24 resultados para classification task


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This is the Brown trout habitat assessment on the River Bela catchment produced by the Environment Agency North West in 1997. The Environment Agency (EA) and its predecessor the National Rivers Authority undertook strategic fish stock assessments in 1992 and 1995 on the River Bela catchment. These surveys found low numbers of brown trout {Salmo trutta) at some sites. Following this, habitat evaluation assessments were undertaken on the eleven poorest sites Factors probably responsible for declining trout populations on the three main tributaries of the Bela catchment include: Overgrazing by farm stock; Lack of suitable cover for parr; the absence of suitable spawning areas; existing potential of certain areas within the catchment not being utilised, due to poor dispersal. Habitat Improvement Schemes (H.I.S) are discussed and prioritised.

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Rockfishes (Sebastes spp.) tend to aggregate near rocky, cobble, or generally rugged areas that are difficult to survey with bottom trawls, and evidence indicates that assemblages of rockfish species may differ between areas accessible to trawling and those areas that are not. Consequently, it is important to determine grounds that are trawlable or untrawlable so that the areas where trawl survey results should be applied are accurately identified. To this end, we used multibeam echosounder data to generate metrics that describe the seafloor: backscatter strength at normal and oblique incidence angles, the variation of the angle-dependent backscatter strength within 10° of normal incidence, the scintillation of the acoustic intensity scattered from the seafloor, and the seafloor rugosity. We used these metrics to develop a binary classification scheme to estimate where the seafloor is expected to be trawlable. The multibeam echosounder data were verified through analyses of video and still images collected with a stereo drop camera and a remotely operated vehicle in a study at Snakehead Bank, ~100 km south of Kodiak Island in the Gulf of Alaska. Comparisons of different combinations of metrics derived from the multibeam data indicated that the oblique-incidence backscatter strength was the most accurate estimator of trawlability at Snakehead Bank and that the addition of other metrics provided only marginal improvements. If successful on a wider scale in the Gulf of Alaska, this acoustic remote-sensing technique, or a similar one, could help improve the accuracy of rockfish stock assessments.

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The Ecological Society of America and NOAA's Offices of Habitat Conservation and Protected Resources sponsored a workshop to develop a national marine and estuarine ecosystem classification system. Among the 22 people involved were scientists who had developed various regional classification systems and managers from NOAA and other federal agencies who might ultimately use this system for conservation and management. The objectives were to: (1) review existing global and regional classification systems; (2) develop the framework of a national classification system; and (3) propose a plan to expand the framework into a comprehensive classification system. Although there has been progress in the development of marine classifications in recent years, these have been either regionally focused (e.g., Pacific islands) or restricted to specific habitats (e.g., wetlands; deep seafloor). Participants in the workshop looked for commonalties across existing classification systems and tried to link these using broad scale factors important to ecosystem structure and function.

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This report argues for greatly increased resources in terms of data collection facilities and staff to collect, process, and analyze the data, and to communicate the results, in order for NMFS to fulfill its mandate to conserve and manage marine resources. In fact, the authors of this report had great difficulty defining the "ideal" situation to which fisheries stock assessments and management should aspire. One of the primary objectives of fisheries management is to develop sustainable harvest policies that minimize the risks of overfishing both target species and associated species. This can be achieved in a wide spectrum of ways, ranging between the following two extremes. The first is to implement only simple management measures with correspondingly simple assessment demands, which will usually mean setting fishing mortality targets at relatively low levels in order to reduce the risk of unknowingly overfishing or driving ecosystems towards undesirable system states. The second is to expand existing data collection and analysis programs to provide an adequate knowledge base that can support higher fishing mortality targets while still ensuring low risk to target and associated species and ecosystems. However, defining "adequate" is difficult, especially when scientists have not even identified all marine species, and information on catches, abundances, and life histories of many target species, and most associated species, is sparse. Increasing calls from the public, stakeholders, and the scientific community to implement ecosystem-based stock assessment and management make it even more difficult to define "adequate," especially when "ecosystem-based management" is itself not well-defined. In attempting to describe the data collection and assessment needs for the latter, the authors took a pragmatic approach, rather than trying to estimate the resources required to develop a knowledge base about the fine-scale detailed distributions, abundances, and associations of all marine species. Thus, the specified resource requirements will not meet the expectations of some stakeholders. In addition, the Stock Assessment Improvement Plan is designed to be complementary to other related plans, and therefore does not duplicate the resource requirements detailed in those plans, except as otherwise noted.

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We have applied a number of objective statistical techniques to define homogeneous climatic regions for the Pacific Ocean, using COADS (Woodruff et al 1987) monthly sea surface temperature (SST) for 1950-1989 as the key variable. The basic data comprised all global 4°x4° latitude/longitude boxes with enough data available to yield reliable long-term means of monthly mean SST. An R-mode principal components analysis of these data, following a technique first used by Stidd (1967), yields information about harmonics of the annual cycles of SST. We used the spatial coefficients (one for each 4-degree box and eigenvector) as input to a K-means cluster analysis to classify the gridbox SST data into 34 global regions, in which 20 comprise the Pacific and Indian oceans. Seasonal time series were then produced for each of these regions. For comparison purposes, the variance spectrum of each regional anomaly time series was calculated. Most of the significant spectral peaks occur near the biennial (2.1-2.2 years) and ENSO (~3-6 years) time scales in the tropical regions. Decadal scale fluctuations are important in the mid-latitude ocean regions.

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The National Oceanic and Atmospheric Administration (NOAA) National Ocean Service (NOS) initiated a coral reef research program in 1999 to map, assess, inventory, and monitor U.S. coral reef ecosystems (Monaco et al. 2001). These activities were implemented in response to requirements outlined in the Mapping Implementation Plan developed by the Mapping and Information Synthesis Working Group (MISWG) of the Coral Reef Task Force (CRTF) (MISWG 1999). As part of the MISWG of the CRTF, NOS' Biogeography Branch has been charged with the development and implementation of a plan to produce comprehensive digital coral-reef ecosystem maps for all U.S. States, Territories, and Commonwealths within five to seven years. Joint activities between Federal agencies are particularly important to map, research, monitor, manage, and restore coral reef ecosystems. In response to the Executive Order 13089 and the Coral Reef Conservation Act of 2000, NOS is conducting research to digitally map biotic resources and coordinate a long-term monitoring program that can detect and predict change in U.S. coral reefs, and their associated habitats and biological communities. Most U.S. coral reef resources have not been digitally mapped at a scale or resolution sufficient for assessment, monitoring, and/or research to support resource management. Thus, a large portion of NOS' coral reef research activities has focused on mapping of U.S. coral reef ecosystems. The map products will provide the fundamental spatial organizing framework to implement and integrate research programs and provide the capability to effectively communicate information and results to coral reef ecosystem managers. Although the NOS coral program is relatively young, it has had tremendous success in advancing towards the goal to protect, conserve, and enhance the health of U.S. coral reef ecosystems. One objective of the program was to create benthic habitat maps to support coral reef research to enable development of products that support management needs and questions. Therefore this product was developed in collaboration with many U.S. Pacific Territory partners. An initial step in producing benthic habitat maps was the development of a habitat classification scheme. The purpose of this document is to outline the benthic habitat classification scheme and protocols used to map American Samoa, Guam and the Commonwealth of the Northern Mariana Islands. Thirty-two distinct benthic habitat types (i.e., four major and 14 detailed geomorphological structure classes; eight major and 18 detailed biological cover types) within eleven zones were mapped directly into a geographic information system (GIS) using visual interpretation of orthorectified IKONOS satellite imagery. Benthic features were mapped that covered an area of 263 square kilometers. In all, 281 square kilometers of unconsolidated sediment, 122 square kilometers of submerged vegetation, and 82.3 square kilometers of coral reef and colonized hardbottom were mapped.

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A brief description is given of a program to carry out analysis of variance two-way classification on MICRO 2200, for use in fishery data processing.