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“Canonical” Ecological Niche
Modeling
Google “Species Distribution Model”
The Essence of the Method
• Use primary occurrence data
• Use raster environmental data sets
• Combine the two data streams in a model
• Use the model to make a map
• Map is interpreted as “probability of
presence” of the species
• It’s simple, right?
It’s More Complicated…
• Accumulate input data
• Data quality – occurrence data
• Data quality – environmental data
• Consistency between occurrence data and
environmental data
• Check biogeographic/ecological scenario
• Choose area for model calibration
• Calibrate the model
• Model evaluation
• Check model extrapolation
• … NOW, you can interpret your model
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)
Owens, H. L., L. P. Campbell, L. L. Dornak, E. E.
Saupe, N. Barve, J. Soberón, K. Ingenloff, A. Lira-
Noriega, C. M. Hensz, C. E. Myers, and A. T.
Peterson. 2013. Constraints on interpretation of
ecological niche models by limited
environmental ranges on calibration areas.
Ecological Modelling 263:10-18.
Model evaluation
Peterson et al. 2008. Rethinking receiver operating
characteristic analysis applications in ecological niche
modelling. Ecological Modelling, 213, 63-72.
Model thresholding
Peterson 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
Qiao, H., J. Soberón, and A. T. Peterson.
2015. No silver bullets in correlative
ecological niche modeling: Insights from
testing among many potential algorithms for
niche estimation. Methods in Ecology and
Evolution 6:1126-1136.

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D1T2 canonical ecological niche modeling

  • 3. The Essence of the Method • Use primary occurrence data • Use raster environmental data sets • Combine the two data streams in a model • Use the model to make a map • Map is interpreted as “probability of presence” of the species • It’s simple, right?
  • 4.
  • 5.
  • 6. It’s More Complicated… • Accumulate input data • Data quality – occurrence data • Data quality – environmental data • Consistency between occurrence data and environmental data • Check biogeographic/ecological scenario • Choose area for model calibration • Calibrate the model • Model evaluation • Check model extrapolation • … NOW, you can interpret your model
  • 7. 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) Owens, H. L., L. P. Campbell, L. L. Dornak, E. E. Saupe, N. Barve, J. Soberón, K. Ingenloff, A. Lira- Noriega, C. M. Hensz, C. E. Myers, and A. T. Peterson. 2013. Constraints on interpretation of ecological niche models by limited environmental ranges on calibration areas. Ecological Modelling 263:10-18. Model evaluation Peterson et al. 2008. Rethinking receiver operating characteristic analysis applications in ecological niche modelling. Ecological Modelling, 213, 63-72. Model thresholding Peterson 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 Qiao, H., J. Soberón, and A. T. Peterson. 2015. No silver bullets in correlative ecological niche modeling: Insights from testing among many potential algorithms for niche estimation. Methods in Ecology and Evolution 6:1126-1136.