Cover
Title Page
List of Contributors
Preface
1 Environmental Pest Management
1. 1.1 Introduction
2. 1.2 Modern Developments in Pest Control
3. 1.3 The Disillusionment with Integrated Pest Management
4. 1.4 A Call for Environmental Pest Management
5. Acknowledgements
6. References
Part I: General Background
1. 2 Approaches in Plant Protection
  1. 2.1 Introduction
  2. 2.2 History of Plant Protection Approaches
  3. 2.3 Integrated Pest Management: What Does it Take?
  4. 2.4 Transforming Agriculture Systems for IPM
  5. Acknowledgements
  6. References
2. 3 The Economics of Alternative Pest Management Strategies
  1. 3.1 Introduction
  2. 3.2 Economic Decisions at Farm Level Based on Threshold Models Assuming Use of a Given Pest Control Technique and Certainty
  3. 3.3 Uncertainties and Economic Decisions at Farm Level About Pest Control: Assumes a Given Pest Control Technique and Applies the Threshold Approach
  4. 3.4 Choice of Alternative Pest Control Techniques at Farm Level Assuming Certainty
  5. 3.5 The Economics of the Timing of Pest Control and the Optimal Choice of Techniques Given Uncertainty
  6. 3.6 A Note on Biological Pest Control
  7. 3.7 Discussion of the Modelling of the Economics of Pest Management at the Farm Level
  8. 3.8 Concluding Comments
  9. References
Part II: Impact of Pest Management Practices on the Environment
1. 4 Effects of Chemical Control on the Environment
  1. 4.1 Introduction
  2. 4.2 Pesticides in Agriculture
  3. 4.3 Impacts of Pesticides on the Environment
  4. 4.4 Concluding Remarks
  5. References
2. 5 Environmental Impacts of Arthropod Biological Control
  1. 5.1 Introduction
  2. 5.2 The ‘Invasion’ Process of Establishing Non‐native Biocontrol Agents
  3. 5.3 Ecological Processes Underlying the Environmental Impact of Biocontrol
  4. 5.4 Ecological Impact Assessment and Cost–benefit Analysis
  5. 5.5 Case Study I: Biocontrol of Emerald Ash Borer (Agrilus planipennis)
  6. 5.6 Case Study II: Biocontrol of Tamarisk (Tamarix spp.)
  7. 5.7 Concluding Remarks
  8. Acknowledgements
  9. References
3. 6 Effects of Transgenic Crops on the Environment
  1. 6.1 Range and Scope of Transgenic Crops
  2. 6.2 Conceptual Framework
  3. 6.3 Primary Effects
  4. 6.4 Secondary Effects
  5. 6.5 Tertiary Effects: Broader Spatial and Temporal Scales
  6. 6.6 Quantifying Risks and Benefits of Transgenic Traits
  7. 6.7 Variation Among Countries in Risk Assessment and Management
  8. 6.8 Conclusions
  9. References
Part III: Influence of Unmanaged Habitats on Pest Management
1. 7 Ecosystem Services Provided by Unmanaged Habitats in Agricultural Landscapes
  1. 7.1 Introduction
  2. 7.2 Global Importance of Arthropod Natural Enemies in Pest Management
  3. 7.3 Importance of Multitrophic Interactions to Biological Pest Control
  4. 7.4 Importance of Unmanaged Vegetation for Biological Control
  5. 7.5 Landscape Use to Maximize Biological Control
  6. 7.6 Conclusions
  7. References
2. 8 The Role of Ecosystem Disservices in Pest Management
  1. 8.1 Introduction
  2. 8.2 EDS and Unmanaged Habitats
  3. 8.3 Landscape Context and the EDS from Unmanaged Habitats
  4. 8.4 Managing for EDS from Unmanaged Habitats
  5. 8.5 Conclusions and Future Research
  6. References
Part IV: Effects of Global Changes on Pest Management
1. 9 Effect of Climate Change on Insect Pest Management
  1. 9.1 Introduction
  2. 9.2 Observed Climate Changes Influencing Agro‐Ecosystems
  3. 9.3 Insect Responses to Climate Change
  4. 9.4 Overview of Insect Pests in Agro‐Ecosystems and Climate Change
  5. 9.5 How Climate Change and Insect Responses May Affect Various Ecological Processes Important for Plant Protection
  6. 9.6 Climate Change and IPM Approaches
  7. 9.7 Directions for Future Research
  8. Acknowledgements
  9. References
2. 10 Effects of Biological Invasions on Pest Management
  1. 10.1 Invasion Science
  2. 10.2 Invasions – A Natural Process?
  3. 10.3 Perception and Value of Introduced and Invasive Alien Species
  4. 10.4 When to Act, and Why?
  5. 10.5 How Best to Control Invasive Species?
  6. 10.6 Case Studies
  7. 10.7 Conclusions
  8. Acknowledgements
  9. References
Part V: Pest Control and Public Health
1. 11 Pesticides and Human Health
  1. 11.1 Introduction
  2. 11.2 Human Exposure to Pesticides
  3. 11.3 Acute Toxicity
  4. 11.4 Chronic Human Health Effects
  5. 11.5 Conclusions
  6. References
2. 12 Human Health Concerns Related to the Consumption of Foods from Genetically Modified Crops
  1. 12.1 History of GM Foods and Associated Food Safety Concerns
  2. 12.2 Status and Commercial Traits Regarding Genetically Modified Organisms
  3. 12.3 The Bases for Unintended Health Risks
  4. 12.4 Guidelines and Approaches Used for Risk Assessment of GM Foods
  5. 12.5 Recent Research on in vivo Evaluation of GM Foods Consumption
  6. 12.6 Shortcomings and Research Needs in the Risk Assessment of Genetically Modified Foods
  7. 12.7 Conclusion
  8. References
Part VI: Policies Related to Environmental Pest Management
1. 13 Effectiveness of Pesticide Policies
  1. 13.1 Introduction
  2. 13.2 Denmark – a Pioneer in Pesticide Policies
  3. 13.3 Effects
  4. 13.4 Comparing Denmark to the EU and Internationally
  5. 13.5 Conclusion
  6. References
2. 14 Impacts of Exotic Biological Control Agents on Non‐target Species and Biodiversity
  1. 14.1 Environmental Safety of Biological Control
  2. 14.2 Legislation and Regulation of Biological Control
  3. 14.3 Risk Assessment
  4. 14.4 Postrelease Validation of Predicted Outcomes
  5. 14.5 Implications of Biological Control Regulation Policy: What has it Meant for Biological Control Practice?
  6. 14.6 The Future for Biological Control Regulation
  7. Acknowledgements
  8. References
3. 15 Pesticides in Food Safety versus Food Security
  1. 15.1 Introduction
  2. 15.2 Use of Plant Protection Products in Farming Systems
  3. 15.3 Food Security in a Changing World
  4. 15.4 Food Safety and Pesticides in a Global Market
  5. 15.5 Towards Sustainability
  6. 15.6 Conclusion
  7. References
4. 16 External Costs of Food Production
  1. 16.1 Introduction: Pesticide Externalities
  2. 16.2 Background: The Impact of Pesticide Use
  3. 16.3 The Challenge in Estimating Externalities from Pesticide Use
  4. 16.4 Externality Estimation Methods
  5. 16.5 Overview of Existing Studies on Externalities of Pesticides
  6. 16.6 Integrated Pest Management
  7. 16.7 The Role of Information
  8. 16.8 Conclusion
  9. References
5. 17 The Role of Pest Management in Driving Agri‐environment Schemes in Switzerland
  1. 17.1 Introduction
  2. 17.2 Policy Context of the Swiss Agricultural Sector
  3. 17.3 Ecological Focus Areas for Biodiversity Protection
  4. 17.4 Ecosystem Service Provision as a New Paradigm
  5. 17.5 Conclusion
  6. References
Part VII: Concluding Remarks, Take‐Home Messages and a Call for Action
1. 18 Environmental Pest Management
  1. 18.1 The Prevalence of a Pest‐centric, Bottom‐up Approach to Pest Control
  2. 18.2 The Main Messages Presented in this Volume
  3. 18.3 The Role of Governments in Pest Management
  4. 18.4 Characteristics of Top‐down, Environmental Pest Management
  5. Acknowledgements
  6. References
Index
End User License Agreement

List of Tables

Chapter 01
1. Table 1.1 Selected definitions of Integrated Pest Management proposed or used by prominent authorities, arranged in chronological order (based in part on Bajwa and Kogan 2002).
Chapter 02
1. Table 2.1 Changes in pest‐related challenges and crop protection approaches over the last century, as illustrated by strawberry production on the central coast of California, USA.
Chapter 08
1. Table 8.1 The components of unmanaged habitat and the possible ecosystem services and disservices that they generate. The lists here are not exhaustive and the extent of their occurrence will depend on a range of factors including the plant and animal species composition of the unmanaged habitat, the scale under consideration and the background landscape context.
Chapter 10
1. Table 10.1 Mechanisms and pathways of dispersal proposed by Hulme et al. (2008). Mechanisms involving commodities and transportation are associated with human activities.
Chapter 11
1. Table 11.1 Online pesticide information resources.
2. Table 11.2 Pesticides evaluated for carcinogenicity by the International Agency for Research on Cancer (IARC) and the US National Toxicology Program (NTP) as of December 2015.
Chapter 12
1. Table 12.1 Introduced commercial traits through genetic modification of plants. Data taken from ISAAA (2015).
2. Table 12.2 Number of approved genetically modified events in different countries (alphabetical order). Data taken from ISAAA (2015).
3. Table 12.3 Genetically modified plant species with approved events (alphabetical order). Data taken from ISAAA (2015).
4. Table 12.4 Key studies on health risk evaluation of GM foods consumption.
Chapter 13
1. Table 13.1 Danish pesticide tax 1996–2013 (% of retail price, excluding VAT and other taxes).
2. Table 13.2 Important policy instruments directed towards farmers in Danish pesticide action plans (1986–2015).
3. Table 13.3 Pesticide sales 1999–2008 in Europe, tonnes of active ingredient (index: year 2000 =100). Countries are listed in alphabetical order.
4. Table 13.4 Treatment frequency index (TFI) in wheat and yield in wheat (2006–2007) (Jørgensen and Jensen 2011).
Chapter 14
1. Table 14.1 Summary of international organizations that regulate or advise on the release of biocontrol agents. Source: Adapted from van Lenteren et al. (2006a).
Chapter 16
1. Table 16.1 Sample studies of pest control externality costs.
Chapter 17
1. Table 17.1 Management regulations and quality criteria for major types of Ecological Focus Areas (EFA) in Switzerland in 2016 (Bundesrat 2016), ordered according to their popularity with farmers, i.e. extensively used and low‐input hay meadows make up the highest share of EFA (FOAG 2015). Q I: Quality level I, which means that basic rules for EFA management are respected (management‐oriented approach); Q II: Quality level II, which means that certain indicators for ecological quality are actually present on the EFA (result‐oriented approach; has not been defined for all types of EFA).
2. Table 17.2 Seed mixtures (adapted to the prevailing site conditions) recommended for Ecological Focus Areas on arable land in Switzerland. Plant species are listed in alphabetical order.
3. Table 17.3 Seed mixtures tested for functional EFA types on arable land. Plant species are listed in alphabetical order.

List of Illustrations

Chapter 01
1. Figure 1.1 The history of pest management and changes in agro‐ecosystem sustainability. Historic data are based on Abrol and Shankar (2012) and https://courses.cit.cornell.edu/ipm444/lec‐notes/extra/ipm‐history.html.
Chapter 02
1. Figure 2.1 Strawberry production on the Central Coast of California, USA, in 2014 showing strip cropping of alfalfa for control of the mirid bug Lygus hesperus via suction removal from alfalfa trap crop with tractor‐mounted vacuums (a, b), hedgerows with native perennials that provide shelter and food resources for natural enemies of strawberry pests (c), comparison of plants protected with anaerobic soil disinfection (d) and growers’ standard pre‐plant practice (e) in an organic field infested with Macrophomina spp. and Fusarium oxysporum fungal diseases, and plastic mulch for weed control (f).
2. Figure 2.2 Trend in (a) kg of insecticides and miticides active ingredients (AI) per ha per year applied to strawberry on the Central Coast of California 2004–2013, (b) average environment impact quotient (EIQ) rating times (kg AI per ha per year), and (c) average persistence of the same materials as determined by their half‐life (persistence in days).
Chapter 03
1. Figure 3.1 A typical representation of the threshold economic model for deciding whether or not it is economic to control a pest. The curve OAB represents the loss in value of crop production experienced by a farmer as a function of pest density and line EH represents the cost of eliminating the pest. See text for additional explanations.
2. Figure 3.2 Illustration of the relationship for the price received per unit yield of some crops as a function of the level of pest infestation. See text for additional explanations.
3. Figure 3.3 Illustration of a case in which two pest control thresholds exist. In this case, it does not pay to control the pest if its density is less than x₁ or greater than x₂.
4. Figure 3.4 A case in which the benefit function of pest control is uncertain. In the case shown, it is believed that the benefit function may be as low as shown by the relationship OCD, V₁(x), or as high as OAB, V₂(x), and that it may assume any value in between. See text for additional explanations.
5. Figure 3.5 Diagram to illustrate influences on decisions to undertake pest control if there is uncertainty about the level of a pest infestation when pest control is undertaken.
6. Figure 3.6 A case in which two optimal techniques of applying a control agent depend on the size of the area to be treated.
7. Figure 3.7 A diagram to illustrate the economics of choosing between a GM herbicide‐resistant crop and one that is not.
8. Figure 3.8 An illustration of the economics at farm level of choosing between Bt seeds and conventional seeds when a pest is to be managed. Planting of Bt seeds involves inescapable upfront costs once it is decided to plant it whereas the option of controlling the pest remains open if conventional seeds are planted. See text for additional explanations.
Chapter 04
1. Figure 4.1 Impact of pesticides on organisms and ecosystems. Application of agricultural chemicals affects all animals and plants in and around the crop, including soil biota. Aquatic organisms may also be affected by residues in run‐off and ground water.
2. Figure 4.2 Effects of various types of pesticides on organisms. (a) Direct effects. (b) Indirect effects. Different grey tones refer to different groups of organisms.
Chapter 05
1. Figure 5.1 Conceptual model of the classic biocontrol methodology. The process begins with foreign exploration for suitable natural enemies in the home range of the target invasive pest, followed by non‐target organism (NTO) testing to assess the risk to native species from the selected biocontrol agents at the target area. If the biocontrol agents are judged to pose little to no risk, they are released, before ideally establishing, dispersing and suppressing pest populations.
2. Figure 5.2 Larvae and adults of the parasitoid wasp Tetrastichus planipennisi (Hymenoptera: Eulophidae) emerging from a gallery of their host, the emerald ash borer larva, Agrilus planipennis Fairmaire (Coleoptera: Buprestidae).
3. Figure 5.3 Tamarisk beetle, Diorhabda elongate (Coleoptera: Chrysomelidae).
Chapter 06
1. Figure 6.1 Modes of interaction with transgenic crops.
2. Figure 6.2 Example of the effects of an agricultural management practice (cover cropping, CC) on a suite of indicators of ecosystem services, with higher numbers indicating increased ecosystem service benefit.
Chapter 07
1. Figure 7.1 Interactions between farm management, landscape features and agricultural ecosystem services (ES) and disservices (EDS). The underlined services are primarily provided by insects.
2. Figure 7.2 Number of scientific articles that report on investigations of the relationship between landscape features and crop protection found in the ISI Web of Science database in December 2015.
Chapter 08
1. Figure 8.1 A schematic example of the possible pathways of ecosystem services (ES) and ecosystem disservices (EDS) flowing from an area of unmanaged habitat to a simple agricultural food web. Dotted arrows indicate links between components of the food web (black boxes), the white solid arrows represent ES and the black solid arrows represent EDS flowing from components of the non‐crop habitat.
2. Figure 8.2 Examples of the differing scales of unmanaged habitat. The ES and EDS flowing from a number of small patches of unmanaged habitat in a relatively complex landscape (a) are likely to differ widely from those flowing from a large patch of unmanaged habitat in a simple landscape (b). Consideration of landscape context is therefore essential when managing for ES and EDS.
Chapter 09
1. Figure 9.1 Summary of publications from the literature in different groupings ranked in decreasing order per class. (a) Publication type: lab expt = experiments conducted indoors; glasshouse = experiments conducted in closed spaces exposed to solar radiation; pot expt = experiments outside but in a constrained substrate. (b) Region of world where data were collected from. (c) Insect order assessed (including nematodes; ‘na’ indicates order not identified). (d) Trait measured in the manuscript to assess climate change impacts. Papers having multiple groupings (e.g. two orders were assessed or four traits were measured) were counted in each of the appropriate groups.
2. Figure 9.2 Network analysis exhibiting regions (source interaction node = shaded box), order (interaction type = dotted line) and publication type (target interaction node). Region name abbreviations: Aust = Australasia/Pacific; C Amer = Central America; M‐East = Middle East; sc‐Asia = subcontinental Asia; N‐Amer = North America; S‐Amer = South America; nd = region not defined. Publication type abbreviations: f‐survey = field survey; desk = desktop analysis; l‐expt = lab experiment; f‐expt = field experiment; glass = glasshouse experiment; p‐expt = pot experiment. To increase clarity of network, insect orders (dotted line) and number of publications per order are not labelled; see text for more detail. Distances between regions and publication type are to maximize spatial clarity of interactions. More centralized nodes have a more diverse range of interactions.
3. Figure 9.3 Network analysis exhibiting regions (source interaction node = shaded box), publication type (interaction type = dotted line) and climate change measure (target interaction node). Region name abbreviations: Aust = Australasia/Pacific; C Amer = Central America; M‐East = Middle East; sc‐Asia = subcontinental Asia; N‐Am = North America; S‐Am = South America; not‐def = region not defined. Climate change measure abbreviations: gene = genetics; uv‐b = ultraviolet radiation b; prec = precipitation; temp = temperature; CO₂ = carbon dioxide; ENSO = El Niño southern oscillation; ag‐int = agricultural intensity; l‐cover = landcover; na = climate change mechanisms not identified. To increase clarity of network, publication type (dotted line) and associated numbers are not labelled; see text for more detail. Distances between regions and measures are to maximize spatial clarity of interactions. More centralized nodes have a more diverse range of interactions.
4. Figure 9.4 Network analysis exhibiting publication type (source interaction node = shaded box), measure (interaction type = dotted line) and climate change mechanism (target interaction node). Publication type abbreviations: f‐surv = field survey; desk = desktop analysis; l‐exp = lab experiment; f‐exp = field experiment; glass = glasshouse experiment; p‐exp = pot experiment. Climate change mechanism abbreviations: gene = genetics; uv‐b = ultraviolet radiation b; prec = precipitation; temp = temperature; CO₂ = carbon dioxide; ENSO = El Niño southern oscillation; ag‐int = agricultural intensity; seas = season; salt = salinity; cover = landcover; na = climate change mechanisms not identified. To increase clarity of network, measure (dotted line) and associated numbers are not labelled; see text for more detail. Distances between regions and measures are to maximize spatial clarity of interactions. More centralized nodes have a more diverse range of interactions.
Chapter 10
1. Figure 10.1 The invasion process and associated management strategies at each stage (after Agriculture Victoria 2015; Harvey and Mazzotti 2014; Kolar and Lodge 2001; Sakai et al. 2001; Simberloff et al. 2013). Management efficiency transitions to greater cost with time and area affected as management options become limited.
2. Figure 10.2 Effect of propagule pressure on probability of establishment. A constant marginal benefit response (middle curve) suggests that the probability of establishment will continue to increase with additional propagules. A delayed marginal benefit (lower curve) might result from Allee effects or other factors, in which the probability of establishment increases with propagule numbers only greater than a particular population size (see text). The redundant past threshold model shows that after some level of propagule pressure, the probability of establishment no longer increases at the same rate.
Chapter 11
1. Figure 11.1 Pesticide classification hierarchy. This figure illustrates the relationship between functional group and chemical class for some commonly used and historical pesticides. Information is provided with the pesticide registration year along with WHO Acute Toxicity Hazard Classification (WHO ‐ www.who.int/ipcs/publications/pesticides_hazard/en/). The figure does not include all pesticides or all classes of chemicals, but rather a subset of pesticides. DBCP, dibromochloropropane; DDT, dichlorodiphenyltrichloroethane.
2. Figure 11.2 Background on the United States Agricultural Health Study, the largest and longest prospective study of farmers and their spouses focusing on the human health effects of pesticides.
Chapter 13
1. Figure 13.1 Treatment frequency index (TFI) for Denmark 1985–2014. The TFI is a standard indicator for pesticide use, calculated as the number of pesticide applications on cultivated areas per calendar year in conventional farming, assuming the use of a fixed standard dose and based on sales numbers (Danish Environmental Protection Agency 2012). The figure for 1985 is an average of the years 1981–1985 (Danish Environmental Protection Agency 1998). For the years 1997–2013, the numbers reflect the Danish Environmental Protection Agency’s so‐called ‘new method’ for calculating TFI. The change in calculation methods in the late 1990s meant that the TFI figure calculated was a bit higher (in the interval 0.07–0.27) compared to when the old method was used (Pedersen et al. 2015).
2. Figure 13.2 Pesticide load indicator (PLI), based on sales (solid line) or on use (dashed line) for Denmark, 2007–2014. The PLI consists of three main categories of load: (1) human health (measures the degree of exposure to pesticides of the spray operator), (2) environmental fate (a measure of the degradation time of the pesticides in soil and their potential for accumulation in food chains and for transport from soil to ground water), (3) environmental toxicity (a measure of the toxicity of the pesticide to non‐target organisms in the field and surrounding nature) (Danish Environmental Protection Agency 2012). The sales figures in the table are based on sales data from the companies and estimated by Copenhagen University in December 2015 (Ørum 2015). These data are more up to date than the data in official statistics from the Danish Environmental Protection Agency. Data on PLI based on use are not available before 2011.
3. Figure 13.3 Organic farmland in Denmark, 1995–2014. The figure shows amount of farmland which is fully organic.
Chapter 17
1. Figure 17.1 Schematic view of the role of cross‐compliance mechanism, agri‐environment schemes (AES) and label programmes in relation to laws and regulations.
2. Figure 17.2 Agricultural production regions of Switzerland. Arable farming is mostly concentrated in the lowlands (light grey), which also include hilly parts. The mountain regions (dark grey) comprise the areas with permanent settlement and mostly grassland‐based agriculture. The summer grazing areas (medium grey) are only seasonally used.
3. Figure 17.3 Development of the total surface of ecological focus areas in hectares within the Swiss utilized agricultural area (UAA) (without trees). Total UAA in 2014 was 1 051 183 ha. An additional 2 400 000 high‐stem trees are also managed under the scheme. With an assumed average density of 100 trees ha⁻¹, this corresponds to another 24 000 hectares EFA. Lowland (black) and mountain regions (grey) are shown on Figure 17.2.
4. Figure 17.4 Evolution of the area of EFA in arable regions in Switzerland. Total EFA types for arable area – open squares; wildflower strip – closed squares; rotational fallow – open triangles; conservation headland – closed circles; improved field margin – open circles.
Chapter 18
1. Figure 18.1 Primary players in pest control schemes over time. (a)1940s to early 1960s. (b) Mid‐1960s to late 1980s. (c) Early 1990s to mid‐2010s. (d) Proposed environmental pest management scheme: (1) pesticide regulation, (2) funding of invited research, (3) support for extension and farmers’ participatory programmes, (4) policies to influence farmers’ practices, (5) research outputs used to fine‐tune governmental policies. Arrows indicate flow direction of inputs. Shade intensity of player’s box and arrow width indicate relative importance of player’s input.

List of Contributors

David Adamson
The Centre for Global Food and Resources
University of Adelaide
SA
Australia

Nigel R. Andrew
Centre of Excellence for Behavioural and
Physiological Ecology, Natural History Museum
University of New England
Armidale
NSW
Australia

Bruce Auld
School of Agricultural and Wine Sciences
Charles Sturt University
Orange
NSW
Australia

Barbara I.P. Barratt
AgResearch
Invermay Agricultural Centre
Private Bag
Mosgiel
New Zealand

Nir Becker
Department of Economics and Management
Tel‐Hai College
Israel

Ana Maria Calderón de la Barca
Centro de Investigación en Alimentación y Desarrollo
Hermosillo
México

Stefano Colazza
Department of Agricultural and Forest Sciences
University of Palermo
Palermo
Italy

Moshe Coll
Department of Entomology
The Robert H. Smith Faculty of Agriculture,
Food and Environment
The Hebrew University of Jerusalem
Rehovot
Israel

Antonino Cusumano
Laboratory of Entomology
Wageningen University
Wageningen
The Netherlands

Antonio DiTommaso
Soil and Crop Sciences Section
School of Integrative Plant Science
Cornell University
Ithaca
NY
USA

Jian J. Duan
USDA‐ARS
Beneficial Insects Introduction
Research Unit
Newark
DE
USA

Clark A.C. Ehlers
Environmental Protection Authority
Private Bag
Wellington
New Zealand

Margaret I. FitzSimmons
Department of Environmental Studies
University of California, Santa Cruz
Santa Cruz
CA
USA

Peter A. Follett
USDA‐ARS
US Pacific Basin Agricultural Research Center
Nowelo St.
Hilo
USA

Mark A.K. Gillespie
Department of Engineering and Natural Sciences
Western Norway University of Applied Science
Sogndal
Norway

Felix Herzog
Agroscope
Zürich
Switzerland

Sarah J. Hill
Centre of Excellence for Behavioural and
Physiological Ecology
Natural History Museum
University of New England
Armidale
NSW
Australia

Jane A. Hoppin
North Carolina State University
Department of Biological Sciences
Center for Human Health and the Environment
Raleigh
NC
USA

Katja Jacot
Agroscope
Zürich
Switzerland

David E. Jennings
Department of Entomology
University of Maryland
College Park
MD
USA

Catherine E. LePrevost
North Carolina State University
Department of Applied Ecology
Center for Human Health and the Environment
Raleigh
NC
USA

Deborah K. Letourneau
Department of Environmental Studies
University of California, Santa Cruz
Santa Cruz
CA
USA

John Losey
Department of Entomology
Cornell University
Ithaca
NY
USA

Javier Magaña‐Gómez
Universidad Autónoma de Sinaloa
Culiacán
México

Maria Navajas
Institut National de la Recherche
Agronomique, INRA
UMR CBGP
Montferrier‐sur‐Lez
France

Helle Ørsted Nielsen
Aarhus University
Department of Environmental Science
Roskilde
Denmark

Diego J. Nieto
Department of Environmental Studies
University of California, Santa Cruz
Santa Cruz
CA
USA

Anders Branth Pedersen
Aarhus University
Department of Environmental Science
Roskilde
Denmark

Ezio Peri
Department of Agricultural and Forest Sciences
University of Palermo
Palermo
Italy

George K. Roderick
Department of Environmental Science,
Policy and Management
University of California
Berkeley
CA
USA

Matthew Ryan
Soil and Crop Sciences Section
School of Integrative Plant Science
Cornell University
Ithaca
NY
USA

Francisco Sánchez‐Bayo
School of Life & Environmental Sciences
The University of Sydney
Eveleigh
NSW
Australia

Morgan W. Shields
Bio‐Protection Research Centre
Lincoln University
Lincoln
New Zealand

Pieter Spanoghe
Ghent University
Department of Crop Protection
Laboratory of Crop Protection Chemistry
Ghent
Belgium

Janice Thies
Soil and Crop Sciences Section
School of Integrative Plant Science
Cornell University
Ithaca
NY
USA

Clement A. Tisdell
School of Economics
University of Queensland
Brisbane St Lucia
QLD
Australia

Matthias Tschumi
Lund University
Lund
Sweden

Eric Wajnberg
INRA
Sophia Antipolis
France

Thomas Walter
Agroscope
Zürich
Switzerland

Peter B. Woodbury
Soil and Crop Sciences Section
School of Integrative Plant Science
Cornell University
Ithaca
NY
USA

Steve D. Wratten
Bio‐Protection Research Centre
Lincoln University
Canterbury
New Zealand

Challenges for Agronomists, Ecologists, Economists and Policymakers