Uncertainty in Species Distribution Mapping

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‘Correct predictions’ by different models( based on presence-only tiger records in 20 grids collected from independent surveys)Percentage of correct prediction100%75%50%25%MaxEntOccupancyCountLogistic regression0%1 2 3 4Treshholds on probability of occurrence34 1 = Very low, 2= low, 3= medium, 4= high
ConclusionsBetter to model than simply to map occurrence: accounting samplingefforts & environmental variablesIgnoring detection probability ~ underestimating the populationparametersVariation in results from different modelsModel robustness for some variables & areasAccount for missing detections whenever possible: use occupancyFor some cases, presence-only model is still an acceptable choice.
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 22 and 23: Types of dataSpecies occurrence (re
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 34: AcknowledgementFinancial & programm

Uncertainty in Species Distribution Mapping

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