SeedWhere ("Where can I move Seed"? ) maps climate similarity across geographic regions. While the tool can be used to map similarity of climate for any purpose, it was originally intended to support decisions on seed movements to support sustainable forest management.

A number of similarity measures and seed/plant transfer options are possible. This version gives users several choices including: 1) the original Seedwhere, which uses a Gower similarity metric; 2) a threshold approach, which maps areas that fall within user-defined climate limits of a location of interest (e.g., within 5 days of the growing season length at the chosen location); and 3) Universal Response Functions, which are statistical models based on forest genetics analyses. All analyses can be carried out on user-defined study areas within North America and can include climate change scenarios – allowing comparisons of current climate to projected future climates. To get started, select the approach desired.

For more information on SeedWhere see:

McKenney, D.W., Mackey, B.G., Joyce, D, SeedWhere: A computer tool to support seed transfer and ecological restoration decisions. Environmental Modeling and Software, 1999. 14: p. 589-595.

For details on the spatial climate models used here see and/or:

McKenney, D.W., Hutchinson, M.F., Papadopol, P.P., Lawrence, K.M., Pedlar, J.H., Campbell, K., Milewska, E., Hopkinson, R.F., Price, D., Owen, T., 2011. Customized spatial climate models for North America. Bulletin of the American Meteorological Society 92, 1611-1622. doi:10.1175/2011BAMS3132.1

McKenney, D.W., Pedlar, J., Hutchinson, M., Papadopol, P., Lawrence, K., Campbell, K., Milewska, E., Hopkinson, R., Price, D., 2013. Spatial climate models for Canada's forestry community. The Forestry Chronicle, 89(5): p. 659-663.

Gower Metric

The Gower metric provides a measure of similarity between the climate at a location of interest and the climate at all other locations in the study area. In the context of sustainable forest management, this metric provides a simple approach to visualizing how far forest managers might move seed or other plant material away from its maternal climate in the absence of detailed population genetics work. The types of questions this might be relevant for include:

* How similar are the climatic conditions at a seed collection site to other areas?

* How similar are the climatic conditions at a regeneration area to seed already in storage?

Outputs are in the form of maps that show the similarity of climate on a 0 to 1 scale, where 1 is exactly similar and 0 is the least similar. SeedWhere normalizes the values for each selected climate variable so that the similarity metric can be calculated using any number of user-selected variables. When using the climate change models, the program can compare the current climate at the selected location to the projected climate in the selected region (for seed deployment questions) or the future climate at the selected location to the current climate of the selected region (for seed procurement questions). The output also includes a table that summarizes the range of values of the selected climate variables over the geographic area selected.

Additionaly the gower results can be limted to a user defined climatic range. This range can be defined for any of climatic variables, any points that have climatic values outside the range are discarded and not displayed

To proceed make your selections and click on “Draw SeedWhere Map”. You may download your mapped results or statistical results.

URF Approach

The universal response function (URF) approach was developed by Wang et al. (2010) as a means to analyze data from provenance trials, which consist of a variety of seed sources (or provenances) planted at a number of test sites (or common gardens). The approach models a measured provenance characteristic (e.g., height growth) as a function of climate (e.g., mean annual temperature) at both the provenance and test site. The resulting URF can estimate the performance of any seed source at any planting site within the limits of the data used to develop the model. Here we have pulled together a number of published URF equations and related climate data to allow the URF predictions to be mapped under both current and future climates.

For White pine (Pinus strobus) and black spruce (Picea mariana) see:

Yang J, Pedlar JH, McKenney DW, Weersink A (in press) The development of universal response functions to facilitate climate-smart regeneration of black spruce and white pine in Ontario, Canada. Forest Ecology and Management.