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Biological Conservation 122 (2005) 465–478

BIOLOGICAL

CONSERVATION

Responses of butterfly and moth species to restored cattlegrazing in semi-natural grasslands

Juha Poyry *, Sami Lindgren, Jere Salminen, Mikko Kuussaari

Finnish Environment Institute, Research Programme for Biodiversity, Mechelininkatu 34 A, P.O. Box 140, FIN-00251 Helsinki, Finland

Received 2 March 2004; received in revised form 18 August 2004; accepted 3 September 2004

Abstract

The effects of restorative grazing on the abundance of butterfly and moth species were studied in mesic semi-natural grasslands of

SW Finland differing in management history: (1) old continuously grazed, (2) restored (with ca 5 years of reinitiated grazing), and

(3) abandoned former pastures.

Generalized linear modelling of species abundances and indicator species analysis produced qualitatively similar results. Only

three species (Polyommatus icarus, Lycaena hippothoe and Camptogramma bilineatum) were most abundant in old pastures, whereas

12 species (Polyommatus semiargus, Polyommatus amandus, Brenthis ino, Aphantopus hyperantus, Scopula immorata, Idaea serpen-

tata, Scotopteryx chenopodiata, Epirrhoe alternata, Cybosia mesomella, Polypogon tentacularius, Hypena proboscidalis and Crypto-

cala chardinyi) were most abundant in abandoned pastures. None of the old-pasture species had become more abundant in restored

pastures. Three species, Epirrhoe hastulata, Xanthorhoe montanata and Chiasmia clathrata, occurred equally abundantly in aban-

doned and in restored pastures indicating a slow progress of restoration.

Species associated with old pastures differed from species associated with abandoned pastures in their recent distributional

changes in Finland. The species of old pastures showed decreasing trends, whereas those of abandoned pastures showed mainly

increasing trends in their distribution. In five out of 11 species, the preferred successional stage differed markedly between this study

and previous studies conducted in Central Europe.

We conclude that (1) ca 5 years of restorative grazing in mesic grasslands has been insufficient for the colonisation of old-pasture

species in the restored sites, (2) different management intensities are needed regionally for the maintenance of grassland insect diver-

sity and (3) application of the knowledge on successional preferences of different species in conservation management, even in cli-

matically similar regions, should be made with caution.

� 2004 Elsevier Ltd. All rights reserved.

Keywords: Butterflies and moths; Cattle grazing; Restoration management; Semi-natural grasslands; Species responses

1. Introduction

Agricultural modernization has caused a widespread

decline of organisms in European agricultural land-

scapes (Krebs et al., 1999; Benton et al., 2003). Pres-

ently, national agri-environment support schemes are

0006-3207/$ - see front matter � 2004 Elsevier Ltd. All rights reserved.

doi:10.1016/j.biocon.2004.09.007

* Corresponding author. Tel.: +358 9 40300 206; fax: +358 9 40300

290.

E-mail address: juha.poyry@ymparisto.fi (J. Poyry).

the main tool in attempts to halt and eventually reverse

this negative development (Sutherland, 2002; Kleijn and

Sutherland, 2003). Existing schemes have indeed pro-

duced positive effects on some organisms (Ovenden

et al., 1998; Kleijn et al., 2001). However, it is becoming

evident that their impact is not sufficient and new meth-

ods for the management of agricultural biodiversity are

urgently needed (Sutherland, 2002). Initiatives for new,more comprehensive means such as large-scale habitat

restoration have also been proposed (Bignal, 1998; Suth-

erland, 2002). One of the potentially very important

466 J. Poyry et al. / Biological Conservation 122 (2005) 465–478

means is the use of grazing animals to restore semi-nat-

ural grasslands from abandoned and overgrown former

semi-natural pastures or from improved grassland pas-

tures and cultivated fields (WallisDeVries, 1995).

Grazing management is commonly used in the resto-

ration of semi-natural habitats (WallisDeVries et al.,1998). The prevailing management regimes that are ap-

plied in many European countries are targeted at inten-

sive grazing, which has been demonstrated to be most

suitable in maintaining and restoring high vascular spe-

cies diversity (e.g., Bakker, 1998). Our knowledge on

the effects of restorative grazing on other organisms such

as insects is largely based on studies focusing on an indi-

vidual declining or threatened species, often a butterfly,with a high conservation status (Thomas, 1991; Pullin,

1996). Among the few available studies, both positive

and negative responses to restarted grazing management

have been reported (Thomas, 1990, 1991; Dolek and

Geyer, 2002). Failed attempts at restoration due to

unsuitable grazing intensity have also been documented

(Oates, 1995). A clear gap in our knowledge is that the

effects of restoration with grazing on insect communitiesin semi-natural habitats have been only rudimentarily

studied, as is also the case with overall species-specific re-

sponses (but see WallisDeVries and Raemakers, 2001). It

is thus imperative to gather further knowledge concern-

ing what proportion of insect species, and more specifi-

cally which species, are expected to react positively and

which negatively to the effects of restored grazing.

Many studies have explored the abundance of insects(often butterflies, seldom moths) over a continuum of

successional stages in grasslands. The insect communi-

ties of grasslands with low vegetation caused by high

grazing intensity have typically been compared with

areas where extensive grazing (i.e., grazing with lower

intensity) and/or increasing periods of abandonment

have resulted in higher vegetation. These reports include

both qualitative (Erhardt, 1985; BUTT, 1986; Erhardtand Thomas, 1991; Oates, 1995) and quantitative (Bal-

mer and Erhardt, 2000) approaches in comparing spe-

cific responses to successional development of

vegetation. However, it is not known whether this

knowledge can directly be applied to predict possible

specific responses to restarted grazing.

In this paper we present results from a large-scale field

study in which we examined the responses of butterflyand day-active moth species to restorative grazing. We

compared the abundances of different species among

old, restored and abandoned former pastures. We also

investigated whether the observed distributional changes

differed among the groups of species assigned to the stud-

ied pasture types. The analysis was based on the records

published in the Atlas of FinnishMacrolepidoptera (Hul-

den et al., 2000). We chose butterflies and macromoths asthe study group due to the existing standard tools (e.g.,

Pollard�s transect method), their well known ecology,

and because they have generally been widely used as

model taxa in various ecological and environmental stud-

ies (Pollard and Yates, 1993; Boggs et al., 2003).

The effects of restorative grazing on species composi-

tion, richness, diversity and general abundance have

been dealt with in a separate paper (Poyry et al.,2004). The corresponding results for vascular plant com-

munity structure within the same study areas have been

presented by Pykala (2003).

2. Material and methods

2.1. Study sites

Three kinds of mesic semi-natural grasslands, in total

33 sites, differing in their management history were stud-

ied in SW Finland: (1) old pastures, which have been

grazed annually for at least several decades or longer

(n = 6 for 1999 and n = 5 for 2000), (2) abandoned pas-

tures, where grazing ceased >10 years ago (n = 6 for

1999 and n = 6 for 2000) and (3) restored pastures, wheregrazing was reinitiated ca 5 (min = 3, max = 8) years ago

after >10 years of abandonment (n = 6 for 1999 and n = 4

for 2000) (Fig. 1). A list of the sites and their main char-

acteristics has been presented in Poyry et al. (2004).

In 1999, all the study sites were located in Somero,

along the Hantala valley region, within an area of 20

km2 comprising the largest occurrence of semi-natural

grasslands in the country (Kontula et al., 2000), but in2000 they were located in a larger area of 30 · 100 km2

in SW Finland (Fig. 1). In 1999, areas of the study sites

varied from 0.29 to 1.31 ha, whereas in 2000 all sampled

areas were 0.25 ha in size. All sites were located along

small river valleys and brooks. The average nearest-

neighbour distance among the sites was 600 m in 1999

and 7300 m in 2000. A typical slope orientation at the

sites was SE, S or SW, with a slope angle from 5� to20�. The predominant soil type in the study sites was clay.

Old pastures were selected from the sites which had

been located and evaluated as botanically valuable in

the National inventory of semi-natural grasslands

(Vainio et al., 2001). These were supplemented with

comparable restored pastures included in the Finnish

agri-environmental scheme and partly overgrown yet

still unforested abandoned pastures located in the sameregion. All restored pastures and most old pastures were

included in the Finnish agri-environmental support

scheme for the management of semi-natural grasslands

(Salminen and Kekalainen, 2000). The grazing animal

in all pastures was cattle, usually dairy heifers but in

four cases beef cattle. All except two sites were owned

by local farmers and other private land-owners. None

of the sites were located in a nature conservation area,but about 2/3 of the sites were included in the Finnish

proposal for the EU Natura 2000-network.

Fig. 1. The study area and locations of the studied semi-natural grasslands in SW Finland. Old, continuously grazed pastures are indicated with

black dots, restored pastures with dotted circles and abandoned former pastures with open circles. The topographical variation is shown with

isoclines of 5 m for the study area of 1999 and larger lakes and rivers are indicated with grey shading for the study area of 2000. The shore of the

Baltic Sea and regional and state borders are marked with black lines. Reproduced from Poyry et al. (2004). � 2004 Published by Ecological Society

of America.

J. Poyry et al. / Biological Conservation 122 (2005) 465–478 467

2.2. Study organisms

The study organisms were butterflies and day-active

moths (Lepidoptera), including species in the families

Zygaenidae, Sphingidae, Drepanidae, Geometridae,

Arctiidae and Noctuidae. The nomenclature follows

the European check-list of Lepidoptera (Karsholt and

Razowski, 1996) as modified by Kullberg et al. (2002).

The nomenclature of the larval host plants follows the

Field Flora of Finland (Hamet-Ahti et al., 1998).

2.3. Transect counts

Amodification of the widely used transect-method, in

which butterflies are counted weekly along a permanent

route within a 5 · 5 m2 square ahead of the counter (Pol-

lard, 1977), was applied in the study. All sites were

walked through to search for butterflies and moths ina serpentine-like manner so that the whole site area

was covered once during each visit (Douwes, 1976; Bal-

mer and Erhardt, 2000). In 1999, due to size differences

between the study areas, searching time (11 min per 0.25

ha) and transect-length were linearly matched with the

study area. Transects were counted four times during

the summer of 1999, twice in June, once in mid-July

and once in mid-August. In 2000, transect-length was

350 m in each 0.25 ha site, and the transects werecounted seven times, starting in the last week of May

and continuing with a intervening period of ca. two

weeks until the third week of August. This period covers

the flight-season of most butterfly and day-active moth

species in Finland (Kuussaari et al., 2002).

2.4. Environmental variables

A number of environmental variables were measured

for the study sites (for details see Appendix A and Poyry

et al., 2004). They were classified into the following main

groups: (1) adjusting variables, (2) historical land-use, (3)

current land-use, (4) geography and topography, (5) lo-

cal habitat characteristics and (6) weather variables.

Adjusting variables include study year and sampled site

area. Historical land-uses include five variables, the mostimportant for the questions addressed in this study being

a three-class categorical variable indicating the manage-

ment history of the study sites (C = old continuously

grazed pasture, R = formerly abandoned pasture with

restarted grazing and A = abandoned former pasture).

Grazing in the study year, length of the grazing period

and averages and CVs of six different measurements of

468 J. Poyry et al. / Biological Conservation 122 (2005) 465–478

grazing intensity were included as measures of current

land-use. Geography and topography variables include

latitude, longitude and a solar radiation index calculated

from slope direction and steepness (Griffiths, 1985; Luo-

to et al., 2001). Local habitat characteristics include 11

variables, comprising measures of vascular plant speciesrichness and density and nectar plant density indices.

Weather variables included the annual averages and

CVs of temperature, wind speed, cloudiness, proportion

of direct sun-shine during a count and proportion of

counts made under inappropriate weather conditions

(there were only a few such cases).

2.5. Data analysis

Two main methods were used to compare abun-

dances of individual species between the three pasture

types: generalized linear modelling (GLM) and indicator

species analysis (ISA).

Generalized linear modelling (McCullagh and Nelder,

1989) as implemented in the software GLIM, version

3.77 (Payne, 1986; Nicholls, 1991; Crawley, 1993) wasused to construct multiple regression models. The re-

sponse variables were abundances of individual species

with a minimum of 15 observed individuals. The analy-

sis of Parnassius mnemosyne was restricted to the study

area of 1999 due to the isolated nature of its occurrence

(Luoto et al., 2001).

The variables adjusting for the effects of study-year

(1 = 1999, 2 = 2000) and area were forced first into theexplanatory models. As the main question of this study

was to compare species abundance among three groups

of grasslands, grazing history was next added to the

models as a categorical explanatory variable. An F-ratio

test of the deviance reduction was applied to test for the

statistical significance of inclusion of the explanatory

variable into the model (McCullagh and Nelder, 1989;

Crawley, 1993).As multiple statistical tests from the same data set can

potentially increase the probability of making Type I er-

rors (i.e., rejecting true H0 of no difference between the

pasture types), more stringent significance levels with

sequential Bonferroni correction were calculated for

the tested species (Rice, 1989). Because different species

can be considered as independent entities, arguments

may be presented both for and against the necessity ofusing corrections for multiple testing to eliminate Type

I errors (Cabin and Mitchell, 2000; Quinn and Keough,

2002). It is also clear that attempts to eliminate Type I

errors inflate Type II errors (i.e., accepting false H0 of

no difference between the pasture types), and cause loss

of power in the statistical tests used and inability to de-

tect existing real differences (Cabin and Mitchell, 2000;

Quinn and Keough, 2002). In our case, 32 parallelGLM tests with p < 0.05 would create a family-wise er-

ror rate of 81% of making one Type I error (Quinn and

Keough, 2002). Simultaneously, application of sequen-

tial Bonferroni correction caused a drop from 19 to 12

of the species with strong evidence against H0. This

means that by eliminating 1 Type I error we may intro-

duce 6 Type II errors of not detecting real abundance

difference among the pasture types. Hence, we showoriginal uncorrected p-values but also indicate which

species showed strong evidence against H0 with Bonfer-

roni corrected significance levels.

Finally, a posteriori pair-wise F-ratio tests with

GLMs were applied to the species with significant differ-

ences in abundance among the three pasture types so

that abundances in two pasture types were compared

at the same time.Indicator species analysis (ISA) (Dufrene and Legen-

dre, 1997) as implemented in the software PC-ORD ver-

sion 4.22 (McCune and Mefford, 1999) was applied to

study whether an individual butterfly or moth species

would show indicator value for any of the three pasture

types. An indicator value for each species i in each group

j of sites was calculated according to Dufrene and Leg-

endre (1997):

INDVALij ¼ Aij � Bij � 100; ð1Þ

where INDVALij = indicator value for species i in group

j, Aij = relative abundance of species i in group j and

Bij = relative frequency of species i in group j. In this

method the highest indicator value max[INDVALij] is

saved as a summary of the overall indicator value IND-

VALi of the species i. Statistical significance of IND-

VALi was evaluated using a Monte Carlo method, i.e.,by randomly rearranging the data for a large number

of times, with the default in the software being 1000

times. After the rearrangement procedure, a probability

distribution of possible indicator values in the data is

gained, and the observed indicator value of species i is

compared to the distribution to receive estimate of sta-

tistical significance. The probability of a type I error is

then the proportion of randomized indicator values thatexceeds the observed indicator value (Dufrene and Leg-

endre, 1997; McCune and Mefford, 1999).

Multivariate ordination methods with non-metric mul-

tidimensional scaling (NMDS) (Clarke, 1993; McCune

and Grace, 2002) were applied to explore the main dis-

tributional patterns of butterfly and moth species and

their relationships to environmental variables as imple-

mented the software PC-ORD, version 4.22 (McCuneand Mefford, 1999). Sørensen (Bray-Curtis) distance

measure was used in the NMDS analysis (Clarke,

1993; McCune and Grace, 2002). Ordination axes were

rotated (Varimax rotation) to maximise the correlation

between the main component of variation and the first

ordination axis. The NMDS scree plots were inspected

to select for the final number of dimensions in the

NMDS run (McCune and Mefford, 1999). The ordina-tion results are presented as species plots. Species scores

J. Poyry et al. / Biological Conservation 122 (2005) 465–478 469

were calculated by weighted averaging from the site

scores. Species occurring most abundantly (with strong

statistical significance, p < 0.05) in any of the three pas-

ture types according to GLM and ISA (i.e., indicator

species) are shown highlighted in ordination plots. Vec-

tors of the environmental variables having the strongestcorrelations (p < 0.01) with ordination axes were added

to ordination plots in order to assign the indicator spe-

cies to the main environmental gradients.

2.6. Pasture type preference and distributional trends

The absolute distributional trend in Finland was cal-

culated for each butterfly and moth species as the num-ber of positive 10 · 10 km2 atlas square records during

1988–1997 divided by the corresponding number in the

period before 1988 (Hulden et al., 2000). As a corrected

measure, the relative distributional trend for each spe-

cies was then calculated by taking into account the over-

all numbers of records from the two time periods. The

number of positive squares for all species in 1988–1997

was divided by the number of positive squares for allspecies before 1988. Relative distributional trend was

then calculated by dividing the uncorrected distribu-

tional trend by this correction value. Relative trends

were separately calculated for butterflies, geometrid

moths, tiger moths and noctuid moths, since data

sources and observational intensity differed between

these groups (Hulden et al., 2000). Only resident butter-

fly species of agricultural environments (Pitkanen et al.,2001) and resident day-active species of other families

(Kuussaari et al., 2002, M. Kuussaari and J. Poyry,

unpublished data) were included in the calculations, in

order to minimize bias within each taxonomic group.

After calculating the relative population trends, we com-

pared the trends in the two groups with largest numbers

of associated species, old pastures and abandoned pas-

tures, as indicated by GLM analyses. We also testedwhether there was a relationship between distributional

change and the GLM coefficient for the effect of aban-

donment on species abundance. The statistical tests ap-

plied here included the Mann–Whitney U test and

Pearson�s correlation as implemented in the software

Statistix, version 7.0 (Anonymous, 2000).

3. Results

3.1. Abundance differences among pasture types

Aminimum of 15 individuals was observed for a total

of 32 species of butterflies and moths. Results of general-

ized linearmodelling with pasture type as the explanatory

variable showed that the abundances of 19 out of the 32tested species differed with strong statistical significance

(p < 0.05) among the pasture types (Table 1). Using a

posteriori pair-wise tests, species may be assigned to

groups according to their preferred pasture types (Table

1, Fig. 2). Thus, three species, Lycaena hippothoe, Poly-

ommatus icarus and Camptogramma bilineatum, oc-

curred most abundantly in old pastures, but none of

these showed significant recovery in restored pastures.Nine species (Polyommatus semiargus, Polyommatus

amandus, Brenthis ino, Aphantopus hyperantus, Scotop-

teryx chenopodiata, Epirrhoe alternata, Polypogon tenta-

cularius, Hypena proboscidalis and Cryptocala chardinyi)

occurred most abundantly in abandoned pastures (Ta-

ble 1, Fig. 2). In addition, for two species, Scopula

immorata and Idaea serpentata, abundances increased

in abandoned pastures, but no pair-wise differencescould be detected. Three species, E. hastulata, Xanthor-

hoe montanata and Chiasmia clathrata, occurred equally

abundantly in abandoned and restored pastures but in

lower numbers in old pastures. Finally, two species, Lyc-

aena virgaureae and Siona lineata, appeared to have suf-

fered from restoration, and they occurred most

abundantly in both old and abandoned pastures (Table

1, Fig. 2).After sequential Bonferroni correction the number of

species with strong evidence for differences among the

pasture types decreased to 12 (Table 1). Now a posteri-

ori pair-wise tests showed that two species, L. hippothoe

and P. icarus, occurred most abundantly in old pastures.

Eight species (all the nine listed above except P. semiar-

gus) occurred most abundantly in abandoned pastures,

but only one species, C. clathrata, was observed mostabundantly in both restored and abandoned pastures.

3.2. Indicator species of pasture types

According to indicator species analysis eleven species

(P. semiargus, P. amandus, B. ino, A. hyperantus, S.

chenopodiata, X. montanata, E. alternata, C. clathrata,

Cybosia mesomella, P. tentacularius and C. chardinyi)were shown to be indicators of abandoned pastures

and two species, L. hippothoe and P. icarus, were indica-

tors of old pastures (Table 2). By contrast, no species

showed indicator value for restored pastures. C. meso-

mella was the only species for which association with a

pasture type that had not been detected with GLM anal-

yses (due to the low number of observed individuals)

was detected with ISA.

3.3. Species distribution along environmental gradients

NMDS ordination for species scores showed that spe-

cies concentrating in (Fig. 3(c)) or indicating (Fig. 3(b))

old pastures were located at low values (<0) along Axis

1, whereas species occurring most abundantly in aban-

doned pastures were located at high values (>0). Speciesassociated with different pasture types were not separated

along Axis 2. Environmental variables describing effects

Table 1

Results of the GLM analyses for the pasture type preferences of species with at least 15 observations

Species Deviance Change in

deviance

df F p-Value Variable coefficient

(restored pastures)

Variable coefficient

(abandoned

pastures)

A posteriori

comparison

CR CA RA

Thymelicus lineola (n = 263) 79.736 8.985 27 3.042 0.064 0.302 ± 0.172 0.458 ± 0.156 – – –

Ochlodes sylvanus (n = 47) 38.445 0.420 27 0.295 0.747 0.210 ± 0.375 0.209 ± 0.372 – – –

Parnassius mnemosyne (n = 16) 40.909 0.481 14 0.165 0.850 0.419 ± 0.649 0.080 ± 0.703 – – –

Pieris napi (n = 313) 63.219 7.781 27 3.323 0.051 �0.272 ± 0.141 �0.379 ± 0.142 – – –

Lycaena virgaureae (n = 101) 148.900 26.910 27 4.880 0.016 �1.458 ± 0.352 �0.018 ± 0.216 * ns ns

Lycaena hippothoe (n = 15) 36.021 14.072 27 10.548 <0.001 �2.437 ± 1.041 �1.881 ± 0.771 * * ns

Aricia artaxerxes (n = 57) 54.831 5.339 27 2.629 0.091 �0.303 ± 0.410 0.479 ± 0.319 – – –

Polyommatus semiargus (n = 64) 38.336 7.815 27 5.504 0.010 �0.123 ± 0.389 0.666 ± 0.311 ns ns *

Polyommatus amandus (n = 120) 66.470 63.900 27 25.956 <0.001 �0.267 ± 0.350 1.460 ± 0.264 ns ** ***

Polyommatus icarus (n = 158) 113.300 123.620 27 29.459 <0.001 �1.036 ± 0.200 �2.451 ± 0.279 * *** ns

Argynnis aglaja (n = 15) 30.027 1.198 27 1.077 0.355 �0.548 ± 0.647 �0.668 ± 0.681 – – –

Argynnis adippe (n = 59) 90.050 10.950 27 3.283 0.053 �1.109 ± 0.440 0.148 ± 0.297 – – –

Brenthis ino (n = 284) 113.410 98.790 27 23.519 <0.001 �0.257 ± 0.205 1.146 ± 0.163 ns ** **

Boloria selene (n = 41) 84.630 10.460 27 3.337 0.051 �0.007 ± 0.500 1.050 ± 0.412 – – –

Coenonympha glycerion (n = 236) 197.950 1.780 27 0.243 0.786 �0.223 ± 0.168 �0.113 ± 0.154 – – –

Aphantopus hyperantus (n = 1177) 248.940 202.100 27 21.920 <0.001 0.355 ± 0.091 1.021 ± 0.081 ns *** *

Scopula immorata (n = 147) 115.540 15.340 27 3.585 0.042 �0.195 ± 0.253 0.555 ± 0.194 ns ns ns

Scopula immutata (n = 48) 67.306 2.911 27 1.168 0.326 0.289 ± 0.408 0.603 ± 0.365 – – –

Idaea serpentata (n = 54) 71.980 10.214 27 3.831 0.034 0.284 ± 0.428 1.015 ± 0.365 ns ns ns

Scotopteryx chenopodiata (n = 1274) 707.160 624.540 27 23.845 <0.001 0.465 ± 0.111 1.709 ± 0.091 ns ** **

Camptogramma bilineatum (n = 20) 31.724 7.236 27 6.158 0.006 �0.527 ± 0.545 �1.558 ± 0.636 ns * ns

Xanthorhoe montanata (n = 160) 146.230 37.330 27 6.893 0.004 0.937 ± 0.264 1.314 ± 0.241 ns * ns

Epirrhoe tristata (n = 35) 37.892 0.315 27 0.224 0.800 0.186 ± 0.463 0.230 ± 0.430 – – –

Epirrhoe hastulata (n = 17) 32.640 11.636 27 9.625 <0.001 1.273 ± 1.153 2.442 ± 1.038 ns * ns

Epirrhoe alternata (n = 37) 49.456 15.044 27 8.213 0.002 0.520 ± 0.645 1.633 ± 0.538 ns * ns

Odezia atrata (n = 137) 218.790 22.020 27 2.717 0.084 0.105 ± 0.259 0.876 ± 0.221 – – –

Chiasmia clathrata (n = 292) 211.640 122.03 27 15.568 <0.001 1.786 ± 0.266 2.126 ± 0.254 ** *** ns

Siona lineata (n = 52) 43.999 8.760 27 5.376 0.011 �0.836 ± 0.475 0.350 ± 0.306 ns ns *

Polypogon tentacularius (n = 271) 149.750 164.590 27 29.676 <0.001 0.620 ± 0.263 2.019 ± 0.221 ns *** **

Hypena proboscidalis (n = 53) 131.120 99.010 27 20.388 <0.001 �7.828 ± 27.720 3.893 ± 1.013 ns * **

Euclidia glyphica (n = 92) 56.902 2.759 27 1.309 0.287 �0.003 ± 0.290 0.358 ± 0.254 – – –

Cryptocala chardinyi (n = 62) 29.418 64.632 27 59.320 <0.001 �0.519 ± 0.729 2.241 ± 0.471 ns *** ***

Variable coefficients of restored (R) and abandoned (A) pastures are compared with old continuously grazed (C) pastures (coefficient value set at 0).

Species showing strong evidence (p < 0.05) against H0 (no abundance differences between the three pasture types) after sequential Bonferroni

correction are marked in bold. Abbreviations for a posteriori comparisons are: ns = p P 0.05, * = p < 0.05, ** = p < 0.01 and *** = p < 0.001.

470 J. Poyry et al. / Biological Conservation 122 (2005) 465–478

of the grazing intensity correlated strongly with Axis 1

(Fig. 3(a), see also Poyry et al., 2004). Hence, values along

Axis 1 for the species associated with old pastures corre-

spond to variable vectors describing strong grazing inten-

sity, and values along Axis 1 for the species associated

with abandoned pastures correspond to variable vectors

describing missing or low grazing intensity. Results of

two different methods (GLMand ISA) show qualitativelygood agreement with each other when compared visually.

3.4. Pasture type preference and distributional trends

Species associated, according to GLM analyses, with

old pastures (L. hippothoe, P. icarus and C. bilineatum)

showed mainly negative distributional trends (median =

�17%, variation�30% to 0%), whereas species associatedwith abandoned pastures had in most cases become more

widely distributed in Finland (median = +10%, variation

(�45%)+1 to+19%(+201%) (Mann–WhitneyU test, two-

tailed p = 0.029; Table 3). For all species, no significant

relationships could be detected between distributional

change and the effect of abandonment on species abun-

dance (Pearson�s correlation, r = 0.292, p = 0.225; Fig.

4). This result appeared to be caused by three species,

I. serpentata, E. hastulata and C. chardinyi, for which

distributional change showed clear discrepancy from

the ten other species preferring abandoned pastures.

The first two species have experienced sharp declines,with relative changes of �23% and �45%, respectively,

whereas C. chardinyi has considerably expanded its

range in Finland (Table 3; Fig. 4).

4. Discussion

4.1. Colonization success by the species of old pastures

Not surprisingly, species composition in restored pas-

tures appears to be a mixture of species occurring in old

or in abandoned pastures (see also Poyry et al., 2004).

-3 -2 -1 0 1 2-3

-2

-1

0

1

2

3 Abandonedpastures

Old and abandonedpastures

Old pastures

Abandoned andrestored pastures

Ida ser

Sco immoPol sem

Pol ten

Aph hyp

Sco che

Epi altBre ino

Pol ama

Cry cha

Xan mon

Chi cla

Epi has

Sio lin

Lyc vir

Cam bilLyc hip

Pol ica

Effe

ct o

f aba

ndon

men

t on

abun

danc

e

Effect of restoration on abundance

Fig. 2. Coefficients for the effects of abandonment and restoration on

species abundance (according to GLM; Table 1) plotted against each

other. Species are marked with open circles, and the size of the circle is

relative to the strength of statistical evidence againstH0 (no abundance

differences between the pasture types). Four groups of species can be

distinguished on the basis of their responses to abandonment and

restarted grazing: (i) species preferring old continuously grazed pastures,

(ii) species preferring abandoned pastures, (iii) species occurring

abundantly both in restored and abandoned pastures and (iv) species

suffering from restarted grazing but occurring abundantly in old and

abandoned pastures. Abbreviations of scientific names are shown for

each species with significant (p < 0.05) abundance differences among the

pasture types.H. proboscidalis is excluded from thefigure due to the large

error range of the coefficient estimate in restored pastures (see Table 1).

J. Poyry et al. / Biological Conservation 122 (2005) 465–478 471

Species concentrating in old continuously grazed pas-

tures or species that are dependent on the occurrence

of low vegetation can be expected to colonize the re-

Table 2

Results of the indicator species analysis

Species Indicator group Indicator valu

Lycaena hippothoe 1 40.9

Polyommatus icarus 1 62.6

Polyommatus semiargus 3 48.9

Polyommatus amandus 3 68.5

Brenthis ino 3 56.6

Aphantopus hyperantus 3 52.6

Scotopteryx chenopodiata 3 70.2

Xanthorhoe montanata 3 49.7

Epirrhoe alternata 3 46.2

Chiasmia clathrata 3 60.1

Cybosia mesomella 3 43.4

Polypogon tentecularius 3 73.7

Cryptocala chardinyi 3 84.9

Indicator values are only shown for species with strong evidence (p < 0.05)

reshuffling of the data). Indicator groups are (1) old continuously grazed pa

stored pastures in the long run. Our results showed that

after five years of restorative management no significant

increase in the abundance of L. hippothoe, P icarus or C.

bilineatum had occurred in the restored sites, and that

the processes of habitat transformation and colonization

obviously need more time (see Gibson et al., 1992; Mor-timer et al., 2002).

A successful colonization is possible only when the

following minimum requirements are met in the restored

sites: firstly the host plants of a herbivorous insect

should occur with sufficient abundance to support an in-

sect population (e.g., Hanski et al., 1995); secondly graz-

ing should create the vegetation structures and niches

where insect individuals can complete their life-cycle(e.g., Thomas, 1991; Dolek and Geyer, 2002); and

thirdly there should be adjacent populations of the col-

onizing species, from which immigrants can arrive (Han-

ski and Kuussaari, 1995; Thomas and Hanski, 1997).

The first criterion may not be fulfilled by each species

preferring old pastures. Although restorative grazing

has been observed already to have increased vascular

plant species richness in the restored sites (Pykala,2003), the larval host plants showed differing responses

to restarted grazing (J. Pykala, submitted manuscript).

The larval host plant of L. hippothoe, Rumex acetosa,

had become commoner and more abundant in restored

pastures, but its average frequency was still far below

the frequencies occurring in old pastures. This indicates

that the amount of larval host plant may still be insuffi-

cient for the successful reproduction of L. hippothoe. Bycontrast, the larval host plants of C. bilineatum, Galium

spp., showed no difference in frequency or abundance

among the three pasture types. The potential larval host

plants ofP. icarus, species of the family Fabaceae, showed

either increases in restored pastures when compared with

abandoned pastures (Trifolium pratense and T. repens) or

no differences among the pasture types (e.g., Lathyrus

pratensis,T.medium andV. cracca). For these two specieseither unsuitable vegetation structures in restored

e (observed) Indicator value (randomized) p-Value

18.4 ± 7.8 0.017

35.4 ± 7.5 0.004

35.8 ± 6.0 0.031

37.5 ± 7.0 0.001

41.2 ± 7.0 0.020

38.5 ± 3.1 0.001

53.0 ± 6.3 0.004

31.2 ± 8.2 0.032

27.5 ± 8.1 0.032

38.2 ± 8.0 0.010

21.6 ± 8.0 0.027

36.6 ± 7.2 0.001

31.4 ± 7.8 0.001

against H0 (the same or a higher indicator value obtained by random

stures and (3) abandoned pastures.

-1.5 -1.0 -0.5 0.0 0.5 1.0 1.5-1.0

-0.5

0.0

0.5

1.0

1.5

-1.5 -1.0 -0.5 0.0 0.5 1.0 1.5-1.0

-0.5

0.0

0.5

1.0

1.5

Lyc hip

Pol ica

Pol sem

Pol amaBre ino

Aph hyp

Sco immo

Ida serp

Sco cheEpi alt

Pol ten

Hyp pro

Cry cha

Xan monChi claEpi has

Lyc vir

Sio lin

Lyc hip

Pol ica

Cam bil

Cyb mes

Pol ten

Chi cla

Xan mon

Epi hasCry cha

Epi alt

Pol sem

Aph hypPol ama

Bre ino

Indicator value for pasture-type Old pastures Abandoned pastures Other species

Axi

s 2

Axis 1

-1.5 -1.0 -0.5 0.0 0.5 1.0 1.5-1.0

-0.5

0.0

0.5

1.0

1.5

9

1011

12

16151413

8 7

65

4

3

21

17 18

19 2021

Axi

s 2

Axis 1

Species Environmental variables

(c)

(b)

(a)

Axi

s 2

Axis 1

Preference for pasture-type Most abundant in old Least abundant in restored Least abundant in old Most abundant in abandoned No statistical differences Other species

Fig. 3. Results of an NMDS ordination for the species scores (obtained by weighted averaging of site scores). (a) Locations of the species scores and

the strongest correlations of the environmental variables (p < 0.01) with the ordination axes. Abbreviations for the variables are: 1, nectar plant

abundance (average of three measurements); 2, study year; 3, nectar plant abundance (average of two measurements); 4, litter coverage on ground

(average) in June/July; 5, mean vegetation height in September; 6, litter coverage on ground (average) in September; 7, wind speed (average); 8,

latitude; 9, area; 10, temperature (average); 11, coverage of bare soil on ground (average); 12, vegetation height (CV) in September; 13, coverage of

litter on ground (CV) in June/July; 14, Coverage of litter on ground (CV) in September; 15, proportion of vegetation <10 cm (average); 16, coverage

of bare soil on ground (CV); 17, length of grazing period in the study year; 18, Grazing in the study year; 19, vascular plant species richness (indicator

species); 20, vascular plant species richness (grassland specialists); 21, openness. (b) Species ordination as in (a) but species with a significant indicator

value according to indicator species analysis (ISA) have been highlighted with group-specific symbols and with the abbreviations of scientific names.

(c) Species ordination as in (a) but species with significant associations to the pasture types according to generalized linear modelling (GLM) have

been highlighted with group-specific symbols (see Fig. 2) and with the abbreviations of scientific names. Three overlapping symbols (i.e., Siona

lineata, S. immorata and C. chardinyi) have been slightly moved to enhance the resolution of (c). (a) Partly reproduced from Poyry et al. (2004). Partly

owned � 2004 Published by Ecological Society of America.

472 J. Poyry et al. / Biological Conservation 122 (2005) 465–478

-3 -2 -1 0

-40

-20

0

20

200

Pol ica

Lyc hip

Cam bil

Lyc vir

B

Ap

Sio linPol sem

Sco im

Dis

trib

utio

na

l ch

an

ge

(%

)

Effect of abandon

Pasture type preference Most abundant in old Least abundant in restored Least abundant in old Most abundant in abandon

Fig. 4. The relationship between the coefficient for the effect of abandonment

those butterfly and moth species which showed a significant relationship bet

associations (see Fig. 2) and abbreviations of scientific names are indicated fo

the data published in the Atlas of Finnish Macrolepidpotera (Hulden et al.,

Table 3

A summary of the preferred pasture types of butterflies and moths

according to GLM and ISA analyses, and an overview of the recent

known population changes of the species in Finland

Species Preferred

pasture type

Absolute

change

(%)

Relative

change

(%)

Lycaena virgaureae Old, abandoned 2 21

Lycaena hippothoe Old �41 �30

Polyommatus semiargus Abandoned �7 10

Polyommatus amandus Abandoned 0 19

Polyommatus icarus Old �16 0

Brenthis ino Abandoned �2 16

Aphantopus hyperantus Abandoned �1 17

Scopula immorata Abandoned �22 1

Idaea serpentata Abandoned �41 �23

Scotopteryx chenopodiata Abandoned �20 3

Camptogramma bilineatum Old �35 �17

Xanthorhoe montanata Restored,

abandoned

�11 15

Epirrhoe hastulata Restored,

abandoned

�57 �45

Epirrhoe alternata Abandoned �17 7

Chiasmia clathrata Restored,

abandoned

�11 15

Siona lineata Old, abandoned �14 11

Cybosia mesomella Abandoned �24 14

Polypogon tentacularius Abandoned �29 2

Hypena proboscidalis Abandoned �16 22

Cryptocala chardinyi Abandoned 107 201

Calculations of the relative distributional changes are based on

the data published in the Atlas of Finnish Macrolepidoptera (Hulden

et al., 2000).

J. Poyry et al. / Biological Conservation 122 (2005) 465–478 473

pastures or weak dispersal ability by the adult individuals

may prevent successful colonization, but it is not possible

to distinguish what factor is more important. In general,

vegetation structure in restored pastures resembled that

in old pastures, although mean vegetation height was

on average lower in old pastures (see Poyry et al., 2004).Importantly, our study sites are located in a region where

different successional stages of semi-natural grasslands

are still common (see Kontula et al., 2000), and for many

species of butterflies and moths grassland patches along

the river valleys may form practically non-isolated step-

ping-stones along which the butterfly individuals may

move long distances as has been observed with the

Clouded Apollo butterfly (Luoto et al., 2001;M. Kuussa-ari & M. Luoto, unpublished data).

4.2. Pasture type preference and population trends

Because the amount of traditionally managed semi-

natural grasslands has strongly decreased in Finland as

well as elsewhere in Europe, it could be predicted that

species concentrating in intensively grazed grasslands

should have declined more than species thriving in aban-

doned grasslands. Our observations on distributional

trends and successional preferences among butterflies

and moths fit well into this prediction. Similar observa-tions on the dependence of declining species on early

successional low vegetation structures have been

1 2 3 4

Xan mon

Chi clare ino

h hypPol ama

Hyp pro

Cry cha

Sco che

Epi alt

Pol ten

Epi has

Ida ser

mo

ment on abundance

ed

on species abundance and the recent distributional trend in Finland for

ween pasture type and abundance in GLM analyses (Table 1). Group

r each species. Calculations of the distributional trends were based on

2000).

474 J. Poyry et al. / Biological Conservation 122 (2005) 465–478

reported in numerous studies of butterflies in NW

Europe (e.g., Thomas, 1991, 1993).

4.3. Successional preferences on a European scale

Comparisons of successional preferences of speciesassociated with one pasture type, either old or aban-

doned, with studies conducted elsewhere in Europe can

reveal interesting differences between regions. Appropri-

ate material for such comparisons is provided by studies

of butterfly and moth communities inhabiting different

vegetation heights of semi-natural grassland in Switzer-

land (Erhardt, 1985; Balmer and Erhardt, 2000). It was

possible to compare successional associations among ele-ven species of butterflies and moths occurring in grass-

lands in southern Finland and in mountainous regions

of Switzerland. The preferences were markedly different

in several species. One species (C. bilineatum) of the three

that were associated with old continuous pastures in Fin-

land did not prefer low early successional vegetation in

Switzerland and four (P. semiargus, S. immorata, I. ser-

pentata and P. tentacularius) of the seven species associ-ated with abandoned pastures in Finland preferred a

different successional stage in Switzerland (Erhardt,

1985; Balmer and Erhardt, 2000).

Associations of butterflies with different stages of

grassland vegetation are particularly well known inGreat

Britain (for reviews see BUTT, 1986; Oates, 1995), but

only two species that showed clear associations in our

study also occur there, namely P. icarus and A. hyperan-

tus. Successional preferences of these two species are

qualitatively similar in Finland and Great Britain.

It is well known that butterflies may occupy very differ-

ent vegetation heights and stages of succession in different

climatic zones (e.g., Thomas, 1991, 1993). Species depend-

ent on warm microclimates created by the early succes-

sional low vegetation in the northern part of their

ranges gradually shift their preference towards higher veg-etation further south. However, southern Finland and

mountainous areas of Switzerland are located in rather

similar (boreomontane) climatic zones. Hence, one might

expect that in these countries species would favour similar

successional stages of semi-natural grassland. In contrast

to this expectation, nearly half (5 from 11) of the com-

pared species showed clear differences in their succes-

sional preferences between Finland and Switzerland.This observation holds an important message for conser-

vation managers: knowledge of habitat preference of but-

terflies and moths gained in one region should only be

applied with caution in practical management planning

elsewhere, even in areas with similar climatic conditions.

4.4. Conclusions for management

In our study, clearly more species (15) were associ-

ated with abandoned (three of which also with restored)

pastures than with old continuous pastures (three spe-

cies). Although the species associated with old pastures

had not yet returned to the restored sites, the overall

species composition as indicated by an ordination anal-

ysis was already similar between old and restored pas-

tures (Poyry et al., 2004). We have also observed thatspecies richness and total abundance of butterflies and

moths were highest in abandoned pastures among the

three management history types (Poyry et al., 2004).

Studies conducted in Central Europe have similarly con-

cluded that a larger proportion of butterfly and moth

species are associated with mid-late successional grass-

land vegetation (Balmer and Erhardt, 2000). These

observations challenge the existing management instruc-tions applied in Finland and in many other Western

European countries (see WallisDeVries et al., 1998).

The results of the present study showed that even

though the majority of butterflies and moths in grass-

lands prefer abandoned pastures, there may be more

declining and conservationally important species asso-

ciated with old continuously grazed areas. Hence it

could be argued that the existing management instruc-tions of intensive grazing have been adequate, but

that the time for restoration has not been sufficient

for the species of old pastures to have colonised the

restored sites. This should not be understood as

meaning that only the species dependent on low veg-

etation need attention when constructing management

plans for grassland insects (Dolek and Geyer, 2002).

Obviously, the requirements of all members of the in-sect community in semi-natural grasslands are never

met in one particular site at a time. Thus, more var-

iation in grazing intensity between pastures and possi-

bly yearly varying grazing regimes should be allowed

on the regional level compared with the present man-

agement instructions (see Brown et al., 1990; Morris,

1990; Dolek and Geyer, 2002). This recommendation

is also in agreement with proposals for enhancing het-erogeneity in the management of biodiversity in agri-

cultural areas (Benton et al., 2003) and with the

predictions of theoretical models of highest local

diversity in regional habitat mosaics (e.g., Levin and

Paine, 1974).

We conclude by suggesting that, with the above

specifications, the use of restorative cattle grazing of

previously abandoned semi-natural grasslands to con-struct grassland patch networks, is an important addi-

tion to the proposed tools to halt the decline of

biodiversity in European agricultural landscapes (Wal-

lisDeVries, 1995; Bignal, 1998; Sutherland, 2002). But-

terflies and moths appear to be, along with vascular

plants, useful indicator taxa for monitoring the effects

of restoration in semi-natural grasslands, because they

include certain species with positive and other specieswith negative responses to the onset of restarted

grazing.

J. Poyry et al. / Biological Conservation 122 (2005) 465–478 475

Acknowledgements

This work was funded by the Finnish Ministry of

Environment (for the project ‘‘Maintaining biodiver-

sity in traditional rural landscapes – optimal manage-

ment and area networks’’ through the FinnishBiodiversity Research Programme FIBRE coordinated

Appendix A

A list of the environmental variables measured during the study, their assign

analyses

Variable group and variable Details of measurement a

Adjusting variables

Year 1 = 1999, 2 = 2000

Site area Measured from digitized m

Land use history

Grazing history type Classified as a three-class

study sites (C = old contin

restarted grazing and A =

�redundant� type to which

Use of fertilizers and supplement forages Use of fertilizers and supp

Enrichment Soil nutrient enrichment d

plant composition (see Pyk

as a three-class variable (0

Use as arable field Cultivation was coded as

Spreading of hayseeds Spreading of hay seeds w

Current grazing management

Grazing in the study year Grazing during the study

Length of grazing period in the study year Length of the grazing seas

were present and ending i

Lepidopteran larvae are s

Mean vegetation height Average of direct measure

each study site during mid

Vegetation height (CV) Coefficient of variation of

sample squares in each stu

Proportion of vegetation <10 cm (average) Mean of proportion of lo

each study site during mid

Proportion of vegetation <10 cm (CV) Coefficient of variation of

sample squares in each stu

Coverage of bare soil on ground (average) Mean of coverage of bare

during mid-September

Coverage of bare soil on ground (CV) Coefficient of variation of

in each study site during m

Coverage of litter on ground (average) Mean of coverage of litter

site during plant surveys i

Coverage of litter on ground (CV) Coefficient of variation of

squares in each study site

Coverage of litter on ground (average) Mean of coverage of litter

site during mid-Septembe

Coverage of litter on ground (CV) Coefficient of variation of

squares in each study site

Coverage of mosses on ground (average) Mean of coverage of moss

site during plant surveys i

Coverage of mosses on ground (CV) Coefficient of variation of

squares in each study site

Geography and topography

Longitude Longitudinal midpoint of

coordinate system, was m

by the Academy of Finland), the Finnish Environment

Institute (SYKE), and the Maj and Tor Nessling

Foundation (Grant No. 2003008). Ilkka Hanski, Risto

Heikkinen, Marko Nieminen and Juha Pykala are

thanked for constructive criticism on the manuscript.

Michael J. Bailey improved the language of themanuscript.

ation to main groups and details of their measurement and usage in

nd usage

aps with the accuracy of 0.01 hectares

categorical variable indicating the management history of the

uously grazed pasture, R = formerly abandoned pasture with

abandoned former pasture). Old pastures were selected as the

other types were compared in GLM analysis

lement forages was coded as binary variables (0 = no, 1 = yes)

ue to fertilizers or supplementary forages as indicated by vascular

ala, 2003, Biodiversity & Conservation 12, 2211–2226) was coded

= no, 1 = low to moderate and 2 = severe enrichment)

a binary variable (0 = no, 1 = yes)

as coded as a binary variable (0 = no, 1 = yes)

year was coded as a binary variable (0 = ungrazed, 1 = grazed)

on was measured as weeks, starting from the first date when cattle

n the first week of September, representing the period when

ensitive to the effects of grazing

ments of vegetation height made from 15 1-m2 sample squares in

-September

direct measurements of vegetation height made from 15 1-m2

dy site during mid-September

w vegetation (<10 cm) measured from 15 1-m2 sample squares in

-September

proportion of low vegetation (<10 cm) measured from 15 1-m2

dy site during mid-September

ground measured from 15 1-m2 sample squares in each study site

coverage of bare ground measured from 15 1-m2 sample squares

id-September

on ground measured from 15 1-m2 sample squares in each study

n June or July (see Pykala, 2003)

coverage of litter on ground measured from 15 1-m2 sample

during plant surveys in June or July (see Pykala, 2003)

on ground measured from 15 1-m2 sample squares in each study

r

coverage of litter on ground measured from 15 1-m2 sample

during mid-September

es on ground measured from 15 1-m2 sample squares in each study

n June or July (see Pykala, 2003)

coverage of mosses on ground measured from 15 1-m2 sample

during plant surveys in June or July (see Pykala, 2003)

a site, derived from digitized maps in the Finnish uniform map

easured with the accuracy of 1 m

(continued on next page)

Appendix A (continued)

Variable group and variable Details of measurement and usage

Latitude Latitudinal midpoint of a site, derived from the Finnish uniform map

coordinate system, was measured from digitized maps with the accuracy of

1 m

Solar radiation The direction and the angle (steepness) of slope was measured from digital

maps with a resolution of 1:20,000. The slope measurements were

combined to calculate a general index of solar radiation with the following

equation (Griffiths, 1985):

Solar radiation = [cos(altitude)*sin(slope angle)*cos(ground

direction � sun direction) + sin(altitude)*cos(slope angle)]

where altitude is the angle of the sun above the horizon, sun direction

is the deviation of direction of the sun from south (south = 0,

east = �90, west = +90), and ground direction is the downgrade

direction of the ground from south (south = 0, east = �90, west = +90).

The solar radiation index was calculated for three times of day, 9 am,

12 am and 3 pm, and the average of these values was used in the

analysis

Local habitat characteristics

Openness Habitat types surrounding the focal grassland patch were measured as

percentages (%) of the bordering habitat. The percentages of open habitat

types (e.g., grasslands, cultivated fields, road banks) were summed to

describe the openness of a patch

Proportion of moist grassland vegetation The percentage (%) of moist grassland was estimated for each site to

describe the internal variation in habitat quality

Vascular plant species richness (total) The total number of vascular plant species observed within the study site

(see Pykala, 2003)

Vascular plant species richness (grassland specialists) The number of grassland-specialized vascular plant species observed within

the study site (see Pykala, 2003)

Vascular plant species richness (positive indicator species) The number of vascular plant species indicating well managed and low-

nutrient semi-natural grassland (see Pykala, 2003)

Vascular plant species density (average) The mean of vascular plant species observed within 1-m2 sample squares

(15 squares per site)

Vascular plant species density (CV) The coefficient of variation of vascular plant species observed within 1-m2

sample squares (15 squares per site)

Nectar plants (measurement II, average of measurements II

and III, and average of measurements I, II and III)

Amounts of nectar plants were measured in the field twice in 1999, in late

June and mid-August, and three times in 2000, in the first half of June, the

first half of July and the first half of August. On each occasion, the cover

classes (1 = <2%, 2 = 2–4%, 3 = 4–8%, 4 = 8–16%, 5 = 16–32%, 6 = 32–

64% and 7 = >64%) of 12 most abundant nectar plants were estimated and

summed to an index describing overall nectar abundance. Simultaneously a

simpler index of nectar abundance ranging from 0 (no nectar plants) to 10

(several abundant nectar plant species) was visually estimated. As the

correlation between the two indices was relatively high (r = 0.81), we

decided to use the simpler index in the analyses

Since the early summer of 1999 was very warm and dry, but that of 2000

was cool and partly rainy, the first measurement of 1999 and the second

measurement of 2000 were made at approximately the same phase of the

season. This measurement (referred to as Measurement II) and the yearly

averages of the individual nectar plant measurements were used in the

analyses

Weather variables

Temperature (average) The annual average of temperature observations made during butterfly and

moth counts

Temperature (CV) The annual coefficient of variation of temperature observations made

during butterfly and moth counts

Proportion of direct sunshine (average) The annual average of the proportion of direct sunshine observed during

butterfly and moth counts

Proportion of direct sunshine (CV) The annual coefficient of variation of the proportion of direct sunshine

observed during butterfly and moth counts

Wind speed (average) The annual average of wind speed during butterfly and moth counts

measured in the Beaufort scale

Wind speed (CV) The annual coefficient of variation of wind speed during butterfly and moth

counts measured in the Beaufort scale

476 J. Poyry et al. / Biological Conservation 122 (2005) 465–478

Appendix A (continued)

Variable group and variable Details of measurement and usage

Proportion of counts with <50% direct sun shine The proportion of counts with <50% direct sunshine during the count was

used to describe the weather differences between different sites

Proportion of counts with inappropriate weather The proportion of counts that did not fulfill the basic weather assumptions

of the transect method (Pollard, 1977, Biological Conservation 12, 115–

134) was used to describe the weather differences between different sites

J. Poyry et al. / Biological Conservation 122 (2005) 465–478 477

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