Ecology and Prediction of Compensatory Growth: From Theory to Application in Forestry.

Chao Li,Robert Lalonde,Hugh Barclay,Bernard Roitberg

doi:10.3389/fpls.2021.655417

Abstract

Compensatory growth has been observed in forests, and it also appears as a common phenomenon in biology. Though it sometimes takes different names, the essential meanings are the same, describing the accelerated growth of organisms when recovering from a period of unfavorable conditions such as tissue damage at the individual level and partial mortality at the population level. Diverse patterns of compensatory growth have been reported in the literature, ranging from under-, to compensation-induced-equality, and to over-compensation. In this review and synthesis, we provide examples of analogous compensatory growth from different fields, clarify different meanings of it, summarize its current understanding and modeling efforts, and argue that it is possible to develop a state-dependent model under the conceptual framework of compensatory growth, aimed at explaining and predicting diverse observations according to different disturbances and environmental conditions. When properly applied, compensatory growth can benefit different industries and human society in various forms.

Highlights

The dynamics of any forest are likely to emerge as a function of a number of variables and processes, including but not limited to: natural perturbations, species-specific responses to such perturbations, community structure, age structure, and access to limiting resources such as nitrogen (Harper, 1977; Davis et al, 2001)
One is to provide a comprehensive review of diverse concepts and examples of compensatory growth (CG) studies from different research fields to show the ubiquity of CG phenomenon, and the other is to describe existing understanding, modeling and applications of CG and how the lens of CG could benefit forestry research and practice
In the section Understanding and Predicting Compensatory Growth, we summarize understanding of CG and associated modeling efforts; and in section Discussion, we discuss the analogs in CG research and their related scaling-up issue, as well as the usefulness of lens of CG

Summary

Introduction

The dynamics of any forest are likely to emerge as a function of a number of variables and processes, including but not limited to: natural perturbations (e.g., fires), species-specific responses to such perturbations, community structure, age structure, and access to limiting resources such as nitrogen (Harper, 1977; Davis et al, 2001). Given the complex nature of forests, it is not surprising that we may observe a very wide range of growth dynamics (e.g., Huang et al, 2009). One of the great challenges is to develop forest management policies for optimizing fiber production across aging dynamics associated with widely divergent age and community structures. That it is possible to develop best practice guidelines if one can construct the appropriate framework to elucidate the aforementioned variation in forest productivity within and among different plantings or natural communities. We further argue that such a framework is already well-developed for a number of non-forest biological systems and that we can avoid reinventing the wheel by incorporating the relevant concepts from life history theory and population ecology, as well as animal and plant sciences. While our focus is on silvicultural practices, our approach could be applied to natural forests

Objectives

Findings

Discussion

Conclusion