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true, "supportsSqlExpression" : false }, "supportsDatumTransformation" : true, "supportsCoordinatesQuantization" : true }, { "currentVersion" : 10.81, "id" : 2, "name" : "Danaus plexippus (monarch butterfly) breeding records habitat suitability", "type" : "Raster Layer", "description" : "", "geometryType" : null, "copyrightText" : "Dilts, T.D, Steele, M., Black, S., Craver, D., Cruz, E., Engler, J., Jepson, S., Jones, A., McKnight, S., Pelton, E., Taylor, A., Forister, M. 2018. Western Monarch and Milkweed Habitat Suitability Modeling Project Version 2 - Maxent Model Outputs. Xerces Society/US Fish and Wildlife Society/University of Nevada Reno. 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All four monarch models exclude overwintering months (November through March). The four monarch models are for 1) all occurrence records, 2) adult occurrence records, 3) breeding occurrence records, and 4) breeding occurrence records omitting locations within 3.6 km of tropical milkweed (Asclepias curassavica). The thirteen species of milkweed that were modeled were: Asclepias speciose (showy milkweed), Asclepias fascicularis (narrowleaf milkweed), Asclepias eriocarpa (woollypod milkweed), Asclepias asperula (antelope horn or spider milkweed), Asclepias subverticillata (whorled milkweed), Asclepias erosa (desert milkweed), Asclepias cordifolia (heartleaf milkweed), Asclepias subulata (rush milkweed), Asclepias californica (California milkweed), Asclepias tuberosa (butterfly milkweed), Asclepias viridiflora (green milkweed), Asclepias cryptoceras (pallid milkweed), and Asclepias incarnata (swamp milkweed). Asclepias curassavica (tropical milkweed) was not modeled.
These models were developed by correlating a set of environmental covariates to the known occurrence points of more recent origin and higher spatial accuracy. A different subset of uncorrelated variables was selected for each species from a set of 25 possible covariate rasters. All modeling was performed using Maxent software (maximum entropy) using species-specific tuning of the regularization, feature type, and background parameters. Additionally, occurrence data was thinned to a 3.6 km grid in order to minimize the effects of biased sampling. The method follows work done for a phase I habitat suitability modelling effort (Steele, M., Engler, J.D., Jepsen, S., Black, S., Cruz, L., Taylor, A., & Jones, A. 2017. Modeled habitat suitability for milkweeds and monarch butterfly reproduction in the Western U.S. United States Fish and Wildlife Service Unpublished Report.), and expands upon it to develop more species models and use more occurrence data collected through 2016.
In addition to the species-specific milkweed models two composite milkweed maps were created to represent the sum of the habitat suitability, which is largely representative of milkweed species diversity, and maximum habitat suitability regardless of species, portraying the highest value of relative suitability among the thirteen species models.
Each model also has an associated uncertainty map that was derived by randomly withholding 20% of the data to be used for cross-validation. Uncertainty is represented as the standard deviation of habitat suitability for the 25 replicate models generated from cross-validation. Uncertainty can be interpreted as confidence with which the final model is supported by the available occurrence data. High uncertainty is not necessarily indicative of a poor model, but possibly a less than ideal amount of occurrence data.
All of these models are being distributed via USFWS ServCat in their original 270 m pixel resolution for use by the USFWS, the Xerces Society, the University of Nevada Reno, and their partners. These models are imperfect because they are based on limited and spatially biased data, but it is appropriate to use them to help plan prioritize habitat improvement actions at a regional scale, and to identify areas for future surveys. Consideration of local factors, nativeness, and landscape context is highly advised for any conservation delivery. The models include embedded metadata and Esri layer files. Full documentation of the methods used to develop these models will be provided in a report that is currently in draft and will be submitted for peer review in 2018.
The following is a list of the final variables that were used in this model, as well their permutation importance (expressed as a percentage):
Land cover 28.8
Mean Temperature of Warmest 26.4
Fascicularis 23.3
Subverticillata 21.5
This model had an AUC of 0.826.