About this dataset

Context

The dataset tabulates the Marine population over the last 20 plus years. It lists the population for each year, along with the year on year change in population, as well as the change in percentage terms for each year. The dataset can be utilized to understand the population change of Marine across the last two decades. For example, using this dataset, we can identify if the population is declining or increasing. If there is a change, when the population peaked, or if it is still growing and has not reached its peak. We can also compare the trend with the overall trend of United States population over the same period of time.

Key observations

In 2023, the population of Marine was 941, a 0.21% decrease year-by-year from 2022. Previously, in 2022, Marine population was 943, a decline of 0.95% compared to a population of 952 in 2021. Over the last 20 plus years, between 2000 and 2023, population of Marine increased by 31. In this period, the peak population was 972 in the year 2010. The numbers suggest that the population has already reached its peak and is showing a trend of decline. Source: U.S. Census Bureau Population Estimates Program (PEP).

Content

When available, the data consists of estimates from the U.S. Census Bureau Population Estimates Program (PEP).

Data Coverage:

• From 2000 to 2023

Variables / Data Columns

• Year: This column displays the data year (Measured annually and for years 2000 to 2023)
• Population: The population for the specific year for the Marine is shown in this column.
• Year on Year Change: This column displays the change in Marine population for each year compared to the previous year.
• Change in Percent: This column displays the year on year change as a percentage. Please note that the sum of all percentages may not equal one due to rounding of values.

Good to know

Margin of Error

Data in the dataset are based on the estimates and are subject to sampling variability and thus a margin of error. Neilsberg Research recommends using caution when presening these estimates in your research.

Custom data

If you do need custom data for any of your research project, report or presentation, you can contact our research staff at research@neilsberg.com for a feasibility of a custom tabulation on a fee-for-service basis.

Inspiration

Neilsberg Research Team curates, analyze and publishes demographics and economic data from a variety of public and proprietary sources, each of which often includes multiple surveys and programs. The large majority of Neilsberg Research aggregated datasets and insights is made available for free download at https://www.neilsberg.com/research/.

Recommended for further research

This dataset is a part of the main dataset for Marine Population by Year. You can refer the same here

About this dataset

Context

The dataset tabulates the population of Marine by gender, including both male and female populations. This dataset can be utilized to understand the population distribution of Marine across both sexes and to determine which sex constitutes the majority.

Key observations

There is a slight majority of female population, with 52.24% of total population being female. Source: U.S. Census Bureau American Community Survey (ACS) 2019-2023 5-Year Estimates.

Content

When available, the data consists of estimates from the U.S. Census Bureau American Community Survey (ACS) 2019-2023 5-Year Estimates.

Scope of gender :

Please note that American Community Survey asks a question about the respondents current sex, but not about gender, sexual orientation, or sex at birth. The question is intended to capture data for biological sex, not gender. Respondents are supposed to respond with the answer as either of Male or Female. Our research and this dataset mirrors the data reported as Male and Female for gender distribution analysis. No further analysis is done on the data reported from the Census Bureau.

Variables / Data Columns

• Gender: This column displays the Gender (Male / Female)
• Population: The population of the gender in the Marine is shown in this column.
• % of Total Population: This column displays the percentage distribution of each gender as a proportion of Marine total population. Please note that the sum of all percentages may not equal one due to rounding of values.

Good to know

Margin of Error

Data in the dataset are based on the estimates and are subject to sampling variability and thus a margin of error. Neilsberg Research recommends using caution when presening these estimates in your research.

Custom data

If you do need custom data for any of your research project, report or presentation, you can contact our research staff at research@neilsberg.com for a feasibility of a custom tabulation on a fee-for-service basis.

Inspiration

Neilsberg Research Team curates, analyze and publishes demographics and economic data from a variety of public and proprietary sources, each of which often includes multiple surveys and programs. The large majority of Neilsberg Research aggregated datasets and insights is made available for free download at https://www.neilsberg.com/research/.

Recommended for further research

This dataset is a part of the main dataset for Marine Population by Race & Ethnicity. You can refer the same here

Six metrics were used to determine Population Vulnerability: global population size, annual occurrence in the California Current System (CCS), percent of the population present in the CCS, threat status, breeding score, and annual adult survival. Global Population size (POP)—to determine population size estimates for each species we gathered information tabulated by American Bird Conservancy, Birdlife International, and other primary sources. Proportion of Population in CCS (CCSpop)—for each species, we generated the population size within the CCS by averaging region-wide population estimates, or by combining state estimates for California, Oregon, and Washington for each species (if estimates were not available for a region or state, “NA” was recorded in place of a value) and then dividing the CCSpop value by the estimated global population size (POP) to yield the percentage of the population occurring in the CCS. Annual Occurrence in the CCS (AO)—for each species, we estimated the number of months per year within the CCS and binned this estimate into three categories: 1–4 months, 5–8 months, or 9–12 months. Threat Status (TS)—for each species, we used the International Union for Conservation of Nature (IUCN) species threat status (IUCN 2014) and the U.S. Fish and Wildlife national threat status lists (USFWS 2014) to determine TS values for each species. If available, we also evaluated threat status values from state and international agencies. Breeding Score (BR)—we determined the degree to which a species breeds and feeds its young in the CCS according to 3 categories: breeds in the CCS, may breed in the CCS, or does not breed in the CCS. Adult Survival (AS)—for each species, we referenced information to estimate adult annual survival, because adult survival among marine birds in general is the most important demographic factor that can affect population growth rate and therefore inform vulnerability. These data support the following publication: Adams, J., Kelsey, E.C., Felis J.J., and Pereksta, D.M., 2016, Collision and displacement vulnerability among marine birds of the California Current System associated with offshore wind energy infrastructure: U.S. Geological Survey Open-File Report 2016-1154, 116 p., https://doi.org/10.3133/ofr20161154. These data were revisied in June 2017 and the revision published in August 2017. Please be advised to use CCS_vulnerability_FINAL_VERSION_v9_PV.csv

About this dataset

Context

The dataset tabulates the population of Marine by race. It includes the population of Marine across racial categories (excluding ethnicity) as identified by the Census Bureau. The dataset can be utilized to understand the population distribution of Marine across relevant racial categories.

Key observations

The percent distribution of Marine population by race (across all racial categories recognized by the U.S. Census Bureau): 88.57% are white, 0.42% are Asian, 3.13% are some other race and 7.87% are multiracial.

Content

When available, the data consists of estimates from the U.S. Census Bureau American Community Survey (ACS) 2019-2023 5-Year Estimates.

Racial categories include:

• White
• Black or African American
• American Indian and Alaska Native
• Asian
• Native Hawaiian and Other Pacific Islander
• Some other race
• Two or more races (multiracial)

Variables / Data Columns

• Race: This column displays the racial categories (excluding ethnicity) for the Marine
• Population: The population of the racial category (excluding ethnicity) in the Marine is shown in this column.
• % of Total Population: This column displays the percentage distribution of each race as a proportion of Marine total population. Please note that the sum of all percentages may not equal one due to rounding of values.

Good to know

Margin of Error

Data in the dataset are based on the estimates and are subject to sampling variability and thus a margin of error. Neilsberg Research recommends using caution when presening these estimates in your research.

Custom data

If you do need custom data for any of your research project, report or presentation, you can contact our research staff at research@neilsberg.com for a feasibility of a custom tabulation on a fee-for-service basis.

Inspiration

Neilsberg Research Team curates, analyze and publishes demographics and economic data from a variety of public and proprietary sources, each of which often includes multiple surveys and programs. The large majority of Neilsberg Research aggregated datasets and insights is made available for free download at https://www.neilsberg.com/research/.

Recommended for further research

This dataset is a part of the main dataset for Marine Population by Race & Ethnicity. You can refer the same here

Comprehensive demographic dataset for Marine City, MI, US including population statistics, household income, housing units, education levels, employment data, and transportation with year-over-year changes.

This graph shows the number of active duty U.S. Marine Corps personnel from 1995 to 2010. In 2010, there were 202,612 active duty U.S. Marine Corps members, as compared to 172,955 in 2000.

About this dataset

Context

The dataset tabulates the Marine On St. Croix population over the last 20 plus years. It lists the population for each year, along with the year on year change in population, as well as the change in percentage terms for each year. The dataset can be utilized to understand the population change of Marine On St. Croix across the last two decades. For example, using this dataset, we can identify if the population is declining or increasing. If there is a change, when the population peaked, or if it is still growing and has not reached its peak. We can also compare the trend with the overall trend of United States population over the same period of time.

Key observations

In 2023, the population of Marine On St. Croix was 657, a 0.31% increase year-by-year from 2022. Previously, in 2022, Marine On St. Croix population was 655, a decline of 0.15% compared to a population of 656 in 2021. Over the last 20 plus years, between 2000 and 2023, population of Marine On St. Croix increased by 17. In this period, the peak population was 713 in the year 2017. The numbers suggest that the population has already reached its peak and is showing a trend of decline. Source: U.S. Census Bureau Population Estimates Program (PEP).

Content

When available, the data consists of estimates from the U.S. Census Bureau Population Estimates Program (PEP).

Data Coverage:

• From 2000 to 2023

Variables / Data Columns

• Year: This column displays the data year (Measured annually and for years 2000 to 2023)
• Population: The population for the specific year for the Marine On St. Croix is shown in this column.
• Year on Year Change: This column displays the change in Marine On St. Croix population for each year compared to the previous year.
• Change in Percent: This column displays the year on year change as a percentage. Please note that the sum of all percentages may not equal one due to rounding of values.

Good to know

Margin of Error

Data in the dataset are based on the estimates and are subject to sampling variability and thus a margin of error. Neilsberg Research recommends using caution when presening these estimates in your research.

Custom data

If you do need custom data for any of your research project, report or presentation, you can contact our research staff at research@neilsberg.com for a feasibility of a custom tabulation on a fee-for-service basis.

Inspiration

Neilsberg Research Team curates, analyze and publishes demographics and economic data from a variety of public and proprietary sources, each of which often includes multiple surveys and programs. The large majority of Neilsberg Research aggregated datasets and insights is made available for free download at https://www.neilsberg.com/research/.

Recommended for further research

This dataset is a part of the main dataset for Marine On St. Croix Population by Year. You can refer the same here

Comprehensive demographic dataset for Marine Terrace, Cambria, CA, US including population statistics, household income, housing units, education levels, employment data, and transportation with year-over-year changes.

The graph illustrates the number of personnel in each branch of the U.S. Military for the year 2025. The x-axis lists the military branches: Army, Navy, Marine Corps, Air Force, and Coast Guard. The y-axis represents the number of personnel, ranging from 41,689 to 452,823. Among the branches, the Army has the highest number of personnel with 452,823, followed by the Navy with 337,209 and the Air Force with 321,211. The Marine Corps and Coast Guard have 170,201 and 41,689 personnel, respectively. The data is displayed in a bar graph format, effectively highlighting the distribution of military personnel across the different branches.

Data on the Population Status of Marine Turtles in the pacific ocean. Information is useful also for Palau's marine turtles

The Southern Resident killer whale (SRKW) population is threatened by a number of identified risk factors including prey availability, contaminants, vessel noise and disturbance, and small population size. However, the population may also be subject to internal factors that limit population growth. Continued assessment of the discreetness of this population through morphological and genetic characteristics is important to maintaining ESA status. In addition, an annual census provides important information that allows demographic analyses of this population to be conducted in order to assess population viability. The components of the project represent a significant level of investment of base funds over many years and these data and analyses provide the foundation of information on the population against which all research and management actions are measured that are attempting to address key risk factors of the SRKW population as protected under the ESA and MMPA. Data taken seasonally.

The Gridded Population of the World, Version 3 (GPWv3): Coastlines are derived from the land area grid to show the outlines of pixels (cells) that contain administrative units in GPWv3. The coastlines are designed for cartographic use with the GPWv3 population raster data sets. GPWv3 is produced by the Columbia University Center for International Earth Science Information Network (CIESIN) in collaboration with Centro Internacional de Agricultura Tropical (CIAT). To provide a set of coastlines consistent with GPWv3 raster data for cartographic purposes.

Trawl survey data with high spatial and seasonal coverage were analysed using a variant of the Log Gaussian Cox Process (LGCP) statistical model to estimate unbiased relative fish densities. The model estimates correlations between observations according to time, space, and fish size and includes zero observations and over-dispersion. The model utilises the fact the correlation between numbers of fish caught increases when the distance in space and time between the fish decreases, and the correlation between size groups in a haul increases when the difference in size decreases. Here the model is extended in two ways. Instead of assuming a natural scale size correlation, the model is further developed to allow for a transformed length scale. Furthermore, in the present application, the spatial- and size-dependent correlation between species was included. For cod (Gadus morhua) and whiting (Merlangius merlangus), a common structured size correlation was fitted, and a separable structure between the time and space-size correlation was found for each species, whereas more complex structures were required to describe the correlation between species (and space-size). The within-species time correlation is strong, whereas the correlations between the species are weaker over time but strong within the year.

Comprehensive demographic dataset for Marine Villa, Saint Louis, MO, US including population statistics, household income, housing units, education levels, employment data, and transportation with year-over-year changes.

This dataset is part of the 2018 Belgian submission for the Marine Strategy Framework Directive (MSFD) linked to descriptor 1, criterion 3. Occurrence of breeding seabirds describes the observation of eight seabird species (Common tern, Black-headed Gull, Herring Gull, Common Gull, Small Black-backed Gull, Yellow-legged gull, Big Stern and Little Stern) on the Belgian coast between 1992 and 2015.

http://geo.abds.is/geonetwork/srv/eng//resources.get?uuid=59d822e4-56ce-453c-b98d-40207a2e9eec&fname=cbmp_small.png" alt="logo" height="67px" align="left" hspace="10px"> The Arctic marine data set contains a total of 111 species and 310 population time series from 170 locations. Species coverage is about 34% of Arctic marine vertebrate species (100% of mammals, 53% of birds, and 27% of fishes) (Bluhm et al. 2011). At the species level, even though the representation of Arctic fish species is lower than that of mammals and birds, the data are dominated by fishes, primarily from the Pacific Ocean (especially the Bering Sea and Aleutian Islands). However, there are more population time series in total for bird species, which is reflective of this group being both better studied historically and also monitored at many small study sites compared to fish and marine mammal species, which are regularly monitored at a much larger scale through stock management. Note that the time span selected for marine analyses is 1970 to 2005 (compared with 1970 to 2007 for the ASTI for all species). CAFF Assessment Series No. 7 April 2012 - The Arctic Species Trend Index - Tracking trends in Arctic marine populations

Herring eggs are deposited on the seabed in discrete gravel beds or flat stone and the herring are completely reliant on these spawning beds for reproduction. Spawning beds refers to known discrete gravel beds used by herring. Nearby spawning beds are grouped into spawning grounds, which may contain one or more spawning beds. Spawning grounds are further grouped into spawning areas.

Suggested Citation: Nolan, C; O'Sullivan, D. (2023). Herring Spawning Areas. Marine Institute, Ireland. https://doi.org/10/kr82

Scottish Marine and Freshwater Science Vol 11 No 14 The interim Population Consequence of Disturbance (iPCoD) is a framework that allows individual-level effects from disturbance to be scaled to population-level impacts. This approach is parameterised by published figures for specific UK populations or derived from the literature for a given species. The original iPCoD model was developed in 2013, with subsequent reviews of the recommended demographic input parameters in 2014 and 2017. This current report by SMRU Consulting establishes the most up-to-date information on five key species of UK marine mammal (harbour porpoise, bottlenose dolphin, minke whale, harbour seal and grey seal) for use in the iPCoD model. The report also examines the sensitivity of model output to potential misspecification in the various input parameters that are obtained via expert elicitation. Two approaches were used in the sensitivity testing: the effect of changing the value of a single parameter independently of the others and the effect of adjusting all the demographic parameters systematically to compare scenarios with the same population trajectory but different combinations of demographic parameters. The observed sensitivity to misspecification is complex, however, in general, the demographic parameter most sensitive to this issue was pup/calf survival. However, the sensitivities identified were only apparent at relatively high (and somewhat unrealistic) levels of impact, and therefore SMRU Consulting conclude that the metric of counterfactual of population size, which is presented in impact assessments, is robust to misspecification in demographic rates. Several criteria are still to be explored, such as the sensitivity of alternative output metrics, a wider range of impact scenarios and the effect of any density-dependence. Future directions and recommendations for the iPCoD approach are also suggested. The updated demographic parameters will improve assessments, and will now be available in time for the upcoming ScotWind leasing round. Where the sensitivity analysis has identified sources of variability and uncertainty in outputs, this will aid interpretation of assessments by advisors and decision makers. The project was undertaken by SMRU Consulting and funded by Scottish Government.

The U.S. Geological Survey, Western Ecological Research Center (USGS-WERC) was requested by the Bureau of Ocean Energy Management (BOEM) to create a database for marine birds of the California Current System (CCS) that would allow quantification and species ranking regarding vulnerability to offshore wind energy infrastructure (OWEI). This was needed so that resource managers could evaluate potential impacts associated with siting and construction of OWEI within the California Current System section of the Pacific Offshore Continental Shelf, including California, Oregon, and Washington. Along with its accompanying Open File Report (OFR), this comprehensive database can be used (and modified or updated) to quantify marine bird vulnerability to OWEIs in the CCS at the population level. For 81 marine bird species present in the CCS, we generated numeric scores to represent three vulnerability indices associated with potential OWEI: population vulnerability, collision vulnerability, and displacement vulnerability. The metrics used to produce these scores includes global population size, proportion of the population in the CCS, threat status, adult survival, breeding score, annual occurrence in the CCS, nocturnal and diurnal flight activity, macro-avoidance behavior, flight height, and habitat flexibility; values for these metrics can be updated and adjusted as new data become available. The scoring methodology was peer-reviewed to evaluate if the metrics identified and the values generated were appropriate for each species considered. The numeric vulnerability scores in this database can readily be applied to areas in the CCS with known species distributions and where offshore renewable energy development is being considered. We hope that this information can be used to assist meaningful planning decisions that will impact seabird conservation. These data support the following publication: Adams, J., Kelsey, E.C., Felis J.J., and Pereksta, D.M., 2016, Collision and displacement vulnerability among marine birds of the California Current System associated with offshore wind energy infrastructure: U.S. Geological Survey Open-File Report 2016-1154, 116 p., https://doi.org/10.3133/ofr20161154.

About this dataset

Context

The dataset tabulates the Marine City population over the last 20 plus years. It lists the population for each year, along with the year on year change in population, as well as the change in percentage terms for each year. The dataset can be utilized to understand the population change of Marine City across the last two decades. For example, using this dataset, we can identify if the population is declining or increasing. If there is a change, when the population peaked, or if it is still growing and has not reached its peak. We can also compare the trend with the overall trend of United States population over the same period of time.

Key observations

In 2022, the population of Marine City was 4,029, a 0.74% decrease year-by-year from 2021. Previously, in 2021, Marine City population was 4,059, a decline of 0.27% compared to a population of 4,070 in 2020. Over the last 20 plus years, between 2000 and 2022, population of Marine City decreased by 584. In this period, the peak population was 4,613 in the year 2000. The numbers suggest that the population has already reached its peak and is showing a trend of decline. Source: U.S. Census Bureau Population Estimates Program (PEP).

Content

When available, the data consists of estimates from the U.S. Census Bureau Population Estimates Program (PEP).

Data Coverage:

• From 2000 to 2022

Variables / Data Columns

• Year: This column displays the data year (Measured annually and for years 2000 to 2022)
• Population: The population for the specific year for the Marine City is shown in this column.
• Year on Year Change: This column displays the change in Marine City population for each year compared to the previous year.
• Change in Percent: This column displays the year on year change as a percentage. Please note that the sum of all percentages may not equal one due to rounding of values.

Good to know

Margin of Error

Data in the dataset are based on the estimates and are subject to sampling variability and thus a margin of error. Neilsberg Research recommends using caution when presening these estimates in your research.

Custom data

If you do need custom data for any of your research project, report or presentation, you can contact our research staff at research@neilsberg.com for a feasibility of a custom tabulation on a fee-for-service basis.

Inspiration

Neilsberg Research Team curates, analyze and publishes demographics and economic data from a variety of public and proprietary sources, each of which often includes multiple surveys and programs. The large majority of Neilsberg Research aggregated datasets and insights is made available for free download at https://www.neilsberg.com/research/.

Recommended for further research

This dataset is a part of the main dataset for Marine City Population by Year. You can refer the same here