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Overview

The Climate-Adapted Seed Tool (CAST) helps land managers identify seed sources best adapted to local climate conditions at their planting sites. CAST currently serves five western US states (CA, OR, WA, ID, & NV), though some features are limited to California.

The climate is changing faster than trees can evolve, resulting in climate adaptation mismatch (CAM) wherein trees grow more slowly and suffer higher mortality because they are not well adapted to the climate they now grow in. Reforestation efforts on public and private lands provide opportunities to plant trees that are better adapted to warming climate conditions. By planting seeds that are pre-adapted to the climates of our planting sites we can grow healthier forests, sequester more carbon, grow more lumber, and reduce wildfire risk (Aitken and Bemmels 2015).

The focal metric used in CAST is percent decline in productivity (%DP). %DP is the percent decline in tree volume or biomass that managers should expect due to using a seed source that is not well adapted to the climate the trees will grow in. %DP incorporates the effects of climate on both growth rate and survival. To optimize tree growth and survival managers should seek to minimize the %DP of their chosen seed source. CAST also estimates percent decline in survival (%DS), CO₂ sequestered, and lumber produced (see settings).

Presentations

• Stewart J.A.E., Young D.J.N. (2024) Evidence-Based Tools for Improved Reforestation Outcomes. Quarterly Meeting of the California Climate Hub. Virtual.

• Stewart J.A.E., Wright J.W., Zhao Y., O’Neill G.A., Moran E.V., Thorne J.H., Boynton R.M. (2024) Climate Adapted Seed Tool (CAST): Planting for the Future with Climate-Adapted Seeds. Sierra Nevada Science Symposium, Merced, CA.

• Stewart J.A.E. (2022) The Climate-Adapted Seed Tool: Using Provenance Tests to Inform Oak Seed Transfer in a Changing Climate. 8th California Oak Symposium. San Luis Obispo, CA.

• Stewart J.A.E. (2022) Adapting Forests to Climate Change via Climate-Adapted Seed Transfer. The 10th Biennial UCSC Plant Science Symposium. Santa Cruz, CA.

• Wright J.W. (2021) Adapting Forests to Climate Change via Climate-Adapted Seed Transfer. UC Forestry and Range. Virtual.

• Stewart J.A.E. (2021) Optimizing Assisted Gene Flow for Forests. Introduction, Breeding, Propagation and Deployment of Pacific Northwest Conifers Around the World: 70 years of Progress, Opportunities and Challenges. Virtual.

Provenance Tests

The effects of climate adaptation mismatch (CAM) are measured with provenance test experiments, where seeds from different climates are planted at common locations and the trees are measured over time. Most provenance trials use robust randomized block designs, but trials planted for demonstration purposes sometimes plant trees in rows ordered by the climate of the seed origin. These demonstrations make the effects of CAM obvious to the casual observer (Fig 1).

The transfer functions currently used in the tool are fit to lodgepole pine data from the Illingworth Trial and Douglas-fir data from the Munger and Trinity trials. The Illingworth trial established over 70,000 lodgepole pine trees from 184 seed source locations at 60 planting locations and measured them for up to 32 years of growth. Together, the Munger and Trinity trials, planted over 25,000 Douglas-fir trees from 77 seed source locations at 6 planting locations and measured them for up to 100 years. We have similar data, albeit sometimes with smaller sample sizes, from 12 other Western-North-American tree species. Preliminary analyses of data for these species suggest the way lodgepole pine and Douglas-fir respond to climatic transfer of seeds is a reasonable first approximation of how most other species respond (see also Aitken and Bemmels 2015). However, species do vary in their responses and transfer functions tailored to other species are in development.

Statistical Models

CAST uses two types of statistical models: climate transfer functions and growth and yield functions. Climate transfer functions use provenance test data to estimate the effects of seed source on tree growth and survival (Fig 2). Growth and yield functions use Forest Inventory and Analysis (FIA) data to estimate the effects of site climate on CO₂ storage and lumber production in the absence of CAM. The two models are integrated to estimate the effects of seed source on growth and yield.

The transfer functions in CAST fit multidimensional asymmetric bell-shaped curves (Fig 3) to provenance test data and four climate variables. The climate variables are mean annual temperature, mean cold-month temperature, mean annual precipitation, and temperature differential (also known as continentality, the difference between summer and winter temperatures). Growth and yield functions (CO₂ and lumber production) fit modified Monod curves to FIA data. They currently use two climate variables: mean annual temperature and mean annual precipitation. Model fitting was conducted with Stan by Dr. Joe Stewart and in collaboration with Dr. Jessica Wright.

Age and species-specific models available in CAST are currently limited to those described in Table 1. Climate transfer functions for other species and tree ages are in development. The lodgepole pine transfer function is currently used as a stand-in for species that do not yet have their own transfer functions in CAST.

Climate Data

CAST uses downscaled historical PRISM climate surfaces and LOCA future climate surfaces. PRISM surfaces were statistically downscaled to 300-m resolution by Dr. Joe Stewart in collaboration with Dr. Robert Hijmans. The future climate data currently used in the tool is the ensemble of 10 GCMs selected by the California Department of Water Resources Climate Change Technical Advisory Group based on their historical performance at the global scale, across the Southwestern United States, and for specific needs of California water resources planning (Lynn et al. 2015). The emissions scenario used by the tool is Representative Concentration Pathway 8.5 (RCP 8.5). RCP 8.5 is the trajectory that most closely matches recent historical (2005-2020) emissions (Schwalm et al. 2020) and is a good choice for near-term (e.g. 2021-2050) climate projections. Medium-term (e.g. 2051-2100) projections are more influenced by human behavior and this uncertainty is not yet accounted for in CAST.

Seedbank Inventory

To facilitate finding the best seed for your project CAST integrates seedbank inventory data. The data currently used in the tool is a static snapshot of CALFIRE and USFS seedbank inventory from December 2020. Seedbank inventory is not available in the public version of the tool. For access to the tool with seedbank inventory please contact JoeStewart :at: UCDavis.edu.

Using CAST with Other Tools

Recommended Postfire Reforestation Workflow for Natural Lands:

1. Use PostCRPT to prioritize areas in need of conifer restoration. Use local knowledge and site surveys to thoughtfully assess and potentially adjust model predictions.

2. Use PReSET to prioritize areas where restoration is likely to succeed. Use local knowledge and site surveys to thoughtfully assess and potentially adjust model predictions.

3. Use CAST (this tool) to select native seeds that are likely to be pre-adapted to the changing climate conditions they will grow in. Use local knowledge and other data (e.g. soils, hydrology, sun exposure) to thoughtfully assess and potentially adjust model predictions.

Recommended Timber Production Workflow:

Use CAST (this tool) to select native seeds that are likely to be pre-adapted to the changing climate conditions they will grow in. Use local knowledge and other data (e.g. soils, hydrology, sun exposure) to thoughtfully assess and potentially adjust model predictions.

Development

CAST is developed by Joe Stewart and Yueru Zhao in collaboration with Jessica Wright. Greg O’Neill has been a crucial advisor.

Version History

• CAST version 0.059 – Released August 12, 2024. Updated climate-based growth and yield (GY) functions. GY functions are now available for estimating carbon storage and lumber production for six species, Abies concolor, A. magnifica, Pinus contorta, P. jeffreyi, P. ponderosa, and Pseudotsuga menziesii. GY functions are fit to FIA data using modified Monod functions, loosely based on methods from Zhu et al. (2018). GY functions are fit to ≈ 9,400 surveys of FIA plots from 5 western states. GY functions now use proportion of species-specific biomass (≥ 75% tree biomass belonging to that species) instead of the FIA forest type attribute to classify stands by species type. Other minor updates.

• CAST version 0.042 – Released June 16, 2024. Incudes option to find planting locations for a specified seed source location. Sped up rendering of large geographic transfer distances by reducing raster resolution when large geographic transfer limits are selected. Squashed minor user interface bugs. Other optimizations.

• CAST version 0.03 – Released April 5, 2023. Future climate periods are now available at 5-yr resolution instead of decadal resolution. The default climate period to optimize seeds for has been updated to the multiple of five years that is nearest to 20 yrs in the future (currently 2045). This follows the rough guideline that seeds should be optimized for conditions ≈ 20 years in the future (Aitken and Bemmels 2015). Updated near-term 19-yr mean climate periods to incorporate observed climate up through 2022 (i.e., the 19-yr mean climate for for 2030 is calculated as the annual-weighted mean of PRISM for 2021-2022 and the GCM-ensemble mean projected climate for 2023-2039). Minor code optimizations. Updates to broken links.

• CAST version 0.023 – Released June 17, 2022. Accounts for geographic uncertainty associated with seed-zone elevation bands. Includes climate transfer functions for Pinus contorta and Pseudopsuga menzessi and growth and yield functions for P. Ponderosa, P. contorta, and P. menzessi. The climate transfer function for P. contorta is used for generalized predictions for other species that are data depauperate or where climate transfer functions have not yet been fully tested. Expands geographic coverage (for raster-based predictions) outside of California to areas of the conterminous United States west of the eastern edge of Idaho (includes CA, OR, WA, NV, ID, and portions of MT, UT, & AZ). Includes an experimental species suitability feature based on SDMs (click on the species heading above the dropdown menu on the right to access). Added ‘regional constraints’ and ‘display productivity relative to’ options under settings.

• Seed Zone Climate Tracker version 0.3 – Released Jan, 2021. An early predecessor to the Climate-Adapted Seed Tool. The Seed Zone Climate Tracker uses standardized Euclidean climate distances (SECD) to find analog climate conditions across space (CA seed zones) and time. While the SECD approach may be an improvement over no implementation of climate-based seed transfer, it does not incorporate any biological data (e.g., seed transfer experiments) and necessarily uses arbitrary weighting of climate/environmental variables–determined by the domain of the analyses. Climate data used in the Seed Zone Climate Tracker is BCMv65 .

Funding

This project is supported by CAL FIRE’s Reforestation Services Program, Fire Resource Assessment Program, by the University of California Office of the President, and by the USFS Pacific Southwest Research Station.