ArcGIS REST Services Directory Login | Get Token

Layer: grndfsh_squid_adfa (ID: 10)

Name: grndfsh_squid_adfa

Display Field:

Type: Raster Layer

Geometry Type: null

Description: The New York Department of State (NYDOS) modeled the seasonal abundance groundfish species from the NOAA Northeast Fisheries Science Center’s (NEFSC) bottom trawl survey program as a function of environmental variables to support the State's offshore planning efforts. A description of the model inputs and modeling process are described below. FISH DATA. NEFSC has been conducting biannual fisheries-independent bottom trawl surveys from 1963 to the present. The starting locations (“station”) of each tow were assigned based on a stratified random sampling design, and strata were defined in 1963 based on water depth, latitude, and historical fishing patterns. The number of stations allotted to a stratum is proportional to its area. Each tow proceeds at approximately 3.5 knots for 30 minutes, using #36 Yankee (or similar) gear. Once onboard, fish are weighed, measured, sexed, and identified to species. Stone Environmental, Inc. obtained trawl stations and catch records from NEFSC from 1975 - 2009. They calculated species abundance (number of individuals) for each station and summarized it by five-year intervals, season (spring/fall), and life state (juvenile/adult). Life stage categories were defined based on published estimates of length at maturity. For more details, please see the Stone Environmental Report prepared for NYDOS (2010).ENVIRONMENTAL DATA. The NOAA National Center for Coastal Monitoring and Assessment (CCMA) provided environmental predictor variables for the New York Bight region in raster (GeoTIFF) format. These predictor variables included: bottom depth, bottom slope, distance from continental shelf, distance from shore, sea surface temperature, water column stratification, sea surface turbidity, surface chlorophyll a concentration, zooplankton biomass, bottom slope of slope, and mean bottom sediment grain size. Dynamic oceanographic predictor variables (e.g., sea surface temperature and zooplankton biomass) were compiled from existing information and summarized as long-term seasonal averages. Maps of bathymetry and bottom sediments were derived using geostatistical interpolation of existing point data. For more details about the environmental predictor variables, please see the NOAA NCCOS report prepared for NYDOS (2010).MODELING. DOS modeled abundance as a function of 11 environmental predictor variables based on previous studies of environmental correlates of fish abundance. DOS implemented models as zero-inflated GLMs. The zero-inflation component was necessary as the data exhibited a preponderance of absences likely arising from both unsuitable environmental conditions and the difficulty of catching the fish when they were in fact present. Because model residuals displayed spatial autocorrelation, an additional, geostatistical model was necessary to capture this pattern. This hybrid approach is known as regression-Kriging. To avoid extrapolation beyond the range of the data, maps were clipped to the spatial extent of the NEFSC surveys. For more details, please see the New York Atlantic Ocean Study prepared by NYDOS (2013).

Definition Expression: N/A

Copyright Text: NOAA Northeast Fisheries Science Center, NOAA National Center for Coastal Monitoring and Assessment, Stone Environmental, Inc

Default Visibility: false

MaxRecordCount: 0

Supported Query Formats: JSON, AMF

Min Scale: 0

Max Scale: 0

Supports Advanced Queries: false

Supports Statistics: false

Has Labels: false

Can Modify Layer: false

Can Scale Symbols: false

Use Standardized Queries: true

Drawing Info:
HasZ: false

HasM: false

Has Attachments: false

HTML Popup Type: esriServerHTMLPopupTypeNone

Type ID Field: null

Fields: None

Supported Operations:   Query   Generate Renderer   Return Updates