Topic 1. Some steric-height features of the water off the Pacific coast of Canada; Topic 2. Possible warming of the water at station P in the northeast Pacific during 1956-1984 [abstract]

TOPIC 1: In terms of seasonal scale, temperature effect dominates the annual change of steric height in the open ocean whereas salinity effect controls it along the continental shelf. Large portion of the annual change of height relative to the 1000-db surface is contained in the upper 100m layer. However, in interannual scale large anomalies of steric height in the open ocean, are more often than not, caused by halosteric rather than thermosteric effect. At least in the open ocean the heights are almost totally determined by the behavior of deep water. Their interannual variability appears to be related to the cumulative effect of Eckman pumping. TOPIC 2: There is a "trend" that over the past 28 years the water at Station P has warmed. Least-square analysis indicates that this warming may be significant but shortening of the time-series data by approximately 10 years fails to show that this is the case. These "trends" have to be interpreted with care. The warming may be "apparent" in that it is not indicated clearly in the deep isopynal surfaces which, during the above period, have deepened. Thus warming at the isobaric surfaces may be the effect of the downward migration of the isopynal surfaces.

Periodic autoregressive moving average models for the analysis of streamflow [abstract]

EXTRACT (SEE PDF FOR FULL ABSTRACT): Streamflow values show definite seasonal patterns in their month-to-month correlation structure. The structure also seems to vary as a function of the type of stream (coastal versus mountain or humid versus arid region). The standard autoregressive moving average (ARMA) time series model is incapable of reproducing this correlation structure. ... A periodic ARMA time series model is one in which an ARMA model is fitted to each month or season but the parameters of the model are constrained to be periodic according to a Fourier series. This constraint greatly reduces the number of parameters but still leaves the flexibility for matching the seasonally varying correlograms.

Multiscale analysis of factors that affect the distribution of sharks throughout the northern Gulf of Mexico

Identification of the spatial scale at which marine communities are organized is critical to proper management, yet this is particularly difficult to determine for highly migratory species like sharks. We used shark catch data collected during 2006–09 from fishery-independent bottom-longline surveys, as well as biotic and abiotic explanatory data to identify the factors that affect the distribution of coastal sharks at 2 spatial scales in the northern Gulf of Mexico. Centered principal component analyses (PCAs) were used to visualize the patterns that characterize shark distributions at small (Alabama and Mississippi coast) and large (northern Gulf of Mexico) spatial scales. Environmental data on temperature, salinity, dissolved oxygen (DO), depth, fish and crustacean biomass, and chlorophyll-a (chl-a) concentration were analyzed with normed PCAs at both spatial scales. The relationships between values of shark catch per unit of effort (CPUE) and environmental factors were then analyzed at each scale with co-inertia analysis (COIA). Results from COIA indicated that the degree of agreement between the structure of the environmental and shark data sets was relatively higher at the small spatial scale than at the large one. CPUE of Blacktip Shark (Carcharhinus limbatus) was related positively with crustacean biomass at both spatial scales. Similarly, CPUE of Atlantic Sharpnose Shark (Rhizoprionodon terraenovae) was related positively with chl-a concentration and negatively with DO at both spatial scales. Conversely, distribution of Blacknose Shark (C. acronotus) displayed a contrasting relationship with depth at the 2 scales considered. Our results indicate that the factors influencing the distribution of sharks in the northern Gulf of Mexico are species specific but generally transcend the spatial boundaries used in our analyses.

Solomon Islands: Western Province situation analysis

Aquatic agricultural systems (AAS) are places where farming and fishing in freshwater and/orscoastal ecosystems contribute significantly to household income and food security. Globally, theslivelihoods of many poor and vulnerable people are dependent on these systems. In recognitionsof the importance of AAS, the CGIAR Research Program (CRP) is undertaking a new generationsof global agricultural research programs on key issues affecting global food security and ruralsdevelopment. The overall goal of the research program is to improve the well-being of peoplesdependent on these systems. Solomon Islands is one of five priority countries in the AAS program,sled by WorldFish. In Solomon Islands, the AAS program operates in the Malaita Hub (MalaitasProvince) and the Western Hub (Western Province). This program and its scoping activities aressummarized in this report.