To collect information about the location and water depth of the fishing grounds, we attached data loggers to otter boards of three bottom otter trawlers in Ise Bay, with GPS data loggers on deck. We likewise asked the fishermen to record the outcomes of every haul on a logbook in chronological order. In the event that there are missing record(s) on the logbook, all succeeding records will be misaligned. As such, we will be unable to integrate the data with environmental/GPS data logger records. Thus, a method to recover the correspondence relationship between both records is needed to make the most of the acquired data.
Our method consists of two steps. First, we used a random forest model to calculate the probability that any combination of a logbook record and a data logger record are derived from the same haul. The differences of “latitude”, “longitude”, “heading”, “speed”, and “haul duration” between both records were used as explanatory variables. As for all possible combinations between the logbook records and data loggers, a maximum likelihood algorithm was applied to each record on the logbook. This could predict which data logger records are most likely to be integrated.
We examined the performance of the model by removing some records from the actual complete logbook records. If the missing record was once in a trip, the success rate of integration was very high. Without using “heading” as an explanatory variable, the success rate reduced drastically. The model was also applied to actual incomplete logbook records.
In Aomori Prefecture Japan, Fisherman were surveyed on their opinions regarding the construction of offshore wind farms near the Prefecture. Out of 511 fisherman that participated in the survey, 16.4% did not support offshore windfarms. 58.9% said they would support windfarms if certain stipulations were met prior to their construction. 12.3% “Support offshore windfarms without exception.” 11.5% “Not sure.” 0.8% “No answer.” The response ratio of “Unacceptable” varied depending on the area of sea and showed a relatively higher opposition ration the coast of Mutsu Bay. As a result of the survey about “Anxiety,” “Essential conditions” and “Great expectations” when accepting offshore wind farms, the responses of “Abandonment of facilities after project,” “Installation in areas that does not disturb the fishery” and “Stability of the fisheries cooperative management” had relatively high numbers.
The survey results clearly showed the most important concern was that offshore windfarms do not affect the fisheries during or after their construction is completed on the coasts of Aomori Prefecture, Japan.
The influence of properties of sandy soil i.e., diameter and saturation level were discussed from the relationship between essentially saturated zone and sampling weight of moisture with soil moisture sampler which can be easily measured. The weight of water sampled in a saturated zone was almost constant at around 6 grams for all particle sizes. The finer the particle size, the lower the saturated water level showing the same weight of water taken as in the saturated zone as essentially saturated zone. These results show that it is possible to easily estimate the essentially saturated zone and particle size by grasping the weight of water sampled and the saturation level at several points along the beach.