Search

Abstract: Sea turtles have iteroparous reproduction, migrating periodically from foraging habitat to nesting grounds where they generally lay several clutches at regular intervals throughout a nesting season. The total length of the nesting season depends ultimately on environmental conditions that are conducive to the production of viable hatchlings, and varies from 3 to 4months to year-round nesting. As with many migratory marine species, the ease of monitoring marine turtles on their nesting beaches opposed to on their foraging grounds, has resulted in a focus of research on breeding females for population studies and provides a useful albeit limited population index. To explore the precision of monitoring regimes to sample nesting turtle populations, we developed theoretical models for 3 1/2-month and 9-month nesting populations. We used individual-based models for tagged animals and parametric and non-parametric models to estimate annual nest abundance for track count data. These simulation models show that seasonality substantially influenced both the length and temporal position of optimal sampling regimes, showing a five to sevenfold greater effort in monitoring required for longer nesting seasons in order to encounter between 83 and 90% of the annual population. The implications for trend detection and inter-annual and inter-species variations are discussed. [Copyright &y& Elsevier]

We present here a copper speciation model that accounts for the long-term (‘coastal-acidification’) and short-term (daily and seasonal variation) variability in water pH and water temperature. The developed model is applied to a sub-tropical estuary (Moreton Bay, Australia) at a one hundred year time scale so that outputs are consistent with climate change projections. The model predicts that the mean cupric ion concentration (Cu2+) in the estuary will increase by 115% over the next 100 years as a result of the projected decrease in pH and increase in water temperature. Through calibration, the estimated concentration of copper-complexing dissolved organic matter (DOM) in the estuary is found to be 22.5nM. An increase in the concentration of Cu2+, which is the most toxic and bioavailable form of copper, has implications for ecosystem health and may have a negative effect on the detoxifying capacity of DOM. Models that provide a framework for coupling biological, chemical and physical processes are important for providing a holistic perspective of coastal systems, especially for better understanding a system within the context of climatic and non-climatic drivers. [Copyright &y& Elsevier]

Abstract: Bioaccumulation models are an important and widely-used tool for assessing ecosystem health with regards to heavy metal contamination. However, these models do not usually account for the potentially significant effect of temperature-dependency in metal uptake. In this study, we explored the role of temperature-dependency in heavy metal bioaccumulation by developing and comparing two kinetic-based copper bioaccumulation models for a common estuarine oyster (Saccostrea glomerata): (i) a standard first-order model that ignores temperature effects; and (ii) a modified first-order model that uses a standard temperature function to account for the temperature-dependency of the uptake rate constant. The models were calibrated within a Bayesian framework so that parameters could be treated as random variables and any uncertainty propagated through to the model output. A 12-month biomonitoring study was carried out within Moreton Bay, Queensland, Australia to provide time-series data for the modelling. Results of the modelling showed that the two bioaccumulation models provided comparable fits of the biomonitoring field data. However, dependent on the time of year and monitoring period selected, the copper uptake rate would vary dramatically due to temperature effects, which could result in an overestimation or underestimation of the copper uptake rate. Finally by calibrating the bioaccumulation models within a Bayesian framework, these models were able to utilize prior knowledge of the model parameters as part of the calibration process and also account for the uncertainty and variability in the bioaccumulation predictions. The ability to account for uncertainty and variability is an important consideration when undertaking environmental risk assessments especially in coastal waterways where there are strong seasonal variations. [Copyright &y& Elsevier]

Abstract: The loggerhead sea turtle is an endangered species exposed to many anthropogenic hazards in the Pacific. It is widely held that pelagic longline fisheries pose the major risk for Pacific loggerheads but the effects of other risk factors such as human-induced global climate change have rarely been considered. So we used generalised additive regression modelling and autoregressive-prewhitened cross-correlation analysis to explore whether regional ocean temperatures affect the long-term nesting population dynamics for the 2 Pacific loggerhead genetic stocks (Japan, Australia). We found that both Pacific stocks have been exposed to slowly increasing trends in mean annual sea surface temperature in their respective core regional foraging habitats over the past 50 years. We show that irrespective of whether a population was decreasing or increasing that there was an inverse correlation between nesting abundance and mean annual sea surface temperature in the core foraging region during the year prior to the summer nesting season. Cooler foraging habitat ocean temperatures are presumably associated with increased ocean productivity and prey abundance and consequently increased loggerhead breeding capacity. So warming regional ocean temperatures could lead to long-term decreased food supply and reduced nesting and recruitment unless Pacific loggerheads adapt by shifting their foraging habitat to cooler regions. So the gradual warming of the Pacific Ocean over the past 50 years is a major risk factor that must be considered in any meaningful diagnosis of the long-term declines apparent for some Pacific loggerhead nesting populations. [Copyright &y& Elsevier]

The Hawaiian green sea turtle genetic stock is endemic to the Hawaiian Archipelago. This stock was depleted over the past century mainly due to over-exploitation that ceased during the 1970s following protection under the US Endangered Species Act. Nesting trends suggest the stock has been recovering but no formal stock assessment has been undertaken. So, we used a Bayesian state-space surplus-production model to describe Hawaiian green turtle population dynamics given limited data and uncertainty about sea turtle demography. Data series comprised commercial landings of green turtles reported from the Archipelago (1944–1973) and nester abundance recorded at the primary rookery on East Island, French Frigate Shoals (1973–2004). The model incorporated process and observation error and was fitted using Markov chain Monte Carlo simulation with a mix of informative and non-informative priors. We estimated that the Hawaiian green turtle stock was ca. 20% of pre-exploitation biomass when monitoring and protection began in the 1970s. The stock is estimated to be now ca. 83% of pre-exploitation biomass with an intrinsic growth rate ca. 5.4% pa (95% Bayesian credible interval: 3.1–8.9%). Rebound or recovery potential (also exploitation rate at MSP) of this stock was estimated to be 3.4% (1.6–6.2%), which is consistent with estimates for other long-lived late-maturing marine species. So, this once-seriously-depleted green turtle stock is well on the way to recovery and a limited harvest might now be demographically feasible. These findings are relevant for supporting informed public policy debate on the restoration of indigenous hunting rights in the Archipelago. Parameter estimates and model structure from the Bayesian surplus-production model were incorporated in an interactive easy-to-use stochastic simulation model to help support policy analysts in stock recovery planning and to explore sustainable harvest potential. [Copyright &y& Elsevier]

The green sea turtle is one of the long-lived species that comprise the charismatic marine megafauna. The green turtle has a long history of human exploitation with some stocks extinct. Here we report on a 30-year study of the nesting abundance of the green turtle stock endemic to the Hawaiian Archipelago. We show that there has been a substantial long-term increase in abundance of this once seriously depleted stock following cessation of harvesting since the 1970s. This population increase has occurred in a far shorter period of time than previously thought possible. There was also a distinct 3–4 year periodicity in annual nesting abundance that might be a function of regional environmental stochasticity that synchronises breeding behaviour throughout the Archipelago. This is one of the few reliable long-term population abundance time series for a large long-lived marine species, which are needed for gaining insights into the recovery process of long-lived marine species and long-term ecological processes. [Copyright &y& Elsevier]

A stochastic simulation model was developed for the southern Great Barrier Reef (sGBR) green sea turtle stock to foster better insight into local population dynamics and to assess the risk of harvesting on long-term stock viability. The model was ageclass-structured with time-varying, nonlinear and stochastic demographic processes that were parameterised using recent findings on sex- and ageclass-specific growth and survivorship and female breeding behaviour subject to environmental stochasticity. Monte Carlo based uncertainty analysis was used to estimate population growth given demographic parameters subject to sampling error and environmental stochasticity. Model validity was based on replication of stock reference behaviours with sensitivity evaluated using parameter perturbation and Monte Carlo simulation within a fractional factorial sampling design. Fertility and adult survival were the most important high level parameters affecting population growth, where fertility is a function of fecundity and temporal variability in breeding likelihood. A dynamic stochastic form of the model was then used to evaluate stock viability given various turtle harvesting scenarios. It was found, given model assumptions, that even limited turtle harvesting would result in the sGBR stock being categorised, as vulnerable under IUCN criteria for listing of threatened species. It is apparent that extensive harvesting of either eggs or turtles is probably not a prudent management policy, if the long-term viability of the sGBR green sea turtle stock is the primary conservation objective. [Copyright &y& Elsevier]

Abstract: The leatherback turtle Dermochelys coriacea is considered to be at serious risk of global extinction, despite ongoing conservation efforts. Intensive long-term monitoring of a leatherback nesting population on Sandy Point (St. Croix, US Virgin Islands) offers a unique opportunity to quantify basic population parameters and evaluate effectiveness of nesting beach conservation practices. We report a significant increase in the number of females nesting annually from ca. 18–30 in the 1980s to 186 in 2001, with a corresponding increase in annual hatchling production from ca. 2000 to over 49,000. We then analyzed resighting data from 1991 to 2001 with an open robust-design capture–mark–recapture model to estimate annual nester survival and adult abundance for this population. The expected annual survival probability was estimated at ca. 0.893 (95% CI: 0.87–0.92) and the population was estimated to be increasing ca. 13% pa since the early 1990s. Taken together with DNA fingerprinting that identify mother–daughter relations, our findings suggest that the increase in the size of the nesting population since 1991 was probably due to an aggressive program of beach protection and egg relocation initiated more than 20 years ago. Beach protection and egg relocation provide a simple and effective conservation strategy for this Northern Caribbean nesting population as long as adult survival at sea remains relatively high. [Copyright &y& Elsevier]

• Drift speeds and trajectories were similar for shallow and standard depth DFADs. • Tuna aggregation times were similar for shallow and standard depth DFADs. • Purse-seine catch rates for tunas were similar for shallow and standard depth DFADs. An at-sea experiment was undertaken to evaluate the performance of 150 shallow depth (5 m) prototype drifting fish-aggregating devices (DFADs) with rope appendages, compared to 150 standard depth (∼ 40 m) traditional design DFADs with purse-seine net appendages, in the equatorial eastern Pacific Ocean tuna purse-seine fishery, seeking a solution to reduce purse-seine fishing mortality on undesirable sizes of bigeye tuna. Following concurrent deployments of the two DFAD types along transects, the average daily drift speeds were significantly different but similar as were the drift trajectories among the two DFAD types. Based on evaluations of the time-series of acoustic data from the echo-sounder buoys attached to the shallow and standard depth DFADs, the average time before aggregation by non-tuna species was 15.3 d (range: 3.2–65.5) and 18.2 d (range: 1.1–101.2), respectively, and the average time before aggregation by tuna species was 62.2 d (range: 3.3–248.3) and 70.2 d (range: 1.5–270.5), respectively. Analyses of the catch per set data for tunas and non-tuna species, using generalized additive mixed models with Bayesian inference, indicated no significant differences in catch rates from sets on shallow and standard depth DFADs. There was a similar proportion of bigeye tuna in the catch for purse-seine sets on the shallow and standard depth DFADs. [ABSTRACT FROM AUTHOR]