simulate how dryland soil respiration (Rs) and soil C pool size responded to precipitation ... soil respiration and C pool dynamics at rainfall event, seasonal and ...
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JOURNAL OF GEOPHYSICAL RESEARCH, VOL. 113, G03024, doi:10.1029/2008JG000685, 2008
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Effects of changing precipitation regimes on dryland soil respiration and C pool dynamics at rainfall event, seasonal and interannual scales Weijun Shen,1,2 G. Darrel Jenerette,3 Dafeng Hui,4 Richard P. Phillips,5 and Hai Ren1 Received 26 January 2008; revised 27 March 2008; accepted 22 April 2008; published 21 August 2008.
[1] Predicted precipitation regime changes in arid ecosystems have the potential to alter
soil C balance, but the influence of changes in different aspects of precipitation (amount, seasonality, and intensity) and the factors contributing to such effects are poorly understood. We used a process-based ecosystem model (PALS) that was modified, parameterized, and evaluated for a Mojave Desert ecosystem in the southwestern US to simulate how dryland soil respiration (Rs) and soil C pool size responded to precipitation changes at multiple temporal scales. The effects of changing precipitation on Rs were largely mediated by the contrasting respiratory response of plants (Ra) and soil microbes (Rh) and confounded by predrought duration, season, soil temperature, plant phenology, and substrate availability. Increases in precipitation amount stimulated Rs and increased the contribution of Ra to Rs, whereas reductions in summer rainfall and strong increases in rainfall event size reduced total Rs and decreased the contribution of Ra to Rs. Increases in annual rainfall and decreases in summer rainfall benefited dryland soil C sequestration, whereas strong increases in rainfall event size resulted in a loss of soil C, with labile soil C pools being more responsive to precipitation regime changes than recalcitrant C pools at a decadal scale. These simulation results implied that dryland soils may act as C sinks with increased precipitation amount or C sources with decreased precipitation amount, but the strength of the sink/source may be mediated by accompanying shifts in rainfall seasonality and event size distribution. Citation: Shen, W., G. D. Jenerette, D. Hui, R. P. Phillips, and H. Ren (2008), Effects of changing precipitation regimes on dryland soil respiration and C pool dynamics at rainfall event, seasonal and interannual scales, J. Geophys. Res., 113, G03024, doi:10.1029/2008JG000685.
1. Introduction [2] Soil respiration (Rs) is a primary pathway through which organic carbon (C) is released into the atmosphere. Rs is influenced by a variety of abiotic and biotic factors, such as soil temperature, moisture, atmospheric [CO2], substrate quality and availability, vegetation and microbial community structure, and land-use and disturbance regimes [Rustad et al., 2000; Raich and Tufekcioglu, 2000; Hui and Luo, 2004; Carrasco et al., 2006; Davidson and Janssens, 2006]. Although temperature is often considered the most important factor controlling this flux, other factors such as
1 South China Botanical Garden, Chinese Academy of Sciences, Guangzhou, China. 2 Nicholas School of the Environment and Earth Sciences, Duke University, Durham, North Carolina, USA. 3 Department of Botany and Plant Sciences, University of California Riverside, Riverside, California, USA. 4 Department of Biological Sciences, Tennessee State University, Nashville, Tennessee, USA. 5 Department of Biology, Duke University, Durham, North Carolina, USA.
soil moisture may be of greater importance in water-limited ecosystems [Davidson et al., 1998; Conant et al., 2004; Jenerette and Lal, 2005; Harper et al., 2005; Borken et al., 2006]. Dry lands, which include arid and semiarid lands and occupy 41% of the global terrestrial surface [Reynolds et al., 2007], store about 241 Pg or 15.5% of world’s total of 1550 Pg organic C to 1-meter [Lal, 2004] and a large amount of inorganic carbon [Schlesinger, 1985]. Compared to temperate forests containing 104– 155 Pg of soil organic C [Taylor and Lloyd, 1992], the response of dryland ecosystems to global environmental changes have received less attention and are poorly understood [Conant et al., 2000; Huxman et al., 2004; McLain and Martens, 2006]. With the large extent and the great amount of soil C stored, dryland ecosystems may play an important role in terrestrial C balance and feedbacks to climate change [Lal, 2004]. [3] Global and regional precipitation regimes are likely to change because of warming-induced alterations in global air circulation and hydrologic cycling patterns. Over the 20th century, precipitation has increased by 7 – 12% in the middle and high latitudes of the northern hemisphere, especially during autumn and winter [IPCC, 2001]. Across the US, precipitation in the last century increased by about 5 – 10%, reflected primarily in the number of heavy and extreme
Copyright 2008 by the American Geophysical Union. 0148-0227/08/2008JG000685$09.00
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rainfall events [Karl and Knight, 1998; Hulme and Sheard, 1999]. During this century, a 7% increase in the global mean precipitation is projected by general circulation models (GCMs), especially in the tropics and at middle and high latitudes [Solomon et al., 2007]. Along with increases in precipitation amount, the intensity of precipitation events and the frequency of extreme events are also expected to increase [Easterling et al., 2000; Solomon et al., 2007]. Seasonality of precipitation may also change, as winter rainfalls increase while summer rainfalls decrease [Magana et al., 1997; Kalvova and Nemesova, 1997]. While many researches have been done to understand the effects of elevated temperature and atmospheric [CO2], few have focused on how the predicted precipitation regime changes might affect terrestrial ecosystems [Weltzin et al., 2003]. [4] In dry lands, ecosystem processes such as Rs and primary production are controlled by sporadic rainfall events; hence, these ecosystems are predicted to be highly responsive to predicted changes in future precipitation regimes [Huxman et al., 2004]. However, the response of dry lands to changes in precipitation regimes is unclear as drying of soils (or drought) may reduce Rs, whereas wetting soils may increase Rs [Orchard and Cook, 1983; Skopp et al., 1990; Borken et al., 1999, 2003, 2006; Davidson et al., 1998; Davidson and Janssens, 2006; Cisneros-Dozal et al., 2007]. The components of Rs (i.e., root respiration Ra and microbial respiration Rh) may also be differentially affected by precipitation pulse size and timing; microbial respiration may respond to very small or moderate rainfall events, while photosynthetic activity of plants that is related to root respiration generally increases following relatively large events or a series of small ones [Huxman et al., 2004]. This suggests that Rs may be influenced not only by the amount of precipitation, but by the seasonality and intensity of precipitation. However, there have been relatively few studies on the effects of the seasonality and intensity of precipitation on Rs [but see Borken et al., 1999; McLain and Martens, 2006; Potts et al., 2006], and no studies to our knowledge, on the combined effects of precipitation amount, seasonality and intensity on Rs. Moreover, most field studies have lasted only a couple of growing seasons, and thus are likely to be less effective at capturing the large temporal variation in the amount and seasonality of precipitation in dryland regions. Furthermore, because of the large costs associated with doing precipitation manipulation experiments, extensive model experiments can help provide explicit predictions requiring further field studies [Zavaleta et al., 2003; Zhou et al., 2006]. [5] The objective of this study was to analyze both the combined and individual effects of changes in precipitation amount, seasonality (seasonal distribution and seasonal timing), and intensity (rainfall event size distribution) on Rs using a process-based modeling approach. Specifically, we used the modified Patch Arid Land Simulator (PALS) model to address the following questions: (1) How will dryland Rs respond to alterations in the amount of precipitation, as well as the seasonality and intensity of precipitation? (2) How will the responsive behaviors differ between the autotrophic and heterotrophic components of Rs? (3) How will the C source-sink relations of different compartments of soil C pools (e.g., litter, root biomass, and
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organic C in mineral soil) change in response to precipitation regime changes?
2. Methods and Materials 2.1. Site Description [6] This modeling research is based on data gathered at the Nevada Desert FACE Facility (NDFF) on the Nevada Test Site (NTS), 15 km north of Mercury, Nevada (36°490-N, 155°550-W; elevation 968 m). The mean annual temperature (MAT) is 21°C at the NDFF, ranging from 19°C to 48°C [Jordan et al., 1999]. The annual average precipitation (MAP) is 141.2 mm. Soils at the NDFF site are Aridosols derived from calcareous alluvium with textures ranging from loamy sands in the upper layers (0 – 16 cm) to coarse sands in the deep layers [Jordan et al., 1999]. Vegetation at the NDFF is typical of the Mojave Desert, and consists of perennial and deciduous shrubs, grasses and forbs, as well as annual grasses. 2.2. Model Description and Parameterization [7] PALS is a processes-based ecosystem model developed for the three North American warm deserts (Chihuahuan, Mojave, and Sonoran) [Kemp et al., 1997, 2003; Reynolds et al., 2000, 2004; Gao and Reynolds, 2003; Shen et al., 2005, 2008]. It simulates Carbon (C), Nitrogen (N), and water (H2O) dynamics of desert ecosystems in a daily time step. The model consists of four interacting modules: (1) atmospheric environment and surface energy budget, (2) soil water distribution and water cycling, (3) C/N cycling in the plant-soil-atmosphere system, and (4) phenology, physiology, and growth of plant functional types (FTs) [Reynolds et al., 2004; Shen et al., 2005]. Seven plant functional types were built in PALS to represent the Mojave Desert shrubland ecosystem for this study, including evergreen shrubs (C3), deciduous shrubs (C3), C3 and C4 perennial grasses, forbs (C3), and native and exotic annual grasses (C3). The energy budget and plant production modules had been described in detail in previous studies [Gao and Reynolds, 2003; Kemp et al., 1997, 2003; Reynolds et al., 2000, 2004; Shen et al., 2005], here we only focus on describing the two modules closely related to the Rs, i.e., the water cycling module that relates precipitation (Ppt) to soil water content (SWC) and the nutrient cycling module that relates SWC to soil respiration. [8] The water cycling module simulates daily plant transpiration, soil evaporation, and soil water content and movement in six layers (the upper two layers are 10 cm thick, the rest 20 cm). Soil water content is a function of rainfall, soil texture, and evapotranspiration processes [Kemp et al., 1997; Reynolds et al., 2000, 2004]. Water recharge of each layer is the balance between water holding capacity of the layer, the amount of water that percolates out of the upper layer, and previous water content of the layer. Water is removed from the top two layers by evaporation and from all the layers by transpiration (see Kemp et al. [1997] for the calculations of evaporation and transpiration). [9] Soil respiration is simulated separately as autotrophic respiration (Ra) and heterotrophic respiration (Rh). In the old versions of PALS, Ra was calculated as a fixed fraction of photosynthetically assimilated C [see Shen et al., 2005]. For this study, Ra or root respiration is further distinguished
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as growth (Rg) and maintenance respiration (Rm), which are simulated by using the scheme described by Thornley and Cannell [2000], i.e., a maintenance tax (Rm) is subtracted from photosynthetic assimilation rate (A, g C m2 day1) and the excess (Ex, =A-Rm) is used for growth with an efficiency Yg (also called growth yield) [see Amthor, 2000]. Total root Rg (in g C m2 day1) is the sum of those of the 7 plant FTs: Rg ¼
7 X
Ex;j ra;j
j¼1
1 Yg;j Yg;j
ð1Þ
where j represents different plant FTs, ra is the allocation ratio to roots, ra = 0.35, 0.30, 0.1, 0.08, 0.2, 0.25, 0.25 for evergreen shrubs, deciduous shrubs, C4-perennial grasses, C3-perennial grasses, forbs, native annuals, and exotic annuals, respectively [Reynolds et al., 2000; Shen et al., 2005]; Yg is the growth yield of roots, Yg = 0.80 is used for all the seven plant functional types [Amthor, 2000]. [10] Rm (g C m2 day1) is the product of root biomass (Br, g dry matter (DM) m2), basal maintenance respiration at the reference temperature of 20°C (R0m, g C g1 dry matter (DM) day1), and three modifiers (unitless) that account for the effects of root temperature ( f (Tr)), N content ( f (N)), and plant water potential ( f (y)) on Rm. Total Rm is a sum of those of the 7 plant FTs (j): Rm ¼
7 X
Br;j R0m;j f ðTr Þ f Nj f y j
mineral soils. The detailed description of litter and SOM decomposition is given by Kemp et al. [2003] and Shen et i al. [2005]. The rates of soil respiration (dC dt ) associated with the decomposition of these pools are calculated using the following equation: dCi ¼ Fi Ki f ðTs Þ f ðWs Þ Ci dt
f ðWs Þ ¼
ð3Þ
where ql(=0.067°C1) and qh(=0.830°C1) are the parameters regulating low- and high-temperature responses, respectively [Hanan et al., 1996]; root temperature, Tr, is assumed to be equal to the average soil temperature (Ts) of the top 5 layers. [11] The water-effect scalar, f (y) is defined as:
f ðy Þ ¼
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