Uncertainty in Species Distribution Mapping

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Types of dataSpecies occurrence (response variables):• Presence only• Presence-’absence’• Detection-Nondetection• CountPredictors: Macro-habitat (global/landscape level features)
Modeling approaches used:Presence only data: Maximum Entropy (MaxEnt)Presence-’absence’ data: Logistic regression (R)Count data: Zero-inflated Negative Binomial regression (R)Detection-non detection data: Occupancy (Program PRESENCE)
Page 1 and 2: UNCERTAINTY INPREDICTING SPECIES DI
Page 3 and 4: Outline Background Why species dist
Page 5 and 6: www.tamrin.proboards.com/Why: Examp
Page 7: Conservation vs.DevelopmentHigh Con
Page 11 and 12: Kernel Density
Page 13 and 14: Home-range buffer 2
Page 15 and 16: Predicting species distribution: ty
Page 17: Other issues : scaleAdapted from: K
Page 20 and 21: Study Area
Page 24 and 25: Relative importance of variablesMax
Page 26 and 27: MaxEnt
Page 28 and 29: Count
Page 30 and 31: “All models are wrong, butsome ar
Page 32 and 33: ‘Correct predictions’ by differ
Page 34: AcknowledgementFinancial & programm

Uncertainty in Species Distribution Mapping

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