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Effects of changes in agricultural land-use on landscape structure and arable weed vegetation over the last 50 years

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Effects of changes in agricultural land-use on landscape structure and arable weed vegetation over the last 50 years
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        U      N     C     O      R      R      E     C      T      E      D       P      R     O     O      F Effects of changes in agricultural land-use on landscape structureand arable weed vegetation over the last 50 years Cornelia Baessler*, Stefan Klotz UFZ Centre for Environmental Research Leipzig-Halle Ltd., Department of Community Ecology, Theodor-Lieser Str. 4, D-06120 Halle, Germany Received 19 January 2005; received in revised form 5 December 2005; accepted 12 December 2005 Abstract Agricultural dynamics and associated changes in the structure of habitat patches affect species composition and distribution in thelandscape.Land-use,landscapechanges andvegetationchangesofweedswereanalysedina4 km 2 area inCentralGermany(Saxony-Anhalt)from 1953 to 2000. This period includes the collectivisation (1952–1968), the agricultural industrialisation (1969–1989) and the privatisationof agricultural land following the political changes in East Germany in 1990. For the analyses, historic and current aerial photographs andvegetationdatawereused.Landscapeindicesandtheaverageamountofmineralfertilizerswereusedasindicatorsforlandscapestructureandland-use intensity. Intensification of agriculture and the collectivisation in East Germany in the fifties and sixties led to a decline of the spatialheterogeneity of the landscape matrix (arable fields). The average number and cover of weed species, especially archaeophytes, decreasedsignificantly since 1957. However, the total number of weed species increased. There was a remarkably high number of species with anaverage cover below 0.05%, called ‘‘chance’’species in 2000. Out of 17 tested landscape indices only mean patch size and mean patch fractaldimension were significantly correlated with the average number of weed species. The average amount of the mineral fertilizer potash used asland-use intensity indicator was significantly negatively correlated with the total number of weed species. However, there was an increase inthe number of farms after 1990 without changes in landscape structure and arable weed vegetation. The results suggest that structuralvariability of the landscape and habitat quality are the principal correlates of plant species diversity. # 2005 Published by Elsevier B.V. Keywords:  Agricultural policies; Landscape change; Landscape indices; Land-use history; Vegetation change; Weeds 1. Introduction Agriculturalland-useisdynamicandisrelatedtochangesin the structure of habitat patches, e.g. their spatial pattern,size or connectivity (Arx von et al., 2002; LaGro, 2001;Wagner et al., 2000). Agricultural intensification implieschanges such as an increase in plot size of arable fields andthe removal of linear elements. The resulting habitatisolation affects plant population dynamics and its basicprocesses at the landscape level, e.g. migration orcolonisation. This is likely to play an increasingly importantrole for biodiversity patterns at the landscape level becausemany plant populations become isolated in otherwiseunsuitable landscapes. This is why biodiversity studiesneed to be conducted also at the landscape level (Wienset al., 1993).More than half of the territory of the E.U. is managed byfarmers today (Vidalis and Lucas, 1999). The highest levelof plant species diversity was reached in the 19th century,including many archaeophytes, known to be typical ‘weeds’adapted to agricultural land-use (Ja¨ger, 1977). However,increasing agricultural intensification led to changes inlandscapestructureandthusinthecompositionanddiversityof weed communities after 1950 (e.g. Medley et al., 1995).In East Germany, four periods of agricultural policiesafter the Second WorldWarcan be distinguished. During thefirst period from 1945 to 1952 a land reform was carried out(Eckart and Wollkopf, 1994). A state pool of the wholeground was created and small- and medium-sized farming www.elsevier.com/locate/ageeAgriculture, Ecosystems and Environment xxx (2006) xxx–xxx 1234567891011121314151617181920212223242526272829303132333435363738394041424243444546474849505152535455565758 * Corresponding author. Tel.: +49 345 5585 317; fax: +49 345 5585 329. E-mail address:  cornelia.baessler@ufz.de (C. Baessler).0167-8809/$ – see front matter # 2005 Published by Elsevier B.V.doi:10.1016/j.agee.2005.12.007AGEE 2731 1–8        U      N     C     O      R      R      E     C      T      E      D       P      R     O     O      F units were developed during this time. During the secondperiod (1952–1968) called ‘‘collectivisation’’, which wasconnected with the creation of the socialist state and of socialist public property, small farms were pooled to formlarge agricultural producers’ cooperatives (‘‘LPG’’). Onlyfewcompanieswith manyemployeeshandledalargeareaof arable fields and a high number of animals. In the thirdperiod (1968–1989) of ‘‘industrial agriculture’’ agriculturalintensification increased, with progressive enlargement of farms associated with a separation of the farms for plant andanimal production. However, 1990 marked another majorturning point in agricultural policy, when the fourth periodstarted with the privatisation of agricultural land followingthe political changes in East Germany. All agriculturalproducers’ cooperatives had been shut down by the end of 1991 (Eckart and Wollkopf, 1994) and since 1990, allGerman agricultural policies are subject to E.U. norms andregulations.So far numerous reports have dealt with the changes inthe weed communities in Germany (e.g. Hilbig andBachthaler, 1992; Otte, 1984). Only a few (e.g. Voigtla ¨nderet al., 2001) however have included the period after thepolitical change and thus the modified agricultural situationin East Germany since 1990.The objectiveof this study was to explorethe influence of changing agricultural land-use and landscape structure onweed species richness in the last 50 years. We used data setsfrom the periods 1952–1968, 1969–1989 and after 1990 andfocused on the following questions:   What were the effects of changing agricultural land-useon the landscape structure, especially the arable fields?   How did plant species numbers and species compositionof agricultural habitats change?   Whatarethe mainfactorscontrollingspeciesrichnessandcomposition in arable fields? 2. Material and methods 2.1. Study area The study area is located in the dry region of CentralGermany near the village of Friedeburg (10 8 34 0 E, 45 8 12 0 N)and covers about 4 km 2 . It has subcontinental climaticconditions with a mean annual air temperature of about 9  8 C(Veit et al., 1987) and an average annual precipitation below500 mm.A plateau with nutrient rich loess deposits borders thesteep slopes of the river Saale valley that forms the eastborder of the study area. The rivers Saale and Schlenzeformedawidefloodplainwith alluvial soiltothe southofthestudyarea.Thegeodiversityinthestudyareaiscoupledwithhigh habitat and land-use diversity. The slopes are coveredwith woodland, meadows and pastures, and the areas of thefloodplain and the plateau are under intense arable use. 2.2. Floristic data Floristicinventoriesofweedspeciesofarablefieldsinthestudy area were available for the three periods from surveysperformed in 1957 (Schubert and Mahn, 1959, 120 releve ´s),1979 (Westhus, 1980, 115 releve´s) and 2000 (220 releve´s).The current floristic composition of arable fields wasdocumented by vegetation releve´s that were made from Mayto September 2000, just before harvesting of the differentcrop types. The releve´s (100 m 2 ) were randomly placed inthe total arable area. The sample plots were located at least20 m from the field margins, because the agriculturalconditions and thus the vegetation of this area often differfrom the rest of the field (Elsen van, 1989). As in pastinventories, the phytosociological method was followedaccording to Braun-Blanquet (1951) and Wilmanns (1989). Nomenclature of plant species follows Rothmaler (1994). 2.3. Land-use intensity and landscape structure As general indicators of land-use intensity the averageamount of mineral fertilizers applied and farm size structurewas used. Data for the three periods were taken for 1957,1979 and 2000 from statistical yearbooks of the formerGerman Democratic Republic (GDR) and the states of EastGermany (Staatliche Zentralverwaltung fu¨r Statistik, 1960,1980, 1987; Statistisches Landesamt Sachsen-Anhalt, 2000,2001).Landscape structure was quantified by a set of landscapeindices derived from land-use data. Data used for the threeperiods were extracted from aerial photos (black and whiteorthophotos) recorded in 1953 (1:22,000), 1969 (1:12,300)and 1997 (1:14,500). For the third period, we had to use theaerial photo recorded in 1969 because no aerial photo closerto 1979 was available. However, from the end of the 1960suntil the beginning of the 1980s landscape structure did notchange a lot (Schubert, 2001, personal communication).Minor changes of landscape structure between 1997 and2000 were updated and ground truthing was performed byfield mapping in 2000. To minimise possible interpretationerrors the interpretation of all aerial photos was carried outby the same person. The land-use classification systemincluded only seven types: woodland (including all woodyhabitats), meadows, dry and semi-dry grassland, arablefields, built-up areas, the river Saale and ‘‘others’’(unclassified areas, total proportion  < 3%, Table 1). Basedon the landscape elements (Forman, 1995; McGarigal andMarks, 1994) of the seven selected land-use types landscapeindices were determined for each period. The landscapeindices were calculated using FRAGSTATS, version 3.3(McGarigal and Marks, 1994). In addition to the indices available in FRAGSTATS the index number of shapecharacterising points (NSCP) was used as a measure of shape and boundary complexity (Moser et al., 2002). The calculation of this index was carried out with an ArcViewscript developed by Moser et al. (2002). C. Baessler, S. Klotz/Agriculture, Ecosystems and Environment xxx (2006) xxx–xxx 2AGEE 2731 1–8 585960616263646566676869707172737475767778798081828384858687888889899091919292939494959596888889909191929394949596979899100101102103104105106107108109110111112113114114115116117118119120121122123124125126127128129130131132133134135136137138139140141142143144145146147148149150151152153154155156157158159160161162163164165166167        U      N     C     O      R      R      E     C      T      E      D       P      R     O     O      F 2.4. Statistical analysis A pairwise Wilcoxon-test was used to test for differencesof average species numbers per releve´ among all periods.This test is optimal for the comparison of pairwiseobservations (Sachs, 1999). In contrast to the  t  -test, theWilcoxon-test is independent from the data allocation, and itis very efficient for a small as well as for a large number of samples.Since there was an unequal number of releve´s per period,the total species number for each period was calculated by aresampling procedure. According to the lowest number of releve´s for all three periods, 115 releve´s were randomlychosen 1000 times from all releve´s of the respective period.Therefore, there were 1000  115 species lists for eachperiod. The average of the total species numbers of theselists was used.To quantify weed species turnover, the number of: (1)common species, (2) species loss and (3) species gainbetween all periods was calculated. Data used for thisanalysis were available from the resampling procedure. The1000  115 species lists of one period were compared withthe corresponding species lists of the same resamplingprocedure of the other two periods irrespective of thenumber of common species, species loss and species gain.The average of the accordant number received for eachparameter and period was used.To calculate the average cover of each species over allreleve´s of each period the cover code was replaced by themean value of the respective cover class (Wilmanns, 1989).The differences of the average cover among periods wastested with a one-factorial variance analysis (ANOVA) andsubsequent multiple comparison Scheffe´-test. The signifi-cance was evaluated using the Bonferroni correction bydividing the significance level (  p  = 0.05) by the number of simultaneous tests (Legendre and Legendre, 1998). Onlyspecies with an average cover  0.02% in at least one periodwere included in the analysis ( n  = 130 species).The relationship between landscape indices and land-useintensity parameters and the total and average number of weed species was tested with Kendall’s tau rank correlation.Kendall’s tau represents a probability and will take valuesbetween   1 and +1, with a positive correlation indicatingthat the ranks of both variables increase together while anegativecorrelation indicates that as the rank of onevariableincreases the other one decreases. Kendall’s tau rank correlation was used instead of Spearman’s rank correlationbecause there is a direct interpretation of Kendall’s tau interms of probabilities of observing concordant anddiscordant pairs (Conover, 1980). 3. Results 3.1. Changes in land-use and landscape structure The number of farms in East Germany heavily decreasedbetween 1957 and 1960 from 825,124 to 20,317 andcontinued to decrease until 1979 (4816) with a concomitantincreaseinmean farm size(12–576–1231 ha).After thestartofprivatisationin1990, the numberoffarms increased again(29,807 in 2000) accompanied by a decrease of farm size to187 ha. The use of mineral fertilizers, i.e. phosphorous,potash and lime consistently increased from 1957 to 1979and decreased again thereafter. In contrast, nitrogenapplication increased continuously from 1957 to 2000(Table 1) with a pronounced increase between 1957 and1979.Changes in land-use were confined to an increase in thearea of meadows, dry grasslands and built-up areas and to adecrease in woodland. The proportion of agricultural areadid not significantly change (Table 1). However, significantstructural changes took place in arable fields, predominantlybetween 1957 and 1979 as shown in Fig. 1. There was adecreaseinthenumberofpatches,patchdensity,meanpatchfractal dimension, the number of shape characterising pointsand edge density, and an increase in mean patch size, and inthe size of the smallest and largest field (Table 1). Thisindicated a coarser landscape pattern, attributable to largerfields with a reduction of edges and linear elementsassociated with field delimitation. C. Baessler, S. Klotz/Agriculture, Ecosystems and Environment xxx (2006) xxx–xxx  3AGEE 2731 1–8 167168169170171172173174175176177178179180181182183184185186187188189190191191192193194195196197198199200201202203204205206207208209210211212213214215216217218219220221222223224225226227228229230231232233234235236237238239240241242243 Table 1Land-use intensity (amount of mineral fertilizers [kg ha  1 a  1 ]) used in thedistrict of Halle, East Germany, from 1957 to 2000 (Staatliche Zentralver-waltung fu¨r Statistik, 1960, 1980, 1987; Statistisches Landesamt Sachsen- Anhalt, 2000, 2001), proportion of land-use types and structural traits of thearable fields in the study area Friedeburg, Central Germany from 1953 to20001953/1957 1969/1979 2000Land-use intensity—fertilizer applicationNitrogen (N) 34.9 114.7 150Phosphorous (P 2 O 5 ) 28.5 67.3 21.5Potash (K  2 O) 71.1 83.9 29.3Lime (CaO) 114.8 156 105.8Proportion of land-use typesWoodland (%) 17.05 13.97 12.03Meadows (%) 3.72 6.04 5.92Dry grassland (%) 0.85 4.64 5.38Arable field (%) 63.44 58.31 61.42Built-up area (%) 8.21 8.57 10.83River Saale (%) 4.03 5.48 2.61Others (%) 2.71 2.98 1.81Landscape structure of arable fieldsNumber of fields 285 53 28Patch density (PD;  x  /100 ha) 51.67 8.91 5.04Mean size (MPS; ha) 1.23 6.54 12.19Smallest field (ha) 0.07 0.16 0.39Largest field (ha) 12.67 44.64 55Mean patch fractal dimension(MPFD)1.08 1.03 1.04Number of shape characterisingpoints (NSCP)1354 318 318Edge density (ED; m/ha) 320.08 87.26 90.52        U      N     C     O      R      R      E     C      T      E      D       P      R     O     O      F 3.2. Changes in weed species numbers and composition There was a highly significant decrease (  p < 0.001,Wilcoxon-test) of the average number of weed species perreleve´ from 20 species in 1957 to 14 species in 1979(decrease of 30%). Since 1979, there was no significantchange (15 species in 2000). There is also a highlysignificant difference between the average number in 1957and 2000 (  p < 0.001). The total number of weed species(calculated after resampling) increased from 128 species in1957 to 187 in 2000 (121 species in 1979).Although the weed flora changed among periods, all croptypes were dominated by the same few species:  Stellariamedia ,  Chenopodium album ,  Fallopia convolvulus ,  Polygo-num aviculare ,  Galium aparine ,  Amaranthus retroflexus  and Cirsium arvense . Weed cover decreased substantially duringthewholetime(averagevaluesperperiod:0.21–0.15–0.04%).Thespecieswiththehighestcoverdifferedamongperiods.In1957, S.media wasthemostdominantweedspecies(3.50%),followed by  C. album  (1.55%) and  P. aviculare  (1.38%). In1979, G.aparine reachedthehighestcover(4.34%),followedby C.album (2.26%)and S.media (1.76%).In2000,thelowesttotal cover was reached. The species with the highest coverreached only 0.70% ( C. album ) followed by  F. convolvulus (0.44%) and  P. aviculare  (0.42%). In 2000, there was also aclearincreaseinthe numberofspecieswith verylow averagecover.Three-quarterofthespecieshadanaveragecoverbelow0.05%. Most of these were either typical agricultural weedspecieslike  Hyoscyamusniger  , Knautiaarvensis or Sherardiaarvensis ,whichbecamereallyrareorspeciestypicalforotheradjacent habitats, like  Lepidium ruderale ,  Lysimachianummularia  or  Tanacetum vulgare .The cover of 23 species, out of the 130 tested, changedsignificantly over the period (Table 2). While the cover of 16 C. Baessler, S. Klotz/Agriculture, Ecosystems and Environment xxx (2006) xxx–xxx 4AGEE 2731 1–8 243244245246247248249250251252253254255256257258259259260261262263264265266267268269270271272273274275276 Fig. 1. Changes of landscape structure in the study area Friedeburg (Central Germany) from 1953 to 2000 illustrated by the patch boundaries.Table 2Weed species with significant changes in average cover between the periods 1957, 1979 and 2000 (after ANOVA and Scheffe´-test with Bonferroni correction)Plant species Average cover Scheffe´-test (  p )1957 1979 2000 1957–1979 1957–2000 1979–2000  Amaranthus retroflexus  0.01 0.87 1.90 n.s. n.s. n.s.  Arenaria serpyllifolia  0.49 0.00 0.00 n.s. n.s. n.s. Capsella bursa-pastoris  0.42 0.08 0.05  ** ** n.s. Consolida regalis  1.09 0.03 0.04  ** ** n.s.  Descurainia sophia  0.39 0.03 0.16  ** n.s. n.s. Euphorbia esula  0.02 0.00 0.00 n.s. n.s. n.s. Euphorbia exigua  0.47 0.03 0.19  ** n.s. n.s. Euphorbia peplus  0.19 0.07 0.02 n.s. n.s. n.s. Galium aparine  0.21 4.34 0.39  ** n.s.  **  Lamium amplexicaule  0.35 0.13 0.02 n.s.  ** n.s.  Lithospermum arvense  0.21 0.01 0.01  ** ** n.s.  Mentha arvensis  1.17 0.05 0.08  ** ** n.s. Papaver rhoeas  0.60 0.03 0.34  * n.s. n.s. Plantago intermedia  0.00 0.05 0.00 n.s. n.s. n.s. Senecio vulgaris  0.15 0.01 0.02  ** ** n.s. Silene noctiflora  0.33 0.21 0.02 n.s.  ** n.s. Sinapis arvensis  0.63 0.17 0.00 n.s.  ** n.s. Sonchus oleraceus  0.39 0.22 0.02 n.s.  ** n.s. Stellaria media  3.43 1.76 0.55 n.s.  ** n.s. Thlaspi arvense  0.25 0.02 0.01  ** ** n.s. Veronica agrestis  0.40 0.00 0.00  ** ** n.s. Veronica hederifolia  0.99 0.18 0.00  ** ** n.s. Veronica polita  0.00 0.18 0.35 n.s.  ** n.s.n.s., not significant at  p  0.00038; all ANOVAs were significant. *  p  0.00038. **  p  0.00007.        U      N     C     O      R      R      E     C      T      E      D       P      R     O     O      F species declined and of two species increased significantly,only five species showed fluctuating values from 1957 to2000. Typical weed species showing a highly significantdecrease were, e.g.  Consolida regalis ,  Lithospermumarvense ,  Mentha arvensis ,  Silene noctiflora ,  S. media  and Thlaspi arvense . In contrast,  A. retroflexus  and  Veronica polita  showed a significant increase in cover.Theweedspeciesturnoverwasmirroredinthechangesof weed species numbers (Table 3). There was nearly the samenumberofcommonspeciesamongallperiods. Nevertheless,the lowest number of common species (50) was found whencomparingtheweedspeciesof1957and2000.Manyspecieswere lost after 1957. However, there is a clear increase in thenumber of species gain from the first (28.4 species) to thesecond period (48.4 species). 3.3. Relating weed species richness to land-use and landscape structure The correlation between weed species numbers andlandscape indices as well as land-use parameters is shown inTable 4. There was no significant correlation between anylandscape index and total number of weed species. Sixlandscape indices were positively correlated to the averagenumber of weed species (Kendall’s tau: 1.00; percent of landscape, mean shape index, area-weighted mean shapeindex, mean patch fractal dimension, area-weighted meanpatch fractal dimension and sum of the number of shapecharacterising points). Furthermore, the land-use parameterlime was negatively correlated to the average number of weed species and phosphorous and potash were negativelycorrelated to the total number of weed species (Kendall’stau:   1.00). 4. Discussion The main results of the study were that: (1) the spatialheterogeneity of the landscape matrix of arable fieldsdeclined significantly through time, (2) the average weedspecies number per releve´ and the average weed speciescover decreased significantly; especially typical weedspecies (archaeophytes) decreased; whereas the totalnumber of weed species increased and (3) the mainfactors influencing species richness on the arable fields arethe complexity of the landscape matrix and thus patch sizein conjunction with the number of field boundaries, andland-use intensity, especially the application of mineralfertilizer. C. Baessler, S. Klotz/Agriculture, Ecosystems and Environment xxx (2006) xxx–xxx  5AGEE 2731 1–8 276277278279280281282283284285286287288289290291292293294295296297298298299300301302303304305306307308309310311312313314315316317318319320 Table 3Average number of common, gained and lost species between the sequent time periods with resampling (1000 permutations)Time period Average number of common species Average number of species gain Average number of species loss1957/1979 52.6 28.4 36.71979/2000 57.6 48.4 23.31957/2000 50.0 56.0 39.3Table 4Kendall’s tau rank correlations of landscape indices and land-use parameters vs. weed species numbers; data from 1957, 1979 and 2000Index/parameter Total species number Average species numberCA Total class area   0.33 0.33%LAND Percent of landscape 0.33 1.00NUMP Number of patches   0.33 0.33MPS Mean patch size 0.33   0.33PSCOV Patch size coefficient of variation   0.33 0.33PSSD Patch size standard deviation 0.33   0.33TE Total edge   0.33 0.33ED Edge density   0.33 0.33MPI Mean proximity index 0.33   0.33MSI Mean shape index 0.33 1.00AWMSI Area-weighted mean shape index 0.33 1.00MPFD Mean patch fractal dimension 0.33 1.00AWMPFD Area-weighted mean patch fractal dimension 0.33 1.00PD Patch density   0.33 0.33SUMNSCP (whole area) Sum of the number of shape characterising points 0.33 1.00NSCP (arable fields) Number of shape characterising points 0.00 0.82AWNSCP Area-weighted mean of NSCP 0.33   0.33Nitrogen 0.33   0.33Phosphorous   1.00   0.33Potash   1.00   0.33Lime   0.33   1.00
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