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International Journal of Biodiversity Science, Ecosystem Services & Management, 2013 Vol. 9, No. 2, 155–165, http://dx.doi.org/10.1080/21513732.2012.760488 a,b, a,c a U. Petersen *, N. Wrage-Mönnig and J. Isselstein a b Department of Crop Sciences, University of Göttingen, Von-Siebold-Str. 8, 37075 Göttingen, Germany; Thünen-Institute of Biodiversity, Bundesallee 50, 38116 Braunschweig, Germany; Department of Agricultural Sciences, Faculty of Life Sciences, Rhine-Waal University of Applied Sciences, Marie-Curie-Str. 1, D-47533 Kleve, Germany Herbicide application on permanent grassland to reduce weeds and improve forage quality is common agricultural practice. However, it still remains unclear how long it takes for the herbicide-disturbed swards to recover in terms of yield and forage quality. In a removal experiment in the Solling Uplands (Germany), the sward composition of permanent grassland had been manipulated by herbicides in order to obtain either relatively pure grass swards or swards with comparatively large amounts of forbs and legumes, in addition to untreated control swards. The short-term resilience of these sward types was examined under a gradient of management intensity regulated by both cutting regime and fertilizer supply. In the next growing season, the yield did not differ among any of the three sward types regardless of the management regime. All disturbed swards showed a complete recovery in terms of biomass. Yield was only inﬂuenced by functional sward characteristics across all disturbance treatments; the growth form of the dominant species determined the yield in fertilized plots. For the variation in forage quality (crude protein, water-soluble carbohydrates and ﬁbre content), the functional group identity of the remaining vegetation was important, but management had a much larger inﬂuence than vegetation. Keywords: herbicide; grassland; resilience; disturbance; yield; nutritive value; monocots; dicots 1. Introduction indeed dominating, why do farmers ‘improve’ their grass- lands by herbicide application? Herbicide application on grassland is a common agri- The impact of a disturbance like herbicide treatment on cultural management practice. It aims at a reduction of a grassland plant community mainly depends on the distur- less valuable forage species in the grass sward and con- bance’s duration and intensity and on the resistance and sequently achieving higher yields and improved fodder resilience of the original vegetation (Touzard and Clement values. These herbicide treatments are often combined with 2001; Renne and Tracy 2007). The original biodiversity over-sowing of desired species (Frame and Laidlaw 2011). and the traits (mainly in terms of re-colonization abilities) However, their establishment and effectiveness in improv- of the remaining species are important for the vegeta- ing the sward performance usually require 12 years given tion’s resilience (Virágh 1987; Lavorel 1999; Roxburgh that weather and management are optimal for the estab- and Wilson 2000; Symstad and Tilman 2001; McLaren lishment of grass seedlings (Opitz v. Boberfeld 1994). and Turkington 2010). In addition, the environmental con- On grassland, herbicides have usually been applied against ditions at the disturbed site play an important role for certain groups of species, e.g. broadleaved or annual dicots the speed and completeness of the recovery of different (Lewis and Hopkins 2000). Due to environmental con- vegetation characteristics like cover, biomass and compo- cerns, herbicide use has decreased since the 1990s (Lewis sition (Fowler 1981; Virágh 1989; Symstad and Tilman and Hopkins 2000), but remains common practice: in 2001; Touzard and Clement 2001; Renne and Tracy 2007; Britain, for example, up to 7% of grassland is treated Slocum and Mendelssohn 2008). annually (Frame and Laidlaw 2011). In diverse grassland, only a severe loss in species Reducing weeds means reducing biodiversity at least numbers is expected to completely disrupt the grassland in the short term (Virágh 1987), no matter whether ecosystems, as ecosystem processes seem to saturate at dicot weeds or monocot weeds are targeted. According small (around ﬁve) numbers of species (Roy 2001; Wrage to the results of biodiversity investigations, where pre- et al. 2011). Compared to ley farming systems, even inten- dominantly positive relationships between biodiversity and sively managed permanent grasslands host higher species many important ecosystem functions were found in ﬁeld numbers (Dykmans et al. 1999; Klimek et al. 2007; Pywell experiments (Quijas et al. 2010), this loss of biodiversity et al. 2007). Consequently, herbicide application as a man- could have negative consequences at least for parts of the agement method should not have detrimental effects on grassland ecosystem. However, most of these experiments agriculturally important ecosystem services such as pro- lack direct applicability to agricultural systems (Isselstein ductivity. 2005; Wrage et al. 2011). If the positive relationship is *Corresponding author. Email: Ute.Petersen@agr.uni-goettingen.de © 2013 Taylor & Francis 156 U. Petersen et al. Table 1. Experimental factors and treatment levels of the In contrast to productivity, forage quality should react GrassMan experiment. to changes in diversity more severely: it is supposed to improve if less palatable weeds are gone. Thus, besides Factor Level Acronym Time scope the main drivers of quality changes, maturity and nutrient Sward type 1.1 Untreated Co One herbicide status (Bruinenberg et al. 2002), forage quality is also inﬂu- control sward application enced by biodiversity and species composition (White et al. 1.2 Dicots reduced −Dic 2004). The presence of forbs and legumes can improve for- 1.3 Monocots −Mon age quality in terms of crude protein (CP) content as Seng reduced et al. (2008) and Seip et al. (2011) found when compar- Utilization 2.1 Cut once (July) 1 Continuous ing pure grass swards (made up either from pure Lolium management perenne or different grass species) with mixed permanent 2.2 Cut three times 3 grassland. Some dicot species contain higher amounts of (May, July, September) Mg and Na than grasses (Wilman and Riley 1993). In this article, we report ﬁrst results of the grassland Fertilization 3.1 No fertilization x management experiment (GrassMan), an experiment on 3.2 180/30/100 kg NPK −1 −1a N/P/Kha yr managed permanent grassland manipulated once by herbi- cides to vary species composition and functional diversity Notes: The acronyms of the different treatments are generated by the com- in the swards (Petersen et al. 2012). To analyse the recov- bination of the factor level abbreviations in the order sward-utilization- fertilization, e.g. –Dic1x = dicot-reduced sward, cut once, no fertilization. ery process under different environmental conditions, the The four combinations of utilization and fertilization are referred to as resulting swards were subjected to four different combina- management categories in the text. tions of fertilization and cutting regimes. Here, we exam- N fertilizer: calcium ammonium nitrate N27, P&K fertilizer: Thomaskali (8% P O , 15% K O, 20% CaO). ined the resilience of forage yield and quality focussing 2 5 2 on the short-term effects of the herbicide disturbance, that is, whether the manipulated swards recovered until the next growing season or whether yield and quality were changed. The GrassMan experiment was set up in the summer We hypothesized that: of 2008. It is a three-factor experiment incorporating the factors sward type, utilization and fertilization (Table 1). It has got six replicates resulting in 72 experimental plots, herbicide application and strong reduction of any each 15 m by 15 m large. To account for potential spatial functional group does not affect the yield in the heterogeneity due to the location on a shallow slope bor- following growing season; dering a forest on the upper part, the experimental layout the remaining vegetation’s ability to compensate the was a Latin rectangle design with the six replicates (blocks) losses depends on the traits of the remaining species arranged in 6 rows and 12 columns, two columns forming and the management and one block. any substantial change in the functional composi- Since we wanted to test disturbances in both directions, tion (distribution of functional groups and species i.e. to obtain dicot-reduced (–Dic) and monocot-reduced composition) affects forage quality. (–Mon) swards on top of the untreated control sward (Co), herbicides against dicots (active ingredients Fluoroxypyr + −1 Triclopyr and Mecoprop-P; 3 l ha each) and monocots 2. Methods −1 (Clethodim 0.5 l ha ) were applied each on a third of 2.1. Site and experimental design the experimental plots. The dead plant material was not The experimental site is located between Silberborn and removed, to mirror common practice in managed grass- Neuhaus, in the Solling Uplands, Germany (51 44 53 N, lands. The herbicide application followed 4 weeks after 9 32 42 E, 490 m a.s.l.) on long-term permanent the ﬁrst harvest of the whole area, at the end of July grassland managed by the experimental farm of the 2008. In spring 2009, three initially distinct sward types University of Goettingen at Relliehausen since 1966. The had developed on the experimental area. They differed ◦ 2 mean annual temperature is 6.9 C and mean annual rainfall in species numbers (7–16 per m ), species composition amounts to 1028 mm (Deutscher Wetterdienst, “German and functional group composition (Petersen et al. 2012). Meteorological Service” 1960–1991, station Silberborn- Starting with a grass:forb:legume ratio of 76:22:2 (June Holzminden, 440 m a.s.l.). The soil of the experimental 2008), a gradient ranging from 39:52:9 (–Mon) up to area was determined as a shallow (40–60 cm), stony haplic 93:7:0 (–Dic) was generated. The fertilized plots (acronym −1 Cambisol (Keuter et al. 2012) on middle Bunter (Triassic NPK) received 50 kg N ha in 2008 and the plots belong- sandstone) (Hedemann 1950). The grassland had been used ing to the three times cut regime were harvested a second as summer pasture for cattle and had received an annual time at the end of October that year. The complete man- −1 −1 −1 fertilizer amount of 80 kg N ha yr until two years prior agement with NPK fertilization (90 kg N ha at the to the start of the experiment. Its vegetation was classiﬁed end of April, the remaining N, P and K at the end of as a nutrient poor, moderately wet Lolio-Cynosuretum with May) and scheduled harvests did not start until spring high abundances of Festuca rubra and Agrostis capillaris. 2009. International Journal of Biodiversity Science, Ecosystem Services & Management 157 2.2. Measurements by Gesellschaft für Ernährungsphysiologie (‘Society for Nutrition Physiology’, 2008) incorporating crude ash, CP, Species composition and functional diversity were moni- crude fat and ADF contents among others. tored by means of vegetation relevés on permanent sub- plots where the dry matter (DM) yield proportions of each species were estimated according to Klapp and Stählin 2.3. Statistical analyses (1936). Two 9 m sub-plots per plot, each with an addi- tional 1 m quadrant in its centre for different scales of Univariate statistical analyses were conducted with R (ver- diversity measures, were recorded twice a year at the begin- sion 2.12.2) (R Development Core Team 2011). ANOVAS, ning of May before the ﬁrst and in mid-August 4 weeks linear contrasts and linear models (lm) were used to com- after the second harvest. The yield proportions of the pare the importance of treatment factors and functional species occurring in at least one-third of the plots with diversity inﬂuencing the measured parameters as well as proportions larger than 5% were included in the statisti- their means. For the comparison of means of all treatments, cal analyses as factor ‘species identity’ (ID). Additionally, Tukey’s ‘Honest Signiﬁcant Difference’ method (Miller the mass proportions of grasses, forbs and legumes and the 1981; Yandell 1997) was used with a conﬁdence level of amount of dead plant material were determined by the sort- 0.95. To take into account the environmental heterogeneity ing of sub-samples of each plot taken at harvest. Another and its inﬂuence on forage yield and quality, the rows and functional grouping comprised the three functional groups, blocks of the experimental area were added to the models grasses, forbs and legumes, comparable to the classiﬁca- ﬁrst of all factors. The best ﬁtting models including only tion used by Roscher et al. (2004) with further subdivisions row, block and the signiﬁcant independent predictive vari- into species with tall and with small stature. Besides ables and interactions were obtained by the comparison of growth height and stature, the criterion for this subdivi- the Akaike Information Criteria of the full and the reduced sion into six groups was also the sensitivity to defoliation. models (Zuur et al. 2009). The collinearity of continuous These criteria closely follow the classiﬁcation of grasses variables like forb and grass content, or individual species into understory grasses and tall meadow grasses accord- yield proportions, was checked beforehand in a special ing to Klapp (1954) and Klapp and Opitz von Boberfeld version of the pairs plot following Zuur et al. (2009). (2006). This classiﬁcation was adopted for legumes and If vegetation characteristics like species number, propor- forbs. Relative growth rates of single species according to tion of tall species, amounts of legumes and so on were Grime et al. (1988) were not included in this classiﬁca- included, the factor sward type was excluded from the mod- tion as almost all common species had the same growth els since it was strongly correlated with all the vegetation −1 −1 rate (1–1.4 g g week ). The only fast growing species, characteristics. To obtain homoscedasticity and normal dis- Urtica dioica and Holcus lanatus, were only present in tribution of the residuals, the data were ﬁtted in general small amounts on the experimental area. All traits needed least square (gls) models including the ‘varIdent’ variance for this classiﬁcation, as well as information on the main structure (different variance per factor level, ‘nlme’ pack- propagation type of the species (vegetative vs. by seeds), age Pinheiro et al. 2009) if necessary. Additionally, a part were acquired from Schrader and Kalthofen (1974), Grime of the data were transformed according to the results of the et al. (1988) and the database BiolFlor Version 1.1 (Klotz boxcox analysis (MASS package in R; Venables and Ripley et al. 2002). 2002) as indicated in the results. To analyse the inﬂuence The DM yield per hectare was projected from the aver- of management and vegetation characteristics on forage age yield of two 1.50 m × 15 m stripes per plot harvested quality as a whole, all NIRS-measured quality parameters with a Haldrup forage combine harvester (cutting height were included as dependent variables in an ordination (they 7 cm). For forage quality analyses, mixed herbage samples took the place of the ‘species’ in ordination of vegetation per harvested plot were taken and dried on the same day relevés), whereas management (fertilization and utilization at 60 C (for 48 hours) in a forced-air oven. The material frequency) and vegetation characteristics (sward type, pro- was then ground to pass through a 1-mm screen. We esti- portions of functional groups or tall and small grasses, mated CP, water-soluble carbohydrates (WSCs), neutral forbs and legumes and species ID) represented the indepen- detergent ﬁbre (NDF) and acid detergent ﬁbre (ADF) con- dent, ‘environmental’ variables. For statistics, vegetation tents by near-infrared reﬂectance spectroscopy (NIRS). characteristics of the three-cut regime were averaged ﬁrst The spectra were analysed using the large dataset of cal- over all harvest dates. Since the spatial distribution of sev- ibration samples from different kinds of grasslands by eral species depended on rows and blocks of the Latin rect- the Institute VDLUFA Qualitätssicherung NIRS GmbH, angle, these two spatial variables were excluded from direct Kassel, Germany (Tillmann 2010). As described in Kesting ordinations. The program Canoco for Windows version 4.5 et al. (2009), samples showing a lack of accuracy (H value (ter Braak and Šmilauer 1997–2004) was used for redun- exceeding 3) were excluded from further statistical anal- dancy analysis (RDA, constrained ordination) including yses (1 out of 144 samples). For the calculation of the Monte Carlo permutation tests for assessing importance energy content (metabolizable energy, ME) of the forages, and signiﬁcance of the environmental variables (ter Braak we determined the dry ash content by incinerating sam- and Šmilauer 2002). We used the variance partitioning ples of the ground material in a mufﬂe furnace (550 C) procedure (Borcard et al. 1992; Vandvik and Birks 2002) for 5 hours. ME was calculated according to the equation to quantify the proportions of variance in quality explained 158 U. Petersen et al. by management, vegetation characteristics or environmen- more space. In the –Dic swards, however, the seed propa- tal inﬂuences (date, percentage of open soil and position gating tuft grasses could not expand signiﬁcantly (data not within the Latin rectangle). The quality of the constrained shown) and still had the same yield proportion as in the ordination was judged by comparison of its ordination dia- control plots. grams with those from an unconstrained ordination (here The 12 experimental treatments resulted in widely −2 a principal component analysis, PCA) and the amount of spread annual yields ranging from an average of 550 g m −2 residual variance in the RDA. in the –Mon3x up to 1220 g m in the Co3NPK treatment. Within none of the four management categories, the yields differed signiﬁcantly among the three sward types. In the plots without fertilization cut three times, the –Mon-swards 3. Results tended to have the largest yields, but the yield increase 3.1. Yields due to fertilization was signiﬁcantly smaller than that in The yield proportions of single species as well as their the control swards (interaction fertilization × sward type frequency in the vegetation relevés were affected by the –Mon, P = 0.019). In the fertilized swards cut only once, herbicide application. Particularly the dicot species became the –Dic-swards tended to produce more forage than the less frequent (Table 2) in the –Dic swards; the grasses other sward types. The untreated control swards gained were mainly reduced in yield proportions, and their fre- most from the intensive treatment with fertilization and quency hardly changed. Several species showed seasonal three cuts. The management in terms of fertilization and ﬂuctuations. For example, Poa trivialis, Poa pratensis and utilization frequency was mainly responsible for yield dif- Cardamine pratensis decreased later in the year, while ferences in overall yields in 2009 (Table 3). However, the Dactylis glomerata and Taraxacum Sec. Ruderalia had inﬂuence of the experimental factors on single yields was higher yield proportions in August. The herbicides against not constant, as shown in Table 4. During the course of dicots did not completely eliminate all forbs, but were very the year 2009, fertilization gained importance, whereas the effective in removing legumes. The most common forbs sward type did not explain signiﬁcant amounts of yield were mainly reduced in yield proportion, not in frequency. variation apart from the very ﬁrst cut after herbicide appli- The same applied to the grasses. Red fescue (F. rubra)was cation in October 2008. We did not ﬁnd any signiﬁcant hardly affected by the herbicide against monocots; it even relationship between the proportions of grasses, forbs and slightly increased its frequency. The available space was legumes and yield within the four management categories colonized mainly by species belonging to the functional (Figure 1(a)–(c)). The variance explained by the lm did not group spared by the herbicides. In the –Mon swards, seed differ regardless of whether one of the functional groups or propagating as well as vegetatively spreading dicots gained the sward type was included. Table 2. Relative change of degree of presence of the 20 most frequent species in 9 m before (June 2008) and after (May, August 2009) the herbicide application within the three sward types. Relative change Overall degree of presence in 9 m (%) (± % of presence in June 2008) June 2008 May 2009 August 2009 All plots Co −Dic −Mon Co −Dic −Mon Poa pratensis ag. 98.6 0 −12.5 −8.3 −2.1 −6.2 −4.2 Lolium perenne 97.9 2.2 0 0 0 −4.2 −19.1 Festuca rubra 95.8 −2.1 0 2.1 −12.8 −10.9 −2.2 Dactylis glomerata 70.1 20.6 23.6 15.1 20.6 11.9 0 Poa annua 29.9 −84.5 −71.6 −93.7 −100 −92.8 −93.7 Deschampsia cespitosa 28.5 −6.0 22.9 −16.8 −12.3 0 8.4 Holcus mollis 27.1 −24.9 33.0 −14.4 −37.5 −11.2 0 Ranunculus repens 100 0 −2.1 0 0 0 0 Trifolium repens 100 0 −89.6 0 0 −68.7 0 Veronica chamaedrys 99.3 0 −2.1 −2.1 0 2.1 −2.1 Cerastium holosteoides 98.6 −4.2 −87.5 2.1 −55.3 −83.3 −19.1 Rumex acetosa 98.6 2.2 −2.1 0 4.4 0 0 Stellaria graminea 95.1 −4.2 −95.6 4.5 −34 −69.5 −13.6 Taraxacum Sec. Ruderalia 73.6 14.8 5.6 30.5 32.5 22.3 30.5 Achillea millefolium 66.7 13.3 −56.6 −2.8 10.1 −13.3 8.4 Cardamine pratensis 53.5 29.5 −34.7 41.6 −29.7 −65.3 −54.2 Cirsium arvense 34.0 −33.3 −64.7 0 −14.4 −23.4 9.2 Rumex obtusifolius 27.8 −33.2 −33.2 −6.0 −24.8 −8.4 −24.9 Note: Means over management categories. International Journal of Biodiversity Science, Ecosystem Services & Management 159 Table 3. Importance of the experimental factors in explaining the differences in annual yield 2009. 2 2 Factors df Sum Mean F value P (>F) Percent of variance explained Sward type 2 135.9 67.9 0.4546 0.637 0.28 Fertilization 1 27670.1 27670.1 185.1709 <0.001 58.5 Utilization 1 5859.4 5859.4 39.2114 <0.001 10.4 Fertilization × Utilization 1 4825.1 4825.1 32.2903 <0.001 8.6 Notes: ANOVA including spatial effects (row + block). Response variable square root transformed. Table 4. Proportion of variation in single and total yields 2008–2009 explained by the experimental factors (%). June 2008 Oct 2008 May 2009 July 2009 September 2009 Total 2009 July 1 cut July 3 cuts ∗∗∗ Sward type 1.7 26.6 7.2 1.1 0.4 0.2 1.7 2.1 ∗∗∗ ∗∗∗ Utilization 0.5 37.4 58.5 ∗∗∗ ∗∗∗ ∗∗∗ ∗∗∗ ∗∗∗ ∗∗∗ ∗∗∗ Fertilization 0 23.1 32.0 39.3 77.7 10.4 50.9 77.3 ∗∗∗ Use × Fert 1.0 8.6 Sw × Fert 2.7 Notes: June 2008 is the baseline yield without any experimental treatments. ANOVA based on gls estimation allowing for different variances per utilization (June 2008), per fertilization level (July 2009, July 1 cut) or per sward type (September 2009) or based on linear models with transformation of the response ∗∗∗ ∗ variable. Response variable raised to the power of 0.25 (October 2008, May 2009), or 0.5 (July 3 cuts, total 2009). P < 0.001, P < 0. However, using the ﬁner division into tall and small the –Mon-swards had signiﬁcantly lower energy contents grasses, forbs and legumes, we found signiﬁcant effects than those from the other two sward types (linear contrasts on yield in May 2009 (Figure 2), when we had recorded in gls model including one variance term per utilization both vegetation and yield data. A larger proportion of tall type, P = 0.005). This distinction was not visible in fer- grasses (Figure 2(a)) or tall species altogether (data not tilized plots (signiﬁcant interaction sward type –Mon × shown) increased yields signiﬁcantly in May 2009 – yet, fertilization, P = 0.014). only in the fertilized plots. The number of tall species or For four analysed forage quality parameters (CP, WSC, grasses was irrelevant. The higher the number of small NDF and ADF), we found signiﬁcant sward effects at dif- species present, the less forage was harvested on NPK- ferent harvest dates (Figure 3). However, these effects were plots. This trend was also visible in the yield × species ID not consistent across the fertilization levels; we found sig- correlation (data not shown). Achillea millefolium (classi- niﬁcant interactions between sward type and fertilization ﬁed as a tall forb) showed a tendency to increase total yield (Figure 3(a), (c), (d)). When comparing the forage qual- in fertilized plots, whereas A. capillaris (a small grass) ity of the ﬁrst growth cycles (i.e. forages cut in May and seemed to decrease total yield in fertilized plots when it the ones cut for the ﬁrst time in July), apart from a gen- was present in large amounts. However, the correlations eral loss of quality due to senescence of the sward, we were not signiﬁcant at the 5% level and none of the other detected a signiﬁcant time × sward interaction. From May frequent species showed any visible correlation with yield to July, the swards rich in forbs increased in ADF contents at all. The variability in yield at the experimental area signiﬁcantly more (P = 0.043) than the other swards. was best explained by a lm containing the amounts of tall The unconstrained ordination (PCA) of the quality grasses, small species, the factor fertilization and all inter- parameters showed the same main gradients determin- action terms (R = 0.529, P < 0.001). Still, fertilization ing forage quality as the constrained ordination (RDA) adj alone (excluding interactions with vegetation) accounted (Figure 4). The environmental variables selected for RDA for 21.3% of all variation in the yield. explained 81.7% of the total variation of the forage quality parameters in 2009. The cutting regime, or rather the age of the swards at harvest, explained most of the variation (57%, 3.2. Forage quality P < 0.010, Monte Carlo permutation test). The variation in The energy content of the forages at the ﬁrst and third sugar and protein contents made up the second gradient −1 harvests (May: 11.6 ± 0.2 MJ (kg DM) , September: of forage quality variation. It was mainly determined by −1 11.6 ± 0.2 MJ (kg DM) ) was not inﬂuenced by any of the fertilization regime, which explained 12% of the total the experimental factors. At the second harvest in July, variation (P < 0.010). After accounting for management the cutting regime (1-cut regime, 10.6 ± 0.2 MJ (kg inﬂuences, only forbs, the three species Rumex acetosa, −1 −1 DM) ; 3-cut regime, 11.1 ± 0.1 MJ (kg DM) )was Trifolium repens and A. millefolium, the amount of tall responsible for most of the variation in energy content forbs or the sward type –Mon (not included in the ordina- (ANOVA based on gls including one variance term per tion diagram in Figure 4) explained signiﬁcant (P < 0.050, level of the factor utilization, P < 0.001, data not shown). Monte Carlo permutation test) conditional proportions of However, in unfertilized plots, the forage samples from the remaining variance if added to the ordination model 160 U. Petersen et al. 1600 1600 (a) (b) 1200 1200 1000 1000 800 800 600 600 200 200 20 40 60 80 100 20 30 40 50 60 70 80 Grass (% of DM) Forbs (% of DM) (c) 1x 1400 1NPK 3x 3NPK 01 510 5 Legumes (% of DM) Figure 1. Relationships between total yield 2009 and proportions of grasses (a), forbs (b) and legumes (c) under the four management regimes (legend: middle right). None of the correlations between yield and independent variable within one management category were signiﬁcant. For abbreviations of experimental treatments please refer to Table 1. as separate groups. The remaining species and functional NPK regression y = 4.73 x + 206.05 groups shown in Figure 4 only accounted for signiﬁcant (a) No P = 0.034 NPK parts of the remaining variation (after extracting the inﬂu- R = 0.204 adj ences of management) if added as single extra independent variables. The variable dead material in forage samples was the only one that did not explain any extra variation, since it was highly correlated with cutting regime. The results of the variance partitioning emphasized the inﬂuence of management on forage quality. Just a small part (up to 0 510 15 20 8.6%) of variation in forage quality was solely due to sward Yield proportion tall grasses (%) characteristics. (b) No NPK 4. Discussion NPK regression y = –5.72 x + 695.66 4.1. Yields P = 0.001 R = 0.488 adj The main objective of this study was to investigate the effects of different herbicides on forage yield and quality in managed permanent grassland under different man- agement categories. We hardly found any inﬂuences of 60 70 80 90 disturbance by herbicides, of functional diversity or of Yield proportion small species (%) botanical composition on yield in this experiment: most of Figure 2. Yield May 2009 dependent on proportion of tall the yield variation was due to the management category, grasses (a) and proportion of small species (b) grouped by fer- supporting our ﬁrst hypothesis. tilization level (with regression lines). The corresponding linear The sward effect found in October 2008 was the only model includes a signiﬁcant interaction between nutrients and tall sign of the previous disturbance, since both treated swards grasses (P = 0.032) and nutrients and small species (P = 0.017), response variable untransformed. had lower yields than the control sward, indicating the –2 –2 Yield May 2009 (g m ) Yield May 2009 (g m ) –2 100 200 300 400 100 200 300 400 –2 Yield 2009 (g m ) Yield 2009 (g m ) International Journal of Biodiversity Science, Ecosystem Services & Management 161 May 2009 July 2009 September 2009 (a) (b) (c) (d) (e) (f) (g) (h) (i) (j) (k) (l) Co3NPK –Dic3NPK –Mon3NPK Co1NPK –Dic1NPK –Mon1NPK Co3NPK –Dic3NPK –Mon3NPK Co3x –Dic3x –Mon3x Co1x –Dic1x –Mon1x Co3x –Dic3x –Mon3x Figure 3. Box and whisker plots showing the four quartiles, the median (calculation of outliers by the default method in R) and the means, denoted by small squares, of selected forage quality characteristics in the six different sward type × fertilization level combinations at each of the three harvests. Second cut (July) of the three cut regime not presented. Asterisks denote signiﬁcant differences from the ∗∗∗ ∗∗ ∗ ∗ control sward of the same fertilization level ( P < 0.001, P < 0.01, P < 0.05, ( )P = 0.0506). Linear contrasts in linear models; either models with different variances per fertilization level (graphs (c), (k)) or sward type (graph (f)) or response variable either square root (graph (h)) or not transformed (all others). For abbreviations of experimental treatments please refer to Table 1. ongoing recovery process after the herbicide application. types analysed here. Only about 20% of total biomass (the By May 2009, however, in the following growing season, yield proportion of dicots before herbicide application) the treated swards had fully recovered in terms of biomass was removed in the –Dic plots. Due to the insensitiv- production: their yields did not differ from those of the ity of some grasses, the biomass removal in the –Mon control swards (Petersen et al. 2012). In other removal plots cannot be estimated from their pre-treatment propor- experiments (e.g. Symstad and Tilman 2001; McLaren and tions. In other removal experiments, the loss of biomass Turkington 2010; Šmilauer and Šmilauerová 2012), it took due to the disturbance was higher, e.g. 30–50% depend- a year or more for the remaining vegetation to reach the ing on the distribution of the functional groups (Symstad biomass production of the control plots after the removal and Tilman 2001; McLaren and Turkington 2010) or had taken place. around 50% (Virágh 1987; Šmilauer and Šmilauerová This may be due to the moderate removal of biomass 2012). Consequently, biomass production levels took and the intermediate species number in the different sward longer to recover, especially if the remaining vegetation ADF (% dry matter) NDF (% dry matter) WSC (% dry matter) CP (% dry matter) 25 30 35 40 45 50 55 60 65 70 4 6 8 10 12 10 15 20 25 162 U. Petersen et al. Of crucial importance for productivity are the traits of the remaining species after a disturbance. As reported in a review on observational studies (Jiang et al. 2009), the WSC abundance of the dominant species along with their special traits (here in all swards A. capillaris and F. rubra as low- to Legumes medium-yielding grasses) may inﬂuence yields more than TRI_REP DES_CES a shifted monocot:dicot ratio. We likewise did not ﬁnd any ACH_MIL 3 cuts inﬂuence of dicot or monocot proportions on yield, only Litter the presence of productive bunch grasses made a differ- ADF Grass ence to yields in the ﬁrst cut. This is consistent with the Dead Forbs ﬁndings of Mokany et al. (2008), who showed that it was RAN_REP NDF 1 cut LOL_PER not the ‘diversity’ (Tilman 1997) but rather the ‘mass ratio’ RUM_ACE (Grime 1998) hypothesis that better explained ecosystem Dependent variables process variation in natural communities. Thus, the more of the taller grasses were present in the plots, the higher Explaining variables CP yields we got in the ﬁrst cut, underlining the importance of Experimental factors special traits as hypothesized. NPK The effects of functional diversity on ecosystem functions also depend on management (e.g. Bernhardt- –1.0 1.0 RDA-axis 1, eigenvalue 0.658 Römermann et al. 2011). In line with this, we only found effects of special traits (growth characteristics) in fertil- Figure 4. Ordination diagram of a redundancy analysis (RDA) ized plots, i.e. dependent on agricultural management as with forage quality characteristics (contents of CP, WSC, ADF, we had anticipated in our second hypothesis. Silletti et al. NDF in 2009, untransformed) as dependent variables and the (2004) likewise found different growth responses of one of experimental factors utilization and fertilization (cf. Table 1) and vegetation characteristics (instead of sward types) as explaining the remaining species after neighbour removal to depend variables. Quality characteristics of the three-cut variant are aver- on the nutrient status of the soil. In our experiment, the aged across harvest dates. Explaining variables with a correlation faster-growing tall grasses gained more biomass from the coefﬁcient with the ﬁrst and second ordination axis <–0.2 and fertilization than the smaller species. >0.2 are included. Not only productivity related traits, but also dispersal Notes: Abbreviation of species names: ACH_MIL, Achillea millefolium; DES_CES, Deschampsia cespitosa;LOL_PER, abilities are of importance. Since the tall tuft grasses exhib- Lolium perenne; RAN_REP, Ranunculus repens;RUM_ACE, ited poor re-colonization abilities, they could not increase Rumex acetosa;TRI_REP, Trifolium repens. Explaining vari- their yield proportions in the –Dic plots; so their inﬂuence ables: Grass/Forbs/Legumes, yield proportions in %; litter, % of on total yield did not lead to any differences between con- soil covered by dead plant material; dead, proportion of dead plant trol and –Dic-swards. In the disturbed plots, the traits of the material found in sorted samples in %. fastest-colonizing (A. capillaris, Ranunculus repens and R. acetosa) or most resistant (F. rubra in the –Mon swards) had recruitment limitations as encountered by Symstad species dominated. Since these are not the highest yielding and Tilman (2001); Roxburgh and Wilson (2000) found a species, the treated plots did not have higher yields than the control. recovery rate comparable to ours, when they removed all graminoids (approximately 50–60% of total biomass) by herbicide in a dicot-dominated lawn. Six weeks after the 4.2. Forage quality removal, the cover values they recorded in their herbicide treatment were similar to those of the control plots. In line with the results for yield, the inﬂuence of sward After the disturbance by herbicides in our experiment, characteristics on special forage quality characteristics sufﬁcient species remained to compensate for the losses, no depended on management regime. We only found sig- matter which groups of species were missing. As Schwartz niﬁcantly reduced energy contents in unfertilized –Mon et al. (2000) and Waide et al. (1999) pointed out, most of swards cut once in July. Fertilization did not increase the ecosystem processes are saturating at low species num- energy contents. Since the energy content of forages bers; Roy (2001) summarized that, in many studies, ﬁve depends on all cell contents (protein, carbohydrates and plant species were enough to reach 90% of the productiv- fats) and the ﬁbre content determining their digestibility ity effect. Since the remaining vegetation in our experiment (Voigtländer and Jacob 1987), the equal energy contents in consisted of at least seven species per m , the ecosystem fertilized versus unfertilized swards can be explained by functions, in this case the yield, should not have shown a their contrasting contents of CP and WSC in May and July lower rate of functioning. In accordance with this, we did (Figure 3(a), (b), (d), (e)). Low CP contents in unfertilized not ﬁnd any effects, or the existing effects were too small swards were compensated for by higher WSC proportions compared to the variability in our treatments as is often and vice versa. In September, CP and WSC did not differ the case in experiments with no controlled environments among the fertilization regimes, leading to equal energy (Balvanera et al. 2006). contents again. RDA-axis 2, eigenvalue 0.112 –1.0 1.0 International Journal of Biodiversity Science, Ecosystem Services & Management 163 The senescence of the swards combined with higher probably have found higher yields in treated versus con- amounts of structural tissue (= higher amounts of dead trol plots – at least under high nutrient levels. Even a small plant material, see Figure 4) reduced forage quality in proportion of high yielding grasses was able to increase terms of digestibility (Duru et al. 2008) in the swards of the yields in fertilized plots in the ﬁrst cut. Forage quality 1-cut regime. The –Mon-swards contained less energy due was strongly inﬂuenced by phenological development of to increased levels of ADF and decreased levels of WSC the sward, which hardly differed among our three sward (Figure 3). This is consistent with Lopez et al. (1991), types since they all belonged to the same plant community Bruinenberg et al. (2004) and Andueza et al. (2010) who and had the same set of early and late ﬂowering species, also reported increased ADF values in forbs compared with albeit in different proportions. Only at single harvest dates, grasses due to higher lignin contents. the inﬂuences of forbs and grasses on quality character- For the summer re-growth, Bruinenberg et al. (2002) istics were visible, although, most of the time, relatively reported higher digestibility in forb species than in grass small compared with fertilization effects. In the short term, species. This is comparable with our results. The –Dic- the herbicide application did not lead to changes in yields swards had higher NDF and ADF contents than the –Mon- contrary to the results of biodiversity experiments sug- swards in the second (data not shown) and the third cuts gesting higher yields in swards hosting higher species (Figure 3(i), (l)), whereas the CP contents were highest in diversity. However, it signiﬁcantly affected forage quality. the –Mon-swards. High CP contents in forbs were sim- So, depending on the subsequent utilization of the forage, ilarly found by Wilman and Riley (1993); Bruinenberg application of herbicides against either monocots or dicots et al. (2004) and Andueza et al. (2010). These study results might be useful to adapt forage quality. clearly support our third hypothesis. However, there may be other crucial factors inﬂu- encing forage quality far more than sward composition Acknowledgements does. Especially the cutting date along with the pheno- This work was supported by the Ministry of Science and Culture logical development of the swards can be responsible for of Lower Saxony and the ‘Niedersächsisches Vorab’ and is part the largest changes in quality (van Soest et al. 1978; of the Cluster of Excellence ‘Functional Biodiversity Research’. We would like to thank Uwe von Borstel and Bernd Gehlken, Bruinenberg et al. 2002; Cop et al. 2009; Bochi-Brum et al. who recorded the vegetation relevés in 2009, and Peter Tillmann 2011). This is due to a declining leaf:stem ratio when the (VDLUFA), who was responsible for the analysis of the NIRS grasses start their generative growth (Duru et al. 2008). spectra. Further, the accumulated biomass needs to be supported by structural tissues. Contents of soluble carbohydrates, mainly found in the leaf tissue, are in decline, reducing References digestibility. This is also mirrored in our data. The forage Andueza D, Cruz P, Farruggia A, Baumont R, Picard F, Michalet- of the late ﬁrst cut in July had the highest NDF and ADF Doreau B. 2010. Nutritive value of two meadows and rela- contents (Figure 3(h), (k)). The high ADF contents in the tionships with some vegetation traits. Grass Forage Sci. –Mon1x swards could be due to higher proportions of fruit- 65(3):325–334. ing Rumex acetosa, R. repens and red fescue. The other Balvanera P, Pﬁsterer AB, Buchmann N, He J-S, Nakashizuka T, sward types hosted larger amounts of A. capillaris still in Raffaelli D, Schmid B. 2006. Quantifying the evidence for biodiversity effects on ecosystem functioning and services. bloom. Ecol Lett. 9(10):1146–1156. In the redundancy analysis, most variation in forage Bernhardt-Römermann M, Römermann C, Sperlich S, Schmidt quality of the whole year 2009 was explained by manage- W. 2011. Explaining grassland biomass – the contribution of ment, that is to say, fertilization and cutting regime. As also climate, species and functional diversity depends on fertiliza- reported by Cop et al. (2009), who analysed the quality of tion and mowing frequency. J Appl Ecol. 48(5):1365–2664. Bochi-Brum O, Garcia R, Bodas R, Calleja A, Andres S, Lopez S. forages by means of ordination as well, the main gradient in 2011. Nutritive value of herbage from mountain hay meadow our redundancy analysis was the contrast in ﬁbre contents managed under traditional and intensive harvest systems as induced by different cutting dates. The CP content as the affected by nitrogen fertilisation and time of cutting. Anim second largest gradient showed a much smaller variability. Prod Sci. 51(6):549–556. Just in the third ordination axis, the sward characteristics Borcard D, Legendre P, Drapeau P. 1992. Partialling out the spatial component of ecological variation. Ecology. 73(3): were the determining factors but they hardly explained any 1045–1055. (eigenvalue: 0.046) of the remaining variation in forage Bruinenberg MH, Valk H, Korevaar H, Struik PC. 2002. Factors quality. affecting digestibility of temperate forages from seminatural To sum up, the swards showed a high resilience towards grasslands: a review. Grass Forage Sci. 57(3):292–301. a herbicide treatment in terms of yield; they had recov- Bruinenberg MH, Van Gelder AH, Gonzalez Perez P, Hindle VA, Cone JW. 2004. Estimating rumen degradability of forages ered until the following growing season. Yield was mainly from semi-natural grasslands, using nylon bag and gas pro- inﬂuenced by fertilization and cutting regime; the distur- duction techniques. NJAS-Wagen J Life Sci. 51(4):351–368. bance was not visible any more. The propagation traits Cop J, Lavrenci ˇ cˇ A, Košmelj K. 2009. Morphological develop- of the remaining species were important as those species ment and nutritive value of herbage in ﬁve temperate grass able to spread more quickly and became dominant. If these species during primary growth: analysis of time dynamics. fast colonizers had been high yielding species, we would Grass Forage Sci. 64(2):122–131. 164 U. Petersen et al. Duru M, Cruz PP, Raouda AHK, Ducourtieux C, Theau JP. 2008. Lopez S, Carro MD, Gonzalez JS, Ovejero FJ. 1991. Rumen Relevance of plant functional types based on leaf dry mat- degradation of the main forage species harvested from per- ter content for assessing digestibility of native grass species manent mountain meadows in North-western Spain. J Agr and species-rich grassland communities in spring. Agron J. Sci. 117(03):363–369. 100(6):1622–1630. McLaren JR, Turkington R. 2010. Ecosystem properties deter- Dykmans A, Mack H, Weissbach F. 1999. The effect of grassland mined by plant functional group identity. J Ecol. 98(2): extensiﬁcation on yield, forage quality and botanical com- 459–469. position at different grassland locations. Landbauforschung Miller RG. 1981. Simultaneous statistical inference. New York Völkenrode. Mitteilungen der Bundesforschunganstalt für (NY): Springer. Landwirtschaft. [Farming research Völkenrode. Announce- Mokany K, Ash J, Roxburgh S. 2008. Functional identity is more ments of the Federal Agricultural Research Center (FAL)]. important than diversity in inﬂuencing ecosystem processes 206:125–139. in a temperate native grassland. J Ecol. 96(5):884–893. Fowler N. 1981. Competition and coexistence in a North Carolina Opitz von Boberfeld W. 1994. Grünlandlehre [Grassland grassland: II. The effects of the experimental removal of science]. Stuttgart (Germany): Ulmer. species. J Ecol. 69(3):843–854. Petersen U, Wrage N, Köhler L, Leuschner C, Isselstein J. 2012. Frame J, Laidlaw AS. 2011. Improved grassland management. Manipulating the species composition of permanent grass- New ed. Ramsbury (UK): Crowood. lands – a new approach to biodiversity experiments. Basic Gesellschaft für Ernährungsphysiologie. 2008. Neue Appl Ecol. 13(1):1–9. Gleichungen zur Schätzung der umsetzbaren Energie Pinheiro J, Bates D, DebRoy S, Sarkar D, The R Core Team. 2009. für Wiederkäuer von Gras- und Maisprodukten [New equa- NLME: linear and nonlinear mixed effects models. R package tions for estimation of metabolisable energy for ruminants version 3. 1–96. from grass and maize products]. Proc Soc Nutr Physiol. 17: Pywell RF, Bullock JM, Tallowin JB, Walker KJ, Warman EA, 191–198. Masters G. 2007. Enhancing diversity of species-poor grass- Grime JP. 1998. Beneﬁts of plant diversity to ecosystems: imme- lands: an experimental assessment of multiple constraints. diate, ﬁlter and founder effects. J Ecol. 86(6):902–910. J Appl Ecol. 44(1):81–94. Grime JP, Hodgson JG, Hunt R. 1988. Comparative plant ecol- Quijas S, Schmid B, Balvanera P. 2010. Plant diversity enhances ogy: a functional approach to common British species. provision of ecosystem services: a new synthesis. Basic Appl London (UK): Unwin Hyman. Ecol. 11(7):582–593. Hedemann H-A. 1950. Entwicklung und Struktur des R Development Core Team. 2011. R: a language and environment Sollinggewölbes [Development and structure of the Solling for statistical computing. Vienna (Austria): R Foundation for Uplands] [dissertation]. Clausthal-Zellerfeld (Germany): Statistical Computing. Bergakademie Clausthal. Renne I, Tracy B. 2007. Disturbance persistence in managed Isselstein J. 2005. Enhancing grassland biodiversity and its grasslands: shifts in aboveground community structure and consequences for grassland management and utilisation. the weed seed bank. Plant Ecol. 190(1):71–80. In: McGilloway, DA, editor. Grassland: a global resource. Roscher C, Schumacher J, Baade J, Wilcke W, Gleixner G, Wageningen (The Netherlands): Wageningen Academic Weisser WW, Schmid B, Schulze ED. 2004. The role of Press. p. 305–320. biodiversity for element cycling and trophic interactions: an Jiang L, Wan SQ, Li LH. 2009. Species diversity and produc- experimental approach in a grassland community. Basic Appl tivity: why do results of diversity-manipulation experiments Ecol. 5(2):107–121. differ from natural patterns? J Ecol. 97(4):603–608. Roxburgh SH, Wilson JB. 2000. Stability and coexistence in a Kesting S, Wrage N, Isselstein J. 2009. Herbage mass and nutri- lawn community: experimental assessment of the stability of tive value of herbage of extensively managed temperate the actual community. Oikos. 88(2):409–423. grasslands along a gradient of shrub encroachment. Grass Roy J. 2001. How does biodiversity control primary productiv- Forage Sci. 64(3):246–254. ity? In: Saugier B, Mooney HA, editors. Terrestrial global Keuter A, Hoeft I, Veldkamp E, Corre MD. 2012. Nitrogen productivity. San Diego (CA): Academic Press. response efﬁciency of a managed and phytodiverse temper- Schrader A, Kalthofen H. 1974. Gräser.: Biologie— ate grassland. Plant Soil. [Internet]. [cited 2012 Dec 11]; Bestimmung—Wirtschaftliche Bedeutung. Berlin 14. Available from: http://dx.doi.org/10.1007/s11104-012- (Germany): VEB Deutscher Landwirtschaftsverlag. 1344-y Schwartz MW, Brigham CA, Hoeksema JD, Lyons KG, Klapp E. 1954. Wiesen und Weiden. Behandlung, Verbesserung Mills MH, van Mantgem PJ. 2000. Linking biodiversity to und Nutzung von Grünlandﬂächen. Berlin (Germany): Paul ecosystem function: implications for conservation ecology. Parey. Oecologia. 122(3):297–305. Klapp E, Opitz von Boberfeld W. 2006. Taschenbuch der Gräser. Seip K, Breves G, Isselstein J, Abel H. 2011. Nitrogen excretion 13th ed. Stuttgart (Germany): Ulmer. of adult sheep fed silages made of a mixed sward or of pure Klapp E, Stählin A. 1936. Standorte, Pﬂanzengesellschaften und unfertilised grass alone and in combination with barley. Arch Leistung des Grünlandes. Stuttgart (Germany): Ulmer. Anim Nutr. 65(4):278–289. Klimek S, Richter gen. Kemmermann A, Hofmann M, Isselstein Seng M, Bonorden S, Nissen J, Isselstein J, Abel H. J. 2007. Plant species richness and composition in managed 2008. Fermentation patterns and nutrient contents of forb- grasslands: the relative importance of ﬁeld management and containing silages and their effects on microbial fermenta- environmental factors. Biol Conserv. 134(4):559–570. tion in the artiﬁcial rumen system RUSITEC. J Agri Sci. Klotz S, Kühn I, Durka W. 2002. BIOLFLOR – Eine Datenbank 146(3):333–341. zu biologisch-ökologischen Merkmalen der Gefäßpﬂanzen Silletti AM, Knapp AK, Blair JM. 2004. Competition and in Deutschland. Schriftenreihe für Vegetationskunde. 38: coexistence in grassland codominants: responses to neigh- 41–281. bour removal and resource availability. Can J Bot. 82(4): Lavorel S. 1999. Ecological diversity and resilience of 450–460. Mediterranean vegetation to disturbance. Divers Distrib. Slocum MG, Mendelssohn IA. 2008. Use of experimental dis- 5(1–2):3–13. turbances to assess resilience along a known stress gradient. Lewis GC, Hopkins A. 2000. Weeds, pests and diseases of Ecol Indic. 8(3):181–190. grassland. In: Hopkins A, editor. Grass its production & Šmilauer P, Šmilauerová M. 2012. Asymmetric relationship utilization. 3rd ed. London (UK): Blackwell Science Ltd. between grasses and forbs: results from a ﬁeld experiment International Journal of Biodiversity Science, Ecosystem Services & Management 165 under nutrient limitation. Grass Forage Sci. [Internet]. Venables WN, Ripley BD. 2002. Modern applied statistics with [cited 2012 Jul 3]; 13. Available from: http://dx.doi.org/ S. 4th ed. New York (NY): Springer. 10.1111/j.1365-2494.2012.00888.x Virágh K. 1987. The effect of herbicides on vegetation dynamics: Symstad AJ, Tilman D. 2001. Diversity loss, recruitment lim- a ﬁve year study of temporal variation of species composition itation, and ecosystem functioning: lessons learned from a in permanent grassland plots. Folia Geobot. 22(4):385–403. removal experiment. Oikos. 92(3):424–435. Virágh K. 1989. An experimental approach to the study of com- ter Braak CJF, Šmilauer P. 1997–2004. Canoco for win- munity stability – resilience and resistance. Acta Botanica dows 4.53. Wageningen (The Netherlands): Plant Research Hungarica. 35(1–4):99–125. International. Voigtländer G, Jacob H. 1987. Grünlandwirtschaft und Futterbau. ter Braak CJF, Šmilauer P. 2002. Canoco reference manual Stuttgart (Germany): Ulmer. and CanoDraw for Windows User’s guide: software for Waide RB, Willig MR, Steiner CF, Mittelbach G, Gough L, canonical community ordination (version 4.5). Ithaca (NY): Dodson SI, Juday GP, Parmenter R. 1999. The relationship Microcomputer Power. between productivity and species richness. Annu Rev Ecol Tillmann P. 2010. Anwendung der Nahinfrarotspektroskopie Syst. 30:257–300. (NIRS) an Grünlandproben [Usage of near-infrared White TA, Barker DJ, Moore KJ. 2004. Vegetation diversity, reﬂectance spectroscopy for grassland samples]. VDLUFA- growth, quality and decomposition in managed grasslands. Schriftenreihe. 66:145–150. Agric Ecosyst Environ. 101(1):73–84. Tilman D. 1997. Distinguishing between the effects of species Wilman D, Riley JA. 1993. Potential nutritive value of a wide diversity and species composition. Oikos. 80(1):185. range of grassland species. J Agri Sci. 120(1):43–50. Touzard B, Clement B. 2001. Plant diversity dynamics in an Wrage N, Strodthoff J, Cuchillo MH, Isselstein J, Kayser M. eutrophic alluvial reed bed after experimental small-scale 2011. Phytodiversity of temperate permanent grasslands: disturbances. Bot Helv. 111(1):45–58. ecosystem services for agriculture and livestock manage- van Soest PJ, Mertens DR, Deinum B. 1978. Preharvest fac- ment for diversity conservation. Biodivers Conserv. 20(14): tors inﬂuencing quality of preserved forage. J Anim Sci. 3317–3339. 47(3):712–720. Yandell BS. 1997. Practical data analysis for designed experi- Vandvik V, Birks H. 2002. Partitioning ﬂoristic variance in ments. Boca Raton (FL): Chapman & Hall/CRC. Norwegian upland grasslands into within-site and between- Zuur AF, Ieno EN, Walker N, Saveliev AA, Smith GM. 2009. site components: are the patterns determined by environment Mixed effects models and extensions in ecology in R. New or by land-use? Plant Ecol. 162(2):233–245. York (NY): Springer.
International Journal of Biodiversity Science, Ecosystem Services & Management – Taylor & Francis
Published: Jun 1, 2013
Keywords: herbicide; grassland; resilience; disturbance; yield; nutritive value; monocots; dicots
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