Map with a message

In writing for conservation, ecology and related fields the use of a map to illustrate the location of a study site, the distribution of a species, the extent of a protected area, or related matters, is often essential. A well-designed map draws attention to the elements of interest rather than to peripheral information, and conveys spatial information in a clear, uncluttered and informative way. A poorly designed map confuses, and obfuscates the message.

In this chapter we demonstrate how failure to structure your graphics results in obfuscation of a map’s message, introduce a useful range of freely available map data, introduce the geographical information system QGIS and some techniques to facilitate mapping (including video tutorials), and provide case studies of good map design, with a video tutorial.

Don’t obfuscate the message

There is more than one way to draft a map. The following variations on Figure 1 from Hoffmann et al. (2015) illustrate the effects of a range of questionable design decisions—all of which can be commonly encountered in the literature—and how they obfuscate the map’s message. Each variation compromises one or more of the principles for good map design.

Figure 20: Latitude and longitude ticks outside bounding box The size of the area of interest (i.e. the original extent of the forest and the location of the seed collection sites) has to be reduced to accommodate the outward-pointing tick marks and their labels, compromising simplicity, legibility and good composition. Only in a large and complex map may it be necessary to place these elements outside the bounding box.

__Latitude and longitude ticks outside bounding box__ The size of the area of interest (i.e. the original extent of the forest and the location of the seed collection sites) has to be reduced to accommodate the outward-pointing tick marks and their labels, compromising simplicity, legibility and good composition. Only in a large and complex map may it be necessary to place these elements outside the bounding box.

Figure 21: A continental country is not an island International borders have not been included on either the main or inset map, potentially confusing for a reader not familiar with the geography of South America. As well as compromising legibility and good composition, omission of international borders misrepresents a continental country as an island.

__A continental country is not an island__ International borders have not been included on either the main or inset map, potentially confusing for a reader not familiar with the geography of South America. As well as compromising legibility and good composition, omission of international borders misrepresents a continental country as an island.

Figure 22: Area of interest too small The area of interest—the original forest extent and the seed collection sites—should occupy a greater proportion of the map space. This compromises four of our design principles: a clear visual hierarchy, legibility, accessibility and good composition.

__Area of interest too small__ The area of interest---the original forest extent and the seed collection sites---should occupy a greater proportion of the map space. This compromises four of our design principles: a clear visual hierarchy, legibility, accessibility and good composition.

Figure 23: Inappropriate choice of symbol Symbols should be chosen for their simplicity. A star symbol is more complex than a circle symbol and should be used only after exhausting other possibilities. The star lies further down the hierarchy of choices, at least below circle, square and triangle. Its use here compromises simplicity and good composition.

__Inappropriate choice of symbol__ Symbols should be chosen for their simplicity. A star symbol is more complex than a circle symbol and should be used only after exhausting other possibilities. The star lies further down the hierarchy of choices, at least below circle, square and triangle. Its use here compromises simplicity and good composition.

Figure 24: Graphic not clear The resolution is too low and thus the image is not sharp. This problem typically results from designing or exporting a figure in raster rather than vector format, combined with a lack of understanding of how the resolution of a raster graphic influences sharpness. In raster format, a figure requires a minimum resolution of 600 PPI. In this case the resolution is too low, and thus legibility and accessibility are compromised and the intended message is not conveyed clearly.

__Graphic not clear__ The resolution is too low and thus the image is not sharp. This problem typically results from designing or exporting a figure in raster rather than vector format, combined with a lack of understanding of how the resolution of a raster graphic influences sharpness. In [raster format](#raster-graphics){class="toc"}, a figure requires a minimum resolution of 600 PPI. In this case the resolution is too low, and thus legibility and accessibility are compromised and the intended message is not conveyed clearly.

Figure 25: No bounding box / no latitude and longitude tick marks / dangling geographical lines. Good composition and accessibility are compromised by the absence of a bounding box and latitude and longitude information, and by the dangling geographical lines.

__No bounding box / no latitude and longitude tick marks / dangling geographical lines__. Good composition and accessibility are compromised by the absence of a bounding box and latitude and longitude information, and by the dangling geographical lines.

Figure 26: Unnecessary connecting line The connecting line between the inset and the main map is unnecessary, compromising simplicity and good composition. The arrow is intended to indicate that the rectangle on the inset represents the position of the geographical area of the main map, but the clearly visible rectangle is self-explanatory.

__Unnecessary connecting line__ The connecting line between the inset and the main map is unnecessary, compromising simplicity and good composition. The arrow is intended to indicate that the rectangle on the inset represents the position of the geographical area of the main map, but the clearly visible rectangle is self-explanatory.

Figure 27: No legend The absence of a legend hinders interpretation of the figure. The viewer has to read the caption to ascertain that the white-filled circles represent the sites where seeds were collected. This complicates the presentation of the message, compromising simplicity.

__No legend__ The absence of a legend hinders interpretation of the figure. The viewer has to read the caption to ascertain that the white-filled circles represent the sites where seeds were collected. This complicates the presentation of the message, compromising simplicity.

Figure 28: Overly thick lines Overly thick lines are ugly, noisy and distracting, compromising both a clear visual hierarchy and good composition. A line thickness of 0.1–0.3 mm is typically suitable for schematic maps. Some of these lines are, however, 0.5 mm thick.

__Overly thick lines__ Overly thick lines are ugly, noisy and distracting, compromising both a clear visual hierarchy and good composition. A line thickness of 0.1--0.3 mm is typically suitable for schematic maps. Some of these lines are, however, 0.5 mm thick.

Figure 29: Scale bar oversized and with unusual divisions / unnecessary north arrow Oversized scale bar compromises the visual hierarchy and unusual, non-standard divisions compromise simplicity. The map is not for navigation and therefore the north arrow is unnecessary (the latitude and longitude tick marks indicate orientation). However, if north is not at the top of the figure (e.g. the figure includes a sampling grid that was not oriented north–south but you wish to orient the grid vertically in the figure), inclusion of a north arrow could be warranted.

__Scale bar oversized and with unusual divisions / unnecessary north arrow__ Oversized scale bar compromises the visual hierarchy and unusual, non-standard divisions compromise simplicity. The map is not for navigation and therefore the north arrow is unnecessary (the latitude and longitude tick marks indicate orientation). However, if north is not at the top of the figure (e.g. the figure includes a sampling grid that was not oriented north--south but you wish to orient the grid vertically in the figure), inclusion of a north arrow could be warranted.

Figure 30: No font hierarchy Absence of a font hierarchy (all elements are labelled with text of the same font size) compromises a clear visual hierarchy and obscures the message, and inconsistent use of serif and sans serif fonts compromises consistency.

__No font hierarchy__ Absence of a font hierarchy (all elements are labelled with text of the same font size) compromises a clear visual hierarchy and obscures the message, and inconsistent use of serif and sans serif fonts compromises consistency.

Figure 31: Too many tick marks / tick marks too long / inappropriate divisions Compromises simplicity and good composition.

__Too many tick marks / tick marks too long / inappropriate divisions__ Compromises simplicity and good composition.

Figure 32: Combination of several poor design decisions Too much information obfuscates the message, which is on the map, but where? This type of over-designed map can be regularly encountered in the conservation and ecology literature.

__Combination of several poor design decisions__ Too much information obfuscates the message, which is on the map, but where? This type of over-designed map can be regularly encountered in the conservation and ecology literature.

Locating spatial data

The starting point for drafting a map is one or more base data layers—such as national or adminstrative boundaries, water bodies, roads or relief—for geographical context. Many of the most useful sources of map data are freely available (Table 12). The sections below describe and illustrate each in turn.

Table 12: Sources of freely available base, ecological, environmental and satellite imagery map layers. The 1:2 million data provided by DIVA is an earlier version of the data provided by GADM, so in most cases it is advisable to use the latter. The Earth System Grid Federation climate predictions are available at several nodes.

Data Format Source
Background map data
1:2 million global data Vector DIVA–GIS
1:2 million global data Vector, raster GADM
1:2, 1:10, 1:110 million global data Vector, raster Natural Earth
Biodiversity Hotspots Vector Critical Ecosystem Partnership Fund
Climate
Past, current & predictions Raster WorldClim
Model predictions Raster Earth System Grid Federation
Digital elevation Raster CGIAR
Ecoregions
Global 200 Ecoregions Vector Global 200
Terrestrial Ecoregions Vector Terrestrial Ecoregions of the World
Protected areas Vector Protected Planet
Satellite imagery Raster USGS Earth Explorer
Shaded relief and hillshade
Shaded relief Raster Natural Earth, ESRI
Hillshade Raster ESRI
Species range data Vector IUCN Red List

Background map data

1:10 million scale maps of northern Madagascar using the 1:110, 1:50, 1:10 million [Natural Earth](http://www.naturalearthdata.com/){target="_blank"} data and the 1:2 million [GADM](https://gadm.org/){target="_blank"} data.Figure 33: 1:10 million scale maps of northern Madagascar using the 1:110, 1:50, 1:10 million Natural Earth data and the 1:2 million GADM data.

Natural Earth provides global vector and raster data designed for maps at scales of 1:10, 1:50 and 1:110 million; i.e. maps for which 1 cm on a scale bar represents 100, 500 and 1,100 km, respectively. DIVA-GIS provides global and country-level vector and raster data suitable for maps at a scale of 1:2 million (i.e. for which 1 cm on a scale bar represents 20 km). The vector data provided by Natural Earth and DIVA are in the popular shape file format.

It is important to choose data of the correct scale. The 1:10 million scale maps in Figure 33 show the same geographical area using the 1:110, 1:50 and 1:10 million Natural Earth data and the 1:2 million GADM data. The data intended for mapping at scales of 1:110 and 1:50 million produce geographical lines that are too coarse—resulting in maps in which the geographical area is barely recognizable—and using data suitable for mapping at a scale of 1:2 million produces geographical lines that are too fine and therefore run together in a manner that is not visually pleasing.

As a general guide the Natural Earth 1:10 million scale data are suitable for a country-scale map and the 1:50 million scale data are suitable for an inset map of a continent or part thereof. For a map of the world at postcard size, the 1:110 million scale data are ideal. For a map of part of a country the finer-scale GADM/DIVA data may be a better choice (depending on the size of the country).

Madagascar and south-eastern Africa, shown with the 1:10 million cross-blended hypsometric tints raster layer from [Natural Earth](http://www.naturalearthdata.com){target="_blank"}.Figure 34: Madagascar and south-eastern Africa, shown with the 1:10 million cross-blended hypsometric tints raster layer from Natural Earth.

The Natural Earth data layers align precisely with one another (e.g. where rivers and country borders are the same, the lines are coincident) and therefore result in neat maps. The Natural Earth and GADM/DIVA data layers do not necessarily align with one another, however, and care is required in mixing data layers from these two sources on the same map.

The Natural Earth 1:10 and 1:50 million raster layers also register precisely with the respective vector data, and include land cover, shaded relief, oceans and drainages with lakes. The cross-blended hypsometric tints data provide shaded relief combined with custom elevation colours based on climate—humid lowlands are green and arid lowlands brown. The map colours gradually blend into one another across regions and from lowlands to highlands. Figure 34 combines the 1:10 million cross-blended hypsometric tints raster layer with the 1:10 million country vector layer.

Biodiversity hotspots of Madagascar and south-eastern Africa (data from [Critical Ecosystem Partnership Fund](https://www.cepf.net/our-work/biodiversity-hotspots/hotspots-defined){target="_blank"}).Figure 35: Biodiversity hotspots of Madagascar and south-eastern Africa (data from Critical Ecosystem Partnership Fund).

Biodiversity hotspots

Myers et al. (2000) identified 25 global biodiversity hotspots, since expanded to a total of 36, where exceptional concentrations of endemic species are undergoing exceptional loss of habitat (Figure 35). To qualify as a hotspot a region has to contain at least 1,500 endemic species of vascular plants and to have 30% or less of its original vegetation remaining.

Climate

Madagascar and south-eastern Africa mean March precipitation (data from [WorldClim](http://worldclim.org/){target="_blank"}).Figure 36: Madagascar and south-eastern Africa mean March precipitation (data from WorldClim).

Hijmans et al. (2005) developed interpolated climate surfaces for global land areas (Figure 36), available at WorldClim, in raster format. Data are available for current (c. 1950–2000), future (2050 and 2070) and past (mid Holocene, c. 6,000 years ago, and Last Glacial Maximum, c. 22,000 years ago) conditions at resolutions of 30 seconds (c. 1 km2), and 2.5, 5 and 10 arc-minutes (10 arc-minutes is c. 340 km2). Data include average monthly mean, minimum and maximum temperature and precipitation, and 19 bioclimatic variables derived from the monthly temperature and rainfall values.

The Earth System Grid Federation provides climate model output and observational data from the Coupled Model Intercomparison Project. These data are summarized by the Intergovernmental Panel on Climate Change in their assessment reports, and the data, including scenarios based on representative concentration pathways of greenhouse gas concentration, are available for modelling.

High resolution topography of northern Madagascar, using SRTM data from [CGIAR](https://cgiarcsi.community/){target="_blank"} combined with a  [digital elevation model](https://ieqgis.wordpress.com/2015/04/04/create-great-looking-topographic-maps-in-qgis-2/){target="_blank"} and [hillshade](https://ieqgis.wordpress.com/2017/09/02/adding-esris-world-hillshade-layer-to-qgis/){target="_blank"} as a [map service](https://services.arcgisonline.com/arcgis/rest/services/Elevation/World_Hillshade/MapServer/0){target="_blank"}.Figure 37: High resolution topography of northern Madagascar, using SRTM data from CGIAR combined with a digital elevation model and hillshade as a map service.

Digital elevation

The CGIAR Consortium for Spatial Information provides satellite radar topography mission digital elevation data at a spatial resolution of c. 30 m on the line of the Equator, in tiles of 5 × 5 and 30 × 30 degrees. This has several uses, including production of high resolution topographic maps (Figure 37).

Ecoregions

Ecoregions of Madagascar and south-eastern Africa (data from [Terrestrial Ecoregions of the World](https://www.worldwildlife.org/publications/terrestrial-ecoregions-of-the-world){target="_blank"}).Figure 38: Ecoregions of Madagascar and south-eastern Africa (data from Terrestrial Ecoregions of the World).

Olson & Dinerstein (2002) identified the Global 200 ecoregions that feature particular species richness and endemic species, unusual higher taxa, unusual ecological or evolutionary phenomena, and global rarity of habitats. The Global 200 actually comprises 238 (142 terrestrial, 53 freshwater and 43 marine) priority ecoregions, available as three shapefiles, one each for terrestrial, freshwater and marine ecoregions.

The Terrestrial Ecoregions of the World (Olson et al., 2001) is a biogeographical regionalization of the original distribution of distinct assemblages of species and communities, available as a single shape file containing all 867 terrestrial ecoregions, classified into 14 biomes (e.g. forests, grasslands, deserts; Figure 38). An ecoregion is defined as ‘relatively large units of land or water containing a distinct assemblage of natural communities sharing a large majority of species, dynamics, and environmental conditions’.

Protected areas

Protected areas of Madagascar and south-eastern Africa (data from [Protected Planet](https://www.protectedplanet.net){target="_blank"}).Figure 39: Protected areas of Madagascar and south-eastern Africa (data from Protected Planet).

Protected Planet provides access to the World Database on Protected Areas, which contains global data for individual protected areas (Figure 39). The complete database is available for non-commercial use, but the shapefile is large and may take a long time to download, depending on the speed of your connection, and may be slow to display. You can, however, download shapefiles of individual protected areas. An alternative is to use the database as a map service.

Protected areas of Madagascar and south-eastern Africa (Figure \@ref(fig:Madagascar-PAs)) combined with shaded relief as a [map service](https://services.arcgisonline.com/ArcGIS/rest/services/World_Shaded_Relief/MapServer/0){target="_blank"}.Figure 40: Protected areas of Madagascar and south-eastern Africa (Figure 39) combined with shaded relief as a map service.

Shaded relief and hillshade

Shaded relief can be used to add visually pleasing topographical context (Figure 40). Natural Earth provides shaded relief in raster format at 1:10 and 1:50 million, and World Shaded Relief is available as a map service that can be added as a map layer. Figure 40 combines protected areas with shaded relief. Partial transparency is used to make the shaded relief visible beneath the other map layers.

The Hillshade map service portrays elevation as an artistic hillshade. It can be used on its own, or in combination with shaded relief (Figure 37), to add topographical context.

Species range data

Range of the Near Threatened brown lemur _Eulemur fulvus_, in northern Madagascar, combined with shaded relief as a [map service](https://services.arcgisonline.com/ArcGIS/rest/services/World_Shaded_Relief/MapServer/0){target='_blank'}.Figure 41: Range of the Near Threatened brown lemur Eulemur fulvus, in northern Madagascar, combined with shaded relief as a map service.

Range data (Figure 41) are available for species whose conservation status has been assessed for the IUCN Red List, individually by species and, in some cases, by taxonomic group.

Introducing QGIS

The geographical information system QGIS has many strengths, including the facility to produce publication quality maps. QGIS has extensive facilities for spatial analysis but here we focus on its facilities for mapping.

To install QGIS, download the appropriate package for your system. Documentation includes a User Guide, Training Manual and, for beginners, a useful Gentle Introduction to geographical information systems. If you are new to QGIS, Natural Earth provides a quick start kit that includes a sample of themes styled in a QGIS project file. Download the kit, unzip it, and then open the required project file (i.e. that with the extension ‘.qgs’).

The following sections, each of which includes a video tutorial, provide an introduction to using QGIS and to some of the most useful tools for the preparation of publication-ready map figures.

Layers and projections
Importing data
Filtering and selecting a subset of features
Adding a map service
Tidying up

Layers and projections

To construct a map, data are added in layers. A typical map includes one or more background layers (e.g. boundaries of the country or region of interest, rivers or other physical features, locations of urban centres, land cover) and one or more layers containing the data of interest (e.g. location of a study site, survey transects, presence/absence of a species). Background map layers for countries, country-level administrative areas, rivers, roads, urban areas, protected areas and other spatial data, are available and therefore you will not usually need to prepare these yourself. Most map layers are in vector format, as a shapefile. Land cover data and satellite imagery are in raster format, typically as GeoTIFF.

Vector and raster map layers are usually in decimal degrees of latitude and longitude (i.e. of the form 4.5° rather than 4°30’) and based on the World Geodetic System (WGS) 84 standard. To create a map these data have to be projected (i.e. represented on the plane) and a coordinate reference system used to define how the two-dimensional, projected map relates to real locations. There are three main families of projections (cylindrical, conical and planar) and a bewildering number of coordinate reference systems.

For the preparation of an illustrative map we can narrow the selection. At the scale of a country or small region, the Universal Transverse Mercator (UTM) coordinate reference system, which is a cylindrical projection, is generally the best choice. It divides the earth between 84°N and 80°S latitude into 60 zones, each of 6° of longitude. The zone for any particular area can be determined from a UTM zone map (Figure 42). For example, most of Madagascar lies in zone 38S (i.e. 38 south). The QGIS documentation provides advice on choosing a suitable projected coordinate system, and on working with projections in QGIS.

The 60 numbered UTM zones, each of which is 6° of longitude.

Figure 42: The 60 numbered UTM zones, each of which is 6° of longitude.

Figure 43: QGIS Fundamentals demonstrates how to obtain and store map data, create a new QGIS project, add vector and raster data layers, and set the project’s coordinate reference system.

Importing data

When adding your own data to a map, any points (e.g. location of signs of a species), lines (e.g. location of survey transects) or polygons (e.g. the area surveyed) need to be in decimal degrees.52 If the data have been collected in degrees and minutes, or degrees minutes seconds, convert them using degrees + (minutes/60) + (seconds/3600). For how to import data (e.g. the path of a transect or survey) from a GPS, see the QGIS documentation.

Figure 44: Import Delimited Text Layer demonstrates how to import latitude and longitude data in CSV (comma separated values) format and save the data as a new shapefile.

Filtering and selecting a subset of features

If a shapefile has many features you may wish to display only a subset on a map. You can do this either by applying a filter or by selecting features and then saving the selection as a new shapefile.

Figure 45: Filtering and Selecting demonstrates how to use these two methods to display the protected areas in a single country from the World Database of Protected Areas.

Adding a map service

A data layer can also be added from a map service, and will automatically scale as you rescale a project. You need to connect to a map service to display it as a layer (i.e. you cannot display the layers if you are offline). A useful layer to add for geographical context is world shaded relief.

Figure 46: Adding a Map Service demonstrates how to add the world shaded relief map service, and how to combine it with layer transparency.

Tidying up

Juxtaposition of data from different sources—such as the 1:10 million scale data from Natural Earth with data from the World Database on Protected Areas—may result in misalignment of geographical lines and thus an untidy and potentially confusing map. One way to resolve this untidiness is to clip the features of one layer by those of a second layer.

Figure 47: Clipping demonstrates how to clip one layer with another.

Map studies

The following map studies illustrate the design of a range of map figures, each of which presents a particular type of data. The design of these figures avoids obfuscation of the respective messages by adhering to our design principles.

Location of the study site at LuiKotale, on the south-western edge of Salonga National Park, Democratic Republic of the Congo (a modified version of Figure 1 in @beauneWhatWouldHappen2015).Figure 48: Location of the study site at LuiKotale, on the south-western edge of Salonga National Park, Democratic Republic of the Congo (a modified version of Figure 1 in Beaune (2015)).

Study 1 A single site (with video tutorial)
Study 2 Several sites
Study 3 Species occurrence
Study 4 Protected areas
Study 5 Several types of site
Study 6 Variable symbol size

Study 1 A single site

As this study (Figure 48) is at a scale of c. 1:16 million we use 1:10 million data for the main map, and 1:50 million data for the inset map, all from Natural Earth (Table 12).

Figure 49: Map Study 1 demonstrates how to draft Figure 48 in QGIS.

Greyscale version of Figure \@ref(fig:map-study-1).Figure 50: Greyscale version of Figure 48.

Message The study site at LuiKotale lies on the south-eastern edge of Salonga National Park in the Democratic Republic of the Congo, in central Africa.

The figure is interpretable in greyscale (Figure 50) without requiring modification, and the following additional points are of note:

  • The study site at LuiKotale does not have a fixed size and therefore a rectangle, not to scale, is centred on the location.

  • A raster land-cover layer (cross-blended hypsometric tints) provides geographical context.

Locations where tree seeds were collected in fragments of the Araucaria moist forest in southern Brazil, and the original extent of this forest type (a modified version of Figure 1 in @hoffmannIdentifyingTargetSpecies2015).Figure 51: Locations where tree seeds were collected in fragments of the Araucaria moist forest in southern Brazil, and the original extent of this forest type (a modified version of Figure 1 in Hoffmann et al. (2015)).

Study 2 Several sites

As this study (Figure 51) is at a scale of c. 1:10 million we use 1:10 million data for the main map, and 1:50 million data for the inset map (both from Natural Earth; Table 12), and shaded relief, as a map service, in combination with partial transparency (70%) on the 1:10 million layer, to provide geographical context. The original extent of the Araucaria moist forest is an ecoregion and therefore we use the appropriate polygon from Terrestrial Ecoregions of the World (Table 12).

Message The 26 seed collection sites lie within the original extent of the Araucaria moist forest, which spans the southern Brazilian states of São Paulo, Paraná, Santa Catarina and Rio Grande do Sul; these states border Argentina and Paraguay in South America.

The ways in which this figure adheres to our design principles is described in Applying the framework to a map.

Sites surveyed for the Eurasian otter _Lutra lutra_ in Albania in 2013 (a modified version of Figure 1 in @balestrieriEurasianOtterLutra2016).Figure 52: Sites surveyed for the Eurasian otter Lutra lutra in Albania in 2013 (a modified version of Figure 1 in Balestrieri et al. (2016)).

Study 3 Species occurrence

As this study (Figure 52) is at a scale of c. 1:3 million we use the 1:2 million GADM data for the main map, and the 1:50 million Natural Earth data for the inset map (Table 12).

Message In a survey of a total of 73 sites in the major river catchments of Albania (which lies in the eastern Mediterrean, bordering Montenegro, Serbia, Macedonia and Greece) signs of the European otter Lutra lutra were found at 43 sites.

The figure is interpretable in greyscale (Figure 53) without requiring modification, and the following additional points are of note:

A greyscale version of Figure \@ref(fig:map-study-3).Figure 53: A greyscale version of Figure 52.

  • Black- and white-filled circles are used to indicate presence and absence, respectively (this is more intuitive than the contrary).

  • Rivers and their labels, and other water bodies, are denoted, intuitively, in blue.

  • Rivers in neighbouring countries are not shown, to focus attention on Albania and avoid an overly noisy figure.

Study 4 Protected areas

As this study (Figure 54) is at a scale of c. 1:10 million we use 1:10 million data for the main map, and 1:50 million data for the inset map (both from Natural Earth (Table 12), and shaded relief, as a map service, in combination with partial transparency on the 1:10 million layer, to provide geographical context.

Designated and proposed protected areas in Liberia, West Africa (a modified version of Figure 1 in @greengrassCommercialHuntingSupply2016).Figure 54: Designated and proposed protected areas in Liberia, West Africa (a modified version of Figure 1 in Greengrass (2016)).

Message There are two designated and 14 proposed protected areas in Liberia, West Africa. The map indicates their locations (two lie close to the capital, Monrovia).

The figure is interpretable in greyscale (Figure 55) without requiring modification, and the following additional points are of note:

  • Protected areas are denoted, intuitively, in green, and designated protected areas in a darker shade.

  • Labels for the designated areas have the same font size, which is larger than the labels for other elements.

Greyscale version of Figure \@ref(fig:map-study-4).Figure 55: Greyscale version of Figure 54.

Study 5 Several types of site

As this study (Figure 56) is at a scale of c. 1:10 million we use 1:10 million data for the main map, and 1:50 million data for the inset map (both from Natural Earth; Table 12), and shaded relief, as a map service, in combination with partial transparency on the 1:10 million layer, to provide geographical context. The vector layer for Bénoué National Park is from Protected Planet (Table 12). The locations of the tourist camps, cattle watering, poaching and camps/sites of gold diggers were obtained in decimal degrees, with a GPS, and imported in CSV format.

Human activity recorded in Bénoué National Park, Cameroon, during February–March 2013 (a modified version of Figure 1 in @scholteDecliningPopulationVulnerable2016).Figure 56: Human activity recorded in Bénoué National Park, Cameroon, during February–March 2013 (a modified version of Figure 1 in Scholte & Iyah (2016)).

Message Various signs of human activity (tourist camps, watering of cattle, poaching, and camps and sites of gold diggers) were found along the section of the Bénoué river that lies along the border of Bénoué National Park, Cameroon.

Geyscale version of Figure \@ref(fig:map-study-5).Figure 57: Geyscale version of Figure 56.

The figure is interpretable in greyscale (Figure 57) without requiring modification, and the following additional points are of note:

  • Bénoué National Park is denoted, intuitively, in green, and hunting zones in a paler shade.

  • Labels for the protected area and the hunting zones have the same font size and weight as they are equally important parts of the message (and this font size is larger than that of other elements), and they are positioned as centrally as possible within their respective elements, with lettering spaced to emphasize extent.

  • The four types of human activity (tourist camps, watering of cattle, poaching, and camps and sites of gold diggers) are equally important in the message and their symbols therefore have the same size.

Study 6 Variable symbol size

As this study (Figure 58) is at a scale of c. 1:10 million we use 1:10 million data from Natural Earth (Table 12), and shaded relief, as a map service, in combination with partial transparency on the 1:10 million layer, to provide geographical context. The vector layer for Bénoué National Park is from Protected Planet (Table 12). The locations of the hippopotamuses were obtained in decimal degrees, with a GPS, and imported in CSV format.

Figure 58: Distribution of hippopotamus Hippopotamus amphibius in Bénoué National Park, Cameroon (a) in July 2011 (rainy season) and (b) during February–March 2013 (dry season) (a modified version of Figure 3 in Scholte & Iyah (2016)).

Distribution of hippopotamus _Hippopotamus amphibius_ in Bénoué National Park, Cameroon (a) in July 2011 (rainy season) and (b) during February–March 2013 (dry season) (a modified version of Figure 3 in @scholteDecliningPopulationVulnerable2016).

Message In 2011 hippopotamuses were found at a number of locations along the section of the Bénoué river that lies along the border of Bénoué National Park, but in 2013 hippopotamuses were generally only found in the vicinity of four tourist camps, where they received some protection.

The figure is interpretable in greyscale (Figure 59) without requiring modification, and the following additional points are of note:

Figure 59: Greyscale version of Figure 58.

Greyscale version of Figure \@ref(fig:map-study-6).
  • Bénoué National Park is denoted, intuitively, in green, and hunting zones in a paler shade.

  • The number of hippopotamuses at each location was used to scale the circle symbol.

  • Labels for the protected area and the hunting zones have the same font size and weight as they are equally important parts of the message (and this font size is larger than that of other elements), and they are positioned as centrally as possible within their respective elements, with lettering spaced to emphasize extent.

  • The same font size and weight is used for the four tourist camps as they are all equally important for the message.

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