An Index of Abundance for Coastal Species of Juvenile Sharks from the Northeast Gulf of Mexico

A fishery-independent assessment of juvenile coastal shark populations in U.S. waters of the northeast Gulf of Mexico was conducted using two methods: gillnets and longlines. Surveys were conducted monthly during April–October in two fixed sampling areas from 1996 to 1998. The Atlantic sharpnose shark, Rhizoprionodon terraenovae, and the blacktip shark, Carcharhinus limbatus, were the most common species captured with either longlines or gillnets. An additional 14 shark species were captured, and juvenile indices of abundance were developed for 8 species with gillnets and 6 species of sharks with longlines. Trends in catch-per-unit-effort were found to vary depending on species. Length-frequency information revealed that the majority of sharks captured were juveniles. Given the direct relationship between stock and recruitment for sharks, continued monitoring of juvenile abundance will aid in determining the strength of the parental stock size and for predicting future population strength.

Gross energy requirement in fishing operations

Energy is a key input into the fish harvesting process. Efficient use of energy helps in reducing operational costs and environmental impact, while increasing profits. Energy optimisation is an important aspect of responsible fishing as enunciated in the Code of Conduct for Responsible Fisheries. Gross Energy Requirement (GER) is the sum of all non-renewable energy resources consumed in making available a product or service and is expressed in energy units per physical unit of product or service delivered. GER is a measure of intensity of non-renewable resource use and it reflects the amount of depletion of earth’s inherited store of non-renewable energy in order to create and make available a product or service. In this study, GER in fish harvesting up to the point of landing is estimated in selected fish harvesting systems in the small-mechanised sectors of Indian fisheries and compared with reported results from selected non mechanised and motorised fishing systems to reflect the situation during 1997-1998. Among the fish harvesting systems studied, GER t fish-1 ranged from 5.54 and 5.91 GJ, respectively, for wooden and steel purse seiners powered by 156 hp engines; 6.40 GJ for wooden purse seiner with 235 hp engine; 25.18 GJ for mechanised gillnet/line fishing vessel with 89 hp engines; to 31.40 and 36.97 GJ, respectively, for wooden and steel trawlers powered by 99-106 hp engines.

Scoping report: current status of index-based insurance in Bangladesh

With current and anticipated increases in magnitude of extreme weather events and a declining consistency in weather patterns, particularly challenging for agriculture, there has been a growing interest in weather index-based insurance (IBI) schemes in Bangladesh. A number of weather index-based insurance products have already been tested and applied across Asia and Africa, with varying degrees of success, as a mechanism to improve livelihood security by enabling vulnerable populations to transfer risk associated with climate change, extreme weather events and other hazards. In the process, these efforts have generated important new knowledge on how these schemes can be designed and implemented for optimal results. However, the practice of index-based insurance is still limited in Bangladesh, and the experience and knowledge generated by the different stakeholders involved needs to be better communicated.

Real-time climate monitoring using an AVHRR-based vegetation index

A normalized difference vegetation index (NDVI) has been produced and archived on a 1° latitude by 1° longitude grid between 55°S and 75°N. The many sources of data errors in the NDVI include cloud contamination, scan angle biases, changes in solar zenith angle, and sensor degradation. Week-to-week variability, primarily caused by cloud contamination and scan angle biases, can be minimized by temporally filtering the data. Orbital drift and sensor degradation introduces interannual variability into the dataset. These trends make the usefulness of a long-term climatology uncertain and limit the usefulness of the NDVI. Elimination of these problems should produce an index that can be used for climate monitoring.