interactions above- and below-ground on farms. Results from the soil carbon stock analysis in shelterbelts and paddocks, followed by variance partitioning, highlighted the variability at the different scales (some more than others) (Figure 3-5). The results observed showed that the variability resided largely at the shelterbelt or within-shelterbelt scale, while farm scale played a minor role for all three soil carbon stocks (Figure 3-5). This outcome was further corroborated by the mixed-effect models (Table 3-6) the shelterbelt model was most highly
103 ranked for the majority of soil carbon stocks in shelterbelts. The same was not observed for soil carbon stock variability in paddocks (Table 3-7). It was widely recognised that soil carbon stocks were spatially variable and this variability was also dependent on the present above-ground conditions (Grange & Rawson, 2010). Indeed, land cover and changes thereof, including farm management, can lead to different soil carbon stocks (Guo & Gifford, 2002; Schipper et al., 2010).
Soil carbon stocks under different above-ground cover (i.e. pastures or trees) can be affected by farm management of paddocks and the potential spillover from paddocks into the shelterbelt soil (Didham et al., 2015). Observations of soil carbon stock variability in both paddocks and under shelterbelts were in line with those of previous studies (Figure 3-3 and Figure 3-4; Appendix A). Furthermore, soil carbon stocks under native shelterbelts may hint at the influence vegetation might have on below-ground soil stocks over time (Figure 3-4). The top-soil in paddocks was often filled with the fine roots of grasses and other small herbaceous vegetation, adding to 75% of total root biomass (Don et al., 2009). This could be expected since the shelterbelt area was a somewhat undisturbed area where leaf litter and woody debris accumulated, decomposed at the surface and fed back into the soil (Simón et al., 2013). The adjacent pasture could be seen as being under constant production pressure with irrigation, fertiliser and herbicide application. This could explain why shelterbelts, in some studies, contained more carbon in the organic layer compared to in paddocks (Gale & Cambardella, 2000; Rees et al., 2005). This was presumably because of high inputs of organic matter associated with decomposing fine-root and leaf litter of the above-ground tree and other herbaceous ground-cover plants in shelterbelts. Such differences have been
reported world-wide, highlighting the effect of increasing trees on farms and their positive effect on soil carbon stocks (Baah-Achemfour et al., 2014; Lal, 2005; Nair et al., 2010; Smith & Reid, 2013; Takimoto et al., 2008). On the other hand, lower soil carbon and nitrogen levels have been found in paddocks in New Zealand, which have been interpreted as an effect of the increased farming intensity and livestock (Elmore & Asner, 2006; Lettens et al., 2005; Schipper et al., 2007). However, not everyone has found decreased soil carbon stocks on farms, as the effects appeared to vary over time, land use changes, soil types and a range of management practices (Guo & Gifford, 2002; McSherry & Ritchie, 2013; Paul et al., 2002; Schipper et al., 2010). This highlights the potential of different factors to work at different scales over time and space. Simultaneously, local farm effects can be overwritten by the characteristics and effect of soil type, climatic zone or altitude (Cierrad et al., 2015; Kumar et
104 al., 1992; Schipper et al., 2010). Active management of paddock soil moisture levels and pH was not unexpected as pastures and arable land was managed for these two characteristic in regard to pasture and crop growth worldwide (Rutledge et al., 2015). At the same time, other processes that influenced soil carbon stocks might dominate the effect of shelterbelt tree species at the landscape level and lead to a high level of variation between paddock and shelterbelt soil carbon stocks. For example, the effects of different land uses (McLauchlan, 2006), land use history (Verheyen et al., 1999), management (Jandl et al., 2007) and soil type (Schipper et al., 2007) all influenced soil carbon stocks at the paddock/shelterbelt scales of analysis, rather than farm or landscape scale. At the landscape level, excluding these diverse landscape effects from soil carbon stock assessments may lead to erroneous estimates. Therefore, including such effects in quantifying soil carbon stocks and attributes under shelterbelts could help to improve estimates.
Land use played a minor role in explaining the results of soil carbon stocks variability (Table 3-6). This minor role could first be reflected in the management of adjacent fields, resulting in spillover into the shelterbelt and the trimming or pruning of the shelterbelt itself. The role of farm and shelterbelt management on carbon stocks above- and below–ground has been identified by other studies as influencing these stocks (Didham et al., 2015; Appendix A). More recently, studies have been looking into spillover effects from managed pastures into non-productive land and vice versa. The results indicated that there is an effect on adjacent land, such as shelterbelts, but their magnitude was yet to be clarified (Allan et al., 2015; Blitzer et al., 2012; D’Acunto et al., 2014; Didham et al., 2015). While this study found that primarily fine scale variables, such as the shelterbelt type and local soil characteristics helped explained carbon stocks and their variability, the effects of land use around
shelterbelts warrant further investigation.
There have been very few studies that had gathered and analysed above- and below- ground biomass for carbon stocks assessment in shelterbelts and paddocks across the
agricultural landscape, particularly in New Zealand (Czerepowicz et al., 2012; Appendix A). This chapter, to my knowledge, presented the results of the first region wide assessment of above- and below-ground carbon stocks for native and exotic shelterbelts in New Zealand. The use of multiple biomass measures and farm characteristics across the landscape should enable the development of a more comprehensive picture of shelterbelt carbon stocks and their sequestration potential than was possible to date. Thus, the field-based, landscape-scale approach used in this study filled a gap in the shelterbelt carbon stock literature between
105 using satellite imagery to estimate above-ground carbon stocks in shelterbelts (Czerepowicz et al., 2012) and the information offered by other international assessments, but not New Zealand-specific, and investigations of shelterbelt carbon potential (Benhamou et al., 2013; Follain et al., 2007; Walter et al., 2003). In New Zealand, for example, much of what has been published about native species and their carbon stock potential comprised studies at a few sites with other settings (i.e. urban parkland) and not in the agricultural landscape (McGruddy, 2006; Schwendemann & Mitchell, 2014; Watson & Marden, 2004). The results from this study could be used to generate new hypotheses about possible causes and drivers of shelterbelt carbon stock variation and the direct species-specific research at national scales in order to best address the hypotheses.
This study has confirmed the great potential of shelterbelts in the agricultural
landscape for carbon sequestration, as observed by Falloon et al. (2004); Walter et al. (2003), thanks to the effects of shelterbelts or woody field margins on above- ground carbon stocks. Providing more accurate estimates of soil carbon stocks was a crucial step given the potential of carbon mitigation in the agricultural landscape. This study has highlighted the importance of estimating carbon stocks at the landscape scale by investigating different shelterbelt species. Until recently, there was a perception that using native species for shelterbelts and carbon storage above-and below- ground was not effective due to their different growth habits and a slightly more demanding establishment phase. Therefore, efforts were directed towards faster growing, less time-demanding species for shelter. These assumptions arose primarily from anecdotal stories within the farming community. However, the current results put both shelterbelt types on a similar basis in regard to carbon stocks (Figure 3-3 and Figure 3-4). In addition, using native species would create a more ‘natural’ shelterbelt system due to the presence of multi-aged species and diversity of both characteristics and growth rates (Anton et al., 2015; Cierrad et al., 2015). Kirby and Potvin (2007) noted that it is not only the amount of carbon sequestration that is important, but also the potential benefits through other ecosystem services native species would provide in the agricultural landscape. This may have future impacts in regard to the selection of shelterbelt species and potential benefits apart from carbon sequestration on farms.
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