How to use some of the functions of the Spatial Portal are covered in the User Guides. User Guides 2, 3, 7, 8 and 10 outline steps.
The Spatial Portal provides a range of analytical tools that demonstrate the value of integrating spatial information:
In the Atlas Spatial Portal, you can map:
Maps can be downloaded in various formats and the status of mapped layers as generated from any combination of analyses can be restored by entering the web address (URL) supplied when you click “Save session”.
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 spatial accuracy of occurrence locations varies greatly. Some records will only state that a species was observed in Australia while others will be accurate to within less than 5m on the ground. The Darwin Core term coordinateUncertaintyInMeters, where available, can help you view spatial accuracy. You can examine many of the Darwin Core terms for mapped occurrence records using the Spatial Portal’s legend
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 over 60 international and national agencies. See http://spatial.ala.org.au/layers for a list of the layers with some metadata containing links to the data providers.
There are two types of layers in the Spatial Portal, environmental layers that contain continuous values (e.g., temperature, ph) and contextual layers that contain class values (e.g., states and territories, bioregions).
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). In some cases, these ‘outliers’ can in fact be real extensions to the range of the species. All related information to the occurrence needs to be examined to see if it is an error of some type or a genuine observation.
Yes, you can use the lists portal to create a list of any combination of species and use that list in a variety of places in the Atlas. To create a List, you will need to have a login as the List is stored against your name. The List can simply be a set of species names, one per line in a CSV file. Names should be the standard genus species pair, e.g., Eucalyptus gunnii.
The Atlas matches the uploaded names against the National Species List. Any unmatched names are flagged. You can then use the Google search option to find out more about any of the unmatched names.
Once the List has been created, you can share administration of it with any other registered users. The choice is yours.
When the list has been created, it can be used in the Spatial portal anywhere a species can be entered; use “Use existing species list”.
There are two special types of species lists, “Invasive” and “Threatened” that are set by the overall List administrator. “Invasive” is a flag on a list that says that the taxa in the list have been designated by someone somewhere in the Australian region. Likewise, the “Threatened” flag means that the list of taxa have been considered to have some form of sensitivity to extinction somewhere in the Australian region.
Yes, you can map your own list of species (taxa) or map a set of taxa locations and associated data. All that is required is a CSV-formatted file with the records starting with three values
and then any number of optional values that you may want to filter/display on. Those additional fields can be either alpha or numeric. We would strongly suggest that you use a header on the CSV file where the names match the Darwin Core terms.
Use the Spatial Portal menu item Import | Points
This can easily be done with any combination of the environmental layers in the Spatial Portal. Use the menu item Add to Map > Areas > Environmental envelope and then select a layer of interest and then set the lower/upper bound values. The selection will feedback the total number of taxa within those bounds. After you accept these bounds, you can then add another environmental layer and continue the filtering until the combination of environmental parameters are fulfilled.
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 if the environment layers have world extent) suitable conditions occur (see the Pinot case study), if we have the required environmental layers.
If you want to find out what biologically related data is within a defined area, then area reports in the Spatial Portal can deliver. An area can be defined by any one of 15 different options. For example, you can use the gazetteer to lookup say “Royal National Park” and then use that as the defined area. You can also digitize the boundaries of the area in the Spatial Portal if there none of the other area defining options are applicable. Note that in the Spatial Portal, “area” can mean multiple polygons.
Once the area is defined, which you can define ‘on the fly’, you can generate an area report containing lists of all species, endemic species, invasive species, species with a conservation status, lifeforms, occurrence records, publications, gazetteer points, points of interest and more.
There are two types of report, an onscreen report that is quick and a PDF report that isn’t. The onscreen report contains most of the details in the PDF report but it is interactive and you will only see what information you select. You can download any of the lists in the report. Depending on the size of the area, the PDF report (which can be well over 100 pages) can take considerable time to generate as a lot of information needs to be gathered and formatted. In short, if you want to know much of what the Atlas knows an area, area reports are a great solution.
More information on Area Reports.
If you want to find the closest named location (a gazetteer location) to any point within the Australian region, you can simply click on the map in the Spatial Portal and the closest 5 locations will be displayed. Why would you use this function? An example may illustrate why. A group of Atlas users focusing on Australia’s islands wanted to find out what information was available on all Australian islands. Of particular interest, were islands that had not be named in the Australian gazetteer. What they did was to zoom in on an area of the coast and then use this function to identify which islands did not have a name.
More information can be found at Tools | Nearest locality
This simple tool lets you interactively examine the environmental values at two or more points. You click on two or more points on the map and then click ‘Compare points’ and a list of all environmental values of those points is listed in a pop-up window in the Spatial Portal. You can then download this list as a CSV file and sort, or analyse the differences in environment between these selected points. Simple, if you are looking for differences in environments.
The term ‘sampling’ comes from the use of the locations of species records to sample the values of any of the environmental and contextual layers available in the Spatial Portal. For example, if you have records of a species at various locations and want to find out what the annual rainfall and mean annual temperature associated with the sightings, then Sampling is how to do it. In this case, sampling will produce a spreadsheet file containing the two locations (=rows) and associated data such as the species names, data flags etc and two additional columns; one for the precipitation value and one for mean annual temperature. You can sample any or all environmental and contextual layers.
The records of species locations can come from mapping a species or uploading your own locations (which don’t have to be ‘species’ locations).
Filtering is subsetting the Atlas occurrence record data using the facets (attributes of records that are indexed in our database) available via ‘Add to map | Facets‘ and on the legends in the Spatial Portal. If you wanted to map all species occurrences that were recorded between 1900 and 1920, you are effectively filtering on the total Atlas holdings for the records taken between 1900 and 1920. To do this, you would use ‘Add to Map | Facet’, select the Facet called “Decade” and check boxes for 1900 and 1910. The result will be a new map layer of all occurrences between 1900 and 1920. You could for example also filter occurrence records that came from certain institutions, by a group of Collectors or various ‘data quality’ flags.
If you have mapped a species (or genus or even list of species), you can use the same mechanism in the legend area of the Spatial Portal to select the facet of interest and then the values of that facet and then create a new mapped point layer representing the occurrence records that have only the selected characteristics.
Filtering can also be applied to a set of occurrence records that have been uploaded using Import | Points.
A scatterplot is an X-Y 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. You could for example plot mean annual temperature (short name called Bio01 in the Spatial Portal) against annual precipitation (Bio12) for say Eucalyptus gunnii (Cider Gum). In this case, temperature will form the X-axis and rainfall the Y axis and the points on the graph will show you what combinations each observation has. The distribution of points is usually informative.
If you want to see what subset of all our environmental layers may have some influence on the distribution of a species (or genus, family etc), then we have a tool called the Scatterplot List. This tool produces scatterplots for all combinations of multiple environmental layers for any species or group of species. For example, you could plot Eucalyptus gunnii against multiple temperature, rainfall and solar radiation variables. This makes it easy to see if there are any systematic relationships between the distribution and environmental parameters.
See Scatterplot case study for an example of how this tool can be used.
Tabulation, or more accurately, cross-tabulation is the direct counterpart of scatterplots for layers that have class rather than numeric values. In the case of tabulation, the X and Y axes of a table are equivalent to the X and Y axes of a scatterplot.
An example of a cross-tabulation would be a table of Australian States and Territories and the reserve classes (CAPAD) such as National Parks, Forestry reserves, flora reserve etc. So what are in the ‘cells’ within the table? We provide three options – the area (square kilometres), number of species (richness) or number of occurrence records.
Using tabulation, you can therefore do some amazing analyses. You could for example see how well a species (or genus or species group etc) are represented across States and Territories, reserve types, bioregions etc. You can download the table as a CSV-formatted file to analyse as you wish. As we build the number of contextual layers (layers with class values), more combinations are made available. The tabulation tables are built each month to reflect updated occurrence record data. This IS surely powerful stuff?
More information can be found at Tools | Tabulate.
This is the area equivalent to compare points. You select or generate two areas and either a taxa, a lifeform or a species list on which to base the comparison. The areas can either be defined on the fly using any of the area generation options, or the two areas can be defined as those contained within the polygons defining a contextual layer and the area outside those polygons. For example, you could compare the bird species within Bush Heritage areas and outside those areas. We would like to be able to add the ability of comparing one or more classes within a contextual layer to all other classes in a contextual layer.
The output from this tool is a table with two rows (the IN area and the OUIT area) and three columns – the area in square kilometers of each area, the number of species in the area and the number of occurrence records in the area. This table is automatically exported as a CSV file.
More information can be fgound at Tools | Compare areas.
The occurrence records in the Atlas are points. Admitted, the accuracy of the location can often mean that the species was seen within a defined area, but the Atlas can only treat it primarily as a point, with an uncertainty radius if that information is available (see coordinateUncertaintyInMeters). There are three other types of species data (checklist areas, expert distribution polygons and prediction areas) but these are special cases.
Points to grid transforms point occurrence data into a sites by species data matrix. This form of data allows you to compare areas by their species composition. Sites in this tool mean grid squares. The output from the tool is therefore a matrix of user-defined sized grid cells by species. Usually, the species in question will be a species group such as Eucalyptus, lifeforms such as amphibians but can be as generic a List as you like.
As a side-product of this tool, you can optionally generate a species richness and an occurrence density map. Could be handy. Could be illuminating?
More information about this option can be found at Tools | Points to grid.
Why would you want to generate point in the SPatial Portal? We had a number of users ask us if it was possible to get an average of environmental conditions within a given area. We developed this tool to generate points on a regular (of a user defined sized) grid within a user-defined area. Simple. What the tool produces is a new point layer that you can do with as you wish, but mostly we suspect useful for sampling layers?
More information can be found at Tools | Generate points.
In the case of biodiversity, diversity is basically the number of different species present. Phylogenetic diversity is the differences between species in terms of their evolutionary history. A phylogenetic tree is the foundation from which phylogenetic diversity can be estimated. Such a tree ideally represents both time and character differences between species. Character differences can either by in physical properties such as the number of legs, or differences in DNA sequences.
In the Spatial Portal, phylogenetic diversity is based on any available phylogenetic tree and any defined area. The output is the phylogenetic diversity of the species in the tree within the defined area.
More information can be found at Tools | phylogenetic diversity.
Classification combines a set of environmental layers (not contextual 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 on the map is colour coded to reflect the relationships with all other domains; similar coloured domains/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.
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 else those environmental conditions occur and would therefore expect the species to occur. This approach is called ‘niche modelling’ or ‘species distribution modeling’. 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.
This is a tough one. GDM or Generalized Dissimilarity Modelling is probably the most complex tool within the Spatial Portal. It is normally used over a large number of species (a group such as Eucalyptus or lifeforms such as amphibians) and over regions to continental areas to identify how well all the species align with environmental factors.
GDM accepts any species list and a suite of environmental layers and then warps the environmental layers to best align with the species distributions. For example, if you use Western Australia as an area, Eucalyptus as the species list and say rainfall, temperature and solar radiation layers, you will produce new rainfall, temperature and solar radiation layers that best align with the distribution of Eucalypts in Western Australia. These new layers could be used in further analysis such as area classification.
More information can be found at Tools | GDM.