JIMAR PFRP ANNUAL REPORT FOR FY 2007

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JIMAR PFRP ANNUAL REPORT FOR FY 7 P.I./Sponsor Name: PI: David S. Kirby; Co-PIs: Adam Langley, Valerie Allain Oceanic Fisheries Programme, Secretariat of the Pacific Community, BPD5, 9888 Noumea, New Caledonia Project Proposal Title: Regime Shifts and Recruitment in Western and Central Pacific Ocean Tuna Fisheries Funding Agency: NOAA NOAA Goal (Check those that apply): To protect, restore, and manage the use of coastal and ocean resources through ecosystem-base management To understand climate variability and change to enhance society s ability to plan and respond To serve society s needs for weather and water information To support the nation s commerce with information for safe, efficient, and environmentally sound transportation. Purpose of the Project (one paragraph) To detect and characterise long-term environmental variability in time series of physical, biological and fisheries data; to determine whether the regime shifts documented for the North Pacific are evident in the tropical WCPO; and to incorporate indicators of longterm environmental variability in tuna recruitment estimation. The project has three components, each of which has a PI and Research Assistant (RA): i) Exploratory data analysis of ecosystem model input/ouput plus comparable datasets, using various methods for multivariate time-series analysis to derive ecosystem indicators (PI: David Kirby; RA: Karine Briand) ii) Use ecosystem indicators to improve recruitment estimation for tunas in the stock assessment software MULTIFAN-CL (PI: Adam Langley; RA: Karine Briand) iii) Stomach contents analysis for data pre- and post the regime shifts of the late 97s and 99s (PI: Valerie Allain; RA: Marie-Laure Coudron)

. Progress during FY 7: Component (i) Quantitative indicators of ecosystem state were derived from multivariate analysis of physical and biological oceanographic variables for the WCPO; statistical tests were then applied to determine the existence of regime shifts in the mean and variance of the indicators. Shifts were found at times that are broadly consistent with other studies for the north Pacific (976, 989, 998) although earlier shifts (ca. 96) appear to be just as significant. There is no signal of a regime shift in 976 in the western equatorial Pacific, although shifts are evident in 989 and 998. There is a strong shift in the physical variables of the central equatorial Pacific in 976, and a strong shift in current direction and primary production in this area in 998. The methods are sound for the purposes of ecosystem monitoring but are inadequate to build causal or predictive relationships between the ocean environment and tuna recruitment. Other statistical models Component (ii) have proved useful in that regard. The best single indicator for monitoring the effect of environmental variability on yellowfin recruitment appears to be the area of the western Pacific warm pool, which accounts for 5% of the variance in GLM predicted recruitment (see below) and which expanded significantly in the 96s. Component (ii) A generalised linear model (GLM) was developed to predict yellowfin recruitment from a range of oceanographic variables, from different areas and spatial/temporal scales. The final model accounted for 68% of observed variation in quarterly recruitment for the period 98, with the inclusion of different oceanographic variables derived from two zones within the equatorial region of the WCPO. The robustness of the recruitment model was investigated by cross-validation. The model was then applied to hindcast recruitment for the period 95 979. Recruitment predictions from the GLM closely followed trends in recruitment estimates from the assessment model through most of this period. The long-term trend in predicted recruitment was largely driven by sea surface temperature in the northwestern area of the equatorial region. This work has direct application to stock assessment for yellowfin tuna in the WCPO. Principally, the GLM enables recent (last yr) recruitment to be estimated more precisely, thereby increasing the precision of estimates of current biomass and exploitation rates. Increased precision of the current age structure of the population also improves the accuracy of short-term (next yr) stock projections from the assessment model. In a broader context, the recruitment model provides a tool to investigate how yellowfin recruitment may change in response to short- and long-term variation in the oceanographic conditions of the WCPO. The modelling approach was also applied to bigeye tuna, with the final model accounting for 7% of the observed variation in quarterly recruitment. This allows confidence in stock assessment estimates for bigeye recruitment, with similar benefits for estimating recent recruitment and carrying out stock projections as noted for yellowfin.

Component (iiii) Datasets from previous diet studies for tunas (New Caledonia: Grandperrin-IRD 959-97; French Polynesia: ECOTAP-IRD 995-997) were compared with recent work (Allain: GEF-PFRP -5) in order to identify any changes in diet that might indicate regime shifts in the pelagic ecosystem. Table. Sample sizes (number of individuals) for comparative diet study New Caledonia French Polynesia Species OLD NEW OLD NEW Albacore 5 5 8 97 Yellowfin 5 96 9 8 Bigeye 8 59 97 For New Caledonia, the diets of all three species seems to have changed between the two studies, although the small sample sizes (Table ) for albacore and bigeye in the new data and for bigeye in the old data must limit the extent of our inference. The diversity of fish prey families (Fig. 5) fell 7% (bigeye), 5% (albacore) and 6% (yellowfin) between old and new studies, with albacore consuming % more epipelagic crustacea and yellowfin consuming 8% more epipelagic forage fish and % less mesopelagic molluscs. For French Polynesia, the diets of all three species seem to have changed between the two studies. The diversity of prey families fell % (bigeye), % (albacore) and 9% (yellowfin) between old and new studies, with albacore consuming 6% more epipelagic crustacea and % less mesopleagic molluscs, yellowfin consuming % more epipelagic forage fish and % less mesopleagic molluscs, and bigeye consuming % more epipelagic forage fish and 7% less mesopleagic molluscs. Comparing diet studies is a difficult task, especially when working on rescued data; this study highlighted the importance of metadata. Taxonomic identification level appears to be a major problem in the comparison process as it highly depends on the identification skills; analysis of the data at the family level is probably a good compromise between accuracy and precision. Environmental variability is highly likely to have played an important role in the changes apparent in the diet data. However, the lack of continuous monitoring means that it is difficult to discern interannual (ENSO type) variability from that at a decadal scale. Furthermore, the lack of precision in the rescued data makes it difficult to conclude that apparent changes are the result of an ecosystem regime shift.

. Plans for the next fiscal year (one paragraph): None - Project ends October 7.. List of papers published in refereed journals during FY 6. Langley A, Briand K, Kirby DS, Murtugudde R (in press) Influence of oceanographic variability on recruitment of yellowfin tuna thunnus albacares in the western and central Pacific Ocean. Canadian Journal of Fisheries and Aquatic Sciences Kirby DS, Briand K, Langley A, Murtugudde R (submitted) Ecosystem indicators for regime shifts and tuna recruitment in the western and central Pacific Ocean. Marine Ecology Progress Series 5. Other papers, technical reports, meeting presentations, etc. Oral presentations to the second and third meetings of the Scientific Committee of the Western and Central Pacific Fisheries Commission, August 5/6, Manila/Honolulu. Oral presentations to PFRP-PI meeting, November 6, Honolulu, HI, and to the 58 th Annual Tuna Conference, Lake Arrowhead, CA. 6. Graduates (Names of students graduating with MS or PhD degrees during FY 6. Provide titles of their thesis or dissertation): Marie-Laure Coudron obtained her Master degree at the University of Caen in September 6 presenting her work entitled 998 regime shift detection by comparing tuna diets in French Polynesia. 7. Awards (List awards given to JIMAR employees or to the project itself during the period): 8. Publication Count (Total count of publications for the reporting period and previous periods categorized by NOAA lead author and Institute (or subgrantee) lead author and whether it was peer-reviewed or non peer-reviewed (not including presentations): Peerreviewed Non-peer reviewed JL Lead Author NOAA Lead Author Other Lead Author FY5 FY6 FY7 FY5 FY6 FY7 FY5 FY6 FY7

9. Students and Post-docs (Number of students and post-docs that were associated with NOAA funded research. Please indicate if they received any NOAA funding. For institutes that award subcontracts, please include information from your subgrantees): Marie-Laure Coudron (Masters degree candidate, University of Caen) worked on diet data providing results for this and one other PFRP project: Trophic structure and tuna movement in the cold tongue-warm pool pelagic ecosystem of the equatorial Pacific.. Personnel: (i) Number of employees by job title and terminal degree that received more than 5% support from NOAA, including visiting scientists (this information is not required from subgrantees): Karine Briand MS Research Assistant ( months) Marie-Laure Coudron MS intern ( months) (ii) Number of employees/students that received % of their funding from an OAR laboratory and/or are located within that laboratory. (iii) Number of employees/students that were hired by NOAA during the past year: 5

. Images and Captions. Figure. Statistically significant shifts (solid line, dates) in mean values of the two principal component (PC) scores (first two panels) from a multivariate analysis of oceanographic variables selected by the GLM for yellowfin recruitment (third panel) P=.; Cutoff length=;ar()=.68 (MPK) PC 96 9 8-9 5 8 9 6 8 9 7 8 9 8 8 9 9 8 - - - -5-6 P=.; Cutoff length=;ar()=. (MPK) PC 989 998 9 8 9 5 8 9 6 8 9 7 8 9 8 8 9 9 8 - - - B illi -. 6. 5.. Recruitment estimated E +8 957 965 976 99.. 9 8 9 5 9 5 8 9 6 9 6 8 9 7 9 7 8 9 8 9 8 8 9 9 9 9 8 Figure. Statistically significant shifts (solid line, dates) in mean values of the two principal component (PC) scores (first two panels) from a multivariate analysis of oceanographic variables selected by the GLM for bigeye recruitment (third panel) P=.; Cutoff length=;ar()=.55 (MPK) PC 976 9 8-9 5 8 9 6 8 9 7 8 9 8 8 9 9 8 - - - 96-5 -6 P=.; Cutoff length=;ar()=. (MPK) PC 98 9 8 9 5 8 9 6 8 9 7 8 9 8 8 9 9 8 - - 998 - M illi - 5 Recruitment estimated E +6 5 959 99 5 9 8 9 5 9 5 8 9 6 9 6 8 9 7 9 7 8 9 8 9 8 8 9 9 9 9 8 6

Figure. Recruitment GLM for yellowfin tuna. Observed : MULTIFAN-CL recruitment estimate; predicted : GLM recruitment estimate Hindcast period Model period Recruitment (millions of fish) 5 5 5 Predicted Observed 95 96 97 98 99 Figure. Recruitment GLM for bigeye tuna. Observed : MULTIFAN-CL recruitment estimate; predicted : GLM recruitment estimate Hindcast period Model period sh) llions of fish) tment (millions of fi ecruitment (mi Recrui 6 8 95 96 97 98 99 7

Figure 5. Diversity of fish prey families in tuna diet studies 7 ALBACORE YELLOWFIN BIGEYE 6 Number of prey fish families 5-5% - % - 6% - 9% - 7% - % old new old new old new old new old new old new NC FP NC FP NC FP Nb families only in new Nb families only in old Nb common families Figure 6. Changes in prey proportions by vertical class (% weight). : epipelagic; : mesopelagic; : bathypelagic; Crust: crustacea; Mol: molluscs; Fish: fish l 8. 7. 6. 5..... albacore +% C NEW NEW CALEDONIA NEW CALEDONIA yellowfin +8% F -% M bigeye Crust Moll Fish. 8. FRENCH POLYNESIA 7. 6. 5.... +6% C -% M +% C -% M +% F -7% M Crust Mol Fish.. old new old new old new. For multi-year projects, provide budget for the next year on a separate page. All funds requested in the original proposal and approved budget revisions have been received and are hereby aquitted. No further funding is requested for next year. 8