336 Chapters
Medium 9781780643373

13: Evolution and Changes in the Understorey of Deciduous Forests: Lagging Behind Drivers of Change

Kirby, K.J.; Watkins, C. CABI PDF

13 

Evolution and Changes in the

Understorey of Deciduous Forests:

Lagging Behind Drivers of Change

Martin Hermy*

Department of Earth and Environmental Science, University of Leuven,

Leuven, Belgium

13.1 Introduction

The great changes in land cover that have occurred over the last few centuries are likely to continue over the coming decades (Goldewijk,

2001; Williams, 2006; Hansen et al., 2013). In some places forests have been cleared, while elsewhere reforestation has taken place. This pattern of deforestation and reforestation is likely to recur, so a fragmented and changing forest cover either already is or is going to be the main characteristic of the world’s future forests.

Some forests – such as ancient forests (Peterken, 1977; Hermy et al., 1999) and old-growth forest (Nakashizuka, 1989; Mladenoff et al.,

1993) – have deep roots in the past. Others originated just a few centuries ago. Still others are mixtures of different types, often resulting in a complex mosaic of different origins (Verheyen et al., 1999; Kirby and Watkins, Chapter 4).

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Medium 9781780640884

4 Challenges to Agroecosystem Management

Boelee, E. CABI PDF

4

Challenges to Agroecosystem Management

Petina L. Pert,1* Eline Boelee,2 Devra I. Jarvis,3 David Coates,4 Prem

Bindraban,5 Jennie Barron,6 Rebecca E. Tharme7 and Mario Herrero8

1Commonwealth

Scientific and Industrial Research Organisation (CSIRO), Cairns,

Queensland, Australia; 2Water Health, Hollandsche Rading, the Netherlands;

3Bioversity International, Rome, Italy; 4Secretariat of the Convention on Biological

Diversity (CBD), Montreal, Canada; 5World Soil Information (ISRIC) and Plant

Research International, Wageningen, the Netherlands; 6Stockholm Environment

Institute, University of York, UK and Stockholm Resilience Centre, Stockholm

University, Stockholm, Sweden; 7The Nature Conservancy (TNC), Buxton, UK;

8Commonwealth Scientific and Industrial Research Organisation (CSIRO), St Lucia,

Queensland, Australia

Abstract

As growth in population, gross domestic product (GDP) and consumption continues, further demands are placed on land, water and other resources. The resulting degradation can threaten the food security of poor people in fragile environments, particularly those whose livelihoods rely largely on agricultural activities. The concept of diversified or multifunctional agroecosystems is a relatively recent response to the decline in the quality of the natural resource base. Today, the question of agricultural production has evolved from a purely technical issue to a more complex one characterized by social, cultural, political and economic dimensions. Multifunctional agroecosystems carry out a variety of ecosystem services, such as the regulation of soil and water quality, carbon sequestration, support for biodiversity and sociocultural services, as well as meeting consumers’ needs for food. In turn, these systems also rely on ecosystem services provided by adjacent natural ecosystems, including pollination, biological pest control, maintenance of soil structure and fertility, nutrient cycling and hydrological services. However, poor management practices in agroecosystems can also be the source of numerous disservices, including loss of wildlife habitat, nutrient runoff, sedimentation of waterways, greenhouse gas emissions, and pesticide poisoning of humans and non-target species. This chapter discusses the challenges to agroecosystem management, and how adopting a diversified approach will enable farmers to farm longer and more sustainably in an environment of greater uncertainty, in the face of climate change.

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Medium 9781780644370

12 The Development and Prospect of Discovery of Bt Toxin Genes

Soberon, M.; Gao, Y.; Bravo, A. CABI PDF

12

The Development and Prospect of Discovery of Bt Toxin Genes

Jie Zhang,* Changlong Shu and Zeyu Wang

State Key Laboratory for Biology of Plant Diseases and Insect

Pests, Institute of Plant Protection, Chinese Academy of

Agricultural Sciences, Beijing, People’s Republic of China

Summary

Bacillus thuringiensis (Bt) Cry protein-based insect control has proven to be effective in reducing the use of chemical insecticides and in increasing crop yields. However, Bt crops increase selection pressure for resistant insects and accelerate their succession. The discovery and application of different Bt toxins that have no crossresistance with known toxins has been proposed as a strategy for the management of resistant insects. Additionally, the discovery of novel Bt toxins with a new insecticidal spectrum will control insect succession. In fact, the discovery of new Bt toxins is one of the most important areas in

Bt research, and the most advanced molecular biology methods available have been applied to this task. In this chapter, we summarize the published methods for Bt toxin discovery.

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Medium 9781780640884

2 Drivers and Challenges for Food Security

Boelee, E. CABI PDF

2

Drivers and Challenges for Food Security

Jennie Barron,1* Rebecca E. Tharme2† and Mario Herrero3

1Stockholm Environment Institute, University of York, UK and Stockholm Resilience

Centre, Stockholm University, Stockholm, Sweden; 2The Nature Conservancy (TNC),

Buxton, UK; 3Commonwealth Scientific and Industrial Research Organisation (CSIRO),

St Lucia, Queensland, Australia

Abstract

At the global scale, humanity is increasingly facing rapid changes, and sometimes shocks, that are affecting the security of our food systems and the agroecosystems that are the ultimate sources of food. To plan and prepare for resilient food production and food security in a sustainable and efficient way, we are challenged to better understand the conditions and likely responses of these diverse agroecosystems under various drivers of change and scenarios of future trends. Among the many direct drivers and indirect pressures that exist or are emerging, the discussion in this chapter focuses on the main themes of drivers of demographic changes, globalization of economic and governance systems (including markets), and climate change. The current state of health of water and land resources, and of ecosystems and their services, are considered alongside these drivers, as these are critical determinants of the pathways with sufficient potential to move food-producing systems towards more sustainable production.

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Medium 9781780643946

13 Identifying and Assessing Critical Uncertainty Thresholds in a Forest Pest Risk Model

Venette, R.C. CABI PDF

13

Identifying and Assessing

Critical Uncertainty Thresholds in a Forest Pest Risk Model

Frank H. Koch1* and Denys Yemshanov2

1USDA

Forest Service, Southern Research Station, Eastern

Forest Environmental Threat Assessment Center, Research

Triangle Park, North Carolina, USA; 2Natural Resources Canada,

Canadian Forest Service, Great Lakes Forestry Centre, Sault

Ste. Marie, Ontario, Canada

Abstract

Pest risk maps can provide helpful decision support for invasive alien species management, but often fail to address adequately the uncertainty associated with their predicted risk values. This chapter explores how increased uncertainty in a risk model’s numeric assumptions (i.e. its principal parameters) might affect the resulting risk map. We used a spatial stochastic model, integrating components for entry, establishment and spread, to estimate the risks of invasion and their variation across a two-dimensional gridded landscape for Sirex noctilio, a non-native woodwasp detected in eastern North

America in 2004. Historically, S. noctilio has been a major pest of pine (Pinus spp.) plantations in the southern hemisphere. We present a sensitivity analysis of the mapped risk estimates to variation in six key model parameters: (i) the annual probabilities of new S. noctilio entries at US and Canadian ports; (ii) the S. noctilio population-carrying capacity at a given location; (iii) the maximum annual spread distance; (iv) the probability of local dispersal (i.e. at a distance of 1 km); (v) the susceptibility of the host resource; and (vi) the growth rate of the host trees. We used Monte Carlo

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