Parameters of 150 Temperate and Boreal Tree Species for an Individual-Based Forest Landscape and Disturbance Model (2024)

See all articles by Dominik Thom

Dominik Thom

affiliation not provided to SSRN

Werner Rammer

affiliation not provided to SSRN

Katharina Albrich

Natural Resources Institute Finland

Kristin H. Braziunas

affiliation not provided to SSRN

Laura Dobor

Czech University of Life Sciences Prague (CULS)

Christina Dollinger

affiliation not provided to SSRN

Winslow D. Hansen

Cary Institute of Ecosystem Studies

Brian J. Harvey

University of Washington

Tomas Hlásny

Czech University of Life Sciences Prague (CULS)

Tyler J. Hoecker

affiliation not provided to SSRN

Juha Honkaniemi

Natural Resources Institute Finland

William S. Keeton

University of Vermont - Rubenstein School of Environment and Natural Resources

Yuta Kobayashi

Tokyo University of Agriculture and Technology

Sofia Saenz Kruszka

University of Washington

Akira S. Mori

Tokyo University of Agriculture and Technology

Jenna E. Morris

University of Washington

Stephen Peters-Collaer

University of Vermont

Zak Ratajczak

Kansas State University

Trond Simensen

Norwegian Institute for Nature Research

Ilié Storms

KU Leuven

Kureha F. Suzuki

Tokyo University of Agriculture and Technology

Anthony Taylor

affiliation not provided to SSRN

Monica G. Turner

affiliation not provided to SSRN

Susan Willis

affiliation not provided to SSRN

Rupert Seidl

Technische Universität München (TUM)

Abstract

Understanding the impacts of changing climate and disturbance regimes on forest ecosystems is greatly aided by the use of process-based models. Such models simulate processes based on first principles of ecology, which requires parameterization. Parameterization is an important step in model development and application, defining the characteristics of trees and their responses to the environment, i.e., their traits. For species-specific models, parameterization is usually done at the level of individual species. Parameterization is indispensable for accurately modeling demographic processes, including growth, mortality, and regeneration of trees, along with their intra- and inter-specific interactions. As it is time-demanding to compile the parameters required to simulate forest ecosystems in complex models, simulations are often restricted to the most common tree species, genera, or plant-functional types. Yet, as tree species composition might change in the future, it is important to account for a broad range of species and their individual responses to drivers of change explicitly in simulations. Thus, species-specific parameterization is a critical task for making accurate projections about future forest trajectories, yet species parameters often remain poorly documented in simulation studies.We compiled and harmonized all existing tree species parameters available for the individual-based forest landscape and disturbance model (iLand). Since its first publication in 2012, iLand has been applied in 50 peer-reviewed publications across three continents throughout the Northern Hemisphere (i.e., Europe, North America, and Asia). The model operates at individual-tree level and simulates ecosystem processes at multiple spatial scales, making it a capable process-based model for studying forest change. However, the extensive number of processes and their interactions as well as the wide range of spatio-temporal scales considered in iLand require intensive parameterization, with tree species characterized by 66 unique parameters in the model. The database presented here includes parameters for 150 temperate and boreal tree species and provenances (i.e., regional variations). Excluding missing values, the database includes a total of 9,249 individual parameter entries. In addition, we provide parameters for the individual susceptibility of tree species to wind disturbance (five parameters) for a subset of 104 tree species and provenances (498 parameter entries). To guide further model parameterization efforts, we provide an estimate of uncertainty for each species based on how thoroughly simulations with the respective parameters were evaluated against independent data.Our dataset aids the future parameterization and application of iLand, and sets a new standard in documenting parameters used in process-based forest simulations. This dataset will support model application in previously unstudied areas and can facilitate the investigation of new tree species being introduced to well-studied systems (e.g., simulating assisted migration in the context of rapid climate change). Given that many process-based models rely on similar underlying processes our harmonized parameter set will be of relevance beyond the iLand community. Our work could catalyze further research into improving the parameterization of process-based forest models, increasing the robustness of projections of climate change impacts and adaptation strategies.