Layer: Animal Species (ID: 6)

Parent Layer: Animal Species Theme

Name: Animal Species

Display Field: OBJECTID

Type: Feature Layer

Geometry Type: esriGeometryPolygon

Description: <DIV STYLE="text-align:Left;"><DIV><DIV>GENERAL NOTE ⦁ A habitat segment layer was used across multiple taxa to intersect points in the High sensitivity category. This layer was derived from remotely sensed 90m Landsat imagery. The imagery was used to create fine-scale habitat patches that delineated areas of similar vegetation type. This layer was used across multiple taxa as a basis for transforming point occurrence data into polygon layers by intersecting the two layers and retaining the selected habitat segments. MAMMALS (Class: Mammalia) Sensitivity = High ⦁ The majority of the mammal data was extract from the Endangered Wildlife Trust’s Red List database (https://www.ewt.org.za/resources/resources-mammal-red-list/).⦁ Species occurrence records were filtered to only include those recorded post-2002 and those which had accurate GPS coordinates. All occurrence records were filtered to remove any low quality data.⦁ Following that, for each species, the associated GPS points were intersected with the habitat segment layer. ⦁ The segments were then extracted and each was designated as High sensitivity. Sensitivity= Medium⦁ Areas delineated as Medium sensitivity were derived from a statistical method known as species distribution modelling. Species distribution models (SDMs) are empirical methods that relate species occurrence data to environmental predictor variables based on statistically derived response curves that best reflect the ecological requirements of the species. These relationships are then used to predict the potential distribution of a species in geographic space. SDMs were developed for each species independently and paired all valid species occurrence points (including those collected prior to 2002) with remotely sensed environmental variables that represented land cover, habitat type, topography, soils, primary productivity and climate. The SDMs were run at the 30 arc-second spatial scale.⦁ Several SDMs were produced for each species and various statistics such as the AUC measure were used to evaluate model performance allowing only high quality models to be retained for the remainder of the modelling procedure. Models with low quality were discarded. ⦁ SDMs produce a probability surface representing relative habitat suitability across the predicted range of occurrence. This probability surface was converted to a binary (present/absent) surface using a threshold to most accurately incorporate true presences and true absences.⦁ The binary vector surface was then filtered to only include habitat patches where a species can be regarded as present that were larger than ~1km2. REPTILES (Class: Reptilia) Sensitivity= Very high⦁ Taxa that qualify are those with a EOO of less than 10km2.⦁ Experts reviewed the species list and added any missing species not selected with EOO calculation and to remove taxa that are Data Deficient. ⦁ Experts mapped occupied habitat based on data points and habitat descriptions for each selected taxa ⦁ Additional experts then reviewed mapped distributions and maps were corrected based on feedback received. Sensitivity= High Species occurrence data from the Reptile IUCN Red List assessment were used. Only data collected post-2002 were included. These data were then intersected with the habitat segment layer. All data were vetted by taxon experts. Sensitivity= Medium Species distribution maps compiled for the Reptile IUCN Red List assessment were used to delineate areas of Medium sensitivity for each species. AMPHIBIANS (Class: Amphibia) Sensitivity=Very high⦁ Taxa that qualify are those with a EOO of less than 10km2.⦁ Experts reviewed the species list and added any missing species not selected with EOO calculation and to remove taxa that are Data Deficient. ⦁ Experts mapped occupied habitat based on data points and habitat descriptions for each selected taxa ⦁ Additional experts then reviewed mapped distributions and maps were corrected based on feedback received. Sensitivity= High Species occurrence data from the Amphibian IUCN Red List assessment were used. Only data collected post-2002 were included. These data were then intersected with the habitat segment layer. All data were vetted by taxon experts. Sensitivity= Medium Species distribution maps compiled for the Amphibian IUCN Red List assessment were used to delineate areas of Medium sensitivity for each species. BIRDS (Class: Aves) Sensitivity= Very high⦁ NA for any species included in the environmental screening tool. Sensitivity= High⦁ Species distribution models (SDMs) and SABAP2 data (sabap2.adu.org.za) were combined to delineate the High sensitivity. The models were created by BirdLife South Africa.⦁ SDMs were created using an ensemble modelling approach, namely the Biomod2 package in the R platform. The package makes use of multiple SDM algorithms and produces a number of model outputs from which to compare model performance and fit. The SDMtoolbox and R package BlockCV was used to control for spatial autocorrelation within the occurrence data used within SDM, as well as control for how data was split amongst model folds and runs. ⦁ Environmental covariate layers used in SDM differed amongst species and/or guilds. An ecological trait-based assessment of species and guilds was conducted in order to select, collate and/or create ecologically meaningful variables for SDM frameworks. Broad groups of covariates used across all species included bioclimatic layers representing climate (e.g. annual rainfall, temperature range, etc.), topographical layers (e.g. slope, aspect, etc.), land cover and metric/s of habitat quality (remote sensing based).⦁ In addition to scrutinising facets of model performance such as AUC and kappa coefficient (κ), we conducted an additional assessment of model validation. The assessment compared the modelled distribution of suitable habitat to independent sources (i.e. not used in the SDM) of known occurrence and distribution. If models did not conform to the known distribution, and/or failed to predict known areas of suitability with a reasonable accuracy, the model was rejected and further refined/rerun with varied covariates and/or occurrence data ⦁ In addition, point locations were used to inform the SDM as well as for verification of the model. These point data were obtained through the mobile app BirdLasser as well as point data collected through tracking projects as well as academic and other studies. ⦁ SABAP2 data for each species was downloaded from the SABAP2 website in geoJSON format and then converted into shapefile format. ⦁ SDM data received in raster format. Raster then converted to a polygon shapefile using the appropriate tool in ArcMap. Shapefile then projected to determine size of each polygon and smaller patches deleted ( &lt; 2 – 4 ha). The size of the patch to be deleted differs from species to species, for example smaller areas will be deleted for forest based species than species with large ranges. ⦁ The Select by Location tool was then used to identify the areas in the SDM which intersects with SABAP2 data. A small buffer was added to each pentad to include a wider area. Areas which do not overlap with pentads were excluded from the data layer (these can potentially added in tier three in the future and after further evaluation). ⦁ The final sensitivity layers represents areas where the species was actually observed during SABAP2. Unsuitable habitat was excluded from the relative course area covered by one pentad by identify suitable habitat used by the species. Sensitivity= Medium⦁ NA for any species currently included in the environmental screening tool. BUTTERFLIES (Class: Insecta) Sensitivity = Very high⦁ Taxa that qualify are those with a EOO of less than 10km2.⦁ Experts (Dr Silvia Kirkman and Dr Dave Edge) reviewed the species list and added any missing species not selected with EOO calculation and to remove taxa that are Data Deficient. ⦁ TSP mapped occupied habitat based on data points and habitat descriptions for each selected taxa ⦁ Expert Dr Dave Edge reviewed mapped distributions⦁ Maps were corrected based on comments from expert Sensitivity= High. Species occurrence data from the Butterfly Red Listing process were used. Only data collected post-2002 were included. These data were then intersected with the habitat segment layer. All data were vetted by taxon experts. Sensitivity= Medium⦁ Areas delineated as Medium sensitivity were derived from a statistical method known as species distribution modelling. Species distribution models (SDMs) are empirical methods that relate species occurrence data to environmental predictor variables based on statistically derived response curves that best reflect the ecological requirements of the species. These relationships are then used to predict the potential distribution of a species in geographic space.⦁ SDMs developed by Dr S Kirkman from her PhD thesis were used. These models were generated at a 5 arc minute resolution. FRESHWATER FISHES (Class: Actinopterygii)Sensitivity= Very high⦁ Habitat for highly range-restricted threatened taxa that have an extent of occurrences of less than or equal to 10 km2 or single-site species, which is assessed as Critically Endangered. All historic (pre-2002) and current (post-2002) occurrence records of freshwater fish taxa that are categorised as Critically Endangered. As such, all known, valid, historic occurrence records were used to build the very high-sensitivity layer. Occurrences were intersected with the FEPA Sub-Quaternary Catchment layer to create catchment-specific occurrence polygons, indicating the presence of a Critically Endangered freshwater fish in that catchment. Sensitivity= High⦁ The high sensitivity category only applied to freshwater fishes that were assessed as Vulnerable or Endangered. The ‘high’ sensitivity layer is comprised of all valid, post-2002 occurrence records. Occurrence records for each freshwater fish (i.e., the assumed, current distribution of the species) were plotted in R. Occurrence data were then intersected with the River Freshwater Ecosystem Priority Areas (FEPA) Sub-Quaternary Catchment layer to create catchment-specific occurrence polygons, indicating the recent presence of a Vulnerable or Endangered freshwater fish in that catchment. Sensitivity = Medium⦁ Taxa that qualify for inclusion in the ‘medium’ sensitivity layer were categorised as either Vulnerable or Endangered. For these taxa, species distribution models (SDMs) were used to generate predictive geographic ranges. All valid occurrence records for each freshwater fish were used to independently develop a unique, accurate SDM for each taxon using a Bayesian additive regression trees (BART) algorithm via functions from the embarcadero R package. A comprehensive suite of environmental and hydrological variables was used to generate these SDMs. Modelled distributions were converted to a binary output (presence/absence) for each species using a threshold that maximizes true skill statistics from the SDM. Odonata (Order: Odonata) Sensitivity= Very high⦁ NA Sensitivity= High⦁ The high sensitivity category applied to all threatened Odonata species that have records post-2010, and these were intersected with the River Freshwater Ecosystem Priority Areas (FEPA) Sub-Quaternary Catchment layer to create catchment-specific occurrence polygons, indicating the recent presence of these species in that catchment. Sensitivity = Medium⦁ The medium sensitivity category applied to all threatened Odonata species that did not have records pre-2010, and these were intersected with the River Freshwater Ecosystem Priority Areas (FEPA) Sub-Quaternary Catchment layer to create catchment-specific occurrence polygons, indicating the most recent pre-2010 occurrence of the species.</DIV></DIV></DIV>

Service Item Id: aa35dbdf42d64b1287b146d65b89642e

Copyright Text:

Default Visibility: false

MaxRecordCount: 2000

Supported Query Formats: JSON, geoJSON, PBF

Min Scale: 0

Max Scale: 0

Supports Advanced Queries: true

Supports Statistics: true

Has Labels: false

Can Modify Layer: true

Can Scale Symbols: false

Use Standardized Queries: true

Supports Datum Transformation: true

Extent:

Drawing Info:

Renderer:

Unique Value Renderer:

Field 1:

Field 2:

Field 3:

Field Delimiter:

Default Symbol:

N/A

Default Label:

UniqueValueInfos:

Value: Very High
Label: Very High
Description: N/A
Symbol:
Value: High
Label: High
Description: N/A
Symbol:
Value: Medium
Label: Medium
Description: N/A
Symbol:
Value: Low
Label: Low
Description: N/A
Symbol:

Transparency:

Labeling Info:

Advanced Query Capabilities:

HasZ: false

HasM: false

Has Attachments: false

HTML Popup Type: esriServerHTMLPopupTypeAsHTMLText

Type ID Field: null

Fields:

OBJECTID_1 ( type: esriFieldTypeOID, alias: OBJECTID_1 )
Shape ( type: esriFieldTypeGeometry, alias: Shape )
OBJECTID ( type: esriFieldTypeString, alias: OBJECTID, length: 60 )
SENSITIVIT ( type: esriFieldTypeString, alias: Sensitivity category:, length: 15 )
THEME ( type: esriFieldTypeString, alias: THEME, length: 40 )
SENSFEAT ( type: esriFieldTypeString, alias: Sensitivity features:, length: 100 )
DEVELOP ( type: esriFieldTypeString, alias: DEVELOP, length: 50 )
ID_2 ( type: esriFieldTypeInteger, alias: ID_2 )
Shape_Length ( type: esriFieldTypeDouble, alias: Shape_Length )
Shape_Area ( type: esriFieldTypeDouble, alias: Shape_Area )

Supported Operations: Query Query Attachments Query Analytic Generate Renderer Return Updates

Iteminfo Thumbnail Metadata