Nonlinear response of soil respiration to increasing nitrogen additions in a Tibetan alpine steppe

The study was conducted on the Sanjiaocheng Sheep Breeding Farm (37°18^'N, 100°15^'E, 3290 m a.s.l), an alpine steppe located in Qinghai Province, China. The long-term mean annual temperature is 0.08 °C and the mean annual precipitation is 387 mm (1980–2012). The native vegetation is a typical alpine steppe community, characterized by the dominant species of Stipa purpurea, Carex rigescens, Poa crymophila Keng, Agropyron cristatum, Heteropappus altaicus (Willd.) Novopokr, etc. The soil type at the study site is classified as chestnut according to Chinese classification or Haplic Calcisol according to the FAO (Food and Agriculture Organization) classification, with 61.0% sand, 33.4% silt, and 4.9% clay. The chemical properties of the 0–30 cm soil layer at the beginning of the experiment were as follows: soil organic C 20.5 g kg⁻¹, total- N 2.5 g kg⁻¹, total phosphorous (P) 0.6 g kg⁻¹, pH 9.5, NO₃⁻-N 11.5 mg kg⁻¹, NH₄⁺-N 0.1 mg kg⁻¹ and available P 2.2 mg kg⁻¹.

The experimental site was fenced and the N enrichment experiment started in May 2013. Other than grazing, no other management had been applied on the site before the experiment. A gradient of eight N levels (0, 1, 2, 4, 8, 16, 24, and 32 g m⁻² yr⁻¹, labeled N0, N1, N2, N4, N8, N16, N24 and N32, respectively) was established and arranged in randomized complete blocks with five replications. The plot size was 6 m × 6 m and a total of forty plots was created. The distance between any two adjacent plots within a block was 1 m and each block was separated by 2 m buffer strips. N fertilizer, in the form of ammonium nitrate, was applied at the beginning of each month during the growing season from May to September every year. At each plot, a specific amount of fertilizer was dissolved in 10 L of water and sprinkled by a backpack sprayer. Two passes were made across each plot to ensure an even distribution of the fertilizer. The control plot received the same amount of water without N.

2.3.1. Rs and its components

2.3.2. Plant and soil sampling

2.3.3. Laboratory analyses

To examine the nonlinear response patterns of Rs, Ra and Rh along the N addition gradient, an empirical function (y = a + bx^c/e^dx, where y is Rs, Ra or Rh, x is the N addition rate, and a, b, c and d are the coefficients, Yang et al 2010) was employed to characterize the relationships of these variables with N addition rates during each growing season. One-way ANOVA was used to compare the treatment difference for Rs, Ra and Rh as well as biotic and abiotic variables. Ordinary least square regressions were conducted to explore the relationships of Rs, Ra and Rh with biotic and abiotic parameters. All these analyses were performed with SPSS statistic 16.0 (IBM SPSS, Chicago, Illinois, USA).

Structural equation modeling (SEM) was used to examine the relative importance and direct and indirect pathways of various factors regulating Ra and Rh along the N addition gradient. Before SEM analysis, we constructed an a priori conceptual model of hypothetical relationships (figure S1 available at stacks.iop.org/ERL/12/024018/mmedia). Theoretically, a number of biotic and abiotic factors are assumed to influence soil CO₂ flux, but our model only adopted those factors showing significant correlations with Ra or Rh along this N addition gradient, at least in 2015 (see figures 3 and 4). Therefore, we hypothesized that, soil temperature directly influenced Ra and Rh, and also indirectly influenced them through regulating root and microbial biomass. Meanwhile, soil inorganic N and pH affected Rh directly and also indirectly via MBC (figure S1). During SEM analysis, data were fitted to the model using the maximum likelihood estimation method. This procedure compared the model-implied variance–covariance matrix with the observed variance–covariance matrix, and used the chi-square goodness-of-fit statistic and its associated P value to test the model fit to the data. The covariance structure of the data was considered not to be significantly different from the expected model if the P value was larger than 0.05 (Grace 2006). SEM analyses were conducted using Amos version 21.0 (Amos Development Corporation, Chicago, IL, USA).

With the N addition rate continuously increasing, the seasonal means of Rs and Ra exhibited first increasing and subsequent decreasing trends at a threshold of 8 g N m⁻² yr⁻¹ (figures 1(a)–(d)). In contrast, a linear negative relationship was fit to Rh data under increasing N additions (figures 1(e) and (f)). During the two experimental years, except for Rh in 2014, additional N inputs significantly altered Rs and its components (table S1). The annual budgets for the three parameters were also influenced by N additions, showing similar patterns as seasonal averages along the N addition gradient (table S1).

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In general, the seasonal dynamics of Rs and its autotrophic and heterotrophic components followed a bell-like pattern in both experimental years, with higher values in the mid-growing season and lower values in the early and late seasons (figure 2). Inter-annual variations of Rs, Ra and Rh were observed across the two experimental years. The maximum values of Rs and its components appeared in mid-August in 2014 but in mid-July in 2015. In addition, N input exaggerated their inter-annual variability by strengthening the maximum values (figure 2).

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Increasing N additions had significant influences on the biotic and abiotic factors (table 1). ANPP consistently displayed a saturation trend with increasing N additions regardless of inter-annual variation, with a saturation point occurring at 8 g N m⁻² yr⁻¹. The relationship between root biomass and the N addition rate was characterized by a hump-shaped pattern similar to Rs and Ra, with a peak appearing in the N8 treatment. In 2014 no significant response to the N addition was observed in MBC, whereas in 2015, it increased gradually until 4 g N m⁻² yr⁻¹ and thereafter declined.

Soil temperature increased with increasing N additions up to 4 g N m⁻² yr⁻¹ and then decreased after this N level in 2014, while in 2015, no obvious change was found among the N0 to N4 treatments, but the N8 to N32 treatments significantly reduced soil temperature. In both years, soil moisture generally showed a funnel-like pattern along the N gradient, with the minimum at 8 g N m⁻² yr⁻¹. Soil inorganic N increased monotonously with increasing N additions in 2015, but the increasing trend leveled off after the N8 treatment in 2014. Soil pH was also negatively related to the N addition rate in 2015, while no obvious trends were observed along the eight N levels in 2014.

Across the 40 experimental plots, Rs, Ra and Rh increased linearly with increasing soil temperature in both experimental years (figures 3(d), (k) and (r); figures 4(d), (k) and (r)). Meanwhile, Rs and Ra were also positively related to root biomass (figures 3(b) and (i); figures 4(b) and (i)). In addition, Rh increased with MBC in 2015 (figure 4(q)). Soil inorganic N also negatively influenced Rs and Rh (figures 4(f) and (t)), but positively regulated both variables in 2015 (figures 4(g) and (u)).

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The SEM analysis indicated that, along the gradient of N additions, root and microbial biomass were the direct controllers of Ra and Rh. Soil temperature directly influenced Ra and Rh in both years, and it also indirectly affected the Ra via root biomass and the Rh via MBC. Although the soil temperature, inorganic N and pH were all significantly correlated with Rh (figure 4), only the soil temperature entered the final model (figure 5).

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In the current study, we used the deep-collar method to distinguish Ra and Rh, a method which has been widely applied to partition Rs in other studies (Zhou et al 2007, Hasselquist et al 2012, Li et al 2013, Suseela and Dukes 2013). Given that roots in the top 30 cm of soil accounted for more than 90% of the biomass of those in the 0–50 cm soil profile at our experimental site (data not shown), the 60 cm long collar was long enough to exclude most of the living roots. It has been reported that the deep-collar method generally results in a transient increase of Rs due to the decomposition of dead roots and disturbance (Hanson et al 2000, Zhou et al 2007). It has also been suggested that the transient increase of Rs lasted for about five months after collar insertion in a prairie in Southern Great Pains, USA (Zhou et al 2007). Given that collars were inserted into the soil in May 2013, the effects of dead root decomposition on the Rh measured after a whole year should be minimized. More importantly, our results revealed that the contribution of Rh to Rs was 46%–63% and 52%–70% in 2014 and 2015, respectively, and these values are within the range reported in grassland ecosystems (25%–90%, Subke et al 2006). Therefore, despite the fact that some uncertainties may be inevitable, the root exclusion method is a feasible way to partition the two components of Rs in this alpine steppe.

Although individual studies reported inconsistent responses of Rs and its components to N enrichment, a recent meta-analysis showed that N addition, in aggregate, increased Rs and Ra but reduced Rh in grasslands (Zhou et al 2014). However, to date, information is still lacking about how Rs and its autotrophic and heterotrophic components change from limited to saturated N scenarios. The present study revealed that in a N-limited alpine steppe, with the N addition rate continuously increasing, both Rs and Ra exhibited hump-shaped response patterns while Rh declined linearly (figure 1). Nevertheless, it should be noted that our study only showed the responses of soil CO₂ fluxes to short-term N additions (three years), but it remains unclear whether long-term N enrichment would cause some differences. For example, the N-induced shifts in plant community composition and structure exert great influences on ecosystem C cycling (Niu et al 2010, Chen et al 2016), but we know little about how these changes will affect Rs after a long time period, particularly under multiple N loads. Thus, experiments with long duration and multiple N loads (at least more than five N addition levels) are called for to better depict the Rs/Ra/Rh–N rate relationships in future studies.

The seasonal dynamics of Ra and Rh displayed temporal variability across the two experimental years (figure 1). Inter-annual variation of Rs, Ra and Rh have been frequently reported in grasslands and other ecosystems (Liu et al 2002, Concilio et al 2009), which may result from temporal variations in various biotic and abiotic factors (Luo and Zhou 2006). First, the precipitation distribution varied significantly during the two growing seasons (figure S2). In particular, for the peak plant growth in August, the precipitation amount in 2015 (79 mm) was significantly lower than in 2014 (186 mm). Low soil moisture in 2015 (11%) compared with 2014 (30%) may have repressed root and microbial activities (Luo and Zhou 2006), thus leading to reduced Rs during this period (figure 2). Second, the soil's inorganic N concentration increased linearly with increasing N additions in 2015, but the increasing trend leveled off after the N8 treatment in 2014 (table 1). The distinct response patterns are possibly due to the high NO₃⁻-N leaching to deeper soils under larger precipitation amounts in 2014. This is partly supported by the greater soil NO₃⁻-N concentration in the 30–50 cm soil layers measured in mid-August (figure S3). The high inorganic N accumulated in 0–10 cm of soil may be toxic to microbial growth and activities (Aber et al 1989), thus resulting in significant negative correlations of Rs and Rh with this variable in 2015 (figures 4(f), (t)). Third, the root and microbial biomass in 2014 was greater than those in 2015 (table 1). Larger root biomass indicates more C was allocated below ground (Peng and Yang 2016), which is usually associated with higher root respiration (Bai et al 2010). Meanwhile, increased microbial biomass was generally observed to have higher Rh (Zhou et al 2014, Chen et al 2016). These differences between the two experimental years may lead to greater soil CO₂ fluxes during the peak growth stage in 2014 (figure 2).

Several biotic and abiotic factors regulate the change of Ra and Rh along this N addition gradient. The SEM analysis indicated that root biomass and MBC were direct controllers of Ra and Rh, and further, that soil temperature also directly and indirectly explained their variations (figure 4). Root biomass had a direct effect on Ra, because larger root biomass means greater root surface area for respiration (Zhou et al 2014). Consistent with this point, root biomass had a similar hump-shape response pattern to Ra along this N gradient (table 1). Before the N saturation (8 g N m⁻² yr⁻¹), root biomass increased in both years (table 1). This is because during this time, albeit with the N addition reducing growth limitation to a certain degree, plants are still under the limited-N condition. Thus, they need to allocate a portion of C to roots for additional N uptake to maintain plant growth (Peng and Yang 2016). Meanwhile after the saturation point, root biomass decreased; this was likely due to 1) decreased root production. In cold regions, such as the tundra or alpine steppe, experimental N addition generally decreased C input to roots (Peng et al 2017), especially under high levels of N addition (Sullivan et al 2007). This is likely because temperature is usually the major growth-limiting factor in these sites, and plants cannot absorb too much N due to the low growth rate even under N addition. Meanwhile, high N accumulation in mineral soils may be harmful for root growth (Marschner 2011), thus resulting in low production of roots. 2) increased root turnover rate, or in other words, reduced root life span. For instance, Bai et al (2008) reported that an addition of 32 g N m⁻² yr⁻¹ significantly reduced root life span from 81 d to 64 d in a 0–30 cm soil depth in a temperate steppe on the Inner Mongolian Plateau. Taken together, the decreased root production and increased turnover rate may cause reduced root standing biomass at high N addition levels.

Microbial biomass directly explained the variance in Rh along the gradient of N additions in 2015 (figure 4). Low N addition levels (from 1 to 4 g N m⁻² yr⁻¹) gradually increased microbial biomass, but high levels of N addition suppressed it (table 1). The stimulation of microbes by low N may be due to the reduced C and N limitation after increased litter input from the first two years; furthermore, the decrease in the microbial biomass under the high N supply is potentially because the high dose of N addition reduced the C transfer to the rhizosphere, and induced shifts in the microbial community and decomposing enzymes; this would enhance the formation of recalcitrant compounds, thus causing decreased microbial respiration (DeForest et al 2004, Janssens et al 2010, de Vries et al 2014). However, under low N levels, the changes in the microbial biomass did not match well with the changes in Rh, and the underlining mechanisms need further investigation.

Soil temperature was the only environmental factor entering the final SEM (figure 5), likely indicating that it is the most important abiotic factor regulating Rh, while the effects of pH and inorganic N are relatively weaker along this N-addition gradient. Soil temperature not only directly explained the variations of Ra and Rh by regulating respiration enzymes (Atkin and Tjoelker 2003), but also indirectly influenced them via affecting root and microbial growth (Janssens et al 2010). We observed that soil temperature displayed a decreasing trend with increasing N additions, especially for those plots receiving a N rate of more than 8 g m⁻² yr⁻¹ (table 1). This is likely because N addition increased above-ground plant growth and the more closed canopy prevented the incoming solar radiation to the soil surface (Luo and Zhou 2006). Consistent with this deduction, we observed a negative relationship between soil temperature and light interception in 2015 (figure S4). Thus, the CO₂ respired from roots and microbes could be reduced at high-level N input due to the decreased soil temperature, especially in cold regions where temperature is usually considered a limiting factor for living beings (Lloyd and Taylor 1994).

In grassland ecosystems, water availability is usually observed to constrain CO₂ flux with or without N additions (Harpole et al 2007, Xia et al 2009, Yan et al 2010). However, in our present experiment, we did not find any significant correlations of Rs, Ra and Rh with soil moisture along the N addition gradient (figures 3(e), (i), (s); figures 4(e), (i), (s)). This is likely because of the large moisture variation during both growing seasons (figure S5). Previous studies indicated that there might be a threshold of soil moisture in grasslands (8%–14% V/V%, Zhou et al 2007, Yan et al 2010), above which water is not the constraint of soil C process responses to climate change. Due to this point, it may be that, in aggregate, there were no detectable influences of the N-induced soil moisture changes on soil CO₂ fluxes since the soil moisture was above the critical level at most of our measurement times (figure S5). Nevertheless, as we mentioned above, precipitation-associated water changes are still very important in this alpine steppe because they regulate the seasonal dynamics and inter-annual variation of Rs and its components (figure 2).