Table of Contents

Cover

Title Page

List of Contributors

Preface

Chapter 1: Introduction to Global Climate Change and Terrestrial Invertebrates

1.1 Background
1.2 Predictions for Climate and Atmospheric Change
1.3 General Mechanisms for Climate Change Impacts on Invertebrates
1.4 Themes of the Book
Acknowledgements
References

Part I: Methods for Studying Invertebrates and Climate Change

Chapter 2: Using Historical Data for Studying Range Changes
1. Summary
2. 2.1 Introduction
3. 2.2 Review of Historical Data Sets on Species' Distributions
4. 2.3 Methods for Using Historical Data to Estimate Species' Range Changes
5. 2.4 Challenges and Biases in Historical Data
6. 2.5 New Ways of Analysing Data and Future Perspectives
7. Acknowledgements
8. References
Chapter 3: Experimental Approaches for Assessing Invertebrate Responses to Global Change Factors
1. Summary
2. 3.1 Introduction
3. 3.2 Experimental Scale: Reductionist, Holistic and Integrated Approaches
4. 3.3 Experimental Design: Statistical Concerns
5. 3.4 Experimental Endpoints: Match Metrics to Systems
6. 3.5 Experimental Systems: Manipulations From Bottle to Field
7. 3.6 Team Science: the Human Dimension
8. 3.7 Conclusions
9. Acknowledgements
10. References
Chapter 4: Transplant Experiments – a Powerful Method to Study Climate Change Impacts
1. Summary
2. 4.1 Global Climate Change
3. 4.2 Climate Change Impacts on Species
4. 4.3 Climate Change Impacts on Communities
5. 4.4 Common Approaches to Study Climate Change Impacts
6. 4.5 Transplant Experiments – a Powerful Tool to Study Climate Change
7. 4.6 Transplant Experiment Trends Using Network Analysis
8. 4.7 What's Missing in Our Current Approaches? Next Steps for Implementing Transplant Experiments
9. Acknowledgements
10. References

Part II: Friends and Foes: Ecosystem Service Providers and Vectors of Disease

Chapter 5: Insect Pollinators and Climate Change
1. Summary
2. 5.1 Introduction
3. 5.2 The Pattern: Pollinator Populations and Climate Change
4. 5.3 The Process: Direct Effects of Climate Change
5. 5.4 The Process: Indirect Effects of Climate Change
6. 5.5 Synthesis, and the View Ahead
7. Acknowledgements
8. References
Chapter 6: Climate Change Effects on Biological Control in Grasslands
1. Summary
2. 6.1 Introduction
3. 6.2 Changes in Plant Biodiversity
4. 6.3 Multitrophic Interactions and Food Webs
5. 6.4 Greater Exposure to Extreme Events
6. 6.5 Range Changes
7. 6.6 Greater Exposure to Pest Outbreaks
8. 6.7 Non-Target Impacts
9. 6.8 Conclusion
10. Acknowledgements
11. References
Chapter 7: Climate Change and Arthropod Ectoparasites and Vectors of Veterinary Importance
1. Summary
2. 7.1 Introduction
3. 7.2 Parasite–Host Interactions
4. 7.3 Evidence of the Impacts of Climate on Ectoparasites and Vectors
5. 7.4 Impact of Human Behaviour and Husbandry on Ectoparasitism
6. 7.5 Farmer Intervention as a Density-Dependent Process
7. 7.6 Predicting Future Impacts of Climate Change on Ectoparasites and Vectors
8. Acknowledgements
9. References
Chapter 8: Climate Change and the Biology of Insect Vectors of Human Pathogens
1. Summary
2. 8.1 Introduction
3. 8.2 Interaction with Pathogens
4. 8.3 Physiology, Development and Phenology
5. 8.4 Population Dynamics, Life History and Interactions with Other Vector Species
6. 8.5 Case Study of Forecasts for Vector Distribution Under Climate Change: The Altitudinal Range of Aedes albopictus and Aedes japonicus in Nagasaki, Japan
7. 8.6 Vector Ecology and Evolution in Changing Environments
8. Acknowledgements
9. References
Chapter 9: Climate and Atmospheric Change Impacts on Aphids as Vectors of Plant Diseases
1. Summary
2. 9.1 The Disease Pyramid
3. 9.2 Interactions with the Pyramid
4. 9.3 Conclusions and Future Perspectives
5. Acknowledgements
6. References

Part III: Multi-Trophic Interactions and Invertebrate Communities

Chapter 10: Global Change, Herbivores and Their Natural Enemies
1. Summary
2. 10.1 Introduction
3. 10.2 Global Climate Change and Insect Herbivores
4. 10.3 Global Climate Change and Natural Enemies of Insect Herbivores
5. 10.4 Multiple Abiotic Factors
6. 10.5 Conclusions
7. Acknowledgements
8. References
Chapter 11: Climate Change in the Underworld: Impacts for Soil-Dwelling Invertebrates
1. Summary
2. 11.1 Introduction
3. 11.2 Effect of Climate Change on Nematodes: Omnipresent Soil Invertebrates
4. 11.3 Effect of Climate Change on Insect Root Herbivores, the Grazers of the Dark
5. 11.4 Effect of Climate Change on Earthworms: the Crawling Engineers of Soil
6. 11.5 Conclusions and Future Perspectives
7. Acknowledgements
8. References
Chapter 12: Impacts of Atmospheric and Precipitation Change on Aboveground-Belowground Invertebrate Interactions
1. Summary
2. 12.1 Introduction
3. 12.2 Atmospheric Change – Elevated Carbon Dioxide Concentrations
4. 12.3 Altered Patterns of Precipitation
5. 12.4 Conclusions and Future Directions
6. Acknowledgements
7. References
Chapter 13: Forest Invertebrate Communities and Atmospheric Change
1. Summary
2. 13.1 Why Are Forest Invertebrate Communities Important?
3. 13.2 Atmospheric Change and Invertebrates
4. 13.3 Responses of Forest Invertebrates to Elevated Carbon Dioxide Concentrations
5. 13.4 Responses of Forest Invertebrates to Elevated Ozone Concentrations
6. 13.5 Interactions Between Carbon Dioxide and Ozone
7. 13.6 Conclusions and Future Directions
8. Acknowledgements
9. References
Chapter 14: Climate Change and Freshwater Invertebrates: Their Role in Reciprocal Freshwater–Terrestrial Resource Fluxes
1. Summary
2. 14.1 Introduction
3. 14.2 Climate-Change Effects on Riparian and Shoreline Vegetation
4. 14.3 Climate-Change Effects on Runoff of Dissolved Organic Matter
5. 14.4 Climate Change Effects on Basal Freshwater Resources Via Modified Terrestrial Inputs
6. 14.5 Effects of Altered Terrestrial Resource Fluxes on Freshwater Invertebrates
7. 14.6 Direct Effects of Warming on Freshwater Invertebrates
8. 14.7 Impacts of Altered Freshwater Invertebrate Emergence on Terrestrial Ecosystems
9. 14.8 Conclusions and Research Directions
10. Acknowledgements
11. References
Chapter 15: Climatic Impacts on Invertebrates as Food for Vertebrates
1. Summary
2. 15.1 Introduction
3. 15.2 Changes in the Abundance of Vertebrates
4. 15.3 Changes in the Distribution of Vertebrates
5. 15.4 Changes in Phenology of Vertebrates, and Their Invertebrate Prey
6. 15.5 Conclusions
7. 15.6 Postscript: Beyond the Year 2100
8. Acknowledgements
9. References

Part IV: Evolution, Intervention and Emerging Perspectives

Chapter 16: Evolutionary Responses of Invertebrates to Global Climate Change: the Role of Life-History Trade-Offs and Multidecadal Climate Shifts
1. Summary
2. 16.1 Introduction
3. 16.2 Fundamental Trade-Offs Mediating Invertebrate Evolutionary Responses to Global Warming
4. 16.3 The Roles of Multi-Annual Extreme Droughts and Multidecadal Shifts in Drought Regimens in Driving Large-Scale Responses of Insect Populations
5. 16.4 Conclusions and New Research Directions
6. Acknowledgements
7. References
Chapter 17: Conservation of Insects in the Face of Global Climate Change
1. Summary
2. 17.1 Introduction
3. 17.2 Vulnerability Drivers of Insect Species Under Climate Change
4. 17.3 Assessment of Insect Species Vulnerability to Climate Change
5. 17.4 Management Strategies for Insect Conservation Under Climate Change
6. 17.5 Protected Areas and Climate Change
7. 17.6 Perspectives on Insect Conservation Facing Climate Change
8. Acknowledgements
9. References
Chapter 18: Emerging Issues and Future Perspectives for Global Climate Change and Invertebrates
1. 18.1 Preamble
2. 18.2 Multiple Organisms, Asynchrony and Adaptation in Climate Change Studies
3. 18.3 Multiple Climatic Factors in Research
4. 18.4 Research Into Extreme Climatic Events
5. 18.5 Climate change and Invertebrate Biosecurity
6. 18.6 Concluding Remarks
7. References

Species Index

Subject Index

End User License Agreement

List of Illustrations

Chapter 2: Using Historical Data for Studying Range Changes

Figure 2.1 (A) Map of participant countries (black polygons) of the GBIF facility*, and (B) geo-referenced occurrence records for species in the UK, since 1950 (all 37,673,744 records = grey and black bars; Class: Insecta records = black bars, with the percentage of Insecta records displayed at the top of each bar). Bars illustrate the increase in records over time. We highlight insect data which comprise ∼18% of the c.38 million geo-referenced records held in GBIF for the UK. Summary data were obtained from GBIF.org (accessed 07/08/15). *note that there are data held in the GBIF database for species that occur outside of these countries.
Figure 2.2 Range expansion by the comma butterfly, Polygonia c-album, in mainland Britain. Change in distribution is mapped between two time periods: 1970–1985 (grey squares) and 1995–2010 (grey and black squares). To take account of changes in recorder effort over time, in (A) and (C) we only plot well-recorded hectads (10 × 10 km grid squares; see Section 2.4 for definition of ‘well-recorded’ squares). In (A), the dot-and-dashed arrow denotes a northwards range margin shift of 345 km between the northern range margin in the first (dashed horizontal line) and second (solid horizontal line) time periods. The length and location of the solid arrow in the middle of (A) denotes the location of the range core in 1970–1985 (white cross) and the bearing and magnitude of shift of the range core over the two time periods (98 km at 353°N). In (B) the solid line denotes observed range margin change between the two time periods, along each of 24 compass directions (0 to 345°). These data demonstrate a general shift northwards, with the maximum shift of 356 km occurring along the 345° axis (black square in B). The dotted line in (B) represents a shift of 300 km between the range margins in the earlier and later time periods, along all axes, and is plotted to aid interpretation. In (C), the dot-and-dashed arrow denotes range margin shift of 356 km along the 345° axis, between the range margins in the first (dashed line) and second (solid line) time period. Distribution records were extracted on 16/04/14 from the Butterflies for the New Millennium database.
Figure 2.3 Number of (A) butterfly and (B) moth records per year since 1950 (records prior to 1950 are not shown) in the UK. Butterfly records were extracted on 16/04/14 from the Butterflies for the New Millennium database, and moth records were extracted on 08/10/13 from the National Moth Recording Scheme database.
Figure 2.4 Variation in recording effort for UK butterflies, showing recorded (A), well-recorded (B) and heavily recorded (C) locations. On each map, circles represent hectads (10 × 10 km grid squares) where at least one species (A), 10% (B) or 25% (C) of the total number of species in the UK (grey circles, following Hickling et al., 2006) or in the local species pool (black and grey circles, following Mason et al., 2015) were observed in both time periods of study (1970–1985 and 1995–2010). Distribution data were extracted on 16/04/14 from the Butterflies for the New Millennium database.

Chapter 3: Experimental Approaches for Assessing Invertebrate Responses to Global Change Factors

Figure 3.1 The complex of climate and atmospheric change factors that directly and indirectly influence invertebrate biology is best investigated by a spectrum of experimental approaches. The direct effects of global change factors on rapidly responding metrics (e.g., insect physiology, growth) are amenable to study via small-scale, chamber systems. More complex direct and indirect effects on slowly responding metrics (e.g., community composition) are best studied with large-scale, open-air systems. Figure adapted from Lindroth (2010).
Figure 3.2 Examples of experimental systems used for evaluating the effects of climate and atmospheric change on invertebrates. (A) Controlled environment chamber with wheat, soybean, and fall armyworm (Spodoptera frugiperda). Insect cages shown in the rear. (Photo credit: R.L. Lindroth). (B) Greenhouse with hybrid poplar and gypsy moth (Lymantria dispar). (Photo credit: R.L. Lindroth). (C) Open-top chamber with aspen, maple and forest tent caterpillar (Malacosoma disstria). (Photo credit: R.L. Lindroth). (D) Open-top chamber with ant communities in eastern deciduous forest, USA. (Photo credit: S.L. Pelini). (E) Open-air warming study (B4WarmED) with forest tent caterpillar in southern boreal forest, USA. (Photo credit: M.A. Jamieson). (F) Free Air CO₂ and Ozone Enrichment study (Aspen FACE) with diverse insects in northern deciduous forest, USA. (Photo credit: R. Anderson, Skypixs Aerial Photography, Lake Linden, MI).

Chapter 4: Transplant Experiments – a Powerful Method to Study Climate Change Impacts

Figure 4.1 Flowchart showing known species' response to climate change impacts.
Figure 4.2 Schematic illustrating latitudinal (A) and altitudinal (B) transplant experiments. Grey areas indicate current species range; filled triangles show species transplanted within their range (a), hatched triangles show species moved outside of their range (b) into a warmer climate to simulate future conditions.
Figure 4.3 Redrawn percentage herbivory data/12 months from the latitudinal extent of five species from Eastern Australia. (a) Acacia falcata at four locations along its coastal range (Batemans Bay, Sydney, Grafton, Gympie) and transplant sites 200 km towards the tropics from Andrew and Hughes (2007); (b $c04-math-001$ e) four locally common understorey shrub species from major plant families transplanted into the centre of their current range and two sites ∼600 km beyond their current equatorial range limit (denoted C, W1 and W2 respectively) from Nooten and Hughes (2014).
Figure 4.4 Redrawn Proportion of herbivore guilds from the latitudinal extent of nine host plant species on the East Coast of Australia. (a) Acacia falcata combined (native range) and transplanted A. falcata (transplant) and a congener at sites 200 km towards the tropics from Andrew & Hughes (2007); (b $c04-math-002$ i) eight locally common species transplanted into the centre of their current range (c) and at two sites ∼600 km beyond their current equatorial range limit (W1 and W2) and an associated congener (if present) from Nooten and Hughes (2014). Key: phloem feeders (open bar); leaf chewers (diagonal bars); mesophyll feeders (cross hatch bars).
Figure 4.5 Network analysis exhibiting the relationship between continents of study and climatic drivers tested (nodes) and their interactions via transplant study type (edges). Continent (shaded: North America –NA; Europe – EU; Australia – AU; South America – SA) and Climatic driver (Temperature – Temp; Temperature and Precipitation - T & P; Precipitation – Precip; and Geographic – Geogr) were characterised as nodes and Transplant type (Latitude – Lat; Altitude – Alt; Longitude – long; Local – Loc) was identified as the edge between nodes. Number on each edge indicates number of papers (out of 22 papers assessed) showing that connection between Nodes.
Figure 4.6 Network analysis exhibiting the relationship between transplant type and climatic drivers tested (nodes) and their interactions via the taxa transplanted (edges). Transplant type (shaded: Latitude – Lat; Altitude – Alt; Longitude – long; Local – Loc) and Climatic driver (Temperature – Temp; Temperature and Precipitation - T & P; Precipitation – Precip; and Geographic – Geogr) were characterised as nodes and taxa transplanted (Plant – Pl; Insect – Ins; Soil cores – sc; Soil cores and plants – Sc + Pl) was identified as the edge between nodes. Number on each edge indicates number of papers (out of 22 papers assessed) showing that connection between Nodes.

Chapter 5: Insect Pollinators and Climate Change

Figure 5.1 Development rates of (A) the alkali bee, Nomia melanderi, and (B) the alfalfa leafcutter bee, Megachile rotundata, as a function of rearing temperature. Values are 100/t, where t is the mean development time in days. In (A), development times are from the end of overwintering (as a prepupa) until pupation (dashed line, open circles), or from the start of the pupal stage until adult emergence from the pupal skin (solid line, filled circles). In (B), each curve was fitted to data on development from overwintering (as a prepupa) until adult emergence for males (dashed lines) and females (solid lines) in each of three study years. Data in (A) from Stephen (1965); in (B) from O'Neill et al. (2011).

Chapter 6: Climate Change Effects on Biological Control in Grasslands

Figure 6.1 Major pathways through which climate change may impact on grassland biological control systems.
Figure 6.2 Main pathways through which climate change may impact on defence compounds that protect grassland plants from invertebrate herbivory.

Chapter 7: Climate Change and Arthropod Ectoparasites and Vectors of Veterinary Importance

Figure 7.1 Ectoparasite developmental success at a range of temperatures (grey dotted line), varying between the species' minimum thermal tolerance and maximum thermal tolerance. Development success is highest around the species-specific optimum temperature. Horizontal lines correspond to the range of temperatures represented in Figure 7.2 and 7.4 for North (solid lines) and South (dashed lines) Europe under current (black circles) and future climatic conditions (grey squares and triangles). Future (dark grey squares) and future+ (light grey triangles) scenarios correspond to low and high climate change scenarios respectively (e.g., IPCC's RCP 2.6 and RCP 8.5 scenario projections for the 2080s).
Figure 7.2 Potential change in the seasonal pattern of relative risk of hypothetical parasitic or vector-borne disease transmission in northern Europe under current and future climatic conditions. Future (dark grey dashed line) and future+ (light grey dotted line) scenarios show the potential change due to low and high climate change scenarios (e.g., IPCC's RCP2.6 and RCP8.5 scenario projections for the 2080s) respectively. Under current climatic conditions (black solid line) temperatures are sub-optimal (see Figure 7.1) and therefore a low to moderate increase in temperature (dark grey dashed line) results in a year-round increase in relative risk of disease. A greater increase in temperature (light grey dotted line) results in an increase in relative risk for the majority of the year but takes the parasite above its optimal temperature for development success during the summer months, resulting in a “summer dip” in risk. The overall impact of this is that increasing temperatures do not necessarily translate to increases in disease risk.
Figure 7.4 Potential change in the seasonal pattern of relative risk of parasitic or vector-borne disease transmission in Southern Europe under current and future climatic conditions. Future (dark grey dashed line) and future+ (light grey dotted line) scenarios show the potential change due to low and high climate change scenarios (e.g., IPCC's RCP2.6 and RCP8.5 scenarios) respectively. Figure 7.4 adapted from Rose et al. (2016). Under current climatic conditions (black solid line) temperatures span the optimal temperature for parasite development success (see Figure 7.1) with development possible over the cooler winter months but increases in mortality rates in the summer resulting in a “summer dip” in disease risk. An increase in temperature (dark grey and light grey) takes the parasite further beyond the optimal temperature for development success (Figure 7.1) resulting in an increase in winter risk but a corresponding increase in magnitude of the “summer dip”.
Figure 7.3 Predicted probability of blowfly strike in Great Britain in 2003/2004 (first column), based on reported cases of blowfly strike, mean monthly air temperature and mean monthly rainfall. The model was projected onto future mean air temperature and rainfall data to predict the future probability of blowfly strike in the 2080s under the low (IPCC B1) and high (IPCC A1fi) emissions scenarios of climate change. Output shown is redrawn from data underlying predictions reported by Rose & Wall (2011). Black indicates a probability of blowfly strike of 0, and white indicates a probability of blowfly strike of 1.

Chapter 8: Climate Change and the Biology of Insect Vectors of Human Pathogens

Figure 8.1 Climate seasonality at Nagasaki, Japan (A) rainfall (B) mean temperature (C) maximum temperature (D) minimum temperature. Lines indicate the seasonal trajectories of 1989 and 2014, see inset legend of panel (A) for guidance. inset panels in (B), (C) and (D) show temperature trends from January 1879 to December 2014.
Figure 8.2 Climate change and population dynamics of vectors of human diseases (A) association between monthly cutaneous leishmaniasis cases (CL_T) and Lutzomyia trapidoi (SF_T-3) in Panamá. There is a three month lag between Lu. trapidoi (time – 3 months) and the cutaneous leishmaniasis cases (time). (B) 75th quantile of the distribution of simulated weekly population size of Aedes aegypti (N_t) as function of the average environment. In the X axis a larger value means a more frequent oscillation between enviroments that change the life history parameters of Aedes aegypti. Panel (A) is redrawn from Chaves et al. (2014a), Panel (B) is redrawn from Chaves et al. (2014b).
Figure 8.3 Land use change and presence of immature and adult Aedes albopictus, Ae. flavopictus and Ae. japonicus in/around trees with ovitraps at Mt Konpira in 1989 and 2014. (A) immatures 1989, (B) adults 1989, (C) immatures 2014, (D) adults 2014, (E) Mt Konpira land use and vegetation in 1984, (F) Mt Konpira land use and vegetation cover in 2005. In all panels further details are presented in the inset legends, contours in panels (E) and (F) are for altitude.

Chapter 9: Climate and Atmospheric Change Impacts on Aphids as Vectors of Plant Diseases

Figure 9.1 Disease pyramid. Numbers refer to sections within this chapter. Sections 9.1.1, 9.1.2 and 9.1.3 highlight the impacts of global environmental change on aphids, plants and viruses, respectively. Sections 9.2.1, 9.2.2 and 9.2.3 highlight the effects of environmental change on the two-way aphid–host-plant, plant–virus and virus–aphid interactions, respectively. Section 9.2.4 combines all four corners of the disease pyramid to highlight the effects of environmental change on the three-way aphid–host-plant–virus interaction.

Chapter 10: Global Change, Herbivores and Their Natural Enemies

Figure 10.1 Summary of the findings from Hentley et al. (2014b) where a reciprocally crossed experiment (A) tested the effect of eCO₂ on aphid escape responses to either ladybird predation (B) or conspecific alarm pheromone (C). Grey bars correspond to ambient CO₂ and white bars eCO₂. Figure and full details of the methodology and results can be found in Hentley et al. (2014b).

Chapter 11: Climate Change in the Underworld: Impacts for Soil-Dwelling Invertebrates

Figure 11.1 Direct and indirect effect of climate change on nematodes. The solid arrows indicate direct effects, while dashed arrows indicate indirect effects. Blue arrows represent shift in the community whereas green arrows indicate a positive impact and red arrows a negative impact on the community. Indirect effects are mediated by (1) changes in the soil structure, (2) increased soil moisture resulting from lower stomatal conductance, (3) shifts in the plant community, (4) a reduction of plant quality (often reflected by higher C:N ratio), and (5) decreased population of predators and/or parasitoids, and (6) a higher N rhizodeposition. Details and references in the text. (Drawings: I. Hiltpold, WSU, Australia)
Figure 11.2 Direct and indirect effect of climate change on insects. The solid arrows indicate direct effects, while dashed arrows indicate indirect effects. Blue arrows represent shift in the community whereas green arrows indicate a positive impact and red arrows a negative impact on the community. See Figure 11.2 for nature of the indirect effects. Details and references in the text.
Figure 11.3 Direct and indirect effect of climate change on earthworms. The solid arrows indicate direct effects, while dashed arrows indicate indirect effects. Blue arrows represent shift in the community whereas green arrows indicate a positive impact and red arrows a negative impact on the community. See Figure 11.2 for nature of the indirect effects. Details and references in the text.

Chapter 12: Impacts of Atmospheric and Precipitation Change on Aboveground-Belowground Invertebrate Interactions

Figure 12.1 Aboveground–belowground invertebrate interactions can arise through three broad mechanisms, whereby invertebrates can affect each other by (A) Modifying plant traits that alter host plant suitability, (B) causing shifts in plant community composition that alter host plant availability or (C) Directly inputting plant-derived organic matter (e.g., Leaf litter or Insect faecal material or frass) into the soil.
Figure 12.2 Simulated root herbivory (a) Reduced root C:N, root and shoot biomass, and affected foliar amino acids differently – roots cut early in the experiment stimulate amino acid production presumably through compensatory nodulation, whereas roots cut late in the experiment reduced foliar amino acid concentrations. Root herbivory therefore had positive and negative impacts on aphids, respectively. e[CO₂] reduced (b) root C:N, but increased concentrations of (c) essential and (d) non-essential amino acids in the foliage which stimulated (e) aphid population growth. Elevated air temperature increased plant growth, particular in terms of (f) plant height and (g) shoot biomass. Higher temperatures moderated both foliar amino acids and aphid performance, and therefore the aboveground–belowground interaction operating under ambient temperature conditions. Adapted from Ryalls et al. (2015).
Figure 12.3 Fecundity (number of offspring produced in six days) of Myzus persicae and Brevicoryne brassicae (Mean ± S.E.M.) feeding on Brassica oleracea plants under different Delia radicum densities (control = no D. radicum) and drought-stress treatments. Within each aphid species, means with different letters are significantly different [ANOVA, post hoc Tukey honestly significant difference (HSD) test: P<0.05]. Reproduced from Tariq et al. (2013a).
Figure 12.4 Performance of Aphidius colemani and Diaeretiella rapae (Mean ± S.E.M.) on Myzus persicae and Brevicoryne brassicae reared on Brassica oleracea plants under a well-watered regime (200 ml/pot/week; “Control”) and a reduced water regime (100 ml/pot/week; “drought stressed”) with/without Delia radicum. Within each parasitoid species, means with different letters are significantly different (P <0.05): (a) Percentage parasitism (b) sex ratio. Reproduced from Tariq et al. (2013b).

Chapter 13: Forest Invertebrate Communities and Atmospheric Change

Figure 13.1 A typical FACE set-up in a forest system (Eucalyptus ‘EucFACE’, Sydney, Australia). Studies from FACE sites have benefits over those in more controlled, simplified environments in that they integrate the complex of biotic and abiotic factors occurring in the system
Figure 13.2 Conceptual diagram summarising the main directions of the responses of invertebrates to elevated CO₂ and O₃. Arrows show the direction of responses based on the literature; the size of the arrows give some idea of our degree of confidence (i.e., the number of studies showing the same result). Adapted from Facey et al. (2014).

Chapter 14: Climate Change and Freshwater Invertebrates: Their Role in Reciprocal Freshwater–Terrestrial Resource Fluxes

Figure 14.1 Conceptual Figure of climate-change effects on terrestrial and aquatic systems. On the left, (1) represents the direct (solid arrow) effects of climate change on terrestrial (riparian and shoreline) vegetation and (2) subsequent indirect (dashed arrow) and direct effects on runoff of dissolved organic matter (DOM). On the right, (3) represents the direct effects of climate change (temperature and hydrology) and (4) the indirect effects (dashed box) of changed relative availability of basal resources, and interactions between (3) and (4), on several freshwater invertebrate parameters. (5) represents both direct and indirect influences of altered freshwater communities on emergent freshwater insect parameters. The flows of terrestrial matter to freshwater systems and aquatic matter (i.e. emergent freshwater insects) to terrestrial systems, and alterations in quantity, quality, and timing caused by climate change, are depicted in the middle.
Figure 14.2 Illustration of the interactions and logical sequence underlying the proposed research questions (1-6). Suggestions intend to narrow the prevailing knowledge gaps on how climate-change driven alterations in basal resource quality, together with warming, may influence aquatic invertebrate secondary production (1), community size structure (2), and elemental composition (3); how this can influence aquatic insect emergence (4), what consequences such changes have for terrestrial food webs (5), and how climate change influences resource cycling across the aquatic–terrestrial boundary on the large scale (6).

Chapter 15: Climatic Impacts on Invertebrates as Food for Vertebrates

Figure 15.1 Contrasting population changes within a single taxon of insectivorous bird species (Warblers; Superfamily Sylvioidea) breeding in the UK. Dashed lines represent 95% confidence intervals around the mean population index, where a value of 100 represents the species' population size in 1994. The Figure is redrawn from Breeding Bird Survey (BBS) data from the Bird Trends Report (Baillie et al., 2014) with permission from the British Trust for Ornithology (BTO). The BBS is a partnership scheme of BTO/JNCC/RSPB.
Figure 15.2 Phenological mismatches between vertebrate predators and their invertebrate trophic resources can arise when predators and prey alter their phenology at different rates. Figure adapted from Grossman, 2004.

Chapter 16: Evolutionary Responses of Invertebrates to Global Climate Change: the Role of Life-History Trade-Offs and Multidecadal Climate Shifts

Figure 16.1 A synthesis of the major types of life-history trade-offs that could mediate the evolutionary responses of invertebrates to global warming and multidecadal drought regimes.
Figure 16.2 Multidecadal drought regimes may be a key factor determining the evolutionary responses of invertebrates to global change. (A) The temporal dynamics of multidecadal drought regimes may combine contrasting periods of anticipatory and non-anticipatory multidecadal trends or periods of increased variance and ramp-down trends. Anticipatory multidecadal droughts are periods of drought that anticipate the effects of future global warming. Non-anticipatory decadal droughts are mild, wet periods that temporally counteract the effects of global warming, creating contrasting selective regimes that may not coincide with future scenarios of global warming. Temporal sequences of different types of drought regimes can be expected in novel climates, with impacts on the landscapes of functional genetic variation, and creating contingent effects that may limit future evolutionary responses. (B) Drought dynamics also show spatial gradients in their trends. In this example, we illustrate three contrasting types of drought dynamics that have been observed in the Iberian Peninsula along a longitudinal transect (West-East arrow) during recent decades. Multidecadal responses of invertebrates are expected to track the spatial gradients in drought regimes and consistently differ across the spatial gradients.
Figure 16.3 Multidecadal drought regimes and evolutionary responses of invertebrates. Changing multidecadal drought regimes (A) will alter the selective regimes experienced by invertebrates (B). This effect may produce spatiotemporal shifts in the distribution of genetic polymorphisms mediating adaptive responses to changing regimes (C). In c we illustrate three hypothetical alleles that differ in their drought sensitivity (black dot: frequency of an allele positively selected during increased drought periods; grey dot: an allele with intermediate performance during increased drought; white dot: an allele that suffers strong negative selection during increased drought and warming periods). (D) Multidecadal shifts in drought regimes may produce peaks of population extinctions, thereby creating new genetic landscapes that may determine future responses. (E) Multidecadal shifts in climate and drought regimes are expected to affect allelic distributions, causing changes in the leading and trailing edges of the distributions. The hypothetical distributional changes for a drought-resistant allele (black dot) in the leading and trailing edges are illustrated.

Chapter 17: Conservation of Insects in the Face of Global Climate Change

Figure 17.1 Temporal evolution of scientific publications combining topics 'Biodiversity' + 'Climate Change' + 'Conservation' and adding the string 'Insect', respectively. Points: number of publications per year for each search. Bars: proportion of the total publications of each search per year. Each search was performed on the ISI Web of Knowledge, including the Science Citation Index Expanded, Social Science Citation Index, Arts and Humanities Citation Index, and Conference Proceedings Citation Index–Science databases from 1990 to 2014. For the topic 'climate change' and 'conservation' we used a set of synonymous words in all possible combinations, that is, (climate change OR global warming OR climatic change OR climate-change OR changing climate) and (conservation OR adaption OR management OR restoration OR planning OR reserve design OR strategy OR land-use OR land use OR landscape OR protected area OR park). Please, note that the term 'biodiversity' was included in these searches to minimise the number of articles exclusively focussed on ecosystem services without an explicit mention of biodiversity.
Figure 17.2 Drivers of species vulnerability under climate change and its link with each specific type of conservation strategy to mitigate the impact on species. Modified from Arribas et al. (2012a).
Figure 17.3 Protected areas and climate change. (A) Change in climatic conditions of two Spanish National Parks (Monfrague and Ordesa) in the future. Black areas: current extension of the National Parks. Dark grey areas: similar climatic conditions to the reserve in the present. Light grey areas: similar climatic conditions to the reserve in the future. White areas: similar climatic conditions to reserve in both present and future. Modified from Lobo (2011). B) Average climatic suitability of the potential distribution of endemic water beetles overlapping with both National Parks (i) and Natura 2000 (ii) networks in the Iberian Peninsula using different thresholds to consider a cell as protected. Bars: potential distribution as estimated for present (black bars) and future climatic conditions for the scenarios b2 (grey bars) and a2 (white bars). Modified from Sánchez-Fernández et al. (2013).

Chapter 18: Emerging Issues and Future Perspectives for Global Climate Change and Invertebrates

Figure 18.1 European summer temperatures for 1500–2010. (A) Statistical frequency distribution of best-guess reconstructed and instrument-based European ([35°N, 70°N], [25°W, 40°E]) summer land temperature anomalies (degrees Celsius, relative to the 1970–1999 period) for the 1500–2010 period (vertical lines). The five warmest and coldest summers are highlighted. Grey bars represent the distribution for the 1500–2002 period (Luterbacher et al., 2004), with a Gaussian fit in black. Data for the 2003–2010 period are from Hansen et al. (1999). (B) The running decadal frequency of extreme summers, defined as those with temperature above the 95th percentile of the 1500–2002 distribution. A 10-year smoothing is applied. Dotted line shows the 95th percentile of the distribution of maximum decadal values that would be expected by random chance. Reproduced from Barriopedro et al. (2011) with permission.

List of Tables

Chapter 5: Insect Pollinators and Climate Change

Table 5.1 Known or suggested effects of global warming on insect pollinators. See text for discussion

Chapter 8: Climate Change and the Biology of Insect Vectors of Human Pathogens

Table 8.1 Factors associated with Aedes albopictus and Aedes japonicus ovitrap colonization (or adult presence) at focal trees in 1989 and 2014 at Mt Konpira, Nagasaki, Japan. Parameter estimates are for the best logistic generalized linear model selected through a process of backward elimination. Moran's I indicates the Moran's I index of spatial autocorrelation estimated from model residuals through a 1000 replicates Monte Carlo. ΔAIC is the difference between the AIC from the “full” model, including all potential covariates, and the “best” model
Table 8.2 Summary of observed and expected patterns of climate change impacts on the different components of vectorial capacity, and other factors that might influence the ability of bloodsucking insects to transmit pathogens. Vectorial capacity (VC) is a parameter that quantifies the expected number of secondary inoculations on vertebrate hosts per infective vertebrate per time unit and is defined by the following formula (Garrett-Jones, 1964): $c08-math-001$ , where N is the abundance of vector per vertebrate host, a is the biting rate, μ is the mortality rate per unit time, e^{- μ} is the survival rate per unit time and n is the duration of the extrinsic incubation period. Climate change impacts are presented regarding both an increase in temperature (global warming) and increased weather variability

Chapter 10: Global Change, Herbivores and Their Natural Enemies

Table 10.1 Summary of major aspects of global change, the causes and the likely impacts on organisms
Table 10.2 Effects of abiotic stressors associated with global change (increased temperature, CO₂, UV-B radiation and altered precipitation) on the performance (e.g., reduced developmental rate or increased abundance) of aboveground herbivore feeding guilds. General trends identified as “+” positive response, “−” negative response and “?” unknown. References citing examples of prevailing trends are given where possible
Table 10.3 The effect of component aspects of global change on interspecific interactions between herbivores and their natural enemies in agro-ecosystems. Net effect on prey performance in the presence of an antagonist; ‘+’ positive response, ‘−’ negative response, ‘=’ no effect. Only studies that gave a clear indication of herbivore performance were included. Only primary literature referenced. (* Studies from forest or grassland ecosystems)

Chapter 11: Climate Change in the Underworld: Impacts for Soil-Dwelling Invertebrates

Table 11.1 Summary of the Impact of Climate Change on Nematodes, Insects and Earthworms

Chapter 13: Forest Invertebrate Communities and Atmospheric Change

Table 13.1 Summary of the literature observing individual insect responses to elevated concentrations of CO₂ and O₃ conducted within forested FACE sites
Table 13.2 Summary of the literature considering the effects of elevated CO₂ and/or O₃ concentrations on multiple species of invertebrates in forest/woodland ecosystems. Results show the effects of elevated concentrations of the given gas, that is, a reported decrease represents a decline under elevated compared with ambient conditions. FACE = Free Air Carbon dioxide Enrichment; OTC = Open Top Chamber

Chapter 16: Evolutionary Responses of Invertebrates to Global Climate Change: the Role of Life-History Trade-Offs and Multidecadal Climate Shifts

Table 16.1 A review of the various processes and mechanisms affecting invertebrate exposure to the impacts of global warming. Exposure is ultimately determined by large-scale spatial and temporal macroclimatic gradients and a variety of local-scale effects. Species' traits and behavioural responses are also key to determining exposure, and therefore exposure and species sensitivity are ultimately linked
Table 16.2 A review of the various mechanisms mediating invertebrate responses to the impacts of global warming. The vulnerability component involved is highlighted (E=exposure, S=sensitivity, A=adaptive capacity)

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Title: Global climate change and terrestrial invertebrates / editors Scott Johnson, Hefin Jones.

Description: Chichester, UK ; Hoboken, NJ : John Wiley & Sons, 2017. | Includes bibliographical references and index.

Identifiers: LCCN 2016039782 (print) | LCCN 2016052637 (ebook) | ISBN 9781119070900 (cloth) | ISBN 9781119070870 (pdf) | ISBN 9781119070825 (epub)

Subjects: LCSH: Soil invertebrates–Effect of global warming on. | Climatic changes.

Classification: LCC QL365.34 .G56 2017 (print) | LCC QL365.34 (ebook) | DDC 363.738/74–dc23

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List of Contributors

Pedro Abellán
Department of Biology
Queens College
City University of New York
Flushing NY11367
USA

Nigel R. Andrew
Centre for Behavioural and Physiological Ecology, Zoology
University of New England
Armidale
NSW 2351
Australia

Paula Arribas
Department of Life Sciences
Natural History Museum
London SW7 5BD
UK
and
Department of Life Sciences
Imperial College London
Ascot SL5 7PY
UK

Cristina Canhoto
Centre of Functional Ecology
Department of Life Sciences
University of Coimbra
3000-456 Coimbra
Portugal

Jofre Carnicer
GELIFES, Conservation Ecology Group
9747 AG
Groningen
The Netherlands
and
CREAF, Cerdanyola del Vallès 08193
Spain
and
Department of Ecology
University of Barcelona
08028
Barcelona
Spain

Luis Fernando Chaves
Nagasaki University Institute of Tropical Medicine (NEKKEN), Sakamoto 1-12-4
Nagasaki
Japan
and
Programa de Investigación en Enfermedades Tropicales (PIET)
Escuela de Medicina Veterinaria
Universidad Nacional
Apartado Postal 304-3000
Heredia
Costa Rica

Cristina Domingo
Department of Geography
Autonomous University of Barcelona
Spain
and
CREAF, Cerdanyola del Vallès 08193
Spain

Lauren Ellse
School of Biological Sciences
Life Sciences Building
University of Bristol
Bristol BS8 1TH
UK

Sarah L. Facey
Hawkesbury Institute for the Environment
Western Sydney University
NSW 2751
Australia

Jessica R. K. Forrest
Department of Biology
University of Ottawa
Ottawa
ON K1N 6N5
Canada

Philippa J. Gerard
AgResearch
Ruakura Research Centre
Private Bag 3123
Hamilton
New Zealand

Andrew N. Gherlenda
Hawkesbury Institute for the Environment
Western Sydney University
NSW 2751
Australia

Richard Harrington
Rothamsted Insect Survey
Rothamsted Research
Harpenden
AL5 2JQ
UK

William T. Hentley
Department of Animal and Plant Sciences
University of Sheffield
Sheffield
UK

Jane K. Hill
Department of Biology
University of York
YO10 5DD
UK

Ivan Hiltpold
Department of Entomology and Wildlife Ecology
University of Delaware
DE 19716
USA

Scott N. Johnson
Hawkesbury Institute for the Environment
Western Sydney University
NSW 2751
Australia

T. Hefin Jones
School of Biosciences
Cardiff University
Cardiff CF10 3AX
Wales
UK

Micael Jonsson
Department of Ecology and Environmental Science
Umeå University
SE 901 87 Umeå
Sweden

Renée-Claire Le Bayon
Functional Ecology Laboratory
University of Neuchâtel
Switzerland

Richard L. Lindroth
Department of Entomology
University of Wisconsin-Madison
Madison
WI 53706
USA

Renata J. Medeiros
School of Biosciences
Cardiff University Cardiff CF10 3AX
Wales
UK

Andrés Millán
Department of Ecology and Hydrology
University of Murcia
Espinardo 30100
Spain

Uffe N. Nielsen
Hawkesbury Institute for the Environment
Western Sydney University
NSW 2751
Australia

Sabine S. Nooten
Hawkesbury Institute for the Environment
Western Sydney University
NSW 2751
Australia

Sören Nylin
Department of Zoology
Stockholm University
Sweden

Georgina Palmer
Department of Biology
University of York
YO10 5DD
UK

Josep Peñuelas
CREAF, Cerdanyola del Vallès 08193
Catalonia
Spain
and
CSIC, Global Ecology Unit CREAF-CSIC-UAB
Bellaterra 08193
Catalonia
Spain

Alison J. Popay
AgResearch
Ruakura Research Centre
Private Bag 3123
Hamilton
New Zealand

Kenneth F. Raffa
Department of Entomology
University of Wisconsin-Madison
Madison
WI 53706
USA

James M. W. Ryalls
Hawkesbury Institute for the Environment
Western Sydney University
NSW 2751
Australia

Hannah Rose Vineer
School of Veterinary Sciences
Life Sciences Building
University of Bristol
Bristol BS8 1TH
UK

David Sánchez-Fernández
Institute of Evolutionary Biology
CSIC-University Pompeu Fabra
Barcelona 08003
Spain
and
Institute of Environmental Sciences
University of Castilla-La Mancha
Toledo 45071
Spain

Joanna T. Staley
Centre for Ecology and Hydrology
Wallingford
UK

Constanti Stefanescu
CREAF, Cerdanyola del Vallès 08193
Spain
and
Museum of Natural Sciences of Granollers
08402, Granollers
Spain

Robert Thomas
School of Biosciences
Cardiff University
Cardiff CF10 3AX
Wales
UK

Andreu Ubach
Department of Ecology
Universitat de Barcelona
08028, Barcelona
Spain

James Vafidis
School of Biosciences
Cardiff University
Cardiff CF10 3AX
Wales
UK

Josefa Velasco
Department of Ecology and Hydrology
University of Murcia
Espinardo 30100
Spain

Roger Vila
IBE, Institute of Evolutionary Biology
08003, Barcelona
Spain

Ruth N. Wade
Department of Animal and Plant Sciences
University of Sheffield
Sheffield
UK

Richard Wall
School of Biological Sciences
Life Sciences Building
University of Bristol
Bristol BS8 1TH
UK

Chris Wheat
Department of Zoology
Stockholm University
Sweden

Christer Wiklund
Department of Zoology
Stockholm University
Sweden