An assessment has been completed on the sRedList platform for the species Azteca xanthochroa on the 23/10/2023. All outputs from this assessment are reported in the .csv and .shp files that were downloaded at the end of the assessment and they can be pushed on SIS through SIS Connect. This report is here to detail how these results were obtained (e.g., which parameters were used on the sRedList platform), to provide context around results (e.g., saving the different maps created on the platform), and help communication among assessors and with reviewers.





Step 1: Distribution

You used the sRedList platform to create a distribution map of your species from occurrence records.

Download data

You gathered 270 raw occurrence records from GBIF + Uploaded . They are distributed as follows:


Filter data

To filter occurrence records, the platform offers some automated filters from the CoordinateCleanR package (see sRedList documentation for more information); you chose to apply those filters in your assessment. In addition, you excluded all records made before 1900 (but keeping records that do not have year information). You also excluded all records with coordinates uncertainty higher than 10km (but keeping records that do not have coordinate uncertainty information). You restricted to occurrence records included in a square of coordinates: -180,-76,-90,90. You excluded occurrence records made at sea.

Occurrence records are displayed here (valid records in yellow and excluded records in purple; you can click on observation get more information and exclusion reason, check the sRedList documentation for more details):

After applying these filters, your point range map included 258 occurrence records.

The elevation of occurrence records was extracted:

Create range map

To create a polygon range map, you chose first to draw an alpha hull around occurrence records, fixing the alpha hull parameter to 0.7 (note that the parameter provided here differs from the alpha parameter per se as we scale it by the length of the diagonal of the geographic extent of the points (in meters) in order to have a reasonable range of values that work for species with different range sizes; the true unscaled alpha parameter is then displayed as a caption at the bottom of the plot).. You then buffered that polygon by 100 km. You excluded all the marine area from the polygon.

The range map created at this step is:

Smooth range map

You used the smoothing option to make polygon edges less sharp with a smoothing parameter of 500.

The final range map used in the next analyses is:




Step 2: Countries of occurrence

Countries of occurrence were extracted by overlapping the distribution saved in step 1 with a map of countries matching the list of countries and subnational entities from the Red List (see the sRedList documentation for further details). As you selected the species occurs in the system(s): Terrestrial, we used a terrestrial map of countries. The following map was obtained:

The list of realms is: Neotropical

The list of countries of occurrence is:

Belize; Costa Rica [Costa Rica (mainland)]; El Salvador; Guatemala; Honduras [Honduran Caribbean Is., Honduras (mainland)]; Mexico [Campeche, Chiapas, Hidalgo, Oaxaca, Puebla, Tabasco, Tlaxcala, Veracruz]; Nicaragua [Nicaragua (mainland)]; Panama


Entities are written in italics if they overlap with the polygon distribution but not with occurrence records (they are included in countries.csv in the ZIP output). By default, we assumed for all countries the codes ‘Native’ for origin, ‘Resident’ for seasonality. For presence, we assumed ‘Extant’ for all countries with occurrence records and ‘Possibly Extant’ for countries overlapping with the distribution but without occurrence records (i.e., those written in italics). If you want to edit those, or the list of countries, you will have to do that manually in SIS. If you do not want to use this list at all, you can delete the ‘countries.csv’ file from the ZIP output.




Step 3: Extent of occurrence

The extent of occurrence was calculated as the area of the minimum convex polygon around the distribution saved in Step 1. If you are confident that the distribution represents the true range of your species (including inferred presences), you can use this estimate in criterion B1.


The extent of occurrence calculated by the platform was 929,710km2. The final extent of occurrence (present in the downloaded output) has a value of 929,710km2 and as justification :‘The EOO has been estimated as the Minimum Convex Polygon around the distribution on the sRedList platform.’.




Step 4: Area of Habitat

As you have drawn distribution maps from occurrence points, we calculate the species known area of occupancy based on these records. Note that this is a very conservative estimate of the area of occupancy as it is only based on known occurrences (or even just a sample if there were more than 2000 records in GBIF). The value of known area of occupancy is 344km2.


Habitat preferences

The habitat distribution of occurrence records was extracted:

The habitat preferences used to map Area of Habitat were:

Habitat lookup Habitat name Suitability
1.6 Forest - Subtropical/Tropical Moist Lowland Suitable
1.9 Forest - Subtropical/Tropical Moist Montane Suitable
14.1 Artificial/Terrestrial - Arable Land Unknown

Note that the major importance and seasonality fields are left empty from the habitats.csv file, so you might want to complete that information in SIS later.

Elevation preferences

Elevation preferences were suggested by the platform with a lower elevation limit of 1m and an upper elevation limit of 5175m (calculated as the minimum and maximum elevation within the species range). After a possibility to manually edit these values and add uncertainty in the estimates, the elevation preferences used to map Area of Habitat were 0, 1700-2500.

Density

The final density value you used to estimate population size was 10-20 mature individuals / km2 of suitable habitat.

AOH calculation

The calculated Area of Habitat has a value of 307,497-348,486 km2.


When rescaled at a 2x2km grid, this provides a value of 498,156-560,396 km2; this value can be used (if you trust the map) as an upper bound of area of occupancy if you consider likely that all the mapped suitable habitat is occupied by the species. If you know part of it is not occupied, you might want to reduce this estimate.


Based on the estimated Area of Habitat and the density value provided, we estimate the population size of your species is 3,074,970-6,969,720 mature individuals.




Step 6a: Fragmentation

This step was not performed on the platform.


Step 7: Summary and assign categories

After the summary step, these are the parameters that are included in the final output allfields.csv:

Variable Value
AOO.justification The area of occupancy was estimated on the sRedList platform. Its lower bound (344km2) was estimated as the area of 2x2km grid cells intersecting with occurrence records (258 occurrence records were retrieved from GBIF (N=251), occurrence records uploaded by sRedList user (N=7)); this estimate assumes that the species range has been extensively surveyed at a 2x2km scale. The upper bound of area of occupancy (498156-560396km2) has been estimated by rescaling the map of Area of Habitat to a 2x2km grid; this estimate assumes that all suitable habitat is occupied by the species (at a 2x2km scale).
AOO.range 2000-560396
CurrentTrendDataDerivation.value Inferred
EOO.justification The EOO has been estimated as the Minimum Convex Polygon around the distribution on the sRedList platform.
EOO.range 929710
ElevationLower.limit 0
ElevationUpper.limit 2500
NoThreats.noThreats false
PopulationReductionPast.direction Reduction
PopulationReductionPast.justification Based on forest change…
PopulationReductionPast.qualifier Inferred
PopulationReductionPast.range 9
PopulationReductionPastBasis.value c) a decline in area of occupancy, extent of occurrence and/or quality of habitat
PopulationReductionPastCeased.value No
PopulationReductionPastReversible.value No
PopulationReductionPastUnderstood.value Yes
PopulationSize.range 3074970-6969720
SevereFragmentation.isFragmented No
ThreatsUnknown.value false
internal_taxon_id 6111241
internal_taxon_name Azteca xanthochroa



These parameters lead to the following Red List criteria application (note though that this is just for visualisation and will not be pushed to SIS):





Thank you for using sRedList! You can now either go to SIS and paste the parameters calculated here that you find interesting, or use the ZIP file to push your assessment to SIS Connect.