File List Supplement1.xls (md5: 4202b5bccb5ee828f646f50530394c47)

  Please be advised that the ESA cannot guarantee the forward migration of proprietary file formats such as Excel (.xls) documents.
Description
  SupplementA.xls is an Excel spreadsheet containing 5 sheets with example calculations. The first 4 sheets (labeled Model 1 - Model 4) contain calculations for models considered in APPLICATION TO YELLOWSTONE BISON:
  Model 1: Makes no assumptions about equality of survival rates for different age classes.
  Model 2: Assumes survival rates are equal for ages 0–1, 2–3, 4–5, 6–7, 8–9, 10–11, 12–13.
  Model 3: Assumes survival rates are equal for ages 0–1, 2–3, 4–5, 6–11, 12–13.
  Model 4: Assumes survival rates are equal for ages 0–13.
  The last sheet (labeled 3 Years) contains calculations for a hypothetical example with 3 age classes and 3 years of data, and no assumptions about equality of survival rates.

Inputs for each of these metrics come GIS modeling of the ZOIs. Each metric is calucated for three flood events (2-year, 20-year, and 100-year) and converted to expected annual (see worksheet 'EADExample' and project report). For buidlings, roads, and critical facilities exposed, GIS modeling tallies the number/miles for each event and the worksheets here simply convert to expected annual. For expected annual damages to buildings, there are four worksheets. 'Inputs' worksheet is where we enter charateristics for each building. 'Coastal_DDF' contains a number of depth-damage functions taken from FEMA's HAZUS software and from the USACE (2015) NACCS report. 'Damage' applies characteristics of the buildings and the appropriate depth damage functions to calculate pre-project and post-project damages for each building affected at each project site and across each flood event modeled. The UID column is a unique identifier to track each combination of building and NFWF project site. Finally, the worksheet 'Metric9ByProject' sums up damages across all buildings for each project and flood scenario and converts the result to expected annual damages pre-project and post-project.

Excel Age-Range creator for Office for National Statistics (ONS) Mid year population estimates (MYE) covering each year between 1999 and 2014

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These files take into account the revised estimates for 2002-2010 released in April 2013 down to Local Authority level and the post 2011 estimates based on the Census results. Scotland and Northern Ireland data has not been revised, so Great Britain and United Kingdom totals comprise the original data for these plus revised England and Wales figures.

This Excel based tool enables users to query the single year of age raw data so that any age range can easily be calculated without having to carry out often complex, and time consuming formulas that could also be open to human error. Simply select the lower and upper age range for both males and females and the spreadsheet will return the total population for the range. Please adhere to the terms and conditions of supply contained within the file.

Tip: You can copy and paste the rows you are interested in to another worksheet by using the filters at the top of the columns and then select all by pressing Ctrl+A. Then simply copy and paste the cells to a new location.

ONS Mid year population estimates

Open Excel tool (London Boroughs, Regions and National, 1999-2014)

Also available is a custom-age tool for all geographies in the UK. Open the tool for all UK geographies (local authority and above) for: 2010, 2011, 2012, 2013, and 2014.

This full MYE dataset by single year of age (SYA) age and gender is available as a Datastore package here.

Ward Level Population estimates

Excel single year of age population tool for 2002 to 2013 for all wards in London.

New 2014 Ward boundary estimates

This data is only for wards in the three London boroughs that changed their ward boundaries in May 2014. The estimates in this spreadsheet have been calculated by the GLA by taking the proportion of a the old ward that falls within the new ward based on the proportion of population living in each area at the 2011 Census. Therefore, these estimates are purely indicative and are not official statistics and not endorsed by ONS.

Dataset for the article: Cortinovis C., Geneletti D., Haase D. (2022). Higher immigration and lower land take rates are driving a new densification wave in European cities. npj Urban Sustainability 2, 19. doi:10.1038/s42949-022-00062-0

The dataset includes three excel workbooks. The main workbook "EU_cities_data.xlsx" calculates residential density in 2006, 2012 and 2018 and its trends in the two periods 2006-2012 and 2012-2018 for 331 European cities and greater cities. The worksheet "CITIES_GREATER_sel" is the basis to reproduce the analyses and figures presented in the paper and related Supplementary Material, using the code R code "EU_cities_plot" available at doi:10.6084/m9.figshare.19773151.

The main workbook is linked to two datasets containing demographic data for the selected cities and greater cities: - EU_cities_population.xlsx: total population at the 1st of January of the three reference years; - EU_cities_demo_balance.xlsx: data on births and deaths in each city during the analysed period, and calculation of net migration figures.

Population data are based on the Eurostat Urban Audit (https://ec.europa.eu/eurostat/web/cities/data/database) and on datasets from national statistical offices. The numerous corrections to the original Urban Audit database and the final source of each value are indicated in the two datasets (see worksheet "sources and legend").

Residential area and land take for residential use are based on the Copernicus Urban Atlas (https://land.copernicus.eu/local/urban-atlas) version 021 for the reference year 2012, version 012 for the reference year 2018, and the consolidated “Revised” version available in 2021 for the reference year 2006.

Cities’ and greater cities’ boundaries were retrieved from the GISCO Eurostat spatial database linked to the Urban Audit, version 2018 ( https://ec.europa.eu/eurostat/web/gisco/geodata/reference-data/administrative-units-statistical-units/urban-audit).

Abstract The dataset was derived by the Bioregional Assessment Programme. This dataset was derived from multiple datasets. You can find a link to the parent datasets in the Lineage Field in this metadata statement. The History Field in this metadata statement describes how this dataset was derived. This dataset shows the Australian Bureau of Statistics (ABS) Mesh Blocks across Victoria, with the 2011 census population and housing counts attached as attributes. It was derived by the Bioregional Assessment Programme from the ABS Mesh Block Population Counts Aus 2011 dataset, and the ABS Boundaries 2011 dataset. The source datasets are identified in the Lineage field in this metadata statement. The processes undertaken to produce this derived dataset are described in the History field in this metadata statement. ## Dataset History The ABS 2011 Mesh Block Population Count spreadsheet (https://data.bioregionalassessments.gov.au/datastore/dataset/ee39fa76-db4e-412a-af0a-115d965b5813) was joined to the Victorian ABS Mesh Block boundaries (https://data.bioregionalassessments.gov.au/datastore/dataset/8b65c3a4-7010-4a79-8eaa-5621b750347f) using the unique MB_CODE11 field within ESRI ArcMap 10.2. Two additional fields were added to show Mesh Block Area (km2) and Population Density (people/km2). These field values were calculated within ESRI ArcMap 10.2 using the Field Calculator tool. ## Dataset Citation Bioregional Assessment Programme (2014) Victorian ABS Mesh Block Population 2011. Bioregional Assessment Derived Dataset. Viewed 29 September 2017, http://data.bioregionalassessments.gov.au/dataset/b27fdf82-dd1e-4841-a228-21f671a95368. ## Dataset Ancestors * Derived From ABS Mesh Block Population Counts Aus 2011 * Derived From ABS Boundaries 2011

File List SpomAndOnePopThreeStates.nb

Description The worksheets allow calculating and plotting demo-genetic eigenvalues for either one local population fluctuating among several states or a set of 2 or 3 populations exchanging migrants (SPOM model). All variables are described in the Graphs section.