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Background selection complexity influences Maxent predictive performance in freshwater systems
Tyler E. Schartel
,
Yong Cao
Illinois Natural History Survey
Natural Resources and Environmental Sciences
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Dive into the research topics of 'Background selection complexity influences Maxent predictive performance in freshwater systems'. Together they form a unique fingerprint.
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Keyphrases
Maximum Entropy
100%
Performance Prediction
100%
Freshwater Systems
100%
Background Selection
100%
Species Distribution Models
83%
Selection Strategy
50%
Validation Data
50%
Presence-absence
33%
Area under the Curve
33%
Modeling Performance
33%
Sampling Bias
33%
Lotic Systems
33%
Modeling Prediction
33%
True Skill Statistic
33%
Prediction Specificity
33%
Geographical Constraints
16%
Midwestern United States
16%
Prediction Accuracy
16%
Across Species
16%
Statistical Measures
16%
Pairwise Comparison
16%
Habitat Factors
16%
Species Occurrence
16%
Species Occurrence Data
16%
Stream Size
16%
Freshwater mussels
16%
Absence Data
16%
Core Habitat
16%
Intensive Survey
16%
Presence-background
16%
Pseudo-absences
16%
Agricultural and Biological Sciences
Selection Method
100%
Lotic Systems
66%
Mussel
33%
Biochemistry, Genetics and Molecular Biology
Background Selection
100%
Species Distribution
83%
Mussel
16%