In the previous two chapters I examined the two essential components of genetic engineering, these being (i) the ability to cut, modify and join DNA molecules in vitro, and (ii) the host/vector systems that allow recombinant DNA molecules to be propagated. With these components at his or her disposal, the genetic engineer has to devise a cloning strategy that will enable efficient use of the technology to achieve the aims of the experiment. In Chapter 1 I showed that there are basically four stages to any cloning experiment (Fig. 1.1), in volving generation of DNA fragments, joining to a vector, propagation in a host cell, and selection of the required sequence. In this chapter I examine some of the strategies that are available for completing the first three of these stages by the traditional methods ogfene cloning, largely restricting the discussion to cloning eukaryotic DNA in E. coli. The use of the polymerase chain reaction (PCR) in amplification and cloning of sequences is discussed in Chapter 7, as this is now a widely used protocol which in some cases bypasses standard cloning techniques. Selection of cloned sequences is discussed in Chapter 8, although the type of selection method that will be used does have to be considered when choosing host/vector combinations for a particular cloning exercise.

Which approach is best?

The complexity of any cloning experiment depends largely on two factors: (i) the overall aims of the work, and (ii) the type of source material from which the nucleic acids will be isolated for cloning.

Introduction: disturbance in temperate conifer–hardwood forests

More than one-fourth of the world's forest land lies within the cool-to-cold temperate zones of the northern and southern hemispheres. Their distinctive mosaics of evergreen conifers and deciduous hardwood species have been shaped by fire, wind and herbivory over thousands of years. In the last few centuries human activities have increasingly changed the dynamics of these mosaics. Over much of the conifer–hardwood forest zone fire frequencies have been reduced by fire suppression and exclusion, harvesting has replaced fire as the main disturbance, global warming may be causing an increase in the frequency of high winds, and the intensity of grazing has increased.

Scientists and forest managers would like to understand how changing disturbance regimes and interactions among disturbances will influence forest successional trajectories. Managers of nature reserves would like to know what types of manipulations would restore the forest to a natural condition. The main purpose of this book is to illuminate the role of disturbances in temperate conifer–hardwood forests for these scientists and managers. Therefore, I have chosen three major themes for the book:

1. To show how three major disturbance types – fire, wind and herbivory – work in combination to influence the successional trajectories and structural characteristics of forests.

2. To show how deciduous and evergreen tree species interact to form various mixtures by differentially influencing their environment and the disturbance regime. For this book, the deciduous and evergreen groups will be referred to as ‘hardwoods’, principally a mixture of maple (Acer), oak (Quercus), ash (Fraxinus), basswood (Tilia) and birch (Betula) species, and ‘conifers’, principally a mixture of pines (Pinus), spruces (Picea), cedar (Thuja), fir (Abies) and hemlock (Tsuga) species. The common and scientific names of species referred to frequently in the book are listed in Appendix I.

3. […]

Introduction

The previous chapter provided general background information on how disturbances work in the forest. This chapter shows how to detect and measure the impact that disturbances discussed in Chapter 2 have upon the forest at the individual tree and stand scale (1–10 ha). Chapter 4 follows with a synthesis of stand dynamics in the Great Lakes forests, obtained using the methods presented in this chapter. Thus, this pair of chapters (3 and 4) presents methods for studying stand dynamics and then the results of application of those methods to the Great Lakes forest. Chapters 5 and 6 form a similar pair of methods/applications but at the landscape scale.

Here I start with discussion of the different types of evidence on stand disturbance history, then proceed to show how to use such evidence to construct a disturbance chronology which chronicles the occurrence of disturbance and its impact on stand structure for the last few centuries. Much of the chapter is devoted to interpreting tree rings for stand history and dealing with the various problems that are inherent in these methods. The importance of choosing a sampling scheme (i.e. the all-important question of which trees to core) that matches the objectives of a given study is another important topic discussed below.

Use of stand data for interpretation of stand history

Several lines of field evidence are available to those investigating stand history. They provide different levels of detail, time resolution, and types of information about stand history (Table 3.1).

The forest landscape comprises a collection of many contiguous stands. We may delineate and label these stands according to species composition, developmental stage, stand age, or vegetation growth stage (VGS, a concept which integrates composition, development and age defined below). If the landscape is a complex one, with more than one ecosystem type, there may be several different stand delineation/labeling systems in place, each of which is adjusted to take into account the unique disturbance–physiographic–tree species interactions in each ecosystem. The main effect of a disturbance regime on the landscape is to determine what proportion of stands are in each stage or stand age. If the disturbance regime is stable over sufficient time – two to three rotation periods for the predominant disturbance type – then a characteristic distribution of stands among growth stages or stand age will result. This chapter will start with the relatively simple concept of stand age distributions for simple landscapes and gradually work through to the more complex situations of multi-ecosystem landscapes with multiple successional webs and the presence of old-growth forest on the landscape.

Stand age distribution across the landscape

We can immediately break stand age distributions into two types: stable ones that are capable of perpetuation over time without change in shape, and unstable, or irregular ones. Only flat or monotonically decreasing stand age distributions can be stable (Figure 5.1). Stand age distributions that are unimodal or have two or more large peaks with gaps between are unstable (Figure 5.2).

In a nutshell, this book covers the natural and settlement history of the forests in the deciduous-to-boreal forest transition zone of the Lake States (Minnesota, Wisconsin and Michigan) of eastern North America, the different types of disturbances that occur there, and how to study disturbances at the stand and landscape scales. Then several case studies from the Great Lakes Region are used to develop important concepts about the dynamic interactions between disturbance and forest size structure and composition. The dynamics of different forest types within this region are compared with each other. Finally, principles on forest response to disturbance are developed that may be generalized to temperate forests around the world. These include the dynamics of conifer–hardwood mosaics, sensitivity of stands and landscape to changing disturbance regimes, and stability at different scales.

Chapter 1 describes the forest setting of the Lake States, and Chapter 2 follows that with basic information on disturbance regimes. Chapter 3 summarizes my experiences on how to sample and analyze stand disturbance history. The techniques presented there should be applicable in most of the world's closed-canopy temperate forests. Chapter 4 summarizes what we know about stand development and successional trajectories in response to disturbance. Chapter 5 jumps to the landscape scale, and shows how to study landscape age structure and composition.

Importance of disturbance in forests

Disturbances exert strong control over the species composition and structure of forests. As a general rule, landscapes with frequent severe disturbance are dominated by young even-aged stands of shade-intolerant species such as aspen. Conversely, old stands of shade-tolerant species such as hemlock dominate where severe disturbances are rare. Every conceivable mixture between these two extremes can be created by the various combinations of disturbance. To understand how disturbances exert these influences over the forest it is necessary to know the basic concepts and mechanics of disturbance – the function of this chapter. Fire, wind and herbivory have been chosen for detailed discussion because they are very important influences on temperate forests and we know a lot about them and their interactions.

A definition and key concepts

The disturbance regime is simply a description of the characteristic types of disturbance on a given forest landscape; the frequency, severity, and size distribution of these characteristic disturbance types; and the interactions among disturbance types. If the forest experiences a series of unique disturbances over time, so that type, frequency, severity and size cannot be characterized, then there is no stable regime. Apparent stability of the regime, however, is a function of the length of time and size of area observed (Lertzman and Fall 1998).

This concluding chapter is a synthesis of everything said earlier in the book. Here I examine stability of age structure and species composition over time and the different types of dynamics that forests may exhibit as a result of their level of stability. Some of the most important linkages among neighborhood, stand and landscape spatial scales will be made here. The real reason we are interested in the material from all of the previous chapters is to generalize about stability of forests. Under what conditions will they change or stay the same? We need to answer those questions now because we are purposely changing the disturbance regime in forests from one dominated by natural disturbance to one dominated by harvesting. Global climate change will also change the disturbance regime, even in forests reserved from logging, in ways that are difficult to understand.

Sometimes investigators have found that their study site was just big enough for a certain disturbance process to operate in stable fashion, according to the study results (e.g. Lorimer 1980, Lorimer and Frelich 1984, Frelich and Lorimer 1991a; Frelich and Graumlich 1994, Frelich and Reich 1995b). This is because there is a continuum of disturbance processes at overlapping temporal and spatial scales and researchers mostly detect the ones operating at the scale of their study area. Some studies examine a large-scale process in a small study area and conclude that forests are unstable.

Knowledge of stand dynamics (Chapter 4) and landscape structure (Chapter 5) are combined in this chapter to examine in detail the relationship between disturbance and landscape characteristics. The topics progress from wind regimes to fire regimes to complex regimes with wind, fire and herbivory (this latter topic was introduced in Chapter 2). Detailed case studies of landscape characteristics and their sensitivity to changes in disturbance regime are considered in each case. Then two more important issues are introduced that can interact with fire, wind and herbivory to provide even more complexity to landscape structure: (1) disturbance size, and (2) interactions among trees themselves, or neighborhood effects. As we will see here and Chapter 8, trees superimpose a patch-forming mechanism of their own onto that created by disturbance dynamics.

Wind regimes and landscape structure

Windstorms have a great effect on structure and development of individual stands across the landscape in the Great Lakes Region. They pockmark the landscape with young stands in initiation and stem-exclusion phases of development. If wind is the dominant disturbance type in an ecosystem, the combination distribution of stand ages will result, because stands are not susceptible to massive blowdown until they reach the late stem-exclusion or demographic-transition phases, after which they will be hit at random by stand-leveling windstorms. Winds of less than standleveling force also create gaps in older stands, thereby determining the timing and size of new cohorts in multi-aged forests.

Introduction

There is considerable interest in the application of biological systems to remediate polycyclic aromatic hydrocarbon (PAH) contamination in the environment (Chen et al., 1999). Recent research on the bioremediation of environmentally relevant chemicals has centred on four important aspects: first, the characterization of the biodegradation processes useful for the treatment of xenobiotic compounds in soil; second, the development of technical protocols for increasing the degradation rates and substrate ranges of enzymes from microorganisms; third, the design and engineering of bioreactor systems and biotreatment strategies to optimize biodegrada-tion processes; and fourth, development of information on the ecological and human health risks associated with exposure to the chemicals (Mueller, Cerniglia & Pritchard, 1996).

Low-molecular-weight PAHs, such as naphthalene, acenaphthene, acenaphthylene, fluorene, anthracene, and phenanthrene (Fig. 7.1), are transformed rapidly by many bacteria and fungi (Pothuluri et al., 1992a,b, 1993; Sutherland et al., 1995; Eriksson, Dalhammar & Borg-Karlson, 2000). High-molecular-weight PAHs, however, are more recalcitrant in the environment and resist both chemical and microbial degradation (Atlas & Cerniglia, 1995; Ahn, Sanseverino & Sayler, 1999; Kanaly & Harayama, 2000).

Benzo[a]pyrene, one of the most recalcitrant PAHs in soil, adsorbs to the soil matrix and thus is physically unavailable to degradative bacteria and fungi (Banks, Lee & Schwab, 1999). The formation of non-extractable bound residues is a significant sink of PAHs in soils (Richnow et al., 2000).