Insect responses to interacting global change drivers in managed ecosystems

Insect responses to interacting global change drivers in managed ecosystems

Available online at ScienceDirect Insect responses to interacting global change drivers in managed ecosystems Christoph Scherbe...

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ScienceDirect Insect responses to interacting global change drivers in managed ecosystems Christoph Scherber1,2 Insects are facing an increasingly stressful combination of global change drivers such as habitat fragmentation, agricultural intensification, pollution, or climatic changes. While single-factor studies have yielded considerable insights, multifactor manipulations have gained momentum recently. Nevertheless, most work to date has remained within particular domains of research, such as ‘habitat destruction’ or ‘climate change’, and linkages among subdisciplines within the ecological literature have remained scarce. Here, I provide an overview of the most recent developments in the field, with a focus on main functional groups of insects, but also their interactions with other organisms. All major global change drivers (landscape modification, climate change, agricultural management) are covered both singly and in interaction. The manuscript concludes with concepts on how to statistically and conceptually deal with interactions in experimental and observational work. Addresses 1 Agroecology, Department of Crop Science, Georg-August-University Go¨ttingen, Grisebachstr. 6, 37077 Go¨ttingen, Germany 2 Institute of Landscape Ecology, University of Mu¨nster, Heisenbergstr. 2, 48149 Mu¨nster, Germany Corresponding author: Scherber, Christoph ([email protected], [email protected])

Current Opinion in Insect Science 2015, 11:56–62 This review comes from a themed issue on Global change biology Edited by Steven L Chown For a complete overview see the Issue and the Editorial Available online 6th November 2015

just beginning to be explored. In this review, I cover the key concepts necessary to understand insect responses to interacting drivers, show recent experimental progress, and provide approaches to predict the outcome of interacting drivers for insect populations and communities.

Biotic and abiotic drivers of global change Global and anthropogenic environmental changes (GEC) affect what has been termed ‘drivers’ [7], most of which are directly or indirectly related to human population growth [8]. Classes of drivers important for insects can be grouped by compartments and/or biogeochemical cycles. The most important drivers currently recognized (e.g. [9]) are land-use change (including habitat loss), climatic changes, pollution, biological invasion, anthropogenic exploitation of resources, and diseases.

The concept of interacting drivers Consider two GEC drivers, for example drought and elevated CO2, dynamic over time. If both drought and elevated CO2 act independently, the outcome (e.g. insect growth) will equal the sum of the impacts of both processes (e.g. negative growth [10]). However, if both drivers are correlated, the result will be a coupled time series [11]. Recent research [12] has shown that coupled nonlinear time series can appear uncorrelated, positively or negatively correlated (so-called mirage correlations). While there are methods to reconstruct cause-effect relationships from multiple interacting ecological variables [12,13], applications in the field of GEC research have so far been limited. 2214-5745/# 2015 Elsevier Inc. All rights reserved.

Introduction Human activities are increasingly altering all major components of the Earth system, affecting ecosystem flux rates, biodiversity, and community structure [1,2]. Because many different drivers of global change act simultaneously [3], the outcome for particular species or communities may be difficult to predict. Insects are the most species-rich group of organisms on Earth [4,5], inhabiting major parts of terrestrial and aquatic ecosystems. Their responses to interacting global change drivers in a multi-factor world [6] are Current Opinion in Insect Science 2015, 11:56–62

Another approach to multiple interacting GEC drivers is to look at temporally aggregated data, for example by calculating central tendency or working with log-response ratios [14]. In these studies, it has become common practice to classify effects as synergistic, neutral or antagonistic. Recently, the concept of ‘synergism’ versus ‘antagonism’ among drivers was extended [15] to include terms such as ‘double positive’, ‘positive neutral’ or similar. However, this concept falls short if there are more than two interacting drivers. Other studies [16] have differentiated additive from synergistic effects, but usually disregarded antagonistic interactions. Overall, three main questions remain to be answered in the context of multiple interacting drivers: (1) Which are the most important individual drivers for insect performance?

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(2) Does the number of drivers per se influence insect performance? (3) Which are the most commonly observed combinations of drivers, and how do they affect insect performance?

Insect responses to single global change drivers Clearly, habitat destruction and conversion from natural to managed systems are among the most important drivers of changes in insect abundance and diversity [17], affecting agriculturally important processes such as biological control [18]. For example, in a study in 45 Swedish grassland fragments strong negative effects of habitat loss on pollinating insects were reported [19]. Resource consumption in general [20] has been shown to be negatively affected by habitat fragmentation, especially in specialist species. Conversion from (semi-)natural to managed systems often coincides with changes in farming practices, such as organic versus conventional farming [21], or increased pesticide use [22]. A particularly recent development is the study of multiple interacting pesticides such as neonicotinoids [23,24,25]. Biotic exchange and biological invasions may affect insects in a variety of ways, depending on the trophic level at which alien taxa enter local communities. For example, invasive alien plants may provide additional resources to herbivores or pollinators, altering the structure of interaction networks [26]. By contrast, invasive insects can dramatically alter top-down control in ecosystems [27]. In the context of climate change research, many studies have focused on altered temperature [28]. For example, Ref. [29] presented a meta-analysis of responses of insect herbivores to individual drivers and concluded that temperature (but not CO2 or UV radiation) strongly affected key parameters of insect performance. Rapid climate warming may disrupt life-cycle regulation, leading to developmental traps (lost generation hypothesis [30]). Water availability, which is often closely linked to other climatic changes, can also have profound effects on insect herbivores [31–33], with particularly adverse effects on sap-sucking taxa. In dryland ecosystems, shifts in the trophic position of some insect taxa may be expected, depending on local water availability (reviewed in [34]). Other drivers, such as nitrogen deposition or elevated CO2 [7,35], have been shown to act indirectly via changes in primary producer abundance, diversity or physiology (but see [36]). In unfertilized systems, increased CO2 may result in progressive nitrogen limitation [37,38], negatively affecting insect herbivores [39].

Number of drivers In classical biodiversity experiments, the number of species present in a system is manipulated [7]. By analogy, one could imagine experiments that explicitly manipulate the number of global change drivers (e.g. [10]). As more and more drivers are combined, insect performance may be expected to decrease. This would be an example of a sampling effect, where an increasing number of drivers would increase the chance that a particularly adverse driver is present.

Interactions of drivers Increasingly, global change experiments incorporate combinations of GEC drivers [14,40,41] and explicitly test for interactions. In the simplest possible scenario, the interaction among several drivers can be summarized as the sum of individual effects, assuming these effects are additive [16]. However, effects of an interaction may also become stronger over time. For example, growth of insect larvae exposed to combinations of drivers may show complex dynamics over time (Figure 1). Future experiments therefore need to investigate longer-term responses to combined GEC drivers [42]. Several key ingredients are needed to understand interactions among drivers. First, full-factorial manipulations of several factors in experiments are required; that is, we need to move away from experiments manipulating only one or two drivers. Such combined experiments are best done using split-plot or nested designs [43]. Second, interaction terms of sufficient order need to be incorporated in statistical models. Third, it is notoriously difficult to interpret interactions on the basis of numerical model output alone [44], and interactions should be plotted using twodimensional graphs, preferably showing the individual data points instead of using bar graphs (Figure 2).

Recent developments in the study of interacting drivers Most studies so far focused on two or three interacting global change drivers. For pollinators, a recent analysis showed that global change pressures tend to interact in an additive way [45]; that is, the result of the interaction is equal to the sum of the individual effect sizes. For example, human-modified landscapes are often characterized by higher abundances of non-native plants and pollinators [46,47]. Several important interactions have remained little explored, such as those between climatic changes and landscape modification [48], or between agricultural intensification and landscape modification [49]. One of the currently most pressing research questions is the interaction between pesticides and other stressors [50], including parasites and pathogens affecting pollinators. In addition, interacting global change drivers may unexpectedly affect attractiveness of flowers to pollinators [51] (Figure 3), reducing globally important pollination services. Current Opinion in Insect Science 2015, 11:56–62

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Figure 1

Additive vs. non-additive



Number of drivers


Treatment mean






Ctrl. Ctrl. Ctrl. Ctrl. 0




Type of effect






Number of drivers Current Opinion in Insect Science

Theoretical concepts showing insect responses to (a) additive versus non-additive effects and (b) number of global change drivers. In (a), an additive effect means that the response equals the mean across all treatments (dashed grey line); a positive effect indicates that combinations result in a more positive effect than expected from single drivers; a negative effect indicates that the result is more negative than expected; (b) shows a hypothetical example of four drivers temperature (T), drought (D), habitat fragmentation (H) and increased CO2 (C), where an increased number of drivers leads to a stronger response; (b) is partly on the basis of [10].

Figure 2

Elevated CO2


Weight (mg)


No Drought Drought



0 1








Time (weeks) Current Opinion in Insect Science

An example of how to visualize a three-way interaction in global change experiments. The response variable is the weight of beetle larvae (in mg) measured over time (x axis). The two lines in each graph show drought versus ambient treatments, and the two panels show ambient versus elevated CO2. Own figure, on the basis of data from Ref. [10]. Current Opinion in Insect Science 2015, 11:56–62

Global change responses in insects Scherber 59

Figure 3


Morphology Chemistry

Visitation Consumption

Plant quality

Insect performance


+ _ eCO2

+ N deposition


Reproduction Survival

Current Opinion in Insect Science

An example showing how the effects of interacting climate change drivers on performance of insect pollinators, herbivores or parasitoids may be visualized as a conceptual structural equation metamodel. While elevated CO2 (eCO2) often reduces plant quality (tissue, nectar), other drivers such as warming or nitrogen deposition increase it; in addition, effects may be direct (dotted arrows) or plant-mediated (solid arrows). Performance may include behavioural aspects (visitation, consumption) or fitness correlates (reproduction, survival). Own figure, synthesized from [10,51,70] and Box S1 in [41].

For insect herbivores, a wide range of interacting drivers has been studied so far, including land-use intensity and landscape context [52,53,54,55], biodiversity and agricultural management [56], or climate change components such as altered temperature, CO2, rain, ozone, photoperiod or ultraviolet radiation [14] (Figure 3), sometimes over long time scales [57]. Many climate change studies have concentrated on warming, altered precipitation or increased CO2 [14,58,59,60,61,62], and only few studies have investigated more than two drivers (but see [63]). Similar to the findings reported for pollinators, insect herbivores also tend to be affected in a multiplicative way in most cases; that is, the effects of interacting drivers often equals the product of their individual effect sizes [14]. Management of phytophagous agricultural pests in response to global change drivers may require multi-species management approaches [64]. Higher trophic levels, such as carnivores or omnivores (e.g. Carabid beetles [65], trap-nesting taxa [66]), or parasitoids [49,67,68], have received fewer attention. A recent study on host-parasitoid interactions in 30 landscapes [49] found that higher trophic levels were more negatively affected by land-use change (insecticides, annual crop cover) than lower trophic levels. Similar effects were reported for climate change drivers [69], where herbivore biomass was increased relative to

parasitoid biomass in response to interacting climate change. Some of these effects may additionally be modified by altered patterns in plant volatile organic compounds or chemistry [70]. Herbivore control by higher trophic levels in agroecosystems may be modified by biotic interactions and landscape complexity [71]. Finally, a large body of literature reports interactive effects of global change drivers on belowground communities [72–75], in which insects or their larval stages act as predators, herbivores, or decomposers. For example, a study manipulating plant biodiversity, atmospheric CO2, and nitrogen deposition found that plant communities of 1, 4 or 9 species had increasingly higher abundances of Thysanoptera, while other belowground insects were only weakly affected by plant diversity, CO2 or nitrogen (with no significant interactions). Understanding interactive global change effects in belowground systems will be considerably improved when traditional analyses are paired with molecular approaches such as next-generation sequencing, allowing more rapid assessments of belowground insect diversity [76].

Outlook and future directions Recently, interactive effects of global change drivers have been studied in a wide range of insect groups, such as Current Opinion in Insect Science 2015, 11:56–62

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received funding from the Deutsche Forschungsgemeinschaft (DFG FOR1451/2 ‘The Jena Experiment’), the DFG Graduiertenkolleg 1644 ‘Scaling Problems in Statistics’ and the EU-infrastructure project ‘Increase’. The Danish ‘Climaite’ Experiment consortium is thanked for their support.

Figure 4

Ecosystem functioning



Parasitism Predation rates

Pathogen resistance



Plant pathogens



Plant community

Climatic changes

Management intensity

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Pollination Flower visitation



Biodiversity loss


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herbivores, pollinators, or predatory insects. Nevertheless, both insects [77] and global change drivers [16] interact to form complex networks. Unravelling relationships in such complex networks, and disentangling cause and effect of individual and interacting drivers, will require novel statistical and methodological approaches such as structural equation modelling [10,53,78] (Figure 4), or molecular analyses of trophic interactions [76]. Last but not least, novel experimental facilities are needed, such as next-generation biodiversity [79] and climate change experiments [80], where both stochastic and deterministic components of global change are manipulated with sufficient replication. Small-scale, highly controlled experiments need to be combined with largerscale, landscape-wide manipulations [81] of both global change drivers and trophic interactions [82]. Eventually, novel experiments will allow us to predict and respond to pressures of the future to come.

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