Category Archives: Practicum
I recently ran a model of Hemlock on my personal computer.
I modeled ~489 records; the Nautilus model used over 2,000.
From the model output:
This is a representation of the Maxent model for Tsuga_canadensis. Warmer colors show areas with better predicted conditions. White dots show the presence locations used for training, while violet dots show test locations.
This is not really a fair comparison, but the difference between the models with 489 records and 2000+ is interesting for comparing the predictions.
EECS model for Eastern hemlock is different. It uses more data, and it was run 20 times with 10% of the records reserved before being synthesized into one image.
I will post some additional comparisons for other trees in some later posts.
Environmental layers are available to the public via IRMA.
Source metadata are not available at http://tiny.utk.edu/atbi.
I have attempted to map or cross-walk the layers listed by the Simmerman et. al paper to the names of datasets available for download from IRMA.
Table. Mapping from UTK names to IRMA names.
|1||Soil Organic Type||Soil Classification||https://irma.nps.gov/App/Reference/Profile/2198007|
|2||Topographic Convergence Index||Topographic Wetness Index||https://irma.nps.gov/App/Reference/Profile/2208650|
|3||Solar Radiation Data||30 -m Potential Solar Radiation||https://irma.nps.gov/App/Reference/Profile/2208716|
|4||Terrain Shape Index||30-m Topographic Shape Index||https://irma.nps.gov/App/Reference/Profile/2208684|
|5||Terrain Shape Index||30-m Topographic Ruggedness Index Model||https://irma.nps.gov/App/Reference/Profile/2182017|
|6||Digital Elevation Model||30-m Lidar Digital Elevation Model||https://irma.nps.gov/App/Reference/Profile/2180606|
|7||Slope in Degrees||30-m Lidar Slope Model||https://irma.nps.gov/App/Reference/Profile/2180632|
|8||Understory Density Classes||Understory Vegetation at GRSM||https://irma.nps.gov/App/Reference/Profile/1047499|
|9||Leaf On Canopy Cover||Overstory Vegetation at GRSM||https://irma.nps.gov/App/Reference/Profile/1047498|
|10||Vegetation Classes Vegetation Classification||Great Smoky Mountains NP Vegetation Classification||https://irma.nps.gov/App/Reference/Profile/1021458|
Note: I am grateful to http://www.textfixer.com/html/csv-convert-table.php which made it possible to easily create this table from plain text. I expect to add this to my “toolkit” of useful items and it saved me a lot of time.
Poster presented at 2014 North Carolina Partners in Amphibian and Reptile Conservation Meeting.
- Jessel, Tanner; Super, Paul E.; Colson, Thomas (2014): Spatial Data Diversity Supporting Herpetological Research in Great Smoky Mountains National Park. figshare.
Environmental Layers for HPC Maximum Entropy Species Distribution Models in Great Smoky Mountains National Park
Currently there are 10 environmental layers that were used by Simmerman et. al in the demonstration project, “Exploring similarities among many species distributions.”
- Bedrock geology
- Digital elevation model
- Slope measured in degrees
- Solar radiation data
- Soil organic type
- Terrain shape index
- Topographic convergence index
- Leaf on canopy cover
- Understory density classes
- Vegetation classes
The contribution of environmental variables to each “Maximum Entropy” Species Distribution Model (MaxEnt SDM) environmental variables are accessible from each model under the “Environmental Layers” tab.
The help icon accompanying each model provides this text:
This is a species distribution model (SDM) produced by MaxEnt. This SDM is actually a composite from ten cross-validation runs for each species (see cross-validation results tab for more information). Original ATBI record locations are shown with black dots. The color scale goes from 0 probability of presence (dark brown) to 100% probability (dark green).
Below is a screen capture of the model generated for the Fraser fir (Abies fraseri). This model is based on 474 occurrence records. The full size image is available online at <http://seelab.eecs.utk.edu/alltaxa/maps/Abies_fraseri.png>
Interestingly, the MaxEnt model output suggests that the “Digital Elevation Model” contributed 88.8% to the Species Distribution Model for Abies frasieri. This makes sense, since the Fraser fir is a species of conifer favoring cold environments that inhabits only the highest elevations of the Park. The remaining layers contribute less than 5% to the model.
I’m copying out the taxonomic classification from Wikipedia:
The purpose is to access the records from the ATBI database, where I don’t see the Fraser fir listed in the ATBI “plants” kingdom. From <http://tremont22.campus.utk.edu/ATBI_Query.cfm> I searched by “order’ for “pinales.”
Fraser fir is accessible: <http://tremont22.campus.utk.edu/ATBI_Species.cfm?genus=Abies&epithet=fraseri&subspecies=%7E>. Interestingly, the number of specimens in the database is 866. Contrast this with the 474 records that were used to generate the model. The model may simply be older (there does not appear to be a timestamp for the model; either from “Get Info” or opening up “Properties” in GIMP for both the large 299×1302 pixel PNG file and the small 600×269 pixel png) or, not all 866 occurrence records have spatial coordinates associated (e.g., they are “references from the literature.”)
- total herp species in park
- total herp species in the ATBI database
- total herp species in the ATBI database that have n = 30 or more
- total herp species in the ATBI database that need more data to be modeled
Total herp species in the ATBI database that have n = 30 or more
Total herp species in the ATBI database that need more data to be modeled