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Occupancy Modeling: Interactions. Kyra Stillman. Importance. Determine the actual occupancy Monitor population fluctuations Deduce what affects occupancy rates. Variables. Attempt to find p and ψ , detection and occupancy probabilities Covariates influence occupancy and detection

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Presentation Transcript

Importance
Importance

  • Determine the actual occupancy

  • Monitor population fluctuations

  • Deduce what affects occupancy rates


Variables
Variables

  • Attempt to find pand ψ, detection and occupancy probabilities

  • Covariates influence occupancy and detection

  • R can calculate the most likely values


Questions
Questions

  • Is occupancy modeling a viable option in considering the 2011 interactions?

  • If so, which covariates produce the best model?


Determining influential covariates
Determining influential covariates

  • There are six detection and two occupancy covariates, making for 256 possible combinations

  • Narrowed down to three detection and two occupancy


Akaike information criterion
Akaike Information Criterion

  • AIC measures trade-off between fit and info loss

  • Good criterion for comparing occupancy models

  • Lowest comparative AIC means best fitting model


Results
Results

  • Top three models were WindLightPlantPoll/Round, PlantPoll/RoundPoll, and PlantPoll/Round

  • AIC increased drastically after PlantPoll was removed

  • Round as occupancy was in top five models and top three models w/out PlantPoll


P values
p-Values

  • p-value is a measure of statistical significance

  • None of the covariates had p < 0.05

  • p < 0.05 on Const models only because lack of extra but confounding data

  • Cannot use models to state actual occupancy probability

  • Can compare models to each other to examine covariates


Na ve model and graph
Naïve Model and Graph

  • Naïve model where detection probability is assumed 1

  • Const/Const moves occupancy up and detection down as expected

  • WindLightPlantPoll/Round very high values

Red: Naïve Blue: Const/Const

Green: WindLightPlantPoll/Round


Conclusions
Conclusions

  • PlantPres significant covariate due to how data was collected

  • Round significant in more traditional sense

  • Cannot use models to determine actual occupancy/detection rate

  • Too little data, especially for specialist interactions


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