5.1 Representing vegetation and animal distributions
In order to be able to manage biodiversity resources, we need to be able to store information about both plants and animals within our GIS. Such data can be held either for individual species or for groups of species forming a vegetation community.
GIS data for individual species or taxonomic groups
GIS species maps will typically either show the presence or absence of a species or its abundance. Presence / absence maps show the range of a species – the limits of its geographical distribution. Abundance data indicate how many individuals are present at a given location.
The underlying data sources for species maps can be quite varied. In the field, technology now exists to track the movements of individual animals using radar-tracking, GPS collars, and ecological fieldwork. However, only a small number of individuals can be tracked in this way. More commonly, field ecologists may record sightings of individual plants or animals using GPS at static locations. For more elusive species, ecologists may record indirect signs of an animal’s presence. For example, the call of males in the breeding season has been used to map the distribution of the paradise fly-catcher, a rare bird endemic to the Seychelles. In other cases, animal tracks or spoors may be recorded as an indicator of an animal’s presence. For example, otter spraints (droppings) have been used by Scottish Natural Heritage to map the distribution of otters along Scottish coastlines. In a few instances, large mammals have been surveyed using remote sensing techniques. For instance, observers in spotter planes have recorded the number of large African mammals visible over particular time intervals along a given flight-path.
Small areas may be completely surveyed in the field. For example, it may be possible to survey the locations of all standing trees within a small, 2 hectare woodlot. However, in many cases, it may be infeasible to survey an area for a given species or taxa (group of species) in its entirety. In such cases, field observations may only exist for transects or quadrats covering a small sample of the study area. A transect is a straight line surveyed by a field ecologist to assess plant or animal distributions, whilst a quadrat is a sampling unit consisting of a square frame of a given size. To map the species distribution across the whole area (not just the locations that were surveyed), it may be necessary to look statistically at the relationship between the sampled areas where the species is present and other factors, such as slope, elevation, or distance from roads. If any strong relationships exist, these may be used within a GIS to produce a species distribution map for the whole study area.
Many species maps are derived from older records that pre-date technologies such as GPS. For example, the distribution of a rare orchid may be mapped based on the notes accompanying samples in herbarium collections (see, for example, the Kew Gardens GIS web site below). A particular orchid specimen may be recorded as coming from a certain mountain or near a given settlement. The name of this mountain or settlement has to be located on a digital map of place-names through a geo-coding exercise. In many cases, it may be difficult to find the place-names used in herbarium records and where place-names are found, they may provide only a very approximate indication of a specimen’s location (e.g. to within 10 or 20km of its true position). Once the locations of many such specimens have been plotted on the map, then the resultant dot map is converted into a species range map through expert interpretation. This expert interpretation will often make use of knowledge about a species habitat preferences and patterns of climate and vegetation within a region. This process can be highly subjective and the final species range map produced may depend in part on the skill and expertise of the ecologist who produced it.
GIS data concerning vegetation communities
GIS data concerning vegetation communities – assemblages of plants often found together – typically come from two sources:
- Remotely sensed data sources, such as satellite imagery: Well known examples of such data include the Land Cover Map 2000 (see references), as well as several worldwide land cover maps based on AVHRR data (a sample of such data is included in the GIS exercise below).
- Ecological field surveys: In the UK, one of the most commonly used systems for classifying vegetation is the National Vegetation Classification (NVC) and this is often used in ground-based surveys of vegetation.
Remotely sensed vegetation data sets and those derived from ground-based surveys often use different vegetation classifications. A remotely sensed classification typically groups together vegetation that share similar patterns of reflected light, which are detectable from the air or space. A ground-based classification may depend on the presence or absence of a single species, not detectable from the air or from space and only apparent to a field ecologist. For example, the National Vegetation Classification system distinguishes ‘Lowland mixed broadleaved woodland with bluebell’ (NVC class W10) from ‘Lowland mixed broadleaved woodland with dog’s mercury’ (NVC class W8). Distinguishing these two types of vegetation from a satellite image would be very difficult.
In the UK, spatial ecological data for both individual species, taxonomic groups, and vegetation communities are held by the Biological Records Centre (BRC) in Cambridge, as well as local BRCs throughout the country (see below).
Download the attached data set, which contains data on the distribution of blue grouse and elk for the state of Montana in the USA, as well as meta-data describing the origins of these data. Inspect the data and the related meta-data in your GIS software.
Alternatively, if you prefer, you can download and explore data concerning ‘red list’ species, which are maintained by the International Union for Conservation of Nature (IUCN). The ‘red list’ not only indicates species and their status (e.g. critically endangered; endangered; vulnerable), but uses data concerning threads, conservation actions and the spatial distribution of a species to inform these categories. These relationships are explained here: https://nc.iucnredlist.org/redlist/content/attachment_files/summary_sheet_en_web.pdf.
To explore an example of the data used, go to the web site for the International Union for Conservation of Nature: https://www.iucnredlist.org/
In the search box, search for ‘Panthera tigris’ – the tiger. Once the species is returned by the search, click on the ‘Download’ button then choose ‘range (shape file)’. Use this web link if you have difficulty finding the species: https://www.iucnredlist.org/species/15955/50659951.
To download the species distribution data, you will need to register and create an IUCN account, indicating that you plan to use the data for educational purposes. Having downloaded the range shapefile, unzip the files and view them (and their table of attributes) in ArcGIS Desktop or Pro.
Note that you can also download species distributions for taxa here too: https://www.iucnredlist.org/resources/spatial-data-download. Note that not all taxa will have a corresponding range map, unlike the tiger.
For some species (but not the tiger data), alongside the range data, there will also be points representing locations where the species has been found to occur. Typically, two measures are derived from these points. One is ‘Extent of Occurrence’, which can be calculated by software produced by IUCN, but also by the GeoCat software produced by the Royal Botanic Gardens at Kew (see http://geocat.kew.org/). ‘Extent of Occurrence’ (EOO) and a second measure Area of Occupancy (AOO) are often calculated, which are described at the web sites below:
Imagine that you have been asked to try and predict the types of habitat preferred by the blue grouse (or the elk) or one of the IUCN red list species, such as whether it prefers high or low elevation ground or particular vegetation types. Do you think that the data you have explored would be appropriate for this task? Why / why not? Post your thoughts to the course web site.
References (Essential reading for this learning object indicated by *)
For some other examples of species distribution data, see the National Biodiversity Network gateway atlas: https://nbnatlas.org/.
A second example is the Global Biodiversity Information Facility: http://www.gbif.org/. In both cases, you can create an account for yourself and download species distribution data.
You can find out more about the Land Cover Map 2000 and the associated Countryside Information Survey from the Centre for Ecology and Hydrology web site: http://www.ceh.ac.uk/services/land-cover-map-2000