Climate Change Atlas

Multistage modelling approach

Our modelling approach is designed to help determine:

  • How suitable tree and bird species habitats may change under future climates
  • The likelihood that modelled future habitats are colonized by the species
  • How much can unmodelled factors like disturbances and biological characteristics change future outcomes

Multistage modelling scheme

Our mutistage approach uses two models, DISTRIB and SHIFT, and one decision support system, MODFACs.  DISTRIB predicts potential suitable species habitats for 134 tree species under current and future climates.  SHIFT is used to determine the likelihood of the tree species colonizing these new suitable habitats. DISTRIB+SHIFT gives the potential colonization by 2100. MODFACs (Modification factors) which uses a scoring system based on literature survey can be used to look at how outside disturbances and biological factors might influence the future distributions of these species. The results of DISTRIB and MODFACs can be explored via the tree atlas, with SHIFT results coming soon. The bird atlas is the result of the bird DISTRIB model that incorporates output from the tree DISTRIB model to predict the distribution of 147 bird species.
This multi-stage approach can be used to explore and evaluate the impact of climate change on species habitat distributions better than a single-model approach. See (Iverson 2011) for details of our strategy.  Our approach has been used as a decision support system to plan for better management under current and future disturbances via regional assessments.

We briefly discuss each component of the schematic diagram below. Please refer to citations for more detail.


For trees, response variables are the importance values (IV) of 134 tree species. IVs is a relative measure of abundance which is calculated from US Forest Service's Forest Inventory and Analysis (FIA) data for 37 states east of the 100th meridian. It consisted of over 100,000 plots and nearly 3 million tree records. The importance values were calculated as
Importance Value Formula
where x is the species, BA is the basal area and NS is the number of stems. AllSpp indicates all species present in the plot. Therefore, IV is a measure of relative abundance. Its value ranges from 0 to 100 ; the latter indicating monotypic stands of the species. The plot data is aggregated to 20 km cells.

For birds, response variables are incidences of 147 bird species from nearly 1000 Breeding Bird Survey routes. Incidence is calculated as the number of occurrences recorded/route over 7-10 yrs and aggregated to 20 km cells. The incidences range from 0 to 1. 

For the tree DISTRIB model we used 38 predictors which consist of 7 climate variables, 5 elevation classes, 9 soil classes, 13 soil properties and 4 landuse variables. The bird DISTRIB model uses a total of 50 variables, which includes 7 climate variables, 5 elevation classes and 39 modelled tree IVs. Hence the bird DISTRIB is coupled to the tree DISTRIB as the habitat of birds depends on the tree species available.

To model future climates we swap the current climate with future climates predicted by 3 GCM models (HadCM3 (Hadley), GFDL and PCM) under two carbon emission scenarios (the harsh but realistic A1FI (High) and the mild optimistic scenario of B1 (Low) according to IPCC). This results in the following scenarios:

  • Current FIA
  • Current Modelled
  • HadleyCM3 – A1FI (High, “Harsh”)
  • HadleyCM3 – B1 (Low)
  • PCM – A1FI (High)
  • PCM – B1 (Low, “Mild”)
  • GFDL – A1FI (High)
  • GFDL – B1 (Low)
  • Avg. of 3 GCMs – A1FI (High)
  • Avg. of 3 GCMs – B1 (Low)
Note that Hadley High is the harshest and PCM Low is the mildest scenario. See the (Iverson 2008) for details on the data inputs.


The DISTRIB model predicts suitable habitat as depicted by IVs for tree and incidences for bird species under current (~2000) and future (~2100) climates. The DISTRIB species model has served as the core of the multi-stage approach. The FIA data and the DISTRIB model provides a basis for depicting the species current distribution as well as how the habitat for these species might change with changing climate.

The DISTRIB model is based on decision-tree based ensemble approach called TriMod which uses a robust technique called RandomForest for prediction. See (Prasad 2006) for details of the ensemble modelling technique. Using 38 predictors that includes climate, soil, elevation and landuse variables as discussed in the Data section, tree DISTRIB models the IVs of 134 tree species that are mapped as suitable habitats of the species. The bird DISTRIB uses the modelled suitable habitat of trees as input, in addition to climate and elevation variables, to model the incidences of 147 bird species. See (Matthews 2011a) for details on bird DISTRIB.  Future distributions are modelled by swapping the current climate with GCM predicted future climates as discussed in the Data section.
Not all species models are equal - we therefore need to know about the "model reliability" of each modelled species. We therefore rate for each species, the reliability of the DISTRIB model into three classes - high, medium and low - taking into account several model performance factors.

An important caveat when interpreting our DISTRIB model is that we are predicting potential suitable habitat by year 2100 – not where the species will be. See (Iverson 2008) for details of the DISTRIB modelling approach.


DISTRIB predicts future suitable habitats, but these habitats may not be colonized in this century depending on the speed that a tree species can migrate and the fragmented nature of the landscapes. This is where SHIFT, a spatially explicit simulation model steps in, to calculate the likelihood of colonization based on the abundance of a tree species within its current range (source region), the habitat quality of the landscape beyond the source range boundary (sink) and the distance between occupied and unoccupied areas, for a range of historical migration rates (~ 10 km to > 100 km/century). SHIFT thus calculates the likelihood of colonization for suitable sink habitats (in approximately 100 year time period consiting of multiple generations depending on the tree species). See (Prasad 2013) for details on the SHIFT model.


The future suitable habitats predicted by DISTRIB (~ 2100) are intersected with SHIFT likelihood of colonization (100 years), to estimate the likehihood of colonization of these future sink habitats around 2100. This typically shows only a small percentage of the sink habitats (ie., beyond the current range boundary) available to the tree species, has any chance (say > 5%) of colonization. Using this approach we can screen multiple tree speices and assess suitable migration corridors and patches that could help iin assisted colonization of valuable forest tree species that may not be able to keep pace with rapid climate change.

Currently the SHIFT model is not yet implemented in the climate change atlas. We hope to incorporate it shortly. The diagram below shows the DISTRIB output and SHIFT model intersected for post oak (Quercus stellata). It illustrates the nature of DISTRIB and SHIFT and how they are combined to produce potential colonization likelihood by 2100. Notice that only a small percentage of the future sink habitats have any chance of getting colonized.

DISTRIB+SHIFT intersection

MODFACs (Modification Factors)

The DISTRIB and the SHIFT models cannot take into account the multitude of biological and disturbance factors affecting species distribution (insect outbreaks, fire, etc). We therefore use a scoring system based on the available literature to account for these factors. Our scoring system gauges the effect of 9 biological and 12 disturbance components in modifying the interpretations of the species response outcomes from the DISTRIB and SHIFT models. This framework also addresses species model uncertainties in light of climate change. Forest managers and other end users who have expertise locally can modify the tabular scoring system locally or regionally, to obtain customized outputs and inform management relevant decisions. See (Matthews 2011b) for details.
An example for red maple, a highly adaptable species, achieving the highest score of 8.5 is shown below.

ModFacs for Red Maple

Regional species management

We have used the outputs of the multi-stage approach, mainly DISTRIB and MODFACs to assess management options for different regions. See (Swanston 2011) for details on regional assessment.


Prasad, A.M., L.R. Iverson, and A. Liaw 2006. Newer classification and regression tree techniques: bagging and random forests for ecological prediction. Ecosystems, 9:181–199.

Iverson, L. R., A. M. Prasad, S. N. Matthews, and M. Peters. 2008. Estimating potential habitat for 134 eastern US tree species under six climate scenarios. Forest Ecology and Management 254:390-406.

Prasad, A. M., J. Gardiner, L. Iverson, S. Matthews, and M. Peters. 2013. Exploring tree species colonization potentials using a spatially explicit simulation model: implications for four oaks under climate change. Global Change Biology 19: 2196–2208.

Matthews, S. N., L. R. Iverson, A. M. Prasad, and M. P. Peters. 2011. Potential habitat changes of 147 North American bird species to redistribution of vegetation and climate following predicted climate change. Ecography 260:1460-1472.

Matthews, S. N., L. R. Iverson, A. M. Prasad, M. P. Peters, and P. G. Rodewald. 2011. Modifying climate change habitat models using tree species-specific assessments of model uncertainty and life history factors. Forest Ecology and Management 262:1460-1472.

Iverson, L., A. M. Prasad, S. Matthews, and M. Peters. 2011. Lessons learned while integrating habitat, dispersal, disturbance, and life-history traits into species habitat models under climate change. Ecosystems 14:1005-1020.

Swanston, Chris; Janowiak, Maria; Iverson, Louis; Parker, Linda; Mladenoff, David; Brandt, Leslie; Butler, Patricia; St. Pierre, Matt; Prasad, Anantha; Matthews, Stephen; Peters, Matthew; Higgins, Dale; Dorland, Avery. 2011. Ecosystem vulnerability assessment and synthesis: a report from the Climate Change Response Framework Project in northern Wisconsin. Gen. Tech. Rep. NRS-82. Newtown Square, PA: U.S. Department of Agriculture, Forest Service, Northern Research Station. 142 p.