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

It Is Not That Simple1. Spatial Autocorrelation2. Study Design – M3. Study Design – BAM4. MESS and MOP

It Is Not That Simple1. Spatial Autocorrelation2. Study Design – M3. Study Design – BAM4. MESS and MOP

The Area of Distribution

G Physiological requirements

(Abiotic)

A

Favorable bioticenvironment

(Biotic)B

Accessible to dispersal(Movements)

M

Test Arena: The Lawrence Species

Model Evaluation

Model Comparison

It Is Not That Simple1. Spatial Autocorrelation2. Study Design – M3. Study Design – BAM4. MESS and MOP

The Area of Distribution

G Physiological requirements

(Abiotic)

A

Favorable bioticenvironment

(Biotic)B

Accessible to dispersal(Movements)

M

BAM II

ClassicBAM

Hutchinson’sDream

Wallace’sDream

All OK

Effect of BAM Scenarios

It Is Not That Simple1. Spatial Autocorrelation2. Study Design – M3. Study Design – BAM4. MESS and MOP

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

Atlas of Brazilian Triatomines I

Panstrongylus geniculatusPanstrongylus lutzi

Panstrongylus megistusPsammolestes tertius

Rhodnius nasutusRhodnius neglectusRhodnius pictipesRhodnius robustus

Triatoma melanocephalaTriatoma pseudomaculata

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.

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

Thanks Much!town@ku.edu

Biodiversity Informatics journal:https://journals.ku.edu/index.php/jbi

Biodiversity Informatics Training Curriculum:http://www.facebook.com/groups/BiodiversityInformatics

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