Precipitation drives interannual variation in summer soil respiration in a Mediterranean-climate, mixed-conifer forest

University of California at Santa Cruz Department of Environmental Studies 1156 High Street Santa Cruz CA 95060 USA
Climatic Change (Impact Factor: 3.43). 01/2008; 92(1):109-122. DOI: 10.1007/s10584-008-9475-0


Predictions of future climate change rely on models of how both environmental conditions and disturbance impact carbon cycling
at various temporal and spatial scales. Few multi-year studies, however, have examined how carbon efflux is affected by the
interaction of disturbance and interannual climate variation. We measured daytime soil respiration (R
s) over five summers (June–September) in a Sierra Nevada mixed-conifer forest on undisturbed plots and plots manipulated with
thinning, burning and their combination. We compared mean summer R
s by year with seasonal precipitation. On undisturbed plots we found that winter precipitation (PPTw) explained between 77–96% of interannual variability in summer R
s. In contrast, spring and summer precipitation had no significant effect on summer R
s. PPTw is an important influence on summer R
s in the Sierra Nevada because over 80% of annual precipitation falls as snow between October and April, thus greatly influencing
the soil water conditions during the following growing season. Thinning and burning disrupted the relationship between PPTw and Rs, possibly because of significant increases in soil moisture and temperature as tree density and canopy cover decreased. Our
findings suggest that R
s in some moisture-limited ecosystems may be significantly influenced by annual snowpack and that management practices which
reduce tree densities and soil moisture stress may offset, at least temporarily, the effect of predicted decreases in Sierran
snowpack on R

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Available from: Jiquan Chen, Oct 08, 2015
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    • "Seasonal patterns of R S have been attributed to soil temperature [5] [18], soil moisture [10] [19], precipitation, productivity [20], or combinations of these factors [11]. Inter-annual variation of R S is usually controlled by productivity [21], soil water condition [22], or precipitation amount [23] and pattern [10]. Therefore, sampling schedule (in terms of both frequency and pattern) that captures these factors is important for adequately capturing the temporal variation of R S [8] [20] and estimating annual R S . "
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    ABSTRACT: Optimizing a manual measurement schedule (both frequency and pattern) for estimating annual soil respiration (RS) is an important but unresolved issue. We hypothesized that (i) an optimal sampling setup can be found to obtain a reliable annual RS, and (ii) if the desired outcome is a multi-year mean annual RS, a lower sampling frequency might be adequate. Here we explored these issues using a three-year chamber-based dataset, with a sampling frequency of twice per week (defined as control), in an exotic slash pine (Pinus elliottii Englem.) plantation in subtropical China. The results showed that RS during 9:00–11:00 a.m. represented diurnal mean RS well. In order to obtain an annual RS as reliable as the control (deviation within ±5%), the optimal measurement strategy is a biweekly sampling across a year and not a trade-off sampling pattern (monthly sampling combined with weekly sampling depending on the seasons). Furthermore, despite an obvious inter-annual variability in RS (548.4–757.5 g C m−2 year−1, CV = 16.3%), a monthly sampling was sufficient to obtain an unbiased multi-year mean annual RS (deviation within ±5%). Such findings are useful when easy looking for estimates of annual ecosystem carbon budgets. However, the generality needs to be examined in other ecosystems.
    European Journal of Soil Biology 09/2012; 52:41–47. DOI:10.1016/j.ejsobi.2012.06.002 · 1.72 Impact Factor
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    • "Consequently, temperature is still regarded as the key factor for predicting soil respiration because it directly controls plant and microorganism metabolisms on a daily time scale and is indirectly related to the seasonal supply of photosynthesis-derived substrate (Ma and others 2004; Campbell and Law 2005). Timber harvest activities can influence forest soil respiration by altering soil carbon input (Johnson 1992; Johnson and Curtis 2001; Li and others 2007; Jandl and others 2007), organic matter in the soil (Mallik and Hu 1997), forest structure and microclimate (Chen and others 1999; Xu and others 2002), microbial biomass and microorganism community structure (Ponder and Tadros 2002; Fraterrigo and others 2006; Chatterjee and others 2008), litter depth (Concilio and others 2005; DeForest and others 2009), and root distribution and biomass (Henderson 2007). Most previous soil respiration studies have addressed the effects of clearcutting (Weber 1990; Striegl and Wickland 1998) or thinning (Ma and others 2004; Tang and others 2005), whereas comparisons of both silvicultural strategies in the same forest type are rare. "
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    ABSTRACT: We investigated the variability of soil respiration and several potential regulatory factors and modeled their interrelationships from May to August over a 5-year period in oak forests subjected to alternative harvesting treatments as part of the Missouri Ozark Forest Ecosystem Project (MOFEP). Treatments included even-aged management (EAM), uneven-aged management (UAM), and no-harvest management (NHM) and were implemented 7–8years prior to this study. Summer mean soil respiration did not differ among the treatments, possibly because of changes in treatment differences in the separate months and years that tended to cancel each other out when averaged. Summer mean soil respiration and soil moisture tended to be higher in wet years (2004, 2006, and 2008) and lower in dry years (2005 and 2007) in EAM and UAM than in NHM. Summer precipitation was assumed to be the primary driver of variability in summer mean soil respiration through its control on soil moisture and the normalized difference vegetation index (NDVI) in the harvested forests. Nonlinear models using soil temperature, soil moisture and day-of-the-year (DOY) were used to predict within-summer soil respiration for all the treatments. A sensitivity analysis of the model using 30min interval data suggested that soil respiration was more sensitive to soil moisture in the EAM and UAM treatments than in NHM. We also found a change in the soil respiration–soil temperature relationship in the summer for all the treatments. Simulated data sets that removed the covariance structure between soil temperature and moisture suggested that the change in the respiration–temperature relationship resulted from the combined effect of moisture stress and low temperature sensitivity at high temperatures during July and August. Simulations also showed the effect of moisture stress to be more limiting to soil respiration in the harvested forests than in the control at high temperatures, even resulting in a negative relationship at high temperatures. Keywordssoil respiration–soil moisture–temporal variability–precipitation–forest management–Missouri Ozark Forest Ecosystem Project (MOFEP)–NDVI
    Ecosystems 12/2011; 14(8):1310-1327. DOI:10.1007/s10021-011-9482-2 · 3.94 Impact Factor
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    • "As the crop residues in the G plot surface favor lower temperatures and higher soil moisture as, for instance, on day 195, T soil was more than 3 8C cooler and M soil was 10% higher in G than in the SB plot (Fig. 2b and c). Consequently, as temporal variability of FCO2 is governed by the changes in T soil and M soil (Xu and Qi, 2001; Tedeschi et al., 2006; Kosugi et al., 2007; Ohashi and Gyokusen, 2007; Concilio et al., 2009), the G plot's lower FCO2 and its lower CV value are certainly related to the surface residues, especially during the first weeks of our study. "
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    ABSTRACT: Soil management causes changes in physical, chemical, and biological properties that consequently affect soil CO2 emission (FCO2). Here, we studied the soil carbon dynamics in areas with sugarcane production in southern Brazil under two different sugarcane management systems: green (G), consisting of mechanized harvesting that produces a large amount of crop residues left on the soil surface, and slash-and-burn (SB), in which the residues are burned before manual harvest, leaving no residues on the soil surface. The study was conducted during the period after harvest in two side-by-side grids installed in adjacent areas, having 60 points each. The aim was to characterize the temporal and spatial variability of FCO2, and its relation to soil temperature and soil moisture, in a red latosol (Oxisol) where G and SB management systems have been recently used. Mean FCO2 emission was 39% higher in the SB plot (2.87μmolm−2s−1) when compared to the G plot (2.06μmolm−2s−1) throughout the 70-day period after harvest. A quadratic equation of emissions versus soil moisture was able to explain 73% and 50% of temporal variability of FCO2 in SB and G, respectively. This seems to relate to the sensitivity of FCO2 to precipitation events, which caused a significant increase in SB emissions but not in G-managed area emissions. FCO2 semivariogram models were mostly exponential in both areas, ranging from 72.6 to 73.8m and 63.0 to 64.7m for G and SB, respectively. These results indicate that the G management system results in more homogeneous FCO2 when spatial and temporal variability are considered. The spatial variability analysis of soil temperature and soil moisture indicates that those parameters do not adequately explain the changes in spatial variability of FCO2, but emission maps are clearly more homogeneous after a drought period when no rain has occurred, in both sites.
    Soil and Tillage Research 11/2009; 105(2):275-282. DOI:10.1016/j.still.2009.09.008 · 2.62 Impact Factor
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