Effect of Land Disturbance and Stress on Species Traits of Ground Beetle Assemblages

Ecology, 82(4), 2001, pp. 1112±1129 ᭧ 2001 by the Ecological Society of America

EFFECT OF LAND DISTURBANCE AND STRESS ON SPECIES TRAITS OF GROUND BEETLE ASSEMBLAGES

IGNACIO RIBERA,1,3 SYLVAIN DOLEÂ DEC,2 IAIN S. DOWNIE,1 AND GARTH N. FOSTER1 1Environment Division, Scottish Agricultural College, Auchincruive, Ayr KA6 5HW UK 2Ecologie des Eaux Douces et des Grands Fleuves, ESA CNRS 5023, UniversiteÂ Claude Bernard Lyon 1, BaÃt 401C, 69622 Villeurbanne CEDEX France

Abstract. In this paper we test whether the morphology and life traits of species (in our case ground beetles of the family Carabidae) can be related to the main underlying axes of environmental variability of their habitats. Sites were selected a priori to maximize two gradients: land use as a general measure of disturbance characterized by an index of land management, and habitat adversity or stress as characterized by elevation and vegetation structure. The underlying environmental axes and the relationships of the morphology and life traits of the species with them were investigated using RLQ analysis, a multivariate ordination method able to relate a species trait table to a site characteristics table by way of a species abundance table. The ®rst environmental axis was highly statistically signi®cant and explained most of the variability. It was strongly negatively related to the intensity of land management, and positively related to increasing elevation and a set of variables re¯ecting vegetation stress. Two predictions were tested and found to be valid in the studied system: in highly managed lowland sites species were smaller, and the frequency of macropterous species (with better dispersal abilities) was higher. Other traits also showed signi®cant relationships with the main environmental axis: in the intensively managed lowland sites species had broader bodies, longer trochanters, and wider femora (characters associated with plant eaters), were paler in color, overwintered only as adults, bred in spring or autumn, and were active in summer. We conclude that the ground beetle assemblages of the studied sites respond in a similar way to the same underlying environmental factors. This allows the precise de®nition of functional groups, which can be used to characterize functional diversity and its relationships with changes in land management. Key words: agricultural systems; body size; carabid beetles; disturbance; functional groups; habitat templet; land management; life traits; multivariate analysis; stress; three-table analysis.

INTRODUCTION teristic morphologies and life history strategies, being at the same time a ``®lter'' resulting in the ecological One of the objectives of predictive ecology is to sorting of the species able to occupy them. The in¯u- know whether species with certain traits will persist ence of habitat is epitomized in a small set of a priori under a de®ned set of environmental conditions (Rice de®ned axes that are hypothesized to summarize the et al. 1983, Janzen 1985, Southwood 1988, Keddy environmental constraints acting on the species. These 1992, Townsend and Hildrew 1994). This requires an axes are normally related to disturbance and adversity understanding of the relationships between the char- or stress (Southwood 1977, 1988); habitat predictabil- acteristics of the habitats in which species occur and ity and adversity (Greenslade 1983); or to temporal and their morphology and life traits. These relationships spatial heterogeneity, which can be taken as a measure are acknowledged to be complex, a mixture of the effect of disturbance and availability of refugia respectively of local ecological factors with the evolutionary history (e.g., Townsend and Hildrew 1994, see also Kor®atis of the species and the regional faunas (Southwood and Stamou 1999). An equivalent hypothesis for plants 1988, Rosenzweig 1995, Bennett 1997). One of the is that of Grime (1977), with ecological strategies (with attempts to construct such a predictive framework for their respective morphological adaptations) accom- the relationships between habitat and species charac- modating to stress, disturbance, and biological com- teristics is the habitat templet theory (Southwood 1977, petition (Grime 1977, Grime et al. 1997). 1988, Townsend and Hildrew 1994, Kor®atis and Sta- As noted above, the templet concept can be under- mou 1999). This theory assumes that the habitat pro- stood both as an evolutionary forge for shaping species vides the templet on which evolution forges charac- traits, and as an ecological process of species sorting. The occurrence of a species in a certain habitat is de- Manuscript received 28 August 1998; revised 1 February termined by the ®t between its traits and the charac- 2000; accepted 21 March 2000. 3 Present address: Department of Entomology, The Natural teristics of the habitat (an ecological process), but the History Museum, Cromwell Road, London SW7 5BD UK. presence of these traits in the species is the product of E-mail: [email protected] the evolutionary history of adaptation to conditions that 1112 April 2001 EFFECTS OF DISTURBANCE ON SPECIES TRAITS 1113 are supposed to be similar (an evolutionary process). acterization of the axes that maximize environmental In this paper we focus on the ecological scale, testing variability. In a similar way, the habitat used by the whether species in assemblages are sorted according species, and their response to the main environmental to their morphology and life traits. In other words, we factors, is de®ned through their actual occurrence in analyze what happens when an array of species, in the sampled sites, not a priori assigned through aut- which biological traits evolved in a different location, ecological knowledge. This is the ®rst application of arrive in a new habitat (Janzen 1985). this statistical method other than those given by Do- The sites included in this study have a recent history leÂdec et al. (1996). The method proposed by Legendre of human land use, with maximum potential ages of et al. (1997) uses in essence the same statistical ap- ϳ 10 000 yr (the time of the last deglaciation in Scot- proach to link the three matrices, but with a focus on land; Ballantyne and Harris 1994), although certainly a test of the global signi®cance of the relationships. much less for most of them, in particular those with RLQ is more centered on interpretation of the scores more intensive management. It can thus be safely as- of the environmental characteristics of the sites and the sumed that the species studied at these sites have not species traits in common ordination axes (see Methods evolved in situ but their presence is the result of mi- for a more detailed comparison of both methods). gration too recent for there to have been much local In addition to studying the general relationship be- evolution. A signi®cant relationship between species tween morphology and life traits of the species with traits and environmental characteristics will demon- environmental gradients, we speci®cally tested two strate the existence of processes acting on an ecological predictions according to Southwood (1977, 1988), scale in the con®guration of the species assemblages. Greenslade (1983), and Townsend and Hildrew (1994): We studied ground beetles of the family Carabidae (1) species in temporally stable (i.e., predictable), ad- to exemplify the ground-dwelling fauna. They are a verse, and spatially homogeneous environments have well-known group, strongly dependent on land char- on average larger body sizes; and (2) species in tem- acteristics, and with a long tradition of ecological study porally unstable, more favorable, and spatially hetero- (e.g., Thiele 1977, LoÈvei and Sunderland 1996, Nie- geneous environments have greater dispersal abilities. melaÈ 1996). Our study sites were chosen so as to max- In highly unpredictable and unstable habitats species imize two environmental gradients: habitat adversity need good dispersal abilities to move to more favorable or stress, as measured by elevation and vegetation patches when local conditions become unsuitable. If structure, and land management, as a surrogate measure the conditions, albeit ephemeral, are favorable, there of land disturbance. By measuring the response of will be a high turnover rate (i.e., a faster development ground beetle assemblages to disturbance and stress we with shorter generation time), with the result of a small- should be able to characterize species according to a er size of the species. On the contrary, in highly pre- set of functional traits. This functional characterization dictable but unfavorable sites species avoid dispersal, should ideally be based on the simultaneous study of which could only lead to loss of individuals (or to the common biological attributes and the correlation of introduction of undesirable variation, Greenslade these attributes with the main environmental factors 1983), and have a low turnover rate, resulting in an (Lavorel et al. 1999). The usual approach to this prob- increased size. lem is ®rst to apply some ordination method to the matrix of species presences (or abundances) and the MATERIALS AND METHODS environmental characteristics of the sites, and subse- Study area quently to try to relate the species traits with the ordination axes obtained (see e.g., papers in Statzner et Sites were chosen to best represent the diversity of al. 1994, 1997, and references therein). Species traits the Scottish landscape, following a general gradient are usually not included in the analysis because of the from intensive cereal ®elds to extensive upland grass- lack of statistical methods to relate them to the char- lands or moorland dominated by heather (Calluna vul- acteristics of the habitats (the ``fourth-corner'' problem garis), often managed by periodic burning. Land use described in Legendre et al. 1997). is strongly associated with several disturbance factors We used a recently described multivariate method, (e.g., removal of biomass by cropping or grazing, and which provides a general solution to this problem, RLQ soil disturbance by tillage). A set of measures of veg- analysis (DoleÂdec et al. 1996). RLQ analysis aims to etation structure commonly related with habitat adver- investigate the relationships between two tables (``R'' sity and stress was obtained (e.g., biomass at different and ``Q'') that are constructed according to different heights), as well as elevation as a measure of climatic statistical units (environmental characteristics and spe- harshness. Elevation ranged from 20 (Skerray) to 750 cies traits in our case) by way of a third table (``L'') m above sea level (a.s.l.) (Crianlarich, Fig. 1, Table 1). that represents the link between them (a species abun- In Scotland, average temperatures decrease more rap- dance matrix). It makes possible the precise de®nition idly with elevation than the adiabatic lapse rate (Price of the environmental gradients, and the exact location 1983). The weather of upland Britain is considered to of each of the sampled localities on them, through char- be of a ``maritime periglacial'' type (Ballantyne and 1114 IGNACIO RIBERA ET AL. Ecology, Vol. 82, No. 4

were not signi®cant except for sites in which there was considerable change in land use (I. Ribera and I. Down- ie, unpublished results). Pitfall traps offer a standard, highly replicable method of studying ground-dwelling fauna, and have been successfully used in studies using quantitative (e.g., Blake et al. 1994, 1996, Luff 1996, Rykken et al. 1997), as well as qualitative data (e.g., Rushton et al. 1989, 1990). The whole pitfall catch of one season can be taken as a measure of population density for a given species in a particular habitat (Baars 1979, Ericson 1979, Luff 1982, Chiverton 1984), thus avoiding the problem of the possible bias introduced by the different activity of the beetles when considering isolated samples. The catch of pitfalls in enclosed areas has also been demonstrated to be correlated with catches in traps in open ®elds (e.g., r ϭ 0.92 for the logarithm of the abundance of 20 species of carabids, data from Table 1 in Desender 1986). Environmental data Land use was quantitatively characterized through a management intensity score, following Downie et al. (1998, 1999). Eight broad variables were considered at each site, and each of these variables was assigned a score from 0 to 3 in ascending order of intensity (none, low, moderate, or high). Variables included: sward type (0, natural or semi-natural; 1, sown or improved; 2, grass mixture; 3, ryegrass ley); age of the current land use (0, uncultivated; 1, Ͼ10 yr; 2, 5±10 yr; 3, Ͻ5 yr); FIG. 1. Map showing location of sampling areas in Scot- soil disturbance (0, none; 1, only harrowed in last three land, the number of sites in each area (parentheses), and the years; 2, plowed once in last three years; 3, plowed year of sampling. twice or more in last three years); cutting (0, none; 1, topping only; 2, one complete cut and removal of veg- Harris 1994), characterized by strong winds, high pre- etation; 3, two or more complete cuts and removal of cipitation, and 30±40 freeze±thaw events each year, vegetation); grazing (scored on the basis of number of associated with cyclonic activity. livestock, if any, from Ͻ0.8 to Ͼ1.14 livestock units/ Special habitats (e.g., riparian, wetlands, coastal) ha); inorganic fertilizer (0, none; 1, Ͻ50 kg/ha of N, were excluded from the study to avoid biases intro- P, and K; 2, 50±100 kg/ha; 3, Ͼ100 kg/ha); organic duced by the inclusion of habitats with characteristics fertilizer (four levels, from none to heavy manure that could not easily be compared. We sampled each dressing); and pesticides (0, none; 1, fungicide only; site during one season, and the whole study was carried 2, one herbicide and/or one fungicide; 3, two or more out over three years (1995 to 1997). Eighty-seven sites herbicide products and/or insecticide and/or glyphos- were sampled, distributed in nine main areas across phate) (see Table 2 in Downie et al. 1999 for more Scotland (Fig. 1). details). Observed values lay between 1 and 20 within the potential range from 0 to 24 (Table 1). Ground beetle sampling In addition to the management index, standard soil Beetles were sampled with two parallel rows of nine analyses were conducted on four soil samples from pitfall traps (diameter 7.5 cm, 2 m apart) at each site, each site, taken at the initial visit of the sampling sea- starting in early May. Traps were ®lled with ϳ2cmof son (Table 2). Vegetation data were obtained from per- ethylene or propylene glycol, and serviced monthly manent quadrats established beside the pitfall traps, and until the end of the season (end of August or Septem- included standard measures of vegetation structure and ber). For the 1997 sites we used only one row of traps, biomass (Abernethy et al. 1996). Elevation was ob- as results obtained in 1995 and 1996 proved that the tained from 1:25 000 maps of the area. second row was largely redundant (I. Ribera and I. Downie, unpublished results). The analysis of repeated Morphological characteristics of the species samples of some sites (which were not included in this Morphological characteristics of the ground beetle study) demonstrated that between-year differences species were selected in order to re¯ect functional at- April 2001 EFFECTS OF DISTURBANCE ON SPECIES TRAITS 1115

TABLE 1. Sites included in the study, with their general land use, elevation, and management index (see Materials and Methods: Environmental data).

Manage- Elevation ment No. Code Land use Area (m a.s.l.) index 1 gs21 grazing and silage Auchincruive 55 15 2 gs22 grazing and silage Auchincruive 55 12 3 eg11 extensive grass Ae 220 1 4 eg12 extensive grass Ae 230 5 5 eg13 extensive grass Ae 195 5 6 eg14 extensive grass Ae 230 1 7 yh71 young heather Dalwhinnie 390 3 8 oh72 old heather Dalwhinnie 385 1 9 bh73 burnt heather Dalwhinnie 390 7 10 gr11 grass Ae 61 8 11 gr12 grass Ae 62 16 12 sp13 spring barley Ae 62 19 13 ww14 winter wheat Ae 63 17 14 gr15 grass Ae 62 16 15 se16 set-aside grass Ae 70 12 16 fd17 fodder beet Ae 70 16 17 he61 heather Glensaugh 425 1 18 gr62 grass Glensaugh 265 7 19 he63 heather Glensaugh 430 1 20 gr64 grass Glensaugh 170 15 21 gg65 gorse ϩ grass Glensaugh 170 1 22 yc51 young conifer woodland Crianlarich 165 1 23 oc52 old conifer woodland Crianlarich 165 4 24 wh51 wet heather moorland Crianlarich 330 1 25 ug51 upland grassland, wet boggy ¯ush Crianlarich 270 1 26 dg52 dry upland grassland Crianlarich 270 1 27 ig53 improved upland grassland Crianlarich 360 4 28 ug54 upland grassland, ¯ush Crianlarich 165 1 29 dg55 dry upland grassland Crianlarich 180 4 30 uh51 upland bare peat Crianlarich 470 1 31 ug51 upland grassland, wet with Nardus Crianlarich 500 1 32 bg52 base-rich upland grassland Crianlarich 750 1 33 dg53 dry upland grassland with bracken Crianlarich 280 4 34 gz51 grazing pasture Crianlarich 165 9 35 si52 silage and grazing Crianlarich 165 12 36 wt53 wet tussocky grassland Crianlarich 155 4 37 wg54 wet grassland, mainly Myrica Crianlarich 155 1 38 wb61 winter barley Glensaugh 125 16 39 gr62 grass Glensaugh 163 12 40 wb31 winter barley East Lothian 25 20 41 ww32 winter wheat East Lothian 30 18 42 so33 spring oilseed rape East Lothian 70 17 43 wr34 winter oilseed rape East Lothian 65 17 44 gz81 grazing Tain 30 9 45 sp82 spring barley Tain 30 16 46 se83 set aside Tain 30 8 47 re84 reseed grazing Tain 30 12 48 ww85 winter wheat Tain 30 17 49 wb86 winter barley Tain 30 17 50 wo87 winter oats Tain 30 16 51 sp41 spring barley Crieff 45 17 52 ww42 winter wheat Crieff 50 16 53 wb41 winter barley Crieff 140 19 54 wb42 winter barley Crieff 130 19 55 sp41 spring barley Crieff 35 17 56 so42 spring oilseed rape Crieff 35 16 57 so43 spring oilseed rape Crieff 35 16 58 oc41 old conifer woodland Crieff 240 1 59 gh41 gorse at edge of heather moorland Crieff 230 1 60 go41 gorse within grazing pasture Crieff 200 3 61 wh41 wet heather moorland Crieff 235 1 62 dh42 dry heather moorland, newly burned Crieff 230 6 63 ha91 hay Skerray 30 5 64 fr9A forage rape Skerray 20 13 65 gz92 grazing Skerray 35 3 66 re93 reseed grazing Skerray 20 11 67 we94 wet grazing Skerray 20 4 68 re95 reseed grazing Skerray 35 4 1116 IGNACIO RIBERA ET AL. Ecology, Vol. 82, No. 4

TABLE 1. Continued.

Manage- Elevation ment No. Code Land use Area (m a.s.l.) index 69 ro96 rough grazing Skerray 60 2 70 he97 heather moor Skerray 70 2 71 tu98 turnips Skerray 40 10 72 fr99 forage rape Skerray 20 9 73 si41 silage and grazing Crieff 95 12 74 gz42 grazing pasture Crieff 90 10 75 gz43 grazing pasture Crieff 145 7 76 gz44 grazing pasture, rough wet area Crieff 170 3 77 gz41 grazing pasture, wet marshy area Crieff 230 6 78 gz42 grazing pasture, drier area Crieff 235 6 79 gz41 grazing pasture Crieff 215 9 80 gz42 grazing pasture Crieff 220 8 81 gz41 grazing pasture, area of rushes Crieff 35 10 82 gz42 grazing pasture Crieff 35 10 83 se41 set aside Crieff 40 12 84 se42 set aside Crieff 50 12 85 gr61 grass Glensaugh 70 12 86 sp62 spring barley Glensaugh 67 16 87 so63 spring oil seed rape Glensaugh 67 16

tributes, following previous studies that showed their interspeci®c differences were in general much larger, likely functional signi®cance, as assessed with phy- and the six specimens were taken as an appropriate logenetic comparative methods (Ribera et al. 1999a, b, representation of the average size and shape of each and references therein). Ten linear quantitative mea- species. Measurements were chosen to best character- surements and four qualitative characters were col- ize shape, not taxonomic characters. They included ma- lected for all the species (Tables 3 and 4). Six speci- jor linear dimensions of the body, hind legs, eyes, and mens were measured per species, one male and one antennae, following the approach of previous work female from three different localities and dates, to (e.g., Forsythe 1987, Ribera et al. 1999a). All quan- avoid possible biases due to sexual dimorphism, and titative variables were normalized by a log-transfor- geographical or temporal variability. This potential in- mation prior to analysis. For each species, the residuals traspeci®c variation was not considered because the of the regression of each individual variable against

TABLE 2. Environmental variables used in the analysis.

Code Description Texture 1, peat; 2, peaty loam; 3, loamy sand; 4, sandy loam; 5, sandy clay loam; 6, sandy silt loam; 7, silty clay Org organic content (% loss of organic content on ignition), log10 transformed pH soil pH Avail P available P (mg/L), log10 transformed Avail K available K (mg/L) Moist percentage moisture content Bare percentage cover estimate of bare ground in 11 1-m2 quadrats, arcsine transformed 2 Litter percentage cover estimate of litter cover in 11 1-m quadrats, log10 transformed Bryophyte percentage cover estimate of bryophytes in 11 1-m2 quadrats, arcsine transformed Plants/m2 number of reproductive stems (¯owering or fruiting) in 11 1-m2 quadrats Canopy height canopy height (cm) in 11 1-m2 quadrats Stem density number of stems (ramets) in 100 cm2 Biom 0±5 dry mass (g) of biomass 0±5 cm from soil surface in 400 cm2 2 Biom 5ϩ dry mass (g) of biomass Ͼ5 cm from soil surface in 400 cm , log10 transformed 2 Repro biom biomass of reproductive parts (¯owers and fruits) in 100 cm , log10 transformed Elevation elevation in m a.s.l. Management management intensity index (see Materials and Methods: Environmen- tal data) April 2001 EFFECTS OF DISTURBANCE ON SPECIES TRAITS 1117

TABLE 3. Morphological and life trait variables of ground beetles of the family Carabidae in Scotland.

Code Variable A) Quantitative (all measures log-transformed) LYW diameter of the eye, measured from above LAL length of the antenna LPW maximum width of the pronotum LPH maximum depth (ªvaultingº) of the pronotum LEW maximum width of the elytra LFL length of the metafemur (with the articulation segments), from the coxa to the apex LTR length of the metatrochanter LRL length of the metatarsi LFW maximum width of the metafemur LTL total length (length of the pronotum in the medial line plus length of the elytra, from the medial ridge of the scutellum to the apex) B) Qualitative CLG color of the legs (1, pale; 2, black; 3, metallic) CLB color of the body (1, pale; 2, black; 3, metallic) WIN wing development (1, apterous or brachypterous; 2, dimorphic; 3, macropterous) PRS shape of the pronotum (1, oval; 2, cordiform; 3, trapezoidal) OVE² overwintering (1, only adults; 2, adults and larvae or only larvae) FOA food of the adult (1, mostly Collembola; 2, generalist predator; 3, mostly plant material) DAY³ daily activity (1, only diurnal; 2, nocturnal) BRE breeding season (1, spring; 2, summer; 3, autumn or winter) EME main period of emergence of the adults (1, spring; 2, summer; 3, autumn) ACT§ main period of adult activity (1, autumn; 2, summer only) Note: Only the residuals of the regression with LTL, plus LTL, were used in the analysis of the quantitative variables. ² There was no available information on the overwintering stage of Notiophilus aquaticus, which was assumed to be the same as of N. germinyi and N. palustris (the most closely related species). ³ ``Nocturnal'' includes species that can be active during night and day, as they have morphological characteristics very similar to those of strict nocturnal species (Ribera et al. 1999b). The activity period of eight species was estimated according to unpublished information and the known activity period of the most closely related species (M. L. Luff, personal communication 1997). § There was no available information on the activity period of Notiophilus aquaticus and Pterostichus rhaeticus, which was assumed to be similar to that of other species of Notiophilus and P. nigrita, respectively (the most closely related species). total length (TL, length of the pronotum plus length of in particular that included in Luff (1998). Some of the the elytra, Table 3) were used in the analysis to re¯ect variables used are not independent, with strong cor- variation in shape independent of differences in overall relations among them (e.g., overwintering and breeding size. Owing to the constant general shape of all the season). This is fully accounted for by the multivariate species studied, the total length can be considered a ordination methods used, the ®nal axes re¯ecting the very good estimate of size, with a strong log-linear compound effect of all variables (see Materials and relationship with body biomass for European carabids Methods: Statistical analysis). (r ϭ 0.98, JarosõÂk 1989). Statistical analysis Life traits Six life traits of the species were chosen, re¯ecting Abundance values were log-transformed to reduce well-known differences in life and/or ecological strat- the effect of dominant species. To reduce the effect of egies (Table 3). Other traits that could be of functional rare species, only species that occurred in more than or ecological importance were not used because of lack four sites and with more than one specimen were stud- of information for most of the species. Traits were cod- ied. Totals of 87 sites and 95 025 specimens belonging ed according to published information (full data can to 68 species were included in the ®nal analysis. The be obtained from the Appendix. For species displaying entire set of analyses was repeated using presence± polymorphism for some of the variables, information absence data only, to account for possible artifacts due relating to Scottish or northern England populations to sampling method, or to differences in sampling ef- was used whenever possible. When contradictory in- fort. The results were fully consistent with those ob- formation was found, the most recent source was used, tained using abundance data, with only a slight de- 1118 IGNACIO RIBERA ET AL. Ecology, Vol. 82, No. 4

TABLE 4. Carabid beetle species included in the study.

Species Code 1 Agonum fuliginosum (Panzer, 1809) agon fuli 2 Agonum muelleri (Herbst, 1784) agon muel 3 Amara aenea (De Geer, 1794) amar aene 4 Amara apricaria (Paykull, 1790) amar apri 5 Curtonotus aulicus (Panzer, 1797) (ϭAmara aulica) amar auli 6 Amara bifrons (Gyllenhal, 1810) amar bifo 7 Amara communis (Panzer, 1797) amar comm 8 Amara eurynota (Panzer, 1797) amar eury 9 Amara familiaris (Duftschmid, 1812) amar fami 10 Amara lunicollis SchioÈdte, 1837 amar luni 11 Amara plebeja (Gyllenhal, 1810) amar pleb 12 Anchomenus dorsalis (Pontoppidan, 1763) (ϭAgonum dorsale) anch dors 13 Asaphidion ¯avipes (Linnaeus, 1761) asap ¯av 14 Bembidion aeneum Germar, 1824 bemb aene 15 Bembidion bruxellense Wesmael, 1835 bemb brux 16 Bembidion guttula (Fabricius, 1792) bemb gutt 17 Bembidion lampros (Herbst, 1784) bemb lamp 18 Bembidion mannerheimi C.R. Sahlberg, 1834 bemb mann 19 Bembidion obtusum Serville, 1821 bemb obtu 20 Bembidion tetracolum Say, 1823 bemb tetr 21 Bradycellus harpalinus (Serville, 1821) brad harp 22 Bradycellus ru®collis (Stephens, 1828) brad ru® 23 Calathus fuscipes (Goeze, 1777) cala fusc 24 Calathus melanocephalus (Linnaeus, 1758) cala mela 25 Calathus micropterus (Duftschmid, 1812) cala micr 26 Carabus arvensis Herbst, 1784 cara arve 27 Carabus glabratus Paykull, 1790 cara glab 28 Carabus granulatus Linnaeus, 1758 cara gran 29 Carabus nemoralis O. MuÈller, 1764 cara nemo 30 Carabus nitens Linnaeus, 1758 cara nite 31 Carabus problematicus Herbst, 1786 cara prob 32 Carabus violaceus Linnaeus, 1758 cara viol 33 Clivina fossor (Linnaeus, 1758) cliv foss 34 Cychrus caraboides (Linnaeus, 1758) cych cara 35 Dyschinoides globosus (Herbst, 1783) (ϭDyschirius globosus) dysc glob 36 Elaphrus cupreus Duftschmid, 1812 elap cupr 37 Elaphrus uliginosus Fabricius, 1775 elap ulig 38 Harpalus af®nis (Schrank, 1781) harp af® 39 Harpalus latus (Linnaeus, 1758) harp latu 40 Harpalus ru®pes (De Geer, 1774) harp ru® 41 Leistus terminatus (Hellwig in Panzer, 1793) (ϭL. rufescens) leis term 42 Loricera pilicornis (Fabricius, 1775) lori pili 43 Nebria brevicollis (Fabricius, 1792) nebr brev 44 Nebria salina Fairmaire & LaboulbeÁne, 1854 nebr sali 45 Notiophilus aquaticus (Linnaeus, 1758) noti aqua 46 Notiophilus biguttatus (Fabricius, 1779) noti bigu 47 Notiophilus germinyi Fauvel, 1863 noti germ 48 Notiophilus palustris (Duftschmid, 1812) noti palu 49 Notiophilus substriatus Waterhouse, 1833 noti subs 50 Olisthopus rotundatus (Paykull, 1790) olis rotu 51 Patrobus assimilis Chaudoir, 1844 patr assi 52 Patrobus atrorufus (StroÈm, 1768) patr atro 53 Poecilus versicolor (Sturm, 1824) (ϭPterostichus versicolor) poec vers 54 Pterostichus adstrictus Eschscholtz, 1823 pter adst 55 Pterostichus diligens (Sturm, 1824) pter dili 56 Pterostichus madidus (Fabricius, 1775) pter madi 57 Pterostichus melanarius (Illiger, 1798) pter mela 58 Pterostichus niger (Schaller, 1783) pter nige 59 Pterostichus nigrita (Paykull, 1790) pter nigr 60 Pterostichus rhaeticus Heer, 1838 pter rhae 61 Pterostichus strenuus (Panzer, 1797) pter stre 62 Pterostichus vernalis (Panzer, 1796) pter vern 63 Stomis pumicatus (Panzer, 1796) stom pumi 64 Synuchus vivalis (Illiger, 1798) (ϭS. nivalis) synu viva 65 Trechoblemus micros (Herbst, 1784) (ϭTrechus micros) trec micr 66 Trechus obtusus (Erichson, 1837) trec obtu 67 Trechus quadristriatus (Schrank, 1781) trec quad 68 Trechus rubens (Fabricius, 1792) trec rube Notes: Nomenclature follows Kryzhanovskij et al. (1995) and Lindroth (1985, 1986) (names of common use in the United Kingdom are given in parentheses). Codes of the species are those used in Fig. 3. April 2001 EFFECTS OF DISTURBANCE ON SPECIES TRAITS 1119 crease in the amount of the observed correlation, var- the same product of matrices, but, as noted above, it iance explained, and signi®cance values. does not proceed with its eigenvalue decomposition, We initially analyzed each table separately, in order and hence does not obtain the ordination axes. In RLQ to compare results with those of the three-table joint analysis, the eigenvalue decomposition of the cross- analyses. The species abundance table containing the matrix provides ordination axes (the environmental and number of specimens in each species occurring at each the morphological life-trait axes) onto which sites and site was analyzed by correspondence analysis (CA), an species are projected, resulting in new sets of scores eigenanalysis that provides a joint scaling of sites and for the sites and the species respectively. species (e.g., Greenacre 1984, Thioulouse and Chessel As we used a version of RLQ analysis based on the 1992). We computed principal component analysis correspondence analysis of the species abundance ta- (PCA) on both the correlation matrix of the quantitative ble, these new scores for sites and species have a max- morphological traits of the species and on the envi- imal covariance (see DoleÂdec et al. 1996:148 for a dem- ronmental characteristics of the sites. To interpret these onstration). Because the structure of the individual ta- analyses we used the correlation between each quan- bles can only be partially optimized (owing to the con- titative variable and the components of the PCA. Fi- straints imposed by a joint analysis), RLQ takes into nally, we computed multiple correspondence analysis account only a fraction of the total variance. Further- (MCA, Tenenhaus and Young 1985, an extension of more, the highest possible correlation (canonical cor- CA to multi state discrete characteristics, the statistical relation) between rows and columns in a contingency equivalent of PCA with qualitative variables) on the table is given by the square root of the ®rst eigenvalue qualitative morphological and life traits of the species. of its correspondence analysis (Williams 1952). In con- We interpreted this latter analysis by way of correlation sequence, the correlation computed from the ®rst RLQ ratios, which help to investigate the link between the axis cannot be higher than the canonical correlation initial qualitative variables and the new quantitative obtained from the ®rst CA axis of the species abun- scores of individuals generated by MCA. Correlation dance table. This means that the structure of the species ratios represent percentages of variance of a score ex- abundance table can also only be partly optimized, plained by each qualitative variable. The higher the since only the variability associated with environmen- correlation ratio, the better the different categories of tal characteristics of sites and traits of species is ac- the variable are separated. counted for. In summary, the maximization of covari- To investigate the relationships between morpholog- ance results in the best joint combination of the ordi- ical and/or life traits of species and environmental char- nation of sites by their environmental characteristics acteristics of sites, we used a version of RLQ analysis (optimization of the site score variability), the ordi- based on the CA of the species abundance Table L (see nation of species by their traits (optimization of the the Appendix; J species [columns] in I sites [rows], species score variability), and the simultaneous ordi- DoleÂdec et al. 1996). Table L represents a link between nation of species and sites (optimization of the corre- Table R (Appendix) containing the measurements of p lation between the sites scores and the species scores). environmental variables in the I sites, and Table Q We conducted two RLQ analyses, one using the (Appendix) comprising the values of q traits of the J quantitative morphological traits and a second using species. The RLQ analysis enables the study of the joint the qualitative life traits of the species. For the test structure of these three data tables, irrespective of statistic we used the trace of the cross matrix generated whether data are quantitative or qualitative. by the RLQ analysis (the squared covariance between There are few known applications able to deal with the environmental and species traits Tables R and Q). a three-table joint analysis. Legendre et al. (1997) in- This statistic increases with the intensity of the rela- vestigated the relationship between species traits of ®sh tionship between the environmental and the species and habitat characteristics of coral reefs by a novel traits tables through the species abundance table. We method primarily designed to test the signi®cance of tested the global statistical signi®cance of this rela- the relationships. In addition to test the signi®cance of tionship using random permutations. The null hypoth- this relationship, we were also interested in obtaining esis was independence between the two Tables R and an ordination of species and sites on the main envi- Q (i.e., their squared covariance ϭ 0), the alternative ronmental gradients, an option not available in the orig- hypothesis being that they were related (their squared inal formulation of Legendre et al. (1997). The latter covariance Ͼ0). In our model we assumed that the method also required presence/absence or frequency species abundance table provided the measure of the data in the link matrix, whereas RLQ can use the spe- intensity of the relationship between environmental cies abundances. characteristics and species traits. In consequence, we The general mathematical model of RLQ analysis, considered it as ®xed, and permuted the rows of both which basically consists of the eigenanalysis of the the species traits and the environmental characteristics matrix RTLQ, is fully explained in DoleÂdec et al. (1996: tables. This avoids the problem of choosing a model 147) and we give here only some of its basic properties. to randomize the species abundance table (see e.g., The method proposed by Legendre et al. (1997) uses Legendre et al. 1997 for a detailed explanation of al- 1120 IGNACIO RIBERA ET AL. Ecology, Vol. 82, No. 4

TABLE 5. Eigenvalues and percentage of variance of the ®rst TABLE 6. Correlation between the variables and the ®rst two four axes of the separate CA of the species abundance table. axes of the separate PCA of the environmental characteristics of the sites. Statistic Axis 1 Axis 2 Axis 3 Axis 4 Variable Axis 1 Axis 2 Eigenvalue 0.49 0.28 0.20 0.15 Percentage of variance 18 11 8 6 Eigenvalue 7.72 2.30 Percentage of variance 45 14 Texture 0.36 0.28 Org Ϫ0.83 Ϫ0.34 ternative randomization models). The resulting distri- pH 0.80 0.36 Avail P 0.80 0.10 bution of the traces of the 1000 replicated random per- Avail K 0.00 0.30 mutations was compared with the observed value. The Moist Ϫ0.81 Ϫ0.42 number of random permutation values that were equal Bare 0.80 Ϫ0.34 to or larger than this observed value can be considered Litter 0.19 Ϫ0.29 Bryophytes Ϫ0.64 Ϫ0.50 to be the best estimation of its probability, and a mea- Plants/m2 0.38 Ϫ0.14 sure of the signi®cance level of the analysis. For ex- Canopy height 0.66 Ϫ0.56 ample, if only one of the 1000 permutation values was Stem density Ϫ0.57 0.50 Biom 0±5 Ϫ0.77 Ϫ0.10 higher than that observed with the actual data (i.e., the Biom 5ϩ 0.62 Ϫ0.60 total frequency of values upper or equal to the observed Repro biom 0.80 Ϫ0.44 was 2/1001 ϭ 0.002), the signi®cance of the analysis Elevation Ϫ0.71 Ϫ0.31 can be estimated to be Ͻ0.002. If no permutation value Management 0.92 0.06 was higher than the observed one, its signi®cance can Notes: Eigenvalues and percentage of total variance on be estimated to be Ͻ0.001. each axis are also indicated. See Table 2 for the descriptions of the variables. All calculations and graphs were made with ADE-4 (Thioulouse et al. 1997). ADE-4 can be obtained freely through the website of the University of Lyon 1, which The second axis had the highest correlation with can- also provides access to updates and user support opy height, stem density, and biomass Ͼ5 cm (Biom through the ADEList mailing list. The four tables used 5ϩ), although it still retained relative high values for in the analysis (environmental characteristics of the most of the variables highly correlated with the ®rst sites, quantitative morphological characteristics of the axis. Only available potassium (Avail K) and percent- species, qualitative morphological and life trait char- age of litter cover (Litter) had a higher correlation with acteristics of the species, and species occurrence per the second than with the ®rst axis (Table 6). The cor- sites) are available in the Appendix. relation with management intensity was on the contrary very low (r ϭ 0.06), while the correlation with ele- RESULTS vation was higher (r ϭϪ0.31). Separate ordination of the data tables The three ®rst axes of the PCA of the quantitative The four ®rst axes of the CA of the species abun- morphological variables of the species accounted for dance matrix accounted for 43% of the total variance 73% of the total variance (Table 7). The ®rst axis was (Table 5). Additional axes accounted for variance most- mainly correlated with the length of the femur (LFL), ly associated with the occurrence of few species and the length of the tarsi (LRL), and the length of the were not considered in the RLQ analysis. Of special antenna (LAL), in all cases negatively. The second axis importance was the ®rst eigenvalue, corresponding to a canonical correlation equal to 0.7 (or the square root TABLE 7. Correlation between the variables and the ®rst of 0.49). As indicated in the Methods, this value is the three axes of the separate PCA of the quantitative mor- best possible correlation within the species abundance phological characteristics of the species. matrix. Variable Axis 1 Axis 2 Axis 3 The two ®rst axes of the PCA of the environmental characteristics of the sites accounted for 59% of the Eigenvalue 3.17 2.25 1.80 Percentage of variance 32 23 18 total variance (Table 6). The ®rst axis was mainly pos- LYW Ϫ0.32 0.13 0.69 itively associated (r Ͼ 0.8) with the management index, LAL Ϫ0.87 Ϫ0.07 Ϫ0.33 reproductive biomass (Repro biom), percentage of bare LPW 0.38 Ϫ0.70 0.43 LPH 0.40 Ϫ0.46 0.65 ground (Bare), available phosphorus (Avail P), and pH, LEW Ϫ0.54 Ϫ0.62 0.25 and negatively associated with percentage of organic LFL Ϫ0.97 Ϫ0.07 0.08 content (Org) and moisture (Moist) (Table 6). These LTR Ϫ0.02 Ϫ0.67 Ϫ0.58 were all variables highly correlated with the manage- LRL Ϫ0.87 Ϫ0.08 0.29 LFW 0.08 Ϫ0.83 Ϫ0.34 ment index (with r Ͼ 0.6 in all cases). The management LTL 0.07 0.08 Ϫ0.07 index was also highly correlated with elevation (r ϭ Notes: Eigenvalues and percentage of total variance on Ϫ0.68), something that has to be taken into account in each axis are also indicated. See Table 3 for the codes of the interpreting the results (see Discussion). variables. April 2001 EFFECTS OF DISTURBANCE ON SPECIES TRAITS 1121

TABLE 8. Correlation ratios between the variables and the of the scores, as in the separate analysis, but their ®rst six axes of the separate MCA of the qualitative morphological characteristics and life traits of the species stud- squared covariances (pseudo-eigenvalues in the ter- ied. minology of DoleÂdec and Chessel 1994). The 1000 random permutations of the rows of the R and Q ma- Variable Axis 1 Axis 2 Axis 3 Axis 4 Axis 5 Axis 6 trices did not give any value of the trace of the cross- Eigenvalue 0.32 0.22 0.20 0.17 0.15 0.13 matrix (which characterizes the intensity of the link Percentage between environmental variables and morphological of variance 19 13 12 10 9 8 traits through the species abundance) equal or superior CLG 0.34 0.52 0.08 0.16 0.30 0.09 CLB 0.52 0.20 0.41 0.06 0.03 0.04 to the observed value, which can be taken as strong WIN 0.04 0.06 0.21 0.09 0.28 0.61 evidence of its signi®cance (estimated P Ͻ 0.001). PRS 0.06 0.08 0.37 0.57 0.25 0.01 Because the RLQ analysis represents the partial or- OVE 0.62 0.01 0.01 0.00 0.04 0.03 FOA 0.19 0.18 0.31 0.42 0.25 0.09 dination of the environmental characteristics of the DAY 0.56 0.04 0.13 0.01 0.00 0.03 sites, species abundance, and quantitative morpholog- BRE 0.58 0.51 0.03 0.05 0.26 0.04 ical traits of the species, the proportion of variance EME 0.30 0.49 0.19 0.29 0.04 0.06 ACT 0.00 0.14 0.24 0.05 0.02 0.32 attributed to each matrix was compared to that resulting from their separate analyses (Table 9a). The ®rst axis Notes: Eigenvalues and percentage of total variance on each axes are also indicated. See Table 3 for the codes of the of the RLQ analysis accounted for 97.1% of the po- variables. tential variability for the ®rst axis in the separated analysis of the environmental characteristics of the habitats (i.e., the ratio between the variance of the habitat char- was mainly correlated with pronotum, elytra, and femur acteristics accounted for in RLQ [7.5] and that of the width (LPW, LEW, and LFW), and length of the tro- separate analysis [7.72] is 0.971, see Tables 6 and 9a). chanter (LTR), also negatively. The third axis was Similarly, it took into account 43.8% of the potential mainly positively correlated with the diameter of the variability for the ®rst axis in the separate analysis of eye (LYW) and pronotum height (LPH), and negatively the quantitative morphological traits (0.438 ϭ 1.39/ with the length of the trochanter (LTR), although for 3.17, computed as before, see Table 7 for the eigenvalue the latter the highest correlation was with axis two of the separate analysis of the quantitative traits). The (Table 7). two new sets of scores had a correlation of 0.25 along Six ordination axes were considered for the MCA of the ®rst RLQ axis (Table 9a), which has to be compared the qualitative morphological and life trait variables, which accounted for 71% of the total variance (Table 8). According to the correlation ratios, the ®rst axis TABLE 9. Results of the RLQ analysis of (a) quantitative was mainly related to overwintering stage (OVE), species traits and (b) qualitative species traits. breeding season (BRE), daily activity (DAY), and body Statistic Axis 1 Axis 2 color (CLB). The second axis was mainly correlated with color of the legs (CLG), period of emergence of a) Quantitative species traits Eigenvalues 0.64 0.08 the adults (EME), and breeding season (BRE), although Total variance 84.8% 10.5% the latter was most correlated with the ®rst axis, as Covariance 0.80 0.28 seen above. Axis four was mainly correlated with pron- Correlation 0.25 0.13 otum shape (PRS) and food of the adult (FOA), and Variance Habitat 7.50 2.09 axis six with wing development (WIN) and activity Traits 1.39 2.29 period (ACT). None of the variables had their highest b) Qualitative species traits correlation with the third and ®fth axes. Despite their Eigenvalues 0.17 0.009 low variance explained, axes four and six were kept in Total variance 90.2% 4.5% Covariance 0.42 0.09 the RLQ analysis because of the high correlation with Correlation 0.38 0.16 individual variables, which were biologically mean- Variance ingful and important in the joint analysis of the three Habitat 7.30 2.45 Traits 0.16 0.14 data tables (see below). Notes: Eigenvalues are obtained from the singular value Joint analysis of quantitative morphological traits, decomposition of the cross matrix RTLQ and represent a site environmental characteristics, squared covariance; ``total variance'' refers to the percentage of total variance accounted for by each axis; ``covariance'' and species composition refers to the covariance between the two new sets of factorial scores projected onto the ®rst two RLQ axes (square root of The ®rst two axes of the three-table RLQ analysis eigenvalue); ``correlation'' refers to the correlation between extracted 84.8% and 10.5%, respectively, of the total the two new sets of factorial scores projected onto the ®rst variance of the matrix that crosses the site environ- two RLQ axes; ``variance'' refers to the variance of each set mental characteristics and the quantitative morpholog- of factorial scores computed in the RLQ analysis, both for the habitat and for the traits (see Material and Methods: Sta- ical traits of the species (Table 9a). Note that the ei- tistical analysis for more details on the interpretation of the genvalues of these axes do not represent the variance statistics). 1122 IGNACIO RIBERA ET AL. Ecology, Vol. 82, No. 4

TABLE 10. Scores of the environmental variables on the ®rst axis of the RLQ analyses performed on the quantitative and qualitative species traits.

RLQ of quanti- RLQ of quali- Variable tative traits tative traits Texture 0.11 0.12 Org Ϫ0.27 Ϫ0.30 pH 0.33 0.34 Avail P 0.32 0.31 Avail K 0.03 0.06 Moist Ϫ0.29 Ϫ0.33 Bare 0.23 0.21 Litter 0.02 Ϫ0.01 Bryophyte Ϫ0.31 Ϫ0.33 Plants/m2 0.07 0.10 Canopy height 0.19 0.14 Stem density Ϫ0.17 Ϫ0.11 Biom 0±5 Ϫ0.28 Ϫ0.29 Biom 5ϩ 0.19 0.13 Repro biom 0.23 0.19 Elevation Ϫ0.33 Ϫ0.33 Management 0.36 0.35 Note: See Table 2 for the description of the variables.

FIG. 2. Projection of the axes of each separate analysis on the ®rst two RLQ joint ordination axes. The graphs on the considered, as it represented the majority of the total left correspond to the joint analysis of (a) the environmental variance and the best correlation among scores. En- data and (b) the quantitative species traits. The graphs on the vironmental variables, sites, species, and quantitative right correspond to the joint analysis of (c) the environmental morphological traits were respectively arranged along data and (d) the qualitative species traits. Numbers refer to the number of axes selected in each of the separate analysis this ®rst axis (Tables 10 and 11, Fig. 3). (see Results). Environmental variables were ordered along the ®rst axis of the RLQ analysis according to their weight in the linear combination that provided the coordinates of to the highest possible correlation between sites and the sites (Table 10, Fig. 3a). These values basically species, given by the square root of the ®rst eigenvalue agreed with the separate PCA of the environmental of the CA of the species abundance table (0.7, see matrix, with the single exception of elevation, which Results: Separate ordination). This value was as ex- had the highest negative value in the RLQ axis, but pected very low along the second axis (0.13; Table 9a). only the fourth negative value in magnitude in the in- The covariance between the new sets of scores for the dividual PCA (Tables 6 and 10). The agreement be- sites (computed from their environmental characteris- tween the weights of the environmental variables in the tics) and the species (computed from their quantitative separate PCA and the ®rst RLQ axis was expected, morphological traits), which is optimized by the ®rst owing to the high percentage of variability of the en- RLQ axis, was equal to 0.80 (Table 9a, obtained from vironmental matrix accounted for in the RLQ analysis, square root of 7.5 ϫ square root of 1.39 ϫ 0.25). In as noted above (Table 9a and Fig. 2a). contrast, this value was very low on the second axis Sites were ordered along the RLQ axis closely fol- (0.28). lowing a broad classi®cation of their land use (Fig. 3a), The ordination axes obtained with RLQ and those and can be informally placed in the following groups obtained with the separate analysis of the individual tables were graphically compared in Fig. 2a and b. The structure of the environmental matrix described by the TABLE 11. Scores of the quantitative morphological vari- RLQ axes was, as expected, very close to that of the ables of the species on the ®rst RLQ axis. separate analysis (Fig. 2a). By contrast, the RLQ axes did not represent directly the information given by the Variable Axis 1 three ®rst axes of the separate analysis of the quanti- LYW Ϫ0.09 LAL 0.11 tative morphological traits, but a combination of them LPW 0.01 (Fig. 2b). As an example of the different loading of LPH Ϫ0.28 the variables in the separate analysis and in RLQ, total LEW 0.28 size (LTL) had a very low correlation with the ®rst LFL 0.03 LTR 0.25 three PCA axes of the separate analysis (Table 7), but LRL 0.05 it was the variable with the highest correlation with the LFW 0.20 ®rst RLQ axis (Ϫ0.59; Table 11). LTL Ϫ0.59 Only the ®rst axis of the RLQ analysis was further Note: See Table 3 for the codes of the variables. April 2001 EFFECTS OF DISTURBANCE ON SPECIES TRAITS 1123

FIG. 3. First ordination axis of the RLQ analysis of the quantitative species traits: (a) scores of the sites (each vertical line stands for a site, and arrows separate main types of land use [1, upland or very wet grassland, heather, bare peat; 2, rough or wet grass, extensive pastures, gorse, coniferous forest, recently burnt heather; 3, grassland; 4, set aside and forage rape; 5, cultivated ®elds]); and (b) position of species at the average score of the sites in which they occur. The area of each circle is proportional to the frequency of the species; horizontal lines represent the standard deviation of these scores. See Table 4 for the species codes. ordered from lowest to highest values of the RLQ axis: of Amara, and Anchomenus dorsalis), and species typ- (1) 17 sites including heather moorland, upland grass- ical of undisturbed natural sites the lowest (such as lands, one site with bare peat, and two very wet rough Calathus micropterus, Patrobus assimilis, and most of grasslands; (2) 15 sites including different land uses the species of Carabus, with the exception of C. ne- with less intensive management, from conifer forest to moralis) (see Eyre and Luff 1990, or Eyre 1994 for gorse scrub, heather burned recently, or extensive or autecological information on these species). There was very wet grasslands; (3) some lowland grasslands, a gap in the ordination of the species (Fig. 3b), sepa- which also included one hay ®eld, one turnip ®eld, a rating a group typical of the more undisturbed, less dry, upland grassland, a forage oil-seed rape, and a managed upland sites (24 species) from a group more gorse-shrub site with patches of grass (28 sites in total); typical of disturbed, more intensively managed lowland (4) six set-aside and forage rape ®elds; and ®nally, with sites (42 species), with two species having intermediate the highest values, (5) 21 cereal and oilseed rape ®elds. values (Elaphrus cupreus and Trechus rubens). The The grassland sites (group 3) were roughly ordered average abundance of the two groups of species was according to their level of disturbance by management. also clearly different, the latter being on average much There was no geographical pattern in the ordination more abundant than the former. of the sites, with areas with sites from different land Finally, morphological characteristics were corre- uses falling into different general groups (e.g., Crieff, lated with the above species ordination along the ®rst Ae, or Skerray, see Table 1 and Fig. 1). RLQ axis (Table 11). Variables with the highest cor- Species were located in the ®rst RLQ axis at the relations were total size (LTL) and pronotum height or weighted average of the scores of their sites (Fig. 3). ``vaulting'' (LPH) (both negatively correlated), and el- Species typical of disturbed sites had the highest values ytra width (LEW), trochanter length (LTR), and femur (such as the species of Bembidion, most of the species width (LFW) (positively correlated). Species typical of 1124 IGNACIO RIBERA ET AL. Ecology, Vol. 82, No. 4 upland, less managed sites were thus larger and had a qualitative traits of the species, but a combination of more vaulted pronotum, while species typical of low- them, including mainly information on axes 2 and 6 land, intensively managed sites had wider elytra, longer (Fig. 2d). Because of the low variance explained by trochanter, and wider femora. Less important variables the second RLQ axis, this was not further considered. were length of the antenna (LAL) (negatively corre- Environmental variables, sites, species, and qualitative lated), and diameter of the eyes (LYW) (positively cor- species traits were ordered along the ®rst RLQ axis related). (Table 10 and Fig. 4). The weight of the environmental variables was es- Joint analysis of qualitative morphological and life sentially the same as in the previous RLQ analysis, the traits, site environmental characteristics, main difference being a switch in relative position of and species composition the percentage of organic content (Org) and biomass The two ®rst axes of the three-table RLQ analysis of the ®rst 5-cm layer (Biom 0±5) (Table 10). The extracted 90.2% and 4.5%, respectively of the total resulting ordination of the sites (Fig. 4a) was conse- variance of the matrix that crosses the site environ- quently very similar (r ϭ 0.99), with only minor shifts mental characteristics and the qualitative morpholog- in the position of some sites. The general ordination ical and life traits of the species (Table 9b). None of according to land use was preserved without any the 1000 permutations of the rows of the R and Q change. matrices had a value equal or greater than the observed The position of the species was also very similar, trace of the above cross-matrix, demonstrating the high with a gap again present between species occurring in statistical signi®cance of the relationship between the less managed upland sites and species occurring in environmental variables and the qualitative traits (es- more intensively managed grasslands and cultured timated P Ͻ 0.001). ®elds (Fig. 4c). The two intermediate species were as As in the previous RLQ analysis, the proportion of before. Representation of the relative abundance of the variance accounted for by the RLQ analysis was com- species added no further information and it is not pared to that resulting from the separate analyses of shown. the individual matrices (Table 9b). In this case, the ®rst The mean and standard deviation of the scores of the axis of the RLQ analysis accounted for 94.6% of the species included in each of the modalities of the qual- variability explained by the ®rst axis of the separate itative traits are represented in Fig. 4c. Wing devel- analysis of the environmental matrix (i.e., the ratio be- opment (WIN) and breeding season (BRE) had the tween the variance of the habitat characteristics in RLQ highest correlation ratios (Table 12). Brachypterous and the variance of the habitat characteristics in the species were strongly associated with less managed separate analysis, or 7.3/7.72, see Tables 6 and 9b). It sites at higher elevation, while macropterous and di- also accounted for 50% of the potential variability ac- morphic species (the latter with values close to the counted by the ®rst axis of the separate analysis of the origin) were associated with more intensively managed qualitative species traits (0.16/0.32, computed as lowland sites. Species breeding in summer were strong- above, see Tables 8 and 9b). The two new sets of scores ly associated with less managed upland sites, and spe- had a correlation along the ®rst RLQ axis of 0.38, cies breeding in spring or autumn±winter (these two which should be compared with the optimal theoretical groups having similar values) with the more intensively value of 0.7 (Table 9b). This was higher than the cor- managed lowland sites. Associated with the breeding relation obtained with the RLQ analysis of the quan- season was the period of activity, species breeding in titative morphological traits (0.25, see above). The cor- summer having their activity period mostly in autumn, relation of the scores along the second axis was on the and species active only in summer having their breed- contrary very low (0.16; Table 9b). The covariance ing period mostly in spring (Lindroth 1945, Thiele between the two new sets of scores for the sites (com- 1977). puted from their environmental characteristics) and the Other variables with lesser correlation ratios were: species (computed from their qualitative traits) was color of the body and legs (CLB and CLG), with black 0.42 (Table 9b, obtained from square root of 7.30 ϫ species mainly associated with less managed upland square root of 0.16 ϫ 0.38). This value was very low sites and pale species associated with more intensively for the second axis (0.09). managed lowland sites; overwintering stage (OVE), The ®rst two ordination axes of the RLQ analysis with species overwintering as larvae only associated were compared with those of the separate analyses of with less managed upland sites; and food of the adult the environmental and qualitative trait matrices in Fig. (FOA), with Collembola predators and species in which 2c and d. As in the RLQ analysis of the quantitative the plant material is an important part of their diet species traits, the structure of the environmental matrix, mostly associated with intensively managed lowland as described by the ®rst two RLQ axes, was very close sites, and generalist predators associated with less man- to that of the separate analysis (Fig. 2c). Similarly, the aged upland sites. The shape of the pronotum (PRS) is RLQ axes did not represent directly the information known to be related with the diet, species with trape- given by the ®rst six axes of the separate MCA of the zoidal pronota being mostly seed or plant eaters, and April 2001 EFFECTS OF DISTURBANCE ON SPECIES TRAITS 1125

FIG. 4. First ordination axis of the RLQ analysis of the qualitative species traits: (a) scores of the sites (see Fig. 3), (b) position of species at the average score of the sites in which they occur (vertical line), and (c) position of the qualitative traits at the average score of the species in which each of the modalities occur (circles). The area of each circle is proportional to the frequency of the category; horizontal lines represent the standard deviation of these scores. Scores in (b) and (c) are expanded for readability, maintaining the origin aligned with (a). See Table 3 for the codes of the variables.

species with cordiform pronota, predators (Ribera et DISCUSSION al. 1999b). Response to disturbance and stress The main period of emergence (EME) and daily activity (DAY) had correlation ratios close to zero, with We found a highly signi®cant relationship between species of the different modalities being uniformly dis- the species traits, as measured by a set of functional tributed along the ordination axis. morphological and life trait characters, and the environmental characteristics of their habitats, as measured by the main underlying environmental gradient. The TABLE 12. Correlation ratios between the qualitative morphological and life traits of the species and the ®rst RLQ principal interest of this result resides in its generality: axis. it demonstrates the direct relationship, re¯ected in common ordination axes, between an optimized compound Variable Axis 1 measure of environmental variability and an optimized CLG 0.09 compound measure of morphological and functional CLB 0.07 diversity. In both RLQ analyses the ®rst of these or- WIN 0.18 PRS 0.04 dination axes accounted for very large fractions of the OVE 0.04 explained variance for the environmental and the bi- FOA 0.03 ological data sets, indicating the existence of a strong DAY 0.00 BRE 0.12 underlying environmental gradient structuring the EME 0.00 characteristics of the sites and the species occurring in ACT Ϫ0.06 them. The ordination of the sites along this axis closely Note: See Table 3 for the codes of the variables. followed a broad classi®cation of land use. The indi- 1126 IGNACIO RIBERA ET AL. Ecology, Vol. 82, No. 4 vidual variables mostly associated with it were the means that species of different origin, and therefore management index and elevation (positively and neg- likely to behave independently, show the same type of atively correlated respectively), although other vari- response to the same environmental gradient. This ables commonly related with disturbance and stress common response demonstrates that the characters in also had a high correlation. More intensely managed question are truly functional, not evolutionary rem- sites had a high percentage of bare ground, lower pro- nants without further relevance. The scores of the spe- portion of biomass at Ͻ5 cm and a higher proportion cies in the RLQ axes allow the precise de®nition of at Ͼ5 cm; while sites with higher altitude had lower functional groups, which can be used for predictive reproductive biomass and a higher proportion of bryo- purposes in conservation management (I. Ribera, un- phytes (Table 10). Management and elevation were published manuscript). Changes in land use can thus highly negatively correlated, mainly due to the effect be directly related to changes in species traits (that is, of the sites at Crieff and Crianlarich. In these sites there changes in the functional diversity of the assemblage), are strong elevation gradients with farms and more in- rather than ®rst to taxonomic composition and, only tensive grazed grasslands at the bottom of the valley indirectly, to the functional characteristics of the spe- (20 m a.s.l. in Crieff, and 155 m a.s.l. in Crianlarich), cies. and more natural, undisturbed heather or extensive pastures at higher elevation (up to 240 m a.s.l. in Crieff, Morphological and life trait characteristics and 750 m a.s.l. in Crianlarich, Table 1). The relative There is a vast literature relating carabid species importance of the correlation of both variables with the composition with management, habitat characteristics, ordination axes can be taken as evidence that the most or disturbance, as measured by different criteria (e.g., important factor was land management, which always Eyre and Luff 1990, Luff 1990, Holmes et al. 1993, had a higher correlation than did elevation. The second Eyre 1994, see e.g., papers in NiemielaÈ 1996 for a axis of the environmental ordination, although still recent source of references). However, none of these highly related with elevation and some other variables, previous studies included biological or morphological had only a very small correlation with management, data other than size, and the interpretation of possible suggesting a decoupling of the effect of both variables. relationships, if any, was based on the knowledge of However, the low percentage of variance explained by the autecology of individual species. An attempt to this second axis makes its interpretation dif®cult. relate the distribution of carabids with a productivity± The main ordination axis can be considered roughly disturbance templet was used by Eyre (1994), although equivalent to the main diagonal in the habitat templet the axes were roughly de®ned by water content of the proposed by Southwood (1988), with highly disturbed soil and a disturbance index, without the inclusion of but favorable habitats in the bottom left corner, and morphological or biological information. more permanent but highly stressed or adverse habitats Carabids are generally considered to be more adapt- in the top right corner. The species theoretically as- ed to habits than habitats (e.g., Manton 1977, Evans sociated with these two extremes have the most con- 1986, Forsythe 1987): they have structural features that trasting traits in Southwood's (1988) templet and in may be suitable or adapted to perform in several dif- other equivalent schemes (see e.g., Fig. 8 in Southwood ferent habitats, such as the trade-off between wedge- 1988). Thus, in the scheme proposed by Greenslade pushing vs. running specialists, re¯ected in the size of (1983), highly favorable and unpredictable habitats are the metatrochanters and the diameter of the hind femora typical of r-selected species, while highly unfavorable (Evans and Forsythe 1984, and references therein), or and predictable habitats are typical of A-selected spe- the morphological characters linked to diurnal vs. noc- cies (adversity selection). More important than the def- turnal species (Bauer 1985, Bauer and Kredler 1993, inition of the types of selection is the distribution of Ribera et al. 1999b). Only in some cases was the strong the individual morphological and life trait characters effect of environmental constraints recognized, such as along the environmental gradient, which can be used in digger or arboricolous species (Thiele 1977). In our to characterize and predict the functional diversity of study we did ®nd very signi®cant relationships between the ground-beetle assemblages. some of the morphological and life traits of the species Janzen (1985) raised the question of how species that of assemblages of ground beetles and the habitats in had evolved in a particular evolutionary context could which they occur, demonstrating the match between manage to persist when they extend their ranges and habitat characteristics and species traits. Some of these encounter different environments and species assem- relationships were in agreement with the predictions of blages. All ground beetles included in this study have the habitat templet theory, in particular with reference rather widespread ranges in at least the western Pale- to size and dispersal power. arctic, and it is likely that they originated in different One of the quantitatively most important relation- areas, within various communities and environmental ships was that of larger species with less managed, pressures. In spite of that, the assemblages they form upland sites. The detrimental effect that management show some functional traits not randomly distributed has on the larger species has been reported a number in relation to the main environmental trends, which of times (Siepel 1990, Blake et al. 1994, 1996). The April 2001 EFFECTS OF DISTURBANCE ON SPECIES TRAITS 1127 effect can be partly attributed to the preference of the ence of refugia in the surrounding areas (Desender large species of Carabus for undisturbed sites, and of 1982). the many small species of Bembidion for highly dis- The association of Collembola feeders with agricul- turbed sites. Species of Carabus may be absent in man- tural ®elds has been reported for different groups, and aged sites because of the strong temporal variability in has been attributed to the abundance of prey (e.g., Pol- productivity and energy available (Blake et al. 1994). let and Desender 1987). Collembola predators are di- Another possible reason is that large species tend to urnal, and tend to have metallic body and/or legs (Ri- be ¯ightless, with a limited dispersal power in a mosaic bera et al. 1999b). Plant eaters were also found to be landscape (Den Boer 1970, 1990a). mostly associated with highly disturbed sites. This as- The restricted occurrence of species with poor dis- sociation is also apparent when looking at the mor- persal abilities in highly disturbed sites is a prediction phological variables, with species with long trochanters of the habitat templet theory (Southwood 1977, 1988) and wide femurs strongly associated with more dis- (see also the predictions based on a simulation model turbed sites. Such characters are typical of plant and by Travis and Dytham 1999). Species in highly dis- seed-eaters (Ribera et al. 1999b). turbed sites are supposed to have an elevated risk of Daily activity had an almost zero correlation with local extinction, with the need for good dispersal ca- the ordination axis, despite being one of the life traits pabilities for the frequent colonization of ``emptied'' most associated with the morphology of the species patches. Thus, according to Southwood (1962) winged (Ribera et al. 1999b). Diurnal and nocturnal species species are more frequent in temporary habitats to al- seem to be distributed independently of the main en- low dispersal to favorable sites when conditions turn vironmental characteristics. However, there were some dif®cult. There is some previous evidence that ground differences in the distribution of the color of the body, beetles (and other terrestrial arthropods) in highly het- which is strongly associated with diel activity. Metallic erogeneous and fragmented habitats show a higher dis- species had intermediate values, with pale species persal power, as measured with the higher frequency mostly associated with disturbed, highly managed low- of macropterous or dimorphic species in comparison land sites, and black species mostly associated with with more homogeneous habitats (e.g., Den Boer less disturbed upland sites. This ordination differs from 1990b, De Vries et al. 1996). Aukema et al. (1996) the relationship of color with diel activity, in which found that the winged forms of a dimorphic species there is a strong dichotomy between metallic (diurnal) (Pterostichus melanarius) were more frequent in re- and black and pale species (nocturnal). The relationship cently established populations, in comparison with old between color and management could be due to the populations. In cereal ®elds with strong pesticide treat- association of pale species with interstitial or burrow- ment, Sanderson (1994) found that Trechus obtusus ing habits, such as in Clivina fossor, or some species (brachypterous) was much less abundant that T. quad- of Trechus (in particular T. micros) (Lindroth 1945, ristriatus (macropterous), although the author also con- Desender 1983, Luff 1998). Highly disturbed agricul- sidered the alternative explanation that these results tural sites had a higher proportion of bare ground (Table were due to differences in the relative abundance of 6 and 10), and tillage may provide favorable micro- their respective preys. In our study, wing development habitats for these species (Desender 1983). was the life trait variable with the highest correlation with the ®rst ordination axis, with brachypterous spe- CONCLUSIONS cies strongly associated with less managed, upland sites, and macropterous or dimorphic species with high- We found a strongly signi®cant correlation between ly disturbed lowland sites. the functional (i.e., morphological and life history) In addition to the preceding trends predicted by traits of the species and the main environmental gra- Southwood et al. (1977, 1988) and Townsend and Hil- dient of their habitats (in our case disturbance as mea- drew (1994), there were other signi®cant relationships sured with a land management index, and stress or between the morphological and life trait characteristics habitat adversity as measured with elevation and veg- of the species and the RLQ ordination axis. Species etation structure). This common response to the same breeding in summer were strongly associated with less environmental factors can be used to precisely de®ne disturbed sites, and with high elevation. This could be functional groups among the species studied, as well due to a limitation of the active season in high elevation as the functional diversity of a given assemblage. With sites for climatic reasons, but also to a strong summer the use of RLQ analysis, differences in land use can peak in the disturbance of agricultural ®elds, because thus be directly related to differences in functional di- of an increase of agricultural practices. The association versity, instead of ®rst to taxonomic diversity and, only of species overwintering as adults with highly dis- indirectly, to the functional traits of the species. This turbed sites could have the same underlying reason, opens the possibility of the use of RLQ scores in con- i.e., destruction of larval overwintering sites by man- servation management, to monitor and predict the ef- agement practices. In intensively managed or disturbed fects of changes in land use. Some more speci®c pre- ®elds overwintering is known to be related to the pres- dictions of the habitat templet theory, namely a smaller 1128 IGNACIO RIBERA ET AL. Ecology, Vol. 82, No. 4 size and higher dispersal powers in more disturbed, less leoptera, Carabidae) from a pasture ecosystem. I. Adult and stressed sites, were corroborated. larval abundance, seasonal and diurnal activity. Pedobiol- ogia 25:157±167. ACKNOWLEDGMENTS Desender, K. 1986. On the relation between abundance and ¯ight activity in Carabid beetles from a heavily grazed We thank Davy McCracken and Tony Waterhouse in SAC, pasture. Journal of Applied Entomology 102:225±231. and our colleagues Vicky Abernethy, Aileen Adam, and Kev- De Vries, H. H., P. J. den Boer, and Th. S. van Dijk. 1996. in Murphy of the University of Glasgow for their collabo- Ground beetle species in heathland fragments in relation ration in the development of the study and their comments to survival, dispersal, and habitat preference. Oecologia to the manuscript. We also thank all the farmers who kindly 107:332±342. allowed access to their land. Bernhard Statzner and Alfried DoleÂdec, S., and D. Chessel. 1994. Co-inertia analysis: an Vogler provided most useful comments to an earlier version alternative method for studying species±environment re- of the work, as well as Mick Eyre and two anonymous ref- lationships. Freshwater Biology 31:277±294. erees. We ®nally thank the comments and the editorial help DoleÂdec, S., D. Chessel, C. J. F. Ter Braak, and S. Champely. of Andrew D. Taylor. The Scottish Agricultural College re- 1996. Matching species traits to environmental variables: ceived ®nancial support from the Scottish Of®ce Agriculture, a new three-table ordination method. Environmental and Environmental and Fisheries Department, now the Scottish Ecological Statistics 3:143±166. Executive Rural Affairs Department. Downie, I. S., V. J. Abernethy, G. N. Foster, D. I. McCracken, LITERATURE CITED I. Ribera, and A. Waterhouse. 1998. Spider biodiversity on Scottish agricultural land. Pages 311±317 in P. A. Selden, Abernethy, V. J., D. I. McCracken, A. Adam, I. Downie, G. editor. 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APPENDIX A Table R of environmental characteristics of the sites included in the study, Table L with species composition of the ground-beetle assemblages of the sites studied, and Table Q with species morphological and life trait characteristics, along with associated references, are available in the ESA's Electronic Data Archive: Ecological Archives E082-012. Ecological Archives E082-012-A1 file://localhost/Users/Casa/Desktop/appendix-A.htm

Ecological Archives E082-012-A1

Ignacio Ribera, Sylvain Dolédec, Iain S. Downie, and Garth N. Foster. 2001. Effect of land disturbance and stress on species traits of ground beetle assemblages. Ecology 82:1112-1129.

Table R (Appendix A): Environmental characteristics of the sites included in the study, with the land use, National UK Grid Square (1 x 1 km), name of the area, and sampling year. See Fig. 1 for the location of the main areas. See Table 1 for the codes of the environmental variables.

No.Code Land use Grid Area Sampling year Texture Org pHAvail P Avail K Moist Bare Litter Bryophyte Plants/m2 Canopy height Stem density Biom 0-5 Biom 5+ Repro biom Elevation Management 1gs21 grazing and silage NS3723 Auchincruive 1996 6 8.7 5.8 17.0 292 31.7 0.44 4.33 0.00 200.22 18.89 85.11 6.55 6.51 0.30 55 15 2gs22 grazing and silage NS3723 Auchincruive 1996 6 11.3 6.0 44.0 204 33.1 9.56 6.33 0.00 9.00 9.22 47.22 4.28 0.73 0.02 55 12 3eg11 extensive grass NY0392 Ae 1997 4 20.3 4.5 1.6 240 39.4 0.67 1.00 1.78 289.67 16.60 155.44 9.50 4.49 0.24 220 1 4eg12 extensive grass NY0491 Ae 1997 4 16.5 5.3 2.0 100 39.0 0.33 2.00 4.00 182.33 13.49 142.44 7.60 0.79 0.29 230 5 5eg13 extensive grass NY0491 Ae 1997 5.5 15.0 4.9 2.6 144 44.0 7.33 1.56 7.11 76.89 18.38 103.44 8.15 1.39 0.09 195 5 6eg14 extensive grass NY0392 Ae 1997 2 22.2 4.4 2.0 180 46.7 1.33 13.00 13.56 88.89 51.67 39.89 6.47 12.74 0.06 230 1 7yh71 young heather NN6386 Dalwhinnie 1996 1 66.4 3.8 23.0 200 66.4 11.00 7.78 24.00 189.67 20.44 13.56 13.21 19.51 0.11 390 3 8oh72 old heather NN6386 Dalwhinnie 1996 1 62.7 3.8 20.0 218 66.4 3.56 3.11 66.67 77.00 38.44 5.22 20.46 45.13 0.11 385 1 9bh73 burnt heather NN6386 Dalwhinnie 1996 2 30.0 3.9 21.0 188 54.3 30.11 92.44 0.00 0.33 1.44 3.56 0.27 0.00 0.00 390 7 10gr11 grass NY0585 Ae 1997 5 14.6 5.6 22.0 84 36.8 4.78 4.11 0.11 46.22 7.98 73.67 9.14 1.31 0.03 61 8 11gr12 grass NY0585 Ae 1997 4 10.7 5.3 58.0 76 28.6 4.67 2.33 2.44 57.44 20.00 52.89 4.07 5.79 0.12 62 16 12sp13 spring barley NY0485 Ae 1997 4 7.0 6.3 40.0 108 24.5 66.67 3.00 0.67 267.11 63.71 10.67 1.70 21.01 10.22 62 19 13ww14 winter wheat NY0485 Ae 1997 5 7.8 6.6 80.0 60 26.6 57.78 12.89 2.78 333.89 78.42 9.22 2.85 48.81 17.34 63 17 14gr15 grass NY0486 Ae 1997 4 7.5 5.8 49.0 128 28.2 10.89 1.78 1.44 116.56 16.73 50.67 5.31 5.47 0.15 62 16 15se16 set aside-grass NY0385 Ae 1997 4 6.8 7.1 98.0 496 25.4 15.78 11.56 0.44 239.00 29.96 7.22 2.53 6.90 1.64 70 12 16fd17 fodder beet NY0385 Ae 1997 4 8.9 5.9 160.0 164 25.9 72.44 1.00 0.00 3.78 18.42 0.67 0.61 4.21 0.10 70 16 17he61 heather NO6380 Glensaugh 1997 1 93.1 3.4 12.0 100 78.8 1.11 76.67 2.78 76.00 36.38 7.89 5.46 45.53 0.04 425 1 18gr62 grass NO6579 Glensaugh 1997 1 30.7 6.5 6.8 72 49.7 0.22 0.89 1.89 151.67 5.89 202.00 10.59 0.15 0.03 265 7 19he63 heather NO6581 Glensaugh 1997 1 94.2 3.6 9.0 72 90.3 1.22 10.67 57.22 21.22 26.80 3.00 19.68 34.93 0.06 430 1 20gr64 grass NO6678 Glensaugh 1997 4 8.7 5.7 84.0 108 25.1 7.11 6.22 0.67 403.11 19.53 66.67 6.78 10.69 0.93 170 15 21gg65 gorse + grass NO6678 Glensaugh 1997 2.5 17.4 4.2 4.0 164 36.6 1.33 1.33 14.78 933.89 10.24 123.00 15.24 1.54 0.45 170 1 22yc51 young conifer woodland NN3528 Crianlarich 1995 6 29.3 5.0 7.1 86 65.8 3.11 3.33 18.33 105.22 36.84 65.22 8.31 9.84 1.28 165 1 23oc52 old conifer woodland NN3528 Crianlarich 1995 6 12.3 4.9 5.4 40 46.5 40.89 29.56 26.44 12.56 3.56 19.70 2.83 0.22 0.00 165 4 24wh51 wet heather moorland NN3826 Crianlarich 1995 6 27.1 4.0 5.2 96 52.7 6.89 3.11 17.44 178.78 9.82 39.00 14.22 2.38 0.40 330 1 25ug51 upland grassland - wet boggy flush NN3530 Crianlarich 1995 6 21.9 4.6 2.2 56 64 21.44 3.78 24.44 162.89 9.93 74.44 4.82 1.74 0.08 270 1 26dg52 dry upland grassland NN3530 Crianlarich 1995 4 13.5 4.3 1.8 108 45.1 2.33 4.78 21.67 154.89 22.49 85.78 7.67 9.71 0.06 270 1 27ig53 improved upland grassland NN3530 Crianlarich 1995 4 15.2 5.2 3.3 118 45.1 0.00 1.44 22.78 313.56 7.47 178.00 11.63 2.12 0.34 360 4 28ug54 upland grassland - flush NN3825 Crianlarich 1995 4 27 4.5 5.5 106 46.3 9.89 4.56 40.00 140.56 15.49 47.78 6.20 3.42 0.34 165 1 29dg55 dry upland grassland NN3826 Crianlarich 1995 6 10.6 5.6 43 132 34 0.56 3.89 11.33 135.33 23.98 174.67 8.33 8.12 0.07 180 4 30uh51 upland bare peat NN3633 Crianlarich 1995 2 89.2 3.7 17 108 85 6.67 8.89 40.56 124.11 8.40 27.70 15.07 2.09 0.02 470 1 31ug51 upland grassland - wet with Nardus NN3632 Crianlarich 1995 2 31.6 4.9 3.2 88 76.3 0.00 1.78 16.22 283.44 16.33 78.78 14.09 6.53 0.29 500 1 32bg52 base-rich upland grassland NN3733 Crianlarich 1995 4 44.8 4.3 3.3 72 63.2 1.21 4.48 25.00 113.22 10.82 65.20 13.46 5.24 0.11 750 1 33dg53 dry upland grassland with bracken NN3826 Crianlarich 1995 6 22.6 4.2 1.9 120 55.7 1.11 17.78 35.00 138.67 37.82 84.11 14.32 15.81 0.27 280 4 34gz51 grazing pasture NN3528 Crianlarich 1995 6 9 5.5 7.8 64 33.6 0.00 1.44 0.00 46.78 5.04 183.78 9.56 0.18 0.02 165 9 35si52 silage and grazing NN3528 Crianlarich 1995 6 8.8 5.2 8 40 33.9 2.78 7.78 0.00 135.67 11.76 100.78 3.66 3.81 0.32 165 12 36wt53 wet tussocky grassland NN3825 Crianlarich 1995 1 38.7 4.6 4.4 116 78.6 0.22 18.00 22.22 198.67 30.49 31.11 4.90 12.43 0.57 155 4 37wg54 wet grassland - mainly Myrica NN3825 Crianlarich 1995 1 85.2 4.4 6.4 56 91.8 1.67 10.89 47.22 104.11 18.58 45.11 9.77 8.59 0.21 155 1 38wb61 winter barley NO6776 Glensaugh 1997 5 5.5 6.5 156.0 112 21.2 48.33 27.56 1.44 293.33 54.31 6.89 2.56 37.54 8.83 125 16 39gr62 grass NO6776 Glensaugh 1997 4 8.0 5.4 55.0 180 21.9 9.44 2.44 0.89 106.22 13.47 57.00 7.30 3.66 0.25 163 12 40wb31 winter barley NT5577 East Lothian 1996 7 5.5 6.6 43.0 86 19.3 61.11 5.89 0.22 459.33 76.56 9.89 3.75 65.74 26.76 25 20 41ww32 winter wheat NT5577 East Lothian 1996 7 6.7 7.1 41.0 104 22.1 55.56 8.89 0.00 351.11 73.33 9.44 5.04 78.44 17.59 30 18 42so33 spring oil-seed rape NT5776 East Lothian 1996 5 6.7 6.8 380.0 220 21.8 70.00 18.33 0.00 95.33 54.33 2.56 1.41 17.28 8.93 70 17 43wr34 winter oil-seed rape NT5776 East Lothian 1996 7 6.4 7.1 328.0 100 23.3 60.56 37.78 0.00 66.11 102.56 1.00 2.75 86.15 20.61 65 17 44gz81 grazing NH8479 Tain 1996 4 8.5 5.8 56.0 244 25.7 1.78 1.00 0.33 150.67 5.56 129.56 7.96 0.43 0.08 30 9 45sp82 spring barley NH8480 Tain 1996 3 3.8 5.6 76.0 88 13.3 67.78 3.44 3.11 379.00 57.33 9.11 2.79 47.66 17.41 30 16 46se83 set aside NH8479 Tain 1996 4 4.6 5.9 72.0 80 17.7 2.22 13.33 0.00 356.67 28.67 48.89 6.94 8.84 1.17 30 8 47re84 reseed grazing NH8479 Tain 1996 4 4.6 6.0 89.0 140 15.9 0.56 2.33 0.00 97.11 9.67 106.22 8.34 1.36 0.15 30 12 48ww85 winter wheat NH8579 Tain 1996 4 6.0 5.8 82.0 160 20.1 60.56 5.44 8.00 404.44 74.78 7.22 4.74 74.67 18.91 30 17

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49wb86 winter barley NH8579 Tain 1996 4 4.4 5.9 46.0 80 17.1 50.00 1.78 4.22 391.11 56.89 8.78 2.09 44.21 16.32 30 17 50wo87 winter oats NH8478 Tain 1996 4 3.8 6.0 73.0 68 16.0 55.56 4.44 5.11 363.00 90.00 7.22 3.17 72.58 16.96 30 16 51sp41 spring barley NN9522 Crieff 1995 5.5 6.5 6.2 65 104 20.2 76.11 8.44 0.00 282.56 40.93 7.78 1.73 32.97 16.10 45 17 52ww42 winter wheat NN9523 Crieff 1995 6 5.9 5.9 89 122 16.8 68.89 26.56 0.00 349.89 36.40 9.22 3.06 63.95 32.94 50 16 53wb41 winter barley NN9424 Crieff 1995 5.5 5 6.0 82 84 17.4 75.56 10.56 0.56 216.89 30.53 6.33 1.85 23.58 17.21 140 19 54wb42 winter barley NN9524 Crieff 1995 5.5 4.6 6.3 86 108 17.6 80.00 13.22 2.56 216.11 30.20 8.56 1.71 20.27 8.59 130 19 55sp41 spring barley NN9522 Crieff 1995 5.5 8.9 6.4 49 56 27 67.78 10.44 0.33 222.89 35.67 9.33 1.42 28.38 14.72 35 17 56so42 spring oilseed rape NN9522 Crieff 1995 5.5 9.3 5.7 48 100 26.9 60.56 19.22 0.00 205.78 52.58 8.44 1.16 18.82 28.19 35 16 57so43 spring oilseed rape NN9522 Crieff 1995 5.5 9.6 5.3 54 172 26.9 67.78 2.78 0.33 254.44 75.09 7.11 1.50 29.12 57.40 35 16 58oc41 old conifer woodland NN9325 Crieff 1995 6 13.7 4.3 3.1 66 39.1 0.78 12.00 28.89 53.00 12.98 25.30 6.07 1.27 0.11 240 1 59gh41 gorse at edge of heather moorland NN9225 Crieff 1995 6 15.8 4.5 6.8 98 35.8 7.44 9.22 16.67 49.78 17.93 129.22 11.72 14.89 0.54 230 1 60go41 gorse within grazing pasture NN9324 Crieff 1995 6 10.8 5.3 17 120 31.3 3.22 2.67 7.44 43.33 21.31 99.78 9.56 2.09 0.55 200 3 61wh41 wet heather moorland NN9225 Crieff 1995 6 14.3 4.2 4 72 58.4 0.33 2.22 58.89 82.33 18.40 9.00 19.01 21.52 0.65 235 1 62dh42 dry heather moorland newly burned NN9225 Crieff 1995 6 16.8 4.3 1.6 80 41.2 42.33 10.00 7.22 63.56 5.04 16.89 6.30 0.81 0.52 230 6 63ha91 hay NC6563 Skerray 1996 4 13.4 6.0 29.0 88 37.6 4.44 5.56 0.67 515.78 30.22 61.33 6.85 7.35 1.94 30 5 64fr9A forage rape NC6762 Skerray 1996 4 14.0 5.7 30.0 112 28.7 71.11 5.56 0.00 13.00 40.33 8.22 1.17 9.94 0.29 20 13 65gz92 grazing NC6663 Skerray 1996 4 16.7 5.1 6.0 96 36.6 0.00 1.22 36.11 269.00 17.67 107.33 14.90 2.34 0.22 35 3 66re93 reseed grazing NC6662 Skerray 1996 6 33.6 6.3 15.0 64 58.9 1.11 0.89 1.33 59.78 8.78 96.56 6.67 1.00 0.12 20 11 67we94 wet grazing NC6662 Skerray 1996 6 30.5 5.0 6.4 92 60.8 1.22 4.22 7.00 208.56 55.56 37.22 6.25 24.58 0.95 20 4 68re95 reseed grazing NC6762 Skerray 1996 4 18.5 5.3 8.0 128 35.7 0.11 0.89 3.67 145.89 4.56 158.56 8.34 0.08 0.06 35 4 69ro96 rough grazing NC6762 Skerray 1996 3.5 13.9 5.3 10.0 224 25.0 0.00 1.67 26.67 473.56 6.22 163.00 16.64 0.43 0.13 60 2 70he97 heather moor NC6762 Skerray 1996 4 37.1 4.4 22.0 216 63.0 1.89 1.89 39.44 225.00 8.11 12.00 23.05 8.99 0.23 70 2 71tu98 turnips NC6762 Skerray 1996 4 10.5 5.4 24.0 68 24.1 47.78 21.67 0.00 20.67 13.56 7.89 1.43 2.40 0.02 40 10 72fr99 forage rape NC6762 Skerray 1996 2 43.3 4.8 5.2 104 48.4 41.67 1.78 0.00 36.56 21.33 8.56 1.67 5.80 0.19 20 9 73si41 silage and grazing NN9423 Crieff 1995 5.5 6.6 6.0 99 152 19 10.44 3.67 1.56 79.33 12.58 35.67 7.31 3.45 0.21 95 12 74gz42 grazing pasture NN9423 Crieff 1995 6 6.8 5.7 111 116 19.4 10.56 3.67 4.83 161.44 6.47 38.67 5.01 1.55 0.39 90 10 75gz43 grazing pasture NN9424 Crieff 1995 5.5 10.9 5.3 53 140 23.8 2.00 4.22 1.50 122.44 7.20 94.11 8.82 0.44 0.04 145 7 76gz44 grazing pasture - 'rough' wet area NN9424 Crieff 1995 5.5 10.5 5.7 9.8 196 27.2 6.33 5.11 4.44 58.67 7.67 108.56 7.70 1.94 0.02 170 3 77gz41 grazing pasture - wet 'marshy' area NN9425 Crieff 1995 2 20.1 5.5 10 140 50.2 0.67 0.78 6.00 190.44 11.53 116.89 9.35 2.42 0.72 230 6 78gz42 grazing pasture - drier area NN9425 Crieff 1995 5.5 12.3 5.9 3.7 130 31.3 0.33 1.33 0.33 195.00 5.42 84.56 7.63 0.13 0.34 235 6 79gz41 grazing pasture NN9424 Crieff 1995 5.5 11 5.6 26 188 27.5 3.67 3.11 0.89 28.78 3.93 92.33 5.47 0.21 0.04 215 9 80gz42 grazing pasture NN9424 Crieff 1995 5.5 11 5.7 19 92 29.3 0.56 0.89 1.28 166.67 6.36 114.56 7.31 0.29 0.37 220 8 81gz41 grazing pasture - area of rushes NN9422 Crieff 1995 4 28.2 5.2 5 164 44.5 5.00 16.67 0.00 79.44 16.18 52.22 4.17 14.46 0.19 35 10 82gz42 grazing pasture NN9422 Crieff 1995 5.5 13 5.4 15 84 29.6 1.33 1.44 0.67 41.78 3.67 104.56 6.27 0.05 0.04 35 10 83se41 setaside NN9523 Crieff 1995 6 6.1 6.3 99 156 20.6 43.33 27.78 3.00 463.56 2.00 13.22 2.06 0.15 0.40 40 12 84se42 setaside NN9523 Crieff 1995 6 6.6 5.8 48 136 21.3 43.33 36.67 0.78 360.22 4.64 9.22 1.67 0.68 0.20 50 12 85gr61 grass NO6874 Glensaugh 1997 5 6.0 5.9 49.0 116 20.3 10.78 16.22 0.67 432.22 41.22 26.33 2.79 13.99 1.93 70 12 86sp62 spring barley NO6874 Glensaugh 1997 6 9.3 6.2 36.0 108 27.5 60.00 2.89 1.33 189.22 51.38 8.56 1.80 22.05 9.48 67 16 87so63 spring oil seed rape NO6974 Glensaugh 1997 5 6.7 6.1 51.0 96 23.8 62.22 7.89 0.67 158.89 33.56 3.78 1.27 13.13 3.83 67 16

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Ecological Archives E082-012-A2

Ignacio Ribera, Sylvain Dolédec, Iain S. Downie, and Garth N. Foster. 2001. Effect of land disturbance and stress on species traits of ground beetle assemblages. Ecology 82:1122-1129.

Table L (Appendix B): Species composition of the ground beetle assemblages of the sites studied. The number of specimens of each species in each site is given. See Table Q for the codes of the species, and Table R for the codes of the sites. Numbers of species (S) and of specimens (N) are also given (excluding species occurring in less than 5 sites, see Methods).

1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65 66 67 68 69 70 71 72 73 74 75 76 77 78 79 80 81 82 83 84 85 86 87 No Code gs21 gs22 eg11 eg12 eg13 eg14 yh71oh72bh73gr11 gr12 sp13 ww14 gr15 se16 fd17 he61 gr62 he63 gr64 gg65yc51 oc52 wh51 ug51dg52ig53 ug54dg55uh51ug51bg52dg53gz51 si52 wt53wg54 wb61 gr62 wb31 ww32 so33 wr34 gz81 sp82 se83 re84 ww85 wb86 wo87 sp41 ww42 wb41 wb42 sp41 so42 so43 oc41 gh41go41wh41 dh42ha91 fr9A gz92 re93 we94 re95 ro96 he97 tu98 fr99 si41 gz42 gz43 gz44 gz41 gz42 gz41 gz42 gz41 gz42 se41 se42 gr61 sp62 so63 agon 1fuli 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 86 1 0 0 0 0 0 0 5 4 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 11 3 0 0 11 2 0 0 0 0 0 agon 2muel 51 59 0 1 29 0 0 0 0 27 18 44 29 50 82 57 0 0 0 3 0 0 0 0 0 1 0 9 0 0 0 0 0 92 63 0 0 2 3 3 0 0 1 5 24 0 0 1 1 0 13 82 16 20 2 5 3 0 2 1 0 3 20 9 0 53 0 33 0 0 0 4 12 32 0 8 76 56 23 22 42 38 327 385 3 14 2 amar 3aene 25 2 0 1 1 1 0 0 0 1 0 0 0 7 2 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 amar 4apri 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 4 2 2 2 30 1 2 2 0 2 1 0 1 0 0 4 21 1 6 77 0 0 0 0 2 1 0 0 0 0 0 0 0 0 0 0 1 1 0 0 0 0 1 0 4 42 34 3 4 7 amar 5auli 0 0 0 0 0 0 0 0 0 0 0 1 0 0 0 0 0 0 0 0 1 0 0 0 0 0 0 2 27 0 0 0 0 0 0 0 0 0 0 0 0 1 0 0 0 0 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 7 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 0 0 0 0 amar 6bifo 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 9 0 0 0 0 0 0 0 0 1 0 0 0 0 0 0 0 0 1 0 0 0 0 0 5 16 10 4 2 0 1 4 45 0 1 0 0 0 0 0 0 0 0 44 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 5 1 1 5 amar 7comm 1 2 3 1 2 0 0 0 0 0 0 0 0 0 2 0 0 4 0 9 34 0 0 0 0 2 0 0 6 0 0 0 36 6 3 0 0 0 1 0 0 0 0 1 0 0 0 0 0 1 2 0 0 0 1 2 0 0 6 2 0 1 13 0 23 0 1 7 4 0 0 0 0 2 2 0 4 2 4 3 1 9 4 1 0 0 0 amar 8eury 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 1 0 0 0 0 0 0 0 0 0 0 2 0 0 5 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 3 3 0 0 0 amar 9fami 0 0 0 0 0 0 0 0 0 1 6 0 0 8 5 0 0 7 0 41 6 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 10 1 11 22 7 9 0 2 1 1 3 2 4 2 3 1 1 1 1 1 0 2 1 0 1 0 0 0 0 0 2 7 0 0 1 1 0 0 0 0 0 0 0 0 1 0 2 3 1 0 amar 10luni 0 0 18 0 0 9 0 1 0 0 0 0 0 0 0 0 0 0 0 3 0 0 0 0 0 1 0 0 2 0 0 0 24 0 0 0 0 0 0 0 0 0 0 0 0 11 2 1 1 0 3 4 0 0 0 0 0 0 0 0 1 0 1 0 4 0 1 8 1 0 1 0 5 1 0 0 0 0 4 1 0 0 0 1 0 0 0 amar 11pleb 40 4 5 4 1 2 0 0 0 5 8 4 5 50 169 1 0 2 0 117 10 0 0 0 0 0 0 0 1 0 0 0 0 0 0 0 0 140 70 5 2 2 3 358 27 102 147 9 61 31 12 126 14 17 24 13 8 0 31 27 1 9 0 0 0 0 0 2 0 0 0 0 102 345 7 16 37 57 201 43 64 184 889 524 14 9 11 anch 12dors 4 0 0 0 0 0 0 0 3 0 1 28 71 3 11 1 0 0 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 7 1 7 67 1 1 0 27 5 0 2 6 6 21 53 155 201 28 53 15 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 10 8 0 1 0 0 0 0 0 4 20 30 66 13 49 asap 13flav 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 0 0 0 0 0 0 0 0 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 0 0 1 1 0 0 0 0 0 bemb 14aene 356 626 0 0 0 0 0 0 0 16 1 0 33 9 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 5 200 0 0 0 0 0 0 0 0 0 2 1 6 11 11188 264 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 4 0 5 15 54 0 5 935 679 13 58 2 0 0 bemb 15brux 0 0 0 0 0 0 0 0 0 0 0 48 0 0 0 29 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 1 1 1 0 0 0 0 0 0 0 0 10 0 0 0 0 0 0 0 1 0 0 0 0 1 0 0 0 0 0 0 0 0 0 0 bemb 16gutt 2 9 1 0 0 0 0 0 0 39 6 47 16 11 17 76 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 2 0 50 87 1 3 0 1 0 0 1 3 0 83 30 126 128 0 72 117 1 5 3 1 0 24 0 0 211 34 0 0 1 0 6 3 21 5 2 30 21 8 33 88 52 39 119 12 0 13 bemb 17lamp 96 148 0 1 67 0 0 0 0 2 8 6 1 1 38 113 0 0 0 12 0 0 0 0 9 6 1 1 1 0 0 0 1 0 0 0 0 1 4 9 93 41 0 7 5 0 1 0 0 0 126 25 150 226 0 4 6 0 0 14 0 16 0 0 0 0 0 0 0 0 0 0 4 9 11 7 2 3 103 29 5 5 22 19 1 9 14 bemb 18mann 0 0 0 1 10 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 0 10 0 0 0 0 0 0 0 0 0 0 2 bemb 19obtu 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 10 5 0 25 0 0 0 0 0 0 0 85 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 30 0 0 0 0 1 0 0 15 9 1 0 0 6 bemb 20tetr 0 1 0 0 0 0 0 0 0 0 0 82 13 3 12 141 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 0 1 0 0 4 74 1 1 31 18 27 2 0 4 10 0 13 1 0 0 0 0 0 0 2 0 0 0 0 0 0 0 1 0 0 0 0 0 0 0 0 0 0 0 1 1 2 1 brad 21harp 0 0 0 0 0 3 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 2 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 4 0 0 1 2 3 0 2 28 0 2 0 2 5 0 0 0 0 0 0 0 0 1 0 0 0 0 0 0 brad 22rufi 0 0 0 0 0 0 5 1 0 0 0 0 0 0 0 0 2 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 1 0 0 0 0 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 cala 23fusc 0 0 35 106 3 7 0 0 0 0 0 0 0 0 0 0 0 408 0 309 399 0 0 0 1 11 136 0 31 0 0 0 12 3 0 0 0 5071158 0 0 551 1 48019551100 227 41 72 180 0 0 0 0 0 0 0 0 12 8 0 101 38 0 11 2 0 167 344 20 22 1 0 0 4 21 3 5 39 49 0 0 0 0 111 180 345 cala 24mela 8 32 31 28 0 6 50 1 96 5 37 445 268 12 111 61 3 268 0 22 112 0 0 7 0 0 87 0 29 0 0 3 0 0 20 0 0 150 49 3 0 141 0 46 318 88 169 338 48 134 0 0 0 0 0 0 0 0 49 1 0 83 0 0 0 0 0 1 19 188 0 0 0 0 0 1 9 29 7 44 0 1 0 0 131 88 188 cala 25micr 0 0 0 0 0 0 6 23 19 0 0 0 0 0 0 0 53 0 13 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 14 31 0 0 4 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 0 0 0 0 0 0 0 0 cara 26arve 0 0 13 0 0 32 0 0 5 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 11 4 4 0 0 0 1 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 1 45 0 0 1 0 0 0 0 3 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 cara 27glab 0 0 0 0 0 0 4 5 8 0 0 0 0 0 0 0 5 0 1 0 0 0 0 0 0 2 0 0 0 2 1 2 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 7 1 0 3 1 0 0 0 0 0 0 0 0 0 0 0 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Ecological Archives E082-012-A3

Ignacio Ribera, Sylvain Dolédec, Iain S. Downie, and Garth N. Foster. 2001. Effect of land disturbance and stress on species traits of ground beetle assemblages. Ecology 82:1112-1129.

Table Q (Appendix C): Species morphological and life trait characteristics. Nomenclature of the species follows Kryzhanovskij et al. (1995) and Lindroth (1985, 1986) (names of common use in UK are given in brackets). Codes of the species are those used in Figure 3. See Table 2 for the codes of the variables. Values of variables LYW to LFW are the residuals of the log10 transformed regression with LTL (logarithm of the total length, see Methods). Life trait data obtained from Lindroth (1945, 1974), Huizen (1977), Thiele (1977), Luff (1978), Jones (1979), Hengeveld (1980), Houston (1981), Desender (1982, 1983), Desender et al. (1984), Desender and Pollet (1985), Pollet and Desender (1987), Pollet et al. (1987), Brandmayr (1990), Den Boer and Den Boer-Daanje (1990), Desender and Alderweirldt (1990), Kegel (1990), Larochelle (1990), Bauer and Kredler (1993), Sydmonson et al. (1996), Luff (1998), and Martin Luff (personal communication 1997, see Methods). Estimated data for which there was no available published information are noted with "?".

SPECIES CODE LYW LAL LPW LPH LEW LFL LTR LRL LFW LTLCLG CLB WIN PRS OVE FOA DAY BRE EME ACT 1 Agonum fuliginosum (Panzer, 1809) agon fuli -0.03 0.10 -0.03 0.00 0.01 0.05 0.05 0.06 0.01 1.82 2 2 2 1 1 2 2? 1 3 1 2 Agonum muelleri (Herbst, 1784) agon muel -0.02 0.07 -0.02 -0.01 0.02 0.02 0.03 0.01 0.04 1.92 2 3 3 1 1 2 2 1 2 2 3 Amara aenea (De Geer, 1794) amar aene -0.06 -0.14 0.10 0.03 0.04 -0.06 0.05 -0.04 0.05 1.90 1 3 3 3 1 3 1 1 2 2 4 Amara apricaria (Paykull, 1790) amar apri -0.04 -0.11 0.06 0.01 0.02 -0.09 -0.01 -0.10 0.06 1.94 1 1 3 3 2 3 2 3 2 2 5 Curtonotus aulicus (Panzer, 1797) (=Amara aulica) amar auli 0.00 -0.07 0.06 0.03 0.01 -0.04 0.05 -0.03 0.09 2.13 1 1 3 3 2 3 2 3 2 2 6 Amara bifrons (Gyllenhal, 1810) amar bifo -0.10 -0.06 0.08 0.02 0.02 -0.06 0.03 -0.06 0.08 1.85 1 1 3 3 2 3 2 3 2 2 7 Amara communis (Panzer, 1797) amar comm -0.09 -0.09 0.13 0.03 0.03 -0.07 0.01 -0.07 0.03 1.91 2 2 3 3 2 3 1 1 2 1 8 Amara eurynota (Panzer, 1797) amar eury -0.07 -0.13 0.13 0.03 0.06 -0.04 0.05 -0.01 0.07 2.06 1 3 3 3 2 3 1 3 2 1 9 Amara familiaris (Duftschmid, 1812) amar fami -0.07 -0.09 0.10 0.02 0.03 -0.06 0.02 -0.07 0.04 1.87 1 2 3 3 1 3 1 1 2 1 10 Amara lunicollis Schiödte, 1837 amar luni -0.23 -0.10 0.11 0.01 0.02 -0.07 0.00 -0.06 0.02 1.95 2 2 3 3 1 3 1 1 2 2 11 Amara plebeja (Gyllenhal, 1810) amar pleb -0.02 -0.08 0.08 0.02 0.02 -0.03 0.00 -0.02 0.02 1.90 1 3 3 3 1 3 1 1 2 2 12 Anchomenus dorsalis (Pontoppidan, 1763) (=Agonum dorsale) anch dors 0.05 0.16 -0.10 -0.02 0.01 0.08 0.01 0.13 -0.03 1.86 3 1 3 2 1 2 2 1 2 2 13 Asaphidion flavipes (Linnaeus, 1761) asap flav 0.30 0.01 -0.07 0.03 -0.01 0.05 0.02 0.08 -0.02 1.69 1 3 3 2 1 1 1 1 2 2 14 Bembidion aeneum Germar, 1824 bemb aene 0.04 0.06 0.00 -0.01 0.03 0.02 0.04 0.02 0.00 1.66 2 2 2 1 2 2 2? 1 2 1 15 Bembidion bruxellense Wesmael, 1835 bemb brux -0.02 0.06 -0.05 -0.03 0.01 0.02 0.00 0.00 -0.04 1.71 1 1 3 2 1 2 1 1 2 1 16 Bembidion guttula (Fabricius, 1792) bemb gutt 0.03 0.06 0.00 0.01 0.01 0.03 0.04 0.03 -0.02 1.56 1 2 2 1 1 2 2 1 2 1 17 Bembidion lampros (Herbst, 1784) bemb lamp 0.19 0.04 -0.01 0.02 0.00 0.02 0.03 0.05 -0.01 1.60 1 2 2 2 1 1 1 1 2 1 18 Bembidion mannerheimi C.R. Sahlberg, 1834 bemb mann 0.07 0.07 0.04 0.03 0.02 0.05 0.05 0.02 0.04 1.53 1 2 1 1 1 2 2? 1 2 1 19 Bembidion obtusum Serville, 1821 bemb obtu -0.02 0.04 0.02 0.01 0.01 0.02 0.02 0.04 0.01 1.51 1 1 2 1 1 2 2 3 2 1 20 Bembidion tetracolum Say, 1823 bemb tetr -0.02 0.07 -0.05 -0.02 0.01 0.04 0.03 0.01 0.02 1.76 1 1 2 2 1 2 2 1 2 1 21 Bradycellus harpalinus (Serville, 1821) brad harp -0.04 -0.06 -0.02 -0.02 0.02 -0.05 -0.03 -0.12 -0.06 1.69 1 1 2 1 2 3 2? 3 2 2 22 Bradycellus ruficollis (Stephens, 1828) brad rufi -0.12 -0.07 -0.01 -0.01 0.02 -0.06 -0.05 -0.12 -0.08 1.57 1 2 3 1 1 3 2? 3 2 1 23 Calathus fuscipes (Goeze, 1777) cala fusc -0.03 -0.01 0.00 0.00 -0.03 -0.01 0.07 0.05 0.03 2.09 1 2 1 3 2 2 2 3 2 2 24 Calathus melanocephalus (Linnaeus, 1758) cala mela -0.10 0.03 0.02 -0.01 -0.02 -0.02 0.07 0.06 -0.01 1.92 1 1 2 3 2 2 2 3 2 1 25 Calathus micropterus (Duftschmid, 1812) cala micr -0.14 0.04 -0.01 -0.02 -0.01 0.01 0.06 0.07 -0.01 1.92 1 2 1 3 2 2 2 3 2 2 26 Carabus arvensis Herbst, 1784 cara arve 0.00 0.03 0.00 0.02 0.01 0.01 -0.06 0.04 0.00 2.28 2 3 1 1 1 2 1 1 2 2 27 Carabus glabratus Paykull, 1790 cara glab -0.05 0.00 -0.01 0.00 -0.02 0.01 -0.11 -0.04 -0.04 2.40 2 2 1 2 2 2 2 2 3 2 28 Carabus granulatus Linnaeus, 1758 cara gran 0.05 0.08 -0.04 0.00 -0.01 0.03 -0.07 0.05 -0.01 2.29 2 3 1 2 1 2 2 1 2 2 29 Carabus nemoralis O. Müller, 1764 cara nemo 0.05 0.02 0.02 0.03 0.02 0.00 -0.05 0.00 0.01 2.37 2 3 1 2 2 2 2 1 2 2 30 Carabus nitens Linnaeus, 1758 cara nite -0.16 -0.08 0.01 0.04 0.01 -0.01 -0.05 -0.01 -0.01 2.22 2 3 1 1 1 2 1 2 2 1 31 Carabus problematicus Herbst, 1786 cara prob 0.06 0.04 -0.04 0.00 0.00 0.03 -0.09 0.03 -0.07 2.39 2 2 1 2 2 2 2 2 1 2 32 Carabus violaceus Linnaeus, 1758 cara viol -0.02 0.00 -0.05 -0.01 -0.04 -0.01 -0.12 -0.04 -0.08 2.41 2 2 1 2 2 2 2 3 2 2 33 Clivina fossor (Linnaeus, 1758) cliv foss -0.19 -0.18 -0.05 -0.02 -0.10 -0.16 -0.11 -0.21 -0.10 1.80 1 1 2 1 2 2 2 1 3 2 34 Cychrus caraboides (Linnaeus, 1758) cych cara -0.04 0.11 -0.12 -0.01 0.00 0.09 -0.13 0.02 -0.08 2.24 2 2 1 1 2 2 2 3 2 2 35 Dyschiroides globosus (Herbst, 1783) (=Dyschirius globosus) dysc glob -0.06 -0.16 -0.01 0.07 -0.04 -0.12 -0.21 -0.17 -0.14 1.45 2 2 1 1 1 2 1 1 2 1 36 Elaphrus cupreus Duftschmid, 1812 elap cupr 0.25 -0.08 -0.06 0.04 0.03 0.01 -0.12 0.01 -0.07 1.98 3 3 3 2 1 2 1 1 2 2 37 Elaphrus uliginosus Fabricius, 1775 elap ulig 0.30 -0.13 -0.04 0.04 0.02 -0.01 -0.14 -0.01 -0.05 2.00 3 3 3 2 1 2 1 1 2 2 38 Harpalus affinis (Schrank, 1781) harp affi -0.07 -0.08 0.06 0.03 0.01 -0.05 0.11 -0.09 0.11 2.02 1 3 3 3 2 3 2 1 2 1 39 Harpalus latus (Linnaeus, 1758) harp latu -0.10 -0.06 0.09 0.03 0.02 -0.03 0.12 -0.11 0.11 2.01 1 2 3 3 1 3 2 2 2 1 40 Harpalus rufipes (De Geer, 1774) harp rufi 0.02 -0.07 0.03 0.01 -0.01 -0.04 0.12 -0.07 0.06 2.19 1 1 3 3 2 3 2 3 2 2 41 Leistus terminatus (Hellwig in Panzer, 1793) (=L. rufescens) leis term 0.06 0.15 0.00 -0.02 -0.01 0.08 -0.10 0.10 -0.04 1.84 1 1 2 2 2 1 2 3 2 2 42 Loricera pilicornis (Fabricius, 1775) lori pili 0.04 0.06 -0.02 -0.04 -0.01 0.05 0.04 0.06 -0.04 1.90 2 2 3 1 1 1 2 2 3 2 43 Nebria brevicollis (Fabricius, 1792) nebr brev 0.07 0.07 0.01 -0.01 0.01 0.04 -0.10 0.05 -0.09 2.10 1 2 3 2 2 2 2 3 1 1 44 Nebria salina Fairmaire & Laboulbène, 1854 nebr sali 0.03 0.07 0.01 -0.01 0.01 0.06 -0.10 0.06 -0.09 2.08 1 2 3 2 2 2 2 3 1 2 45 Notiophilus aquaticus (Linnaeus, 1758) noti aqua 0.35 -0.16 -0.01 -0.01 -0.04 0.01 -0.11 0.08 0.01 1.77 3 3 2 2 2? 1 1 2 2 2?

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46 Notiophilus biguttatus (Fabricius, 1779) noti bigu 0.37 -0.15 0.03 0.01 -0.03 0.02 -0.12 0.06 -0.02 1.75 3 3 2 2 1 1 1 1 2 2 47 Notiophilus germinyi Fauvel, 1863 noti germ 0.39 -0.13 0.04 0.05 -0.02 0.03 -0.09 0.10 0.02 1.76 3 3 3 2 2 1 1 1 2 2 48 Notiophilus palustris (Duftschmid, 1812) noti palu 0.37 -0.15 0.02 0.02 -0.03 0.01 -0.10 0.06 -0.04 1.78 3 3 2 2 2 1 1 3 2 2 49 Notiophilus substriatus Waterhouse, 1833 noti subs 0.34 -0.16 0.01 0.00 -0.03 0.00 -0.09 0.07 -0.02 1.74 3 3 1 2 1 1 1 1 3 2 50 Olisthopus rotundatus (Paykull, 1790) olis rotu -0.06 0.01 0.00 -0.02 0.00 0.02 0.09 -0.01 0.06 1.86 1 1 2 1 2 2 2? 3 2 2 51 Patrobus assimilis Chaudoir, 1844 patr assi -0.03 0.05 -0.05 -0.02 -0.03 -0.03 0.01 -0.07 0.05 1.91 1 1 1 2 2 2 2? 2 2 2 52 Patrobus atrorufus (Ström, 1768) patr atro 0.05 0.07 -0.04 -0.02 -0.02 0.00 -0.01 -0.02 0.01 1.93 1 1 1 2 2 2 2 3 2 2 53 Poecilus versicolor (Sturm, 1824) (=Pterostichus versicolor) poec vers -0.02 -0.02 0.05 0.01 -0.01 -0.03 0.11 0.05 0.07 2.09 2 3 3 1 1 2 1 2 3 1 54 Pterostichus adstrictus Eschscholtz, 1823 pter adst -0.01 -0.03 0.01 -0.01 -0.01 -0.02 0.06 -0.03 -0.08 2.10 2 2 3 3 2 2 2 2 2 2 55 Pterostichus diligens (Sturm, 1824) pter dili -0.09 -0.01 0.01 0.01 -0.03 -0.03 0.05 -0.07 0.00 1.80 2 2 2 2 2 2 2 1 3 1 56 Pterostichus madidus (Fabricius, 1775) pter madi 0.00 -0.02 0.03 0.01 -0.02 -0.03 0.12 -0.04 0.08 2.20 1 2 1 1 2 3 2 3 2 2 57 Pterostichus melanarius (Illiger, 1798) pter mela -0.01 -0.05 0.03 0.00 -0.02 -0.04 0.09 -0.08 0.06 2.22 2 2 2 3 2 2 2 3 1 2 58 Pterostichus niger (Schaller, 1783) pter nige 0.03 0.02 -0.03 -0.05 -0.02 0.01 0.11 -0.05 0.03 2.29 2 2 3 3 2 2 2 3 1 2 59 Pterostichus nigrita (Paykull, 1790) pter nigr -0.01 0.01 0.02 -0.01 -0.01 -0.04 0.10 -0.04 0.05 2.06 2 2 2 3 2 2 2 1 2 2 60 Pterostichus rhaeticus Heer, 1838 pter rhae -0.01 -0.01 0.04 0.02 -0.02 -0.02 0.12 -0.03 0.07 2.00 2 2 2 3 2 2 2 1 2 2? 61 Pterostichus strenuus (Panzer, 1797) pter stre -0.04 0.01 0.00 -0.01 -0.01 -0.03 0.04 -0.05 0.01 1.83 1 1 2 2 1 2 2 1 2 1 62 Pterostichus vernalis (Panzer, 1796) pter vern -0.05 0.02 0.03 0.01 -0.03 -0.02 0.11 0.02 0.03 1.85 1 1 2 3 1 2 2 1 3 1 63 Stomis pumicatus (Panzer, 1796) stom pumi -0.07 0.08 -0.06 -0.03 -0.06 -0.03 0.03 -0.05 0.01 1.86 1 1 1 2 1 2 2 1 2 1 64 Synuchus vivalis (Illiger, 1798) (=S. nivalis) synu viva -0.09 0.04 -0.01 -0.02 -0.02 0.00 0.07 -0.01 0.06 1.86 1 1 2 1 2 3 2 3 2 2 65 Trechoblemus micros (Herbst, 1784) (=Trechus micros) trec micr -0.38 0.14 -0.03 -0.04 -0.04 0.08 0.01 0.08 0.01 1.63 1 1 3 2 2 1 2? 2 2 1 66 Trechus obtusus (Erichson, 1837) trec obtu -0.14 0.09 0.01 -0.01 0.04 0.07 0.04 0.01 0.13 1.60 1 1 1 1 2 1 2 3 1 2 67 Trechus quadristriatus (Schrank, 1781) trec quad -0.13 0.08 -0.01 -0.03 0.03 0.04 0.04 0.00 0.08 1.62 1 1 3 1 2 1 2 3 2 1 68 Trechus rubens (Fabricius, 1792) trec rube -0.22 0.12 -0.05 -0.01 0.01 0.07 0.05 0.05 0.02 1.75 1 1 3 1 1 2 2 3 2 1

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Ecological Archives E082-012-A4

Ignacio Ribera, Sylvain Dolédec, Iain S. Downie, and Garth N. Foster. 2001. Effect of land disturbance and stress on species traits of ground beetle assemblages. Ecology 82:1112-1129.

Literature cited in the appendices.

Bauer, T., and M. Kredler. 1993. Morphology of the compound eyes as an indicator of life-style in carabid beetles. Canadian Journal of Zoology 71: 799-810.

Brandmayr, T. Z. 1990. Spermophagous (seed-eating) ground beetles: first comparison of the diet and ecology of the harpaline genera Harpalus and Ophonus (Col. Carabidae). Pages 307-316 in N. E. Stork, editor. The role of ground beetles in ecological and environmental studies. Intercept, Newcastle, UK.

Den Boer, P. J., and W. Den Boer-Daanje. 1990. On life history tactics in Carabid beetles: are there only spring and autumn breeders? Pages 247-258 in N. E. Stork, editor. The role of ground beetles in ecological and environmental studies, Intercept, Newcastle, UK.

Desender, K. 1982. Ecological and faunal studies on Coleoptera in agricultural land. II. Hibernation of Carabidae in agro-ecosystems. Pedobiologia 23: 295-303.

Desender, K. 1983. Ecological data on Clivina fossor (Coleoptera, Carabidae) from a pasture ecosystem. I. Adult and larval abundnace, seasonal and diurnal activity. Pedobiologia 25: 157-167.

Desender, K., and M. Alderweireldt. 1990. Yearly and seasonal variation of carabid diel activity in pastures and cultivated fields. Revue d'Écologie et de Biologie du Sol 27: 423-433.

Desender, K., J. Mertens, M. D'hulster, and P. Berbiers. 1984. Diel activity patterns of Carabidae (Coleoptera), Staphylinidae (Coleoptera) and Collembola in a heavily grazed pasture. Revue d'Écologie et de Biologie du Sol 21: 347-361.

Desender, K., and M. Pollet. 1985. Ecological data on Clivina fossor (Coleoptera, Carabidae) from a pasture ecosystem II. Reproduction, biometry, biomass, wing polymorphism and feeding ecology. Revue d'Écologie et de Biologie du Sol 22: 233-246.

Dolédec, S., D. Chessel, C. J. F. Ter Braak, and S. Champely. 1996. Matching species traits to environmental variables: a new three-table ordination method. Environmental and Ecological Statistics 3: 143-166.

Hengeveld, R. 1980. Polyphagy, oligophagy and food specialization in ground beetles (Coleoptera, Carabidae). Netherland Journal of Zoology 30: 564-584.

Houston, W. W. K. 1981. The life cycles and age of Carabus glabratus Paykull and C. problematicus Herbst (Col.: Carabidae) on moorland in northern England. Ecological Entomology 6: 263-271.

Huizen, T. H. P. 1977. The significance of flight activity in the life cycle of Amara plebeja Gyll. (Coleoptera, Carabidae). Oecologia 29: 27-41.

Jones, M. G. 1979. The abundance and reproductive activity of common Carabidae in a winter wheat crop. Ecological Entomology 4: 31-43.

Kegel, B. 1990. Diurnal activity of Carabid beetles living on arable land. Pages 65-76 in N. E. Stork, editor. The role of ground beetles in ecological and environmental studies. Intercept, Newcastle, UK.

Kryzhanovskij, O. L., I. A. Belousov, I. I. Kabak, B. M. Kataev, K. V. Makarov, and V. G. Shilenkov. 1995. A checklist of the ground-beetles of Russia and adjacent lands (Insecta, Coleoptera, Carabidae). Pensoft Publishers, Sofia, Bulgaria.

Larochelle, A. 1990. The food of carabid beetles (Coleoptera: Carabidae, including Cicindelinae). Fabreries, Supplément 5: 1-132.

Lindroth, C. H. 1945. Ground beetles (Carabidae) of Fennoscandia. Vol. 1. Smithsonian Institution Libraries, Washington, USA. (Translated from the German, edited in 1992).

Lindroth, C. H. 1974. Coleoptera: Carabidae. Handbooks for the Identification of British Insects 4(2). Royal Entomological Society, London, UK.

Lindroth, C. H. 1985. Fauna Entomologica Scandinavica, Vol. 15. The Carabidae (Coleoptera) of Fennoscandia and Denmark, I. E. J. Brill, Leiden, The Netherlands.

Lindroth, C. H. 1986. Fauna Entomologica Scandinavica, Vol. 15. The Carabidae (Coleoptera) of Fennoscandia and Denmark, II. With an appendix on the family Rhysodidae. E. J. Brill, Leiden, The Netherlands.

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Luff, M. L. 1978. Diel activity patterns of some field Carabidae. Ecological Entomology 3: 53-62.

Luff, M. L. 1998. Provisional atlas of the Coleoptera: Carabidae (ground beetles) of Britain and Ireland. Institute of Terrestrial Ecology, Huntingdon, UK.

Pollet, M., and K. Desender. 1987. Feeding ecology of grassland-inhabiting carabid beetles (Carabidae, Coleoptera) in relation to the availability of some prey groups. Acta Phytopathologica et Entomologica Hungarica 22: 223-246.

Pollet, M., K. Desender, and M. van Kerckvoorde. 1987. Prey selection in Loricera pilicornis (Col. Carabidae). Acta Phytopathologica et Entomologica Hungarica 22: 425-431.

Symondson, W. O. C., D. M. Glen, C. W. Wiltshire, C. J. Langdon, and J. E. Liddell. 1996. Effects of cultivation techniques and methods of straw disposal on predation by Pterostichus melanarius (Coleoptera: Carabidae) upon slugs (Gastropoda: Pulmonata) in an arable field. Journal of Applied Ecology 33: 741-753.

Thiele, H. U. 1977. Carabid beetles in their environments. Springer-Verlag, Berlin, Germany.

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