AGU 2024 Poster, Talk, and Organized Session

Author

Published

December 3, 2024

I’ll be at AGU in Washington DC this December 9-13th to present on our work building Bayesian Models of tree growth and mortality, and to co-convene a session.

Send me an email if you want to chat about forest C, tree growth modelling, and Bayesian modelling!

Poster: GC21K-0018 Fusion of tree ring data and forest inventory data to improve estimates of tree growth, C sequestration variability, and climate sensitivity

Talk: B34B-06 Growth Reductions are an Early Warning Sign of Tree Mortality in the Northeastern US Detectable in Historic Forest Inventories

Co-convening Sessions:

Advances in Understanding and Predicting Forest Demography and Carbon in a Changing World.

Check out my poster on our work modeling tree growth to improve inter annual estimates of forest C below!

Abstract:

The US Green House Gas Inventory compiles annual estimates of forest carbon stocks and sequestration capacity based on plot-level data collected through the US Forest Inventory and Analysis (FIA) program. Although this inventory design is an “annual” design, each plot is remeasured on a cycle every ~5-10 years, such that estimates of forest C may miss year-to-year variations in tree or plot-level growth and C sequestration between remeasurements. Lack of year-to-year variation in these estimates makes it difficult to quantify the effect of annual climate variability and episodic events (fire disturbances, insect outbreaks, pathogens) on forest C trends. Here, we advance estimates of annual variability of diameter growth for >15,000 trees from 17 common species of the Northeastern US using a suite of Bayesian state-space models, which link tree diameters and annual tree ring data from site trees associated with FIA plots in the 1980’s.

Models that include competition indices, tree size, two species-specific climate variables, and site-level factors capture inter-annual variability in held out annual diameter increments. While the magnitude and sign of posterior estimates of explanatory covariates vary across species, inclusion of annual climate variability consistently improves prediction of annual diameter increments. Validation of these predictions with in-sample and held-out tree ring date indicates a RMSPE of 0.0006 and 0.097 respectively. Using the posterior estimates to predict annual diameter increments from the first measurement of the non-cored, tally trees between remeasurements produces climate sensitive estimates of growth for trees. We compare the state-space model estimates of annual growth to current methods (interpolation and averaging growth from two diameter measurements). Compared to interpolation, state-space estimation enabled with tree-ring data captures annual growth variability at the tree-level, which may indicate that current stock-difference approaches could underestimate variability of forest C sequestration at the plot-scale. This approach lays the foundation to scale this approach to stand-scale estimates of historic annual C sequestration needed to improve annual estimates of the forest C component of the US GHG inventory.

References:

  1. Smith, R. B., Hornbeck, J. W., Federer, C. A., J, P., Krusic, J., & Jr..Krusic, P. J. (1990). Regionally averaged diameter growth in New England forests. Res. Pap. NE-637. Radnor, PA: US. Department of Agriculture, Forest Service, Northeastern Forest Experiment Station. 26 p., 637. https://doi.org/10.2737/NE-RP-637
  2. Hornbeck, J. W., Smith, R. B., & Federer, C. A. (1988). Growth trends in 10 species of trees in New England, 1950–1980. Canadian Journal of Forest Research, 18(10), 1337–1340. https://doi.org/10.1139/x88-206
  3. Canham, C. D., Murphy, L., Riemann, R., McCullough, R., & Burrill, E. (2018). Local differentiation in tree growth responses to climate. Ecosphere, 9(8), e02368. https://doi.org/10.1002/ecs2.2368
  4. Evans, M. E. K., DeRose, R. J., Klesse, S., Girardin, M. P., Heilman, K. A., Alexander, M. R., Arsenault, A., Babst, F., Bouchard, M., Cahoon, S. M. P., Campbell, E. M., Dietze, M., Duchesne, L., Frank, D. C., Giebink, C. L., Gómez-Guerrero, A., García, G. G., Hogg, E. H., Metsaranta, J., … GaytÁn, S. A. V. (2022). Adding Tree Rings to North America’s National Forest Inventories: An Essential Tool to Guide Drawdown of Atmospheric CO2. BioScience, 72(3), 233–246. https://doi.org/10.1093/biosci/biab119
  5. Heilman, K. A., Dietze, M. C., Arizpe, A. A., Aragon, J., Gray, A., Shaw, J. D., Finley, A. O., Klesse, S., DeRose, R. J., & Evans, M. E. K. (2022). Ecological forecasting of tree growth: Regional fusion of tree-ring and forest inventory data to quantify drivers and characterize uncertainty. Global Change Biology. 28: 2442-2460., 28, 2442–2460. https://doi.org/10.1111/gcb.16038