867 resultados para KX observer
Resumo:
In February 2006, an Alternative Platform Observer Program (APP) was implemented in North Carolina (NC) to observe commercial gillnet trips by small vessels [<24 ft (7.2 m)] in nearshore waters out to three nm (5.6 km). Efforts began with outreach to the fishing industry while simultaneously gathering information to be incorporated in a Database of Fishermen. From 30 March 2006 through 31 March 2007, 36 trips were observed. Observed trips of the NC nearshore gillnet fishery targeted seven species: kingfish (Menticirrhus spp.), Spanish mackerel (Scomberomorus maculatus), spiny dogfish (Squalus acanthias), spot (Leiostomus xanthurus), spotted seatrout (Cynoscion nebulosus), striped bass (Morone saxatilis), and weakfish (Cynoscion regalis). Of the 36 trips, 20 (55.6%) were with vessels that were new to the Northeast Fisheries Observer Program (NEFOP), having never carried an observer. Based on the landings data for small vessels from North Carolina Division of Marine Fisheries (NCDMF), the APP has achieved 10.1% coverage by number of trips and 4.0% by pounds landed. No incidental takes of bottlenose dolphins were observed by the APP, although bottlenose dolphins were sighted during 19 (52.8%) observed trips. The APP has drastically increased the number of observed trips of small vessels in the nearshore waters of NC. When combined with trips observed by NEFOP (n=205), the APP resulted in a 15.6% increase in the number of observed gillnet trips. (PDF contains 34 pages)
Resumo:
This paper presents a vaccination strategy for fighting against the propagation of epidemic diseases. The disease propagation is described by an SEIR (susceptible plus infected plus infectious plus removed populations) epidemic model. The model takes into account the total population amounts as a refrain for the illness transmission since its increase makes the contacts among susceptible and infected more difficult. The vaccination strategy is based on a continuous-time nonlinear control law synthesised via an exact feedback input-output linearization approach. An observer is incorporated into the control scheme to provide online estimates for the susceptible and infected populations in the case when their values are not available from online measurement but they are necessary to implement the control law. The vaccination control is generated based on the information provided by the observer. The control objective is to asymptotically eradicate the infection from the population so that the removed-by-immunity population asymptotically tracks the whole one without precise knowledge of the partial populations. The model positivity, the eradication of the infection under feedback vaccination laws and the stability properties as well as the asymptotic convergence of the estimation errors to zero as time tends to infinity are investigated.
Resumo:
Estimating the abundance of cetaceans from aerial survey data requires careful attention to survey design and analysis. Once an aerial observer perceives a marine mammal or group of marine mammals, he or she has only a few seconds to identify and enumerate the individuals sighted, as well as to determine the distance to the sighting and record this information. In line-transect survey analyses, it is assumed that the observer has correctly identified and enumerated the group or individual. We describe methods used to test this assumption and how survey data should be adjusted to account for observer errors. Harbor porpoises (Phocoena phocoena) were censused during aerial surveys in the summer of 1997 in Southeast Alaska (9844 km survey effort), in the summer of 1998 in the Gulf of Alaska (10,127 km), and in the summer of 1999 in the Bering Sea (7849 km). Sightings of harbor porpoise during a beluga whale (Phocoena phocoena) survey in 1998 (1355 km) provided data on harbor porpoise abundance in Cook Inlet for the Gulf of Alaska stock. Sightings by primary observers at side windows were compared to an independent observer at a belly window to estimate the probability of misidentification, underestimation of group size, and the probability that porpoise on the surface at the trackline were missed (perception bias, g(0)). There were 129, 96, and 201 sightings of harbor porpoises in the three stock areas, respectively. Both g(0) and effective strip width (the realized width of the survey track) depended on survey year, and g(0) also depended on the visibility reported by observers. Harbor porpoise abundance in 1997–99 was estimated at 11,146 animals for the Southeast Alaska stock, 31,046 animals for the Gulf of Alaska stock, and 48,515 animals for the Bering Sea stock.
Resumo:
We analyzed skate catch data collected by observers in the North Pacific Groundfish Observer Program (NPGOP) from 1998 through 2008 to document recent changes in the identification of skates by observers and to examine the species composition of observed skate catch in Alaska’s groundfish fisheries as well as recent trends in skate retention by commercial fishermen. Historically, almost all skate bycatch has been reported by NPGOP observers as “skate unidentified.” However, since 2004 observers have been trained to identify skates to the genus and species level. In 2008 over 95% of all skates were identified at least to the genus level, and over 50% were identified to species. The most common species of skates identified by observers in groundfish fisheries are Bathyraja parmifera (Alaska skate), Raja binoculata (big skate), and Bathyraja aleutica (Aleutian skate). Species composition of reported skate catch generally reflects recent survey-derived biomass estimates, with B. parmifera dominating the catches in the Bering Sea and, to a lesser extent, in the Aleutian Islands region, and species of the genus Raja dominating catches in the Gulf of Alaska. A relatively high percentage of the skate catch on longline vessels is still reported at the family or genus level because of difficulties in the identification of skates not brought onboard the vessel. For the larger skate species, the proportion retained for processing has increased in recent years as the market price for skate product has increased. Although observed skate catch does not give a complete account of skate bycatch in the fisheries of the region, observer data provide critical information for the appropriate management of skate populations in Alaska.
Resumo:
Tagging experiments are a useful tool in fisheries for estimating mortality rates and abundance of fish. Unfortunately, nonreporting of recovered tags is a common problem in commercial fisheries which, if unaccounted for, can render these estimates meaningless. Observers are often employed to monitor a portion of the catches as a means of estimating reporting rates. In our study, observer data were incorporated into an integrated model for multiyear tagging and catch data to provide joint estimates of mortality rates (natural and f ishing), abundance, and reporting rates. Simulations were used to explore model performance under a range of scenarios (e.g., different parameter values, parameter constraints, and numbers of release and recapture years). Overall, results indicated that all parameters can be estimated with reasonable accuracy, but that fishing mortality, reporting rates, and abundance can be estimated with much higher precision than natural mortality. An example of how the model can be applied to provide guidance on experimental design for a large-scale tagging study is presented. Such guidance can contribute to the successful and cost-effective management of tagging programs for commercial fisheries.
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This paper applies Micken's discretization method to obtain a discrete-time SEIR epidemic model. The positivity of the model along with the existence and stability of equilibrium points is discussed for the discrete-time case. Afterwards, the design of a state observer for this discrete-time SEIR epidemic model is tackled. The analysis of the model along with the observer design is faced in an implicit way instead of obtaining first an explicit formulation of the system which is the novelty of the presented approach. Moreover, some sufficient conditions to ensure the asymptotic stability of the observer are provided in terms of a matrix inequality that can be cast in the form of a LMI. The feasibility of the matrix inequality is proved, while some simulation examples show the operation and usefulness of the observer.
Resumo:
In July 2006, a mandatory observer program was implemented to characterize the commercial reef fish fishery operating in the U.S. Gulf of Mexico. The primary gear types assessed included bottom longline and vertical line (bandit and handline). A total of 73,205 fish (183 taxa) were observed in the longline fishery. Most (66%) were red grouper, Epinephelus morio, and yellowedge grouper, E. flavolimbatus. In the vertical line fishery, 89,015 fish (178 taxa) were observed of which most (60%) were red snapper, Lutjanus campechanus, and vermilion snapper, Rhomboplites aurorubens. Based on surface observations of discarded under-sized target and unwanted species, the majority of fish were released alive; minimum assumed mortality was 23% for the vertical line and 24% for the bottom longline fishery. Of the individuals released alive in the longline fishery, 42% had visual signs of barotrauma stress (air bladder expansion/and or eyes protruding). In the vertical line fishery, 35% of the fish were released in a stressed state. Red grouper and red snapper size composition by depth and gear type were determined. Catch-per-unit-effort for dominant species in both fisheries, illustrated spatial differences in distribution between the eastern and western Gulf. Hot Spot Analyses for red grouper and red snapper identified areas with significant clustering of high or low CPUE values.
Resumo:
Belugas, Delphinapterus leucas, groups were videotaped concurrent to observer counts during annual NMFS aerial surveys of Cook Inlet, Alaska, from 1994 to 2000. The videotapes provided permanent records of whale groups that could be examined and compared to group size estimates ade by aerial observers.Examination of the video recordings resulted in 275 counts of 79 whale groups. The McLaren formula was used to account for whales missed while they were underwater (average correction factor 2.03; SD=0.64). A correction for whales missed due to video resolution was developed by using a second, paired video camera that magnified images relative to the standard video. This analysis showed that some whales were missed either because their image size fell below the resolution of hte standard video recording or because two whales surfaced so close to each other that their images appeared to be one large whale. The correction method that resulted depended on knowing the average whale image size in the videotapes. Image sizes were measured for 2,775 whales from 275 different passes over whale groups. Corrected group sizes were calcualted as the product of the original count from video, the correction factor for whales missed underwater, and the correction factor for whales missed due to video resolution (averaged 1.17; SD=0.06). A regression formula was developed to estimate group sizes from aerial observer counts; independent variables were the aerial counts and an interaction term relative to encounter rate (whales per second during the counting of a group), which were regressed against the respective group sizes as calculated from the videotapes. Significant effects of encounter rate, either positive or negative, were found for several observers. This formula was used to estimate group size when video was not available. The estimated group sizes were used in the annual abundance estimates.