Studying small purse‐seine vessel fishing behavior with tuna catch data: Implications for eastern Pacific Ocean dolphin conservation

Despite achievements in dolphin conservation for the tuna purse‐seine fishery of the eastern Pacific Ocean, debate continues about the magnitude and importance of dolphin mortality caused by small (unobserved) vessels. In‐port sampling of tuna catch size composition is a potentially cost‐effective means of identifying unobserved vessels that may be catching tunas associated with dolphins because yellowfin tuna caught in association with dolphins are larger, on average, than those caught in other types of purse‐seine sets. A classification algorithm to predict purse‐seine set type (“dolphin” vs. “nondolphin”) was built from port‐sampling data on yellowfin tuna length‐frequencies and the date and location of fishing of large (observed) vessels. This classification algorithm was used to screen the port‐sampling data of small vessels collected during 2006‐2009, assuming the fishing practices of the two groups resulted in similar catch characteristics. From these results, hypothetical time series of dolphin mortality for small vessels were constructed and incorporated into a population dynamics model, along with mortalities of large vessels. Results suggest that any dolphin mortality of small vessels is unlikely to be substantially affecting trends in dolphin abundance. These results underscore the importance of in‐port sampling, in combination with at‐sea observation and fishery‐independent surveys, to effective management.     

Co-Occurrence and Habitat Use of Fin Whales,Striped Dolphins and Atlantic Bluefin Tuna in the Northwestern Mediterranean Sea

Different dolphin and tuna species have frequently been reported to aggregate in areas of high frontal activity, sometimes developing close multi-species associations to increase feeding success. Aerial surveys are a common tool to monitor the density and abundance of marine mammals, and have recently become a focus in the search for methods to provide fisheries-independent abundance indicators for tuna stock assessment. In this study, we present first density estimates corrected for availability bias of fin whales (Balaenoptera physalus) and striped dolphins (Stenella coeruleoalba) from the Golf of Lions (GoL), compared with uncorrected estimates of Atlantic bluefin tuna (ABFT; Thunnus thynnus) densities from 8 years of line transect aerial surveys. The raw sighting data were further used to analyze patterns of spatial co-occurrence and density of these three top marine predators in this important feeding ground in the Northwestern Mediterranean Sea. These patterns were investigated regarding known species-specific feeding preferences and environmental characteristics (i. e. mesoscale activity) of the survey zone. ABFT was by far the most abundant species during the surveys in terms of schools and individuals, followed by striped dolphins and fin whales. However, when accounted for availability bias, schools of dolphins and fin whales were of equal density. Direct interactions of the species appeared to be the exception, but results indicate that densities, presence and core sighting locations of striped dolphins and ABFT were correlated. Core sighting areas of these species were located close to an area of high mesoscale activity (oceanic fronts and eddies). Fin whales did not show such a correlation. The results further highlight the feasibility to coordinate research efforts to explore the behaviour and abundance of the investigated species, as demanded by the Marine Strategy Framework Directive (MSFD).     

Atlantic Bluefin Tuna in the Gulf of Maine, I: Estimation of Seasonal Abundance Accounting for Movement, School and School-Aggregation Behaviour

Direct assessment of the abundance of highly migratory pelagic species, such as tuna, is rarely available and most indices are based on catch information. We estimate the seasonal abundance of North Atlantic bluefin tuna, Thunnus thynnus, in the Gulf of Maine (GOM) from a 3-year aerial survey conducted with commercial spotter pilots, while also utilizing findings from analyses of tracking and tagging data. We apply statistical correction and calibration to seasonal abundance estimates accounting for measured changes in horizontal and vertical movement behaviour, size, shape and aggregation of bluefin tuna schools. Our approach relies on ecological knowledge of bluefin tuna to extrapolate survey observations across areas not sampled by correcting survey abundance estimates based on range of movement search pattern and depth preference. We demonstrate how separate findings obtained through the analysis of data collected across different spatial and temporal scales can be integrated to correct and calibrate estimates of population abundance. We obtain fitted estimates of seasonal abundance of bluefin tuna in the GOM during 1994–1996 in the range of 45,000–51,000 individuals. If tuna behaviour is not accounted for, we estimate that the base or residual survey precision would be 4–7% determined from analysis of recent spotter survey data in the study region. We estimate the precision in estimating seasonal abundance accounting for tuna behaviour to lie within a range of 1,301–3,302%. Under hypothetical future improvements in survey design that achieve a precision of 20% in transect length and placement, we calculate net-precision to lie within a range of 82–93%. This calculation assumes reducible uncertainty in school size estimation and irreducible uncertainty in movement and school-aggregation behaviour. We infer that survey precision could be further reduced by 43–32% to attain 10–50% in which a 3–8 years adaptive survey design may reliably detect a seasonal abundance trend.     

RELATIVE ABUNDANCE, DISTRIBUTION AND INTER-SPECIFIC RELATIONSHIP OF CETACEAN SCHOOLS IN THE EASTERN TROPICAL PACIFIC

The relative abundance of the most common cetacean schools in the eastern tropical Pacific Ocean for 1977–1980 are estimated based on encounter rates with tuna purse-seiners. No temporal trends were apparent in the relative abundance estimates. The geographic distributions for eight different school types are described. Multivariate statistical techniques are used to investigate interrelations between species and relationships to parameters of the physical environment. The results suggest three major species groupings: (1) an inshore grouping of bottlenose dolphins ( Tursiops truncates ), Risso's dolphin ( Grampus griseus ), pilot whales ( Globicephala macrorhynchus ) and, to a lesser extent, common dolphins ( Delphinus delphis ); (2) an offshore pelagic grouping of spotted and spinner dolphins ( Stenella attenuate and S. longirostris ); and (3) an association between pilot whales and common dolphins that overlaps the first grouping in inshore areas and also tends to be segregated from the second grouping. The results also suggest that relative densities of different school types are strongly related to physical environmental parameters, the most important being sea surface temperature, depth of the thermocline and thickness of the oxygen minimum layer.     

World whale stocks

The history of whaling is very largely one of repeated over-exploitation of the various whale stocks which became available through discovery or technological advance. Modern whaling has similarly caused considerable reductions in the numbers of some species in the major whaling grounds. Stock assessment methods are based on catch and effort statistics, biological information including age and reproductive status, marking and sightings records. Catch effort data have to be used with caution, because of changes in species preference, shifts in the whaling grounds and national fleet variations. With allowance made for these factors, cumulative catches adjusted for recruitment can be used to estimate the initial stock number. Changes in stock density after known catches also lead to abundance estimates. Logarithmic regression of age composition data are used to find the total mortality rates. The natural mortality can be estimated from early season catches in a fishery or pre-fishery year classes caught more recently; fishing mortality is found by subtraction, which again leads to abundance estimates. Mathematical approaches incorporating recruitment estimates from actual age composition data and theoretical population models have been employed. Additional estimates come from mark release-recapture experiments and direct sightings counts from whaling vessels and research ships. The latter are the only means of estimating the protected species. The yields which the various stocks can sustain are calculated from direct observations and theoretical considerations of the changes in recruitment, largely due to increased pregnancy rates and the lower ages at sexual maturity which occur in exploited stocks. The results of all the available analyses have been compared and combined to produce the population estimates and yields tabulated. The object of whale management is to bring all stocks to the levels providing the maximum or optimum sustainable yields. These are defined in terms of numbers at the moment, but may be expressed as biomass in the future.     

Behavioural Effects of Tourism on Oceanic Common Dolphins,Delphinus sp., in New Zealand: The Effects of Markov Analysis Variations and Current Tour Operator Compliance with Regulations

Common dolphins, Delphinus sp., are one of the marine mammal species tourism operations in New Zealand focus on. While effects of cetacean-watching activities have previously been examined in coastal regions in New Zealand, this study is the first to investigate effects of commercial tourism and recreational vessels on common dolphins in an open oceanic habitat. Observations from both an independent research vessel and aboard commercial tour vessels operating off the central and east coast Bay of Plenty, North Island, New Zealand were used to assess dolphin behaviour and record the level of compliance by permitted commercial tour operators and private recreational vessels with New Zealand regulations. Dolphin behaviour was assessed using two different approaches to Markov chain analysis in order to examine variation of responses of dolphins to vessels. Results showed that, regardless of the variance in Markov methods, dolphin foraging behaviour was significantly altered by boat interactions. Dolphins spent less time foraging during interactions and took significantly longer to return to foraging once disrupted by vessel presence. This research raises concerns about the potential disruption to feeding, a biologically critical behaviour. This may be particularly important in an open oceanic habitat, where prey resources are typically widely dispersed and unpredictable in abundance. Furthermore, because tourism in this region focuses on common dolphins transiting between adjacent coastal locations, the potential for cumulative effects could exacerbate the local effects demonstrated in this study. While the overall level of compliance by commercial operators was relatively high, non-compliance to the regulations was observed with time restriction, number or speed of vessels interacting with dolphins not being respected. Additionally, prohibited swimming with calves did occur. The effects shown in this study should be carefully considered within conservation management plans, in order to reduce the risk of detrimental effects on common dolphins within the region.     

Abundance and Survival Rates of the Hawai’i Island Associated Spinner Dolphin (Stenella longirostris) Stock

Reliable population estimates are critical to implement effective management strategies. The Hawai’i Island spinner dolphin (Stenella longirostris) is a genetically distinct stock that displays a rigid daily behavioural pattern, foraging offshore at night and resting in sheltered bays during the day. Consequently, they are exposed to frequent human interactions and disturbance. We estimated population parameters of this spinner dolphin stock using a systematic sampling design and capture–recapture models. From September 2010 to August 2011, boat-based photo-identification surveys were undertaken monthly over 132 days (>1,150 hours of effort; >100,000 dorsal fin images) in the four main resting bays along the Kona Coast, Hawai’i Island. All images were graded according to photographic quality and distinctiveness. Over 32,000 images were included in the analyses, from which 607 distinctive individuals were catalogued and 214 were highly distinctive. Two independent estimates of the proportion of highly distinctive individuals in the population were not significantly different (p = 0.68). Individual heterogeneity and time variation in capture probabilities were strongly indicated for these data; therefore capture–recapture models allowing for these variations were used. The estimated annual apparent survival rate (product of true survival and permanent emigration) was 0.97 SE±0.05. Open and closed capture–recapture models for the highly distinctive individuals photographed at least once each month produced similar abundance estimates. An estimate of 221±4.3 SE highly distinctive spinner dolphins, resulted in a total abundance of 631±60.1 SE, (95% CI 524–761) spinner dolphins in the Hawai’i Island stock, which is lower than previous estimates. When this abundance estimate is considered alongside the rigid daily behavioural pattern, genetic distinctiveness, and the ease of human access to spinner dolphins in their preferred resting habitats, this Hawai’i Island stock is likely more vulnerable to negative impacts from human disturbance than previously believed.     

Empirical estimates of historical variations in the catchability and fishing power of pelagic longline fishing gear

I quantify the effects of 11 variables on the catchability and fishing power of pelagic longlines, which are used to catch tunas and billfishes in the open ocean. Extension of the depth range and the duration of longline operations have reduced the catchability of several epipelagic species, such as mako sharks (Isurus spp.), since industrial longlining commenced in the tropical Pacific Ocean in the early 1950s. Reductions in the body size of many species may also have reduced encounters with longline hooks. By contrast, the catchability of commercially valuable bigeye tuna (Thunnus obesus) increased substantially because of the longer duration and extension of the depth range of longlines. Stronger and less visible line materials and increased fishing-master experience also contributed to increased catchability. By affecting the rate of bait loss, the introduction of new bait species increased fishing power. This study highlights significant problems in deriving indices of abundance from commercial catch and effort data. Instead of relying on commercial data, assessments should use tag-recapture experiments or dedicated surveys to obtain fishery-independent estimates of abundance.     

Standardizing fishery-dependent catch and effort data in complex fisheries with technology change

Standardization of commercial catch and effort data is important in fisheries where standardized abundance indices based on fishery-dependent data are a fundamental input to stock assessments. The goal of the standardization is then to minimize bias due to the confounding of apparent abundance patterns with fishing power. There is a high risk of confounding between fishing power and abundance in fisheries where the fleet has altered their fishing technology over the years. Also, the spatial aspects and the fishing history can be so heterogeneous that any standardization really involves an extrapolation, for example to a hypothetical standard vessel. When the standardization involves an extrapolation, then the appropriate modeling strategy is to build a so-called estimation model, rather than a predictive model. Strategies to build such an estimation model from fishery-dependent data include: pay careful attention to subject matter, and collect information about potential confounding effects to include in the model (putting a high value on the acquisition of data on covariates); model variable catchability at a highly disaggregated scale; aim for realistic coefficients when fitting the model and pay relatively less attention to achieving precision or maximizing explained variance; adopt modern statistical methods to combine data from different sources; and if data are deficient, then apply precautionary allowances. These strategies offer some protection against bias due to confounding, in the absence of formal criteria for identifying the best model.