Agricultural and Food Science in Finland, Vol. 11 (2002): 121–135 121 A G R I C U L T U R A L A N D F O O D S C I E N C E I N F I N L A N D Vol. 11 (2002): 121–135. © Agricultural and Food Science in Finland Manuscript received February 2002 A G R I C U L T U R A L A N D F O O D S C I E N C E I N F I N L A N D Vol. 11 (2002): 121–135. Plant communities of field boundaries in Finnish farmland Sanna Tarmi MTT Agrifood Research Finland, Environmental Management, FIN-31600 Jokioinen, Finland. Current address: Depart- ment of Applied Biology, PO Box 27, FIN-00014 University of Helsinki, Finland, e-mail: sanna.tarmi@helsinki.fi Hannu Tuuri MTT Agrifood Research Finland, Data and Information Services, FIN-31600 Jokioinen, Finland Juha Helenius Department of Applied Biology, PO Box 27, FIN-00014 University of Helsinki, Finland To determine the importance of field boundary habitats for farmland biodiversity, we surveyed a total of 193 boundaries from four climatically and agriculturally dissimilar regions in Finland. We meas- ured the current plant species richness and composition of the boundaries, and, based on the differ- ences in vegetation characteristics, we describe six boundary types. The observed plant species were mainly indicators of fresh to wet soils and moderate to rich min- eral nitrogen content. The most frequent species were tall, perennial monocots and dicots indicating the high productivity of the vegetation. Moreover, herbicide-tolerant species were common. No spe- cies rare for Finland were found. In animal husbandry regions, the most frequent species were sown grassland species and typical grassland weeds. In cereal production regions, fast-spreading root weeds tolerant of herbicides were the most frequent. Mean species richness was highest in the cluster Ca- lamagrostis-Phalaris (24 species (s) / boundary (b)), which we considered as representative of moist sites with some disturbance by agricultural practices. Most species-poor were the clusters Elymus- Anthriscus (14 s/b) and Elymus-Cirsium (16 s/b), both found predominantly in cereal production regions in southern Finland. Our results suggest that the biodiversity value of boundaries is lowest in the most intensive cereal production areas and highest in areas of mixed farming. Key words: plant communities, correspondence analysis, boundaries, diversity, species richness Introduction Intensified agricultural land use has drastical- ly reduced semi-natural habitats. Traditional pastures and a variety of natural meadow types have almost disappeared (Alanen 1997). More- over, the amount of field boundaries has been considerably reduced (Ruuska and Helenius 1996, Hietala-Koivu 1999). In particular, sub- mailto:sanna.tarmi@helsinki.fi 122 A G R I C U L T U R A L A N D F O O D S C I E N C E I N F I N L A N D Tarmi, S. et al. Plant communities of field boundaries surface draining of fields to increase the cul- tivated area has decreased boundary areas, a common phenomenon in many European coun- tries since the 1950s. In Finland, the area of fields with subsurface drainage increased from 5.1% (of a total field area of 2 292 000 ha) in 1945 (Hilli 1949) to 53% (2 501 000 ha) in 1998 (Information Centre of the Ministry of Agriculture and Forestry 1999). Subsurface drainage is more common in cereal production regions in southern parts of Finland, where up to 91% of the parcel ditches have been re- moved during the last four decades (Hietala- Koivu 1999). Besides the decrease in the total boundary area, the remaining boundaries have been exposed to herbicide drift from crop spraying and fertiliser misplacement or run- off from cultivated fields, both of which sim- plify plant community structure and decrease species richness (Marrs et al. 1991, Kleijn and Snoeijing 1997, Hansson and Fogelfors 1998). Higher plant species diversity increases the t e m p o r a l s t a b i l i t y o f p l a n t c o m m u n i t i e s (Tilman et al. 1996). More diverse plant com- munities may also utilise soil mineral nitro- gen more efficiently than a species-poor eco- system (Tilman et al. 1996). Diverse plant communities are important also for hetero- t r o p h s e x p l o i t i n g t h e s e h a b i t a t s . S i e m a n n (1998) demonstrated that plant species diver- sity and productivity increased diversity also at higher trophic levels. The decreased area and harmful impacts of agricultural practices on remaining boundary habitats have been a common phenomena in Western Europe during the last century. Despite this, the importance of these habitats for wild- life of the agricultural environment has been shown in many studies. Boundaries enhance ar- thropod diversity, including the natural enemies of crop pests (Dennis and Fry 1992, Canters and Tamis 1999, Pfiffner and Luka 2000). They in- crease overall carabid densities (Fournier and Loreau 1999) in cultivated areas and provide overwintering habitats for e.g. spiders (Bayram and Luff 1993). Flowering plants are a food re- source for pollinators (Lagerlöf et al. 1992, Bäckman and Tiainen 2002). Field boundaries also provide important links among favourable habitat patches for butterfly species (Dover et al. 1992, Sparks and Parish 1995), and the vari- ous boundary types support a diverse butterfly fauna (Saarinen et al. 1998). Boundaries provide important feeding and nesting habitats for game- birds (e.g. Aebischer et al. 1994, Tiainen and Pakkala 2000). As a consequence of intensified land use, the decline in numbers of grey par- tridge, as well as several other farmland bird species, has been reported in Finland (Väisänen 1999). In this research, we tried to estimate the bi- odiversity value of Finnish field boundaries by surveying plant assemblages. Our specific ob- jectives were: 1) to describe plant species di- versity and composition in Finnish field bound- aries, 2) to identify boundary plant communi- ties based on species composition, and 3) to de- scribe the factors determining these types on the basis of the ecological requirements of the plant species. In addition, our objective was to estimate the value of boundary plant com- munities as secondary habitats for meadow plant species. The importance of current bound- ary plant communities for animals is also dis- cussed. We know only one earlier study on Finnish field boundary vegetation, which focused on the species’ value as silage for cattle, rather than on the biodiversity aspect (Hilli 1949). This study was made just before management measures of the 1st Finnish agri-environmental scheme required by EU regulations were applied. One target of the agri-environmental scheme is to maintain biodiversity and landscape in agri- cultural environment. In the basic scheme, man- agement agreement includes the widening of boundaries along waterways to one (main ditch- es) or three (stream, river, lake) meters wide. Boundaries should not be fertilized or treated with pesticides. Mowing is mentioned as a use- ful management for wildlife, but it is not oblig- atory treatment (Ministry of Agriculture and Forestry 2000). 123 A G R I C U L T U R A L A N D F O O D S C I E N C E I N F I N L A N D Vol. 11 (2002): 121–135. Material and methods Botanical studies of field boundaries were in- cluded in a broad nationwide MYTVAS -project on Monitoring the Impacts of the Agri-Environ- mental Support Scheme in 1995–1999. This project was carried out in four watershed regions, which are representative of agricultural regions in Finland. Lepsämänjoki, about 30 km N of Helsinki, and Yläneenjoki, about 50 km NE of Turku, are predominantly cereal production re- gions. Lestijoki, about 60 km SE of Kokkola, is a region of animal husbandry and mixed farm- ing, and Taipaleenjoki, about 20 km W of Joen- suu, is a typical animal husbandry region of small farms and fine-grained landscape structure. The co-ordinates of the regions are Lepsämänjoki 60°20’ N, 60°27’ N, 24°37’ E, 24°49’ E, Yläneen- joki 60°47’ N to 60°56’ N and 22°25’ E to 22°40’ E, Lestijoki 63°39’ N, 63°50’ N, 24°09’ E, 24°25’ E and Taipaleenjoki 62°36’ N, 62°38’ N, 29°10’ E, 29°20’ E. The most common soil types in Lepsämän- joki are sandy clay (in 55% of the boundaries), fine sand (26%), and clay (16%); in Yläneen- joki fine sand (61%) and sandy clay (31%); in Lestijoki fine sand (91%), and in Taipaleenjoki fine sand (59%), mull (19%) and silt (13%) (Tar- mi and Helenius, unpublished data). The aver- age thermal growing season in Yläneenjoki and Lepsämänjoki is 170 days, in Taipaleenjoki 155 days, and in Lestijoki 150 days (Alalammi 1987). Average annual precipitation is 582, 619, 612 and 544 mm, respectively. Our fieldwork period was from the beginning of July to mid-August 1995. To facilitate site selection in the field, we made a preliminary choice of boundaries from aerial photographs (scale 1:20000). Subsequently we refined the choice using the following criteria. (1) Location next to a waterway such as a main ditch, river or lake. (2) No or only a few trees and shrubs present (because these might affect the species composition in the herbaceous layer). (3) No forest edge next to a site because of the possible shading effects and the dispersal of forest field layer species. Only sites matching these criteria were included. We studied 193 boundaries in all (50 in Yläneenjoki, 52 in Lepsämänjoki, 58 in Lesti- joki and 33 in Taipaleenjoki). The boundary was determined as a zone from a field edge to the beginning of a slope. All plant species were measured in one to five 0.25 m2 quadrates (0.5 m x 0.5 m) in each boundary (Fig. 1). The dis- tance of a quadrate to the field was measured as the distance from the field edge to the nearest, parallel side of the quadrate. We aimed at a quad- rate distance of 50 cm from the field edge, but in practice these varied from zero to over two metres depending on the variation in boundary widths. When the boundary width was less than 50 cm, less than five quadrates were studied. When the boundary width was less than one metre, quadrate distance from the field was less than aimed 50 cm. In cases of over one metre the distance from the field was more than 50 cm. The width of a boundary was measured in all five quadrate sites to calculate the mean width based on five values. The minimum distance of the first sample quadrate from one end of a boundary was 10 metres and the distance be- tween quadrates 20 metres. We used Oksanen’s nine class scale (1981), 1 – ≤0.8%, 2 – ≤1.6%, 3 – ≤3.1%, 4 – ≤6.3%, 5 – ≤12.5%, 6 – ≤25%, 7 – ≤50%, 8 – ≤75%, 9 – ≤100%, in estimating plant species’ coverage. Because our field work schedule was tight, field workers identified sterile or difficult grasses only to genus level. In species nomenclature, we fol- low Hämet-Ahti et al. (1986). To describe the ecological characters of the species, we applied Ellenberg et al. (1991) indicator values. In the original data, we determined the cover values of the species in each 0.25 m2 sample quadrate using a nine-class scale. For the statis- tical analyses, we combined the quadrate data to calculate the mean cover of each species in a boundary. Boundaries with only two quadrates were made passive in the correspondence anal- ysis (CA), but were included in classification. Species which were present only in one bounda- ry were dropped from the CA (listed in App. 1) 124 A G R I C U L T U R A L A N D F O O D S C I E N C E I N F I N L A N D Tarmi, S. et al. Plant communities of field boundaries Fig. 1. Profiles of a study bounda- ry. The optimal location for sam- ple quadrates was 50 cm from field edge. See Tables 2 and 5 for the variation of boundary widths and distances of quadrates from fields. and those present only in two or three bounda- ries were unweighted, because in some applica- tions individual samples with species of low fre- quency may distort the analysis (Hill 1979). The quadrate data transformation was as fol- lows: Cover class 9 was merged with class 8. The classes for each species were replaced with the corresponding class centres by calculating the geometric means of lower and upper limits of cover percentages. The first cover class, >0–0.8%, was replaced by the arithmetic mean of the lower and the upper limits, as 0 does not Table 1. Number of boundaries/areas, their division into clusters, and the mean width (cm) of boundaries/clusters. Cluster LEPSÄ YLÄNE TAIPA LESTI Total Mean width SE Min Max 1 1 0 4 40 45 139 23.9 6 780 2 1 1 8 8 18 82 13.1 12 276 3 0 0 11 1 12 109 18.4 18 204 4 1 0 1 3 5 78 11.8 40 100 5 22 37 4 1 64 86 13.9 4 860 6 13 4 1 5 23 130 30.1 13 660 7 14 8 1 0 26 63 5.1 28 108 Total 52 50 33 58 193 SE = standard error of the mean Crop: • cereal • grass ley • rape • cabbage 125 A G R I C U L T U R A L A N D F O O D S C I E N C E I N F I N L A N D Vol. 11 (2002): 121–135. allow computing a geometric mean. A mean cov- er percentage per species was then obtained as an arithmetic mean of the quadrates. Finally, these cover percentages were replaced with the corresponding value from the original scale (classes from 1 to 8). These new values approx- imate the cover percentages of species (Oksanen 1981). We used ordination technique to reveal the major variation in the species abundance data of boundaries. CA was performed with the program Canoco™ (ter Braak 1987). By CA it may be possible to detect whether unknown environmen- tal variables determine the species occurrences in the data set (Jongman et al. 1995). The ordi- nation diagram presented the similarity or dis- similarity of the species compositions of the test boundaries. Based on the scores of the first four axes of ordination, the boundaries were grouped into clusters by Ward’s method (see Jongman et al. 1995). Cluster analysis was performed using the SAS™ Statistical package’s CLUSTER and TREE procedures. The mean species richness was measured for each cluster using only boundaries with an equal sample size of five quadrate samples to allow for the asymptotic dependence of the species number on the sample size. Because clustering is a subjective method, i.e. one may decide the number of groups to be left after fusion, we found it inappropriate to make any statistical test for species richness between clusters. However, we found it important to check whether the distance from the field could, at least partially, be one of the factors affecting the species richness in these data. To test the effect of distance from the field edge on plant species richness, we divided boundaries into three classes: 1) the mean dis- tance of the quadrates from field edge 0–19 cm (n = 60), 2) distance 20–39 cm (n = 36), and 3) distance > 40 cm (n = 50). To test the differenc- es between classes we used ANOVA, which was performed with SYSTAT™ (SPSS™ Inc. 1997). The normality of variables in ANOVA was checked from the normal probability plots of residuals. The homogeneity of variables was test- ed with Cochran’s test. Results The results of the CA ordination indicated dis- similarities in boundary vegetation between the regions. The studied regions formed three groups of plots in the first two axes in CA ordination (Fig. 2). Southern regions were plotted as one cloud of plots, whereas Lestijoki and Taipaleen- joki formed their own groups, from which Taipaleenjoki sites were plotted in a more scat- tered way. Points in the first two groups were arranged in relation to the first axis, while the Taipaleenjoki sites were scattered in relation to the second axis (Fig. 2). Based on the scores of the first four axes of ordination, we classified the boundaries by us- ing Ward’s clustering method. We found seven clusters to represent a reasonable level of ag- Fig. 2. Ordination diagram of correspondence analysis of the studied field boundaries based on their plant species composition. Different symbols represent the four study areas. For axis 1 eigenvalue = 0.424, percentage variance of species data 10.6, and for axis 2 eigenvalue = 0.224, percentage variance of species data 5.6. 126 A G R I C U L T U R A L A N D F O O D S C I E N C E I N F I N L A N D Tarmi, S. et al. Plant communities of field boundaries glomeration even though cluster 4 (C4) includ- ed only five boundaries at this level (Table 1, Fig. 3). Boundaries in C4 were interpreted as out- liers and were not considered as representative boundary group. In the next level of fusion C4 would have been merged with cluster 2 (C2). As in CA results, groups that were formed by clus- tering also indicated that some local environmen- tal factors may determine the vegetation com- position of boundaries. Cluster 1 (C1) included mainly Lestijoki sites and cluster 3 (C3) mainly Taipaleenjoki sites (Fig. 3, Table 1). Cluster 2 (C2) represents mainly sites from Taipaleenjoki and Lestijoki whereas clusters 5 (C5) and 7 (C7) represent mainly sites from Lepsämänjoki and Yläneenjoki. Cluster 6 (C6) is the most inde- pendent of any particular region and includes several sites from southern regions and Lesti- joki. Each cluster was described as a group of boundaries that had the most similar plant spe- cies compositions (Figs. 3 and 4). Because we have mainly genus data on monocot (grassy) species, we use the preliminary results of later studies in these regions to introduce the exact species. Unidentified species belonged most of- ten to the genera Poa, Festuca, Agrostis, Ca- lamagrostis and Carex (App. 1). According to the later studies on these regions (Tarmi and Helenius, unpublished results from 1997–1999), Poa turned out to be mostly P. pratensis, Festu- ca F. pratensis or F. rubra, and Agrostis A. cap- illaris, A. gigantea or A. stolonifera. Calama- grostis was most often C. canescens, C. arundi- nacea, C. epigejos or C. purpurea. Carex was identified as C. acuta, C. canescens, C. nigra, C. ovalis or C. vesicaria species. Each cluster was named by the characteris- tic species (Table 2) and were described as fol- lows: C1 – Ranunculus-Phleum: Grasses such as Ph- leum pratense, Poa sp., Agrostis sp., and Fes- tuca sp. were common. The perennial herbs Ranunculus repens, Rumex acetosa, Trifolium repens, Achillea millefolium, and Leontodon autumnalis were abundant. Annual species were rarely found. C2 – Filipendula-Ranunculus: In this cluster, none of the species attained absolute domi- nance compared to each other, but many spe- cies occurred with moderate frequency. It was characterised by tall herbs favouring moist sites such as Filipendula ulmaria, Angelica sylvestris, Cirsium helenioides and Calama- grostis sp.. Moreover, species of nutrient rich sites such as Urtica dioica, Epilobium angus- tifolium and Galeopsis sp. were common. C3 – Calamagrostis-Phalaris: Tall grasses Ca- lamagrostis sp. and Phalaris arundinacea were characteristic of the cluster. Perennial species indicating moist or wet sites – Carex sp., Achillea ptarmica, Angelica sylvestris, Lysimachia sp., Polygonum amhibium, Peu- cedanum palustre, Lactuca sibirica – were Fig. 3. Ordination diagram of correspondence analysis. Each plot represents one field boundary. Based on their species composition, boundaries are grouped into seven clusters from a cluster analysis (Ward’s method). For axis 1 eigen- value = 0.424, percentage variance of species data 10.6, and for axis 2 eigenvalue = 0.224, percentage variance of species data 5.6. Each symbol represents one cluster. 127 A G R I C U L T U R A L A N D F O O D S C I E N C E I N F I N L A N D Vol. 11 (2002): 121–135. frequent, as well as some annuals such as Polygonum hydropiper, Stellaria media and Galium uliginosum. C4 – Epilobium-Urtica: Most frequent species were Elymus repens, Epilobium angustifo- lium and Urtica dioica. C5 – Elymus-Anthriscus: Elymus repens was a highly dominant species. Other frequent spe- cies were mostly grasses, such as Phleum pratense, Poa sp., Alopecurus pratensis and ruderal herbs like Cirsium arvense, Anthris- cus sylvestris. A characteristic species for only this cluster, even if not very frequent, was Aegopodium podagraria. C6 – Elymus-Tripleurospermum: Elymus repens and Alopecurus pratensis were the most fre- quent grasses. Annual herbs such as Galeop- sis sp., Stellaria media, Tripleurospermum in- odorum, and Polygonum aviculare were char- acteristic of this cluster. C7 – Elymus-Cirsium: The most frequent spe- cies were Elymus repens, Calamagrostis sp., Cirsium arvense, Equisetum arvense, Lathy- rus pratensis, Tussilago farfara, Vicia crac- ca and Achillea millefolium. Fig. 4. Ordination diagram of cor- respondence analysis. Plotted are the most frequently occurring spe- cies, with each plot representing one species. For axis 1 eigenval- ue = 0.424, percentage variance of species data 10.6, and for axis 2 eigenvalue = 0.224, percentage variance of species data 5.6. Species abbreviations: ACH MIL Achillea millefolium, ACH PTA A. ptarmica, AEG POD Aegopo- dium podagraria, AGR SP Agros- tis sp., LYS SP Lysimachia sp., ALC SP Alchemilla sp., ALO PRA Alopecurus pratensis, ANG SYL Angelica sylvestris, ANT SYL Anthriscus sylvestris, ART VUL Artemisia vulgaris, CAL SP Ca- lamagrostis sp., CAR SP Carex sp., CER FON Cerastium fonta- num, CHE ALB Chenopodium al- bum, CIR ARV Cirsium arvense, CIR HEL C. helenioides, DES CES Deschampsia cespitosa, ELY REP Elymus repens, EPI ANG Epilobium angustifolium, ERY CHE Erysimum cheiran- thoides, EQU ARV Equisetum arvense, FES SP Festuca sp., FIL ULM Filipendula ulmaria, GAL SP Galeopsis sp., GAL ALB Galium album, GAL BOR G. boreale, GAL SPU G. spurium, GAL ULI G. uliginosum, GNA ULI Gnaphalium uliginosum, LAC SIB Lactuca sibirica, LAP COM Lapsana communis, LAT PRA Lathyrus pratensis, LEO AUT Leonto- don autumnalis, MAT MAT Matricaria matricarioides, MYO ARV Myosotis arvensis, PHA ARU Phalaris arundinacea, PHL PRA Phleum pratense, PLA MAJ Plantago major, POA SP Poa sp., POL AMP Polygonum amphibium, POL AVI P. aviculare, POL LAP P. lapathifolium, RAN ACR Ranunculus acris, RAN REP R. repens, RUB ARC Rubus arcticus, RUB IDA R. idaeus, RUM ACE Rumex acetosa, SON ARV Sonchus arvensis, SPE ARV Spergula arvensis, STE GRA Stellaria graminea, STE MED S. media, TAR SP Taraxacum sp., TRI MED T. medium, TRI PRA T. pratense, TRI REP T. repens, TRI INO Tripleurospermum inodorum, TUS FAR Tussilago farfara, URT DIO Urtica dioica, VAL SAM Valeriana sam- bucifolia, VIC CRA Vicia cracca, VIC SEP V. sepium, VIO ARV Viola arvensis, VIO PAL V. palustris. 128 A G R I C U L T U R A L A N D F O O D S C I E N C E I N F I N L A N D Tarmi, S. et al. Plant communities of field boundaries T ab le 2 . M os t f re qu en t a nd a bu nd an t s pe ci es a nd g en er a of C lu st er s 1– 7. B ol d a n d u n d er li n ed : s pe ci es f re qu en cy > = 5 0% o f th e si te s. B ol d : s pe ci es f re qu en cy < 5 0% > = 40 % o f th e si te s. I ta li cs a n d u n d er li n ed n ot ic ea bl y m or e fr eq ue nt c om pa re d to o th er c lu st er s. F or th e nu m be r of s it es in e ac h cl us te r, s ee T ab le 1 . M ea n (l og ) of c ov er c la ss is g iv en i n br ac ke ts . C lu st er 1 C lu st er 2 C lu st er 3 C lu st er 4 C lu st er 5 C lu st er 6 C lu st er 7 V eg et at io n ty pe E ly m u s- R a n u n cu lu s – F il ip en d u la - C a la m a g ro st is - E p il o b iu m - E ly m u s- T ri p le u ro E ly m u s- S pe ci es T ot al P h le u m R a n u n cu lu s P h a la ri s U rt ic a A n th ri sc u s S p er m u m C ir si u m M on oc ot yl ed on s E ly m u s re p en s 78 ( 4. 2) 51 ( 1. 9) 72 ( 3. 6) 67 ( 2. 4) 80 ( 3. 6) 92 ( 5. 6) 83 ( 4. 0) 92 ( 5. 9) P h le u m p ra te n se 60 ( 2. 2) 91 ( 4. 0) 61 ( 0. 8) 67 ( 1. 3) 20 ( 0. 2) 52 ( 2. 2) 39 ( 1. 5) 50 ( 1. 2) P o a s p. 60 ( 2. 0) 84 ( 4. 0) 67 ( 1. 2) 67 ( 1. 3) 20 ( 0. 6) 53 ( 1. 6) 35 ( 1. 4) 54 ( 1. 5) A lo p ec u ru s p ra te n si s 44 ( 1. 7) 22 ( 0. 5) 6 (0 .1 ) 17 ( 0. 3) 60 ( 1. 6) 64 ( 3. 0) 61 ( 2. 0) 50 ( 2. 2) C a la m a g ro st is s p. 28 ( 1. 2) 16 ( 0. 3) 61 ( 2. 8) 10 0 (4 .4 ) 60 ( 5. 4) 2 (0 .0 3) 9 (0 .1 ) 69 ( 2. 9) D es ch a m p si a c es p it o sa 36 ( 1. 5) 76 ( 3. 5) 72 ( 2. 9) 58 ( 2. 3) 20 ( 0. 2) 17 ( 0. 7) 9 (0 .3 ) 8 (0 .3 ) A g ro st is s p. 36 ( 1. 3) 82 ( 3. 9) 61 ( 1. 4) 58 ( 1. 3) 20 ( 0. 8) 8 (0 .1 ) 17 ( 0. 2) 19 ( 0. 4) F es tu ca s p. 33 ( 1. 2) 40 ( 1. 2) 17 ( 0. 8) 8 (0 .2 ) 20 ( 0. 2) 42 ( 1. 6) 13 ( 0. 2) 42 ( 1. 9) P h a la ri s a ru n d in a ce a 13 ( 0. 5) 2 (0 .1 ) 11 ( 0. 1) 75 ( 3. 9) 3 (0 .1 ) 17 ( 0. 3) 27 ( 1. 4) C a re x sp . 11 ( 0. 4) 13 ( 0. 6) 22 ( 0. 8) 75 ( 1. 8) 2 (0 .1 ) 4 (0 .2 ) P er en ni al d ic ot yl ed on s R a n u n cu lu s re p en s 58 ( 1. 8) 96 ( 3. 7) 83 ( 2. 8) 75 ( 2. 1) 40 ( 1. 4) 44 ( 0. 9) 39 ( 1. 2) 23 ( 0. 4) V ic ia c ra cc a 41 ( 1. 1) 24 ( 0. 8) 56 ( 1. 2) 50 ( 1. 3) 20 ( 0. 6) 42 ( 1. 1) 43 ( 1. 4) 58 ( 1. 6) C ir si u m a rv en se 46 ( 1. 6) 9 (0 .2 ) 33 ( 0. 9) 33 ( 1. 0) 40 ( 1. 6) 59 ( 1. 9) 57 ( 2. 3) 85 ( 3. 1) A ch il le a m il le fo li u m 48 ( 1. 2) 60 ( 1. 2) 72 ( 1. 4) 25 ( 0. 7) 48 ( 1. 7) 17 ( 0. 2) 58 ( 1. 4) A ch il le a p ta rm ic a 25 ( 0. 3) 51 ( 0. 6) 56 ( 0. 7) 67 ( 0. 9) 6 (0 .1 ) 4 (0 .0 4) 8 (0 .1 ) F il ip en d u la u lm a ri a 34 ( 1. 0) 53 ( 1. 3) 83 ( 3. 5) 42 ( 0. 7) 40 ( 2. 0) 14 ( 0. 4) 22 ( 0. 7) 23 ( 0. 5) T ri fo li u m r ep en s 33 ( 0. 6) 62 ( 1. 6) 22 ( 0. 3) 58 ( 0. 7) 17 ( 0. 2) 30 ( 0. 3) 23 ( 0. ) U rt ic a d io ic a 28 ( 0. 8) 24 ( 0. 8) 67 ( 1. 7) 8 (0 .1 ) 80 ( 4. 2) 22 ( 0. 5) 35 ( 1. 2) 15 ( 0. 3) A n g el ic a s yl ve st ri s 26 ( 0. 6) 31 ( 0. 5) 67 ( 1. 8) 58 ( 1. 2) 19 ( 0. 6) 9 (0 .1 ) 15 ( 0. 2) C ir si u m h el en io id es 18 ( 0. 6) 36 ( 0. 8) 67 ( 3. 1) 60 ( 3. 4) 5 (0 .2 ) R u m ex a ce to sa 28 ( 0. 7) 76 ( 2. 1) 56 ( 1. 1) 17 ( 0. 3) 20 ( 0. 2) 5 (0 .1 ) 13 ( 0. 1) 8 (0 .1 ) 129 A G R I C U L T U R A L A N D F O O D S C I E N C E I N F I N L A N D Vol. 11 (2002): 121–135. E p il o b iu m a n g u st if o li u m 12 ( 0. 5) 9 (0 .2 ) 61 ( 2. 6) 17 ( 0. 7) 80 ( 4. 6) 2 (0 .1 ) 9 (0 .1 ) E q u is et u m a rv en se 38 ( 0. 9) 33 ( 0. 7) 33 ( 0. 8) 17 ( 0. 2) 41 ( 1. 0) 30 ( 0. 8) 69 ( 1. 4) A n th ri sc u s sy lv es tr is 35 ( 1. 0) 4 (0 .1 ) 33 ( 0. 8) 17 ( 0. 2) 63 ( 2. 1) 26 ( 1. 0) 42 ( 0. 7) L a th yr u s p ra te n si s 33 ( 0. 9) 9 (0 .1 ) 28 ( 0. 6) 33 ( 0. 4) 20 ( 0. 2) 44 ( 1. 3) 22 ( 0. 4) 62 ( 2. 2) T u ss il a g o f a rf a ra 17 ( 0. 6) 2 (0 .0 2) 17 ( 0. 7) 42 ( 1. 8) 20 ( 0. 4) 9 (0 .2 ) 4 (0 .2 ) 58 ( 2. 1) T a ra xa cu m s p. 37 ( 0. 9) 36 ( 0. 7) 39 ( 0. 6) 33 ( 0. 3) 20 ( 0. 8) 47 ( 1. 2) 4 (0 .0 4) 50 ( 1. 5) L eo n to d o n a u tu m n a li s 17 ( 0. 4) 58 ( 1. 6) 17 ( 0. 2) 8 (0 .1 ) 2 (0 .1 ) 4 (0 .0 4) L ys im a ch ia s p. 8 (0 .2 ) 4 (0 .1 ) 28 ( 0. 9) 50 ( 1. 7) 4 (0 .0 4) 4 (0 .1 ) P o ly g o n u m a m p h ib iu m 7 (0 .2 ) 4 (0 .1 ) 17 ( 0. 6) 50 ( 1. 4) 2 (0 .0 2) 9 (0 .2 2) P eu ce d a n u m p a lu st re 4 (0 .1 ) 50 ( 0. 8) 2 (0 .0 2) R a n u n cu lu s a cr is 16 ( 0. 3) 33 ( 0. 9) 44 ( 0. 7) 17 ( 0. 3) 40 ( 0. 8) 3 (0 .1 ) 9 (0 .1 3) S o n ch u s a rv en si s 22 ( 0. 5) 2 (0 .0 2) 17 ( 0. 6) 25 ( 0. 4) 40 ( 0. 4) 17 ( 0. 3) 43 ( 1. 4) 46 ( 1. 1) A eg o p o d iu m p o d a g ra ri a 16 ( 0. 7) 4 (0 .1 ) 6 (0 .3 ) 3 1 ( 1 .5 ) 17 ( 0. 5) 15 ( 0. 5) A rt em is ia v u lg a ri s 7 (0 .3 ) 6 (0 .1 ) 3 (0 .1 ) 3 9 ( 2 .0 ) 4 (0 .1 ) L a ct u ca s ib ir ic a 5 (0 .1 ) 2 (0 .1 ) 17 ( 0. 3) 42 ( 1. 1) 4 (0 .1 ) A nn ua l di co ty le do ns G a le o p si s sp . 45 ( 0. 8) 22 ( 0. 3) 56 ( 1. 00 ) 25 ( 0. 3) 20 ( 0. 2) 47 ( 1. 0) 87 ( 2. 0) 50 ( 0. 6) S te ll a ri a m ed ia 45 ( 0. 7) 36 ( 0. 5) 28 ( 0. 6) 67 ( 0. 7) 20 ( 0. 2) 42 ( 0. 5) 83 ( 2. 3) 42 ( 0. 6) T ri pl eu ro sp er m um in od or um 31 ( 0. 8) 9 (0 .1 ) 17 ( 0. 2) 42 ( 0. 4) 20 ( 0. 2) 22 ( 0. 6) 83 ( 2. 8) 50 ( 1. 4) G a li u m u li g in o su m 13 ( 0. 2) 18 ( 0. 3) 39 ( 0. 4) 58 ( 0. 7) 2 (0 .0 2) 4 (0 .0 4) 4 (0 .0 4) P o ly g o n u m a vi cu la re 17 ( 0. 2) 18 ( 0. 3) 11 ( 0. 1) 8 (0 .1 ) 6 (0 .1 ) 57 ( 0. 8) 15 ( 0. 2) L a p sa n a c o m m u n is 15 ( 0. 2) 11 ( 0. 2) 13 ( 0. 2) 43 ( 0. 8) 31 ( 0. 5) C h en o p o d iu m a lb u m 12 ( 0. 2) 7 (0 .1 ) 11 ( 0. 1) 9 (0 .1 ) 43 ( 0. 7) 12 ( 0. 2) E ry si m u m c h ei ra n th o id es 9 (0 .1 ) 4 (0 .0 4) 11 ( 0. 1) 3 (0 .0 3) 3 5 ( 0 .4 ) 15 ( 0. 2) F a ll o p ia c o n vo lv u lu s 7 (0 .1 ) 3 (0 .0 3) 3 5 ( 0 .6 ) 12 ( 0. 1) G a li u m b o re a le 15 ( 0. 4) 4 (0 .1 ) 6 (0 .1 ) 19 ( 0. 7) 3 5 ( 1 .0 ) 19 ( 0. 5) G a li u m s p u ri u m 7 (0 .1 ) 2 (0 .0 2) 3 (0 .0 3) 3 0 ( 0 .6 ) 12 ( 0. 3) P o ly g o n u m h yd ro p ip er 6 (0 .1 ) 2 (0 .0 2) 11 ( 0. 2) 42 ( 0. 4) 20 ( 0. 2) 2 (0 .0 2) 9 (0 .2 ) G n a p h a li u m u li g in o su m 13 ( 0. 2) 16 ( 0. 2) 22 ( 0. 4) 3 3 ( 0 .3 ) 3 (0 .0 3) 26 ( 0. 7) 12 ( 0. 1) M yo so ti s a rv en si s 12 ( 0. 2) 7 (0 .1 ) 8 (0 .1 ) 20 ( 0. 2) 9 (0 .1 ) 3 5 ( 0 .5 ) 15 ( 0. 2) S p er g u la a rv en si s 11 ( 0. 2) 16 ( 0. 2) 11 ( 0. 2) 17 ( 0. 2) 3 (0 .0 3) 3 0 ( 0 .7 ) 4 (0 .0 4) V io la a rv en si s 9 (0 .1 ) 2 (0 .0 2) 6 (0 .1 ) 8 (0 .1 ) 3 0 ( 0 .4 ) 15 ( 0. 2) 130 A G R I C U L T U R A L A N D F O O D S C I E N C E I N F I N L A N D Tarmi, S. et al. Plant communities of field boundaries The mean species richness was highest in the Calamagrostis-Phalaris type (Table 3) whereas Elymus-Anthriscus and Elymus-Cirsi- um types were the most species-poor among all types. When the effect of distance from the field on species richness was tested, no statistically significant differences between the three class- es (ANOVA, df = 2, f = 1.23, P = 0.29) was found. The mean species richness next to field edges with crops was 16.12 ± 0.87 (mean ± SE), at 20–39 cm distance from the field edge 17.14 ± 1.12, and at 40 cm or more from the edge 18.14± 0.95. The mean widths of the boundaries were highest in C1 and in C6 (Table 1). The narrow- est boundaries, slightly over half metre in width, were in C7. The total number of plant species identified in the boundaries was 140. This number does not include plants identified only to genus level, except the Taraxacum genus. After the data modifications that preceded statistical analyses, 100 identified species were included in CA and cluster analysis. The eco- logical requirements of these species were de- scribed based on Ellenberg et al. (1991) classi- fication. However, some species’ ecological re- quirements are not fully understood, so that the occurrence of 87 species in relation to soil mois- ture and 80 species in relation to soil nitrogen were included for further description. In this study, none of the examined species indicated dry soil conditions, but 12% of the species indicated soil conditions between dry and fresh. More than half of the species (52%) indi- cated moderately fresh conditions, 25% indicat- ed moist or nearly wet soils, and 11 % indicated wet soils. For mineral nitrogen, 17% of the spe- cies indicated poor soils and the largest group, 45% of the species, indicated intermediate soils. Nitrogen-rich soils were indicated by 17% of species and 16% (13 species) were nitrogen in- dicators. Discussion Plant species observed during the survey were mainly species indicating fresh to wet soil mois- ture conditions and moderate to rich mineral ni- trogen content in the soil. The most frequent species were tall, perennial monocots and dicots indicating high productivity in the boundaries. Moreover, many of the observed species are known to tolerate herbicides, which has proba- bly enhanced their abundance in boundaries ex- posed to herbicide drift from crop sprayings, or from direct sprayings that were permitted until 1994. As with the results of Kleijn et al. (1998) study of boundaries elsewhere in Europe, we observed no rare plant species. Species listed by Table 3. Plant species richness per 1.25 m2 (five 0.25 m2 quadrates) and distance (cm) of quadrates from the field edge in each cluster. Species Distance richness from field Cluster N Mean SE Min Max Mean SE Min Max 1 37 19 5.4 6 28 28 2.9 0 50 2 12 20 8.2 10 35 40 17.4 0 226 3 9 24 8.3 12 36 38 5.7 0 50 4 3 13 3.6 8 15 43 1.8 40 46 5 48 14 5.1 2 24 21 3.2 0 80 6 19 19 5.6 11 35 29 6.1 0 89 7 19 16 5.6 7 23 19 3.9 0 50 N = number of boundaries, SE = standard error of the mean 131 A G R I C U L T U R A L A N D F O O D S C I E N C E I N F I N L A N D Vol. 11 (2002): 121–135. Hilli (1949) as the most abundant were similar to those in our study except Leucanthemum vul- gare. It used to be a common grassland weed species, but has declined due to gradual chang- es in cultivation methods (Raatikainen 1991). In this study it was found only once. Lestijoki and Taipaleenjoki are dairy produc- tion regions (Granlund et al. 2000) and more than half of the cultivated area in the crop rotation is grassland (Grönroos et al. 1998) for grazing and silage. These are not ploughed annually but at intervals of three to five years. Compared to ce- real production herbicides are rarely used. Ac- cording to our field observations, especially on the pastures, grassland fields often reach in to the boundary area or, on gently sloping river- banks, even to the shoreline. This means that the border between the original boundary and culti- vated grassland is unclear, or in extreme situa- tions there is no original boundary but only ley grassland. Boundaries highly similar in species to ley grassland were mainly grouped into the C1, Ranunculus-Phleum type, even if their rela- tive abundance of species was different. The most commonly cultivated species such as Ph- leum pratense and Festuca pratensis as well as many species that are considered typical grass- land weeds in leys, were frequent. Especially Le- ontodon autumnalis is common in boundaries and in old leys, where the coverage of sown grasses has decreased (Raatikainen 1991). For C2, the Calamagrostis Phalaris type, several species favouring nitrogen and moist soils were characteristic. Of the boundaries studied, C2 rep- resents probably the most fertile sites. In C2 the dominant species indicate moist or wet soil con- ditions. Moisture conditions may explain the high species richness in this group. These bound- aries were probably left in a natural state and were not affected by cultivation practices, as the species composition would indicate. This is be- cause seasonally wet habitats are impossible or not profitable to cultivate. Thereby these bound- aries seem to belong to the least disturbed habi- tat type among the groups. Lactuca sibirica, typ- ically a species of river and stream shores in E and N Finland, is more frequent in this than in the other clusters. C2 and C3 have the highest species diversity of all the groups. This may be partly explained by crop rotation, which is com- mon in the Lestijoki and Taipaleenjoki regions. Crop rotation has been shown to be an impor- tant factor for boundary species composition (Kleijn and Verbeek 2000). In Taipaleenjoki, the landscape is also more fine-grained, and agri- culture is less intensive than in the other regions, which may have contributed to the higher spe- cies richness in C2, the Calamagrostis-Phalaris group. Clusters C5, Elymus-Anthriscus, C6, Elymus- Tripleurospermum, and C7 Elymus-Cirsium, rep- resent southern regions. There more than half the field area is under spring cereal production year- ly, which means ploughing, tilling and the use of herbicides are annual practices. In these fair- ly similar clusters, species tolerant of herbicides and/or capable of spreading fast by rhizomes or seeds to bare soil gaps were the most common. Elymus repens and Cirsium arvense were fre- quent everywhere, most of all in C7. These most frequent species indicate fresh soil moisture con- ditions. Of all six representative clusters C5 was the poorest in species. Only a few species, mainly ruderals, constituted the main part of the vege- tation in C5. However, the mean number of spe- cies was clearly higher even in this species poor group compared with a study on Dutch bounda- ries (Kleijn 1997). Even though the sampling areas in the Dutch study were larger than ours (4 m2), the highest mean number of species among groups was 11.8. Aegopodium podagraria was the characteristic species of C5. It is native to southern Finland and easily invades new sites using rhizomes. C7 is close to C5, but the high- er numbers of frequently encountered species indicate a slightly more heterogeneous vegeta- tion structure. However, the frequency and abun- dance of Elymus repens was very high in both groups. C6 differs from others by the frequent occurrences of annual species, which is indica- tive of recent disturbance destroying permanent vegetation cover. This was probably caused by recent mechanical disturbance during cultiva- tion. Also, heavy rains in summer 1995, just be- 132 A G R I C U L T U R A L A N D F O O D S C I E N C E I N F I N L A N D Tarmi, S. et al. Plant communities of field boundaries fore our fieldwork started, may have caused soil disturbance. In several boundaries we observed gaps caused by erosion without permanent veg- etation cover. Exceptional weather conditions may have enhanced the amount of annuals in 1995 compared to more typical summers. This suggests that temporal aspects such as the stage of vegetation succession, should also be consid- ered in boundary classification. According to this study, the sample quadrate distance from the field was not a significant fac- tor for species richness. However, boundary width has been shown to be significant for over- all species diversity in boundary habitats (Ma et al. 2002). Cultivation practices affect boundary vegetation with different intensity depending on the distance from the field. As a result, variable vegetation zones have developed in the bounda- ry, which increases species diversity in the whole boundary community (Ma et al. 2002). On the basis of our study, the effects of farm- ing practices on species composition seem ob- vious. However, also indirect factors should be considered. The current division between crop and dairy production along Finland’s north-south gradient is partly a consequence of the country’s climatic conditions, which allows profitable crop production only in southern parts of Finland. Another explanatory factor is the agricultural policy of the 70s, which also supported this re- gional specialisation of farms into crop or dairy production. In the past few years an increase in organic production has favoured mixed farming also in the south because of the need for animal manure for organic crop production. Mixed farm- ing could enhance the diversity of boundary types at farm level, which was reported as being important in e.g. providing food for granivorous birds (Wilson et al. 1999). In our results, many of the boundaries were species-poor and dominated by grasses. At a boundary level they have low diversity value but at a landscape level they may increase the inter- boundary diversity among boundaries with dis- similar species compositions (Le Coeur et al. 1997). Tussocks forming grasses are important overwintering sites for spiders and ground bee- tles, some of them being also beneficial to pest predators (Bayram and Luff 1993, Dennis et al. 1994). Among grasses of this growth form Agros- tis and Poa species and Deschampsia cespitosa were common in the studied boundaries. We did not measure the flowering intensity of plants, which prevents us from estimating the exact im- portance of species as sources of nectar. How- ever, it is known that many frequently found species such as Cirsium arvense and Epilobium angustifolium are important nectar flowers for butterflies (Kuussaari et al. 2001) and for bum- blebees (Bäckman and Tiainen 2002). Moreover, such species as Urtica dioica, Festuca sp. and Poa sp. are important host plants for butterfly larvae (Silfverberg 1996). Many common weed species were observed frequently in the boundaries and farmers often regard boundaries as a source of weeds and thus basically harmful. However, weeds have been reported as spreading only short distances into a field (Marshall 1989, Marshall and Arnold 1995, Wilson and Aebischer 1995). When weeds, es- pecially fast spreading clonal weeds such as Ely- mus repens and Cirsium arvense, dominate the boundary community, management is needed to diminish their abundance. Cutting and remov- ing should thus be applied in order to reduce not only weeds but also nutrient and litter accumu- lation in boundaries. If nutrients are not dimin- ished by biomass removal, boundaries buffer nutrient leaching to surface waters for only a short time. Moreover, increased mineral nitro- gen results in higher productivity and litter ac- cumulation, which may decrease the species di- versity by preventing seedlings from becoming established (Foster and Gross 1998). Kleijn (1996) also stressed the importance of cutting and removing to avoid nutrient accumulation, because boundary species are able to capture nutrients from a field. If weeds are a serious problem in a boundary, re-establishment by sow- ing could be an option. Biodiversity values re- mains low if only grassy species are sown. How- ever, species such as Dactylis glomerata have been demonstrated to be effective in suppress- ing invasions of Elymus repens (Marshall 1990). 133 A G R I C U L T U R A L A N D F O O D S C I E N C E I N F I N L A N D Vol. 11 (2002): 121–135. Ideally local seed mixtures of wild plants could be used to enhance species richness, but this may be difficult in practice. Sown species may be too sensitive to herbicides, so that one accidental herbicide drift may destroy the vegetation. Such species may also not have the ability to survive in nutrient rich, disturbed habitats such as bound- aries most often are. Agricultural practices are important for de- termining plant communities in boundaries. These habitats are exposed to herbicides, ferti- lisers, ploughing, and sometimes even used as grassland. The intensity of different disturbance factors and the species’ response to them large- ly determines the species composition. Variation in species compositions was found mainly be- tween regions, therefore regionally focused stud- ies are needed to gain a better understanding about local factors. This study provides a basis for further planning of more analytical studies of field boundary plant communities, and ani- mals dependent on the vegetation. Kleijn et al. (2001) made evident the insuffi- ciency of current agri-environment schemes to protect biodiversity in the Netherlands, where agriculture is extremely intensive comparing to Finland. Nevertheless, we found species poor boundaries especially in southern areas, which may need additional management as mowing with biomass removal or cattle grazing to im- prove species diversity. However, these practis- es are difficult to carry out in boundaries usual- ly not more than three meters wide. Acknowledgements. We are grateful to Virpi Aalto, Erkki Alho, Mira Heiskanen, Teppo Häyhä, Eija Lintula, Anne Nissinen, Aki Sinkkonen and Pekka Ylhäinen, who collected the data in the field. We also want to thank Jan-Peter Bäck- man, Maohua Ma, Laura Seppänen, Iryna Herzon, K.V. 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Lisäksi kasvit olivat typen suosijoita, jotka viihtyvät parhai- ten kohtalaisesti tai sitä runsaammin mineraalityppeä sisältävillä kasvupaikoilla. Yleisimmät lajit olivat korkeakasvuisia, monivuotisia yksi- ja kaksisirkkai- sia, jotka tuottavat biomassaa runsaasti. Myös rikka- kasvien torjunta-aineita sietävät lajit olivat yleisiä. Suomessa harvinaisia kasvilajeja ei pientareilta ha- vaittu. Tuotantomuotojen alueelliset erot näkyivät kasviyhteisöissä. Karjatalousvaltaisilla alueilla ylei- simmät lajit olivat kylvettäviä nurmilajeja ja nurmi- en rikkakasveja. Viljanviljelyalueilla herbisidejä sie- tävät ja nopeasti leviävät juuririkkakasvit olivat ylei- simpiä. Lajimäärä oli suurin Calamagrostis-Phalaris tyypissä (24 lajia /piennar), jonka tulkitsimme ole- van kostea ja luonnontilainen kasvupaikka. Pienim- mät lajimäärät olivat Elymus-Anthriscus (14 lajia/ piennar) ja Elymus-Cirsium tyypeillä, joita löytyi eni- ten viljanviljelyyn keskittyneiltä eteläisiltä alueilta. Tulosten perusteella viljelytoimilla on suuri mer- kitys pientareiden kasviyhteisöjen lajikoostumukseen. Nurmen kuuluminen viljelykiertoon, muokkauksen tehokkuus ja rikkakasvien torjunta-aineiden käyttö ovat ilmeisesti tärkeitä kasvillisuuteen vaikuttavia tekijöitä. Aiemman maatalouspolitiikan seurauksena viljanviljely on keskittynyt eteläisille ja karjatalous taas pohjoisemmille maatalousalueille, mikä on epä- suorasti vaikuttanut alueelliseen piennarkasvillisuu- teen. Jatkotutkimuksissa on tarpeen selvittää, miten pientareet eroavat alueiden sisällä toisistaan ja mit- kä paikalliset tekijät eroja aiheuttavat. 136 A G R I C U L T U R A L A N D F O O D S C I E N C E I N F I N L A N D Appendix 1. List of species found in boundaries. Abbreviation Species Abbreviation Species I ACH MIL Achillea millefolium L. O Leucanthemum vulgare Lam. I ACH PTA A. ptarmica L. I Linaria vulgaris Mill. I AEG POD Aegopodium podagraria L. I Lolium perenne L. I Agrostis capillaris L. O Luzula pallescens Swartz O A. gigantea Roth O L. sudetica (Willd.) DC. O A. stolonifera I LEO AUT Leontodon autumnalis L. I AGR SP Agrostis sp. L. I LYS SP Lysimachia sp. L. I ALC SP Alchemilla sp. L. O Maianthemum bifolium (L.) F.W. Schmidt I Alopecurus geniculatus L. I MAT MAT Matricaria matricarioides (Less.) Porter I ALO PRA A. pratensis L. I Mentha arvensis L. I ANG SYL Angelica sylvestris L. I MYO ARV Myosotis arvensis (L.) Hill O Anthoxanthum odoratum L. O Nardus stricta L. I ANT SYL Anthriscus sylvestris (L.) Hoffm. O Odontites vulgaris Moench O Arctium tomentosum Miller I Peucedanum palustre (L.) Moench I ART VUL Artemisia vulgaris L. I PHA ARU Phalaris arundinacea L. O Atriplex patula L. I PHL PRA Phleum pratense L. I Barbarea vulgaris R.Br. I Phragmites australis (Cav.) Trin. ex Steud. I Betula sp. L. O Pimpinella saxifraga L. I Bidens tripartita L. I PLA MAJ Plantago major L. I CAL SP Calamagrostis sp. Adans. I POA SP Poa sp. L. I C. rotundifolia L. I POL AMP Polygonum amphibium L. O Caltha palustris L. I POL AVI P. aviculare L. O Campanula glomerata L. I P. hydropiper L. O C. patula L. I POL LAP P. lapathifolium L. I Capsella bursa-pastoris (L.) Medik. I Potentilla anserina L. I CAR SP Carex sp. L. O P. erecta I Cerastium arvense L. I P. norvegica L. I CER FON C. fontanum Baumg. I RAN ACR Ranunculus acris L. I CHE ALB Chenopodium album L. I RAN REP R. repens L. I C. suecicum Murr O Rhinanthus serotinus (Schönh.) Oborny O Cicuta virosa L. I Rorippa palustris (L.) Besser I CIR ARV Cirsium arvense Mill. O Rosa majalis J. Herrmann I CIR HEL C. helenioides (L.) Hill I Rosa sp. L. O Convallaria majalis L. I RUB ARC Rubus arcticus L. I Cuscuta europaea L. I RUB IDA R. idaeus L. I Dactylis glomerata L. I RUM ACE Rumex acetosa L. I DES CES Deschampsia cespitosa (L.) P.Beauv. I R. acetosella L. O Eleocharis mamillata (H. lindb.) H. I R. longifolius DC. Lind. ex Dörfler I Elymus caninus (L.) L. O Sagina procumbens L. I ELY REP E. repens (L.) Gould I Salix sp. L. I Epilobium adenocaulon Hausskn. I Scirpus sylvaticus L. I EPI ANG E. angustifolium L. O Scleranthus annuus L. I E. palustre L. O Scrophularia nodosa L. I EQU ARV Equisetum arvense L. O Solidago virgaurea L. I E. fluviatile L. I SON ARV Sonchus arvensis L. I E. palustre L. I S. asper (L.) Hill I E. sylvaticum L. I SPE ARV Spergula arvensis L. O Eriophorum angustifolium Honckeny O Stachys palustris L. I ERY CHE Erysimum cheiranthoides L. I STE GRA Stellaria graminea L. I Euphorbia helioscopia L. I STE MED S. media (L.) Vill. 137 A G R I C U L T U R A L A N D F O O D S C I E N C E I N F I N L A N D Appendix 1. List of species found in boundaries. Abbreviation Species Abbreviation Species I Euphrasia stricta D. Wolff ex O Succisa pratensis Moench J.F.Lehm. I Fallopia convolvulus (L.) Á. Löve I Tanacetum vulgare L. I FES SP Festuca sp.L. I TAR SP Taraxacum sp. Weber I FIL ULM Filipendula ulmaria (L.) Maxim. I Thalictrum flavum L. I Fumaria officinalis L. O Thelypteris phegopteris (L.) Slosson I GAL SP Galeopsis sp. L. O Thlaspi arvense L. I GAL ALB Galium album Mill. I Trifolium hybridum L. I GAL BOR G. boreale L. I TRI MED T. medium L. I G. palustre L. I TRI PRA T. pratense L. I GAL SPU G. spurium L. I TRI REP T. repens L. I GAL ULI G. uliginosum L. I TRI INO Tripleurospermum inodorum Sch. Bip. O Geranium sylvaticum L. I TUS FAR Tussilago farfara L. O Glechoma hederacea L. I URT DIO Urtica dioica L. O Glyceria fluitans (L.) R. Br. O U. urens L. I GNA ULI Gnaphalium uliginosum L. O Vaccinium myrtillus L. I Hierochloë hirta (Schrank) Borbás I VAL SAM Valeriana sambucifolia J.C. Mikan I Hypericum maculatum Crantz O Valeriana sp. I Juncus bufonius L. I Veronica chamaedrys L. O J. effusus L. I V. officinalis L. I J. filiformis L. O V. serpyllifolia L. I LAC SIB Lactuca sibirica (L.) Maxim. O V. spicata L. I Lamium hybridum Vill. O Veronica sp. L. O Lamium sp. L. I VIC CRA Vicia cracca L. I L. purpureum L. I VIC SEP V. sepium L. I LAP COM Lapsana communis L. I VIO ARV Viola arvensis Murray I LAT PRA Lathyrus pratensis L. O V. canina O Lemna minor L. I VIO PAL V. palustris L. Species marked with (I) were included in and species marked with (O) were omitted or made passive in correspondence analysis. The 60 most frequent species (with abbreviations) are plotted in Fig. 3. Title Introduction Material and methods Results Discussion References SELOSTUS