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Range-wide, species-specific, ecological and historical biogeography:
Getting the concepts right in ecological niche modeling and species distribution modeling
A. Townsend PetersonUniversity of Kansas
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It Is Not That Simple1. Spatial Autocorrelation2. Study Design – M3. Study Design – BAM4. MESS and MOP
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It Is Not That Simple1. Spatial Autocorrelation2. Study Design – M3. Study Design – BAM4. MESS and MOP
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The Area of Distribution
G Physiological requirements
(Abiotic)
A
Favorable bioticenvironment
(Biotic)B
Accessible to dispersal(Movements)
M
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Test Arena: The Lawrence Species
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Model Evaluation
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Model Comparison
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It Is Not That Simple1. Spatial Autocorrelation2. Study Design – M3. Study Design – BAM4. MESS and MOP
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The Area of Distribution
G Physiological requirements
(Abiotic)
A
Favorable bioticenvironment
(Biotic)B
Accessible to dispersal(Movements)
M
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BAM II
ClassicBAM
Hutchinson’sDream
Wallace’sDream
All OK
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Effect of BAM Scenarios
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It Is Not That Simple1. Spatial Autocorrelation2. Study Design – M3. Study Design – BAM4. MESS and MOP
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Assess levels of spatial autocorrelation in environmental data, adjust input point data accordingly
Estimate ecological niche (various algorithms)
Evaluation reality of model transfer results, when possible
Transfer to other situations—time and space
Project niche model to geographic space
Model calibration, adjusting parameters to maximize quality
Collate primary biodiversity data documenting occurrences
Process environmental layers to be maximally relevant to distributional ecology of species in question
Collate GIS database of relevant environmental data layers
Assess BAM scenario for species in question; avoid M-limited situations
Saupe et al. 2012. Variation in niche and distribution model performance: The need for a priori assessment of key causal factors. Ecological Modelling, 237–238, 11-22.
Estimate M as area of analysis in study
Barve et al. 2011. The crucial role of the accessible area in ecological niche modeling and species distribution modeling. Ecological Modelling, 222, 1810-1819.
Assess extrapolation (MESS and MOP)
KU Ecological Niche Modeling Group. 2013. Constraints on interpretation of ecological niche models by limited environmental ranges on calibration areas. In preparation.
Model evaluationPeterson et al. 2008. Rethinking receiver operating characteristic analysis applications in ecological niche modelling. Ecological Modelling, 213, 63-72.
Model thresholdingPeterson et al. 2007. Transferability and model evaluation in ecological niche modeling: A comparison of GARP and Maxent. Ecography, 30, 550-560.
Assess spatial precision of occurrence data, adjust inclusion of data (obs and env) accordingly
General Methodological Summary: Peterson et al. (2011) Ecological Niches and Geographic Distributions, Princeton University Press, Princeton.
Refine estimate of current distribution via land use, etc.
Reduce dimensionality
Compare present and future to assess effects of change
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Atlas of Brazilian Triatomines I
Panstrongylus geniculatusPanstrongylus lutzi
Panstrongylus megistusPsammolestes tertius
Rhodnius nasutusRhodnius neglectusRhodnius pictipesRhodnius robustus
Triatoma melanocephalaTriatoma pseudomaculata
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Factor ComparisonsNo geographic structuring with respect to phylogeny, such that evolutionary origin or “geographic inertia” appears to have little explanatory power for the distributions of Leishmania clades in Brazil.
Close coincidence between distributions
of vectors and Leismania clades and
among clades with respect to environment.
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Assess levels of spatial autocorrelation in environmental data, adjust input point data accordingly
Estimate ecological niche (various algorithms)
Evaluation reality of model transfer results, when possible
Transfer to other situations—time and space
Project niche model to geographic space
Model calibration, adjusting parameters to maximize quality
Collate primary biodiversity data documenting occurrences
Process environmental layers to be maximally relevant to distributional ecology of species in question
Collate GIS database of relevant environmental data layers
Assess BAM scenario for species in question; avoid M-limited situations
Saupe et al. 2012. Variation in niche and distribution model performance: The need for a priori assessment of key causal factors. Ecological Modelling, 237–238, 11-22.
Estimate M as area of analysis in study
Barve et al. 2011. The crucial role of the accessible area in ecological niche modeling and species distribution modeling. Ecological Modelling, 222, 1810-1819.
Assess extrapolation (MESS and MOP)
KU Ecological Niche Modeling Group. 2013. Constraints on interpretation of ecological niche models by limited environmental ranges on calibration areas. In preparation.
Model evaluationPeterson et al. 2008. Rethinking receiver operating characteristic analysis applications in ecological niche modelling. Ecological Modelling, 213, 63-72.
Model thresholdingPeterson et al. 2007. Transferability and model evaluation in ecological niche modeling: A comparison of GARP and Maxent. Ecography, 30, 550-560.
Assess spatial precision of occurrence data, adjust inclusion of data (obs and env) accordingly
General Methodological Summary: Peterson et al. (2011) Ecological Niches and Geographic Distributions, Princeton University Press, Princeton.
Refine estimate of current distribution via land use, etc.
Reduce dimensionality
Compare present and future to assess effects of change
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Thanks [email protected]
Biodiversity Informatics journal:https://journals.ku.edu/index.php/jbi
Biodiversity Informatics Training Curriculum:http://www.facebook.com/groups/BiodiversityInformatics
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