Soil C and N as causal factors of spatial variation in extracellular enzyme activity across grassland-woodland ecotones
Introduction
Soil enzymes play a critical role in the environment through facilitation of the mineralization and hydrolysis of complex carbon (C), nitrogen (N) and phosphorus (P) compounds, thus mediating soil organic matter (SOM) decomposition (Burns et al., 2013). Depolymerisation of C compounds may involve cellulolytic (e.g. β 1,4-glucosidase EC 3.2.1.21 and cellobiohydrolase EC 3.2.1.91) or ligninolytic (e.g. phenol oxidase EC 1.10.3.2, lignin peroxidase EC 1.11.1.7) enzymes in soil (Saiya-Cork et al., 2002). On the other hand, decomposition of complex N or P compounds involves enzymes such as chitinase (EC 3.2.1.14) and phosphatase (EC 3.1.3.1), respectively. Depolymerised soluble substrates are then utilized by microbial communities involved in soil C, N and P cycling (Sinsabaugh et al., 2008). Soil enzymes are therefore commonly used as indicators of soil health and functionality of biotic communities (Burns et al., 2013). Identification of the causal factors that control the distribution patterns and activities of soil enzymes has thus been the focus of considerable research (Amador et al., 1997, Saiya-Cork et al., 2002, Šnajdr et al., 2008, Sinsabaugh et al., 2008).
Soil properties such as moisture (Baldrian et al., 2010), pH (Stursova and Sinsabaugh, 2008) and organic matter content (Allison and Vitousek, 2005, Sinsabaugh et al., 2008) have been shown to be major drivers of both microbial community structure and associated enzyme activities. However, soil represents a complex multidimensional environment and most soil properties exhibit non-random and characteristic heterogeneity (Banerjee et al., 2011, Goovaerts, 1998). Consequently, microbial enzyme activities may also vary in relation to the spatial distribution of soil properties across environments (Allison, 2005). Characterisation of the spatial dependence of soil enzymes can thus provide valuable insight, not only into distribution patterns but also the underlying drivers (Banerjee and Siciliano, 2012). Moreover, it is important to determine whether functionally different groups of enzymes (e.g. cellulolytic or ligninolytic) respond similarly to spatial variation in soil properties, and thus contribute to “decomposition hotspots” within ecosystems (Baldrian, 2014). Several studies have examined spatial variation in the activity of enzymes individually, both within and among different land-use systems such as cropland, grassland and forest (Baldrian and Větrovský, 2012, Baldrian, 2014, Baldrian et al., 2010, Šnajdr et al., 2008). However, information on the spatial distribution of soil enzymes across two land-use types (e.g. grassland to woodland) is limited. The area across two land-uses (i.e. ecotones) is particularly interesting because it may encompass biotic and abiotic interactions occurring between adjacent ecosystems and also incorporate aspects of the spatiotemporal characteristics of each ecosystem (Gosz, 1993). Spatial patterns of enzymes in grassland-woodland ecotones can reveal how their distribution changes between two adjoining land-uses.
A recent study has shown that the spatial structure of soil enzyme activities was associated with site-specific soil abiotic factors (Boeddinghaus et al., 2015). While the zone of spatial dependency (i.e. range) may vary with site-specific factors such as local topography and microclimatic conditions, it is also important to examine whether the distribution patterns and determinants of enzyme activities are consistent across sites by distinguishing causal relationships. Structural equation modelling (SEM) is one approach that can be used to delineate complex networks involving many response and predictor variables, to identify such causal relationships, and is thus widely used in soil ecological studies (Grace et al., 2010, Jonsson and Wardle, 2010, Lamb et al., 2011, McLeod et al., 2015).
In this study, we employed a multilevel approach to examine spatial patterns of soil enzyme activities and other soil properties at two grassland-woodland ecotone sites. Our objective was to assess: i) whether the spatial patterns of soil physicochemical properties and enzymes were consistent both within land-use at each site and across the two sites, ii) what edaphic factors were the causal factors of variation in enzyme activities, and iii) whether the drivers and spatial patterns for individual enzymes were consistent at both sites. We hypothesized that soil physicochemical properties and enzyme activities operated at similar spatial scales at each site, and that the drivers of enzyme activities were consistent between both land-use types and across sites.
Section snippets
Study sites and sampling design
The study was conducted at two sites with native woodland adjacent to grassland in south-eastern Australia. The first site was located at Bogo (34.813°S, 148.704°E) in the Bookham-Yass district of New South Wales. The native woodland at this site was dominated by Eucalyptus spp. with some Acacia dealbata and Acacia implexa (de Menezes et al., 2014, Prendergast-Miller et al., 2015). Patches of native Australian and exotic grasses were also common within the woodland. The adjacent grassland was
Effect of land use on soil properties and extracellular enzymes
Soil properties showed considerable variation between woodland grassland at Bogo and Namadgi National Park sites (Table 1). Overall, Bogo had more acidic soils with a relatively low fertility level. Woodland soils had typically higher level of C, N and P contents than grassland soils at Bogo. In particular, mineral N (NH4+ and NO3−) and P contents were 2-times higher in woodland than grassland soils. Consequently, all enzyme activities varied considerably between woodland and grassland soils at
Discussion
The multilevel approach employed in this study allowed us to progressively delineate the edaphic drivers of spatial variability in extracellular enzyme activities. This approach demonstrates that the soil C and N levels were the causal factors of enzyme activities both within and across land-uses, and across enzyme types (cellulolytic, ligninolytic, organic N-degrading and organic P-degrading), thus supporting our hypothesis of this study. In particular, enzyme activities were most strongly
Conclusion
Soil enzymes are ubiquitous in environments and play a critical role in SOM decomposition and nutrient cycling, and thus have been historically used as a surrogate for soil productivity. This is the first study to employ geostatistics, multivariate statistics and SEM to assess spatial patterns of soil enzyme activities and their causal factors. Our results demonstrate that despite the site-specific patterns, and irrespective of enzyme type, soil enzyme activities were consistently governed by
Acknowledgements
The authors thank Drs. Shamsul Hoque and Kelly Hamonts for assistance in field-work. We also thank the editor and two anonymous reviewers for their thorough review and insightful comments.
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