Effects of grazing exclusion on soil organic carbon: Hillslope and soil profile results (an Australian example)

Journal Pre-proof Effects of grazing exclusion on soil organic carbon: Hillslope and soil profile results (an Australian example)

G.R. Hancock, Mitchell Vallely PII:

S0048-9697(19)35839-5

DOI:

https://doi.org/10.1016/j.scitotenv.2019.135844

Reference:

STOTEN 135844

To appear in:

Science of the Total Environment

Received date:

30 May 2019

Revised date:

28 November 2019

Accepted date:

28 November 2019

Please cite this article as: G.R. Hancock and M. Vallely, Effects of grazing exclusion on soil organic carbon: Hillslope and soil profile results (an Australian example), Science of the Total Environment (2018), https://doi.org/10.1016/j.scitotenv.2019.135844

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© 2018 Published by Elsevier.

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Effects of grazing exclusion on soil organic carbon: hillslope and soil profile results (an Australian example)

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GR Hancock1, 2, Mitchell Vallely1

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1 Corresponding author 2 School of Environmental and Life Sciences, Earth Science Building, The University of Newcastle, Callaghan, New South Wales, 2308, Australia. email [email protected]

Submitted to: Science of the Total Environment

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Filename: Stanley-Exclusion_area-rev2 Last modified: 26 November 2019

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Journal Pre-proof Abstract Soil organic carbon (SOC) is an essential component of the soil-landscape system. It is well recognised that SOC can reduce under some agricultural management practices. In recent years a concerted effort has been undertaken to increase SOC by employing different landscape management practices. Here we compare SOC in a grazing environment to that of an area where cattle have been excluded for over ten years using both a hillslope and whole of soil profile sampling strategy. Surface SOC concentrations (determined by cores) were

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significantly higher inside the exclusion area when compared to that outside demonstrating a

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rapid increase in SOC. Whole soil profile (to bedrock) assessment found that SOC decreased

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with depth both inside and outside of the shelterbelt. While SOC decreased with depth, there

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were significantly higher surface concentrations inside the exclusion area compared to outside. At depths greater than 20 cm, SOC became increasingly homogenous for both

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datasets with little difference observed. The results suggest that the influence of the exclusion

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area on SOC accumulation at the site was only within the top 10 – 20 cm of the soil profile. The results highlight the importance of soil depth in quantifying SOC within the soil profile

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and SOC sequestration potential for sites at depth.

Keywords: soil organic carbon; exclusion area; carbon sequestration; shelterbelts; cattle grazing

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Journal Pre-proof 1

Introduction Soil is the third largest carbon pool on Earth and is the largest terrestrial C sink (Lal,

2007; 2008; Eberwein et al., 2015; Stockmann et al., 2015; Minasny et al., 2018). Current literature suggests that C stocks within soil (the top 3 m of the soil profile) are approximately 2300 Gt (Batjes, 2014; Stockmann et al., 2014). Furthermore, 1500 Gt is located within the top 1 m of the soil profile and 615 Gt within the top 20 cm (Stockmann et al., 2014). The soil carbon sink also holds more than double the amount of C stored within the combined biomass

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and atmospheric pools (Stockmann et al., 2014).

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SOC is generally described as the mineral C fraction of soil organic matter (SOM)

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(Baah-Acheamfour et al., 2014; Stockmann et al., 2014). It is the result of the decomposition

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and mineralisation of leaf litter, root exudates, deceased fauna and other organic residues by heterotrophic soil biota and microorganisms (Lal, 2008; Stockmann et al., 2014). The benefits

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of increased SOC include improved structure, stability, water-holding capacity, nutrient

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cycling, diversified microbial ecosystems, as well as regulation of ground and surface water quality (Anaya et al., 2015; Baah-Acheamfour et al., 2015; Eberwein et al., 2015; Stockmann

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et al., 2014; 2015; Lorenz and Lal, 2005). Currently, there is no reference SOC value for optimal soil ecosystem function but it is generally accepted that concentrations ranging between 1 – 3% are acceptable for arable land in temperate regions whilst grasslands and forests have slightly higher values (Hazelton and Murphy, 2007; Stockmann et al., 2014). As a result, SOC is generally considered a good indicator of soil health and fertility (Stockmann et al., 2015). Decomposition of SOM leads to the mineralisation of C and subsequent accumulation of SOC within the soil profile (Anaya et al., 2015; Stockmann et al., 2014). Global demand for food and agricultural products has progressively led to the conversion of natural environments into agricultural land (Lal, 2007;Baah-Acheamfour et al.,

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Journal Pre-proof 2015). Deforestation and other land clearing as a result of agricultural development has profound impacts on soil quality by exposing soil to physical and chemical processes it is commonly protected from (Lal, 2007; Mullan, 2013; Li et al., 2014; Baah-Acheamfour et al., 2015). SOC loss associated with agriculture can occur in a variety of ways. Soil erosion due to decreased stability can entrain soil particles and transport SOC from paddocks resulting in a net loss of soil C content (Follain et al., 2007; Bameri et al., 2012; Stockmann et al., 2015). As well as this, exposure of disturbed soil to oxygen leads to the decomposition of recalcitrant

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forms of C that are then released to the atmosphere as CO2 (Follain et al., 2007; Nair et al.,

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2008; Baah-Acheamfour et al., 2015). A loss of 40 – 60% of SOC stocks has been reported

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for agricultural lands in the U.S. Midwest over the course of the twentieth century

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(Cambardella et al., 2012) whilst the conversion of tropical forests into agricultural land has led to a 72% SOC loss over a 50 year time period (Anaya et al., 2015).

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Previous literature has outlined a variety of positive effects that cultivating vegetation

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on arable land can provide to soil including increasing SOC, improving water holding capacity and soil structure (Davy and Koen, 2013; Korkanc, 2014; Baah-Acheamfour et al.,

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2015; Cardinael et al., 2015; Cunningham et al., 2012; George et al., 2012; Wells et al., 2019). Nevertheless, the outcomes of these studies have suggested that installing vegetation could potentially increase SOC by 35% over a period of 50 years in comparison with adjacent agricultural lands (Baah-Acheamfour et al., 2014). Studies that directly analysed the belowground benefits of shelterbelts have primarily focused on their influence within cropping systems rather than grazing operations (Walter et al,. 2003; Follain et al., 2007; Sauer et al., 2007; Lenka et al., 2012; Korkanc, et al., 2014; Cardinael et al., 2015; Chaplot et al., 2016; Aynekulu et al., 2017; Listopad et al., 2018). In saying this, these studies have highlighted that fenced off areas for ecological service areas and the installation of shelterbelt structures do increase SOC with some estimates ranging from 38% (Lenka et al., 2012) to

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Journal Pre-proof 55% (Sauer et al, 2007; Cardinael et al., 2015; Chaplot et al., 2016). The age of the structures has also been determined to influence SOC accumulation in previous research (Aynekulu et al., 2017; Listopad et al., 2018). It has been demonstrated that SOC will continue to accumulate over multi-decadal timescales (Follain et al., 2007; Hoogmoeed et al., 2012; Baah-Acheamfour et al., 2015). Other benefits to the soil profile include a decrease of bulk density (BD) and soil compaction associated with increased SOM, macro-aggregation and subsurface microbial activity (Lal et al., 1998; Lenka et al., 2012; Jandl et al., 2014; Cardinael

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et al., 2015; Korkanc, 2014; Stockmann et al., 2015; Sun et al., 2015).

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This study aimed to assess how differences in land management influence SOC (and

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other soil physico-chemical properties down the entire soil profile) in the Upper Hunter

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Valley, NSW, Australia. The specific objectives were to (a) assess near surface (top 20cm) (b) whole of profile (surface to bedrock) as well as (c) hillslope soil (hillslope transect) SOC

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distribution and patterns. The study utilises an area where grazing has been excluded for the

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past 15 years and an adjacent area where grazing has been conducted as per normal farm practice. Few studies have examined both near surface, whole soil profile as well as hillslope

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transect (hillslope divide to base of slope) SOC. This project also extends previous work (Martinez et al., 2010). The results are placed in the context of potential of soil C sequestration and climate change mitigation.

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Materials and methods

2.1

Study site The study site is located approximately 22 km west of Merriwa, NSW, Australia

(Figure 1) (latitude 32o 05’ 37”; longitude 150

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07’ 18”). The area is highly agricultural

productive and is and used for cropping and grazing operations due to highly fertile volcanic soils and a subtropical to temperate climate. The landscape at the site is determined primarily

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Journal Pre-proof by the characteristics of the Merriwa plateau and is comprised of gently undulating and rolling hills with an elevation range of 300 – 450 m (McCrae and Cooper, 1985; Storey et al., 1963). The site has been utilised as part of a variety of past studies including landscape evolution and soil erosion, soil moisture, soil C surveys (Martinez et al., 2007; Martinez et al., 2010; Hancock and Coulthard, 2012; Hancock et al., 2015). Soils in the Krui catchment are primarily derived from volcanic geology with pockets of sedimentary derived and alluvial soils present in the lower catchment (Kovac and Lawrie,

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2001). The major soil types present within the landscape are Chocolate Soils and Euchrozems

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(Lixic Ferralsol), Black Earths (Chernozem) and Red Clays (Kovac and Lawrie, 2001). These

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soils are characterised by high clay content, a large shrink-swell capacity, the opening of large

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cracks throughout the soil profile during extended dry periods as well as poor horizon development (Charman and Murphy, 2007). Soils specifically at the study site are part of a

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landscape referred to as “Ant Hill”. Soils within this landscape are predominantly black earths

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that are derived from the underlying basalt. The soil at the study site was determined to be a vertosol with deep soil profiles, high clay content and poor horizon development.

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The climate is classified as having a subtropical to temperate climate. Mean annual rainfall for the area is 602.8 mm (1969 – 2017) (www.bom.gov.au). The highest ever recorded was 947.2 mm in 2010 while the lowest was 291.4 mm in 1980. Precipitation is highest during the summer months with over one-third of total rainfall occurring during December, January and February on average. Mean annual maximum temperature is 23.8°C while the annual minimum is 9.1°C. During January, the mean maximum is 30.7°C while the minimum is 16.3°C. In July, mean maximum is 15.7°C and the minimum is 2.3°C. During the winter months, overnight frosts are common (Stern et al., 2000). The study site is an organic beef cattle farm (Hancock et al, 2015). Grazing density is low to moderate with livestock time managed between paddocks in four week cycles

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Journal Pre-proof (personal correspondence - Doc and Fiona Strachan). The SE paddock adjacent to the shelterbelt was formerly utilised for cropping between 1980 – 2003 but it has been solely utilised for grazing pasture since (Martinez et al, 2010) (Figure 2). It is understood that the adjacent paddock to the NW has only ever been utilised for grazing. The study focusses on an area that extends for approximately 420 m in a NE to SW orientation. Mean width of the structure is 30 m constituting a total area of 12600 m2. The site is on a hillslope with an elevation range of 381 to 358 m with a mean gradient of 5.5%. The area was fenced off in

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2002. Sampling at the site was undertaken between May and December 2015.

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Vegetation is dominated by grasses with native grass species prevalent in the grazing

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paddocks include plains grass (Austrostipa aristiglumis), wiregrass (Aristida ramose),

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wallaby grass (Danthonia spp), red grass (Bothrochloa macra) and blue grass (Dicanthium

2.2

Field sampling

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spp) (Martinez, 2010).

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The study site consisted of a fenced off (‘shelterbelt’ or cattle ‘exclusion area’) area 30

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m wide and 420 m long that ran from the catchment divide to the creek line (Figures 1 and 2). This study employed a transect sampling approach where samples were collected at regular intervals both in and outside the exclusion area (Pennock and Appleby, 2002) (Figure 3). To determine differences in soil properties sampling was undertaken both inside and outside the exclusion area (Figure 3). This consisted of: 1. Surface sampling undertaken at fixed (25 m) intervals along the entire hillslope both inside and outside the exclusion area using a transect approach (Figure 3). Each sample was collected using an open-ended 9.3 x 21 cm cylinder. A steel cap was placed on top of the cylinder to aid insertion and minimise damage to the cylinder before being driven into the soil profile to maximum depth manually by hammer. The core was then extracted using adjustable pliers (Vice Grips) and the soil sample placed 7

Journal Pre-proof in plastic bags for transport. A total of 27 samples were collected inside and outside the exclusion area (54 in total). 2. To better understand if there were any differences at key positions along the hillslope (i.e. top, mid and bottom of slope), intense sampling was undertaken (0-20 cm) (Figure 3). To assess this variability soil cores were collected at the top, mid and bottom of slope using a 2m x 2 m grid (9 samples at 1m spacings). Samples were collected using the same core and method as outlined above with a total of 27 samples

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collected outside and 27 samples collected inside the exclusion area (54 samples

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collected in total).

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3. To quantify differences down the near surface soil profile, depth increment samples

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were collected to 20 cm. To determine the near surface SOC, depth increment sampling using a frame and scraper plate were used. A frame of dimensions 50 cm by

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20 cm (1000 cm2) (Campbell et al., 1998; Loughran et al., 2002) was hammered into

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the ground and a steel scraper used to remove soil at fixed 2 cm increments to a depth of 20 cm. The scraper plate samples were collected in the centre of the 2m by 2m grid

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described above at the top, mid and bottom of the hillslope both inside and outside the exclusion area (6 scraper plates in total). 4. Whole soil profile SOC was assessed with trenches dug both inside and outside of the exclusion area to bedrock at top, middle and bottom slope where the 3x3 grid of cores and a scraper plate (depth increment sampling) were collected. A backhoe was utilised to dig each of the trenches to bedrock. Samples were then collected in 20 cm intervals from the side of the trench to the maximum depth at each sampling site utilising the 20 cm steel core and method outlined above. Figure 3 displays a schematic outlining the sampling described above.

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2.3

Laboratory analysis Each soil sample was weighed and air dried in an oven at a temperature of 40°C for

approximately five to seven days at the University of Newcastle soil laboratory. At the end of this period, samples were than reweighed and the samples returned to the oven for a further 24 hours (or longer) then reweighed to ensure all moisture had been removed. Samples were then passed through a 2 mm sieve and the fine earth or soil (<2 mm) and rock fragment (>2

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mm) fractions separated. The <2 mm fraction was further disaggregated with a mortar and

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pestle, mixed then weighed. For the determination of SOC concentration, a 20.0 – 25.0 g

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subsample of the <2mm fraction was sent to the Environmental Analysis Laboratory at

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Southern Cross University, Lismore for total C calculation using dry combustion in a LECO CNS2000 analyser.

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Particle size analysis was undertaken to determine the clay content of each sample

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utilising the hydrometer technique outlined by Smith and Atkinson (1975). Electrical Conductivity (EC) and pH was determined using a 1:5 solution with distilled water using a

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Eutech EC and pH instrument. BD was determined using the method of Rayment and Higginson (1992). This analysis was conducted at the University of Newcastle.

2.4

Statistical analysis

Basic assessments were conducted using linear regression and student t-tests in Excel and KaleidaGraph software. Additional statistical analysis (Anova) was conducted using GraphPad Prism 7.0 software. All graphs and figures outlining relevant results were developed using this program with plots developed and additional analysis displayed using KaleidaGraph.

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3

Results

3.1

Surface SOC- Hillslope transects and point scale variability (3x3 grid) The inside transect demonstrated a significantly (p<0.05) higher mean SOC

concentration than the outside transect (Table 1). There was no significant difference in BD or

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pH for either inside or outside the shelterbelt.

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Martinez et al. (2010) conducted a study of the site in 2005 shortly after the

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establishment of the shelterbelt with additional data collected in 2011 (Table 2). Compared to

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2005 results, the exclusion area has a significant increase of SOC concentration over the tenyear period (p<0.05). There was no significant difference (p>0.05) between SOC in 2005,

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2011 and 2015 for the outside transect suggesting that SOC is stable.

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There was no significant difference between BD, clay content or soil moisture (p>0.05). There was no significant statistical relationship identified inside or outside of the

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exclusion area between SOC and elevation or hillslope position (not displayed for brevity). Whilst not statistically significant, pH, EC and soil moisture were all found to increase downslope whilst BD decreased (not displayed for brevity).

3.2

Surface SOC- Point scale spatial variability SOC was found to be highest inside the exclusion area at the upper and middle

locations (Figure 4, Table 3). Both of the Top (p<0.05) and Middle (p<0.0001) locations were also deemed to be significantly different. Both the top sites had the highest variability. Contrastingly, the Bottom dataset demonstrated a higher SOC concentration outside of the shelterbelt which was found to be insignificantly different to that inside. For both data sets,

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Journal Pre-proof SOC decreased down the hillslope (Figure 4, Table 3). The difference of means down the slope was found to be strongly significantly higher inside than outside. BD was lower inside the shelterbelt at all sampling sites (Table 4) however it was only significantly different (p<0.05) at the lower location. Soil pH was lower inside of the shelterbelt at the upper, middle and lower locations although this was only found to be significant at the middle site. All sampling sites down the hillslope demonstrated a higher EC value inside the shelterbelt (Table 4). Only the lower location was determined to be

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significantly different (p< 0.0005). Clay content increased down the hillslope both inside and

SOC and the soil profile- Distribution of SOC concentration to bedrock

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3.3

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outside of the shelterbelt (Figure 5) while silt and clay decreased (not shown for brevity).

Soil depth was shallowest at the top (80-100 cm) and increased downslope to a

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maximum depth of 180-220 cm (Figure 6). The highest SOC concentrations were found

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within the 0 – 20 cm depth interval while the lowest was at the bedrock. For consistency, here we only compare the data from the cores collected at the point of bedrock sampling, not those

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from the surface cores and to 80 cm. As with the findings of the previous section, SOC concentrations were higher inside the shelterbelt at the surface (0 – 20 cm). Mean range inside the shelterbelt was 0.78 -2.68% while the outside had a mean range of 0.98 - 2.31%. At depths greater than 20 cm SOC concentration was generally higher, or at least equal, outside of the shelterbelt however not statistically significant (using ANOVA p>0.05). BD increased with depth at the upper and middle locations inside and outside of the exclusion area however there was no observable difference between inside and outside datasets in regards to BD throughout the soil depth profile. Clay content was relatively uniform at the three sampling sites with relatively uniform textural distributions.

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3.4

Depth increment profile (scraper plate) The depth increment (scraper plate) sampling demonstrated that SOC concentration

was highest at the surface and declined with depth for the three sampling sites (Figure 7). For the top and middle positions, SOC was visually highest in the exclusion area while at the bottom site there was no difference between either inside or outside the shelterbelt with

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profiles being very similar (p>0.05).

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For the top site, the SOC profile is very similar both inside and outside until around 12

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cm where the inside sample displays a distinct increase in SOC. For the middle position, both

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inside and outside data sets show very similar trends, with the inside data set being significantly higher (p<0.05). For the bottom sites, both display very similar trends however,

Discussion

4.1

Surface SOC

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the inside data set is non-significantly higher (p>0.05).

Transect SOC concentrations determined for the Stanley site fall within the high range (2.00 – 3.00 %) for Australian soils (Table 1) (Hazelton and Murphy, 2007). Soils at these concentrations generally have good structure and buffering capacity with sufficient organic matter to maintain BD and improve water-holding capacity. pH and EC (below the 2000 μS threshold for the effects of salinity, Hazelton and Murphy, 2007) were also both well within the acceptable range for agricultural systems (Hazelton and Murphy, 2007). Surface SOC was significantly higher inside the exclusion area for both the transect and 3 x 3 m grid datasets with an approximately 14% higher concentration determined. This was consistent with previous literature outlining the influence of exclusion areas on SOC

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Journal Pre-proof (Follain et al., 2007; Sauer et al., 2007; Walter et al., 2003; Lenka et al., 2012; BaahAcheamfour et al., 2014; Korkanc, 2014; Bangura et al., 2015; Cardinael et al., 2015). The results suggest that the exclusion area has been more effective at accumulating SOC within the 0 – 20 cm soil profile than the adjacent grazing paddock although both land uses have recorded increases (Aynekulu et al., 2017). Prior to the establishment of the exclusion area, the field was used for cropping and in later years had improved pasture (lucerne). Since establishment of the shelterbelt, the site has maintained a mix of improved and native pasture

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and is conservatively grazed.

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Literature suggests that the difference observed at Stanley will increase with age

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(Walter et al., 2003; Follain et al., 2007; Sauer et al., 2007; Luo et al., 2010; Cunningham et

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al., 2012; Baah-Acheamour et al., 2014). For instance, Baah-Acheamfour et al. (2014) highlighted in an assessment of the effectiveness of trees increasing soil C in central Alberta,

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Canada and found that a 50-year old shelterbelt had a SOC concentration of 4.70% within the

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top 10 cm of the profile, 35% higher than the adjacent grazing paddock. Sauer et al. (2007) also highlighted that a 35-year old shelterbelt in New England, USA, had a SOC

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concentration of 2.52% (0 – 15 cm). In both these cases, the difference observed was much higher than the results determined for the ten-year old structure at Stanley suggesting that SOC accumulation could increase in the future. Continued monitoring of soil conditions at the site would determine any trends.

SOC was significantly higher (p>0.05) than the values determined by Martinez et al. (2010) at the site in 2005 and 2011 (approximately 24%) (Table 2). These results highlighted that the exclusion area at Stanley was more effective at accumulating SOC within the 0 – 20 cm soil profile than the adjacent grazing paddock. In saying this, the substantial increase observed outside of the exclusion area also demonstrated that moderately grazed organic beef cattle production can also have significant benefits to SOC.

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Journal Pre-proof Results at the study site were also much higher than those outlined by previous literature for exclusion area and similar land management systems (Sauer et al., 2007; BaahAcheamfour et al., 2014). It is unclear why the accumulation rate at the site was greater than those outlined in previous literature as the pasture was consistent along the transects (Martinez et al. (2010). Lenka et al. (2012) presented a similar high accumulation rates for a five-year old shelterbelt in Orissa, India. This could suggest that the installation of a shelterbelt or similar exclusion areas results in an initial spike of soil C accumulation that

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eventually decreases with increasing age. This would also suggest (and we speculate here)

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that the soil types may have a maximum carrying capacity of SOC as outlined by Stockmann

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et al. (2015). While there appears to be no studies previously undertaken to determine if this is

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a common trend, this is another reason for continued analysis of soil conditions at Stanley to determine if accumulation will decrease in the future. If a fast increase in SOC is required

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globally for carbon sequestration purposes, then this work suggests that the soil type here may

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be a candidate. More work is needed to verify this. Previous studies of exclusion areas have concluded that the key factor influencing

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SOC accumulation was the increase of SOM volumes derived from above and belowground sources (Walter et al., 2003; Follain et al., 2007; Sauer, et al., 2007; Hoogmoed et al., 2012; Baah-Acheamfour et al., 2014; Korkanc, 2014). Vertosols in particular have been found to respond positively if perennial vegetation is installed with a mean rise of 15% recorded for various soil types and land uses in an Australian context (Luo et al., 2015). We can only speculate on the mechanism here, as long-term above and below ground biomass data is not available. We believe that there is likely to be several processes. An accumulation of additional biomass due to cattle exclusion is an obvious explanation. However, while there was no significant difference in BD between inside and outside the exclusion area, when sampling it was clear that the soil inside the exclusion area was a lot softer underfoot than

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Journal Pre-proof outside. Attempts were made to assess infiltration rates using a double ring infiltrometer, but due to the cracking nature of the soil, obtaining results proved problematic. A further issue is that of soil compaction by cattle – which occurs outside of the exclusion area. Compaction and its changed could be assessed by the use of cone penetrometers (a focus of future work). However, what was clear from observation was that the soils inside the shelterbelt were ‘softer’ than those outside. The concentration and movement of SOC in the surface 20 cm will be both an

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advective and diffusive type process. Accumulated biomass will diffuse from the surface into

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the soil. Wells and Hancock (2014) and Wells et al. (2013) have examined this process in a

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range of Australian environments using environmental tracers. The input from below ground

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biomass also can only be speculated. However, given the cracking nature of Vertosols, there is the potential for advective type process as cracks open and soil and vegetative matter can be

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transported by water deep into the soil profile. However, this process may be countered by the

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cracks providing oxygen deep into the soil profile thereby allowing the oxidation of SOC. Plant roots may also be contributing to the increase in SOC (Joggaby and Jackson,

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2000; Lorenz and Lal, 2005). Observation of the samples suggested that there was no qualitative difference in plant root presence inside or outside the exclusion area. However, the quantification of root biomass is possible, yet difficult to do, and requires wet sieving. Wet sieving was attempted here but due to the high clay content of the soil and the quantity of samples, it was not feasible. Considerable research is needed to fully understand the complex feedbacks in any soil system including root biomass.

4.2

Soil depth profile distribution SOC decreased with depth both inside and outside of the exclusion area. The results at

Stanley are consistent with prior literature outlining SOC distribution with soil depth (Lenka

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Journal Pre-proof et al., 2012; Davy and Koen, 2013; Mora et al., 2014; Baah-Acheamfour et al., 2015; Cardinael et al., 2015; Nadeu et al., 2015; Olson and Al-Kaisi, 2015; Sun et al., 2015; Wiesmeier et al., 2015; Xue et al., 2015; Cheesman et al., 2016). While SOC decreased with depth regardless of the shelterbelt, there was an identifiably higher surface (0 – 20 cm) concentration at the upper, middle and lower sites inside compared to outside the shelterbelt. At depths greater than 20 cm, SOC became increasingly homogenous in both the inside and outside datasets.

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Cardinael et al. (2015) in a study of tree rows within an alley cropping system also

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found that there was no significant difference between tree rows and cropping fields at depths

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greater than 10 cm. A similar trend was also found by Sun et al. (2015) in a variety of land

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use systems who suggested SOC was homogenous at depths greater than 30 cm. Davy and Koen (2013) also surmised that land uses including cropping, grazing and agroforestry had

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little impact on SOC distribution at depths greater than 10 cm in the Murray-Darling Basin.

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While this is the likely scenario at Stanley, it has been suggested that temporal factors influence the vertical distribution within the soil profile (Lorenz and Lal, 2005; Olson and Al-

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Kaisi, 2013). Literature has highlighted the age of the vegetation may influence the vertical distribution of SOC as growth and development of root stocks occur over decadal timescales (Joggaby and Jackson, 2000; Lorenz and Lal, 2005). Deeper root stocks generally have the effect of providing SOM inputs to greater depths by water infiltration via the creation of pathways attributed to root growth and pedoturbation (Lorenz and Lal, 2005). Continued analysis of the soil depth profile in the future would help determine if this is the case at the site. In saying this, the results of this project would suggest that the influence of the shelterbelt on SOC accumulation at the site was only within the top 10 – 20 cm of the soil profile.

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Journal Pre-proof 4.3

SOC distribution down the hillslope SOC was found to decrease down the hillslope at the surface. Curiously, this decrease

was only identified in the 3 x 3 m grids dataset but not for the transects. These results were inconsistent with previous literature outlining the spatial distribution of SOC with topography (Walter et al., 2003; Yoo et al., 2006; Bameri et al., 2015; Sun et al., 2015). The decrease of SOC downslope was an unexpected result as it generally increases because of sediment transport and erosive processes (Hancock et al., 2010; Bameri et al., 2015). Interestingly, the

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previous study undertaken at the site also demonstrated a similar decrease downslope

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(Martinez et al., 2010) suggesting that site specific processes influence the spatial distribution

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of SOC in relation to the hillslope. It is unclear why this was the case at Stanley but further

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investigation of distribution within the depth profile highlights some interesting findings. As outlined above, SOC decreased with depth at all sampling locations inside and

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outside of the shelterbelt. Surface (0 – 20 cm) SOC also decreased with the hillslope but this

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was not observed at depths greater than 20 cm. Previous literature has suggested that the high shrink-swell capacity of vertosols, which causes large cracks to extend deep into the soil

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profile during dry periods, provides multiple pathways for the transport of organic matter into the subsoil causing the characteristic uniform vertical distribution of SOC for these soil types (Don et al., 2007). Due to the increasing soil depth determined downslope at Stanley, it is hypothesised that a similar effect has occurred at the site with C inputs disseminating throughout the soil depth profile via cracks opened during extended dry periods. This in turn has resulted in a decrease of surface SOC down the hillslope. Therefore, the decreasing SOC trend with the hillslope is influenced predominantly by the soil type at the site.

4.4

SOC sequestration potential

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Journal Pre-proof While this project was not focused on the soil C sequestration potential, results have highlighted the importance of depth in declining SOC within the soil profile. A multitude of research has highlighted that sequestration of atmospheric CO2 within terrestrial C pools could be an effective climate mitigation strategy (Lal, 2004). Of particular interest is the long term storage potential of recalcitrant forms of soil C generally found at depths greater than 40 cm in the soil profile (Lal et al., 1998; Stockmann et al., 2015; Minasny et al., 2018). These forms can have storage times ranging from decadal to millennial timescales (Lal, 2004;

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Stockmann et al., 2015).

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The proportion of SOC at depths greater than 20 cm generally increased down the

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hillslope coincident with increasing depth. This also indicated an increased proportion of

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recalcitrant forms of soil C that have residence times of up to millennial timespans (Stockmann et al., 2015). These results suggest that in regards to soil C sequestration, soil

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depth has equally significant influence on long term storage as above and belowground

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biomass and C inputs. The results demonstrate that surface sampling can underestimate SOC stocks and soil C sequestration potential. More accurate estimations of soil C sequestration

Kaisi, 2013).

4.5

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potential need to incorporate the entire root zone to depths of 1.0 – 2.0 m (Olson and Al-

Study limitations

The results here are based on field data collected over a relatively short period (Listopad et al., 2018). The results suggest that SOC increases rapidly in a short time period. Numerical modelling of this initial period and its development over longer time periods would provide long-term soilscape trajectories under the two different management scenarios examined here (Wells et al., 2013; Jandl et al., 2014; Wells and Hancock, 2014; Welivitiya et

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Journal Pre-proof al., 2016; Cohen et al., 2017; Listopad et al., 2018; Wells et al., 2019). This work is now underway. Previous literature has demonstrated that there is a lateral effect of the establishment of shelterbelts, hedgerows, tree-rows or similar vegetation either side of the structure (Walter et al., 2003; Follain et al., 2007; Bangura et al., 2015). Due to time constraints, this study was not able to conduct a series of transects, 3 x 3 m grids and soil depth profile sampling at the site at further distances from the exclusion area. A sampling set analysing the lateral effect of

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the shelterbelt would have improved the overall understanding of SOC and soil properties.

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This study has examined SOC differences at a single point in time. Follow up

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assessment is required to confirm longer term trends. To better understand SOC change in

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these environments repeat analysis in required to determine if timescales influence SOC and soil properties within the shelterbelt. The study also examined a site with high clay soils.

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Other sites with different soil texture, depth and landscape management should be examined

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to better understand how SOC changes under different land management practices. While it could be said that the increase in SOC by excluding grazing is an obvious

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result, questions can be asked about alternatives for those areas where grazing is necessary for agricultural production, fire management or cultural legacy (for example). While we have not examined soil moisture, if more areas are fenced off, this may have implications for runoff and water supply to streams and water supply. Much more needs to done understand how exclusion areas can be better utilised for carbon storage as well as be part of an economic, ecological and cultural system.

5

Conclusions Here a hillslope and soil profile sampling approach is used to assess differences in SOC

resulting from a change in land management. The combination of increased organic matter

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Journal Pre-proof derived from the exclusion area as well as the protection from grazing livestock provided by fencing is the likely factor for the difference of SOC identified at the site. This was also found to be the key factor in previous literature outlining the belowground effects of excluding grazing. The results highlighted differences in SOC at different hillslope positions. Our findings were: 1. SOC concentrations were statistically higher inside the fenced off area (cattle

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excluded).

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2. The shelterbelt had no statistically significant effect on soil properties at either the

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point or hillslope transect scale over the study period

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3. SOC concentration decreased non-linearly with depth in the total soil depth profile regardless of the shelterbelt. There was no significant increase in SOC at depths

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greater than 20 cm and the shelterbelt had no influence on SOC concentrations and

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stocks within the total soil depth profile. Economic modelling of exclusion areas and conventional grazing in agricultural production

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including carbon accounting would further highlight the costs and benefits.

Acknowledgments This research was largely supported by Australian Research Council Discovery Grants (DP 0556941: “Carbon, nutrient and sediment dynamics in a semi-arid catchment” and DP110101216: “A next generation spatially distributed model for soil profile dynamics and

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Journal Pre-proof pedogenesis incorporating soil geochemistry and organic matter”). Doc and Fiona Strachan are thanked for their support and access to their property. Veikko Kunkel, Abraham Gibson, and James Hugo are thanks for their field support. The authors have no conflict of interest.

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The two anonymous Reviewers are thanked for their helpful and supportive comments.

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List of Figures

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Figure 1. Location of the Stanley study site. The transect is located within the red box with the red line displaying the transect location.

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Figure 2. Fenced of area on the left hand side of fence at the midslope position looking downslope.

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Figure 3. Schematic (not to scale) of the sampling undertaken both inside and outside the fenced area at Stanley.

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Figure 4. Mean SOC (+/- 2) inside and outside the fenced area at the Upper, Middle and Lower hillslope locations.

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Figure 5. Bulk density (top) and clay content (bottom) for the Upper, Middle and Lower hillslope locations (average +/- 1). Figure 6. SOC distribution to bedrock at the Upper (a), Middle (b) and Lower (c) hillslope positions. Figure 7. Depth increment sampled SOC (scraper plate) at the top, middle and bottom of the transect.

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List of Tables

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Table 1. Descriptive statistics for the transect inside (top) and outside (bottom) the exclusion area.

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Table 2. Descriptive statistics for the outside transect in 2005 and 2011.

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Table 3. Average SOC for the 3x3 sample grids at the Upper, Middle and Lower sampling locations.

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Table 4. Mean, standard deviation (in brackets) and p-values for various soil properties at the Upper, Middle and Lower locations.

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Figure 1. Location of the Stanley study site. The property is located on an area called the Merriwa Plateau that is bound by the Liverpool Ranges to the north and the northern extent of 28

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Wollemi National Park to the south. The transect is located within the red box with the red line displaying the transect location.

Figure 2. Fenced of area on the left hand side of fence at the midslope position looking downslope.

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Figure 3. Schematic (not to scale) of the sampling undertaken both inside and outside the fenced area at Stanley.

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4 outside

3.5 SOC (%)

inside 3 2.5

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2

Upper

Middle

Lower

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Figure 4. Mean SOC (+/- 2) inside and outside the fenced area at the Upper, Middle and Lower hillslope locations.

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outside inside

1.2

3

1.1

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1 0.9

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bulk density (g cm )

1.3

0.8 Upper

Lower

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Middle

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80 75

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65 60 55 50 45 40

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clay (%)

70

Upper

outside inside Middle

Lower

Figure 5. Bulk density (top) and clay content (bottom) for the Upper, Middle and Lower hillslope locations (average +/- 1).

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(b )

O u ts id e 0

1

2

3

4

S O C (% )

In s id e O u ts id e

0

1

2

3

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S O C (% )

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0 - 20 20 - 40 40 - 60 60 - 80 80 - 100 1 0 0 -1 2 0 120 - 140 140 - 160 160 - 180 180 - 200 200 - 220

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D e p th (c m )

(c )

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In s id e

0 - 20 20 - 40 40 - 60 60 - 80 80 - 100 1 0 0 -1 2 0 120 - 140 140 - 160 160 - 180 180 - 200 200 - 220

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D e p th (c m )

0 - 20 20 - 40 40 - 60 60 - 80 80 - 100 1 0 0 -1 2 0 120 - 140 140 - 160 160 - 180 180 - 200 200 - 220

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D e p th (c m )

(a )

0

In s id e O u ts id e 1

2

3

4

S O C (% )

F ig u r e 6 .2 .1 .1 . S O C d is t r ib u t io n w it h in t h e s o il d e p t h p r o f ile a t th e ( a ) u p p e r , ( b ) m id d le a n d (c ) lo w e r s a m p lin g lo c a tio n s .

Figure 6. SOC distribution to bedrock at the Upper (a), Middle (b) and Lower (c) hillslope positions.

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0 outside inside

Middle

outside inside

outside inside

5

10

10

15

10

15

20 0

1

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3

4

5

20

0

1

2

3

% SOC

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% SOC

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Bottom

5

depth (cm)

depth (cm)

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0

1

2

3

4

5

%SOC

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Figure 7. Depth increment sampled SOC (scraper plate) at the top, middle and bottom of the transect.

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depth (cm)

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Table 1. Descriptive statistics for the transect inside (top) and outside (bottom) the exclusion area. Max.

Min.

3.41 1.44 7.83 152.6

1.84 0.97 6.08 32.8

2.81 1.34 7.3 94.3

1.63 0.96 6.3 29.7

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Std. Dev inside SOC (%) 2.65* 0.52 Bulk Density (g cm-3) 1.12 0.11 pH 6.72 0.38 70.53 26.93 EC (S) outside SOC (%) 2.32* 0.25 Bulk Density (g cm-3) 1.09 0.11 pH 6.7 0.26 57.4 19.0 EC (S) *indicates a significant difference (p>0.05)

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Table 2. Descriptive statistics (SOC) for the outside transect in 2005 and 2011. Std. Dev 0.22 0.25

Max 2.71 3.31

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Min 1.73 1.76

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Table 3. Average SOC for the 3x3 sample grids at the Upper, Middle and Lower sampling locations. Std Dev

Min

Max

2.65 2.31 1.74

4.04 2.84 2.37

2.15 1.81 1.94

9 9 9

3.08 2.63 2.11

Upper Middle Lower

9 9 9

2.63 2.06 2.19

Outside 0.27 0.14 0.16

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3.11 2.32 2.46

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Table 4. Mean, standard deviation (in brackets) and p-values for various soil properties at the Upper, Middle and Lower locations.

Middle

Lower

Upper out

p

in

out

p

in

out

p

BD (g cm )

0.92 (0.04)

0.96 (0.09)

0.20

1.06 (0.04)

1.14 (0.14)

0.10

1.03 (0.12)

1.15 (0.08)

0.02

clay (%)

57.2 (14.9)

59.9 (7.7)

0.64

63.0 (6.3)

68.2 (3.3)

0.05

75.9 (2.2)

74.4 (3.3)

0.28

Soil water (%)

40.8 (2.04)

33.9 (5.1)

0.002

19.5 (3.5)

17.9 (1.7)

20.7 (7.4)

18.5 (1.4)

0.40

pH

6.70 (0.16)

6.82 (0.20)

0.15

6.45 (0.16)

6.73 (0.25)

0.02

7.12 (0.18)

7.14 (0.22)

0.78

EC (S)

78.7 (13.4)

75.8 (9.5)

0.59

87.1 (5.6)

85.04 (34.7)

0.86

138.6 (30.0)

94.4 (23.3

0.003

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Journal Pre-proof

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Graphical abstract

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Journal Pre-proof Highlights

We examine if excluding cattle changes soil organic carbon (SOC)? Surface SOC concentrations were significantly higher inside the exclusion area At depths greater than 20 cm, SOC became increasingly homogenous for both sites

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After ~10 years of cattle exclusion SOC change only occurred in the top 20cm

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