ENVIRONMENT AND ECOLOGY / RESEARCH PAPER

 

Soil respiration across a disturbance gradient in sclerophyllous ecosystems in Central Chile

Respiración de suelos en un gradiente de perturbaciones en ecosistemas esclerófilos en Chile Central

 

Horacio E. Bown¹, Juan-Pablo Fuentes¹, Jorge F. Perez-Quezada^2,3, and Nicolás Franck^2,3

¹ Facultad de Ciencias Forestales y Conservación de la Naturaleza, Universidad de Chile. Casilla 9206, Santiago, Chile.
² Facultad de Ciencias Agronómicas, Universidad de Chile. Casilla 1004, Santiago, Chile.
³ Centro de Estudios de Zonas Áridas, Universidad de Chile. Casilla 129, Coquimbo, Chile.
Corresponding author: hbown@uchile.cl

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Abstract

Sclerophyllous shrubs and forests are predominant in semiarid Central Chile and have a long history of degradation by fire, cultivation, firewood extraction and grazing. The aim of this study was to compare the amount and environmental drivers of soil respiration across a disturbance gradient in sclerophyllous ecosystems in the National Reserve Roblería del Cobre de Loncha in Central Chile. In a north-facing toe slope, four disturbance conditions were identified: slightly (D1) and moderately disturbed (D2) sclerophyllous forest, (D3) strongly disturbed thorn scrub and (D4) most disturbed A. caven savanna. Twelve 25×25-m plots (625 m²) were distributed equally across D1, D2, D3 and D4. Soil respiration (R_s), soil temperature (T_s), volumetric water content (θ_v) and exchangeable nitrogen (N_s) were measured at six dates in each plot between August 2009 and May 2010. Additionally, T_s and θ_v were continuously recorded from July 2010 to August 2012 (30-minute intervals) in one plot per disturbance condition (i.e., 4 out of 12 plots). The values of R_s increased linearly with θ_v with similar slopes but different intercepts, which increased as the disturbance receded. Once soil water content was taken into account, R_s increased with T_s with the same slope but with a disturbance-dependent intercept. Additionally, the response of R_s to T_s was more pronounced as θ_v increased. The values of N_s were uncorrelated with R_s. The annual values of R_s were 4.4-fold greater in D1 (1,735 g C m^-2 yr^-1) compared with D4 (392 g C m^-2 yr^-1). Disturbance presumably decreased R_s by reducing the litter layer, soil organic matter, root biomass and soil water content, particularly in the hot-dry season. Under a predicted climate change scenario of a 40% decrease in rainfall and 4°C increase in air temperature by the year 2100, we found that annual R_s would be reduced on average by 28% compared with the current climate, with that reduction being more pronounced under more disturbed conditions, suggesting that less disturbed conditions would be more resistant to climate change, thus further justifying the restoration of these damaged ecosystems.

Key words: Acacia caven savanna, disturbance gradient, sclerophyllous forest, soil respiration, thorn scrub.

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Resumen

Los matorrales y bosques esclerófilos son la formación vegetacional dominante en Chile Central, existiendo una larga data de degradación producto del fuego, cultivos, extracción de leña y pastoreo. El objetivo del estudio fue comparar la respiración de suelos y los factores que la controlan a lo largo de un gradiente de perturbaciones en ecosistemas esclerófilos en la Reserva Nacional Roblería del Cobre de Loncha en Chile Central. En bajos de ladera en una exposición norte se identificaron cuatro grados de perturbación: bosques esclerófilos que fueron levemente- (D1) y moderadamente perturbados (D2), matorral espinoso fuertemente perturbado (D3) y sabana de A. caven completamente perturbada (D4). Se establecieron doce parcelas de 25×25 m (625 m²) distribuidas equitativamente en D1, D2, D3 and D4. La respiración de suelos (R_s), temperatura de suelos (T_s), contenido volumétrico de agua en el suelo (θ_v) y nitrógeno intercambiable (N_s) fueron medidos en todas las parcelas en seis fechas entre Agosto de 2009 y Mayo de 2010. Adicionalmente, T_s y θ_v fueron registrados de forma continua, desde Julio de 2010 hasta Agosto de 2012 (cada 30 minutos), en una parcela por nivel de perturbación (i.e. 4 de 12 parcelas). Los valores de R_s aumentaron linealmente con θ_v con similares pendientes pero diferentes interceptos que aumentaron en la medida que las perturbaciones disminuyeron. Una vez contabilizado el contenido de agua en el suelo, R_s aumentó con T_s con la misma pendiente pero con un intercepto que depende del nivel de perturbación. Adicionalmente la respuesta de R_s a T_s fue más pronunciada en la medida que θ_v aumentó. Los valores de N_s no se correlacionaron con R_s. Los valores acumulados de R_s fueron 4.4 mayores en D1 (1735 g C m^-2 yr^-1) comparado con D4 (392 g C m^-2 yr^-1). Las perturbaciones presumiblemente disminuyeron R_s mediado por reducciones en la capa de hojarasca, materia orgánica del suelo, biomasa de raíces y contenido de agua particularmente en la temporada seca y cálida. Bajo un escenario de cambio climático que implica una disminución de 40% de las precipitaciones y un aumento de 4°C en la temperatura del aire para el año 2100, encontramos que el R_s anual se reduciría en promedio en 28% comparado con el clima actual, con esta reducción siendo más pronunciada en las condiciones más perturbadas sugiriendo que las condiciones menos perturbadas serían más resistentes al cambio climático justificando aún más la restauración de estos ecosistemas.

Palabras clave: Bosques esclerófilos, gradiente de perturbaciones, matorrales espinosos, respiración de suelos, sabana de Acacia caven.

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Introduction

The total global emission of CO₂ from soils is the second largest flux (98±12 Pg C yr^-1) in the global carbon (C) cycle after photosynthesis (Raich and Potter, 1995; Raich and Schlesinger, 1992; Schlesinger and Andrews, 2000, Reichstein et al, 2003; Li et al, 2008; Bond-Lamberty and Thomson, 2010), accounting for approximately 25% of the global CO₂ exchange (IPCC, 2001). Soils also contain the largest C reservoir in the biosphere (~1,500 Pg C), approximately twice the atmospheric CO₂-C pool (IPCC, 2001; Jia et al, 2006), which implies that a more rapid oxidation of soil organic matter due to global warming may significantly increase the atmospheric CO₂ concentration (Raich and Potter, 1995; Davidson and Janssens, 2006). Hence, soil respiration (R_s) is an important regulator of climate change as well as a determinant of the global carbon balance (Heinmann and Reichstein, 2008).

Predicting R_s and understanding the drivers that underlie the seasonal and spatial variation of soil respiration are fundamental to predict ecosystem responses to climate change (Li et al, 2008, Raich and Schlesinger, 1992; Vargas et al, 2011a). R_s has been reported to differ across temporal and spatial scales (e.g., Jia et al, 2006; Li et al, 2008; Vargas et al., 2010) as a result of changes in soil temperature (Lloyd and Taylor, 1994; Subke and Bahn, 2010), soil moisture (Gaumont-Guay et al., 2006; Moyano et al, 2012), vegetation (Buchmann, 2000; Bahn et al, 2010), topography (Kang et al, 2003), soil texture (Dilustro et al., 2005; Pumpanen et al, 2008) and primary productivity (Bahn et al., 2008; Vargas et al, 2011b). Thus, better estimates of R_s at longer times and larger spatial scales would require both better understanding of its biotic and abiotic controls and a better spatial representation of R_s across different biomes (Vargas et al., 2011a).

Drylands cover approximately 40% of the world's land area as well as Chile's continental territory, and more than 2 billion and 11 million people, respectively, live in these areas (MEA, 2005; Benites et al, 1994; INE, 2013). A substantial reduction in the provision of ecosystem services of drylands is occurring as a result of water scarcity, land degradation and climate change (MEA, 2005). Global warming will affect arid lands through temperature increases and rainfall decrease across the world, with only a few exceptions (Loik et al, 2004; IPCC, 2007; Dai, 2010), leading to likely losses of ecosystem productivity and biodiversity (MEA, 2005).

Semiarid sclerophyllous (i.e., woody plants with small leathery evergreen leaves) shrublands and forests extend between latitudes 32-36° S (~345,000 ha) in Central Chile (Armesto et al., 2007, CONAF, 1999). Holmgreen (2002) argues that sclerophyllous forests and shrublands largely covered Central Chile in pre-Columbian times and were progressively replaced, primarily in the area between the Andes and the Coastal Ranges, by extensive savannas dominated by the invasive legume N-fixing tree Acacia caven, which was originally restricted to the Gran Chaco region in north-central Argentina. Currently, sclerophyllous ecosystems are usually restricted to dry slopes as isolated forest or shrub clumps (Holmgreen, 2002). Because most of the population lives in Central Chile, sclerophyllous ecosystems have suffered a long history of degradation by fire, cultivation, firewood extraction, and grazing.

The aim of this study was to examine environmental drivers controlling R_s across a land degradation gradient and to integrate R_s on an annual scale under current climate and climate change scenarios. Because R_s represents the second largest flux after photosynthesis in the global carbon cycle, this study is an important step towards estimating primary productivity as determined by land degradation for this understudied biome.

Materials and methods

Study site

The study was performed in the National Reserve 'Roblería del Cobre de Loncha' (34° 08' S, 71°03' W), located in the Coastal Range, approximately 80 km southwest of the city of Santiago in the Metropolitan region in Chile. The physiography of the National Reserve watershed (5,870 ha) is formed by non-continuous peaks cut by deep ravines and valleys, which largely determine the location of human settlements (UNDP, 2011). Parent materials are typically granitic, granodioritic and volcanic rocks (ODEPA, 1968; SERNAGEO -MIN, 1982). The climate is Mediterranean, dry and semi-arid, with a mean annual precipitation of 503 mm, water deficit of 956 mm and mean annual temperature of 14.9 °C. Summer droughts extend for 6-8 months typically from October to April (CONAF, 2008).

The studied site was located in a toe slope in a north-aspect position. Soils developed from colluvial materials that belong to the coarse-loamy, mixed, thermic Typic Xerochrepts family (Soil Survey Staff, 1999) and locally associated with the Quilamuta Series (CIREN, 1996). Soil textures varied from loamy clay in the more disturbed sites to loamy sand in the less disturbed sites.

The natural flora of the site is dominated by the tree sclerophyllous species Cryptocarya alba (Mol.) Looser. (Lauraceae), Quillaja saponaria Mol. (Quillajaceae), Lithraea caustica (Mol.) Hook. et Arn. (Anacardiaceae) and Peumus boldus Mol. (Monimiaceae), the invasive small N-fixing tree legume A. caven (Mol.) Mol. (Fabaceae) and the shrub species Colliguaja odorifera Mol. (Euphorbiaceae) and Retanilla trinervia (Gillies et Hook.) Hook. et Arn. (Rhamnaceae). These tree and shrub species are typical of the sclerophyllous forest, thorn scrub and A. caven savanna in Central Chile (Gajardo, 1994; Luebert and Pliscoff, 2006; Armesto et al, 2007).

Disturbance gradient

Twelve 25×25 m plots (625 m²) were distributed equally across four clearly different disturbance conditions (Figure 1), henceforth identified as D1, D2, D3 and D4, where D1 was the least-disturbed and D4 the most-disturbed condition ("D" stands for disturbance). Plots ranged in altitude between 300 and 800 m. The slightly disturbed sclerophyllous forest (D1) and the moderately disturbed sclerophyllous forest (D2) are dominated by the tree species C. alba, Q. saponaria and L. caustica, with a tree cover >75% (leaf area index, LAI~4.76 m²×m²) and 50-75% (LAI~3.26 m²×m²), respectively (Figure 1). In condition D1, approximately half of the trees are seed-regenerated, while the remaining are second growth-coppices perpetuated presumably by low intensity fire and firewood extraction prior to the creation of the National Reserve in 1996. Condition D2 is a second growth-coppice. The strongly disturbed thorn scrub (D3) has a sparse tree cover of sclerophyllous species (<15%), notably Q. saponaria (up to 16 m in height) but also C. alba, L. caustica and A. caven, with medium shrub cover (~ 50%) of primarily C. odorifera and the thorny R. trinervia of less than 4 m in height (LAI~2.86 m²×m², both shrub and tree cover) (Figure 1). The most-disturbed A. caven savanna (D4) is a xerophytic open woodland dominated by the invasive leguminous tree A. caven and emerging infrequent sclerophyllous trees of Q. saponaria, C. alba and L. caustica, with a dense herbaceous cover composed primarily of European annual herbs and grasses (e.g., slender wild oat, Avena barbata Pott ex Link) that are typically associated with grazing pastures (Armesto et al., 2007) (Figure 1).

Figure 1. Hypothetical model of the soil and vegetation disturbance of shrubland and sclerophyllous forests in Central Chile (based on Whisenant, 1999). The average leaf area index, LAI, (m2 m-2) measured using a ceptometer is shown for each category.

Plot measurements

Diameter at breast height (dbh) was measured for all shoots with a dbh >5 cm within each plot. Shoots were attributed to stools to determine the number of shoots per stool. Tree heights were measured for a random sample of 10 trees per plot. The leaf area index (LAI) of the woody plants, which is the total one-sided area of leaf tissue per unit of ground surface area (Bréda, 2003), was estimated using a ceptometer (AccuPAR LP-80, Decagon Devices, Pullman, WA, USA). Litter biomass was determined using three composite random samples of 30×30 cm per plot that were oven dried at 70 °C followed by recording of the dry mass. These measurements were taken during the summer of 2010.

Soil respiration measurements

Ten soil collars per plot made of polyvinyl chloride (100 mm inner diameter and 50 mm length) were randomly inserted into the soil in June 2009. Soil respiration (R_s) was measured in all collars within each plot using a closed chamber (100 mm inner diameter, Model SRC-1, PP Systems, Amesbury, MA, USA) connected to an infrared gas analyzer (Model EGM-4, PP Systems, Amesbury, MA, USA). Measurements were performed on rainless days between 10 am and 4 pm on the following dates: August 29, 2009 (winter), September 28, 2009 (spring), November 3, 2009 (spring), January 12, 2010 (summer), March 16, 2010 (summer) and May 10, 2010 (autumn). Soil temperature (T_s) was measured simultaneously to R_s to a depth of 10 cm using a digital thermometer (CheckTemp1, Hanna, USA). At each sampling date, four soil samples were randomly cored to a depth of 30 cm from each plot to determine the soil gravimetric water content (θ_g) and available nitrogen (N_s) (Bremner, 1965). The bulk density (r_b) was determined using the paraffin-sealed clod method (Blake, 1965). The volumetric water content (θ_v) was calculated as θ_v = r_b × θ_g.

Soil sampling

Composite soil samples (three per plot) were extracted using a hammer-driven soil core (5.4-cm diam.) sampler (Soilmoisture Equipment Corp.) at a 0-10-cm soil depth in August 2010. Total C and N contents were measured via dry combustion (Dumas method) using a total CNS analyzer (LECO Corp, USA). Particle size distribution was determined using the Hydrometer Method (Gee and Or, 2002).

Auto- and heterotrophic respiration

The values of R_s were partitioned for each disturbance condition into autotrophic (R_a; mostly roots and micorrhizae) and heterotrophic respiration (R_h; soil microbes, micro- and meso-fauna) using the y-intercept method (Kucera and Kirkham, 1971; Baggs, 2006; Kuzyakov, 2006). Briefly, this method fits a linear model of R_s versus root biomass, taking the y-intercept to be heterotrophic respiration (i.e., soil respiration in the absence of roots). Measurements were performed over a period of 12 days ending on July 27, 2011 (winter) when water was not limiting. Five points were randomly selected within each plot, measuring R_s prior to progressively coring and removing the soil to a 30-cm depth in the exact same positions in which the R_s values were measured using a 100-mm inner diameter and 40-cm length soil auger. Soil samples were sieved and washed to recover roots through flotation. Root samples were oven-dried at 70 °C, and the constant mass was recorded. The y-intercept of the linear relationship between R_s and root biomass (W_R) for each disturbance condition were considered R_h, while R_a was calculated as R_s - R_h.

Soil respiration on an annual basis

Soil moisture and temperature sensors (5-TM, Decagon Devices, USA) were installed at three soil depths (5, 15, 25 cm) in one plot per disturbance condition (i.e., 4 out of 12 plots) recording continuously at 30 min intervals (data logger EM-50, Decagon Devices, USA) for approximately two years starting in July 2010. Models of R_s to T_s and θ_v developed specifically in this study from discrete sampling were applied over the two-year series to determine the annual values of R_s under a current climate scenario. CONAMA (2006) predicted a temperature increase of 2-4 °C and rainfall decrease of up to 40% for Central Chile by the year 2100. We simulated R_s under a climate change scenario (CONAMA (2006)) by increasing T_s by 4 °C (a surrogate for an air temperature increase of 4 ° C) and decreasing θ_v by 40% (a surrogate for a rainfall decrease of 40%) over the recorded two-year climatic series.

Data analysis

All analyses were performed using R (R Development Core Team, 2010). Variables were tested for normality and homogeneity of variance, and transformations were made as necessary to meet the underlying statistical assumptions of the models used. A one-way analysis of variance (ANOVA) was used to test the primary effects of disturbance conditions on those vegetation and soil variables measured once at the plot level. A one-way ANOVA was also used to test the primary effects of disturbance conditions on R , T, 6 and V separately for each sampling date. A two-way ANOVA was used to test the primary effects of disturbance conditions and sampling date on the R_s, T_s, θ_v and available N. The responses of R to T_s, θ_v and N_s were fitted using linear and nonlinear models and by considering all sampling dates. An analysis of covariance was performed to test whether the slopes and intercepts of the linear relationship between R_s and W_R significantly differed between disturbance conditions.

Results

Vegetation and soil description

Most biometrical and soil variables exhibited significant differences regarding disturbance conditions (Table 1). The basal area was 12.4fold greater in D1 (31.1 m² ha^-1) compared with D4 (2.5 m² ha^-1), while D2 (23.8 m² ha^-1) and D3 (7.9 m² ha^-1) showed intermediate values between these two extremes. The average tree height was smallest in D4 (2.6 m), with increasing values observed for D3 (7.6 m), D2 (8.4 m) and D1 (9.9 m). The leaf area index was 0.12, 2.84, 3.26 and 4.76 m² m^-2 for the four conditions in decreasing order of disturbance (i.e., D4, D3, D2, D1). Stools (i.e., roots and stumps, which give rise to several shoots from dormant and adventitious buds) per hectare varied approximately six-fold when comparing D1 with D4 (1,611 vs. 240) (Table 1).

Table 1. Soil and vegetation variables across a disturbance gradient in the National Reserve Roblería del Cobre de Loncha in Central Chile.

Soil and vegetation variables are presented as the means (± 1 SE, n=3) for each disturbance condition. Soil respiration, soil water content, soil temperature and exchangeable nitrogen are presented as the means (± 1 SE, n=18) for each disturbance condition. The significance of the main effects of the sampling date (S) and disturbance condition (D) or the interaction between the sampling date and disturbance condition (S × D) are shown as the P range; ns: not significant; *: significant at P≤0.05; **: significant at P≤0.01; ***: significant at P≤0.001. Separation of the means was determined using a Tukey test when applicable. Different letters indicate significant differences at P≤0.05. The soil texture, bulk density, carbon and nitrogen contents were measured for the 0-10 cm soil depth, while exchangeable N and volumetric water content were measured for the 0-30 cm soil depth.

The physical and chemical properties of soils (0-10 cm depth) differed drastically between disturbance conditions. The most-disturbed D4 condition had a greater proportion of clay (38%) and smaller proportion of sand (25%) than the other disturbance conditions, while all conditions exhibited similar proportions of loam. Although not significantly, the bulk density tended to be greater in D4 (1.70 g cm^-3) compared with D1 (1.50 g cm^-3), while D2 (1.58 g cm^-3) and D3 (1.61 g cm^-3) showed intermediate values between these two extremes. Soil C measured 6.31, 5.49, 2.92 and 2.03% for conditions D1, D2, D3 and D4, respectively. Although not significantly, soil N appeared to be greater in D1 and D2 (0.45%) compared with D3 and D4 (0.23%). The soil C/N ratio did not differ significantly between conditions. Litter biomass also changed drastically across the disturbance gradient and was 8.4-fold greater in D1 (110 g dry matter m^-2) compared with D4 (13 g m^-2). Root biomass to a soil depth of 30 cm was approximately two-fold greater in D1 (5.6 kg dry matter m^-2) compared with D4 (2.4 kg m^-2) (Table 1, Figure 2a).

Figure 2. (a) Fine root biomass across disturbance conditions (July 2011), (b) the relationship between soil respiration and root biomass and (c) root respiration, total soil respiration and their ratio (numbers inside grey bars) across disturbance conditions. In (a) and (c), the values are presented as the means (± 1 SE) for each disturbance condition. The separation of means was determined using a Tukey test, when applicable. Different letters indicate significant differences at P≤0.05. In (b), the disturbance conditions are: D1; slightly disturbed sclerophyllous forest (closed circles); D2, moderately disturbed sclerophyllous forest (closed triangles); D3, strongly disturbed thorn scrub (open triangles); and D4, most disturbed Acacia caven savanna (open circles). The intercepts of the linear relationship between soil respiration and root biomass (heterotrophic respiration) in (b) were 1.778 (indicated as D4), 0.796 (indicated as D3), 2.758 (indicated as D2), and 2.044 (indicated as D1).

Soil respiration and potential drivers

The values of R_s, T_s and θ_v were strongly controlled by the effects of the season (F_5,48>25.9, P≤0.001) and disturbance condition (F_3,48>21.5, P≤0.001), while their interaction was relatively weak (F_15,48<4.0, P≤0.001) to not significant (F_15,48=1.3, P=0.25). Disturbance drastically reduced R_s by half, from 3.98 μmol CO₂ m^-2 s^-1 in the two least-disturbed conditions (D1, D2) compared with 1.96 μmol CO₂ m^-2 s^-1 in the two most-disturbed conditions (D3, D4) (Table 1). The values of θ_v slightly decreased with disturbance being, on average, 0.23, 0.22, 0.19 and 0.16 m³ m^-3 for D1, D2, D3 and D4, respectively (Table 1). The opposite occurred with T, with an average of 12.8, 15.8, 17.3 and 26.2 °C for conditions D1, D2, D3 and D4, respectively.

On a seasonal basis, R_s changed drastically being generally greater in winter (3.41 μmol CO₂ m^-2 s^-1) and spring (3.98 μmol CO₂ m^-2 s^-1) than summer (1.26 μmol CO₂ m^-2 s^-1) and autumn (2.46 μmol CO₂ m^-2 s^-1) (Figure 3). The values of θ_v also changed drastically with the season mimicking the values of R_s, being greater in winter (0.36 m³ m^-3) and falling in spring (0.18 m³ m^-3) and summer (0.09 m³ m^-3) to increase again in autumn (0.19 m³ m^-3) (Figure 3). The values of T_s followed the opposite trend with θ_v being lowest in winter (8.3 °C), increasing in spring (16.7 °C), rising abruptly in summer (29.0 °C) and decreasing in autumn (15.6 °C) (Figure 3).

Figure 3. Soil respiration, soil temperature and volumetric water content across disturbance conditions for representative sampling dates (4 out of 6). Values are presented as the means (± 1 SE, n=3) for each disturbance condition and season. The separation of means was determined using a Tukey test when applicable. The disturbance conditions are D1; slightly disturbed sclerophyllous forest; D2, moderately disturbed sclerophyllous forest; D3, strongly disturbed thorn scrub; and D4, most disturbed Acacia caven savanna. Different letters indicate significant differences at P≤0.05. The overall values of Rs, Ts and θv across disturbance conditions are presented as the means (±1 SE, n=12) centered in the upper part of each bar graph.

The values of soil exchangeable NO₃^--N, NH₄+-N and their sum were strongly influenced by the season (F_4,40>3.9, P≤0.01) and disturbance condition [but only for NO₃^--N (F_3,40=3.1, P=0.04)], while the season × disturbance interaction was insignificant (F_12,40<0.8, P>0.13). Soil exchangeable N (NO₃^- -N + NH₄+ -N) was greater in autumn (12.7 mg N kg^-1 dry soil) and winter (10.8 mg N kg^-1 dry soil) than summer (6.5 mg N kg^-1 dry soil) and spring (2.4 mg N kg^-1 dry soil). The same seasonal trend was observed for either ammonium or nitrate alone. Soil exchangeable NO₃^- -N was significantly greater under the disturbance condition D4 [dominated by the N-fixing leguminous tree A. caven (3.21 mg N kg^-1 dry soil)] compared with conditions D3 (3.07 mg N kg^-1 dry soil), D2 (2.26 mg N kg^-1 dry soil) and D1 (1.53 mg N kg^-1 dry soil) (Table 1).

Soil respiration model

Soil respiration increased linearly and significantly with θ_v consistently for all disturbance conditions (Overall Model, R =1.0462+9.5342θ_v, r² =0.25, P<0.001). A covariance analysis showed that adding disturbance conditions to the linear model contributed an additional 21% to explaining the total variance (Overall, r²=0.46, P≤0.001). The intercepts (F_3,64 = 7.61, P≤0.001) but not the slopes (F_3,64=0.84, P=0.48) of these linear relationships were significantly different between disturbance conditions (Figure 4). It is worth noting that intercepts increased as disturbance receded, i.e., the D4 condition exhibited the smallest intercept (0.391) compared with D3 (0.771), D2 (0.997), and D1 (3.332).

Figure 4. Relationship between soil respiration and soil volumetric water content across disturbance conditions. Each point is the average of 10 soil respiration measurements for each plot at each sampling date (3 plots per condition × 6 sampling dates = 18 points per condition). Disturbance conditions are: D1; slightly disturbed sclerophyllous forest; D2, moderately disturbed sclerophyllous forest; D3, strongly disturbed thorn scrub; and D4, completely disturbed Acacia caven savanna.

The relationship between R_s and T_s depended strongly on θ_v. In fact, T_s and θ_v were strongly autocorrelated (Pearson r = -0.74, P<0.001). However, the linear relationship between R_s and θ_v (r²=0.46, P≤0.001) was significantly enhanced when R_s was correlated with the product of T×θ_v (r²=0.59, P≤0.001). The intercepts (F_3,64=14.7, P≤0.001) but not the slopes (F_3,64=1.8, P=0.15) of these linear relationships were significantly influenced by disturbance conditions. Hence, the same slope (0.914) but different intercepts were used to represent the R_s versus T×θ_v relationship, i.e., R_s = -0.828 + 0.914 T×θ_v (D4); R_s= -0.608 + 0.914 T×θ_v (D3); R_s= 0.739 + 0.914 T×θ_v (D2); R_s= 2.108 + 0.914 T×θ_v (D1). The value" of the intercepts for these linear relationships can be related to disturbance, i.e., the smallest intercept was found for D4 (-0.828), compared with D3 (-0.608), D2 (0.739), and D1 (2.108).

An important implication of this model is that the responsiveness of R_s to T_s decreases as the soil θ_v diminishes, independent of the disturbance condition. This model is used below to scale R_s to an annual basis under current climate and climate change scenarios.

Available NO₃^- -N (Pearson r = -0.15, P=0.16), NH₄+ -N (Pearson r = - 0.02, P=0.84) and their sum (Pearson r = -0.08, P=0.46) were not significantly correlated with R_s and were therefore not considered in the model, which was exclusively explained by θ_v, T_s and disturbance conditions.

Separating autotrophic and heterotrophic respiration

The values of R_s increased with root biomass (W_r, kg m^-2) to 30 cm of soil depth (R_s = 1.826 + 0.482 W_r, r²=0.20, P≤0.001), and this relationship was significantly enhanced when we accounted for disturbance conditions (r²=0.42, P≤0.001) (Figure 2b). The intercepts (F_3,48=6.8, P<0.001) but not the slopes (F_3,52= 0.3, P=0.85) of the linear relationship between R_s and W_r were significantly influenced by disturbance conditions, i.e., 2.044, 2.758, 0.796 and 1.778 μmol CO₂ m^-2 s^-1 for conditions D1, D2, D3 and D4, respectively (Figure 2b). The fitted intercepts (assumed to be heterotrophic respiration) enabled us to determine the autotrophic respiration based on the total respiration.

Autotrophic (root) respiration was found to be three-fold greater in D1 (2.46 ± 0.44 μmol CO₂ m^-2 s^-1) compared with D4 (0.82 ± 0.25 μmol CO₂ m^-2 s^-1), while D2 (2.15 ± 0.51 μmol CO₂ m^-2 s^-1) and D3 (1.20 ± 0.32 μmol CO₂ m^-2 s^-1) exhibited intermediate values between these two extremes (Figure 2c). The ratio of the autotrophic to total soil respiration was smaller in condition D4 (0.32) compared with D3 (0.60), D2 (0.43), and D1 (0.54), with an overall average (± 1 SD) for the last three values of 0.48 ± 0.12.

Annual values of soil respiration

The modeled daily values of R_s closely followed the values of θ_v but also the T_s series (Figure 5). On an annual basis, the values of R_s were 4.4-fold greater in condition D1 (1,735 g C m^-2 yr^-1) compared with D4 (392 g C m^-2 yr^-1), while D3 (420 g C m^-2 yr^-1) and D2 (1,073 g C m^-2 yr^-1) showed intermediate values between these two extremes (Table 2).

Figure 5. Soil temperature, soil volumetric water content and modeled soil respiration across disturbance conditions for the period of July 2010-July 2012. Disturbance conditions are: D1: slightly disturbed sclerophyllous forest (black line), D2: moderately disturbed sclerophyllous forest (blue line), D3: strongly disturbed thorn scrub (green line), and D4: most disturbed Acacia caven savanna (red line).

Table 2. Modeled soil respiration for the periods from July 1, 2010-June 31, 2011 (year 1) and July 1, 2011-June 31, 2012 (year 2) across disturbance conditions in the National Reserve Roblería del Cobre de Loncha in Central Chile.

A climate change scenario for year 2100 predicting a 40% decrease in rainfall (simulated as a 40% decrease in volumetric water content) and a 4 °C increase in air temperature (simulated as a 4 °C increase in soil temperature) is also presented. Averages of soil respiration for a current (a) and a climate change scenario (b) and their ratio (b/a) are presented.

Under a climate change scenario predicting a 40% decrease in rainfall and a 4 °C increase in air temperature by the year 2100 (Table 2), we found that the annual R_s would be reduced by 28% on average compared with the current climate and that the reduction would be greater under more disturbed conditions (i.e., 11°% in D1 compared with 45% in D4). Therefore, the slightly disturbed condition proved to be more resistant to the climate change scenario.

Discussion

The modeled annual values of R_s ranged from 371 to 1,803 g C m^-2 yr¹ (Table 2). On average (± 1 SD), the values for this study (905 ± 591 g C m^-2 yr^-1) were 27% higher than those reported for Mediterranean woodlands and shrubs (713 ± 317 g C m^-2 yr¹) by Luo and Zhou (2006) but had confidence intervals that were largely overlapping. The annual values of R were 4.4-fold greater in the least-disturbed D1 condition compared with the most-disturbed D4 condition. Comparing the least- versus the most-disturbed conditions, disturbance induced a reduction in R_s arguably as a result of (1) diminished organic substrates in the litter layer and in the soil, which in turn reduced microbial, micro- and meso-fauna activity (heterotrophic respiration); (2) reduced root biomass and activity and C exudates below ground (autotrophic respiration); and (3) reduced soil water content in the most disturbed conditions, particularly in the dry-hot season.

In temperate forests, approximately 50% of R_s is heterotrophic respiration (R_h) generated by the activity of microbial populations that decompose plant debris and soil organic matter (Hanson et al. 2000; Rey et al., 2011; Saiz et al, 2007; Fuentes et al., 2013). Several studies have demonstrated that the absence of litter-humus layers can decrease R_s in the order of 25 to 30% (e.g., Luo and Zhou, 2006; Saiz et al., 2007). We found a nine-fold difference in litter biomass, 110 g m^-2 vs. 13 g m^-2, which likely contributed to the two-fold difference in R_s (4.46 vs. 2.13 μmol CO₂ m² s¹) when comparing the least - and the most-disturbed conditions (Table 1). Furthermore, a three-fold C concentration difference in the upper 10 cm (6.3% vs. 2.0%) between extremes in disturbance may as well have substantially contributed to differences in R_s. Soil microorganisms consume a range of substrates, from simple sugars contained in fresh residues and root exudates to complex humic acids in SOM, and because respiratory CO₂ release is linearly related to substrate availability (Luo and Zhou, 2006), it could be expected that soils richer in C may also exhibit greater microbial activity and hence soil respiration as occurred in our study.

The other ~50% of R_s is usually derived from the metabolic activity of the rhizosphere; this is termed autotrophic respiration (R_a) (Ryan and Law, 2005). Soil respiration increased as disturbance receded, and this can be partly attributed to heterotrophic respiration driven by soil and litter C substrates. However, we also found that R_s was strongly correlated with root biomass; root biomass increased as disturbance receded and therefore soil respiration was partly driven by root activity. It is now well accepted that the substrate supply from canopy photosynthesis exerts a strong effect on root and microbial respiration (Franck et al, 2011; Högberg et al, 2001; Luo and Zhou, 2006). Large differences in the leaf area index across disturbance conditions suggest that photosynthesis (and its integral, gross primary productivity) decreased in the series D1, D2, D3 and D4, which may have driven root activity and soil respiration in our study.

Temporal variations are known to be greater than spatial variations in R_s in natural ecosystems (Rey et al., 2011; Zhang et al., 2010), and this appears to be mostly explained by the temporal heterogeneity in soil water content in Mediterranean climate ecosystems (Reichstein et al., 2002). A correlation analysis confirmed that R_s was primarily driven by soil water content in our study, which appears to be a frequent pattern in arid and semiarid environments (Jia et al., 2006; Rey et al., 2011; Perez-Quezada et al, 2012).

Land degradation appears to commonly decrease soil water content in dry periods in semiarid environments (Rey et al., 2011); this appears to be partly explained by a lower canopy cover in more disturbed conditions that favor topsoil water loss, particularly during the dry- hot seasons (Breshears et al, 1998; Raz-Yaseef et al, 2012). The less disturbed forest ecosystems in our study also exhibited a protective litter layer that may decrease evaporative water loss, increase infiltration and decrease runoff, which more effectively conserves water in the soil.

Soil respiration was weakly but significantly correlated with soil temperature, and this appears to be common in semiarid environments (Rey et al., 2011; Perez-Quezada et al., 2012). Given that soil water is usually the limiting resource in semiarid environments, several authors argue that the response of soil respiration to soil temperature must depend on soil water availability (Jia et al, 2006; Rey et al., 2011). Recently, Zhang et al. (2010) found that soil water content enhances the response of soil respiration to temperature, as has also been observed in irrigated agro-ecosystems in arid zones (Franck et al., 2011). Our results confirm these findings. Using our fitted model of R_s to θ_v and T_s, we can deduce that for given θ_v values of 0.3, 0.2 and 0.1 m³ m^-3, the slopes of the R_s to T_s relationship would be 0.274, 0.183 and 0.091, respectively.

More N was available at the most disturbed condition under the N-fixing legume tree A. caven, which likely prevented us from observing a significant relationship between soil respiration and available N. Odum (1969) proposed that, in more disturbed conditions, the inorganic nutrients tend to be extrabiotic as opposed to intrabiotic in the less disturbed conditions; this corroborates the results of our study. N availability can play a key role in organic matter decomposition, microbial activity and potentially in a greater abundance of invasive species, which we observed in the most-disturbed condition. Plant litter decomposition is influenced by several factors, including its C/N ratio, the presence of recalcitrant compounds, and soil physical (e.g., particle size distribution) and chemical properties. However, soil respiration was unaffected by N availability, which was likely due to water rather than N driving most biological processes in these ecosystems.

One of the key questions regarding climate change is whether global warming will promote positive feedback between the global carbon cycle and the climate system that would, in turn, enhance global warming (Luo and Zhou, 2006). Current global estimates of soil respiration are in the range of 98 ± 12 Pg yr^-1 and are predicted to increase annually by -0.1 Pg; this increase is likely associated with air temperature increases (Bond-Lamberty and Thomson, 2010). CONAMA (2006) predicts temperature increases of up to 4 °C and rainfall decrease of up to 40% in Central Chile by the year 2100. Under this scenario, we predict that soil respiration will be reduced, not enhanced, in the studied ecosystems, although the net change will depend on the effect of temperature increase and rainfall decrease on other components of the carbon balance. This surprising result is primarily explained by soil water content controlling soil respiration to a greater extent than soil temperature. Annual soil respiration was reduced under a climate change scenario, and it was more pronounced in the most disturbed ecosystems, i.e., 11% in the least-disturbed D1 compared with 45% in the most-disturbed D4 conditions. Soil water content was markedly higher in the least-disturbed compared with the most-disturbed conditions under the current climate scenario; this would also likely occur under a potential climate change scenario. Therefore, less-disturbed ecosystems would be less affected by climate change than more-disturbed ecosystems due to their superior water conservation. Because better-conserved sclerophyllous ecosystems may better resist climate change, the restoration of disturbed sclerophyllous ecosystems may contribute to ameliorating the negative effects of climate change. We are aware that the estimation of R_s under a climate change scenario was performed using models of soil respiration that were developed using a current climate scenario. This scenario neglected the process of acclimation and is thus speculative, although we believe the direction of the change to be correct.

In conclusion, in the studied shrub and sclerophyllous ecosystems in Central Chile, disturbances reduced heterotrophic respiration by decreasing litter C and soil C and also decreased autotrophic respiration by reducing root activity. Disturbances decreased soil water content, particularly in the dry-hot season. Under a climate change scenario, annual soil respiration is expected to decrease, an effect that would be further enhanced by an anthropogenic disturbance. This effect further justifies the restoration of these damaged ecosystems.

Acknowledgements

During this work, the senior author was supported by the Comisión Nacional de Investigación Científica y Tecnológica (CONICYT) through the project FONDECYT N^o 1090259: "Disturbance mediated water and nutrient stresses regulate carbon assimilation and allocation in sclerophyllous forests in Central Chile: A process-based approach". Soil physical variables were provided by FONDECYT N^o 1090283 "Quality and fluxes of soil organic carbon as affected by anthropogenic perturbations of sclerophyllous vegetation of Central Chile". We thank Mr. Jorge Vega B. (Universidad de Chile), Mrs. Cristina Sáez N. (Universidad de Chile), Mr. Roberto Cerda R. (Forest Service CONAF) and Mr. Eric Campos (Universidad de Chile) for their kind advice and valuable technical skills. The experiments and measurements performed for this paper comply with the current laws of Chile.

 

References

Armesto, J.J., M.T.K. Arroyo, and L.F. Hinojosa. 2007. The mediterranean environment of Central Chile. In: Veblen, T.T.Y., R. Kenneth, and A.R. Orme (eds.). The physical geography of South America. Oxford University Press. p. 184-199.

Baggs, E. 2006. Partitioning the components of soil respiration: a research challenge. Plant and Soil 284:1-5.

Bahn, M., M. Rodeghiero, M. Anderson-Dunn, S. Dore, C. Gimeno, M. Drosler, M. Williams, C. Ammann, F. Berninger, C. Flechard, S. Jones, M. Balzarolo, S. Kumar, C. Newesely, T. Priwitzer, A. Raschi, R. Siegwolf, S. Susiluoto, J. Tenhunen, G. Wohlfahrt, and A. Cernusca. 2008. Soil respiration in European grasslands in relation to climate and assimilate supply. Ecosystems 11:1352-1367.

Bahn, M., M. Reichstein, E.A. Davidson, J. Grünzweig, M. Jung, M.S. Carbone, D. Epron, L. Misson, Y Nouvellon, O. Roupsard, K. Savage, S.E. Trumbore, C. Gimeno, J. Curiel Yuste, J. Tang, R. Vargas and I.A. Janssens. 2010. Soil respiration at mean annual temperature predicts annual total across vegetation types and biomes. Biogeosciences 7: 2147-2157.

Benites, J., D. Saintraint, and Y.K. Morimoto. 1994. Degradación de tierras y producción agrícola en Argentina, Bolivia, Brasil, Chile y Paraguay. In: Oficina Regional de la FAO para América Latina y el Caribe. Erosión de Suelos en América Latina. Santiago, Chile. p. 83-116.

Blake, G.R. 1965. Bulk Density. In: Black, C.A., D.D. Evans, J.L. White, L.E. Ensminger, and F.E. Clark (eds.). Methods of Soil Analysis: Part 1, Physical and Mineralogical Properties, Including Statistics of Measurement and Sampling. American Society of Agronomy, Madison, Wisconsin, USA. p. 374-390.

Bond-Lamberty, B., and Thomson, A. 2010. Temperature-associated increases in the global soil respiration record. Nature 464:579-582.

Bréda, N.J.J. 2003. Ground-based measurements of leaf area index: a review of methods, instruments and current controversies. Journal of Experimental Botany 54:2403-2471.

Bremner, J.M. 1965. Inorganic forms of nitrogen. In: Black, C.A., D.D. Evans, J.L. White, L.E. Ensminger, F.E. Clark (eds.). Methods of soil analysis: Part 2, Chemical and Microbiological properties. American Society of Agronomy. Madison, Wisconsin, USA. p. 1179-1237.

Breshears, D.D., J.W. Nyhan, C.E. Heil, and B.P. Wilcox. 1998. Effects of woody plants on microclimate in a semiarid woodland: soil temperature and evaporation in canopy and intercanopy patches. Int. J. Plant Sci. 159:1010-1017.

Buchmann, N. 2000. Biotic and abiotic factors controlling soil respiration in Picea abies stands. Soil Biol. Biochem. 32:1625-1635.

CIREN-Centro de Información en Recursos Naturales. 1996. Estudio agrológico VI Región. Descripción de suelos materiales y símbolos. Centro de Información en Recursos Naturales. Santiago, Chile. 570 pp.

CONAF-Corporación Nacional Forestal. 1999. Catastro y Evaluación de Recursos Vegetacionales Nativos de Chile. Proyecto CONAF-CONA-MA-BIRF. Santiago, Chile. 89 pp.

CONAF-Corporación Nacional Forestal. 2008. Plan de Manejo: Reserva Nacional Roblería del Cobre de Loncha. Ministerio de Agricultura, Corporación Nacional Forestal, Santiago, Chile. 183 p.

CONAMA-Comisión Nacional del Medio Ambiente. 2006. Estudio de variabilidad climática en Chile para el siglo XXI. Departamento de Geofísica, Facultad de Ciencias Físicas y Matemáticas, Universidad de Chile. Santiago, Chile. 71 pp.

Dai, A. 2010. Drought under global warming: a review. In: Wiley Interdisciplinary Reviews: Climate Change. John Wiley & Sons. p. 45-65.

Davidson, E.A., and I.A. Janssens. 2006. Temperature sensitivity of soil carbon decomposition and feedbacks to climate change. Nature 440: 165-73.

Dilustro, J., B. Collins, L. Duincan, and C. Crawford. 2005. Moisture and soil texture effects on soil CO₂ efflux components in southeastern mixed pine forests. For. Ecol. Manag. 204:85-95.

Franck N., J. Morales, D. Arancibia, V. García de Cortázar, J. Perez-Quezada, A. Zurita, and C. Pastenes. 2011. Seasonal fluctuations in Vitis vinifera L. root respiration in the field. New Phytologist 192: 939-951.

Fuentes J.P., H.E. Bown, J. Perez-Quezada and N. Franck. 2013. Litter Removal in a Sclerophyll Forest: Short- and Medium-Term Consequences for Soil Properties. SSSAJ. doi:10.2136/sssaj2013.03.0100

Gajardo, R. 1994. La vegetación natural de Chile: clasificación y distribución geográfica. Editorial Universitaria. Santiago, Chile. 165 pp.

Gaumont-Guay, D., B.T. Andrew, T.J. Griffis, A.G. Barr, K. Morgenstern, R.S. Jass, and Z. Nesic. 2006. Influence of temperature and drought on seasonal and interannual variation of soil, bole and ecosystem respiration in a boreal aspen stand. Agric. For. Meteorol. 140:203-219.

Gee, G.W., and D. Or. 2002. Particle-Size Analysis. In: Dane, J.H. and C.G. Topp (eds.). Methods of Soil Analysis: Part 4 Physical Methods. SSSA Book Series 5.4. Madison, USA. p. 255-289.

Hanson, P.J., N.T. Edwards, C.T. Garten, and J.A. Andrews. 2000. Separating root and soil microbial contributions to soil respiration: A review of methods and observations. Biogeochemistry 48:115-146.

Högberg P., A. Nordgren, N. Buchmann, A. Taylor, A. Ekblad, M. Högberg, G. Nyberg, M. Ottos-son-Löfvenius, and D. Read. 2001. Large-scale forest girdling shows that current photosynthesis drives soil respiration. Nature 411:789-792.

Holmgreen, M. 2002. Exotic herbivores as drivers of plant invasion and switch to ecosystem alternative states. Biological Invasions 4:25-33.

INE-Instituto Nacional de Estadísticas. 2013. Compendio Estadístico 2013. Instituto Nacional de Estadísticas. Santiago, Chile. 512 pp.

IPCC. 2001. Climate change 2001: the scientific basis, Intergovernmental Panel on Climate Change, IPCC Third Assessment Report - Climate Change 2001. Available online at: http://www.grida.no/climate/ipcc_tar/wg1/index.htm (Website accessed: May 26, 2013)

IPCC. 2007. Climate Change 2007: The Physical Science Basis. In: Solomon, S., D. Qin, M. Manning, Z. Chen, M. Marquis, K.B. Averyt, M. Tignor, and H.L. Miller (eds.). Contribution of Working Group I to the Fourth Assessment Report of the Intergovernmental Panel on Climate Change. Cambridge University Press, Cambridge, United Kingdom and New York, NY, USA. 996 pp. Available online at: http://www.ipcc.ch/publications_and_data/publications_ipcc_fourth_assessment_report_wg1_report_the_physical_science_basis.htm (Website accessed: May 24, 2013)

Jia, B., G. Zhou, Y. Wang, F. Wang, and X. Wang. 2006. Effects of temperature and soil water-content on soil respiration of grazed and ungrazed Leymus chinensis steppes, Inner Mongolia. Journal of Arid Environments 67:60-76.

Kang, S., S. Doh, D. Lee, VL. Jin, and J. Kimball 2003. Topographic and climatic controls on soil respiration in six temperate mixed-hardwood forest slopes, Korea. Global Change Biol. 9:1427-1437.

Kucera, C., and D. Kirkham 1971. Soil respiration studies in tallgrass prairie in Missouri. Ecology 52:912-915.

Kuzyakov, Y. 2006. Sources of CO₂ efflux from soil and review of partitioning methods. Soil Biology & Biochemistry 38:425-448.

Li, H.J., J.X. Yan, X.F. Yue, and M.B. Wang. 2008. Significance of soil temperature and moisture for soil respiration in a Chinese mountain area. Agricultural and Forest Meteorology 148:490-503.

Lloyd, J., and J.A. Taylor. 1994. On the temperature dependence of soil respiration. Functional Ecology 8:315-323.

Loik, M.E., D.D. Breshears, W.K. Lauenroth, and J. Belnap. 2004. A multi-scale perspective of water pulses in dryland ecosystems: climatology and ecohydrology of the western USA. Oecologia 141:269-81.

Luebert, F., and P. Pliscoff. 2006. Sinopsis Bioclimática y Vegetacional de Chile. Editorial Universitaria, Santiago, Chile. 296 pp.

Luo, Y. and X. Zhou. 2006. Soil Respiration and the Environment. Elsevier Academic Press. San Diego, California. 257 pp.

MEA-Millenium Ecosystem Assesment. 2005. Millenium Ecosystem Assesment: Ecosystems and Human Well-being: Desertification Synthesis, World Resources Institute, Washington, DC. 26 pp.

Merbold, L., W. Ziegler, M. Mukelabai, and W. Kutsch. 2011. Spatial and temporal variation of CO₂ efflux along a disturbance gradient in a miombo woodland in Western Zambia. Biogeo-sciences 8:147-164.

Moyano, F.E., N. Vasilyeva, L. Bouckaert, F. Cook, J. Craine, J. Curiel Yuste, A. Don, D. Epron, P. Formanek, A. Franzluebbers, U. Ilstedt, T. Kätterer, V. Orchard, M. Reichstein, A. Rey, L. Ruamps, J.-A. Subke, I.K. Thomsen, and C. Chenu. 2012. The moisture response of soil heterotrophic respiration: interaction with soil properties. Biogeosciences 9: 1173-1182.

ODEPA-Oficina de Estudios y Políticas Agrarias. 1968. Uso potencial de los suelos de Chile: estudio basado en el proyecto aerofotogramétrico OEA/Chile y otros antecedentes disponibles. Unidades de uso agrícola de los suelos de Chile. Plan de desarrollo agropecuario 1965-1980.

Odum, E.P. 1969. The strategy of ecosystem development. Science 164:262-270.

Perez-Quezada, J., H.E. Bown, J.P. Fuentes, F.A. Alfaro, and N. Franck. 2012. Effects of afforestation on soil respiration in an arid shrubland in Chile. Journal of Arid Environments 83:45-53.

Pumpanen, J., H. Ilvesniemi, L. Kulmala, E. Siivola, H. Laakso, C. Helenelund, M. Laakso, M. Uusimaa, P. Iisakkala, J. Räisänen, and P. Hari. 2008. Respiration in boreal forest soil as determined from carbon dioxide concentration profile. Soil Science Society of America Journal 72:1187-1196.

Raich, J.W., and C.S. Potter. 1995. Global patterns of carbon dioxide emissions from soils. Global Biogeochemical Cycles 9:23-36.

Raich, J.W., and W.H. Schlesinger. 1992. The global carbon dioxide flux in soil respiration and its relationship to vegetation and climate. Tellus 44:81-99.

Raz-Yaseef, N., D. Yakira, G. Schiller, and S. Cohen. 2012. Dynamics of evapotranspiration partitioning in a semi-arid forest as affected by temporal rainfall patterns. Agricultural and Forest Meteorology 157:77- 85.

Reichstein, M., A. Rey, A. Freibauer, J. Tenhunen, R. Valentini, J. Banza, P. Casals,Y. Cheng, J.M. Grünzweig, J. Irvine, R. Joffre, B.E. Law, D. Loustau, F. Miglietta, W. Oechel, J. Ourcival, J.S. Pereira, A. Peressotti, F. Ponti, Y. Qi, S. Rambal, M. Rayment, J. Romanya, F. Rossi, V. Tedeschi, G.Tirone, M. Xu, and D. Yakir. 2003. Modeling temporal and large-scale spatial variability of soil respiration from soil water availability, temperature and vegetation productivity indices. Global Biogeochemical Cycles 17(4). N° 1104.

Reichstein, M., J. Tenhunen, O. Roupsard, J. Ourcival, S. Rambal, S. Dore, and R. Valentini. 2002. Ecosystem respiration in two Mediterranean evergreen Holm Oak forests: drought effects and decomposition dynamics. Functional Ecology 16:27-39.

Rey, A., E. Pegoraro, C. Oyonarte, A. Were, P. Escribano, and J. Raimundo. 2011. Impact of land degradation on soil respiration in a steppe (Stipa tenacissima L.) semi-arid ecosystem in the SE of Spain. Soil Biology & Biochemistry 43:393-403.

Ryan, M.G., and B.E. Law. 2005. Interpreting, measuring, and modeling soil respiration. Biogeochemistry 73:3-27.

Saiz, G., K. Black, B. Reidy, S. Lopez, and E.P. Farrell. 2007. Assessment of soil CO₂ efflux and its components using a process-based model in a young temperate forest site. Geoderma 139:79-89.

Schlesinger, W.H., and J.A. Andrews. 2000. Soil respiration and the global carbon cycle. Biogeochemistry 48:7-20.

SERNAGEOMIN-Servicio Nacional de Geología y Minería. 1982. Mapa Geológico de Chile. SERNAGEOMIN, Ministerio de Minería. Santiago, Chile.

Soil Survey Staff. 1999. Soil taxonomy: A basic system of soil classification for making and interpreting soil surveys Ed. U.N.R.C. Service. US Government Printing Office, Washington DC. 871 pp.

Subke, J.A., and M. Bahn. 2010. On the 'temperature sensitivity' of soil respiration: Can we use the immeasurable to predict the unknown? Soil Biol. Biochem. 42:1653-1656.

UNDP-United Nations Development Programme. 2011. Biodiversity Conservation in Altos de Cantillana, Chile. In: UNDP Project Document. Santiago, Chile. 89 pp.

Vargas R, D.D. Baldocchi, M.F. Allen, M. Bahn, T.A. Black, S.L. Collins, J.C. Yuste, T. Hirano, R.S. Jassal , J. Pumpanen, and J. Tang. 2010. Looking deeper into the soil: biophysical controls and seasonal lags of soil CO₂ production and efflux. Ecological Applications 20:1569-1582.

Vargas, R., M.S. Carbone, M. Reichstein, and D.D. Baldocchi. 2011a. Frontiers and challenges in soil respiration research: from measurements to model-data integration. Biogeochemistry 102:113.

Vargas R., D.D. Baldocchi, M. Bahn, P.J. Hanson, K.P. Hosman, L. Kulmala, J. Pumpanen, and B. Yang. 2011b. On the multi-temporal correlation between photosynthesis and soil CO2 efflux: reconciling lags and observations. New Phytologist 191: 1006-17.

Whisenant, S.G. 1999. Repairing Damaged Wild-lands: A Process-Orientated, Landscape-Scale Approach. Cambridge University Press. New York, USA. 309 pp.

Zhang, L., Y. Chen, R. Zhao, and W. Li. 2010. Significance of temperature and soil water content on soil respiration in three desert ecosystems in Northwest China. Journal of Arid Environments 74:1200-1211.

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Received June 26, 2013
Accepted March 6, 2014