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97 results returned

  1. Title: Kelp Canopy: Southern California, 2012

    Contributors:

    Summary: This polygon shapefile is a thematic map representing mosaicked multi-spectral imagery targeting both exposed and submerged giant kelp beds along the Naval Air Systems Command (NAVAIR) Point Mugu Sea Range. The imagery used to create this classification was acquired at a spatial resolution of 0.3 meters using a Microsoft UltraCam-X digital camera acquiring in the red, green, blue and near-infrared bands. The image mosaic product used for the classification is a result of the resampling of the 0.3 meter data to 2 meter GSD. Surface kelp canopy and subsurface kelp classifications are seperate. The imagery was collected on October 14-16, November 13-14 and December 9-10, 2012. This dataset is complete at this time, although the user should note any omissions. The data are projected in California Teale Albers using North American Datum 1983. File reindexed to match CDFW kelp administrative kelp bed boundaries modified by changes to California Code of Regulations, Title 14, Section 165, effective April 1, 2014. This dataset is used to assess the extent of kelp resources along the Southern California coast (Point Loma to approximately 3.8 miles north of Point Conception) and includes the Channel Islands. Surface kelp canopy and subsurface kelp classifications are seperate. The data was collected and processed by Ocean Imaging under contract by the Naval Air Systems Command (NAVAIR). The user is cautioned against making direct comparisons between the various kelp surveys for the following reasons: (1)Timing of the survey is important, particularly with respect to growing season, conditions in the ocean, storms, and harvest levels preceding the dates of imagery collection. Season variability may account for differences in surveys which may not reflect a change in the bed's extent, productivity, or harvest level. (2) Statisical significance in change of area should be evaluated. To do this, a variance parameter is needed, which is obtained by repeated measurements. (3) Survey methods may not be consistent. Some method of calibration between the methods should be performed in order to insure a change of area is not due to survey instrumentation and not misinterpreted as a biological change. (4) An area where no kelp data are present may represent an area devoid of kelp, or may represent an area where kelp was not detected due to poor photo quality, missing photo coverage, or other issues with data collection and processing. Image coverage is extensive for the state, but the user is advised to consult the supplementary information for each year to determine whether imagery were acquired for an area of interest. California Department of Fish and Wildlife Marine Resources Region. (2013). Kelp Canopy: Southern California, 2012. California Department of Fish and Wildlife. Marine Resources Region. Available at: http://purl.stanford.edu/xk635rd3987. DISCLAIMER The user is cautioned against making direct comparisons between the various kelp surveys for the following reasons: (1)Timing of the survey is important, particularly with respect to growing season, conditions in the ocean, storms, and harvest levels preceding the dates of imagery collection. Season variability may account for differences in surveys which may not reflect a change in the bed's extent, productivity, or harvest level. (2) Statisical significance in change of area should be evaluated. To do this, a variance parameter is needed, which is obtained by repeated measurements. (3) Survey methods may not be consistent. Some method of calibration between the methods should be performed in order to insure a change of area is not due to survey instrumentation and not misinterpreted as a biological change. (4) An area where no kelp data are present may represent an area devoid of kelp, or may represent an area where kelp was not detected due to poor photo quality, missing photo coverage, or other issues with data collection and processing. Image coverage is extensive for the state, but the user is advised to consult the supplementary information for each year to determine whether imagery were acquired for an area of interest. Please cite the Originators in any reference to the data. NAVAIR and the California Department of Fish and Wildlife must be credited with the distribution of these data. This layer is presented in the WGS84 coordinate system for web display purposes. Downloadable data are provided in native coordinate system or projection.

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  2. Title: Kelp Canopy: Southern California, 2011

    Contributors:

    Summary: This polygon shapefile depicts the 2011 aerial kelp survey that was created from Digital Multi-Spectral Camera image files. The data was collected and processed by Ocean Imaging under contract by the Naval Air Systems Command (NAVAIR). This mosaicked multi-spectral imagery targeted giant kelp beds along the Naval Air Systems Command (NAVAIR) Point Mugu Sea Range. The area from Santa Monica Pier, Los Angeles county to Pt. Magu, Ventura county were not photographed. Some of the outer portions of kelp beds were cut off due to inadequate overlap in aerial surveys and these areas are noted in Grid Code 2. The imagery was collected on November 22 and December 07-08, 2011 from altitudes between 10,000 to 12,500 feet. Surveys were planned to coincide with periods of minimal change between high and low tides to avoid strong tidal induced currents. This dataset is complete, although the user should note any omissions. The data are projected in California Teale Albers using North American Datum 1983. File reindexed to match CDFW kelp administrative kelp bed boundaries modified by changes to California Code of Regulations, Title 14, Section 165, effective April 1, 2014. The dataset is used to assess the extent of kelp resources along the Southern California coast (Point Loma to two miles north of Gaviota Beach). The dataset was collected and created with the same camera system and processing software as the 2008 survey. Surface and subsurface kelp canopy imagery was collected under the same classification scheme. The user is cautioned to look for areas which appear truncated. The user is cautioned against making direct comparisons between the various kelp surveys for the following reasons: 1) Timing of the survey is important, particularly with respect to growing season, conditions in the ocean, storms, and harvest levels preceding the dates of survey photography. Seasonal variability may account for differences in surveys, which may not reflect a change in the bed's extent, productivity, or harvest level. 2) Statistical significance in change of area should be evaluated. To do this, a variance parameter is needed, which is obtained by repeated measurements. 3) Survey methods may not be consistent. Some method of calibration between the methods needs to be performed in order to insure a change of area is not due to survey instrumentation and not misinterpreted as a biological change. 4) An area where no kelp data are present may represent an area devoid of kelp, or may represent an area where kelp was not detected due to poor photo quality, missing photo coverage, or other issues with data collection and processing. Photo coverage is extensive for the state, but the user is advised to consult the supplementary information for each year to determine whether photographs were acquired for an area of interest. California Department of Fish and Wildlife Marine Resources Region. (2012). Kelp Canopy: Southern California, 2011. California Department of Fish and Wildlife. Marine Resources Region. Available at: http://purl.stanford.edu/pq743qn0702. Please cite the Originators in any reference to the data. NAVAIR and the California Department of Fish and Wildlife must be credited with the distribution of these data. This layer is presented in the WGS84 coordinate system for web display purposes. Downloadable data are provided in native coordinate system or projection.

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  3. Title: Kelp Canopy: California, 2009

    Contributors:

    Summary: The data for this polygon shapefile was collected and created with the same camera system and processing software as the 2008 survey. Surface and subsurface kelp canopy imagery was collected and processed with separate classification schemes. The shapefile was created from Digital Multi-Spectral Camera image files. The data was collected and processed by Ocean Imaging under contract by the Resources Legacy Fund Foundation (RLFF) for the Marine Protected Areas Monitoring Enterprise. This dataset represents the 2009 aerial kelp survey. The imagery was collected on October 01, 2009 from an altitude of 12,500 feet. Surveys were planned to coincide with periods of minimal change between high and low tides to avoid strong tidal induced currents. This coverage is complete, although the user should note any omissions. The data are projected in California Teale Albers using North American Datum 1983. File reindexed to match CDFW kelp administrative kelp bed boundaries modified by changes to California Code of Regulations, Title 14, Section 165, effective April 1, 2014. This dataset was developed for the Marine Protected Areas Monitoring Enterprise to assess the extent of kelp canopy resources along the North Central California coast (Pigeon Point to Alder Creek). California Department of Fish and Wildlife Marine Resources Region. (2010). Kelp Canopy: California, 2009. California Department of Fish and Wildlife. Marine Resources Region. Available at: http://purl.stanford.edu/zd395qv1073. Please cite the Originators in any reference to the data. For the north central data: The Resources Legacy Fund Foundation (contract), the Marine Protected Areas Monitoring Enterprise (coordination), Ocean Imaging (data collection and processing), The California Department of Fish and Game (database management). For the Santa Barbara and San Nicolas Islands data: NAVAIR (contract), Ocean Imaging (data collection and processing, The California Department of Fish and Game (database management). For the southern California mainland section: The Central and Region 9 Kelp Consortiums (contract) , MBC Applied Environmental Sciences (data collection and processing), The California Department of Fish and Game (database management). This layer is presented in the WGS84 coordinate system for web display purposes. Downloadable data are provided in native coordinate system or projection.

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  4. Title: Kelp Canopy: California, 2008

    Contributors:

    Summary: This polygon shapefile was collected and created with a different camera system and software than the 2002-2007 surveys. This difference in camera system and processing software allows the collection of both surface and subsurface kelp with separate classification schemes. The shapefile was created from Digital Multi-Spectral Camera image files and was collected and processed by Ocean Imaging under contract by the California Department of Fish and Wildlife (CDFW). The dataset represents the 2008 CDFW Survey. The Northern and Central California Surveys were flown October 06-08, 2008. The Southern California including the Channel Islands imagery was acquired October 20-23, 2008. The photographs were taken from an altitude of 12,500 feet, utilizing CDFW's Partenavia aircraft. Surveys were planned to coincide with periods of minimal change between high and low tides to avoid strong tidal induced currents. This dataset is complete, although the user should note omissions. The data are projected in California Teale Albers using North American Datum 1983. File reindexed to match CDFW administrative kelp bed boundaries modified by changes to California Code of Regulations, Title 14, Section 165, effective April 1, 2014. These data are used to assess the extent of kelp canopy resources along the California coast. California Department of Fish and Wildlife Marine Resources Region. (2009). Kelp Canopy: California, 2008. California Department of Fish and Wildlife. Marine Resources Region. Available at: http://purl.stanford.edu/jx253kn5220. This data was revised on 09-29-09. The revisions resulted in the removal of polygon overlap which increased overall kelp area 0.0008 sq. mi. The overlap involved administrative beds 211 (0.000759 sq. mi.) and 212 (0.000024 sq. mi.). In addition, the data was intersected with the administrative kelp beds. Kelp missed due to inadequate overlap: Santa Cruz Island, bed 112, small section of kelp bed missed approximately 3.77km southwest of Diablo Point; Santa Barbara County, bed 32, section of offshore kelp missed south of Canada Del Cojo; San Luis Obispo County, bed 205, small section of the inshore bed missed by Diablo Canyon and east of Lion Rock; San Luis Obispo County, bed 208, small section of offshore kelp missed 4.25km northwest of Point Estero; San Luis Obispo County, bed 210, small section of offshore kelp missed south of Adobe Creek; Monterey County, bed 216, corner of cove/bay missed from False Sur to Pt. Sur; Santa Cruz County, bed 222, partial cloud cover from Needle Rock to Terrace Point may have hidden offshore kelp; Marin County, bed 301, kelp may have been missed between Double Point; Sonoma County, bed 303, section of kelp bed missed around Fort Ross Cove; Mendocino County, bed 307, section of inshore kelp missed between Slaughterhouse Gulch and Jack Peters Gulch. The user is cautioned to look for areas which appear truncated. DISCLAIMER The user is cautioned against making direct comparisons between the various kelp surveys for the following reasons: 1) Timing of the survey is important, particularly with respect to growing season conditions in the ocean, and storms and harvest levels preceding the dates of survey photography. Seasonal variability may account for differences in surveys, which may not reflect a change in the bed's extent, productivity, or harvest level. 2) Statistical significance in change of area should be evaluated. To do this, a variance parameter is needed, which is obtained by repeated measurements. 3) Survey methods have not been/may not be consistent. Some method of calibration between the methods needs to be performed in order to insure a change of area is not due to survey instrumentation, and not misinterpreted as a biological change. 4) An area where apparently no kelp data are present may truly represent an area devoid of kelp, or may represent an area where kelp was not detected due to poor photo quality, missing photo coverage, or other issues with data collection and processing. Photo coverage is extensive for the state, but the user is advised to consult the supplementary information for each year to determine whether photographs were acquired for an area of interest. These are public data. The Department of Fish and Wildlife must be credited with the collection, analysis and distribution of these data. This layer is presented in the WGS84 coordinate system for web display purposes. Downloadable data are provided in native coordinate system or projection.

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  5. Title: Zoning Map, Mansfield, Massachusetts, 1987 (Raster Image)

    Contributors:

    Summary: This layer is a georeferenced raster image of the historic paper map entitled: Zoning map, town of Mansfield, Mass., prepared by Tibbetts Engineering Corp. ; street update by SRPEDD. It was published by Tibbetts Engineering Corp. in 1987. Scale [ca. 1:7,200]. The image inside the map neatline is georeferenced to the surface of the earth and fit to the Massachusetts State Plane Coordinate System, Mainland Zone (in Feet) (Fipszone 2001). All map collar and inset information is also available as part of the raster image, including any inset maps, profiles, statistical tables, directories, text, illustrations, index maps, legends, or other information associated with the principal map. This map shows features such as roads, railroads, drainage, cities and other human settlements, territorial boundaries, shoreline features, and more. Includes also zoning categories. This layer is part of a selection of digitally scanned and georeferenced historic maps from the Harvard Map Collection. These maps typically portray both natural and manmade features. The selection represents a range of originators, ground condition dates, scales, and map purposes.

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  6. Title: Active Subdivision Map, Marlborough, Massachusetts, 1996 (Raster Image)

    Contributors:

    Summary: This layer is a georeferenced raster image of the historic paper map entitled: Active subdivision map, city of Marlborough, Mass. It was published by the Planning Board in 1996. Scale ca. 1:12,500. The image inside the map neatline is georeferenced to the surface of the earth and fit to the Massachusetts State Plane Coordinate System, Mainland Zone (in Feet) (Fipszone 2001). All map collar and inset information is also available as part of the raster image, including any inset maps, profiles, statistical tables, directories, text, illustrations, index maps, legends, or other information associated with the principal map. This map shows features such as roads, drainage, cities and other human settlements, territorial boundaries, shoreline features, and more. Includes also extent of subdivisions. This layer is part of a selection of digitally scanned and georeferenced historic maps from the Harvard Map Collection. These maps typically portray both natural and manmade features. The selection represents a range of originators, ground condition dates, scales, and map purposes.

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  7. Title: Global GIS : Oil and gas fields

    Contributors:

    Summary: This coverage contains points that describe centerpoint locations of and primary commodity produced by oil and gas fields. A fundamental task in the assessment is to map the locations and type of production for existing oil and gas fields.

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  8. Title: Imagined San Francisco

    Contributors:

    Summary: This project traces the history of urban planning in San Francisco, placing special emphasis on unrealized schemes. Rather than using visual material simply to illustrate outcomes, Imagined San Francisco uses historical plans, maps, architectural renderings, and photographs to show what might have been. By enabling users to layer a series of urban plans, the project presents the city not only as a sequence of material changes, but also as a contingent process and a battleground for political power. Savvy institutional actors--like banks, developers, and many public officials--understood that in some cases to clearly articulate their interests would be to invite challenges. That means that textual sources like newspapers and municipal reports are limited in what they can tell researchers about the shape of political power. Urban plans, however, often speak volumes about interests and dynamics upon which textual sources remain silent. Mortgage lenders, for example, apparently thought it unwise to state that they wished to see a poor neighborhood cleared, to be replaced with a freeway onramp. Yet visual analysis of planning proposals makes that interest plain. So in the process of showing how the city might have looked, Imagined San Francisco also shows how political power actually was negotiated and exercised.

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  9. Title: [Wilkes Exploring Expedition maps, 1841]

    Contributors:

    Summary: By the U.S. Ex. Ex., Charles Wilkes, Esqr., Commander U.S. Dept. of Commerce, National Oceanic and Atmospheric Administration, National Ocean Survey. Relief shown By hachures; depths shown By soundings. Binder's title. Sheets numbered 135 to 161. 38 maps on 27 sheets; 86 x 88 cm. or smaller.

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  10. Title: Ocean Tipping Points

    Contributors:

    Summary: The Ocean Tipping Points collaborative research project seeks to understand and characterize tipping points in ocean ecosystems. This idea is not new. Many scientists before us have studied the complex dynamics of marine ecosystems, highlighting the potential for rapid, dramatic changes in ocean conditions. However, past science has done little to influence the way we manage marine ecosystems. We have an opportunity to change this, as promising new science converges with a paradigm shift toward ecosystem-based management of our coasts and oceans. Tipping points occur when small shifts in human pressures or environmental conditions bring about large, sometimes abrupt changes in a system – whether in a human society, a physical system, an ecosystem or our planet’s climate. System requirements: Geographic Information Systems (GIS) software that reads GeoTIFF format.

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  11. Title: Nitrogen Flux from Onsite Waste Disposal Systems

    Contributors:

    Summary: This raster data layer represents the nitrogen flux coming from onsite waste disposal systems (OSDS) (e.g. cesspools and septic tanks). OSDS point data was obtained from UH/DOH (Bob Whittier & El Kadi) that estimates nitrogen flux from each TMK parcel with OSDS. We converted the points to raster by summing nutrient flux values within 500 m x 500 m pixels. Then focal statistics was used to calculate the total flux within a 1.5 km radius of each oceanic cell. Units are in grams/day per km2. This layer was developed as part of a geospatial database of key anthropogenic pressures to coastal waters of the Main Hawaiian Islands for the Ocean Tipping Points project (http://oceantippingpoints.org/). Ocean tipping points occur when incremental changes in human use or environmental conditions result in large, and sometimes abrupt, impacts to marine ecosystems. The ability to predict and understand ocean tipping points can enhance ecosystem management. The goal of the Hawaii case study of the Ocean Tipping Points project was to gather, process and map spatial data on environmental and anthropogenic drivers of coral reef ecosystem states. Understanding direct anthropogenic drivers is critical for coral reef management and implementing policies to protect ecosystem services generated by coral reefs. Ocean Tipping Points Project. (2016). Nitrogen Flux from Onsite Waste Disposal Systems. Ocean Tipping Points Project. Available at: http://purl.stanford.edu/gh467sr9939. This layer is presented in the WGS84 coordinate system for web display purposes. Downloadable data are provided in native coordinate system or projection.

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  12. Title: SST Long-term Mean, 2000-2013

    Contributors:

    Summary: Sea surface temperature (SST) plays an important role in a number of ecological processes and can vary over a wide range of time scales, from daily to decadal changes. SST influences primary production, species migration patterns, and coral health. If temperatures are anomalous warm for extended periods of time, drastic changes in the surrounding ecosystem can result, including harmful effects such as coral bleaching. This layer represents the mean sea surface temperature (SST) (degrees Celsius) of weekly time series from 2000 – 2013. A continuous, 5km gap-filled weekly SST data set available from 1985 – 2013 was produced from a variety of sources. Please see Lineage Statement for more details. This layer was developed as part of a geospatial database of key anthropogenic pressures to coastal waters of the Main Hawaiian Islands for the Ocean Tipping Points project (http://oceantippingpoints.org/). Ocean tipping points occur when shifts in human use or environmental conditions result in large, and sometimes abrupt, impacts to marine ecosystems. The ability to predict and understand ocean tipping points can enhance ecosystem management, including critical coral reef management and policies to protect ecosystem services produced by coral reefs. The goal of the Ocean Tipping Points Hawaii case study was to gather, process and map spatial information on environmental and human-based drivers of coral reef ecosystem conditions. Ocean Tipping Points Project. (2016). SST Long-term Mean, 2000-2013. Ocean Tipping Points Project. Available at: http://purl.stanford.edu/sm309xd8108. http://purl.stanford.edu/xx299ky8940. Please contact the Ocean Tipping Points project in advance of applying these data sets to project work so the PI can track and communicate data uses and ensure no duplicate efforts are underway. When applying these data for publication, please reference and cite the complete journal article, Wedding et al. 2017. This layer is presented in the WGS84 coordinate system for web display purposes. Downloadable data are provided in native coordinate system or projection.

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  13. Title: Phosphorus Flux from Onsite Waste Disposal Systems

    Contributors:

    Summary: This raster data layer represents the phosphorus flux coming from onsite waste disposal systems (OSDS) (e.g. cesspools and septic tanks). OSDS point data was obtained from UH/DOH (Bob Whittier & El Kadi) that estimates phosphorus flux from each TMK parcel with OSDS. We converted the points to raster by summing nutrient flux values within 500 m x 500 m pixels. Then focal statistics was used to calculate the total flux within a 1.5 km radius of each oceanic cell. Units are in grams/day per km2. This layer was developed as part of a geospatial database of key anthropogenic pressures to coastal waters of the Main Hawaiian Islands for the Ocean Tipping Points project (http://oceantippingpoints.org/). Ocean tipping points occur when incremental changes in human use or environmental conditions result in large, and sometimes abrupt, impacts to marine ecosystems. The ability to predict and understand ocean tipping points can enhance ecosystem management. The goal of the Hawaii case study of the Ocean Tipping Points project was to gather, process and map spatial data on environmental and anthropogenic drivers of coral reef ecosystem states. Understanding direct anthropogenic drivers is critical for coral reef management and implementing policies to protect ecosystem services generated by coral reefs. Ocean Tipping Points Project. (2016). Phosphorus Flux from Onsite Waste Disposal Systems. Ocean Tipping Points Project. Available at: http://purl.stanford.edu/kw453qp4147. This layer is presented in the WGS84 coordinate system for web display purposes. Downloadable data are provided in native coordinate system or projection.

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  14. Title: Wave Power Long-term Mean, 2000-2013

    Contributors:

    Summary: Wave power is a major environmental forcing mechanism in Hawai‘i that influences a number of marine ecosystem processes including coral reef community development, structure, and persistence. By driving mixing of the upper water column, wave forcing can also play a role in nutrient availability and ocean temperature reduction during warming events. Wave forcing in Hawai’i is highly seasonal, with winter months typically experiencing far greater wave power than that experienced during the summer months.This layer represents the mean of maximum daily time series of Wave power (kW/m) from Jan 1 2000 to Dec 31 2013. Data were obtained from the International Pacific Research Center, University of Hawai‘i at Manoa SWAN model (Simulating WAves Nearshore) following Li et al., (2016).Li, N., Cheung, K.F., Stopa, J.E., Hsiao, F., Chen, Y.-L., Vega, L., and Cross, P. 2016. Thirty-four years of Hawaii wave hindcast from downscaling of climate forecast system reanalysis. Ocean Modelling 100:78-95. This layer was developed as part of a geospatial database of key anthropogenic pressures to coastal waters of the Main Hawaiian Islands for the Ocean Tipping Points project (http://oceantippingpoints.org/). Ocean tipping points occur when shifts in human use or environmental conditions result in large, and sometimes abrupt, impacts to marine ecosystems. The ability to predict and understand ocean tipping points can enhance ecosystem management, including critical coral reef management and policies to protect ecosystem services produced by coral reefs. The goal of the Ocean Tipping Points Hawaii case study was to gather, process and map spatial information on environmental and human-based drivers of coral reef ecosystem conditions. Ocean Tipping Points Project. (2016). Wave Power Long-term Mean, 2000-2013. Ocean Tipping Points Project. Available at: http://purl.stanford.edu/sm309xd8108. http://purl.stanford.edu/fy882dd0730. Please contact the Ocean Tipping Points project in advance of applying these data sets to project work so the PI can track and communicate data uses and ensure no duplicate efforts are underway. When applying these data for publication, please reference and cite the complete journal article, Wedding et al. 2017. This layer is presented in the WGS84 coordinate system for web display purposes. Downloadable data are provided in native coordinate system or projection.

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  15. Title: Wave Power Maximum Monthly Climatological Mean, 1979-2013

    Contributors:

    Summary: Wave power is a major environmental forcing mechanism in Hawai‘i that influences a number of marine ecosystem processes including coral reef community development, structure, and persistence. By driving mixing of the upper water column, wave forcing can also play a role in nutrient availability and ocean temperature reduction during warming events. Wave forcing in Hawai’i is highly seasonal, with winter months typically experiencing far greater wave power than that experienced during the summer months.This layer represents the maximum monthly climatological mean of Wave power (kW/m) from 1979 – 2013. Data were obtained from the International Pacific Research Center, University of Hawai‘i at Manoa SWAN model (Simulating WAves Nearshore) following Li et al., (2016).Li, N., Cheung, K.F., Stopa, J.E., Hsiao, F., Chen, Y.-L., Vega, L., and Cross, P. 2016. Thirty-four years of Hawaii wave hindcast from downscaling of climate forecast system reanalysis. Ocean Modelling 100:78-95. This layer was developed as part of a geospatial database of key anthropogenic pressures to coastal waters of the Main Hawaiian Islands for the Ocean Tipping Points project (http://oceantippingpoints.org/). Ocean tipping points occur when shifts in human use or environmental conditions result in large, and sometimes abrupt, impacts to marine ecosystems. The ability to predict and understand ocean tipping points can enhance ecosystem management, including critical coral reef management and policies to protect ecosystem services produced by coral reefs. The goal of the Ocean Tipping Points Hawaii case study was to gather, process and map spatial information on environmental and human-based drivers of coral reef ecosystem conditions. Ocean Tipping Points Project. (2016). Wave Power Maximum Monthly Climatological Mean, 1979-2013. Ocean Tipping Points Project. Available at: http://purl.stanford.edu/sm309xd8108. http://purl.stanford.edu/cr087nm0398. Please contact the Ocean Tipping Points project in advance of applying these data sets to project work so the PI can track and communicate data uses and ensure no duplicate efforts are underway. When applying these data for publication, please reference and cite the complete journal article, Wedding et al. 2017. This layer is presented in the WGS84 coordinate system for web display purposes. Downloadable data are provided in native coordinate system or projection.

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  16. Title: SST Average Annual Maximum Anomaly, 2000-2013

    Contributors:

    Summary: Sea surface temperature (SST) plays an important role in a number of ecological processes and can vary over a wide range of time scales, from daily to decadal changes. SST influences primary production, species migration patterns, and coral health. If temperatures are anomalous warm for extended periods of time, drastic changes in the surrounding ecosystem can result, including harmful effects such as coral bleaching. This layer represents the annual of the maximum annual average anomaly of sea surface temperature (SST) (degrees Celsius) from 2000 – 2013.A continuous, 5km gap-filled weekly SST data set available from 1985 – 2013 was produced from a variety of sources. Please see Lineage Statement for more details. This layer was developed as part of a geospatial database of key anthropogenic pressures to coastal waters of the Main Hawaiian Islands for the Ocean Tipping Points project (http://oceantippingpoints.org/). Ocean tipping points occur when shifts in human use or environmental conditions result in large, and sometimes abrupt, impacts to marine ecosystems. The ability to predict and understand ocean tipping points can enhance ecosystem management, including critical coral reef management and policies to protect ecosystem services produced by coral reefs. The goal of the Ocean Tipping Points Hawaii case study was to gather, process and map spatial information on environmental and human-based drivers of coral reef ecosystem conditions. Ocean Tipping Points Project. (2016). SST Average Annual Maximum Anomaly, 2000-2013. Ocean Tipping Points Project. Available at: http://purl.stanford.edu/sm309xd8108. http://purl.stanford.edu/vj876pn6671. Please contact the Ocean Tipping Points project in advance of applying these data sets to project work so the PI can track and communicate data uses and ensure no duplicate efforts are underway. When applying these data for publication, please reference and cite the complete journal article, Wedding et al. 2017. This layer is presented in the WGS84 coordinate system for web display purposes. Downloadable data are provided in native coordinate system or projection.

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  17. Title: Observed Presence of Alien and Invasive Algae, 2002

    Contributors:

    Summary: This raster data layer represents the presence of alien and invasive algal species within 1 km of an observation. Original data is from Jen Smith, based on MHI surveys in 2002, and invasive species data queried from the FERL biological survey database which is synthesized from NOAA, DAR, CRAMP, TNC, and other surveys (Smith et. al 2002; Hawaii Fish and Benthic Biological Synthesis Database). This data should be considered presence only. Areas with no presence may be due to lack of survey data, surveys that did not identify algae to the species level, or observed absence. Raster values of 1 represent areas within 1 km of positive invasive algae observations while values of 0 represent the remaining area. The cell size is 500 m and the AOI is from the shoreline of the MHI extending 5 km offshore and 1 km inshore. This layer was developed as part of a geospatial database of key anthropogenic pressures to coastal waters of the Main Hawaiian Islands for the Ocean Tipping Points project (http://oceantippingpoints.org/). Ocean tipping points occur when incremental changes in human use or environmental conditions result in large, and sometimes abrupt, impacts to marine ecosystems. The ability to predict and understand ocean tipping points can enhance ecosystem management. The goal of the Hawaii case study of the Ocean Tipping Points project was to gather, process and map spatial data on environmental and anthropogenic drivers of coral reef ecosystem states. Understanding direct anthropogenic drivers is critical for coral reef management and implementing policies to protect ecosystem services generated by coral reefs. Ocean Tipping Points Project. (2016). Observed Presence of Alien and Invasive Algae, 2002. Ocean Tipping Points Project. Available at: http://purl.stanford.edu/vj230dq3177. This layer is presented in the WGS84 coordinate system for web display purposes. Downloadable data are provided in native coordinate system or projection.

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  18. Title: Sediment Export to Nearshore Waters

    Contributors:

    Summary: This raster data layer represents sediment plumes originating from stream mouths and coastal pour points. The Integrated Valuation of Ecosystem Services and Tradeoffs (InVEST) model for sediment retention was modified for the Main Hawaiian Islands, parameterized, and run for each of Main Hawaiian Islands (Falinski et al. 2015, in prep). Results from this model were aggregated into larger drainage areas that flow to single coastal pour points. From these points sediment was dispersed offshore using the Kernel Density tool in ArcGIS with a 1.5 km search radius. The resulting raster depicts simplistic sediment plumes with units in tons of sediment per year, per hectare. This layer was developed as part of a geospatial database of key anthropogenic pressures to coastal waters of the Main Hawaiian Islands for the Ocean Tipping Points project (http://oceantippingpoints.org/). Ocean tipping points occur when incremental changes in human use or environmental conditions result in large, and sometimes abrupt, impacts to marine ecosystems. The ability to predict and understand ocean tipping points can enhance ecosystem management. The goal of the Hawaii case study of the Ocean Tipping Points project was to gather, process and map spatial data on environmental and anthropogenic drivers of coral reef ecosystem states. Understanding direct anthropogenic drivers is critical for coral reef management and implementing policies to protect ecosystem services generated by coral reefs. Ocean Tipping Points Project. (2016). Sediment Export to Nearshore Waters . Ocean Tipping Points Project. Available at: http://purl.stanford.edu/sp963zr9950. This layer is presented in the WGS84 coordinate system for web display purposes. Downloadable data are provided in native coordinate system or projection.

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  19. Title: Non-commercial Fishing (Estimated Average Annual Catch of Reef Fish), 2004-2013

    Contributors:

    Summary: Nearshore fisheries in the Main Hawaiian Islands encompass a diverse group of fishers using a wide array of gears and targeting many different species. Communities in Hawai’i often rely on these fisheries for economic, social, and cultural services. However, the stress from overfishing can cause ecosystem degradation and long-term economic loss. This layer represents the average annual catch of reef fish by non-commercial fishing methods. Average annual catch at the island scale, from 2004 – 2013, was estimated from Marine Recreational Information Program (MRIP) combined fisher intercept and phone survey data (McCoy, 2015; McCoy et al., in prep). These Island scale estimates were spatially distributed offshore using distance to boat harbors and launch ramps, while accounting for marine managed areas, and restricted access areas (de facto MPAs e.g. Military Danger Zones).McCoy K. 2015. Estimating nearshore fisheries catch for the main Hawaiian Islands. Thesis. University of Hawai‘i at Manoa.McCoy, K., Friedlander, A., Kittinger, J., Ma, H., Teneva, L., Williams, I.D. In prep. Estimating nearshore fisheries catch for the main Hawaiian islands. PLoS One. This layer was developed as part of a geospatial database of key anthropogenic pressures to coastal waters of the Main Hawaiian Islands for the Ocean Tipping Points project (http://oceantippingpoints.org/). Ocean tipping points occur when shifts in human use or environmental conditions result in large, and sometimes abrupt, impacts to marine ecosystems. The ability to predict and understand ocean tipping points can enhance ecosystem management, including critical coral reef management and policies to protect ecosystem services produced by coral reefs. The goal of the Ocean Tipping Points Hawaii case study was to gather, process and map spatial information on environmental and human-based drivers of coral reef ecosystem conditions. Ocean Tipping Points Project. (2016). Non-commercial Fishing (Estimated Average Annual Catch of Reef Fish), 2004-2013. Ocean Tipping Points Project. Available at: http://purl.stanford.edu/df008vq3760. Please contact the Ocean Tipping Points project in advance of applying these data sets to project work so the PI can track and communicate data uses and ensure no duplicate efforts are underway. When applying these data for publication, please reference and cite the complete journal article, Wedding et al. 2017. This layer is presented in the WGS84 coordinate system for web display purposes. Downloadable data are provided in native coordinate system or projection.

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  20. Title: Non-commercial Shore-based Line Fishing (Estimated Average Annual Catch of Reef Fish), 2004-2013

    Contributors:

    Summary: Nearshore fisheries in the Main Hawaiian Islands encompass a diverse group of fishers using a wide array of gears and targeting many different species. Communities in Hawai’i often rely on these fisheries for economic, social, and cultural services. However, the stress from overfishing can cause ecosystem degradation and long-term economic loss. This layer represents the average annual catch of reef fish by non-commercial shore-based line fishing methods. Average annual catch at the island scale, from 2004 – 2013, was estimated from Marine Recreational Information Program (MRIP) combined fisher intercept and phone survey data (McCoy, 2015; McCoy et al., in prep). These Island scale estimates were spatially distributed offshore by combing two different proxies for shoreline accessibility (terrain steepness, and presence of roads), while accounting for marine managed areas, and restricted access areas (de facto MPAs e.g. Military Danger Zones). McCoy K. 2015. Estimating nearshore fisheries catch for the main Hawaiian Islands. Thesis. University of Hawai‘i at Manoa.McCoy, K., Friedlander, A., Kittinger, J., Ma, H., Teneva, L., Williams, I.D. In prep. Estimating nearshore fisheries catch for the main Hawaiian islands. PLoS One. This layer was developed as part of a geospatial database of key anthropogenic pressures to coastal waters of the Main Hawaiian Islands for the Ocean Tipping Points project (http://oceantippingpoints.org/). Ocean tipping points occur when shifts in human use or environmental conditions result in large, and sometimes abrupt, impacts to marine ecosystems. The ability to predict and understand ocean tipping points can enhance ecosystem management, including critical coral reef management and policies to protect ecosystem services produced by coral reefs. The goal of the Ocean Tipping Points Hawaii case study was to gather, process and map spatial information on environmental and human-based drivers of coral reef ecosystem conditions. Ocean Tipping Points Project. (2016). Non-commercial Shore-based Line Fishing (Estimated Average Annual Catch of Reef Fish), 2004-2013. Ocean Tipping Points Project. Available at: http://purl.stanford.edu/mm765rq7246. Please contact the Ocean Tipping Points project in advance of applying these data sets to project work so the PI can track and communicate data uses and ensure no duplicate efforts are underway. When applying these data for publication, please reference and cite the complete journal article, Wedding et al. 2017. This layer is presented in the WGS84 coordinate system for web display purposes. Downloadable data are provided in native coordinate system or projection.

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