Response of primary production and biomass allocation to nitrogen and water supplementation along a grazing intensity gradient in semiarid grassland

Europ. J. Agronomy 63 (2015) 27–35

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Response of primary production and biomass allocation to nitrogen and water supplementation along a grazing intensity gradient in semiarid grassland Xiao Ying Gong a,b,1 , Nicole Fanselow c , Klaus Dittert c,2 , Friedhelm Taube b , Shan Lin a,∗ a

Department of Plant Nutrition, China Agricultural University, 100193 Beijing, PR China Institute of Crop Science and Plant Breeding – Grass and Forage Science/Organic Agriculture, Christian-Albrechts-University, Hermann-Rodewald-Str. 2, 24118 Kiel, Germany c Institute of Plant Nutrition and Soil Science, Christian-Albrechts-University, Hermann-Rodewald-Str. 2, 24118 Kiel, Germany b

a r t i c l e

i n f o

Article history: Received 26 May 2014 Received in revised form 5 November 2014 Accepted 16 November 2014 Keywords: Precipitation N fertilizer Compensatory growth Morphological traits Sheep grazing Inner Mongolian steppe

a b s t r a c t Herbivory and resource availability interactively regulate plant growth, biomass allocation, and production. However, the compensatory growth of plants under grazing intensities and manipulated environmental conditions is not well understood. A 2-year experiment with water (unirrigated and irrigated) and nitrogen fertilizer (0 and 75 kg N ha−1 year−1 ) addition was conducted at sites with 4 grazing intensities (0–7 sheep ha−1 ) in an annually rotational grazing system in Inner Mongolia. In this study, grazing had no significant effect on aboveground net primary production (ANPP) and net primary production (NPP). However, high grazing intensity strongly reduced the fraction of belowground net primary production to NPP. Water and nitrogen additions significantly increased ANPP by 39% and by 23%, respectively, but had no effect on belowground net primary production. ANPP showed lower response to nitrogen addition at high grazing intensity sites than at low grazing intensity sites. We found no evidence for grazing optimization on primary production of semiarid steppe, regardless of resource supplementations. Grazed plants minimized the reduction of ANPP by altering allocation priority and morphological traits. Our study highlights the “whole-plant” perspective when studying plant–herbivore interactions. © 2014 Published by Elsevier B.V.

1. Introduction The responses of primary production of natural grassland to herbivory have been investigated in numerous studies concerning plant–animal interactions. Compensatory growth, which is termed as a positive response to injury, leads to three consequences (Belsky, 1986): overcompensation (increase of primary production by grazing), exact compensation (no change of production by grazing), and under compensation (decrease of production by grazing). Overcompensation has been demonstrated in some studies (McNaughton, 1979; Oesterheld and McNaughton, 1988; Turner

∗ Corresponding author at: Department of Plant Nutrition, China Agricultural University, Yuanmingyuan West Road, 2, 100193 Beijing, PR China. Tel.: +86 10 62733636; fax: +86 10 62731016. E-mail address: [email protected] (S. Lin). 1 Present address: Lehrstuhl für Grünlandlehre, Technische Universität München, 85354 Freising, Germany. 2 Present address: Institute of Plant Nutrition and Crop Physiology, Georg-AugustUniversity of Goettingen, Germany. http://dx.doi.org/10.1016/j.eja.2014.11.004 1161-0301/© 2014 Published by Elsevier B.V.

et al., 1993), and the mechanisms underlying was phrased as grazing optimization hypothesis (Hilbert et al., 1981; McNaughton, 1979). However, many studies have found no evidence for overcompensation (Biondini et al., 1998; Ferraro and Oesterheld, 2002; Georgiadis et al., 1989; Milchunas and Lauenroth, 1993), and the validity and biological justification on grazing optimization theory has been questioned (Belsky, 1986; Belsky et al., 1993). Although the debate exists, grazing optimization theory has been used to justify heavy livestock grazing in western North American rangelands, and some authors recommended caution in application of this theory, especially in ecosystem with high risk of overgrazing (Briske, 1993; Painter and Belsky, 1993). Other plant–herbivore theories, including compensatory continuum model (Maschinski and Whitham, 1989) and limiting resource model (Wise and Abrahamson, 2005), claim that compensatory growth was regulated by resource availability. This claim, has been supported by many experimental studies, shows that plant regrowth after defoliation was regulated by water and nitrogen availability (Ferraro and Oesterheld, 2002; Georgiadis et al., 1989; McNaughton et al., 1983; Schiborra et al., 2009). Therefore,

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it is suggested that the grazing optimization occurs occasionally in some species and systems, given the appropriate combination of environmental factors (Briske, 1993). Compensatory growth is an intensively studied topic; however, most studies on grazing optimization have only focused on aboveground net production (ANPP), and the “whole-plant” level response is less known. Belowground net production (BNPP) is an important component of net primary production (NPP), which is about 40–90% of NPP in grassland (Hui and Jackson, 2006). Plants are able to reprioritize carbon allocation in response to imbalance of sources and sinks (Briske et al., 1996). Thus, an enhancement in ANPP, in many cases, should be attributed to the shift in C allocation rather than the overcompensation of the whole plant. 13 C labeling experiments indicate that C allocation to shoot growth is promoted by defoliation (Briske et al., 1996) or by N fertilizer addition (Gong et al., 2014). Therefore, to test grazing optimization theory, both ANPP and BNPP need to be studied under well controlled conditions of resource availability. Moreover, plants have considerable morphological plasticity in response to biotic and abiotic influences as reviewed by Poorter et al. (2012). Thus, evaluation of plant traits brings more insight to the underlying mechanism of plant–herbivore interactions. This study aims at a clear understanding of plant compensatory growth under sheep grazing with manipulated resources availability in the semiarid steppe. As a typical semiarid steppe of North China, Xinlingole grassland has been subjected to advanced degradation (Tong et al., 2004), attributed to the rapid rise in numbers of livestock and overgrazing (Wang and Ripley, 1997). In this grassland, water limitation on herbage production is well known (Bai et al., 2004, 2008), and nitrogen and water interactively constrain primary production (Burke et al., 1997; Chen et al., 2011; Gong et al., 2011a,b; Hooper and Johnson, 1999; Vitousek et al., 1992). We have performed a grazing experiment with four grazing intensities as main plots and water and nitrogen fertilizer additions in the subplots in this semiarid steppe. We hypothesized that (1) grazing has a negative or neutral effect on NPP; (2) overcompensation of ANPP (grazed ANPP > ungrazed ANPP) happens at the expense of BNPP; (3) N effect on ANPP is more significant at sites with lower grazing intensity.

2. Materials and methods 2.1. Study area The Xilin River Basin (latitude 43◦ 26 –44◦ 29 N, longitude 115◦ 32 –117◦ 12 E, and mean elevation 1200 m ASL) is located in the center of the Inner Mongolia grassland. The region has a semiarid continental climate with a short growing period from May to September (Chen, 1988). In the Xilin River Basin, during 1982–2008, average annual air temperature was 0.7 ◦ C and average annual rainfall was 335 mm of which more than 80% occurred from May to September. The precipitation and air temperature during experimental period are shown in Fig. 1. The dominant soil types are Calcic Chernozems derived from aeolian sediments above volcanic rock (Steffens et al., 2008), which is the only soil type found in our experimental sites. Total carbon and nitrogen contents of the top soil (0–30 cm) prior to the start of the study were 1.2% and 0.1%, respectively. Plant available nutrients of the top soil prior to the start of the study were plant available N content (CaCl2 extraction), 6.4 mg kg−1 ; plant available P content (NaHCO3 extraction), 2 mg kg−1 ; and plant available K content (NH4 OAc extraction), 152 mg kg−1 . Soil pH at 0–30 cm depth was 6.6. Detailed soil physical and chemical characteristics of this grassland were sampled at a adjacent site and were published elsewhere (moderate grazing site, Gong et al., 2011a). Dominant species were Leymus chinensis (Trin.)

Fig. 1. Accumulated precipitation (black bars) and irrigation (grey bars) of each 10 days, and air temperature in growing season 2007 (a) and 2008 (b). The total precipitation from May to September was 178 mm in 2007 and 277 mm in 2008. The total amount of irrigation water was 185 mm in 2007 and 120 mm in 2008.

Tzvel., a perennial C3 rhizomatous grass; and Stipa grandis (P.) Smirn., Agropyron cristatum (L.) Gaertn., perennial C3 bunchgrasses; Cleistogenes squarrosa, a perennial C4 bunchgrass. According to the data collected before the onset of the fertilizer experiment (beginning of June 2007), these four species totally accounted for 74–85% of aboveground biomass across grazing intensities (data not shown). 2.2. Experimental design This experiment was designed as a randomized complete block with a split–split plot arrangement with two replications. Four grazing intensities represented the main plots each including subplots with two water supply levels (W0, unirrigated; W1, irrigated simulating precipitation in a wet year) and two N fertilizer treatments (N0, unfertilized control; N1, 75 kg urea–N ha−1 year−1 ). There was an annual shift between grazing and hay making on the main plots. 2.2.1. Grazing treatment We chose four grazing intensities in a rotational grazing system as the main plots of grazing intensities (Fig. 2). Four grazing intensities, ungrazed (G0), low (G1), moderate (G2), and high (G3) grazing intensities, were defined according to the mean stocking rates of two years (0, 2, 4, and 7 sheep ha−1 , respectively, see Appendices Table A1). In this rotational grazing system, annual shifts between grazing and hay-making plots were carried out. Experimental period covered the main grazing season from beginning of June to end of August, which was coincident with the grazing period of the local management regime. The main plots of grazing treatment were replicated in two fixed blocks. Plot size of each grazing plot was 2 ha, except for the low grazing intensity (G1) which had 4 ha, in order to have at least 6 sheep in each plot.

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Fig. 2. Illustration of the layout for the main plots of grazing intensity and subplots in a rotational grazing system. In this rotational grazing system, same land was used for grazing in one year and for hay production in the next year. G0–G3 represent no grazing, low, moderate, and high grazing intensities. Notably, the locations of the main plots of grazing intensities were randomly selected in the field. Nested panels represent the arrangement of subplots within a movable exclosure.W0 and W1 represent unirrigated and irrigated treatments, respectively. N0 and N1 represent no fertilization and fertilizer N supplementation (75 kg N ha-1 y-1 ) treatments, respectively. Lowercase letters a–c indicate the changing of locations of exclosures in each month. For the size of main plots and mobile exclusures see Section 2.2.

2.2.2. Water and nitrogen treatments Within each main plot, water and N addition treatments were carried out inside a movable exclosure (size 4.5 × 4.5 m, height 1 m, Fig. 2) constructed of ∼8 cm square mesh utility fencing with rebar posts at diagonal corners and in between. At the beginning of June, the exclosure cage was set up at location ‘a’ (see Fig. 2) and water and fertilizer was supplied to these subplots (within movable exclosure). One month later, after sampling of plants at location ‘a’, the exclosures were moved to another representative area in the same grazing plots (e.g., location ‘b’). Water and fertilizer treatments were done in the exclosure at location ‘b’. Again, the exclosure cages were moved to another area (e.g., location ‘c’) 1 month later. The locations of movable exclosures were randomly selected in the grazing plots, but the locations were not kept too close to the boundary of grazing plots (>2 m). We employed moveable exclosure method (McNaughton et al., 1996) with changing the locations of subplots monthly. This approach allowed us to quantify aboveground net primary production. Therefore, the interaction effects of grazing and resources supply on ANPP and BNPP were evaluated.

to the other representative sites within the main grazing plot, and again, 25 kg N ha−1 were applied in the N fertilization subplots, and 10 mm additional water was added in all subplots. The long-term rainfall data of 1982–2003 were used to schedule the irrigation management during the two experimental years (2007 and 2008) (details are similar as shown in Gong et al., 2011b). In order to simulate the precipitation of a wet year, the 10-day accumulated rainfall amount of ongoing year was compared with corresponding mean value of wet years and the difference was applied by irrigation (Fig. 1). Total rainfall during the growing seasons were 178 mm in 2007 and 277 mm in 2008. Thus, the irrigated plots received 185 mm of irrigation water in 2007, and 120 mm in 2008. Irrigation was carried out manually using a mobile irrigation facility mounted on a trailer: including water tank, generator, water pump, and injector with water flow controller. Since evapotranspiration of this grassland ranged between 2 and 8 mm per day (Zhao et al., 2011), at least 10 mm water was added at each irrigation event. Irrigation was carried out in the morning in 10-day intervals. 2.4. Data collection and parameters

2.3. Water and nitrogen supplementations N fertilizer was applied to the subplots in order to compensate the grazing induced N loss. A stocking rate of 2 sheep unites ha−1 lead to a net N loss of 9 kg N ha−1 y−1 in a similar rangeland (Giese et al., 2013). Considering the higher stocking rates in this study and up to 40% of urea loss to the air as ammonia, 75 kg N ha−1 y−1 was applied. At the beginning of June, 25 kg N ha−1 was applied in the N fertilization subplots, and 10 mm additional water was added in all subplots. Urea was mixed with fine-sieved dry soil and manually applied, and this 10 mm water was applied immediately after fertilization in order to minimise volatilization loss of nitrogen. Exclosures were moved at the beginning of July and August

Aboveground plant biomass outside the movable exclosures (grazed vegetation) was harvested at the beginning of June–August, and at the end of August in 2007 and 2008, whereas, aboveground biomass inside the enclosure was harvested at end of June–August. Vegetation height was measured using a ruler with 12 replications within each field plot. Afterward, aboveground biomass was clipped at the soil surface in three sampling quadrates of 0.25 m2 in each subplot and aboveground green biomass (AGB) was separated from litter. Samples were oven-dried at 75 ◦ C for 48 h and dry mass was subsequently determined. Root samples were taken following the regime of shoot sampling only in 2007. Within each plot, two root samples were taken using a

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cylindrical auger (diameter: 10 cm) in the same sampling quadrate where shoot materials were cut off. Samples were taken at 0–60 cm depth and put into mesh bags with 0.4 mm of mesh size, and were washed to separate root, soil, and sand. Root sample was separated into a living root part and a dead root part including organic matter. The separation was done based on color and flexibility of roots. All root samples were dried in a drying oven at 75 ◦ C for 48 h and weighed afterwards. Maximum AGB observed outside the exclosure within a growing season was termed as peak aboveground green biomass outside exclosure (PAGB). Aboveground net primary production (ANPP) was calculated by the plant biomass at the initial date of grazing (beginning of June) summed to the monthly herbage growth measured by the movable exclosure method (McNaughton et al., 1996). Belowground net primary production (BNPP) was calculated by summing increases in living root biomass during growing season (Aerts et al., 1989). ANPP and BNPP were calculated using the following equations: ANPP = W 1g + (W 2u – W 1g ) + (W 3u – W 2g ) + (W 4u – W 3g

(1)

BNPP = (W 2u – W 1g ) + (W 3u – W 2g ) + (W 4u – W 3g

(2)

effects. For the peak standing biomass outside cages, the statistical model included grazing intensity, block, year, and their interactions as fixed effects, and year was tested as repeated effects. Multiple comparisons of means were done using the Tukey’s test. 3. Results 3.1. Aboveground and belowground production Peak aboveground green biomass outside the enclosures decreased with the increase of grazing intensity in both years (Table 1, Fig. 3a). However, grazing intensity had no significant effect on aboveground net primary production (ANPP) in the two

where Wi is the plant above- (below-) ground dry mass at sample time ti (i = 1–4 represent beginning of June–September, respectively). Indices u (ungrazed) and g (grazed) indicate samples were taken inside and outside the exclosures. Net primary production (NPP) was calculated as NPP = ANPP + BNPP. Fraction of BNPP to net primary production (fBNPP ) was calculated as: fBNPP = BNPP/NPP. In calculations of ANPP and BNPP, only living biomass was took into account. Some authors also used more elaborated methods based on dynamics of live and senescent tissues as reviewed by Ruppert and Linstädter (2014); however, it is challenging and laborious to quantify senescence rate due to the substantial amount of dead roots in semiarid grassland. Plant material in two quadrates (20 × 20 cm2 ) in each subplot was clipped at the soil surface to determine the tiller density and LAI. Plant materials were put in a cooling box to prevent convolving of leaves. The number of tillers was counted, and afterwards plant material was separated into leaf blades and stems including leaf sheaths. The leaf area was measured using an area meter (LI-3000A, LI-COR, Lincoln, Nebraska, USA) equipped with a transparent belt-conveyer (LI-3050, LI-COR, Lincoln, Nebraska, USA). Thereafter, leaves and stems were oven-dried at 75 ◦ C for 48 h, and dry mass was determined afterwards. The following parameters were derived: tiller weight (g DM tiller−1 ), tiller density (tillers cm−2 ), leaf area index (LAI, leaf area per unit ground area, m2 m−2 ), leaf area ratio (leaf area per unit aboveground dry mass, m2 kg−1 ), leaf weight ratio (leaf dry mass per unit aboveground dry mass, %), and specific leaf area (leaf area per unit leaf dry mass, m2 kg−1 ). 2.5. Statistical analysis Statistical analysis was performed using SAS Version 9.1 (SAS Institute Inc., Cary, NC, USA). Mixed models were used for analysis of variance. For ANPP, the statistical model included grazing intensity, block, water, and N addition, year and their interactions as fixed effects; year was tested as repeated effect; and block × grazing intensity and block × grazing intensity × water were tested as random effects. For LAI, leaf area ratio, leaf weight ratio, specific leaf area, tiller density, and tiller weight, data of three sampling dates in each year were averaged and subjected to the same repeated measurement ANOVA. For parameters collected in a single year (BNPP and fBNPP ), grazing intensity, block, water and N addition, and their interactions were tested as fixed effects; and block × grazing intensity and block × grazing intensity × water were tested as random

Fig. 3. Peak plant aboveground green biomass outside exclosure (PAGB, a), plant aboveground net primary production (ANPP, b), belowground net primary production (BNPP, c), and fraction of BNPP to NPP (fBNPP , d), as affected by grazing intensities, water and nitrogen additions. PAGB, ANPP were shown as the means of two sampling years. BNPP and fBNPP were shown based on data of 2007. For abbreviations of water and N treatments see Fig. 2. Error bars represent standard error of the means.

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Table 1 ANOVA table for the effects of year (Y), grazing intensity (G), water (W), and nitrogen (N) on peak aboveground green biomass outside exclosures (PAGB, g m−2 ), aboveground net primary production (ANPP, g m−2 y−1 ), belowground net primary production (BNPP, g m−2 y−1 ), net primary production (NPP, g m−2 y−1 ), fraction of BNPP to NPP (fBNPP ), and litter dry mass (g m−2 ). Treatments effects on PAGB, ANPP and litter dry mass were tested using data of 2007 and 2008, the rest of parameters were tested using data of 2007. Significant effects are shown in bold font (P < 0.05). Source

df

Y G W N G×N

1 3 1 1 3

PAGB

ANPP

BNPP

F

P

F

P

1.4 9.9

0.30 0.03 – – –

1.4 0.9 98.6 41.1 5.7

0.25 0.50 <0.01 <0.01 0.01

NPP

F

P

3.4 0.1 0.0 2.5

– 0.13 0.79 0.96 0.11

fBNPP

F

P

3.0 0.0 0.0 2.7

– 0.16 0.95 0.89 0.09

Litter mass

F

P

F

P

4.3 0.4 0.7 1.1

– 0.02 0.54 0.43 0.37

2.7 110.9 17.4 0.3 0.9

0.121 <0.01 0.01 0.60 0.49

No significant effect of G × W, W × N and G × W × N was detected.

of BNPP at high grazing intensity (G3) was observed (Fig. 3c). Fraction of BNPP to NPP (fBNPP ), was in the range of 0.3–0.9. fBNPP was not affected by water and N additions but significantly affected by grazing intensity (Fig. 3d). fBNPP was similar between sites with low or moderate grazing intensities (∼0.8) but drastically decreased at high grazing intensity (0.51 at G3). Plant litter was significantly decreased by grazing intensity and water addition, but not affected by N addition (Table 1, Fig. 5).

3.2. Plant, tiller, and leaf traits

Fig. 4. Relative response of ANPP to N addition (ANPPN1 /ANPPN0 , water treatments were pooled) and to water addition (ANPPW1 /ANPPW0 , N treatments were pooled) along the grazing intensity gradient. Data of two years were pooled. Error bars represent standard error of the means.

growing seasons (Table 1, Fig. 3b). Water or N fertilizer addition significantly increased ANPP (Table 1, Fig. 3b). Pooled over the data of grazing intensities in two years, ANPP increased to 39% by addition of water and to 23% by addition of N fertilizer; which was equal to the ANPP increase of 519 kg DM ha−1 by water and 335 kg DM ha−1 by N fertilizer. However, the interaction effect of water and N was not significant. N effect on ANPP differed between grazing intensities, ANPP had higher response to N addition at lower grazing intensity than at higher grazing intensity (Fig. 4). ANPP response to water addition was in the similar magnitude as response to nitrogen, while, water response was not affected by grazing intensity (Fig. 4). Belowground net primary production (BNPP) and net primary production (NPP) was not affected by grazing intensity, water, and N fertilizer additions (Table 1, Fig. 3c). However, a strong reduction

Tiller weight, LAI, and height of plant community were decreased by grazing intensity, whereas, leaf area ratio and leaf weight ratio were increased by grazing intensity (Table 2). Specific leaf area and tiller density were not affected by grazing intensity (Table 2). Plant tiller weight was significantly increased by water and N fertilizer additions, whereas, tiller density was only increased by water supplementation (Table 2). Water addition increased LAI, leaf area ratio, and specific leaf area, but not leaf weight ratio. N addition only increased LAI but had no effect on other traits. Water and N interactively increased LAI. Year as a within-subject effect significantly influenced most of the plant traits (Table 2). The precipitation during the growing season was 178 mm in 2007 and 277 mm in 2008 (Fig. 1). Consequently, LAI, leaf area ratio, leaf weight ratio, and specific leaf area were significantly higher in 2008 than 2007 (data not shown), which is in line with the effect of water addition on plant traits. However, plant tiller weight and density were not significantly different between the two years. Water addition increased vegetation height, but an effect of N fertilizer addition on vegetation height was not found.

4. Discussion Knowledge of plant–herbivore–resources interactions is essential for understanding ecosystem functioning and land use management in semiarid steppe. Aboveground net primary production, one of the fundamentals of ecosystem processes, is interactively constrained by water and N in semiarid steppe (Gong et al., 2011a; Hooper and Johnson, 1999). It has been suggested that overcompensation would most likely happen in conditions with high resource availability (Maschinski and Whitham, 1989). Thus, a grazing experiment with manipulated water and N addition levels was performed to investigate plants’ compensatory growth. However, in this study, neither ANPP nor NPP were increased by grazing in any combination of water and N fertilizer additions. Our findings indicate that the hypothesis of grazing optimization may not be applicable in semiarid steppe. As reviewed by Painter and Belsky (1993), whole-plant overcompensation rarely occurs and grazing optimization theory may have little evolutionary or

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Fig. 5. Litter dry mass (litter DM) as affected by water addition a) and stocking rate b). For abbreviations of water and N treatments please see Fig. 2. Error bars represent standard error of the means.

applied significance. Therefore, our study aims at pursuing better understanding of the mechanism underling plant regrowth. Herbivory may be the most frequent cause of damage for plants in semiarid rangelands. In our study, grazing decreased peak standing biomass and leaf area index of the plant community. Similarly, the standing biomass of dominant species has been shown to decrease along grazing intensities in a study focused on specieslevel responses (Fanselow et al., 2011). However, in our study, ANPP was not significantly reduced along the grazing intensity gradient, which indicates that plants’ regrowth partially compensated herbivore intake. Rapid compensatory growth after defoliation is a strategy of tolerance (Belsky et al., 1993), and it can be achieved by reallocation of substrates from elsewhere (McNaughton, 1979). In this study, ANPP of heavily grazed site (G3) was at the similar level as ungrazed site, while BNPP had a clear (although not statistically significant) reduction at heavily grazed site. Thus, BNPP/NPP was significantly reduced by high grazing intensity form 0.8 to 0.5. These results indicate that ANPP is maintained at the expense of biomass (or carbon) allocation to the root. This finding is in agreement with the functional equilibrium theory, which suggests that plant will allocate relatively more biomass to shoot if the limiting factor for growth is above ground (Davidson, 1969; Poorter

et al., 2012). After defoliation, plant growth is generally limited by carbon gain due to the loss of leaf area, thus, more carbon is allocated to shoot growth (Briske et al., 1996). High grazing intensity did not decrease ANPP in the short-term observation in this study, but may decrease BNPP and, thus, soil carbon storage in the long run. Existing literature indicates that grazing has either negative (Biondini et al., 1998; Ferraro and Oesterheld, 2002; Turner et al., 1993) or neutral (McNaughton et al., 1998; Milchunas and Lauenroth, 1993) effects on BNPP. Studies in the semiarid grassland have shown a clear decrease of ANPP after 3 years of grazing (Schönbach et al., 2010), and 2 years of cutting had no effect on BNPP (Schiborra et al., 2009). However, long history (>20 year) of heavy grazing has led to drastically deceases of BNPP and BNPP/NPP (Gao et al., 2008) and soil organic carbon content (Steffens et al., 2008). Our results highlight the importance of “whole-plant” view on herbivore–plant interactions, since, ignoring belowground production leads to erroneous interpretation of ecological processes and unrealistic prediction of ecological consequences. Water and N fertilizer additions significantly increased ANPP by 39% and by 23%, respectively, in the current study. This indicates a strong control of abiotic factors, namely, water and nitrogen, rather than grazing intensities on ANPP. This is in line with the finding that

Table 2 ANOVA table for the effects of year (Y), grazing intensity (G), water (W), and nitrogen (N) on tiller weight (TW, g tiller−1 ), tiller density (TD, tiller cm−2 ), leaf area index (LAI, m2 m−2 ), leaf area ratio (LAR, m2 kg−1 ), leaf weight ratio (LWR, % DM), specific leaf area (SLA, m2 kg−1 ), and vegetation height (height, cm). Treatments effects on vegetation height were tested using data of 2007. Data were shown as least square means. Lowercase letters indicate differences are significant at P-level of 0.05. TW

TD

LAI

LAR

LWR

SLA

Height

G0 G1 G2 G3

0.069a 0.057b 0.052b 0.038c

0.23 0.23 0.23 0.25

0.78a 0.73a 0.62b 0.58b

4.89b 5.63ab 5.24b 6.16a

57.7c 67.6ab 64.2b 67.8a

8.45 8.28 8.06 9.08

26a 19b 18bc 15c

W0 W1

0.051b 0.057a

0.23b 0.25a

0.60b 0.76a

5.38b 5.58a

64.6 64.0

8.28b 8.66a

19b 20a

N0 N1

0.052b 0.057a

0.23 0.24

0.63b 0.72a

5.40 5.57

63.6 65.0

8.45 8.49

20 20

<0.01 0.04 0.04 0.07 0.12

<0.01 <0.01 0.44 0.09 0.81

<0.01 0.268 <0.01 0.699 0.130

– <0.01 0.03 0.655 0.899

0.57c 0.62bc 0.69b 0.82a

W0N0 W0N1 W1N0 W1N1 Source Y G W N W×N

df 1 3 1 1 1

Significance of treatment effects 0.25 0.33 0.01 0.60 0.01 0.02 0.03 0.37 0.72 0.84

No significant effect of G × W, G × N, and G × W × N was detected.

<0.01 0.01 <0.01 <0.01 0.04

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temporal variability in precipitation and temperature, rather than grazing, determines vegetation dynamics and species coexistence in a grazed steppe (Ren et al., 2012). Interestingly, supplied water generally increased ANPP irrespective to grazing intensities, while N addition was more effective at low grazing intensities. Again, this finding does not support the grazing optimization theory. The N addition being less effective at high grazing intensities may be explained by two mechanisms: firstly, limited leaf area of grazed plants constrains photosynthesis (shortage in carbon source); and secondly, severely damaged plants have exhausted their stored substrate for reconstruction of leaves (shortage in substrate). N effect on ANPP can partially contribute to the change in allocation priority (Gao et al., 2011). Coexisting species generally increased C allocation to shoot growth after N addition (Gong et al., 2014); however, grazed plants may have less substrate to be reallocated to the shoot. Therefore, N fertilization may be a less effective restoration option for heavily grazed grasslands than for lightly or moderately grazed grasslands. Litter layer plays an important role in maintenance of microclimate and nutrient cycling (Aerts, 1997; Aerts et al., 2003). In a rangeland ecosystem, grazing induced litter loss has lead to a higher evaporating water loss and a decline of soil organic carbon (Golluscio et al., 2009; Steffens et al., 2008). Litter mass was strongly reduced by grazing in this study, which is in line with others’ finding (Biondini et al., 1998). One of the explanations for this is that grazing reduces leaf senescence rate, since some of the leaves have been defoliated before senescence (Sanaullah et al., 2010). It has been reported that continuous grazing reduced leaf life span of dominant species (Schleip et al., 2013), which indicates a higher tissue turnover rate in response to herbivory. Moreover, litter mass was reduced by water addition in our experiment; this might be due to the reduction of the leaf senescence rate or the tiller mortality rate during the summer dry period. Beside aboveground–belowground allocation patterns, plants also have considerable plasticity in morphological traits to adapt to disturbance. Plants compensate for defoliation by producing new leaves with larger specific leaf area and more smaller tillers (Oesterheld and McNaughton, 1988). In this study, plant tiller weight was decreased by grazing intensity whereas tiller density was not affected. Plant LAI and vegetation height were decreased by grazing intensity, which corresponds to many of the findings of grazing and defoliation experiments (McNaughton, 1992; Zhao et al., 2009). The significant increases of leaf area ratio and leaf weight ratio along grazing intensities indicate higher biomass allocation to leaf rather than to stem in order to maintain a larger leaf area and a lower height, which has been considered as traits of defoliation tolerance (McNaughton, 1992; Oesterheld and McNaughton, 1988; Schiborra et al., 2009). Moreover, responses of ANPP to water or N addition are related to some key plant functional traits. Relative growth rate can be factored into three components: unit leaf rate (increase in biomass per unit time and leaf area), specific leaf area, and the leaf weight ratio (Poorter and Nagel, 2000). In this study, water and N differed in the way that they modified plant traits to increase growth: water addition increased specific leaf area while N addition probably increased unit leaf rate. Although we did not measure unit leaf rate, it has been shown that N addition increased leaf N content and intrinsic water use efficiency of dominant species (Gong et al., 2011b), therefore, N addition might increase photosynthesis rate and unit leaf rate in our study. Tiller weight was significantly increased by water or N additions, whereas, tiller density was only slightly increased by water addition. Water addition significantly increased LAI, which is seen as positive effects in terms of enhancements of ground cover and photosynthesis. Notably, responses of community-level morphological traits were not due to the shift of species composition in our experiment. We did not detect any significant shift in species

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composition in this 2-year experiment (data not shown). In parallel, longer monitoring (6 year) in a grazing experiment in the same ecosystem has shown little effect on species composition (Ren et al., 2012). Moreover, we found that species-level traits, e.g., leaf area ratio and leaf weight ratio, had similar responses to grazing (see Appendices, Fig. A1). 5. Conclusion In this 2-year study, we found no evidence of grazing optimization on primary production with all combinations of water and N fertilizer supplementations. However, plants minimized the reduction of ANPP by decreasing BNPP/NPP. This indicates that plants’ compensatory growth of shoot is at the expense of allocation to belowground, which may lead to decrease of soil organic matter content in the long run. Water and nitrogen additions significantly increased grassland ANPP but had no effect on BNPP. N fertilizer addition was less effective at heavily grazed sites than at lightly grazed sites, due to the constraints of leaf area for photosynthesis and the limited substrates for regrowth. Notably, our field trials with N and water additions are not tested as potential management practice, since, it is unrealistic to apply fertilization and irrigation in this vast grassland. Our study indicates that short-term grazing (with max. 7 sheep ha−1 ) has limited effect on primary production, and precipitation and nitrogen status need to be specially concerned in optimizing land use practices in semiarid steppe. Responses of primary production to herbivory and resources additions are tightly linked to biomass allocation pattern and organ morphology of plants. Our study highlighted the “whole-plant” perspective when studying primary production of semiarid rangelands. Acknowledgments This research was funded by National Nature Science Foundation of China (NSFC 41071207) and the Deutsche Forschungsgemeinschaft (DFG), project DI 546/3-2, and project TA 215/3-3, FG 536, MAGIM (Matter fluxes in Grasslands of Inner Mongolia as influenced by stocking rate). X.Y. G. was funded by a doctor fellowship from German Academic Exchange Service (DAAD). The authors thank Inner Mongolia Grassland Ecosystem Research Station of Botany Institute, Chinese Academy of Science for providing working facility and meteorological data. We thank the two anonymous referees for constructive comments and suggestions. Appendices.

Table A1 Average stocking rates and herbage allowances (kg dry matter per kg live weight) during grazing seasons in 2007 and 2008. Data represent seasonal means ± SE. Grazing intensity was defined as no grazing, light, moderate, and heavy grazing intensities according to the stocking rates. Grazing intensity G0 2007 Stocking rate (sheep ha−1 ) Herbage allowance (kg DM kg−1 LW) 2008 Stocking rate (sheep ha−1 ) Herbage allowance (kg DM kg−1 LW)

G1

G2

G3

0±0

2.1 ± 0.2

3.9 ± 0.1

6.7 ± 0.2

–

9.8 ± 1.8

4.0 ± 0.5

1.9 ± 0.3

0±0

1.6 ± 0.0

3.8 ± 0.3

7.6 ± 0.4

17.2 ± 0.6

5.1 ± 0.5

1.4 ± 0.1

–

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Fig. A1. Leaf area ratio (a) and leaf weight ratio (b) of dominant species along grazing intensity in 2007. Circles represent Leymus chinensis, diamonds represent Cleistogenes squarrosa, triangles represent Agropyron cristatum, and squares represent Stipa grandis. Error bars are standard error of means. Data of water and N treatments and three sampling times were pooled.

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