Map biodiversity and protected areas

Add data to your map

You’ll add publicly available layers from the Living Atlas related to biodiversity and conservation and the borders of the countries of interest. Protected areas are designed to help conserve the Earth’s biodiversity and guide measurements of progress toward protecting it. The World Database on Protected Areas (WDPA) is updated by governments, non-government organizations, landowners, and communities, and is the most comprehensive global database on terrestrial and marine protected areas.

  1. Sign in to your ArcGIS organizational account or into ArcGIS Enterprise using a named user account.
    Note:

    If you don't have an organizational account, you can sign up for an ArcGIS free trial.

  2. On the ribbon, click your username and choose My Settings.
  3. On the General page, scroll down until you see Units. If necessary, choose Metric.

    Change map units to Metric.

    Making sure your units are Metric will ensure your calculations are correct in later sections.

  4. On the ribbon, click Map.

    A blank map opens. The map extent for a new map is set to the default extent of your organization. Now, you can choose the data you want to add.

  5. On the ribbon, click Add and choose Browse Living Atlas Layers.

    Browse Living Atlas Layers for map data.

    The search pane opens. You'll add data hosted in the Living Atlas, which can be reused to answer the same question for a different taxa or continent. In the description of the items you can see who is authoring these datasets.

  6. In the search box, type Africa Countries. Press Enter.
  7. In the list of results, for Africa Countries, click Add.

    Search for and add the Africa Countries layer.

    The layer is added to the map. The map zooms to the extent of the layer, which is Africa. This layer is a subset of World Countries Generalized. A generalized layer has fewer vertices than the original one. With fewer vertices, the layer draws on the map faster, making it most suitable for visualization.

    The Africa Countries layer

    The layer shows the borders of all countries, which you can click for more information. Each pop-up is configured to show information on the name of the country, its population, flag and links to more information. All this information is sourced from the attribute table of the layer.

  8. From the Living Atlas, search for and add the Global Species Rarity Patterns for Birds layer.

    (birds) Add the Global Species Rarity Patterns for Birds layer.

    The layer is added to the map. To perform calculations involving area at a global scale, you need a grid consistent everywhere in the world. This grid has been created using a width equal to one degree of longitude and variable length so all the cell areas measure approximately 12,100km2. It appears stretched now because the data has been reprojected to the Web Mercator coordinate system for visualization. The layer shows rarity of birds. Rarity and richness are common measures of biodiversity.

    Species richness is a measure of the number of different species in each grid cell. To calculate global richness for birds, the Map of Life analysts used global species range maps and counted the number that overlapped in each cell.

    Species 1 through 4:

    Species ranges diagram

    Calculating richness based on species ranges:

    Overlayed species for richness calculation.

    Species rarity reflects how geographically widespread the species found in each grid cell are, on average. To calculate species rarity, analysts first calculated each species' endemism values, which describe the proportion of a species' range that is represented by a single populated grid cell. Here, this calculation is simplified using the number of populated cells as the total range area.

    Endemism = cell area / range area

    Species 1: 1 / 1 = 1; Species 2: 1 / 2 = 0.5

    Species 1 and 2

    Species 3: 1/3=0.33; Species 4: 1/4=0.25

    Species 3 and 4

    They then calculated total endemism by summing the endemism values in each grid cell across all bird species.

    Total endemism = (cell area / range area 1) + (cell area / range area 2) + (cell area / range area 3) + (cell area / range area 4)

    Total endemism calculation diagram.

    To find the rarity of each grid cell, total endemism was divided by richness.

    Species rarity per cell = total endemism / species richness

    Species rarity calculation

    In this lesson you will use this method to calculate species rarity for birds within protected areas. To do that, the next thing you need to do is add a layer of protected areas. so you’ll need to change the search to all of ArcGIS Online.

  9. In the search pane, click Living Atlas and choose ArcGIS Online.
  10. Search for and add the WDPA_Africa layer. If necessary, add the search term owner:Learn_ArcGIS.
  11. In the Contents pane, uncheck the Africa Countries and Global Species Rarity Patterns for Birds layers.

Subset of the World Database of Protected Areas database.

This layer shows a small subset of the World Database of Protected Areas extracted for the purpose of this lesson. Protected areas are designed to conserve the Earth’s biodiversity and allow us to measure our progress in protecting it. The World Database on Protected Areas (WDPA) is updated by governments, non-government organizations, landowners, and communities, and is the most comprehensive global database on terrestrial and marine protected areas.

The subset you’ll use is for the continent of Africa and was extracted in March 2020. Due to the size of the full WDPA layer, the subset will help you run your analysis quicker. For the complete and updated dataset, use this layer in the Living Atlas.

Calculate protected area of each country

You have added all the relevant layers to describe the conservation efforts for areas with high bird rarity. Now, you’ll begin filtering the information to the top rarest bird areas and the extent of the study area, while calculating the area of each country.

The area of each country will be the base of all the following calculations to describe the conservation effort of each country. First, you’ll make sure you have a single record for each country. Because some countries have islands and other areas that aren’t contiguous (like Alaska to the continental United States), they’re listed separately. Keep in mind that we are working with a generalized layer and therefore the calculations are not exact.

  1. In the Contents pane, point to the Africa Countries layer and click the Perform Analysis button.

    Perform analysis on the Africa Countries layer.

    The Perform Analysis pane opens.

  2. Expand Manage Data and click Dissolve Boundaries.

    The Choose area layer whose boundaries will be dissolved parameter is automatically filled with the Africa Countries layer. The tool requires a few additional parameters.

  3. For Choose dissolve method, choose Areas with same field value and click NAME. Make sure the Create multipart features option is checked.

    Use the Dissolve Boundaries tool.

    In this dataset, countries with multiple related polygons are all shown under the parent country name. Allowing multipart features means you can have a single record with separate polygons, where necessary.

  4. Make sure Result layer name is Dissolve Africa Countries. Add your name or initials to make the layer name unique in your organization.
  5. Uncheck Use current map extent and click Run Analysis.

    Result layer of the dissolve tool

    The tool takes a few minutes to run. The dissolved layer is added to the map.

  6. Point to the Dissolve Africa Countries layer and click the Show Table button.

    The table opens. It contains the layer's attributes: additional information about the data on the map. Each row corresponds to a single country, while each column is a field that includes information on the name of the country and the area in square kilometers. This is the layer of country data that you’ll use from now on, so you’ll remove the Africa Countries layer.

    Note: If the area units of your layer are in square miles, you may not have changed your units in the first section. Do steps 2-3 in the first section and re-run the Dissolve tool.

  7. In the Contents pane, point to the Africa Countries layer, click More Options and choose Remove.

    Remove the Africa Countries layer from the Contents pane.

    Next, you’ll need to know how much area of each country is protected. The WDPA layer you’re using is a small portion of the dataset that shows information only for Africa. On the Item Details page for the WDPA layer, note the different dates of creation and last update. This layer is updated monthly by the United Nations Environmental Programme’s World Conservation Monitoring Centre. The subset version was created with the March 2020 version, you can check in the monthly updates if any protected areas from African countries have been updated.

  8. In the Contents pane, point to the WDPA_Africa layer and click the Perform Analysis button.
  9. Expand Manage Data and click Dissolve Boundaries.
  10. For Choose dissolve method, choose Areas with same field value. Select the field NAME (in capital letters).

    Set parameters for the Dissolve Boundaries tool.

    The NAME field refers to the country that the protected area is located in. The Name field refers to the name of the protected area or park.

  11. Change Result layer name to Dissolve_WDPA_Africa and add your initials to make the layer name unique in your organization. Uncheck Use current map extent.

    Note:
    This tool takes 10 service credits to run. Alternatively, you can add the Dissolve_WDPA_Africa owner:Learn_ArcGIS layer to the map and continue your analysis at Step 13.

  12. Click Run Analysis.

    The tool takes a few minutes. When it finishes, the dissolved layer is added to the map.

  13. Point to the Dissolve Africa Countries layer and click the Show Table button.

    Review the Dissolve WDPA table.

    The table opens. It contains the layer's attributes: additional information about the data on the map. Each row corresponds to a single country, while each column is a field that includes information on the name of the country and the protected area in square kilometers.

Identify top bird diversity cells for each country

Next, you'll filter the biodiversity layer to show only cells with the highest bird rarity. Locating these areas will help you understand where areas with high biodiversity are. To filter the layer, you'll create a logical expression that shows which type of features to display, based on attribute information. Then, you’ll use the Overlay tool to remove the rarity data for countries not on the African continent.

  1. In the Contents pane, uncheck all the layers except the Global Species Rarity Patterns for Birds layer to turn them off.
  2. Point to the Global Species Rarity Patterns for Birds layer and click the Filter button.

    Open the layer filter tool.

    The Filter window opens. There is already a filter set to exclude the areas with no rarity. You’ll edit this query to creating your own.

  3. In the Filter window, click Edit.

    Edit the existing layer filter.

    The Edit tab opens query builder.

  4. For the first drop-down box, make sure Rarity – Birds is chosen. For the second box, choose the operator is.
  5. For the third drop-down box, choose 9.

    Build the query Rarity - Birds is 9.

    The finished expression reads Rarity - Birds is 9. This expression will only show cells that are at the top rank of bird rarity. Now, you'll add a second query to select birds with a ranking of 8.

  6. Click Add another expression and change the boxes to read Rarity - Birds is 8.
    Now you have two expressions, but if you click Apply Filter now, no features will be selected. The default setting is called an AND query, meaning features have to meet the first criteria and the second criteria. You'll need to use an OR query, so that features can meet the first criteria or the second criteria.
  7. Click Display features in the layer that match all of the following expressions and choose Display features in the layer that match any of the following expressions.
  8. Click Apply Filter.

    Result layer for the filter query Rarity - Birds is 9.

    The data on the map is filtered. Only cells at the top ranks of bird rarity are shown. You have selected the top two quantile bins. Quantile bins are a division of the data into equal portions, the number of cells in each quantile is the same.

    Example dataset - Sorting the data into bins - Assigned to a bin

    Quantile creation diagram

    The bird rarity data has been sorted into nine quantiles, so each represents 1/9, or 11.1% of the data. While there may be far fewer species of mammals than birds, we can still compare low and high biodiversity for each group using these bins.

  9. Point to the Global Species Rarity Patterns for Birds layer and click Perform Analysis.

    The Perform Analysis pane opens.

  10. Expand Manage Data and click Overlay Layers.

    The Overlay Layers tool combines two layers into a single layer.

  11. For Choose overlay layer select Dissolve Africa Countries. Make sure for Choose overlay method, Intersect is selected.

    Enter parameters for the Overlay Layers tool.

    By choosing intersect, the features in the input that are overlapped with the overlay features are kept.

  12. Change the Result layer name to Rarity_89_Birds_Africa and add your name or initials. Uncheck the Use current map extent box.
  13. Click Run Analysis.

    Intersected layer result map.

    The tool may take a few minutes to run. When it finishes, the intersected layer is added to the map. The layer shows the bird rarity cells, as well as information about the country they overlap. In cases where cells cross country boundaries the cells are split.

 Identify protected areas with top bird diversity cells for each country

To understand what areas with high rarity have already been protected, you’ll compare the WDPA layer to the rarity layer you created in the previous section.

  1. Zoom and pan your map until the entire continent of Africa is visible.
  2. In the Contents pane, point to the Dissolve_WDPA_Africa layer and click Perform Analysis.
  3. In the Perform Analysis pane, expand Manage Data and click Overlay Layers.

    The tool requires a few parameters.

  4. For Choose overlay layer select Rarity_89_Birds_Africa.
  5. Change the Result layer name to Dissolve_WDPA_Rarity_89_Birds_Africa and add your name or initials. Check Use current map extent.
  6. Click Run analysis.

    Result map of protected areas with high rarity.

    The tool may take a couple of minutes to run. When the analysis finishes, the intersected layer is added to the map. The layer shows the portions of WDPA that contain high bird rarity.

  7. In the Contents pane, turn on the Global Species Rarity Patterns for Birds layer.

    From a visual comparison, you can see that some of the cells showing high rarity for birds are already covered by protected area, but there's a lot that aren't. To calculate the amount of each cell that is protected, you'll use the Summarize Within tool.

  8. In the Contents pane, turn the Global Species Rarity Patterns for Birds layer off, then point to the Rarity 89 Birds Africa layer and click Perform Analysis .
  9. Expand Summarize Data and choose Summarize Within.
  10. For Choose an area layer to summarize other features within its boundaries, make sure Rarity_89_Birds_Africa is chosen. For Choose a layer to summarize, choose Dissolve_Rarity_89_Birds_Africa.

    Using the default setting for Add statistics from the layer to summarize will make sure the total area of protected land inside each grid cell is added.

  11. For Choose field to group by, choose NAME.

    The NAME attribute represents country name. Using this parameter means that each cell will include an attribute showing what country it falls within. Checking the Add percentages option will calculate how much of the attribute value is inside each country.

  12. Name the result layer Summarize_WDPA_Rarity_89_Birds_Africa and click Run Analysis.
    Summarize protected area

    In the result layer, the darker cells show where more land is conserved. The lighter cells show where areas with high species rarity don't have as much protection.

  13. In the Contents pane, point to the Summarize_WDPA_Rarity_89_Birds_Africa layer and click Show Table.

    The Attribute table for the layer opens. The Summarized area in Square Kilometers column is what you're interested in- this is the attribute that shows how much protected area overlaps with each high rarity cell.

  14. Click the Summarized area in Square Kilometers cell and choose Sort Descending.

    Sort Summarized Area field by descending order.

    The table is resorted to show the highest values at the top. Many of the highest values appear to be in Namibia, followed by Ethiopia and Tanzania. If you click a row, the corresponding cell will be selected on the map.

  15. Close the attribute table and save the map.

Symbolize the results

Finally, you’ll edit the values of the purple shading to show which cells are 25, 50, and 75 percent protected. As a derivative of the Global Species Rarity Patterns for Birds layer, the Summarize_WDPA_Rarity_89_Birds_Africa layer consists of 12,100 km2 grid cells. So, for example, if the value of the Summarized area in Square Kilometers attribute is greater than 6,050 km, the cell is more than 50 percent covered by protected area.

  1. In the Contents pane, point to the Summarize_WDPA_Rarity_89_Birds_Africa layer and click Change Style.
  2. In the Change Style pane, for Counts and Amounts (Color), click Options.
  3. Under Classify Data, change 5 classes to 4 and press Enter.
  4. On the color ramp, click the number next to the bottom stop so the number becomes editable. Type 3025 and press Enter.

  5. Click the middle stop and type 6050, then click the third stop and type 9075.

    Symbolized cells by percent covered in protected area.

    The map changes to show the new values. With the new symbology, you can tell that most cells with high bird species rarity have less than half the area protected.

    When you have a range of values that have a critical midpoint, such as this data, you should use a diverging color scheme to emphasize the high and low values. The purple colors you're currently using are continuous, which places emphasis (dark shading) on only one side of the data range (mostly covered by protected area).

  6. Click the Symbols button.

    Change symbology

    The Symbols window shows all the available color ramps.

  7. Scroll down until you see the dark blue to dark orange color ramp. Click the color ramp and click Ok.
    Blue-orange color ramp

    The map changes to show the new color ramp. Now cells that are 75 percent protected and higher are shown in dark blue, while cells that are less than 25 percent protected are shown in dark red.

    Final map of percentage of protection

In this lesson, you found the cells with the highest rarity on the continent of Africa. Then, you calculated the area inside each that's already been protected and symbolized them. In the next lesson, you'll use Arcade scripting to calculate the proportion of each country that's protected.


Calculate proportions with Arcade

You have performed the spatial analysis necessary to obtain the information for each country on how large the country is, how much area is protected, how much area has high rarity of birds, and how much protected area has high rarity of birds. Now, to do the calculations necessary to understand where rare species are best protected, you’ll write attribute expressions to calculate different proportions of interest for each country.

Build the first expression with the expression editor

To build these expressions, you’ll use Arcade, a derivative of JavaScript specific to ArcGIS. Arcade can be used to create a new field whose values will be calculated on the fly. The attribute expression allows you to use the information available in all the layers present in the web map, even if they are not visible. The first expression you build will calculate the proportion of the country that is registered as protected area.

  1. In the Contents pane, turn off all layers but the Dissolve Africa Countries layer.
  2. On the map, click on one of the countries.

    Open a pop-up from the map.

    The pop-up that appears has some default information that you are going to customize.

  3. In the Contents pane, point to the Dissolve Africa Countries layer and click More Options, then choose Configure pop-up.

    Open the Configure Pop-up pane.

  4. In the Configure Pop-up pane, for Attribute Expressions, click Add.

    Add an expression to the pop-up.

    A window to create an attribute expression opens. The attribute expression is built in Arcade.The attribute expression allows to use the information available in all the layers present in the web map, even if they are not visible.

  5. Click Edit and name the expression Protected Proportion. Click Save.

    This expression will calculate the proportion of each country that is protected.

  6. First, you’ll define the WDPA variable. In the Expression editor, on line 4, type var wdpa =.

    Define the WDPA variable in your expression editor.

    To set the variable with the proper WDPA data, you’ll select the map layer.

  7. In the Globals pane, expand $map. For Dissolve_WDPA_Africa, click FeatureSetByName.

    Set the WDPA variable to the correct layer.

    Code is added to the script. The function FeatureSetByName() points to the webmap as first argument, then the name of the layer is passed, arguments are separated by commas inside a function. There is more information about this function here.  You are going to add two more arguments.

  8. After the second argument (the layer name in parentheses), add a comma and type ["NAME_1","AnalysisArea"].

    The expression now reads:

    var wdpa = FeatureSetByName($map,"Dissolve_WDPA_Africa_INITIALS",["NAME_1","AnalysisArea"])

    Note:

    Your layer names will include your initials or name.

    These are the names of the two columns you need to link the layers and the data used in the next calculations. When including strings separated by commas inside square brackets, it is a list of strings. The last argument to include is a boolean, that indicates if the geometry of the feature is necessary, in this case you only require the information from the attribute table so set it with false.

  9. After the third argument, add a comma and type false.

    The first line of the code should read:

    var wdpa = FeatureSetByName($map,"Dissolve_WDPA_Africa_INITIALS",["NAME_1","AnalysisArea"], false)

    The other variables you need are the name of the country, a filtering statement to link the layers using the country name, the filtered information and the proportion of the country that is protected which will be initiated at 0%.

  10. On lines 5- 8, type or paste the following:
    var country_name = $feature.NAME
    var filterStatement = "NAME_1 = @country_name"
    var wdpa_ft_set  = Filter(wdpa, filterStatement)
    var prop_wdpa = 0

    The last bit of the script is a conditional statement that is only going to run if the country has protected areas. If the country doesn’t have protected areas the value returned will be 0.

  11. On lines 9- 13, type or paste the if statement to calculate the proportion of each country that is protected.
    if(count(wdpa_ft_set)>0){
        var wdpa_first = First(wdpa_ft_set)
        var wdpa_area_km2 = wdpa_first['AnalysisArea']
        prop_wdpa = (wdpa_area_km2/$feature.AnalysisArea) *100
    }
  12. Finally, on line 14, add the statement return prop_wdpa, which will ask the script to return the value of proportion protected.

    The full script should be look like the following except for the first line and the comments that have been added. Comments are indicated by a double slash:

    var wdpa = FeatureSetByName($map,"Dissolve_WDPA_Africa_INITIALS",["NAME_1","AnalysisArea"], false) //this variable requests the layer of protected areas that is loaded in the webmap, only the two columns of interest will be returned and the geometry will be omitted as it is not necessary
    var country_name = $feature.NAME //for each feature, which represents a country the name of the country will be stored in the variable country_name
    var filterStatement = "NAME_1 = @country_name" //NAME_1 refers to the field from the the wdpa layer we requested at the beginning of the script. It is possible to use the variable country_name in this statement by adding an @ as prefix
    var wdpa_ft_set  = Filter(wdpa, filterStatement) //The wdpa layer is going to be filtered by matching the fields of the name of the countries that were specified earlier.
    var prop_wdpa = 0 // this line initialises the variable prop_wdpa that will contain the proportion of protected area for a country.
    if(count(wdpa_ft_set)>0){ //this is the start of the conditional code. The code between curly brackets will only be executed if the condition count(wdpa_ft_set)>0 is true. In other words, the code will only be run if the number of features filtered (the number of protected areas the country has) is more than 0.
        var wdpa_first = First(wdpa_ft_set) // because we are working with a dissolved feature, there is only one feature of protected areas per country.
        var wdpa_area_km2 = wdpa_first['AnalysisArea'] // this variable stores the information on the protected area size
        prop_wdpa = (wdpa_area_km2/$feature.AnalysisArea) *100 // the variable prop_wdpa is updated with the division of the protected area size by the country size
    return prop_wdpa //the final result is the value of the proportion of protected area
    }
  13. Click Test. Once you're sure the expression matches the one above, click OK.

Create the second expression

You have built the first expression that provides information on the proportion of the country that is protected. You’ll add one more expression to calculate how much overlap there is between the protected areas and the areas with high rarity of birds. This last calculation will provide a protection score, like what you symbolized in the last lesson, as it is important to keep in mind the different resolutions of the rarity and the protection datasets. A simple overlay would provide a much higher protection of areas with high rarity than there is. Therefore, the calculations will consider protection of high rarity when more than 50% of the cell is protected.

  1. In the Configure Pop-up pane, for Attribute Expressions, click Add.
  2. Name the expression High Rarity Protection Score.

    This expression will calculate the proportion of the cells with more than 50 percent protection of high rarity birds.

  3. In the Expression editor, paste:
    var summ_fset = FeatureSetByName($map,"Summarize_WDPA_Rarity_89_Birds_Africa_INITIALS", ["NAME", "AnalysisArea", "SUM_Area_SquareKilometers"], false)
    var country_name = $feature.NAME 
    var filterStatement = "NAME = @country_name"
    var bird_rar_wdpa_ft_set  = Filter(summ_fset, filterStatement) 
    var sum_is_protected = 0
    for(var f in bird_rar_wdpa_ft_set){
        var f_prop = f.SUM_Area_SquareKilometers/f.AnalysisArea
        if (f_prop>=0.5){ // this statement will only take into account cells that have at least 50% of protection
            sum_is_protected +=  1
        }
    }
    var prot_score = sum_is_protected/count(bird_rar_wdpa_ft_set)
    return prot_score
  4. Replace the Summarize_WDPA_Rarity_89_Birds_Africa_INITIALS placeholder with the name of your layer.
  5. Click OK.
  6. For Pop-up Contents, next to Display, click A list of field attributes and choose A custom attribute display.

    Configure a custom display for the pop-up.

    The list of attributes disappears.

  7. Click Configure.
  8. In the Custom Attribute Display window, click Add Field Name and choose the first arcade expression you wrote, Protected Proportion.

    Add a layer attribute to the pop-up display.

    The attribute {expression/expr0} is added to the window. Now, you’ll add explanatory text.

  9. After the Expression attribute, type % of . Click Add Field Name and choose NAME, then type is designated as protected land.

    Using this syntax, each pop-up will display the result of the arcade expression for each individual country followed by the percent indicator. For example, Tanzania’s pop-up would read "38.31% of Tanzania is designated as protected land.

  10. Press Enter to start a new line, then type or paste the following:

    The country has a protection score of {expression/expr1}%, the percentage of cells with high rarity of birds that are covered by more than 50 percent protected land.

  11. Click OK.

    Completed list of attribute expressions.

  12. Click on one of the countries to see the configured pop-up.

    The title of the pop-up still shows the name of the layer, which is descriptive for analysis purposes, but too lengthy for the pop-up.

  13. For Pop-up Title, delete the name of the layer so only the {NAME} attribute remains.
  14. In the Configure Pop-up pane, click OK.
  15. Save the map.

Symbolize African countries

Finally, you'll symbolize the African countries layer so that you can show that and the Summarize WDPA Rarity 89 Birds Africa layer together. In the last lesson, you colored the cells in the Summarize WDPA Rarity 89 Birds Africa to show the percentage of the cell that was covered by protected land. To show these cells along with the pop-ups you just configured, you'll change the default blue of the country layer to just show border lines.

  1. In the Contents pane, point to Dissolve Africa Countries and click Change Style.
  2. Under Select a drawing style, click Options.

    The Change Style pane opens.

  3. Click Symbols.

    Symbols color options

  4. On the Fill tab, click No Color.

    No color fill option

    The polygons showing each country will only be shown with a border outline. Before you save your edits, you'll change the outline color.

  5. Click the Outline tab and choose a black color for the line.
  6. In the Symbols window, click OK. In the Change Style pane, click OK, then click Done to save your changes.

    Country outlines symbolized with 3 px black line.

  7. In the Contents pane, turn on the Summarize WDPA Rarity 89 Birds Africa layer.

    This layer also has pop-ups, though they haven't been configured. You'll turn them off so you see your custom pop-up when clicking on the map.

  8. Point to the Summarize WDPA Rarity 89 Birds Africa layer and click More Options. In the menu, select Remove Pop-up.

    Remove the layer's pop-up from displaying on the map.

    Finally, notice that the cells are covering up the boundary lines you just symbolized. You'll reorder the layers so that the borders draw on top of the rarity cells.

  9. Point to the Dissolve Africa Countries layer and drag it to the top of the Contents pane above Summarize WDPA Rarity 89 Birds Africa.
  10. Save the map.

Over this lesson, you used data from the Living Atlas to find areas that are most important to protect. Using the continent of Africa as an example, you calculated for each country the percent of protected land, and the proportion of the cells that have a high rarity of bird species and have land that is over 50% protected.

Using the pop-ups, you now have a first picture of the current protection status of areas with high rarity of birds across Africa. Do any of the protection scores surprise you? You can investigate further on your own by focusing on those countries with high rarity but a low protection score, and exploring the human activities taking place there. This analysis can be replicated for other places in the world. If you are interested in trying this for your country, try using the World Countries layer and the full Protected Areas dataset, linked above. The Half-Earth mapping effort uses these and other spatial patterns of biodiversity to identify locations where greater protection of species habitat is needed. This project gives you an introduction to some of the considerations involved in this process. To find out more, visit the Half-Earth Project.