Diet and condition of American Alligators (Alligator mississippiensis)in three central Florida lakes

Understanding the diet of crocodilians is important because diet affects condition, behavior, growth, and reproduction. By examining the diet of crocodilians, valuable knowledge is gained about predator-prey interactions and prey utilization among habitats. In this study, I examined the diet and condition of adult American alligators (Alligator mississippiensis) in three central Florida lakes, Griffin, Apopka, and Woodruff. Two hundred adult alligators were captured and lavaged from March through October 2001, from April through October 2002, and from April through August 2003. Alligators ate a variety of vertebrate and invertebrate prey, but vertebrates were more abundant and fish dominated alligator diets in the lakes. Species composition of fish varied among the lakes. The majority of the diet of alligators from Lakes Apopka and Woodruff was fish, 90% and 84% respectively. Lake Apopka alligators consumed a significantly (P = 0.006) higher proportion of fish in their diet. Fish were 54% of the diet of Lake Griffin alligators and the infrequent occurrence of reptiles, mammals, birds, and amphibians often resulted in a large biomass. Differences in alligator diets among lakes may be due to differences in sample size (higher numbers of samples from Lake Griffin), prey availability, habitat, prey vulnerability, or prey size. Alligator condition (Fulton’s Condition Factor, K) was significantly (P < 0.001) different among the lakes. Alligators from Lake Apopka had the highest condition, followed by those from Lake Griffin, and alligators from Lake Woodruff had the lowest condition. Composition of fish along with diversity and equitability of fish in alligator diets may have contributed to differences in condition among lakes. Condition was probably also due to factors other than diet such as alligator hunting behavior, alligator density, or year-round optimal temperature that prolongs feeding. The observed diet and condition differences probably reflect both habitat differences and prey availability in these three lakes.

Arylsulfatase activity in marine polychaetes

Marine polychaetes, collected from the Vellar Estuary exhibited arylsulfatase activity. Lumbriconeries sp. Polydora sp. Monojis sp. and Heteromastus sp. were selected for this study. Of these, Heteromastus sp. showed maximum enzymatic activity and it has been chosen for the enzyme kinetic studies such as pH, optimal temperature, period of incubation and the effect of DDT. Enzyme activity showed single peak at pH 6.2 possibly indicating the presence of one type of arylsulfatase. Maximum activity was attained after 12h of incubation at 29°C. DDT has an inhibiting effect on the arylsulfatase activity even at the concentration of 10 p.p.m. and the activity was completely lost at 100 p.p.m.

A modeling approach to identify optimal habitat and suitable fishing grounds for neon flying squid (Ommastrephes bartramii) in the Northwest Pacific Ocean

We developed a habitat suitability index (HSI) model to understand and identify the optimal habitat and potential fishing grounds for neon f lying squid (Ommastrephes bartramii) in the Northwest Pacific Ocean. Remote sensing data, including sea surface temperature, sea surface salinity, sea surface height, and chlorophyll-a concentrations, as well as fishery data from Chinese mainland squid f leets in the main fishing ground (150–165°E longitude) from August to October, from 1999 to 2004, were used. The HSI model was validated by using fishery data from 2005. The arithmetic mean modeling with three of the environmental variables—sea surface temperature, sea surface height anomaly, and chlorophyll- a concentrations—was defined as the most parsimonious HSI model. In 2005, monthly HSI values >0.6 coincided with productive fishing grounds and high fishing effort from August to October. This result implies that the model can reliably predict potential f ishing grounds for O. bartramii. Because spatially explicit fisheries and environmental data are becoming readily available, it is feasible to develop a dynamic, near real-time habitat model for improving the process of identifying potential fishing areas for and optimal habitats of neon flying squid.