Modeling twentieth century changes in forest productivity in Sweden using LPJ-GUESS and ORCHIDEE-CN-CAN
Abstract
Productivity in Swedish forests has steadily increased over the last 100 years, but the relative contributions of atmospheric CO2 fertilization, N deposition, warming-induced growing season extension, and management-related factors (e.g., soil scarification, improved plant material, selective species manipulation, fertilization, thinning regimes, etc.) to this trend are difficult to discern from available data. In this study, we compare relevant data on forest production and other related proxies with outputs from two complementary vegetation models (LPJ-GUESS, ORCHIDEE-CN-CAN) in order to provide insight on the roles of different environmental and management-related factors. The primary data for informing the models come from extensive historical experiments in Swedish boreal forests including CO2 enrichment, soil water and nutrient additions, and soil/air temperature manipulations. Factorial simulations will allow for varying individual drivers singly or in combination in order to isolate the drivers, and responding processes, responsible for simulated changes. The results will be compared between the models and with forest production data from the Swedish Forest Inventory, as well as other sources such as remote sensing products and flux measurements. A resultant evaluation of model robustness at the regional scale will allow for reduced structural uncertainty, further refining the models as key tools for forestry and land use decisions under future change scenarios.
- Publication:
-
EGU General Assembly Conference Abstracts
- Pub Date:
- April 2018
- Bibcode:
- 2018EGUGA..2016483R