Evaluating methods for estimating rare events with zero-heavy data: a simulation model estimating sea turtle bycatch in the pelagic longline fishery

Estimating rare events from zero-heavy data (data with many zero values) is a common challenge in fisheries science and ecology. For example, loggerhead sea turtles (Caretta caretta) and leatherback sea turtles (Dermochelys coriacea) account for less than 1% of total catch in the U.S. Atlantic pelagic longline fishery. Nevertheless, the Southeast Fisheries Science Center (SEFSC) of the National Marine Fisheries Service (NMFS) is charged with assessing the effect of this fishery on these federally protected species. Annual estimates of loggerhead and leatherback bycatch in a fishery can affect fishery management and species conservation decisions. However, current estimates have wide confidence intervals, and their accuracy is unknown. We evaluate 3 estimation methods, each at 2 spatiotemporal scales, in simulations of 5 spatial scenarios representing incidental capture of sea turtles by the U.S. Atlantic pelagic longline fishery. The delta-log normal method of estimating bycatch for calendar quarter and fishing area strata was the least biased estimation method in the spatial scenarios believed to be most realistic. This result supports the current estimation procedure used by the SEFSC.

Evaluation of the body burdens of heavy metals in five commercially important fishes from different locations in Kainji Lake

The level and distribution of some heavy metals viz Cadmium, Lead, Copper Zinc, and Cobalt in five commercially important fishes, water and sediments at three different locations in Kainj Lake were determined using standard methods. The results show that the ranges of heavy metals mu g/g in fishes in Dam site Laotian are: Cd (0.05~c0.01-20~c01), (Pb(ND-1.12 plus or minus )1), Cu (0.81~c25-2.93~c06), Zn (20.89 arrow right .15-36.78~c2.97), Co(0.08~c01-0.27~c02); in cover Dam, the ranges are Cd (0.04~c02-0.16~c0.2), Pb (nd-02~c01), Cu(0.75~c05-2.61~c13), Zn(15.70~c1.55-32.23~c2.70), Co(0.04~c02-0.25~c0.01) and in Yuna they are Cd (0.05~c01-0.14~c02), Pb (nd-0.32~c01), Cu (0.23~c07-2.70~c05), Zn(15.50 plus or minus `.35-25.62~c2.47), Co(0.07~c02-23~c0.01). The metals concentration (mg/l) in the water sample from Dam site, cover dam and Yuna respectively are Cd(0.007~c001,. 004~c001 and 0.005~001), Pb(013~c001, ND and ND), Cu(.055~c008.030~c007, 05 plus or minus .010), Zn(0.13~c01, 0.060 plus or minus .0055) and Co (.026 plus or minus .022 plus or minus .004, .024 plus or minus .004), while the metals concentration ( mu g/g) in sediments sample from Dam site, cover dam and Yuna are respectively Cd(.05 plus or minus .01, .02 plus or minus .01), Pb(16.00~c1.00, ND and 9.33~c1.01), Cu(24.00~c1.34, 4.26 plus or minus .91 and 11.08~c1.32), Zn(42.00~c1.00, 35~c10 and 38.00 plus or minus .45), Co(15.00~c1.17, 8.69~c1.21 and 10.91~c44). The concentrations of the tested heavy metals are within the acceptable standards of WHO (1987a)

A general framework for integrating environmental time series into stock assessment models: model description, simulation testing, and example

We present a method to integrate environmental time series into stock assessment models and to test the significance of correlations between population processes and the environmental time series. Parameters that relate the environmental time series to population processes are included in the stock assessment model, and likelihood ratio tests are used to determine if the parameters improve the fit to the data significantly. Two approaches are considered to integrate the environmental relationship. In the environmental model, the population dynamics process (e.g. recruitment) is proportional to the environmental variable, whereas in the environmental model with process error it is proportional to the environmental variable, but the model allows an additional temporal variation (process error) constrained by a log-normal distribution. The methods are tested by using simulation analysis and compared to the traditional method of correlating model estimates with environmental variables outside the estimation procedure. In the traditional method, the estimates of recruitment were provided by a model that allowed the recruitment only to have a temporal variation constrained by a log-normal distribution. We illustrate the methods by applying them to test the statistical significance of the correlation between sea-surface temperature (SST) and recruitment to the snapper (Pagrus auratus) stock in the Hauraki Gulf–Bay of Plenty, New Zealand. Simulation analyses indicated that the integrated approach with additional process error is superior to the traditional method of correlating model estimates with environmental variables outside the estimation procedure. The results suggest that, for the snapper stock, recruitment is positively correlated with SST at the time of spawning.

Monte Carlo simulation of streamflow of the Salt River, Arizona

EXTRACT (SEE PDF FOR FULL ABSTRACT): Evaluations of the impact of climate change (such as a greenhouse effect) upon water resources should represent both the expected change and the uncertainty in that expectation. Since water resources such as streamflow and reservoir levels depend on a variety of factors, each of which is subject to significant uncertainty, it is desirable to formulate methods of representing that uncertainty in the forcing factors and from this determine the uncertainty in the response variables of interest. We report here progress in the representation of the uncertainty in climate upon the uncertainty in the estimated hydrologic response.

Biomonitoring of polycyclic aromatic hydrocarbons (PAH) and heavy metals Ni, V in sediments and anodonts of the Anzali Lagoon and applicability of netural red retention assay (NRR) as biomarkers of these pollutants

Biochemical ecotoxicology and biomarkers using are a new sciences that are used for biomonitoring in aquatic environment. Biomonitoring plays a vital role in strategies to identify, assess, and control contaminants. On the other hands in recent year's attention to polycyclic Aromatic Hydrocarbons (PAHs) and heavy metals increased in aquatic environments because of their carcinogenic and mutagenic properties combined with their nearly ubiquitous distribution in depositional environments by oil pollution or industrial waste waters. The present research aimed to assess PAHs and Ni, V levels in surface sediments and bivalves (Anodonta cygnea)and the effects of PAHs and heavy metals (Ni,V) on the hemocyte of the Anodonta cygnea were investigated in 2 stations (Mahrozeh, Selke in Anzali Lagoon, North of Iran). Samples were collected during at 2 different periods of the year, Dry and rain seasons, (June & September) and to confirm our first observations, Cage station is added. The bivalves hemocytes were monitored for membrane injury by NRR methods (neutral red retention assay). Heavy metal (Ni, V) concentrations were determined by Atomic Absorption in Anodonta cygnea and the sediments in Anzali Lagoon. The vanadium concentration in bivalves and sediments was ND(not detect )-0.4231 μg/g and 1.4381-306.9603 μg/g dry weight respectively. Nickel concentration in bivalves and sediments was 0.0231-1.3351, 0.4024-19.3561 μg/g dry weight respectively. PAHs concentrations were determined by GC-Mass in Anodonta cygnea and the sediments. Average concentration of PAHs is 115-373.788 ng/g dry weight in bivalves and average concentration of PAHs is 34.85-1339.839 ng/g dry weight in sediments. Bioaccumulation sediments factor(BASF) is high about PAHs (>1) and BASF is low for Ni, V (<1) . Internal Damage mechanisms of bivalves hemocytes (cell mortality, dye leakage, decreased membrane stability, are observed (Lowe Methods). Statistical analysis was used to explore the relationship between altered cellular and above contaminants. There are power and negative correlations between PAHs and NRR method for hemocytes in Anodonta cygnea (P<0.0005), but good correlation is not observed between Ni, V and NRR method for hemocytes in every time. This research indicates that the NRR assay is a useful screening technique able to discriminate polluted sites and at first we announce that Anodonta cygnea hemocytes are efficient biomarker for PAHs pollutants in fresh water.