Skin lesions on common bottlenose dolphins (Tursiops truncatus) from three sites in the Northwest Atlantic, USA

Skin disease occurs frequently in many cetacean species across the globe; methods to categorize lesions have relied on photo-identification (photo-id), stranding, and bycatch data. The current study used photo-id data from four sampling months during 2009 to estimate skin lesion prevalence and type occurring on bottlenose dolphins (Tursiops truncatus) from three sites along the southeast United States coast [Sarasota Bay, FL (SSB); near Brunswick and Sapelo Island, GA (BSG); and near Charleston, SC (CHS)]. The prevalence of lesions was highest among BSG dolphins (P=0.587) and lowest in SSB (P=0.380), and the overall prevalence was significantly different among all sites (p<0.0167). Logistic regression modeling revealed a significant reduction in the odds of lesion occurrence for increasing water temperatures (OR=0.92; 95%CI:0.906-0.938) and a significantly increased odds of lesion occurrence for BSG dolphins (OR=1.39; 95%CI:1.203-1.614). Approximately one-third of the lesioned dolphins from each site presented with multiple types, and population differences in lesion type occurrence were observed (p<0.05). Lesions on stranded dolphins were sampled to determine the etiology of different lesion types, which included three visually distinct samples positive for herpesvirus. Although generally considered non-fatal, skin disease may be indicative of animal health or exposure to anthropogenic or environmental threats, and photo-id data provide an efficient and cost-effective approach to document the occurrence of skin lesions in free-ranging populations.

Modeling red sea urchin (Strongylocentrotus franciscanus) growth using six growth functions

The growth of red sea urchins (Strongylocentrotus franciscanus) was modeled by using tag-recapture data from northern California. Red sea urchins (n=211) ranging in test diameter from 7 to 131 mm were examined for changes in size over one year. We used the function Jt+1 = Jt + f(Jt) to model growth, in which Jt is the jaw size (mm) at tagging, and Jt+1 is the jaw size one year later. The function f(Jt), represents one of six deterministic models: logistic dose response, Gaussian, Tanaka, Ricker, Richards, and von Bertalanffy with 3, 3, 3, 2, 3, and 2 minimization parameters, respectively. We found that three measures of goodness of fi t ranked the models similarly, in the order given. The results from these six models indicate that red sea urchins are slow growing animals (mean of 7.2 ±1.3 years to enter the fishery). We show that poor model selection or data from a limited range of urchin sizes (or both) produces erroneous growth parameter estimates and years-to-fishery estimates. Individual variation in growth dominated spatial variation at shallow and deep sites (F=0.246, n=199, P=0.62). We summarize the six models using a composite growth curve of jaw size, J, as a function of time, t: J = A(B – e–Ct) + Dt, in which each model is distinguished by the constants A, B, C, and D. We suggest that this composite model has the flexibility of the other six models and could be broadly applied. Given the robustness of our results regarding the number of years to enter the fishery, this information could be incorporated into future fishery management plans for red sea urchins in northern California.

Benthic macro-biota in Gaula River - Kumaon Himalaya

The density of benthic macro-biota in number over weight of biomass at three sampling stations was 29 units m²/0.614 g m² to 171 units m²/11.346 m² at Station I; 22 units m²/0.410 g m² to 155 units m²/8.717 m² at Station II; 15 units m² 10.321 g m² to 122 units m²/6.793 g m² at Station III. The Caddis fly larvae were the most dominant component and contributed 52.41% in the macro-biota. These animals were abundant in Gaula River when benthic algae were abundant; water is well oxygenated, alkaline and contains sufficient nutrients but observed to be less abundant during high velocity of water, high river depth and higher turbid waters.