Agricultural intensification drives landscape-context

effects on host–parasitoid interactions in

agroecosystems

Mattias Jonsson1,2*, Hannah L. Buckley3, Bradley S. Case3, Steve D. Wratten1,

Roddy J. Hale3 and Raphael K. Didham4,5,6

1Bio-Protection Research Centre, PO Box 84, Lincoln University, Lincoln 7647, New Zealand; 2Department of

Ecology, Swedish University of Agricultural Sciences, PO Box 7044, SE-750 07, Uppsala, Sweden; 3Department of

Ecology, PO Box 84, Lincoln University, Lincoln 7647, New Zealand; 4School of Biological Sciences, University of

Canterbury, Private Bag 4800, Christchurch, New Zealand; 5School of Animal Biology, University of Western Australia,

35 Stirling Highway, Crawley, WA 6009, Australia; and 6CSIRO Ecosystem Sciences, Centre for Environment and Life

Sciences, Underwood Ave, Floreat, WA 6014, Australia

Summary

1. Agricultural land use threatens ecosystem services such as biological control by natural enemies

because of simplification of habitat structure and intensification of disturbance and agrochemical

inputs. Lowparasitism rates of agricultural pests have typically been attributed to a lack of resources

for parasitoids in highly simplified landscapes, but this couldbe confoundedby the nearly ubiquitous

correlation between landscape complexity and the cover of intensively farmedagricultural crops.

2. Here, we disentangle the mechanisms driving landscape-scale effects on host–parasitoid interac-

tions by taking advantage of a landscape modification gradient in which the diversity of habitat

types and annual crop cover in the landscape were uncorrelated. We quantified herbivore densities

andparasitismandhyperparasitismrateson two important croppests (aphidsandPlutellaxylostella)

across 30 landscapes. We used structural equation modelling (SEM) to test whether land-use

intensity (insecticide application and habitat disturbance) or resource availability for parasitoids

(floral resources and alternative host plants) was mediating the effects of habitat diversity and

annual crop cover on the landscape.

3. Rates of primary- and hyperparasitism of aphids and primary parasitism ofP. xylostella decreased

with increasing annual crop cover, whereas decreasing habitat diversity in the landscape had little

effect on parasitism rates. These effects were mediated almost entirely by greater habitat disturbance

and greater frequency of insecticide application, rather than by changes in resource availability.

4. Parasitoids were more sensitive to intensive farming practices than were their herbivore hosts,

and in turn hyperparasitoids were more sensitive than were primary parasitoids. This supports the

theoretical prediction that higher trophic levels should be increasingly sensitive to the disturbances

associated with land-use change.

5. Synthesis and applications.Our work suggests that increased land-use intensity (e.g. higher insec-

ticide inputs and greater levels of disturbance associated with increasing area of annual crops) has

been underestimated as a driver of landscape effects on host–parasitoid interactions. These findings

have important implications for the maintenance of ecosystem services such as biological control.

The promotion of low-intensity farming practices that limit the extent and frequency of agrochemi-

cal inputs and habitat disturbances will be essential for the maintenance of effective biological

control by parasitoids in agroecosystems.

Key-words: biological control, diamondback moth, disturbance, ecosystem service, grey

cabbage aphid, habitat diversity, hyperparasitoid, primary parasitoid, resource availability,

trophic interactions

*Correspondence author. E-mail: mattias.jonsson@slu.se

Journal of Applied Ecology doi: 10.1111/j.1365-2664.2012.02130.x

� 2012 The Authors. Journal of Applied Ecology � 2012 British Ecological Society

Introduction

Increased agricultural production since the 1950s has modified

agricultural landscapes in several ways, including the

destruction and fragmentation of natural habitats, reduction

in habitat diversity, and increases in habitat disturbance and

agrochemical application (Tilman et al. 2001). Agricultural

expansion is therefore considered a major driver of global

biodiversity loss (Tilman et al. 2001). There is increasing evi-

dence that this has important effects on species interactions

(Tylianakis et al. 2008) and ecosystem services such as biologi-

cal control (Bianchi, Booij & Tscharntke 2006). For example,

it has been shown repeatedly that parasitism of crop pests is

higher in complex landscapes with a high diversity of habitat

types and a large proportion of semi-natural habitat cover (see

Chaplin-Kramer et al. 2011). Interpretation of these effects is

confounded by the fact that in most agricultural landscapes,

habitat diversity and semi-natural crop cover are strongly neg-

atively correlated with the extent of intensive agricultural land,

making it difficult to tease apart the mechanisms driving the

observed relationships between landscape structure, biodiver-

sity and ecosystem processes. To date, there have been few

studies that have successfully disentangled the drivers of land-

scape effects on species communities and ecosystem services in

agricultural landscapes (Fahrig et al. 2011).

The commonly accepted mechanism underlying landscape

effects on biological control is that complex landscapes provide

parasitoids with resources, such as adult food and

overwintering sites in proximity to the crop fields (Bianchi,

Booij & Tscharntke 2006; Tscharntke et al. 2008). While there

is explicit, small-scale evidence that parasitoids do use resources

in non-crop habitats and then spill over into adjacent crops to

parasitize pests (Lavandero et al. 2005; Rand, Tylianakis &

Tscharntke 2006), the hypothesis that resource availability is

the key driver of landscape effects on parasitism rates remains

largely untested. An alternative explanation for lower parasit-

ism rates in highly simplified landscapes dominated by agricul-

ture is that parasitism is negatively influenced by increasing

land-use intensity including ploughing, harvesting and insecti-

cide application (Croft 1990; Kruess & Tscharntke 2002). While

there have been many studies contrasting local-vs. landscape-

level determinants of variation in natural enemy attack rates

(e.g. Roschewitz et al. 2005; Geiger et al. 2010; Holzschuh,

Steffan-Dewenter & Tscharntke 2010), there have been no pre-

vious studies that disentangle the relative importance of

resource availability and land-use intensity as drivers of land-

scape effects on host–parasitoid interactions in agroecosystems.

We aimed to identify the drivers of landscape effects on

host–parasitoid interactions through a comparative experi-

ment in which we quantified herbivore densities and parasitism

and hyperparasitism rates across 30 landscapes varying in

degree of agricultural modification. Our study system

comprised two of the world’s most important insect crop pests,

Plutella xylostella L. (diamondback moth) and aphids, mostly

Brevicoryne brassicae L. (grey cabbage aphid), on a globally

significant crop species, Brassica oleracea L. We used a

landscapemodification gradient inNewZealand in which hab-

itat diversity and proportional cover of annual crops in the

landscape were uncorrelated. We used structural equation

modelling (SEM) to test different proximate mechanisms that

might explain the observed landscape effects. We hypothesized

that the effects of habitat diversity and annual crop cover on

host–parasitoid interactions could be mediated by direct or

indirect effects of altered resource availability (floral resources

and alternative crucifer hosts) or land-use intensity (habitat

disturbance and insecticide application).

Materials and methods

GRADIENTS OF HABITAT TYPE DIVERSITY AND ANNUAL

CROP COVER IN THE LANDSCAPE

We conducted the study in B. oleracea (kale) crops grown as winter

feed for cattle and sheep in the Canterbury region of the South Island

of New Zealand (Fig. S1, Supporting Information). The study was

conducted at 30 randomly selected kale fields located at least 6 km

apart with each field managed by a different farmer (Appendix S1,

Supporting Information). Patterns of land use were quantified within

a 500-m radius of the centre of each sampling area, distinguishing 14

land-cover classes using aerial photographs and ArcGIS 9Æ2 (ESRI,

Redlands, California, USA) (Appendix S1, Table S1, Supporting

Information). We selected a 500-m scale because parasitoid species

have been found to respond strongly to landscape composition at this

spatial scale (Thies, Roschewitz & Tscharntke 2005). Based on the

land-cover data, habitat diversity and annual crop cover in the land-

scape were determined for each site. The Shannon diversity index was

used as a measure of habitat diversity, and annual crop cover was cal-

culated as the proportion cover of brassica crops, cereal crops, vegeta-

ble crops and recently harvested annual crops, combined.

INSECT SAMPLING

In each of 30 kale fields, a strip of land at least 120 m long by 15 m

wide along one side of the field was left untreated with insecticide,

and all insect sampling was conducted within this strip. In each field,

P. xylostella pupae were sampled once between 19 February and 5

March 2007, and aphids (predominantlyB. brassicae, but alsoMyzus

persicae Sulzer, the green peach aphid) were sampled once between 19

March and 2 April 2007. Two sampling periods were necessary

becauseP. xylostella abundances usually peak in late summer inNew

Zealand, whereas the aphid populations on brassica grown as winter

feed generally peak in the autumn. Within each 14-day period,

sampling commenced at the slightly warmer, northernmost sites in

the region and ended at the southernmost sites to minimize potential

phenological differences among sites. Sampling was conducted along

a 100-m-long transect located 8 m from the field edge, in the middle

of the unsprayed strip. The number of P. xylostella pupae (excluding

empty pupal cases), live aphids and aphid mummies were counted on

25 kale plants randomly selected along each transect, with c. 4 m

between sampled plants. The primary parasitism rate of aphids was

estimated by dividing the number of mummies found on the plants by

the number of live aphids plus mummies. Plutella xylostella pupae

and aphid mummies were collected (max. five per plant) along each

transect and taken to the laboratory for rearing and assessment of

parasitism (for P. xylostella pupae) and hyperparasitism rates (for

P. xylostella pupae and aphid mummies). The primary parasitism

rate of P. xylostella was estimated by dividing the number of pupae

from which primary- and hyperparasitoids emerged, by the total

2 M. Jonsson et al.

� 2012 The Authors. Journal of Applied Ecology � 2012 British Ecological Society, Journal of Applied Ecology

number of pupae fromwhich any live host or parasitoid emerged (i.e.

ignoring pupae that failed to rear to eclosion). Hyperparasitism rates

of P. xylostella and aphids were calculated as the proportion of para-

sitized P. xylostella pupae and aphid mummies, respectively, from

which hyperparasitoids emerged. We attempted to collect 100

P. xylostella pupae and 100 mummies at each site, but in some

cases a lower number was collected because of low densities and

time constraints. At a few sites, the number of emerged P. xylostel-

la pupae, aphids or mummies found was below 10, and these sites

were excluded from analyses. In all, 27 sites were analysed for

P. xylostella parasitism, 29 for aphid parasitism and 26 for aphid

hyperparasitism.

PROXIMATE MECHANISMS OF LANDSCAPE EFFECTS

ON HOST–PARASITOID INTERACTIONS

From previous studies (Croft 1990; Kruess & Tscharntke 2002;

Lavandero et al. 2005) and our own empirical observations, we iden-

tified four proximate mechanisms related to resource availability and

land-use intensity that were most likely tomediate the landscape-level

effects of habitat diversity and annual crop cover on host–parasitoid

interactions, and wemeasured these in a portion of each 500-m radius

landscape sector (for logistical reasons, proximate variables could not

be measured in the whole landscape sectors) (Table S2, Supporting

Information).

Landscape effects may operate through resource availability for

parasitoids and herbivores, in the form of availability of (i) floral

resources and (ii) alternative crucifer hosts (Appendix S2, Supporting

Information). The cover of flowering plants and of crucifers (predom-

inantly the weed Capsella bursa-pastoris L. shepherds purse) was esti-

mated within a 100-m buffer around each study field between 19

September and 30 November 2007 by the same observer (MJ). This

time of year constitutes a bottleneck in terms of resource and host

availability for specialist brassica herbivores in Canterbury, when the

winter feed crops have been removed by grazing. The area surveyed

for flowers and crucifers corresponded to on average 18% of the area

in the full landscape sectors, and this comprised a good representation

of land-cover types in these sectors (average correlation coefficient of

proportion cover of the broad cover classes between the landscape

subsample and the full landscape was 0Æ87).Landscape effects may also operate through land-use intensity in

the form of (iii) the frequency of insecticide applications and (iv) habi-

tat disturbance (e.g. ploughing or harvest). The frequency of insecti-

cide applications during one season within the brassica field outside

the unsprayed sampling strip was ascertained through interviews with

farmers. The study field comprised on average 70% of the total area

of brassica crops within the full landscape sectors, and the majority of

these fields were managed by the same farmer. We therefore consider

our estimate of the frequency of insecticide application to be represen-

tative of brassica fields in the full landscape sectors. As most of the

parasitoids in this study are relatively host specific (Appendix S2,

Supporting Information), insecticide applications in annual crops

other than brassica are likely to have a small influence on host–para-

sitoid interactions. All insecticides applied to the brassica crops were

broad-spectrum products, including one or a mixture of the following

active ingredients: deltamethrin, chlorpyrifos, imidacloprid and

lambda-cyhalothrin. Insecticides with these ingredients are known to

have significant effects on natural enemies, with the effects on the ben-

eficial arthropod component of the Environmental Impact Quotient

(EIQ) being 22Æ2, 23Æ3, 39Æ3 and 47Æ5, respectively (Kovach et al.

2010). We constructed a simple habitat disturbance index (H) reflect-

ing the frequency of soil and vegetation disturbance within 100 m of

the outer perimeter of each study field. The proportion of cover (pi) of

each of the 14 land-cover classes was weighted by its estimated level

of disturbance (k, Appendix S2; Table S3, Supporting Information),

and the weighted cover scores were summed across classes to derive

the index (equation 1):

H ¼Xðpi � kÞ eqn 1

We conducted a sensitivity analysis to test whether the assumption

about specific differences in disturbance levels between land-cover

classes used for the habitat disturbance index affected the results of

statistical analyses (Appendix S3, Supporting Information).

DISCRIMINATING THE DIRECT AND INDIRECT EFFECTS

OF HABITAT TYPE DIVERSITY AND ANNUAL CROP

COVER ON HOST–PARASITOID INTERACTIONS

We used structural equation models (SEM) to discriminate the rela-

tive direct, indirect and total effects of habitat diversity and annual

crop cover in the landscape on herbivore density and parasitism rate,

using Amos v19Æ0 (Amos Development Corporation, Crawfordville,

Florida, USA). First, we hypothesized that indirect effects of habitat

diversity in the landscape would be mediated by resource availability

(floral resources and crucifer hosts; Fig. 1a). Both crucifer weeds and

flowering plants are likely to be common along borders between habi-

tat types (Bianchi, Goedhart & Baveco 2008), and these resources

could therefore be expected to increase in abundance with increasing

habitat diversity. Secondly, indirect effects of annual crop cover in the

landscape were hypothesized to operate through both altered land-

use intensity (habitat disturbance and insecticide application) and

altered resource availability (Fig. 1a). Increased annual crop cover

may lead to an increase in the intensity and frequency of habitat dis-

turbance and in the frequency of insecticide application (Meehan

et al. 2011), and floral resources might bemore abundant in non-crop

habitats (Steffan-Dewenter, Munzenberg & Tscharntke 2001). Cruci-

fer weed abundance is likely to be highest in the more disturbed habi-

tats, and we therefore hypothesized that any effects of annual crop

cover on host–parasitoid interactions that were mediated by crucifer

availability would occur indirectly via the effect of annual crop cover

on habitat disturbance. In the full SEM model (Fig. 1a), the direct

effects of habitat diversity and annual crop cover on herbivore density

and parasitism were also tested, representing unexplained associations

between these variables. After inspection of goodness-of-fit of the full

model (see Appendix S4, Supporting Information for details of model

fitting procedures), it was evident that the hypothesized relationships

among variables (solid arrows in Fig. 1a) were inadequate to describe

the observed covariance structure of the data. Therefore, we added two

further paths to the full model (dashed arrows in Fig. 1a), with one path

from alternative crucifer hosts to flowers and another path from habitat

diversity to habitat disturbance. In the first case, this makes biological

sense as the effect of crucifer plants on parasitism rates might operate

through increased host-plant availability for herbivores, or via their

contribution to increased flowering resources for parasitoids. In the sec-

ond case, we believe that there is no strong a priori conceptual basis as

to why an increase in habitat diversity should necessarily lead to

changes in habitat disturbance in certain landscapes, but it is easy to see

how a significant statistical relationship between variables could arise

through a ‘selection frequency’ effect, in which increases in habitat

diversity lead to a greater likelihood of including land-use types with

lower average disturbance frequency or intensity.

Proportion parasitism of P. xylostella pupae, hyperparasitism of

aphid mummies, alternative crucifer hosts and floral resources were

Land-use intensity decreases parasitism rates 3

� 2012 The Authors. Journal of Applied Ecology � 2012 British Ecological Society, Journal of Applied Ecology

arcsine-square-root-transformed, whereas the proportional parasit-

ism of aphids was 4th-root-transformed, and P. xylostella, aphid and

mummy density were ln (x + 1)-transformed prior to analysis to

meet the assumptions ofmultivariate normality.

The full SEM model was fit and tested using a maximum likeli-

hood approach (Kline 2005), and the most parsimonious final SEM

models were identified using an information theoretical approach

(see Appendix S4, Supporting Information). Furthermore, we con-

ducted a sensitivity test of the validity of the causal hypotheses

underlying our SEMs by testing a ‘maximal model’ containing all

potential direct and indirect links between ultimate and proximate

variables (Appendix S4, Supporting Information). We also tested

for possible spatial autocorrelation in the residuals of the final mod-

els using SAM 3Æ0 (Rangel, Diniz-Filho & Bini 2006; Appendix S4,

Supporting Information). Finally, we ran confirmatory generalized

linear models to validate the relative effect sizes of proximate vari-

ables identified as important drivers of parasitism in the SEM

(Appendix S5, Supporting Information).

Results

HERBIVORE DENSIT IES AND PARASIT ISM RATES

In the assessment of herbivore density, an average of 38 P.

xylostella pupae were counted on the 25 plants at each site.

During laboratory rearing to estimate parasitism rate, an aver-

age of 66 of the collectedP. xylostella emerged per site (median,

73; range, 17–92). Parasitism was determined as the propor-

tion of individuals that emerged as the larval parasitoidDia-

degma semiclausum Hellen (82Æ1% of parasitoids) or the

pupal parasitoid Diadromus collaris Gravenhorst (17Æ9% of

parasitoids). Diadegma semiclausum was hyperparasitized

by Trichomalopsis sp., but only at low frequencies at five of

the sites and with no hyperparasitism detected at the other

sites. Therefore, landscape effects on hyperparasitism rate of

P. xylostellawere not tested.

Full SEM model Parasitism of Plutella xylostella

Parasitism of aphids Hyperparasitism of aphids

(a)

(c)

(b)

(d)

Fig. 1. Structural equation models discriminating the direct and indirect effects of habitat type diversity and annual crop cover on host–parasit-

oid interactions, showing (a) the full model, and the most parsimonious models for (b) parasitism of Plutella xylostella, (c) parasitism of aphids,

and (d) hyperparasitism of aphids. The full model was the same for all three systems except that no link between floral resources and host density

was present in the aphid parasitismmodel, because aphids do not feed on flowers. Arrows represent causal paths from predictor to response vari-

ables. The two dashed arrows represent paths that were added after initial inspection of the residual covariance matrix and overall model fit. The

number on each path in the parsimonious models is the value of the unstandardized partial regression coefficient, indicating whether the relation-

ship is positive or negative. The statistical significance of individual regression coefficients is indicated by the colour of the line (black, P £ 0Æ05;dark grey, 0Æ05< P £ 0Æ10; light grey P > 0Æ10). The thickness of the line indicates the magnitude of the standardized path coefficients (Tables

S4a–c, Supporting Information). For the four endogenous variables, squared multiple correlations (R2) are given to represent the variance

explained by all the associated pathways linking that variable

4 M. Jonsson et al.

� 2012 The Authors. Journal of Applied Ecology � 2012 British Ecological Society, Journal of Applied Ecology

On average, 2500 live aphids were counted on the 25 plants

at each site. The aphids counted were dominated by

B. brassicae (90Æ6% of aphids), with the remaining aphids

being M. persicae (9Æ4% of aphids). On average, 167 aphid

mummies (parasitized aphids) were counted on the 25 plants at

each site. Primary parasitism of aphids was estimated by divid-

ing the number of mummies counted by the number of live

aphids plus mummies at each site. During laboratory rearing

to estimate hyperparasitism rate, an average of 45 of the col-

lected aphid mummies survived and emerged per site (median,

43; range, 10–88), and hyperparasitism of aphids was

determined as the proportion of individuals that emerged as

Alloxysta sp. (83Æ9% of hyperparasitoids), Asaphes sp. (15Æ9%

of hyperparasitoids) and Dendrocerus sp. (0Æ2% of hyperpar-

asitoids). Diaeretiella rapae McIntosh was the only primary

parasitoid that emerged during rearing from aphid mummies,

so all primary parasitismwas attributed to this species.

DISCRIMINATING THE DIRECT AND INDIRECT EFFECTS

OF HABITAT TYPE DIVERSITY AND ANNUAL CROP

COVER ON HOST–PARASITOID INTERACTIONS

Across our study sites, habitat type diversity and annual crop

cover in the landscape were uncorrelated (sampling period 1:

r = 0Æ06, P = 0Æ75; sampling period 2: r = 0Æ09, P = 0Æ65).Examples of variation in habitat type diversity and annual

(b)

0·2 0·3 0·4 0·5 0·6 0·7 0·8 0·9

Proportion annual crop cover in the landscape

(f)

0·0 0·5 1·0 1·5 2·0 2·5 3·0

Habitat type diversity in the landscape (Shannon)

0·0

0·2

0·4

0·6

0·8

1·0

1·2

1·4

1·6

Hyp

erpa

rasi

tism

of a

phid

s(a

rcsi

n sq

rt pr

opor

tions

, in

radi

ans) (e)

(d)

0·0

0·2

0·4

0·6

0·8

Par

asiti

sm o

f aph

ids

(4th

root

tran

sfor

med

pro

porti

ons) (c)

0·0

0·2

0·4

0·6

0·8

1·0

1·2

1·4

1·6

Par

asiti

sm o

f dia

mon

dbac

k m

oth

(arc

sin

sqrt

prop

ortio

ns, i

n ra

dian

s) (a)

Fig. 2. The relationship between landscape composition and parasitism rates of Plutella xylostella (a, b), parasitism rates of aphids (c, d), and

hyperparasitism rates of aphids (e, f). Parasitism of diamondback moth and hyperparasitism of aphids are presented as arcsine-square-root-

transformed proportions (in radians), and parasitism of aphids is presented as 4th-root-transformed proportions. Untransformed proportion

parasitism of diamondbackmothwas, on average, 0Æ68 (range, 0Æ30–1Æ00), for aphid parasitism 0Æ07 (range, 0Æ00–0Æ31) and for hyperparasitism of

aphids 0Æ79 (range, 0Æ17–1Æ00). The slopes of the fitted lines are calculated from the implied covariances around the sample means, derived from

the SEManalyses

Land-use intensity decreases parasitism rates 5

� 2012 The Authors. Journal of Applied Ecology � 2012 British Ecological Society, Journal of Applied Ecology

crop cover among the study landscapes are shown in Figs S2,

S3 in Supporting Information.

In the SEM analyses, all three models for parasitism rates

(Fig. 1) had acceptable goodness-of-fit indices, with all residual

covariance values <2 for both the full and final models, chi-

square values non-significant for all final models (P. xylostella

parasitism: Chi-square = 17Æ5, df = 22, P = 0Æ73; aphid par-

asitism: Chi-square = 15Æ6, df = 18, P = 0Æ69; aphid hyper-

parasitism: Chi-square = 22Æ2, df = 23, P = 0Æ59) and all

RMSEA values below 0Æ001. However, the relative strength

and significance of direct and indirect paths varied significantly

between models (Fig. 1). Primary parasitism rates of P. xylo-

stella and aphids, as well as hyperparasitism rates of aphid

mummies, all decreased with an increasing proportion of

annual crop cover in the landscape. By contrast, habitat type

diversity in the landscapes only had a weak (positive) effect on

aphid parasitism, and no effect on parasitism rates of P. xylo-

stella or hyperparasitism rates of aphidmummies (Figs 1,2).

In the SEM,we found that the negative effects of annual crop

cover on parasitism rates were mediated by different mecha-

nisms for different species, with increased frequency of insecti-

cide application most important for P. xylostella parasitism,

habitat disturbance most important for aphid hyperparasitism,

and both these variables being important for aphid parasitism

(Fig. 1b–d, Table S4a–c, Supporting Information). Although

the total effect of habitat disturbance on aphid parasitism rates

was negative, the final model also retained a small positive,

albeit non-significant, indirect effect of this variable on aphid

parasitism via increased abundance of crucifer hosts (Fig. 1c,

Table S4b, Supporting Information). There was also a non-sig-

nificant direct negative effect of annual crop cover in the land-

scape retained in the most parsimonious aphid parasitism

model. The positive total effect of habitat diversity on aphid

parasitism rate wasmediated predominantly by a negative asso-

ciation between habitat diversity and habitat disturbance.

Finally, there was a negative direct effect of habitat diversity on

aphid density and a negative direct effect of annual crop cover

onmummydensity, but apart from that no paths including host

density were retained in any of themodels.

No spatial autocorrelation was detected in any of the SEM

models, and no alternative approaches to constructing the habi-

tat disturbance index had a significant effect on SEM results

(Appendix S3, Supporting Information). The alternative SEMs

testing a ‘maximal model’ with all potential direct and indirect

links between ultimate and proximate variables also had no

significant effect on the SEM results (Table S5 Supporting

Information). Finally, the results from the confirmatory gener-

alized linear models did not change interpretation of the most

important factors determining variation in parasitism (Tables

S6, S7, Supporting Information).

Discussion

DRIVERS OF LANDSCAPE EFFECTS

We found that annual crop cover in the landscape had a

strong negative effect on parasitism rates of two important

crop pests (P. xylostella and aphids), whereas habitat

diversity only had a minor positive impact on parasitism rates

of one of the pests (aphids). These landscape-scale effects were

driven primarily by the frequency and magnitude of different

processes associated with the intensity of annual cropping

practices in our study system (insecticide application and hab-

itat disturbance, such as ploughing and harvesting), rather

than by any direct effects of greater resource availability for

parasitoids. To our knowledge, this is the first study to iden-

tify the relative landscape-level influences of habitat diversity

and amount of intensive land use on host–parasitoid interac-

tions in agroecosystems.

Several previous studies have compared the effects of local

land-use intensification and landscape-level complexity on

natural enemy attack rates (e.g. Roschewitz et al. 2005;

Geiger et al. 2010; Holzschuh, Steffan-Dewenter &

Tscharntke 2010). These studies have mostly used organic vs.

conventional farming as a proxy for local land-use intensity

and have therefore not been able to distinguish which aspects

of land-use intensity are most important. Two exceptions are

the recent studies by Geiger et al. (2010) and Krauss, Gallen-

berger & Steffan-Dewenter (2011), which showed that local

pesticide application had persistent negative effects on biodi-

versity, predator–prey ratios and natural enemy attack rates.

Our work now shows that insecticide application and habitat

disturbance are critical drivers of landscape-level effects on

natural enemy attack rates.

Our study contradicts the common assumption that the

negative effect of landscape simplification on parasitism rates

is caused primarily by a lack of resources for parasitoids

(Bianchi, Booij & Tscharntke 2006; Tscharntke et al. 2008).

Although empirical evidence supporting this assumption at

the landscape scale is surprisingly scant, a few studies have

found parasitism rates to be positively related to the availabil-

ity of some habitats in the landscape, such as forest edges or

grasslands, which are known to provide resources for certain

parasitoids (Bianchi et al. 2005; Bianchi, Goedhart & Baveco

2008; and see meta-analysis by Chaplin-Kramer et al. 2011).

It is likely that the relative importance of resource availability

and land-use intensity at the landscape scale depends on the

biological characteristics of the species and landscapes stud-

ied. For example, the availability of a high diversity of habitat

types that provide complementary resources to different

parasitoid species might be more important when high overall

parasitism rates are caused by the combined effects of a high

diversity of parasitoids (Tscharntke et al. 2008). In our study,

only a few species of parasitoids contributed to parasitism,

which might help explain the low importance of habitat diver-

sity and resource availability for parasitism. Exotic parasitoid

species may also be more strongly associated with crop land

than native species, and the fact that all species included in

this study are exotic to New Zealand (Berry, Cameron &

Walker 2000) could also have contributed to the importance

of annual crop cover and land-use intensity. Furthermore,

annual crop cover might have a particularly strong impact on

host–parasitoid interactions when it is positively related to

the frequency of pesticide application and other types of dis-

6 M. Jonsson et al.

� 2012 The Authors. Journal of Applied Ecology � 2012 British Ecological Society, Journal of Applied Ecology

turbance. Naturally, different types of annual crops are grown

under differing intensities of agrochemical inputs and distur-

bance frequencies in different agricultural systems. In our

study, insecticides were more frequently applied to crops

located in landscapes with high annual crop cover. This is in

agreement with a recent study from the mid-western USA

(Meehan et al. 2011), but contrasts with European studies

that found no such relationship (Roschewitz, Thies &

Tscharntke 2005; Herzog et al. 2006).

We were able to discriminate between the mechanistic driv-

ers of landscape effects (i.e. components of land-use intensity

and resource availability) on host–parasitoid interactions

because our comparative analysis was conducted in a system

where (i) habitat diversity and annual crop cover were uncorre-

lated and (ii) land-use intensity (habitat disturbance and insec-

ticide application) and resource availability (crucifer hosts and

floral resources) were largely independent. However, it is

important to acknowledge that most agricultural landscapes

typically exhibit strong collinearity among the potential drivers

of landscape effects. For example, low-intensity organic farms

often have higher levels of crop diversity and a higher propor-

tion of fallow or set-aside land compared to conventional

farms, and organic farms are often located in complex land-

scapes with a relatively high proportion of semi-natural

habitats (Norton et al. 2009). This could lead to a significant

negative relationship both between annual crop cover and

habitat type diversity, and between land-use intensity and

resource availability in the landscape. The SEM approach we

used here would not, in itself, provide the ability to overcome

this type of strong collinearity among predictor variables,

unless it was also possible to test casual inference with experi-

mental manipulation at the landscape scale (e.g. experimental

modification of pesticide application, tillage frequency, floral

resource availability). Nevertheless, the magnitude of collin-

earity could at least be estimated as a means of determining

whether apparent correlations between parasitism rates and

resource distributions (for example) might actually be con-

founded by covariance in some other factor such as the distri-

bution of insecticide use. These effects were not evident in our

study, perhaps because there were no organic farms present

within our study landscapes and no tendency for farmers in

structurally complex landscapes to use lower intensity farming

practices. Habitat disturbance and insecticide application

effects associated with annual cropping do, then, appear to

drive variation in host–parasitoid interactions in our study sys-

tem, rather than resource availability for parasitoids. We

acknowledge that causal inference on the relative importance

of different mechanistic pathways of landscape effects requires

experimental validation, as there is always the possibility that

apparent correlative relationships in SEM analyses can be

determined by hidden extrinsic drivers that we are not aware

of. In our models, any such effects (if they existed) would have

to be almost completely collinear with measured variables that

were entered into the model, as the only unidentified pathway

of landscape effects on parasitism rates was a weak (non-signif-

icant) direct effect from annual crop cover to parasitism rate in

the aphid parasitismmodel.

EFFECTS ON DIFFERENT TROPHIC LEVELS

We found that both primary parasitism rates and hyperparasit-

ism rates of aphids decreasedwith increasing annual crop cover

in the landscape. This suggests that primary parasitoids are

more sensitive to agricultural expansion than their herbivore

hosts, and in turn hyperparasitoids are more sensitive than pri-

maryparasitoids.Weareawareof twoother studies that investi-

gated landscape effects on fourth trophic-level processes in

agroecosystems and both found that hyperparasitism rates

decreasedwith increasing cover of annual crops and decreasing

landscape complexity (Gagic et al. 2011; Rand, van Veen &

Tscharntke 2012). Thus, previous work suggests that the nega-

tive effects of agricultural expansion on primary parasitoids

maybe somewhat ameliorated by the even larger effect it has on

hyperparasitoids. Our results also support the theoretical pre-

diction thathigher trophic levels shouldbe increasingly sensitive

to thedisturbancesassociatedwith land-usechange (Post 2002).

Todate, empirical evidence for this theory, in general terms, has

been relatively weak (Post 2002), although it has been shown

that primary parasitism rates may decrease with increasing

intensityofgrazing (Kruess&Tscharntke2002)andparasitoids

are sensitive tobroad-spectruminsecticides (Croft1990).

The observed effects of annual crop cover and land-use

intensity on host–parasitoid interactions were not an artefact

of density-dependent responses to variation in host density

(Costamagna, Menalled & Landis 2004). There was no signifi-

cant relationship between host density and parasitism rate in

any of the host-parasitoid systems studied (Fig. 1b–d). At the

same time, though, this lack of a relationship provides no evi-

dence that higher parasitism rates in less intensively managed

landscapes would lead to increased pest suppression (Thies &

Tscharntke 1999), as has also been found in a meta-analysis of

natural enemy responses to landscape complexity (Chaplin-

Kramer et al. 2011). Parasitism rates of aphids were probably

too low (0–31%) to have a significant effect on aphid densities,

but for P. xylostella parasitism rates were much higher (30–

100%) and this is likely to influence P. xylostella densities in

subsequent generations (P. xylostella has multiple generations

per year inNewZealand).

The only path including herbivore density that was retained

in any of the SEMmodels comprised a negative direct effect of

habitat diversity on aphid density. However, the mechanism

driving this relationship is unclear. In this case, there was no

direct relationship between parasitism rate and aphid density,

so the lower aphid density in more diverse landscapes could

not be attributed to increased parasitism. Aphid density was

also unrelated to host-plant density, of either cultivated brassi-

cas (there was no effect of annual crop cover, which was

comprised on average of ca 80% brassica crops) or alternative

crucifer hosts (the effect of habitat diversity was not mediated

by cover of alternative crucifer hosts; Fig. 1c).

Conclusions

Studies considering the implications of land-use intensifica-

tion on biodiversity and ecosystem services have mostly

Land-use intensity decreases parasitism rates 7

� 2012 The Authors. Journal of Applied Ecology � 2012 British Ecological Society, Journal of Applied Ecology

focussed on the local effects of this process (e.g. Holzschuh

et al. 2007; Krauss, Gallenberger & Steffan-Dewenter 2011).

However, it has recently been shown that the proportion of

organic farming in the landscape may have significant

effects on biodiversity (Gabriel et al. 2010) and that the spe-

cies richness of certain taxa are negatively affected by vari-

ables such as the percentage of intensively fertilized land

(Billeter et al. 2008). This suggests that land-use intensity at

the landscape level may also be an important determinant

of biodiversity loss and reduction in ecosystem services on

farmland. In our work, we show that reduction in distur-

bance and insecticide applications associated with lower lev-

els of intensive land use can explain why complex

landscapes often have higher natural enemy abundance and

enhanced biological control. While we recognize that the

relative importance of different drivers of landscape effects

probably depends on multiple factors, including landscape

structure and the identity of the species involved, we argue

that land-use intensity has been underestimated as a driver

of landscape effects on ecosystem services. Until we improve

our understanding of the conditions under which different

drivers of landscape effects operate, we suggest that farming

practices that decrease the extent and frequency of agro-

chemical inputs and disturbances should be given equivalent

weight to practices that increase habitat diversity in the

landscape, if we are to maintain natural pest control services

in agroecosystems.

Acknowledgements

We thank the 30 landowners who gave permission to work on their farms.

A. Dumbleton of PGG Wrightson Ltd provided invaluable information on

brassica cropping in Canterbury. I.H. Lynn and J. Barringer at Landcare

Research assisted with vegetation classification. S. Blyth, N. Jørgensen, J.Mar-

tin, M. Mackintosh, R. Neumegen, S. Orre, S. Sam and N. White assisted with

field and laboratory work. Financial support was provided by theTertiary Edu-

cation Commission through the Bio-Protection Research Centre at Lincoln

University. M. Jonsson also acknowledges support from a grant from the

Swedish Research Council for Environment, Agricultural Sciences and Spatial

Planning (FORMAS) to the project: Multifunctional Agriculture: Harnessing

Biodiversity for Sustaining Agricultural Production and Ecosystem Services

(SAPES). F. Bianchi, D. Crowder, B. Ekbom, R.M. Ewers, A.-K. Kuusk,

O. Lundin, T.A. Rand,W.E. Snyder, J. Stenberg, J.M. Tylianakis, C.Winqvist,

two anonymous reviewers and associate editor provided valuable comments on

previous versions of this manuscript.

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Received 20 June 2011; accepted 14March 2012

Handling Editor: Yann Clough

Supporting Information

Additional Supporting Information may be found in the online ver-

sion of this article.

Fig. S1. Map of New Zealand and the Canterbury region with the

locations of the 30 study fields indicated with black circles.

Fig. S2. Examples of land-use maps of landscape sectors (500-m

radius around study transect) with high and low habitat type

diversity.

Fig. S3. Examples of land-use maps of landscape sectors (500-m

radius around study transect) with high and low annual crop cover.

Table S1. Summary statistics for landscape composition in circular

landscapes with a 500-m radius around the centre of each study area.

Table S2. Summary statistics averaged across the 30 sites for proxi-

mate variables potentially explaining landscape effects.

Table S3. The estimated level of disturbance (k-value) used for differ-

ent land-cover classes when calculating the habitat disturbance index.

Table S4. Standardized path coefficients from the structural equation

models in Fig. 1, showing the direct effects, indirect effects and total

effects of factors influencing parasitism.

Table S5. Standardized path coefficients of ‘maximal’ structural equa-

tion models for each response variable (carried out as a sensitivity

analysis to test the robustness of causal hypotheses in the primary

SEM models), showing the direct effects, indirect effects and total

effects of factors influencing parasitism.

Table S6. Confirmatory generalized linear mixed model (GLMM)

analyses testing the relative influence of ultimate and proximate fac-

tors affecting parasitism.

Table S7. Coefficients for the best-fit ultimate-driver and proximate-

driverGLMMmodels for parasitism rates.

Appendix S1. Selection of field sites and quantification of land-use

patterns.

Appendix S2.Resources for parasitoids.

Appendix S3. Sensitivity analysis for the index of habitat disturbance.

Appendix S4. Sensitivity analysis for structural equationmodels.

Appendix S5.Confirmatory linearmodel analyses.

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Land-use intensity decreases parasitism rates 9

� 2012 The Authors. Journal of Applied Ecology � 2012 British Ecological Society, Journal of Applied Ecology