<p>Greater prairie-chickens (<i>Tympanuchus cupido pinnatus</i>; GPC) have
declined throughout large areas in the eastern portion of their range. I used
species distribution modeling to predict most appropriate areas of
translocation of GPC in and around Kankakee Sands, a tallgrass prairie in
northwest Indiana, USA. I used MaxEnt for modelling the predictions based on
relevant environmental predictors along with occurrence points of 54 known lek
sites. I created four models inspired by Hovick et al. (2015): Universal,
Environmental, Anthropogenic-Landcover, and Anthropogenic-MODIS. The Universal,
Environmental, and Anthropogenic-MODIS models possessed passable AUC scores
with low omission error rates. However, only the Universal model performed
better than the null model according to binomial testing. I created maps of all
models with passing AUC scores along with an overlay map displaying the highest
predictions across all passing models. MaxEnt predicted high relative
likelihoods of occurrence for the entirety of Kankakee Sands and many areas in
the nearby landscape, including the surrounding agricultural matrix. With implementation
of some management suggestions and potential cooperation with local farmers,
GPC translocation to the area appears plausible.</p>
<p>Franklin’s ground squirrels (<i>Poliocitellus franklinii</i>; FGS) have
declined throughout a large portion of the eastern periphery of their range.
Because of this, The Nature Conservancy is interested in establishing a new
population of these animals via translocation. The area of interest is
tallgrass prairie in northwest Indiana, USA: Kankakee Sands and the surrounding
landscape. Species distribution modelling can help identify areas that are
suitable for translocation. I used MaxEnt, relevant environmental variables,
and 44 known occurrence points to model the potential for translocation of FGS
to Kankakee Sands and the surrounding area. I created four models inspired by
Hovick et al. (2015): Universal, Environmental, Anthropogenic-Landcover, and
Anthropogenic-MODIS. I created maps of models with passing AUC scores. The
final map was an overlay map displaying the highest relative likelihood of
occurrence predictions for the area in all passing models. Only the Universal
and Anthropogenic-MODIS models had passable AUC scores. Both had acceptable
omission error rates. However, none of the models performed better than the
null model (p < 0.05). MaxEnt predicted that a few areas in and outside of Kankakee
Sands possess high relative likelihoods of occurrence of FGS in both the
Universal and Anthropogenic-MODIS models. However, MaxEnt predicted high
relative likelihoods in the surrounding agricultural matrix in the Universal
Model. FGS prefer to cross through agricultural areas via unmowed roadside
instead of open fields (Duggan et al. 2011). Because of this, high predictions
in agricultural matrices in the Universal model are irrelevant. High relative
likelihood predictions for linear sections that are obviously roads are
disregardable in the context of my modeling efforts. Because of my low sample
size, none of the models are really reliable in predicting relative likelihoods
of occurrence for this area. Despite high relative likelihood predictions, the
appropriateness of a translocation effort to the area is inconclusive.</p>
| Identifer | oai:union.ndltd.org:purdue.edu/oai:figshare.com:article/17029676 |
| Date | 22 November 2021 |
| Creators | Zachary T Finn (11715284) |
| Source Sets | Purdue University |
| Detected Language | English |
| Type | Text, Thesis |
| Rights | CC BY 4.0 |
| Relation | https://figshare.com/articles/thesis/MODELING_THE_POTENTIAL_FOR_GREATER_PRAIRIE-CHICKEN_AND_FRANKLIN_S_GROUND_SQUIRREL_REINTRODUCTION_TO_AN_INDIANA_TALLGRASS_PRAIRIE/17029676 |
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