Preliminary comparison of natural versus model-predicted recovery of vessel-generated seagrass injuries in Florida Keys National Marine Sanctuary

Each year, more than 500 motorized vessel groundings cause widespread damage to seagrasses in Florida Keys National Marine Sanctuary (FKNMS). Under Section 312 of the National Marine Sanctuaries Act (NMSA), any party responsible for the loss, injury, or destruction of any Sanctuary resource, including seagrass, is liable to the United States for response costs and resulting damages. As part of the damage assessment process, a cellular automata model is utilized to forecast seagrass recovery rates. Field validation of these forecasts was accomplished by comparing model-predicted percent recovery to that which was observed to be occurring naturally for 30 documented vessel grounding sites. Model recovery forecasts for both Thalassia testudinum and Syringodium filiforme exceeded natural recovery estimates for 93.1% and 89.5% of the sites, respectively. For Halodule wrightii, the number of over- and under-predictions by the model was similar. However, where under-estimation occurred, it was often severe, reflecting the well-known extraordinary growth potential of this opportunistic species. These preliminary findings indicate that the recovery model is consistently generous to Responsible Parties in that the model forecasts a much faster recovery than was observed to occur naturally, particularly for T. testudinum, the dominant seagrass species in the region and the species most often affected. Environmental setting (i.e., location, wave exposure) influences local seagrass landscape pattern and may also play a role in the recovery dynamics for a particular injury site. An examination of the relationship between selected environmental factors and injury recovery dynamics is currently underway. (PDF file contains 20 pages.)

Factors influencing choice of fishing location in Nankumba Peninsula: A case of study of gillnet and chilimira fisheries

This study was carried out to identify factors that influence choice of fishing location and carry out profitability analysis of Chilimira and Gillnet in different fishing locations. A survey using semi-structured questionnaire was administered to 99 Gillnet and 101 Chilimira fishers in Nankumba Peninsula in Mangochi District. The logit model was used to determine the factors influencing choice of fishing location among the fishers. The study showed that 92.1% of Chilimira fishers are operating in offshore areas while 69.7% Gillnet fishers are operating in inshore areas. Chilimira offshore fishers have higher daily average gross margins than their inshore counterparts and Gillnet fishers. However, they incurred more operating costs than the inshore Chilimira and Gillnet fishers. Furthermore, they find their fishing occupation more rewarding as evidenced by the higher returns to labour. The factors that influenced fisher’s choice of fishing location were Age of the fisher, type of fishing vessel and gear, possession of motor sail engine and access to information about previous day’s catch rates. Finally the study concluded that artisanal fishers in Malawi use different criteria in deciding where to fish. The criterion involves a complex interaction of biological, technological, personal and economical factors and time. However, the resource constrained artisanal fisher will need support to enable him exploit offshore fishery resources. Consequently the study recommends that appropriate fishery development interventions by the government and other stakeholders must adapt to the economics and lifestyles driving the artisanal fishers to fish in particular locations and therefore, build on this foundation to improve the existing fishing technologies.

An environmentally based growth model that uses finite difference calculus with maximum likelihood method: its application to the brackish water bivalve Corbicula japonica in Lake Abashiri, Japan

We present a growth analysis model that combines large amounts of environmental data with limited amounts of biological data and apply it to Corbicula japonica. The model uses the maximum-likelihood method with the Akaike information criterion, which provides an objective criterion for model selection. An adequate distribution for describing a single cohort is selected from available probability density functions, which are expressed by location and scale parameters. Daily relative increase rates of the location parameter are expressed by a multivariate logistic function with environmental factors for each day and categorical variables indicating animal ages as independent variables. Daily relative increase rates of the scale parameter are expressed by an equation describing the relationship with the daily relative increase rate of the location parameter. Corbicula japonica grows to a modal shell length of 0.7 mm during the first year in Lake Abashiri. Compared with the attain-able maximum size of about 30 mm, the growth of juveniles is extremely slow because their growth is less susceptible to environmental factors until the second winter. The extremely slow growth in Lake Abashiri could be a geographical genetic variation within C. japonica.

El Niño reconstructions and confirmation of a pan-Californian model via Radiolarian evidence

Radiolarian number and/or flux rates extracted from Holocene and fossil sediments are used to help detect the presence of, type of (weak or strong), and exact location of the depocenter under an El Niño. These data, along with known provenances of certain radiolarians, support an earlier model that suggests a weak El Niño is a northern and coupled expression of a more southerly strong component dominated by eastern tropical Pacific water underlain by California current and gyre water.