An ArcGIS shapefile layer showing the extent of all extant and relic Adelie penguin (Pygoscelis adeliae) colonies at Whitney Point, Windmill Islands, February 2006. The field 'Status' describes each polygon as extant, relic or maximum. Extant refers to the area used by breeding birds in the summer 2005/06. Maximum refers to the historic maximal extent of the colony. Relic refers to any colony which was not occupied by any breeding pairs during 2005/06.

Positional accuracy is approx. 1-2 m, after accounting for dGPS errors and errors in identification of the boundaries of colonies. Mapping was conducted after the end of the breeding season, so boundaries were identified as the extent of nest pebbles/fresh faeces, and it was considered that they could be reliably identified to within 0.5m.

Data were acquired using a Trimble Pro XH differential GPS. This work was completed as part of ASAC project 1219 (ASAC_1219).

Also for this project, three aerial photographs of Whitney point showing the adelie penguin colonies and taken on 17 December 1990 were georeferenced.

These aerial photographs are film ANTC1219 run 54 frames 21 to 23.

Work on this project also utilised a Digital Elevation Model (DEM) created for Shirley Island. See the metadata record, 'A digital elevation model (DEM) and orthophoto of the Whitney Point area of the Windmill Islands, Antarctica' for more information (linked below).

Since the 2005/06 summer was a low-ice year the opportunity was also taken to survey with differential GPS a section of coastline about 230 metres long east of Whitney Point on Clark Peninsula. This section of coastline was ice free and accessible. The data was collected with differential GPS on 10 February 2006.

The Tufted Puffin (Fratercula cirrhata) is a medium-large pelagic seabird and member of the Auk family. The distribution of the Tufted Puffin is widespread in the North Pacific Ocean and populations have generally declined throughout the southern portion of their range from British Columbia to northern California. The U.S. Fish and Wildlife Service (USFWS) conducted a burrow-nesting seabird survey of the Oregon coast in 2008 and documented an order of magnitude decline in the puffin population since the previous survey in 1988. During summer 2021, USFWS conducted an Oregon coast wide survey of the Tufted Puffin during the chick rearing period from July 14 – August 25 to assess and document the current breeding population. A total of 62 historical colonies were surveyed, 16 active colonies were documented, and no new colonies were detected. The current Tufted Puffin estimated breeding population of Oregon is 519 individuals. The breeding population remains low but stable compared to previous coastwide surveys.

Layered GeoPDF 7.5 Minute Quadrangle Map. Layers of geospatial data include orthoimagery, roads, grids, geographic names, elevation contours, hydrography, and other selected map features.

Layered GeoPDF 7.5 Minute Quadrangle Map. Layers of geospatial data include orthoimagery, roads, grids, geographic names, elevation contours, hydrography, and other selected map features.

This archive contains indicative distribution maps and profiles for MT2.2 Large seabird and pinniped colonies, a ecosystem functional group (EFG, level 3) of the IUCN Global Ecosystem Typology (v2.1). Please refer to Keith et al. (2020) and Keith et al. (2022) for details.

The descriptive profiles provide brief summaries of key ecological traits and processes, maps are indicative of global distribution patterns, and are not intended to represent fine-scale patterns. The maps show areas of the world containing major (value of 1, coloured red) or minor occurrences (value of 2, coloured yellow) of each ecosystem functional group. Minor occurrences are areas where an ecosystem functional group is scattered in patches within matrices of other ecosystem functional groups or where they occur in substantial areas, but only within a segment of a larger region. Given bounds of resolution and accuracy of source data, the maps should be used to query which EFG are likely to occur within areas, rather than which occur at particular point locations. Detailed methods and references for the maps are included in the profile (xml format).

This historic paper map provides an historical perspective of the cultural and physical landscape during this time period. The wide range of information provided on these maps make them useful in the study of historic geography. As this map has been georeferenced, it also can be used as a background layer in conjunction with other GIS data.

Compilation of Wading Bird Colonies data reported by multiple agencies. Active colonies with 50 or more nests are shown in the Wading Bird map in the annual South Florida Wading Bird Report, produced by the South Florida Water Management District.

Link to the ScienceBase Item Summary page for the item described by this metadata record. Service Protocol: Link to the ScienceBase Item Summary page for the item described by this metadata record. Application Profile: Web Browser. Link Function: information

An ArcGIS shapefile layer showing the extent of all extant and relic Adelie penguin (Pygoscelis adeliae) colonies on Shirley Island, Windmill Islands, February 2006. The field Status describes each polygon as extant, relic or maximum. Extant refers to the area used by breeding birds in the summer 2005/06. Maximum refers to the historic maximal extent of the colony. Relic refers to any colony which was not occupied by any breeding pairs during 2005/06.

Positional accuracy is approx. 1-2 m, after accounting for dGPS errors and errors in identification of the boundaries of colonies. Mapping was conducted after the end of the breeding season, so boundaries were identified as the extent of nest pebbles/fresh faeces, and it was considered that they could be reliably identified to within 0.5m.

Data were acquired using a Trimble Pro XH differential GPS. This work was completed as part of ASAC project 1219 (ASAC_1219).

Work on this project also utilised a Digital Elevation Model (DEM) created for Shirley Island. See the metadata record, 'A digital elevation model (DEM) and orthophoto of Shirley Island, Windmill Islands, Antarctica' for more information (linked below).

A central prediction of the current Everglades restoration plan is that the return to natural flows and hydropatterns will result in large, sustainable breeding wading bird populations; a return to natural timing of nesting; and restoration of nesting in the coastal zone. The timing, location, size, and productivity of wading bird nesting will be monitored over the geographic range of the Everglades ecosystem. Monitoring methods will allow for comparison of historical and current information. The geographic regions monitored will include Florida Bay; mangrove estuaries and ecotone; freshwater marshes of ENP; WCAs 1, 2, and 3; Rotenberger and Holey Land; and BCNP.

Nesting of six wading bird species will be monitored: wood stork, white ibis, roseate spoonbill, snowy egret, great egret, and great white heron. These are the species for which the best historical comparisons exist for one or more of the parameters of interest: range of trophic levels, prey sizes, and foraging techniques used (Ogden, 1994; Frederick et al., 1996). Nesting will be monitored between January and late June of each year, with the exception of Florida Bay (November through June). However, there is the possibility that monitoring in the mainland areas will need to be expanded if wood storks begin nesting earlier than January. Evidence of early nesting (eggs or young) is likely to be discovered on January surveys, and timing of surveys will be adjusted accordingly.

The timing, location, and size of nesting events will be monitored using systematic aerial surveys followed by ground counts. Established techniques used in the freshwater marsh sections of the study area (Frederick et al., 2001) will be adapted to specific habitats in Big Cypress and the mainland mangrove estuary. Ground counts will focus on the largest colonies of each species based on the analysis of past years, which suggests that 90% of nesting birds are found on average in 3 to 33 colonies depending on the species (Frederick, personal communication). Accuracy in aerial counts of large colonies will be improved through the use of aerial photography followed by later counts of those photos (Frederick et al., in prep.).

Florida Bay. Roseate spoonbill and ibis nests in Florida Bay are generally located in dense red mangrove stands and are not generally visible from outside the colony. All islands that were previously reported to have had nesting colonies (Lorenz et al., 2001) will be surveyed monthly during the nesting season, and the number of nests will be counted. While traversing Florida Bay by boat, locations of roseate spoonbill and white ibis activity will be investigated for new nesting sites. The timing of colony surveys late in the incubation period and during mild climatic conditions and the limitation of time in an individual colony to less than one hour whenever possible will minimize impacts of surveys on colonies (Lorenz et al., 2001).

Roseate Spoonbill Foraging Location. In order to use nesting effort and nesting success as criteria for ecosystem evaluation, the location of primary foraging grounds must be monitored for each colony group (Lorenz et al., 2001). In order to identify the direction of foraging grounds from nesting colonies, flight line counts similar to those described by Dusi and Dusi (1978) will be made at the two largest colonies in each colony group. Flight line counts will yield an estimate of the proportion of birds using general areas (e.g., eastern, middle, or western mainland sites; mainline keys; etc.). To get more specific foraging locations, individual birds will be followed using a fixed-wing aircraft from their nesting colonies to the first foraging location. Flight line observation and following flights will also greatly aid in identifying new colony sights locations throughout the bay.

Refinement of Nest Survey and Counting Methods. Any periodic surveys are likely to lead to underestimates due to asynchronous nesting and the possibility that nests may start and fail in between survey dates. Comparing typical monthly survey schedules with a large sample of known nesting histories of individual nests shows that the monthly survey schedule that has been followed in the central Everglades since 1986 has been associated with a known correction factor, with annual variation in that correction factor of 26% above and below any annual estimate (Frederick et al., in prep.) Therefore, the resulting nesting population estimates are likely to be associated with this level of error. However, estimation of this error rate is based on only 2 – 4 years of information on marked nests, depending on species. The database of individual nest histories will be expanded in order to refine the estimation of error associated with monthly surveys. This involves close monitoring of individual nests at one or more colonies throughout the nesting season in order to measure both duration and seasonal timing of nesting attempts.

Here are a few use cases for this project:

1. Bacterial Colony Identification: Researchers and lab technicians can use the Colony Counter model to automatically identify and count different types of bacterial colonies grown on agar plates. This can save time and improve accuracy in experiments involving microbiology, healthcare, and pharmaceutical industries.

2. Ecology and Wildlife Monitoring: Using the Colony Counter model on aerial or satellite images, ecologists and conservationists can identify and count the density of various species or habitats like bird colonies, plant distribution patterns, or nesting sites in a given area.

3. Industrial Quality Control: Manufacturers can utilize the Colony Counter model for quality control on products that contain a pattern of features, like in the case of inspecting printed circuit boards for missing components or identifying defects in materials such as textile, ceramics, or metal alloys.

4. Cell Biology Research: The Colony Counter model can assist in analyzing cell culture images from in-vitro cell assays and colony formation assays to identify cell types, growth patterns or quantify cell proliferation in various experimental settings, thus advancing cell biology and related medical research.

5. Astronomy: Scientists can employ the Colony Counter model to identify and classify celestial objects in astronomy imagery, such as star clusters, galaxies or nebulae, to study their formation, evolution, and distribution patterns in the cosmos.

Species distribution models (GAM, Maxent and Random Forest ensemble) predicting the distribution of discrete Lophelia pertusa - Desmophylum pertusum colonies assemblage in the Celtic Sea. This community is considered ecologically coherent according to the cluster analysis conducted by Parry et al. (2015) on image samples. Modelling its distribution complements existing work on their definition and offers a representation of the extent of the areas of the North East Atlantic where they can occur based on the best available knowledge. This work was performed at the University of Plymouth in 2021.

Municipal Map created by CSA in partnership with the Oklahoma Tax Commission.

An ArcGIS shapefile layer showing the extent of all extant Adelie penguin (Pygoscelis adeliae) colonies at Nelly Island, Windmill Islands, December, 1990.

The colony boundaries were digitised from Linhof aerial photographs (ANTC1219, run 53, frames 5-7) that were georeferenced to the Windmill Islands Topopoly GIS dataset.

Data quality cannot be accurately assessed. Errors in the georeferencing process could not be quantified, and there are positional discrepancies between overlapping aerial photographs are up to 2.4 m. Thus, absolute errors in the position of the colonies cannot be quantified, but the colony boundaries should be within ~0.5m of their location within the photographs.

The shapefile and the georeferenced aerial photographs are available for download from a Related URL.

This work was completed as part of ASAC project 1219 (ASAC_1219).

The Sea Bird Colony Database contains current and historical data for all known seabird colonies in Svalbard and around the Barents Sea, including total counts, surveillance data, photographic documentation and references. The database is owned and annually maintained by the Norwegian Polar Institute in partnership with seven Russian institutions.

MS Access database, originally created by Vidar Bakken.

Quality

The data quality is "best available", and highly variable as the database contains historical data, as well as data from recent surveys and censuses. A few, selected colonies are revisited and counted annually, while others are rarely revisited due to their remote locations. A substantial number of colonies are registered with historically recorded positions that are not accurate.

A brief explanation of all the fields in the seabird-colony database:

colony_name - Colony's name.

colony_alternative_name - Colony's alternative name.

region - the region the colony belongs to.

zone:The zone the colony belongs to which could be f.ex. Hornsund, Bellsund, Isfjorden, Prins Karls Forland etc. From a collection of names.

latitude: The colony's latitude.

longitude: The colony's longitude.

location_accuracy: How accurate is the given latitude/longitude? Measured in meters, by GPS or on digital map.

conservation_type: Is the colony located in an area which holds a particular conservation status?

colony_type: The type of terrain the colony is situated in.

ownership: Who owns the colony location.

island: Name of island if colony not situated on the mainland.

island_size: Size of island if colony not situated on the mainland.

island_archipelago: The island belongs to this archipelago.

length: Length of coastline where the colony is situated - usually applies to coast colonies.

distance: Distance from colony to closest coastline.

distance_mainland: Distance from colony to the mainland.

exposure: Direction of the colony- south, west, etc.

area: Area of cliff wall if situated on a vertical cliff (or hillside).

confirmed: Year the colony first were described in literature.

map: The map that shows the colony place, for Svalbard typically numbered maps f.ex. "E8-BARENTSJØKULEN".

comment: Comment about the colony.

geometry: GeoJSON object outlining the colony

historical_colony: Where the colony first was described - field used f.ex. if colony can't be found anymore to keep old data.

colony_area: 1 if there exists a location area polygon for the colony an 0 if not.

predators: Who is predating the colony.

access_id: The corresponding MS access database id for count.

species: Which species.

start_date: Start date of counting.

end_date: End date of counting.

mean: Mean count value for the species in the colony.

max: Max count value for the species in the colony.

min: Min count value for the species in the colony.

accuracy: Count accuracy.Exact or rough estimate.

unit: Unit used for counting - pair, individual, nest, apparently occupied nest etc

method: Counting method used - direct count, from photograph, extrapolated, combination etc.

platform: Viewed from platform - land, boat, helicopter etc.

breeding: Stage of breeding - pre-laying period, eggs only, hatching period etc.

useful: Useful as total count.

count_comment: comment about the count.

colony_reference: This is one or more literature references where the colony has been described.

colony_reference.ref_id: RefenceID from MS database.

colony_reference.ref_unique_id: refence id most likely from the old DBase database.

colony_reference.authors: Publication authors.

colony_reference.title: Publication title.

colony_reference.year: Year publication was published.

colony_reference.volume: Publication volume.

colony_reference.pages: Publication pages.

colony_reference.journal: Publication journal.

This layer is a georeferenced raster image of an historic regional map of Southern Africa from the 19th century originally published in John Bartholomew's XXth Century Citizen's Atlas (1902). This map includes inset plans of Cape Town, Johannesburg / Pretoria and Port Elizabeth. 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, or other information associated with the principal map. This map was georeferenced by the Stanford University Geospatial Center using a Transverse Mercator projection. This map is part of a selection of digitally scanned and georeferenced historic maps of Africa held at Stanford University Libraries.

This dataset includes Adelie penguin colonies and coastline digitised from Eric J. Woehler, G.W. Johnstone and Harry R. Burton, 'ANARE Research Notes 71, The distribution and abundance of Adelie penguins, Pygoscelis adeliae, in the Mawson area and at the Rookery Islands (Specially Protected Area 2), 1981 and 1988'. Copies of the maps as PDF and TIFF downloads are available through the SCAR Map Catalogue (see the links in the related links section). Map 1 [Mawson area, including the Rookery Islands SPA] Map 2 [Rookery Islands SPA] Map 3 [Islands near Mawson Station] Map 4 [Rookery Island 1] Map 5 [Rookery Island 2] Map 6 [Rookery Island 3] Map 7 [Rookery Island 3A] Map 8 [Rookery Island 4] Map 9 [Rookery Island 5] Map 10 [Rookery Island 6] Map 11 [Rookery Island 7] Map 13 [Rookery Island 9] Map 14 [Rookery Island 10 and 11] Map 15 [Giganteus Island] Map 16 [Rookery Island] Map 17 [Bechervaise Island] Map 18 [Verner Island] Map 19 [Petersen Island] Map 20 [Welch Island Sheet 1 of 2] Map 20 [Welch Island Sheet 2 of 2] Map 21 [Klung Island] Map 22 [Un-named island west of Klung Island] Map 23 [Gibbney Island] Map 24 [Un-named island west of Forbes Glacier] Map 25 [Islands surveyed in 1981-82 where Adelie penguin colonies were located]

Data Sources: Banque informatisée des oiseaux de mer au Québec (BIOMQ: ECCC-CWS Quebec Region) Atlantic Colonial Waterbird Database (ACWD: ECCC-CWS Atlantic Region).. Both the BIOMQ and ACWD contain records of individual colony counts, by species, for known colonies located in Eastern Canada. Although some colonies are censused annually, most are visited much less frequently. Methods used to derive colony population estimates vary markedly among colonies and among species. For example, census methods devised for burrow-nesting alcids typically rely on ground survey techniques. As such, they tend to be restricted to relatively few colonies. In contrast, censuses of large gull or tern colonies, which are geographically widespread, more appropriately rely on a combination of broad-scale aerial surveys, and ground surveys at a subset of these colonies. In some instances, ground surveys of certain species are not available throughout the study area. In such cases, consideration of other sources, including aerial surveys, may be appropriate. For example,data stemming from a 2006 aerial survey of Common Eiders during nesting, conducted by ECCC-CWS in Labrador, though not yet incorporated in the ACWD, were used in this report. It is important to note that colony data for some species, such as herons, are not well represented in these ECCC-CWS databases at present. Analysis of ACWD and BIOMQ data (ECCC-CWS Quebec and Atlantic Regions): Data were merged as temporal coverage, survey methods and geospatial information were comparable. Only in cases where total counts of individuals were not explicitly presented was it necessary to calculate proxies of total counts of breeding individuals (e.g., by doubling numbers of breeding pairs or of active nests). Though these approaches may underestimate the true number of total individuals associated with a given site by failing to include some proportion of the non-breeding population (i.e., visiting adult non-breeders, sub-adults and failed breeders), tracking numbers of breeding individuals (or pairs) is considered to be the primary focus of these colony monitoring programs.In order to represent the potential number of individuals of a given species that realistically could be and may historically have been present at a given colony location (see section 1.1), the maximum total count obtained per species per site since 1960 was used in the analyses. In the case of certain species,especially coastal piscivores (Wires et al. 2001; Cotter et al. 2012), maxima reached in the 1970s or 1980s likely resulted from considerable anthropogenic sources of food, and these levels may never be seen again. The effect may have been more pronounced in certain geographic areas. Certain sites once used as colonies may no longer be suitable for breeding due to natural and/or human causes, but others similarly may become suitable and thus merit consideration in long-term habitat conservation planning. A colony importance index (CII) was derived by dividing the latter maximum total count by the potential total Eastern Canadian breeding population of that species (the sum of maximum total counts within a species, across all known colony sites in Eastern Canada). The CII approximates the proportion of the total potential Eastern Canadian breeding population (sum of maxima) reached at each colony location and allowed for an objective comparison among colonies both within and across species. In some less-frequently visited colonies, birds (cormorants, gulls, murres and terns, in particular) were not identified to species. Due to potential biases and issues pertaining to inclusion of these data, they were not considered when calculating species’ maximum counts by colony for the CII. The IBA approach whereby maximum colony counts are divided by the size of the corresponding actual estimated population for each species (see Table 3.1.2; approximate 1% continental threshold presented) was not used because in some instances individuals were not identified to species at some sites, or population estimates were unavailable.Use of both maxima and proportions of populations (or an index thereof) presents contrasting, but complementary, approaches to identifying important colonial congregations. By examining results derived from both approaches, attention can be directed at areas that not only host large numbers of individuals, but also important proportions of populations. This dual approach avoids attributing disproportionate attention to species that by their very nature occur in very large colonies (e.g., Leach’s Storm Petrel) or conversely to colonies that host important large proportions of less-abundant species (Roseate Tern, Caspian Tern, Black-Headed Gull, etc.), but in smaller overall numbers. Point Density Analysis (ArcGIS Spatial Analyst) with kernel estimation, and a 10-km search radius,was used to generate maps illustrating the density of colony measures (i.e., maximum count by species,CII by species), modelled as a continuous field (Gatrell et al. 1996). Actual colony locations were subsequently overlaid on the resulting cluster map. Sites not identified as important should not be assumed to be unimportant.

Resource Mapping data was collected from field survey and all points such as markets, atms, schools were located and appropriate tags were given.

Data was uploaded on Google sheets and addons of Fusion Mas and point map were installed and addons were run to form virtual maps in their own particular webpages.

Source link of those webpages are determined and were added in a iframe in src link.

In web html design a table was made and all three iframe are added in table.

The final html was added as html element in sites.google.com to create a custom website.

The website link: www.sites.google.com/site/pranavrsmap

Webpage and Sheets are the most important data here. Other data are optional and are uploaded for your Geospatial Location research

Figure 5.9. Northern fulmar colony locations and size in number of individuals. Data from Greenland Seabird Colony Register.