See Spatial Portal Help for more information.
The spatial portal provides five analytical tools:
You can sample the values of user-selected environmental and contextual data surfaces at the geographic locations of species occurrences. This produces a spreadsheet file containing locations (rows) by environmental and contextual values (columns).
Filtering is subsetting your data using the facets on the legends in the Spatial Portal. For example, you could filter out occurrence records that came from certain institutions or filter out records that were generated before 1965.
To filter a set of occurrence records (that could include uploaded species locations with additional (facetable) fields, simply select the facet of interest from the legend dropdown box, and tick the records that you want to RETAIN.
If you want to find out where a species could occur, you need to use the environment at known species locations. Once you know what environment a species prefers, you can determine where those environmental conditions occur and would therefore expect the species to occur. This approach is called ‘niche modelling’. The spatial portal uses a modelling technique called MaxEnt developed by Steven Phillips. This method is robust for handling presence-only—data the situation where we know where a species occurs but are unsure about where it does not occur.
Input to MaxEnt is a list of species occurrences and a set of hopefully relevant environmental layers. The outputs are a probability surface map and a suite of diagnostic graphs and values.
See Prediction case study for an example of how this tool can be used.
Classification combines a set of environmental layers into one new layer that retains most of the information in all the input layers. The classification groups on the output layer are referred to as ‘environmental domains’. Each environmental domain (group) on the map is colour coded to reflect the relationships with all other domains; similar coloured groups represent similar environments.
Why is this used? The distribution of species is controlled by environmental conditions and species interactions. When there is inadequate biological data, which is most of the time, environmental domains may be a useful surrogate for biodiversity in environmental planning and management. The classification method used in the spatial portal is called ALOC from the ecological analysis package called PATN.
See Classification case study for an example of how this tool can be used.
A scatterplot is a graph of the sampled values of a pair of environmental variables from a set of species (or genus etc.) locations. Each point on the scatterplot represents the values of the pair of environmental values for a single occurrence record.
See Scatterplot case study for an example of how this tool can be used.
In the Atlas Spatial Portal, you can map:
Maps can be downloaded in various formats and an analysis can be restored by entering the analysis id displayed at the time of the run.
Most of the functions of the Atlas are written as web services. This means that most of the functions that are used on the Spatial Portal can be embedded in your own web site. For example to display a map of the Tasmanian Devil, you would use the URL http://biocache.ala.org.au/ws/density/map?q=Sarcophilus%20harrisii.
See Web Services for a list of available spatial web services.
The data supplied by our data providers determines the accuracy of features on a map, and the accuracy of occurrence locations varies greatly. Some records will only state that the species was observed in Australia while others will be accurate to within less than 5m on the ground. Named locations are generally accurate to within 100m but this will depend on the context, eg the centre of a town in 1950 will probably not be the same as it is today.
No species may be reported for your area because:
The Spatial Portal uses a variety of map layers. The basemaps come from Google, OpenStreetmap and a simple world political boundary outline map useful for publishing thumbnails of species distributions. The environmental and contextual layers come from a wide range of providers.
See http://spatial.ala.org.au/layers for a list of the layers with links to the data providers and other layer details.
Sometimes the data used to generate maps is incorrect. This may be because:
At other times the location is correct and the specimen was found in, eg a botanic garden, a reptile park or supermarket (especially with insects, frogs and other small creatures).
Yes, you can map your own list of species (taxa) or map a set of taxa locations and associated data.
The Atlas uses a globally unique identifier called a LSID (Life Science Identifier) to uniquely label taxa. The Spatial Portal can import a list of LSIDs in comma separated format. For example, the following are scientific names followed by their LSID:
You can use the Spatial Portal menu item’Add to Map > Species > Import LSIDs’ to create an assemblage of taxa as a layer in the Spatial Portal. The easy way to create the list of LSID is to use the Excel macro called getLsid.xlm at http://spatial.ala.org.au/files.
Yes, you can use the Spatial Portal menu item ‘Add to Map > Species > Upload coordinates’ to import your data. The Spatial Portal will expect Comma-Separated Variables format. The fields can either be a set of raw data in the form of ‘1d1, longitude (decimal degrees), latitude (decimal degrees)’.
Or you can upload a file with a header as first record and up to 256 additional alphanumeric fields that can be used for faceting the occurrences on the map: ID, Longitude, Latitude, Altitude, Ph, Method, Feeling 1, 149.50, -23.4, 100,7.7, feel, poorly 2, 150.4,-24.678,90.99,6.7, instrument, better.
This question can be viewed as the reverse of sampling. A user selects environmental layers of interest and lower/upper bound values for each layer. Filtering then identifies how many species are to be found within the defined environmental envelope. You can access this tool from the Spatial Portal menu item ‘Add to Map > Areas > Environmental envelope’.
Why would you want to use this tool? If, for example, you know the environment that best suits Pinot noir grapes, you can find out where in Australia (or the world) suitable conditions occur, if we have the required environmental layers.