Riparian Connected Habitat

Urban Habitat Connectivity Project (UHCP)&nbsp;

Short description:&nbsp;A package of data containing potential habitat and fragmentation for eight species groups in the urban ACT. Each species group has two layer files.&nbsp;Connected habitat layers show potential core and corridor habitat for the species group, and connectivity/fragmentation between these habitat patches. Remnant patches layers contain areas which are predicted to be fragmented and inaccessible for the species group, but may be important for restoration activities. These layers are outputs of ecological connectivity modelling and have been developed using spatial data representing habitat and connectivity requirements specific to the species group.

The following attributes are available in the data table for Connected Habitat layers:

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Species Group* - indicates the species group of interest
Patch ID – a unique identifier for each ‘patch’ of connected habitat, an ID that is given to group all habitat areas which are predicted to be connected to each other.
Habitat Type* – identifies if the polygon meets core or corridor habitat requirements, or if it is a remnant patch.
Habitat Number – a numeric value linked to Habitat Type to support statistics and symbology. Core habitat has a value of 0 and corridor habitat has a value of 1.
Patch Area (Ha)* – the area of the individual polygon in hectares.
Connected Habitat Area (Ha) – the total area of potential habitat in the connected patch, determined by summing the Patch Area for all polygons with the same Patch ID.
Shape area – the polygon’s area, calculated by default in meters squared.
Shape length – the length of the line enclosing the polygon, calculated by default in meters squared.

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* Is also available in the data table for Remnant Patches layers.

Spatial resolution:&nbsp;1:10,000

Coordinate system:&nbsp;GDA2020 MGA zone 55

METHODS

Data collection / creation:&nbsp;Spatial layers for habitat and barriers were created and input into a habitat connectivity/fragmentation model specifically designed for the species group. The model was developed using metrics derived from expert elicitation. These metrics quantified essential habitat and connectivity requirements for the species group, for example the preferred spacing of trees, the maximum crossable width of a road, the typical dispersal distance, etc.&nbsp;The model identified habitat and barriers to connectivity, based on the metrics which could be mapped. Habitat was delineated by patch size to determine core and corridor habitat, and to remove areas which are too small to be functional. The habitat type is visible in the attribute table of the data.

Connectivity between habitat patches is dependent on the species group’s dispersal capacity and the availability of core habitat, suitable corridors and a path without barriers. To assess this core habitat areas were buffered by the species group’s dispersal distance. This identified how far an individual will move to find a new core habitat patch. Movement to this distance is dependent on a suitable path. All habitat was buffered by the distance the species can move outside habitat (through non-habitat areas). This identified how far an individual will move outside any habitat (core or corridor) before they require another habitat patch (i.e. how far they can travel between stepping stones).Connectivity is further complicated by impassable barriers. Barriers were used to slice up the dispersal buffers and identify ‘dispersal patches’, areas which an individual can move within. Fragmentation is seen when a barrier is present, patches are too far from core habitat, or corridor habitat is too far apart.

A unique ID was applied to each patch and represents connectivity/fragmentation. The patches were intersected with habitat to apply the new ID to the habitat areas. The final model outputs identify areas of potential core, corridor or remnant (inaccessible) habitat. Core and corridor habitat are viewable in the connected habitat dataset, whilst remnant patches are available separately. The data was simplified using the Douglas-Peuker algorithm, a tolerance of 0.5-2m, minimum size of 2-5m2 for retention, and holes filled in if less than 20m2. Small adjoining slithers &lt;20m2 were dissolved into neighbouring polygons to optimise drawing speeds. Please contact the project team for the model script or further details on the methodology.

NOTES ON USE

Quality:&nbsp;The habitat connectivity modelling used to produce the data was informed by work by the City of Melbourne&nbsp;(Kirk et al., 2018). The original methods were expanded on, with habitat and connectivity requirements (metrics) specific to the species group determined from expert elicitation and further analysis to consider patch size for core or corridor patches. The expert elicitation process provided the best and most relevant quantitative description of habitat and barriers available (for a species group rather than a specific species). The input datasets were then tailored to the metrics for this project. Existing datasets were refined to be relevant and reflect the metrics identified through expert elicitation. New datasets were created where data was missing. All data was derived from existing authoritative sources and/or remotely sensed data. This data curation process ensured the input datasets, and resulting output, were relevant and fit for purpose.

Limitations:&nbsp;This data should be considered indicative only as there are limitations to the modelling process. It considers all habitat and barriers equally and as discrete objects (i.e. it applies a discrete boundary around a patch and does not account for gradients or flexible boundaries).The model predicts habitat and connectivity based on the data available. It does not assess whether a species is present or consider temporal variability. Some habitat requirements are not mapped (e.g. native vegetation, lack of predators) due to the lack of an accurate or complete dataset. Some of these requirements are critical to the success of the species group. These habitat requirements are available and have been derived from expert elicitation. They should be considered at an area of interest.

The model assumes the input data is up to date and accurate. Many of the habitat and barrier datasets used as inputs into the models are in some way informed by remote sensing data. Remote sensing data has limitations, such as potential for misclassification (e.g. bare ground and pavement could be confused). Additionally, remotely sensed data captures a point in time and will become outdated. Manual checks and improvements using supplementary data for specific sites have been completed to reduce as much error as possible.

Data refinement:&nbsp;Unmapped habitat and connectivity requirements should be considered when using the data. The full list of known habitat and connectivity requirements for each species group, including those considered by the model and those unaccounted for, is available by request. Other data may also be used to track changes post-LiDAR capture. For example, new development footprints may be used to remove non-habitat areas and can be done so at a faster rate than waiting for new LiDAR captures and re-running the model.

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SHARING&nbsp;

Licenses/restrictions on use:&nbsp;Creative Commons By Attribution 4.0 (Australian Capital Territory)

How to cite this data:&nbsp;ACT Government, 2023. Potential Habitat and Fragmentation in Urban ACT dataset, version 3. Polygon layer developed by the Office of Nature Conservation, City and Environment Directorate, Canberra.

CONTACT

For accessibility issues or data enquiries please contact the Connecting Nature, Connecting People team&nbsp;cncp@act.gov.au.&nbsp;

Tags: act, biodiversity, bsud, ced, cncp, conservation, ehw, environment, gdc0b1360df, nature, uhcp, urban-biodiversity, urban-connectivity, urban-habitat
Organization: ACT Government Geospatial Data Catalogue (ACTmapi)