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Large scale analysis of tree growth in space and time under changing climate conditions

Research project The productivity of ecosystems is strongly linked to environmental conditions. In recent years, we have conducted research concerning a dynamic statistical model for the growth process, in both time and space, of individual trees in forest stands of full and different age.

Taking these results as a basis, with the support of large amounts of empirical data the project aims at further developing the underlying model idea to suit different types of forest conditions, with respect to e.g. tree type distribution, size distribution and spatial distribution.

Head of project

Jun Yu
Professor
E-mail
Email

Project overview

Project period:

2018-07-01 2020-06-30

Participating departments and units at Umeå University

Department of Mathematics and Mathematical Statistics, Faculty of Science and Technology

Research subject

Natural resource science, Statistics

Project description

The productivity of ecosystems is strongly linked to environmental conditions. In recent years, we have conducted research concerning a dynamic statistical model for the growth process, in both time and space, of individual trees in forest stands of full and different age. Taking these results as a basis, with the support of large amounts of empirical data the project aims at further developing the underlying model idea to suit different types of forest conditions, with respect to e.g. tree type distribution, size distribution and spatial distribution.

The approach is to model, and thereby describe, the spatio-temporal growth process of individual trees, when being part of a larger system, under varying climate conditions. Estimated changes in stand development will act as indicators of climate change. As the trees, in turn, form the basis of many other species' ecosystems, the analysis will also reflect how climate change affects other species' future.

The model components to be constructed are based on large-scale statistical analyses and the structures that will be studied and described include e.g. within-/between-species dependencies, which reflect how individual trees grow and compete within and between stands. The basis of the modelling approach is a dynamically evolving marked point process structure. The data used, which is obtained from the Swedish National Forest Inventory, will be linked to weather and climate data from the Swedish Meteorological and Hydrological Institute (SMHI). From an ecological point of view, the development and structure of a model for the tree layer constitutes the core from which a framework of other ecological models can be built so that one can estimate other ecological aspects of the Swedish forest.

This project is scientific cooperation between Department of Mathematics and Mathematical Statistics at Umeå University and Department of Forest Resource Management at the Swedish University of Agricultural Sciences, Umeå. The postdoctoral scholarship is financed by the Kempe Foundations