampling design for fishery-independent surveys. We used two criterion functions, minimization of the mean of the shortest distance (MMSD) and uniform distribution of point pairs for variogram estimation (WM), and three arrangements of the two criteria, all WM, all MMSD, and a combination of MMSD (2/3 of samples) and WM (1/3), to construct three optimized sampling designs (denoted as Designs I, II, and III, respectively). These three designs were compared in a simulation study with systematic sampling (Design IV) and stratified random sampling designs (Design V), commonly used in fishery-independent surveys. Three levels of sample size (small, medium, and large) were considered in the simulation study developed using a geostatistical approach. The results showed that for parameter estimation of the spatial covariance function, Design III was better than the other designs at relatively small sample size and Design II performed better than the other designs at relatively large sample size. For estimating fish stock abundance, the performance of the designs considered in this study can be ranked as follows: Design II > Design IV > Design III > Design V > Design I. It is clearly important to evaluate and improve sampling design based on historical survey data. Such a study allows us to identify an optimal sampling design to balance the quality of the data collected and the costs of the sampling programme, leading to the development and optimization of a sustainable and fishery-independent monitoring programme.