Farm-scale spatiotemporal dynamics of predatory beetles in arable crops

Journal of Applied Ecology

2005

42

, 1140–1152

© 2005 British Ecological Society

Blackwell Publishing, Ltd.

Farm-scale spatiotemporal dynamics of predatory beetles in arable crops

J. M. HOLLAND,*† C. F. G. THOMAS,† T. BIRKETT,* S. SOUTHWAY* and H. OATEN*

*

The Game Conservancy Trust, Fordingbridge, Hants SP6 1EF, UK; and

†

Seale-Hayne Agricultural Ecology Group, School of Biological Sciences, University of Plymouth, Seale-Hayne, Newton Abbot, Devon TQ12 6NQ, UK

Summary

1.

The spatial dynamics of farmland invertebrates can provide essential informationrelevant to their management for pest control and biodiversity conservation in sustainableagriculture. Carabid beetles are one of the most important groups contributing tobiological control in arable fields. Previous studies have focused on spatial dynamicswithin single fields and years. In this study we examined their larger scale, long-termdynamics, thereby taking into account the impact of changes in crop rotation and theinfluence of field size.

2.

The spatial distributions of four beetle species were investigated at an unprecedentedspatial scale in a grid of 973 pitfall trap locations across six fields encompassing 64 haof arable land. Week-long trapping was conducted four times in the first year and twicein the two following years.

3.

All species showed strong aggregation but the size and location of patches differedamong species. The distribution of

Pterostichus melanarius

was stable within andbetween years, with a single large patch close to the field boundaries. Patches of

Poeciluscupreus

were also located close to field boundaries but their location changed betweenyears.

Pterostichus madidus

and

Philonthus cognatus

distributions extended across fieldboundaries and were less stable, with patch locations changing between years.

4.

Synthesis and applications

. The spatial extent of a population patch for a givenspecies was species-specific. Species overwintering in field boundaries remained inproximity to these throughout the summer, whereas patches of mid-field overwinteringspecies were more extensive. Patches were generally stable within years but varied for somespecies between years. Species therefore differ in their response to crop managementpractices and consequently blanket management approaches for these importantgeneralist predators of crop pests are inappropriate. For spatially stable species (e.g.


) it may be possible to determine their specific habitat requirementsand to devise predictive and protective measures to preserve populations or manipulatethem at the farm-scale. More mobile species may be better at responding to pest aggre-gations at the farm-scale. However, operations that deplete populations, e.g. soil cultiva-tions, should be spatially and temporally desynchronized at the farm-scale toconserve populations and enable functional biocontrol.

Key-words

: Coleoptera, metapopulation,

Philonthus cognatus

,

Poecilus cupreus

,


,


, SADIE, spatial dynamics


(2005)

42

, 1140–1152doi: 10.1111/j.1365-2664.2005.01083.x

Introduction

Invertebrates, especially insects, perform importantroles in agriculture as pests, natural agents of pestcontrol, elements of food chains, major contributorsto biodiversity and general indicators of ecosystem

†Correspondence: Dr J. M. Holland, The Game ConservancyTrust, Fordingbridge, Hants SP6 1EF, UK (fax +441425 651026; e-mail [email protected]).

1141

Spatiotemporal dynamics of predatory beetles

© 2005 British Ecological Society,


,

42

, 1140–1152

health. The implementation of crop production methodsthat incorporate integrated pest management and otherconcessions to conserve biodiversity remains a centralchallenge for sustainable agriculture. The progressivedevelopment and application of practical techniquesfor managing insect populations depends on detailedknowledge of the basic ecology of individual species.This information, however, is relatively scant for eventhe most common species of interest in agriculturalhabitats. With the notable exception of a few long-termor large-scale studies (den Boer 1977; Aebischer 1991),most published work has been acquired in small-scale,short-term field and laboratory studies.

As theory advances it is increasingly recognized thatlarge-scale spatial processes are of key importance inthe ecology of invertebrates in agricultural habitats.Agricultural landscapes are now seen as, and have beenmodelled as, complex shifting mosaics of habitatpatches in which a metapopulation (Levins 1969) ofinsects may be structured from a series of local popu-lations, each predominantly confined to an individualfield and subject to the range of agricultural operationsthat happen within it (Sawyer & Haynes 1985). Fornon-flying epigeal insects, dispersal between localpopulations that maintains the metapopulation isdependent on field boundary permeability, and hasbeen shown to have a theoretical optimum dependingon the frequency and intensity of pesticide use on thefarm (Sherratt & Jepson 1993).

However, the paradigm of metapopulations fragmentedinto local populations within fields remains attached tothe notion that the field is the key spatial unit, and itsmanagement the most important factor influencingpopulation persistence. Consequently most studies offarmland invertebrates have focused on single fields. Inreality, however, the field is a more or less arbitraryhuman-made unit superimposed on a natural topography,geology and hydrology from which important factorssuch as soil type, structure and drainage are derived.The natural bounds of an insect local population infarmland therefore may not necessarily be relatedonly to the fragmentation of land by field boundaries.Although some field boundaries may be formedfrom natural features, they are mainly formed fromother managed non-crop habitats such as hedgerows,fence lines and uncultivated strips of grassland and,occasionally, small plots of woodland or shelter-belt.The permeability of each boundary type separatingadjacent fields is likely to be characteristic in itseffect on the spatial dynamics of a given species and itsmetapopulation structure. Furthermore, barriers todispersal between fields can affect gene flow (Frankham1995), slow down re-invasion following adverseagricultural operations (Sherratt & Jepson 1993) andretard biological control where an ability to track pestinfestations improves the chances of success (Murdoch& Briggs 1996).

Boundary habitats may also have positive roles, forexample as stable habitats that are seasonally essential

for aestivation or overwintering by some species (Sotherton1984). Recolonization of the annually disturbed croppedareas follows when conditions become more suitable(Wissinger 1997). For species that only or predominantlyinhabit boundary habitats, these features may act ascorridors to movement and dispersal between non-agricultural areas. Non-crop habitats also fragmentlandscapes and understanding the ecology of theseprocesses is critical if policies are to be based uponsound science and good management practices (Hunter2002; Chackoff & Aizen 2005; Schweiger

et al

. 2005).Quantifying the spatial distribution of an insect

population and its relationship or otherwise withnatural environmental factors, human-made featuressuch as field units and field boundaries can reveal muchecological information of potential use to the manage-ment of the species. Traditional studies have quantifieddifferences by taking a few random samples fromrespective habitats or treatments under comparison.However, these types of study are devoid of informativespatial data on the extent of species population dis-tributions and associations with, often continuouslyvarying, environmental factors.

Little is known about the temporal stability ofspatial pattern (Hunter 2002), especially in agriculturalhabitats where disturbance and habitat type areconstantly changing. However, the spatiotemporaldynamics of epigeal insect distributions have beenexamined recently using extensive and frequently sam-pled grids of traps in parts of fields, whole single fieldsor pairs of neighbouring fields, sometimes in conjunctionwith sampling other abiotic and biotic factors (Ericson1978; Hengeveld 1979; Thomas, Parkinson & Marshall1998; Holland, Perry & Winder 1999; Bohan

et al

.2000; Brown 2000; Fernández-García, Griffiths &Thomas 2000; Thomas

et al

. 2001; Holland

et al

.2004b; Pearce & Zalucki 2005). Most of these studieshave been conducted in cereal crops and focusedon Carabidae, one of the most important groups offarmland invertebrates, captured by pitfall trapping.At the spatial scales examined so far it has been shownthat adult stages of carabids exhibit discrete anddistinct spatial distributions. In some cases, patches ofhigh population density have been shown to be quitespatially stable within years, with patches extendingto several hectares. However, the true extent of popu-lation patches, and how non-crop habitats and theirdistribution in fragmented farmland affect the spatialdynamics of beneficial insects at scales beyond that ofthe field, have always been limited by the extent of thesampled area. Moreover, the stability of spatial dis-tributions between years has not been investigated,although there is evidence that invertebrate numbersfluctuate within the same fields between years (Thomas,Holland & Brown 2002). In agricultural habitats sub-stantial changes occur each year as a consequence ofcrop rotations, harvest and soil cultivations that mayimpact on invertebrate survival, leading to the creationof spatial pattern at farm level and beyond.

1142

J. M. Holland

et al.



,

42

, 1140–1152

This paper reports findings from the 3D FarmingProject, which began in 2000 with the overall aims ofinvestigating ways to increase biodiversity on farmlandand manipulating beneficial insects to provide moreeffective aphid control. One of the main componentsinvestigated the spatial–temporal dynamics of predatoryinsects in terms of the distribution, density and dispersal(3D) of populations, and aimed to extend earlier workto a spatial scale approaching that of a whole farm.Using an extensive grid of traps the study yieldedpopulation (activity–density) data in two spatialdimensions across a large area of a single farm. Three-dimensional (3-D) contour plots of population activity–density enabled us to address questions concerningthe spatial distribution and temporal stability ofpopulations and how they might be influenced by fieldboundaries and other factors. This approach allowedus to verify questions with respect to metapopulationtheory and derive information important for thedevelopment of conservation biocontrol in arable crops.These included the following. To what extent and atwhat scale are epigeal insect distributions aggregatedacross a contiguous block of fields? How stable areaggregations within and between years? Do the fieldboundaries and cropping affect abundance and dis-tribution within and across fields?

Materials and methods

The study site in Dorset, UK, comprised a 64-ha block ofsix arable fields separated from each other by various fieldboundary structures (Fig. 1). The block was surroundedby arable crops, except on one side where there was per-manent pasture. There was a cereal–cereal–pea rotationover the 3 years of sampling. The soil was cultivated inthe autumn prior to drilling of winter wheat but forspring-sown cereal and peas the stubble of the previouscrop was retained through the winter and cultivationswere conducted in late winter. The majority of field

boundaries were hedges with a herbaceous–grass bank,although in many places the dominant plant specieswere

Bromus sterilis

L. and

Urtica dioica

L. A grid of973 sampling locations was established across the studysite, arranged in an offset grid pattern with 40-m spac-ing along the rows and 20-m spacing between rowswithin each field. The grid extended across the whole ofthe 64 ha, encompassing the entirety of three smallfields (S1–3) and half the area of each of three largefields (L1–3). Each sample location was surveyed andlocated using the UK Ordnance Survey national gridreference using a differential global positioning system(Trimble Geoexplorer 3, Trimble Navigation Ltd,Sunnyvale, California, USA). At each sampling loca-tion two 6-cm diameter pitfall traps (half-filled with a50% solution of ethylene glycol and detergent) werepositioned 2 m apart and the data pooled for analyses.

To examine the distribution of epigeal beetles acrossthe study area within the year, pitfall traps were openedfor 1 week on four occasions in 2000 (2–9 May, 6–13June, 28 June

−

5 July and 12–19 July). These data wasthen used to identify when beetle abundance anddiversity were highest, allowing optimization of thesampling strategy in the following years. Trapping wasconducted over two further periods in the succeedingyears: 4–11 June and 9–16 July 2001; 10–17 June and8–15 July 2002. The majority of the catch comprisedcarabid beetles (Coleoptera; Carabidae) and rove beetles(Coleoptera; Staphylinidae), which were identifiedto species. We present here the spatiotemporal dis-tributions of three of the most important, common andabundant Carabidae in agricultural habitats,

Pterostichusmadidus

Fbr.,


Ill. and

Poeciluscupreus

L., and one staphylinid species,

Philonthuscognatus

Steph. These species are all predatory andcontribute to biological control (Good & Giller 1991;Sunderland 2002); however, the dietary range of thelarger

Pterostichus

species is broader. Their biologydiffers to some extent, as described in Table 1.

Fig. 1. Study area and cropping each year.

1143

Spatiotemporal dynamics of predatory beetles



,

42

, 1140–1152

The spatial distribution of these beetles was analysedusing SADIE (Spatial Analysis by Distance IndicEs;Perry

et al

. 1999), termed ‘red–blue’ analysis, for eachsampling occasion. This calculates the degree of clus-tering in the form of (i) ‘patches’ of large counts, usingthe overall index

v

j

and its associated probability

P

i

, or(ii) ‘gaps’ of small counts, using the overall index

v

j

andits associated probability

P

j

(Perry

et al

. 1999). The nullhypothesis of spatial randomness is indicated if, for a

particular set, all of these indices have values aroundunity. A value of at least one index above unity suggestsspatial non-randomness of some form; large positivevalues indicate patchiness (

v

i

>

c

. 1·5) and largenegative values (

v

j

<

c

.

−

1·5) indicate membership of agap (Perry

et al

. 1999). Distribution data are presentedas two-dimensional contour maps of the cluster indiceswhere

v

i

> 1·5 and

v

j

<

−

1·5, drawn using the packageSurfer for Windows Version 6.04 (Golden Software Inc.,Golden, Colorado, USA). Analyses were conducted ondata from across the whole study area.

To test whether two data sets were spatially correlated,the correlation coefficient,

X

, between the clusteringindices of each set was calculated according to themethod described by Perry & Dixon (2002). Hence, ifthe indices of set one are denoted

z

i

1

, with mean

q

1

, andthose of set two

z

i

2

, with mean

q

2

, then a measure oflocal spatial association for position

i

is given by:

χ

i

=

n

(

z

i

1

−

q

1

)(

z

i

2

−

q

2

) / [

Σ

i

(

z

i

1

−

q

1

)

2

Σ

i

(

z

i

2

−

q

2

)

2

]

1/2

The overall spatial association is the mean of theselocal values,

X

=

Σ

i

χ

i

/

n

. The significance of

X

wastested against values

X

rand

from a randomization testthat included a Dutilleul (1993) adjustment procedureto provide a probability value,

P

D

. A positive correlationcoefficient indicates that the two data sets are associatedwith patches coinciding spatially. A negative coefficientshows that they are disassociated with patches occurringin different locations to each other. This approach wasused to test for association within years and betweenyears for each species and for between species on eachsampling occasion.

Results

During May 2000


was presentonly in low numbers (Fig. 2), with the catches almostentirely composed of overwintered adults havingemerged in the late spring. By 6 June, newly emergedadults (tenerals) of the next generation had started toappear in areas different from those where the overwin-tered adults had previously been captured (Fig. 3a–d).The distributions of beetles in these first two samplingoccasions were therefore significantly disassociated

Table 1. Key biological features of the four beetle species

SpeciesOverwintering stage and site

Breeding period

Environmental conditions

Method of dispersal

Pterostichus madidus Larvae, field (adult, boundary)* Autumn Hygrophilic, eurythermous Walking†Pterostichus melanarius Larvae, field (adult, boundary)* Autumn Hygrophilic, eurythermous Walking†Poecilus cupreus Adult, boundary and field* Spring Xerophilic, warm preferrent Walking†Philonthus cognatus Larvae, field Autumn Unknown Walking/flight

*Small proportion of the population survive through into following year.†Dimorphic, some individuals capable of flight.

Fig. 2. Mean clustering indices (left y-axis) showing level ofaggregation into patches of higher than average density (vj)and gaps of lower than average density (vj) and mean number(± 1 SE) per pair of pitfall traps (right y-axis) on each samplingoccasion for Pterostichus madidus, Pterostichus melanarius,Poecilus cupreus and Philonthus cognatus.

1144

J. M. Holland

et al.



,

42

, 1140–1152

(negative

X

) but were spatiotemporally stable (positive

X

) from 13 June until 19 July (Table 2). By 5 July(Fig. 3c) large numbers of tenerals were caught in threeof the pea fields, S2, L3 and S3. These patches persistedin the same location until 19 July (Fig. 3d). The SADIEred–blue analysis of


revealed thepresence of significant spatial structure on all sampledates and this increased between successive samplingoccasions, although the numbers captured started todecline on the last sampling occasion (Fig. 2). The largest

patches of Pterostichus madidus were found duringthe period 28 June−5 July within S3 (Fig. 3c), wherecomplete coverage occurred, in S2, where a patchcovered approximately 6 ha, and in L3, where patchescovered three-quarters of the sampled area. Additionalsmall patches were found within S1 and L2 on 19 July.

Fewer Pterostichus madidus were caught in thefollowing 2 years but their distribution was still stronglyaggregated (Fig. 2), although this declined from Juneto July in each year. In June 2001 a large patch of

Fig. 3. Spatial clustering for Pterostichus madidus across the study area for total beetles caught per pair of pitfall traps at eachlocation for (a) 2–9 May 2000; (b) 6–13 June 2000; (c) 28 June−5 July 2000; (d) 12–19 July 2000; (e) 4–11 June 2001; (f ) 9–16 July2001; (g) 10–17 June 2002; (h) 8–15 July 2002. Maps indicate clusters of relatively large counts (denser contour pattern ‘patches’,for which vi > 1·5) and small counts (lighter contour pattern ‘gaps’, for which vj < −1·5).

1145Spatiotemporal dynamics of predatory beetles

© 2005 British Ecological Society, Journal of Applied Ecology, 42, 1140–1152

Pterostichus madidus covered L3 and small patchesoccurred in all the other fields, but there were more inthe wheat fields (Fig. 3e). By July their location hadchanged, with the two largest patches occurring in L3(wheat) and L2 (peas) covering 15 ha, and parts ofL1 (peas) (Fig. 3f). The patches persisted in L2 and L3through 2002, covering 20 ha (Fig. 3g,h and Table 2).As the trapping grid covered only half of these fields,the patches may have extended further.

Fewer Pterostichus melanarius were captured thanPterostichus madidus, but the population size (activity–density) of the former reached its peak earlier in thesummer (Fig. 2). This species showed a much morerestricted distribution, with a 10-ha patch spreadingacross S1 and along one edge of S2 by June 2000(Fig. 4a,b). The patches were found in the samelocation on all subsequent sampling occasions (seeAppendix S1) and consequently had high spatiotemporalstability, even though the cropping changed (Table 2).The spatial statistics were highly significant on allsampling occasions.

Poecilus cupreus was the least numerous of the speciesbut showed strong evidence of spatial pattern in thefirst 2 years (Fig. 2). The distribution was similar to thatof Pterostichus melanarius during 2000 (Fig. 5a–d),with an 8-ha patch occurring along the edge of the threesmall pea fields, and these remained stable through theyear (Table 2). By June 2001 Poecilus cupreus had becomemore widespread although still remained in proximityto the field boundaries (Fig. 5e). By July 2001 smallpatches were found only in those fields growing peas,L1 and L2. In June 2002 there was no significant spatialpattern but some had formed by July, although thepatches were small (Fig. 5g) and there was only weakassociation with their location in 2001 (Table 2).

Philonthus cognatus numbers were lower in July com-pared with June each year (Fig. 2), indicating loss ofthe species from the monitored area either throughmortality or dispersal. The distribution of patches wasmore ephemeral than for the other species within 2000,

Table 2. Association indices comparing distribution of the insect species between sampling periods within years and betweenyears for June and July (***PD < 0·001 or > 0·999, **PD < 0·01 or > 0·99, *PD < 0·05 or > 0·975)



Poecilus cupreus

Philonthus cognatus

X PD X PD X PD X PD

Within years2–9 May 2000 −0·28 *** 0·57 *** 0·62 *** 0·56 ***6–13 June 2000 0·68 *** 0·88 *** 0·61 *** −0·0228 June−5 July 2000 0·83 *** 0·91 *** 0·47 *** 0·28 ***12–19 July 2000 −0·37 *** 0·52 *** 0·48 *** 0·14 **4–11 June 2001 0·25 *** 0·70 *** 0·48 *** −0·109–16 July 2001 0·72 *** 0·80 *** 0·07 0·02

Between yearsJune 2000–01 0·43 *** 0·75 *** 0·28 *** −0·44 ***June 2001–02 0·38 *** 0·77 *** 0·03 0·28 **July 2000–01 < 0·001 0·83 *** −0·18 ** 0·09July 2001–02 0·65 *** 0·77 *** 0·15 * 0·13 **

Fig. 4. Spatial clustering for Pterostichus melanarius for (a) 2–9 May 2000; (b) 6–13 June 2000. Notation as in Fig. 3.

1146J. M. Holland et al.


with considerable variation in the level of associationbetween sampling occasions (Table 2). Large patcheswere found in May 2000 covering the cereal fields L1(13 ha) and half of L2 (9 ha) (Fig. 6a). By 5 July thepatches were identified covering two of the pea fields,S1 (4 ha) and most (9 ha) of S2 (Fig. 6c), and on 19 Julywere in L1 and S2 (Fig. 6d). In June 2001 large patchescovered most of S1, S2 and L3, but by July these wererestricted to L1 (Fig. 6e,f). Patches occurred in L1, S1and S2 in June 2002, although these only persistedthrough to July in L1. The greatest change in distribu-tion occurred between 2000 and 2001, with disassociation

for the pattern in June and no significant associationfor July (Table 2).

The distribution of Poecilus cupreus was positivelyassociated with that of Philonthus cognatus andPterostichus melanarius on most sampling occasions(Table 3). The latter two species were associated witheach other on most sampling occasions, althoughduring 2001 and 2002 there was also dissociation.Pterostichus madidus showed no clear pattern of

Fig. 5. Spatial clustering for Poecilus cupreus for all sampling occasions. Notation as in Fig. 3.



association with Philonthus cognatus or Poecilus cupreusbut was disassociated with Pterostichus melanarius.

Discussion

The spatial scale, extent and duration of this studyexceeded all previous investigations of this type andallowed us to answer some key questions regarding thespatiotemporal dynamics of epigeal insects whiletesting for the existence of metapopulations. The four

epigeal beetles showed strong evidence of spatialpattern when examined across the contiguous blockof six fields. However, the patch size within each fieldand across the site varied among the species; forexample, the patches of Pterostichus melanarius coveredapproximately 10 ha whereas those of Pterostichusmadidus were interlinked, extending across severalfields, and covered 23 ha in July 2000. This is muchlarger than previously found for these species in arablefields (Thomas, Parkinson & Marshall 1998; Holland,Perry & Winder 1999; Brown 2000), reflecting the scaleof this compared with previous studies.

Fig. 6. Spatial clustering for Philonthus cognatus for all sampling occasions. Notation as in Fig. 3.



Although occasional individuals could occuranywhere in the grid, the main aggregations of differentspecies occupied different areas of the study site. Thishas been shown previously in smaller scale studiesof some of these species. Pterostichus melanarius andPoecilus cupreus were found to be spatially separated,occurring in different fields (Thomas et al. 2001;Winder et al. 2001) or in different parts of the same

field; Poecilus cupreus remained close to hedgerows,while the reverse was found for Pterostichus melanarius(Fournier & Loreau 1999; Winder et al. 2001). However,in a larger scale study patches of both species werefound at the edge and in the centre of fields (Brown2000). A number of putative mechanisms may causethis spatial differentiation, including preferences amongspecies for slightly different environmental conditions;active avoidance among congenerics; competitiveexclusion; mutual predation; differential effects ofhistorical and current management within fields; orthose abiotic and biotic factors influenced by suchmanagement, especially prey availability and soilmoisture (Thiele 1977; Irmler 2003). Most probably acombination of positive and negative mechanisms willdrive the spatial dynamics (Thomas, Holland & Brown2002). Moreover, the apparent drivers may changeaccording to the spatial resolution of the study. At thesubfield level, crop cover determined the spatial patternof Carabidae (Greenslade 1964; Best et al. 1981). Atthe field scale, soil moisture, prey abundance, croptype and weed cover were correlated with their spatialdistribution (Hengeveld 1979; Holland, Perry & Winder1999; Bohan et al. 2000; Winder et al. 2001; Thomas,Holland & Brown 2002). When distributions across thelandscape were considered, moisture gradients, soil type,soil pH and field size were important (Judas & Schaefer2002), as was connectivity of semi-natural elements(Schweiger et al. 2005). The scale, intensity and fre-quency of sampling may therefore determine whetherrelationships to factors responsible for spatial patternare detected. Some adjustment may also be necessaryaccording to the hypothesis being tested and the likelydynamics of any distribution. For most carabids a 30-mgrid spacing was judged sufficient (Holland, Perry &Winder 1999), although for larger carabids thataggregate in larger patches this spacing can be increased,as in this study (Pearce & Zalucki 2005).

The four species exhibited stable distribution pat-terns within each year, with patches and gaps generallyremaining in the same parts of the study area. Thiscorroborates the findings of most other studies ofwithin-year distributions (Thomas, Parkinson &Marshall 1998; Holland, Perry & Winder 1999; Fernández-García, Griffiths & Thomas 2000; Thomas et al. 2001).However, in other studies using grids smaller than asingle field, Pterostichus melanarius has been shownto be more mobile within the year, moving in responseto the distribution of slugs (Bohan et al. 2000) oraphids (Winder et al. 2001). Redistribution of carabidsfrom June to August was likewise found using agrid-sampling approach that encompassed two pairs offields (Brown 2000; Thomas, Holland & Brown 2002).In that case captures increased in a bean and declinedin a wheat crop during July and August. The temporalvariation in species distributions between June andJuly found in this study may be explained by differencesin the numbers of adult overwinterers and emergingtenerals dominating the catch. For example, in June

Table 3. Association indices comparing the distribution of thefour insect species on each sampling occasion (***PD < 0·001or > 0·999, **PD < 0·01 or > 0·99, *PD < 0·05 or > 0·975)

Philonthus cognatus

Poecilus cupreus


2–9 May 2000Poecilus cupreus −0·03Pterostichus madidus

0·35*** −0·02


0·31*** 0·41*** 0·17*

6–13 June 2000Poecilus cupreus

0·16*


−0·31*** 0·31***


0·38*** 0·65*** 0·11

28 June−5 July 2000Poecilus cupreus 0·42***Pterostichus madidus

0·36*** 0·53***


0·32** 0·51*** 0·15

12–19 July 20/00Poecilus cupreus 0·13*Pterostichus madidus

0·03 0·38***


0·31*** 0·53*** 0·10

4–11 June 2001Poecilus cupreus −0·34***Pterostichus madidus

0·53*** −0·35***


0·07 0·30*** −0·17**

9–16 July 2001Poecilus cupreus 0·37 ***Pterostichus madidus

0·22 *** −0·08


−0·07 0·19 ** −0·53 ***

10–17 June 2002Poecilus cupreus 0·28***Pterostichus madidus

−0·43*** −0·09


0·47*** 0·16* −0·59***

8–15 July 2002Poecilus cupreus 0·16**Pterostichus madidus

0·27*** 0·22*


−0·20** −0·0739 −0·60***



Pterostichus madidus was more abundant in wheat thanpeas but the reverse was found in July. In June theadults that had survived the winter dominated thecatch, whereas by July most of the beetles caught weretenerals. This may also have held true for Philonthuscognatus.

In contrast to the spatial stability of distributionswithin a year, the location of patches between yearsvaried among the four species. Distributions maychange either as a consequence of differences insurvival between locations or because of movement.Patches of Pterostichus melanarius remained inproximity to field boundaries in the smaller fields overthe 3 years and mark–release–recapture studies con-ducted within the same fields confirmed that there waslittle movement outside these areas (Holland et al.2004a). In contrast, patches of Poecilus cupreus changedbetween years even though this species also utilizes fieldboundaries as overwintering and summer foragingsites. Instead, they appeared to follow the pea crops inrotation. In 2002 Poecilus cupreus virtually disappearedwhen no peas were grown, suggesting that conditionsdirectly related to the crop type were driving the dis-tribution of this species.

The distribution of Pterostichus madidus was stablebetween years when the June data were compared butwas unstable for July. This may occur if the same areaswere used for overwintering each year, with the emergentbeetles then dispersing. This species was found to bemore dispersive than Pterostichus melanarius and wascapable of crossing field boundaries (Holland et al.2004a). Philonthus cognatus had a more ephemeraldistribution within years compared with the carabidspecies. Although this species also overwinters withinfields as larvae and is susceptible to intensive soilcultivations (Andersen 1999), it is highly dispersive, likemost Staphylinidae, and will readily fly (Bohac 1999).Thus emergence within one area followed by dispersalmay explain the distribution patterns found here.

Crop rotations and the associated husbandry cause thegreatest disruptions in farmland and affect insectsthrough their impact on: the type and timing ofcultivations; extent and timing of vegetation cover;abundance of prey; environmental conditions; agro-chemical inputs and time of harvest (Kromp 1999;Holland & Luff 2000; Thorbek & Bilde 2004). Of thespecies studied here only Poecilus cupreus was linked toa particular crop. Evidence on the impact of crop typeis contradictory for many species, in part because of theinadequacies of experimental design but also becausedifferent species may favour particular crops accordingto their respective phenologies, environmental require-ments and diet. Such preferences ultimately affectspecies’ composition and dominance ratios (reviewedfor Carabidae by Hance 2002).

Non-crop habitats have been identified as beingimportant refuges and overwintering habitats for alarge number of carabid species (Lee & Landis 2002).However, these field boundary features can also act asbarriers to dispersal, especially for those species thatpredominantly inhabit field centres, thus affecting theirspatial dynamics at the farm scale. In the present study,population patches of three species (Pterostichus madidus,Poecilus cupreus and Philonthus cognatus) spanned fieldboundaries, whereas those of Pterostichus melanarius wereconfined by the boundaries. Mark–release–recapturestudies confirmed that the movement of Pterostichusmelanarius was much more restricted than that ofPterostichus madidus (Holland et al. 2004a) and the fieldboundaries may have been restricting movement, asfound in previous studies of Pterostichus melanarius andPoecilus cupreus (Thomas, Parkinson & Marshall 1998).However, there may simply have been no incentive todisperse. Pterostichus madidus had a more fragmentedspatial pattern and, although a small proportion of markedindividuals traversed field boundaries (Holland et al.2004a), therefore movement was not considered to bethe primary mechanism; instead factors determiningsurvival were more likely to be responsible. Theobstruction posed by different field boundary types is,however, likely to differ for each species (Duelli et al.1990). In farmland landscapes where fields are dividedby linear boundary features, the survival of metapopu-lations and their constituent local populations cantheoretically depend upon the ability of species tore-invade fields following catastrophic disturbancescausing population crashes, which, within intensivelyfarmed fields, can occur relatively frequently. Barriers todispersal can also restrict opportunities for gene flowbetween local populations (Frankham 1995) and mayinfluence fitness (Reed & Frankham 2003), althoughonly a few dispersers are necessary for significant geneflow and all fields have gateway access for machinerythrough which beetles can also pass.

The findings presented here and in the associatedstudy (Holland et al. 2004a) therefore suggest that thepatches of these large Carabidae found within eachfield are isolated to a large extent from each other bythe field boundaries. Studies conducted in morehomogeneous forest habitats, where there is lessdisturbance and fewer barriers to dispersal, revealedthat patches of Pterostichus madidus and Pterostichusmelanarius extended to 1·2 km2 (Judas, Dornieden &Strothmann 2002). Thus in farmland the impact ofcatastrophic disturbances is likely to be severe andlong-term unless sufficient individuals survive in thesurrounding non-crop habitats or are protected withinthe field to repopulate the field. Moreover, the rate ofrecolonization is likely to be positively correlated withthe scale of the disturbance. In contrast, the moremobile species, such as Philonthus cognatus, may be



better suited to the unstable conditions that occur inarable fields. Further investigations of recolonizationare needed to identify the impact of farming practiceson invertebrate distributions.

The extent to which the distribution patternsdetected here could be extrapolated across thelandscape needs further investigation before we candetermine at what scale metapopulations of beetlesexist in farmed landscapes. The detection of stable localpatches extending across several fields supports thetheory that metapopulations exist in farmland. How-ever, some species were found to be quite ephemeralin their location across the study area and local popu-lations may exist at much larger scales (e.g. Philonthuscognatus). Moreover, because of the annual fluctuationsin abundance, studies based upon a single year of datamay not reflect the true extent of a species’ distributionand should be treated with caution. This was evidentwhen insect abundance across a 64-km2 block ofarable farmland was measured annually for 30 years(Holland 2002). Landscape-scale investigations there-fore need to take temporal changes into consideration.Regional distributions have been described (Luff1998), and geographical position, local soil and cropconditions and year were the most influential factors(Luff 2002).

The species studied here are known to feed on croppests but the fluctuations in their spatial dynamics indicatethat the level of biocontrol offered by each species maybe expected to vary within each field between years(Pearce & Zalucki 2005). This may not be importantprovided the total level of biocontrol remains un-affected. However, when the total number of predatoryinvertebrates across the study area was mapped therewere similar fluctuations across the study area becausethe pattern detected reflected that of the dominantspecies, Pterostichus madidus (Holland et al. 2003). Thereis other evidence that beetle diversity has declinedon farmland, with dominance by a few species (Croy1987). Conservation biocontrol should therefore aimto encourage diversity as this will ensure that speciesare foraging for a greater proportion of the year andwill be better able to withstand the impact of adversefarming operations. Farmland diversity may be achievedthrough manipulation of the non-crop areas that areutilized for overwintering and as a foraging resource inthe summer. Reducing field size and thereby improvingthe boundary–field ratio is one approach; however, thismay restrict the movement of epigeal invertebrates andrestrict re-invasion after catastrophic events. Beetleabundance also varied considerably between years as aconsequence of cropping, indicating that implementinga heterogeneous approach to crop distribution at farmand landscape scales would encourage biocontrolthrough the desynchronization of adverse husbandrypractices. Conservation biocontrol should also aim toencourage the more mobile species that are better ableto respond to the ephemeral environmental conditionsand pest infestations that occur in arable fields. These

approaches are also compatible with conservationstrategies aimed at encouraging farmland biodiversityper se, and with recent changes to the CommonAgricultural Policy and the widespread availability ofagri-environment payments (Ormerod et al. 2003) theyare more acceptable and achievable on farm.

Acknowledgements

The study was conducted as part of the 3D FarmingProject, which was funded under the SustainableArable LINK Programme by the Department of theEnvironment, Food and Rural Affairs and ScottishExecutive Environmental Rural Affairs Department,with additional financial support from Dow Agro-Sciences, Home-Grown Cereals Authority, HorticulturalDevelopment Council, Processors and Growers ResearchOrganization, Tesco, Unilever, The Game ConservancyTrust, The Chadacre Agricultural Trust, The DulvertonTrust, The Manydown Company, The WorshipfulCompany of Farmers and The Yorkshire AgriculturalSociety. Sincere thanks to all those that helped withthe study, especially Christina Reynolds, Sue Thomas,Barbara Smith, Sam Bishop, Vicky Carter andCatherine Holley. We gratefully thank Lord Cranbornefor permission to use Cranborne farm and the staff ofCranborne Estates.

References

Aebischer, N.J. (1991) Twenty years of monitoring invertebratesand weeds in cereal fields in Sussex. The Ecology of TemperateCereal Fields (eds L. G. Firbank, N. Carter, J. F. Darbyshire& G. R. Potts), pp. 305–331. Blackwell Scientific Publications,Oxford, UK.

Andersen, A. (1999) Plant protection in spring cereal productionwith reduced tillage. II. Pests and beneficial insects. CropProtection, 18, 651–657.

Best, R.L., Beegle, C.C., Owens, J.C. & Oritz, M. (1981)Population density, dispersion and dispersal estimatesfor Scarites substriatus, Pterostchichus chalcites andHarpalus pensylvanicus (Carabidae) in an Iowa cornfield.Environmental Entomology, 10, 847–856.

den Boer, P.J. (1977) Dispersal power and survival: carabids ina cultivated countryside. Miscellaneous Papers, Landbou-whogeschool Wageningen, The Netherlands. 14, 1–19.

Bohac, J. (1999) Staphylinid beetles as bioindicators.Agriculture, Ecosystems and Environment, 74, 357–372.

Bohan, D.A., Bohan, A.C., Glen, D.M., Symondson, W.O.,Wiltshire, C.W. & Hughes, L. (2000) Spatial dynamics ofpredation by carabid beetles on slugs. Journal of AnimalEcology, 69, 367–379.

Brown, N.J. (2000) Carabid ecology in organic and conven-tional farming systems: population density, diversity and highresolution spatial dynamics. PhD Thesis. University ofBristol, Bristol, UK.

Chackoff, N. & Aizen, M. (2005) Edge effects on pollinatorassemblages in grapefruit plantations bordering prematuresubtropical forest. Journal of Applied Ecology, in press.

Croy, P. (1987) Faunisitsch-ökologische Untersuchungen derCarabidaen im Umfeld eines industriellen Ballungsgebeites.Entomologische Nachrichten und Berichte, 31, 1–9.

Duelli, P., Struder, M., Marchand, I. & Jakob, S. (1990)Population movements of arthropods between natural andcultivated areas. Biological Conservation, 54, 193 –207.



Dutilleul, P. (1993) Modifying the t-test for assessing thecorrelation between two spatial processes. Biometrics, 49,305–314.

Ericson, D. (1978) Distribution, activity and density of someCarabidae (Coleoptera) in winter wheat fields. Pedobiologia,18, 202–217.

Fernández-García, A.F., Griffiths, G.J.K. & Thomas, C.F.G.(2000) Density, distribution and dispersal of the carabidbeetle Nebria brevicollis in two adjacent cereal fields. Annalsof Applied Biology, 137, 89–97.

Fournier, E. & Loreau, M. (1999) Effects of newly plantedhedges on ground-beetle diversity (Coleoptera, Carabidae)in an agricultural landscape. Ecography, 22, 87–97.

Frankham, R. (1995) Conservation genetics. Annual Reviewof Genetics, 29, 305–327.

Good, J.A. & Giller, P.S. (1991) The diet of predatory staphyli-nid beetles: a review of records. Entomologist’s MonthlyMagazine, 127, 77–89.

Greenslade, P.J.M. (1964) The distribution, dispersal and sizeof a population of Nebria brevicollis (F.), with comparativestudies on three other Carabidae. Journal of Animal Ecology,33, 301–309.

Hance, T. (2002) Impact of cultivation and crop husbandrypractices. The Agroecology of Carabid Beetles (ed. J.M.Holland), pp. 231–250. Intercept, Andover, UK.

Hengeveld, R. (1979) The analysis of spatial patterns of someground beetles (Col. Carabidae). Spatial and TemporalAnalysis in Ecology (eds R.M. Cormack & J.K. Ord),pp. 333–346. International Co-operative Publishing House,Fairland, USA.

Holland, J.M. (2002) Carabid beetles: their ecology, survivaland use in agroecosystems. The Agroecology of CarabidBeetles (ed. J.M. Holland), pp. 1–40. Intercept, Andover,UK.

Holland, J.M. & Luff, M.L. (2000) The effects of agriculturalpractices on Carabidae in temperate agroecosystems.Integrated Pest Management Reviews, 5, 105–129.

Holland, J.M., Begbie, M., Birkett, T., Southway, S., Thomas,S.R., Alexander, C.J. & Thomas, C.F.G. (2004a) The spatialdynamics and movement of Pterostichus melanarius andP. madidus (Carabidae) between and within arable fields inthe UK. International Journal of Ecology and EnvironmentalSciences, 30, 35–50.

Holland, J.M., Birkett, T., Begbie, M., Southway, S. &Thomas, C.F.G. (2003) The spatial dynamics of predatoryarthropods and the importance of crop and adjacentmargin habitats. Landscape Management for FunctionalBiodiversity (eds W.A.H. Rossing, H.-M. Poehling &G. Burgio), pp. 65–70. Bulletin No. 26. IOBC/WPRS .

Holland, J.M., Perry, J.N. & Winder, L. (1999) The within-field spatial and temporal distribution of arthropods inwinter wheat. Bulletin of Entomological Research, 89,499–513.

Holland, J.M., Winder, L., Woolley, C., Alexander, C.J. &Perry, J.N. (2004b) The spatial dynamics of crop andground active predatory arthropods and their aphid preyin winter wheat. Bulletin of Entomological Research, 94,419–431.

Hunter, M.D. (2002) Landscape structure, habitat frag-mentation and forest entomology. Agricultural and ForestEntomology, 4, 159–166.

Irmler, U. (2003) The spatial and temporal pattern of carabidbeetles on arable fields in northern Germany (Schleswig-Holstein) and their value as ecological indicators. Agriculture,Ecosystems and Environment, 98, 141–151.

Judas, M. & Schaefer, M. (2002) Regionalization of macro-fauna populations. Spatial Modelling in Forest Ecologyand Management: A Case Study (eds M. Jansen, M. Judas& J. Saborowski), pp. 87–113. Springer-Verlag, Berlin,Germany.

Judas, M., Dornieden, K. & Strothmann, U. (2002) Distribution

patterns of carabid beetle species at the landscape-level.Journal of Biogeography, 29, 491–508.

Kromp, B. (1999) Carabid beetles in sustainable agriculture:a review on pest control efficacy, cultivation impactsand enhancement. Agriculture, Ecosystems and Environment,74, 187–228.

Lee, J.C. & Landis, D.A. (2002) Non-crop habitat manage-ment for carabid beetles. The Agroecology of Carabid Beetles(ed. J.M. Holland), pp. 279–304. Intercept, Andover, UK.

Levins, R. (1969) Some demographic and genetic con-sequences of environmental heterogeneity for biologicalcontrol. Bulletin of the Entomological Society of America,15, 237–240.

Luff, M.L. (1998) Provisional Atlas of the Ground Beetles(Coleoptera, Carabidae) of Britain. Biological RecordsCentre, Huntingdon, UK.

Luff, M.L. (2002) Carabid assemblage organization and spe-cies composition. The Agroecology of Carabid Beetles (ed.J.M. Holland), pp. 41–80. Intercept, Andover, UK.

Murdoch, W.W. & Briggs, C.J. (1996) Theory for biologicalcontrol: Recent developments. Ecology, 77, 2001–2013.

Ormerod, S.J., Marshall, E.J.P., Kerby, G. & Rushton, S.P.(2003) Meeting the ecological challenges of agriculturalchange: editors’ introduction. Journal of Applied Ecology,40, 939–946.

Pearce, S. & Zalucki, M. (2005) Do predators aggregate inresponse to pest density in agro-ecosystems: assessingwithin field spatial patterns. Journal of Applied Ecology, inpress.

Perry, J.N. & Dixon, P.M. (2002) A new method to measurespatial association for ecological count data. Ecoscience, 9,133–141.

Perry, J.N., Winder, L., Holland, J.M. & Alston, R.D. (1999)Red–blue plots for detecting clusters in count data. EcologyLetters, 2, 114–120.

Reed, D.H. & Frankham, R. (2003) Correlation betweenfitness and genetic diversity. Conservation Biology, 17, 230–237.

Sawyer, A.J. & Haynes, D.L. (1985) Spatial-analysis of cerealleaf beetle abundance in relation to regional habitat features.Environmental Entomology, 14, 92–99.

Schweiger, O. et al. (2005) Quantifying the impact of environ-mental factors on arthropod communities in agriculturallandscapes across organisational levels and spatial scales.Journal of Applied Ecology, in press.

Sherratt, T.N. & Jepson, P.C. (1993) A metapopulationapproach to modelling the long-term impact of pesticideson invertebrates. Journal of Applied Ecology, 30, 696–705.

Sotherton, N.W. (1984) The distribution and abundance ofpredatory arthropods overwintering on farmland. Annalsof Applied Biology, 105, 423–429.

Sunderland, K.D. (2002) Invertebrate pest control by carabids.The Agroecology of Carabid Beetles (ed. J. M. Holland),pp. 165–214. Intercept, Andover, UK.

Thiele, H.U. (1977) Carabid Beetles in Their Environments.Springer-Verlag, Berlin, Germany.

Thomas, C.F.G., Holland, J.M. & Brown, N.J. (2002) Thespatial distribution of carabid beetles in agriculturallandscapes. The Agroecology of Carabid Beetles (ed. J.M.Holland), pp. 305–344. Intercept, Andover, UK.

Thomas, C.F.G., Parkinson, L., Griffiths, G.J.K., Garcia, A.F.& Marshall, E.J.P. (2001) Aggregation and temporal sta-bility of carabid beetle distributions in field and hedgerowhabitats. Journal of Applied Ecology, 38, 100–116.

Thomas, C.F.G., Parkinson, L. & Marshall, E.J.P. (1998)Isolating the components of activity-density for the carabidbeetle Pterostichus melanarius in farmland. Oecologia, 116,103–112.

Thorbek, P. & Bilde, T. (2004) Reduced numbers of generalistarthropod predators after crop management. Journal ofApplied Ecology, 41, 526–538.



Winder, L., Alexander, C.J., Holland, J.M., Woolley, C. &Perry, J.N. (2001) Modelling the dynamic spatio-temporalresponse of predators to transient prey patches in the field.Ecology Letters, 4, 568–576.

Wissinger, S.A. (1997) Cyclic colonization in predictablyephemeral habitats: a template for biological control inannual crop systems. Biological Control, 10, 4–15.

Received 15 November 2004; final copy received 15 June 2005Editor: Paul Giller

Supplementary material

The following supplementary material is available forthis article online.

Fig. S1. Spatial clustering for Pterostichus melanariusacross the study area for total beetles caught per pair ofpitfall traps at each location on certain dates.

Farm-scale spatiotemporal dynamics of predatory beetles in arable crops

Documents

Transcript of Farm-scale spatiotemporal dynamics of predatory beetles in arable crops