Uncertainty in Species Distribution Mapping

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A case study: predict<strong>in</strong>g tiger distribution• Critically endangered• Elusive: high association with uncerta<strong>in</strong>ty• Urgent need for distribution maps• Year of the tiger

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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 21 and 22: Study Area17 km17 km
Page 23 and 24: Modeling approaches used:Presence o
Page 25 and 26: Summary of predictionsMaxent Logist
Page 27 and 28: Logisticregression
Page 29 and 30: Occupancy
Page 31 and 32: Concordance (%) between modelsOvera
Page 33 and 34: ConclusionsBetter to model than sim

Uncertainty in Species Distribution Mapping

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