Guy R. Larocque

The effect of climate change on forest dynamics is likely to increase in importance in the forthcoming decades. For this reason, it is essential to predict the extent to which changes in temperature, precipitation, and atmospheric CO₂ might affect the development of forest ecosystems and successional pathways. The gap model ZELIG-CFS was used to simulate the potential long-term effects of climate change on species-specific annual change in mean basal area and stand density under two scenarios of representative concentration pathways (RCP), 4.5 and 8.5, for the boreal forest region of Ontario, Canada, where mean temperature, precipitation, and atmospheric CO₂ are expected to increase. Forest ecosystems in this boreal region included pure and mixed stands of black spruce (Picea mariana [Mill.] B.S.P.), paper birch (Betula papyrifera Marsh.), balsam fir (Abies balsamea [L.] Mill.), jack pine (Pinus banksiana Lamb.), trembling aspen (Populus tremuloides Michx.), white spruce (Picea glauca [Moench] Voss), northern white cedar (Thuja occidentalis L.), American larch (Larix laricina [Du Roi] K. Koch), and balsam poplar (Populus balsamifera L.). Simulation results under climate change generally predicted a decline in the basal area and stand density for black spruce, balsam fir, jack pine, and white spruce, but an increase for paper birch, trembling aspen, American larch, and balsam poplar. However, the extent of change differed regionally among species. Forest composition is expected to change over the long term. Simulation results indicated that shade-intolerant deciduous and conifer species will increase their dominance over the 100-year time horizon. This transition toward the increasing presence of deciduous forests is likely explained by more favorable temperature conditions for their growth and development.

Many process-based models on C cycles can also simulate the C exchange in forest ecosystems, which allow them to predict C budgets (see Chapter 8). However, C accounting models are a special type of C cycle models. Some of their model components are based on the use of mechanistic relationships, but empirical relationships obtained from large forest inventory datasets are also used. This chapter focuses on the use of forest inventory-based models that can be applied to provide estimates of C stocks and evaluate the impacts of disturbance regimes on C budget at landscape and national levels. The objective of this chapter is to describe the structure and characteristics of this type C budget models and discuss their limitations and future development. Following the introduction, the overview of forest C accounting models will be given. Three models will be introduced, and their applications will be discussed. Then, the limitations and possible improvements under changing climatic conditions will be addressed as well.

The objective of this chapter is to review different types of process-based models and describe how they can be used in a context of the application of the basic principles of ecological forest management. Relatively few process-based models have been used to address forest management questions. However, as the international community increasingly demands that forests be managed sustainably, which requires that forest managers evaluate the impacts of environmental disturbances on ecosystem dynamics, it is likely that process-based models will be used more frequently in the decision-making process for forest management.

There are two broad categories of succession models: ecosystem- and landscape-based models (FLMs). In this chapter, the basic concepts and characteristics of both broad types of succession models are reviewed, along with some of their strengths and limitations. Their development history is discussed, and the applicability of models commonly used is described and compared. Several key characteristics, including modeled processes, forest types, main drivers, spatial scaling, and contributions, are summarized. Lastly, the use of succession models in relation to ecological indicators and their application in ecological forest management, the modeling of regeneration dynamics, and the application of remote sensing are presented.

Forest biodiversity refers to the variability among all forest life forms (trees, plants, animals, fungi, and microorganisms) from genetics to species and ecosystems and their associated ecological processes. Conserving forest biodiversity is a fundamental goal of sustainable forestry. Therefore, governments, non-government organizations (NGOs), academic institutions, corporations, partnerships, and others tasked with managing and conserving the world’s forests require mechanisms to monitor their progress toward this goal. One of the mechanisms to accomplish this is using a suite of biodiversity indicators. These indicators are data-based measures that convey information beyond what is directly measured or assessed. Given the multitude of possible indicators, frameworks are used to organize them to understand better and show their relationships and interconnectedness. Indicators and indicator frameworks can be used to educate, support policy, and inform management decisions. In this chapter, we do not provide an extensive list of forest biodiversity indicators; instead, we intend to discuss concepts associated with biodiversity conservation about indicator frameworks. Through this approach, we aim to provide the reader with sufficient understanding to review and select among the many contemporary indicators most relevant to their needs/questions.

This chapter uncovers different issues on SFM. In Section 14.2, controversies surrounding the definition and application of SFM that led to the development of processes on criteria and indicators (C&I) are presented. The basic elements of C&I that are common to all processes are reviewed, and forest certification is briefly discussed. Then, the main processes that are most applied are reviewed. In Section 14.3, the pan-European and Montréal Processes for temperate and boreal forests are described, and some examples of application are provided. The processes for tropical forests are covered in Section 14.4, which include the International Tropical Timber Organization (ITTO), the African Timber Organization (ATO), and Tarapoto processes. In Section 14.5, the importance of collaboration and cooperation among processes is highlighted. In particular, efforts to promote collaborations among organizations involved in the development of processes and to harmonize the different processes are discussed. The application of C&I must be based on different sources of information and data to ensure that they report the state of forests as exactly as possible. These sources are discussed in Section 14.6. Regarding data sources, the importance of statistically based forest inventories and the use of remote sensing techniques are reviewed.

The second edition of Ecological Forest Management Handbook continues to provide forestry professionals and students with basic principles of ecological forest management and their applications at regional and site-specific levels. Thoroughly updated and revised, the handbook addresses numerous topics and explains that ecological forest management is a complex process that requires broad ecological knowledge. It discusses how to develop adaptive management scenarios to harvest resources in a sustainable way and provide ecosystem services and social functions. It includes new studies on ecological indicators, the carbon cycle, and ecosystem simulation models for various forest types: boreal, temperate, and tropical forests. NEW IN THE SECOND EDITION Provides a comprehensive collection of sustainable forest management principles and their applications Covers new ecological indicators that can be applied to address forest environmental issues Includes all types of models: empirical, gap, and process-based models Explains several basic ecological and management concepts in a clear, easy-to- understand manner This handbook is intended for researchers, academics, professionals, and undergraduate and graduate students studying and/or involved in the management of forest ecosystems. Chapter 18 of this book is available for free in PDF format as Open Access from the individual product page at www.taylorfrancis.com. It has been made available under a Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 license.

This chapter will focus on empirical growth and yield models, which are based on statistical relationships between indicators of forest growth and yield and a selection of explanatory variables (e.g., tree size, competition intensity, stand density, or site variables), even though process-based models (i.e., models that are based on the modeling of physiological processes to quantify tree or stand development) have the same objectives but using more theoretical approaches. The use of empirical growth and yield models in forestry will be discussed (Section 6.2) with respect to different spatial and temporal horizons. The different components of growth and yield models will then be described by looking at how traditional models work and how new technologies can be included (Sections 6.3 and 6.4). Section 6.5 will explore how empirical models have been modified to integrate the representation of the effects of global change by looking at each component of net stand yield: net yield = tree growth + tree recruitment − mortality. As some effects are hard to capture using empirical relationships, a summary of how process-based models tackle the problem will also be presented. Section 6.6 will describe some basic approaches to quantifying uncertainty in model predictions. The final section (6.7) will conclude on perspectives on the development of growth and yield models.