Assessing the influence of climate on the growth rate of boreal tree species in northeastern Canada through long-term permanent sample plot data sets

T Searls,D.W Mckenney,X Zhu,J Steenberg,R Mazumder,F.-R Meng,G Yan

doi:10.1139/cjfr-2020-0257

Abstract

Climate has a considerable influence on tree growth. Forest managers benefit from the empirical study of the historic relationship between climatic variables and tree growth to support forest management frameworks that are to be applied under scenarios of climate change. Through this research, we have utilized long-term permanent sample plot records, historic climate data sets, and linear mixed modelling techniques to evaluate the historic influence of climatic variables on the growth rates of major boreal tree species in Newfoundland and Labrador, Canada. For the commercially significant spruce and fir forests of the province, we found growing degree-days (GDD) to negatively correlate with tree productivity in warmer regions, such as much of Newfoundland (±1350 GDD), but positively correlate with growth in cooler regions, such as those in Labrador (±750 GDD). With respect to precipitation, environmental moisture was not on average a limiting factor to species productivity in the province. These dynamics have implications for the productivity of the spruce–fir forests of the study area when considered alongside contemporary climate projections for the region, which generally entail both a warmer and wetter growing environment.

Highlights

Accurate predictions of forest growth are a fundamental component of any forest management framework (Peng 2000)
Given the negative growth response to the precipitation variable observed through this study, and given the insignificant growth response to the growing degree-days (GDD) variable, we found no evidence of climate–growth relationships currently that would support red maple or other fast-growing temperate species having a ecophysiological advantage under scenarios of climate change versus the established balsam fir and black spruce forests of the province
We observed the growth response of species to cumulative annual GDD to contrast between sites in LD and NF for the major commercial species in the province

Summary

Introduction

Accurate predictions of forest growth are a fundamental component of any forest management framework (Peng 2000). Empirical models of forest growth and yield (G&Y) have been used as the basis of forest management frameworks for over two centuries (Paulsen 1795; Subedi and Sharma 2011; Sullivan and Clutter 1972). Simple parameterizations and high predictive accuracy have led to the gradual establishment of the empirical approach to G&Y as the operational standard in modern forestry management applications (Vanclay 1994). Despite their current prominence, the use of many empirical models rests on an underlying assumption of a constant growing environment (Vanclay 1994; Yaussy 2000; Kimmins 2004). Empirical models often have limited predictive capability when long-term changes occur in growing conditions

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