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Reprint of “Soil extracellular enzyme dynamics in a changing climate”
Soil Biology & Biochemistry 56 (2013) 53e59
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Review
Reprint of “Soil extracellular enzyme dynamics in a changing climate”q Hugh A.L. Henry* Department of Biology, University of Western Ontario, London, Ontario N6A 5B7, Canada
a r t i c l e i n f o
a b s t r a c t
Article history: Received 16 August 2011 Received in revised form 1 November 2011 Accepted 21 December 2011 Available online 15 November 2012
Assays for extracellular enzyme activity (EEA) have become a common tool for studying soil microbial responses in climate change experiments. Nevertheless, measures of potential EEA, which are conducted under controlled conditions, often do not account for the direct effects of climate change on EEA that occur as a result of the temperature and moisture dependence of enzyme activity in situ. Likewise, the indirect effects of climate on EEA in the field, that occur via effects on microbial enzyme producers, must be assessed in the context of potential changes in plant and soil faunal communities. Here, EEA responses to warming and altered precipitation in field studies are reviewed, with the goal of evaluating the role of EEA in enhancing our understanding of soil and ecosystem responses to climate change. Seasonal and interannual variation in EEA responses to climate change treatments are examined, and potential interactions with elevated atmospheric CO2, increased atmospheric N deposition and changes in disturbance regimes are also explored. It is demonstrated that in general, soil moisture manipulations in field studies have had a much greater influence on potential EEA than warming treatments. However, these results may simply reflect the low magnitude of soil warming achieved in many field experiments. In addition, changes in plant species composition over the longer term in response to warming could strongly affect EEA. Future challenges involve extending studies of potential EEA to address EEA responses to climate change in situ, and gaining further insights into the mechanisms, such as enzyme production, stabilization and turnover, that underlie EEA responses. Ó 2012 Elsevier Ltd. All rights reserved.
Keywords: Climate warming Extracellular enzyme activity Precipitation
1. Introduction Over the last decade, assays for extracellular enzyme activity (EEA) have become an increasingly common tool for examining soil microbial responses in climate change experiments (Weedon et al., 2011). Coupled with these assays being relatively easy to perform and inexpensive, they provide a useful integrative measure of microbial activity that complements other soil carbon and nutrient analyses (Allison et al., 2007). Such measures are critical for exploring the mechanisms whereby soil organic matter decomposition may respond to climate change, driving feedbacks between climate, ecosystems and atmospheric CO2 concentrations (Bengtson and Bengtsson, 2007). Extracellular enzymes are the “proximate agents of organic matter decomposition,” and key
DOI of original article: 10.1016/j.soilbio.2011.12.026. An error resulted in this article appearing in the wrong issue. The article is reprinted here for the reader’s convenience and for the continuity of the special issue. For citation purposes, please use the original publication details: Hugh A.L. Henry: Soil extracellular enzyme dynamics in a changing climate, 47C, pp. 53e59. * Tel.: þ1 519 661 2111x81548; fax: þ1 519 661 3935. E-mail address: [email protected]. q
0038-0717/$ e see front matter Ó 2012 Elsevier Ltd. All rights reserved. http://dx.doi.org/10.1016/j.soilbio.2012.10.022
enzymatic reactions include those involved in the degradation of cellulose and lignin, those that hydrolyze reservoirs of organic N such as proteins, chitin and peptidoglycan, and those that mineralize P from nucleic acids, phospholipids and other ester phosphates (Sinsabaugh et al., 2008). When these suites of enzymes are examined simultaneously, EEA can be used to infer shifts in microbial demand for carbon (including labile versus recalcitrant forms), nitrogen and phosphorus (Sinsabaugh and Moorhead, 1994). Despite these potential advantages, when shifts in EEA occur in response to climate change treatments, the underlying mechanisms can be unclear, with the direct effects of climate change treatments confounded with possible indirect effects (Kardol et al., 2010; Weedon et al., 2011). Specifically, measures of potential EEA, which are conducted under controlled conditions in the laboratory, often do not account for the direct effects of climate on enzyme activity in situ (Fig. 1 e solid line) (Wallenstein and Weintraub, 2008). Moreover, with respect to the indirect effects of climate on EEA, the direct effects of climate on enzyme production that occur via changes in microbial activity and community composition (Fig. 1 e dashed lines) are potentially confounded with or fail to properly account for the indirect effects of climate on soil microorganisms that occur via changes in plant
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H.A.L. Henry / Soil Biology & Biochemistry 56 (2013) 53e59
climate change
soil microorganisms
extracellular enzymes
N deposition
consumers
plants
CO2 atm
litter and SOM
disturbance
detritivores
Fig. 1. Conceptual framework outlining the distinctions among direct effects of climate on enzyme activity in situ (solid line), the effects of climate on enzyme production that occur via changes in microbial activity and community composition (dashed lines) and the indirect effects of climate on soil microorganisms (dotted lines). Global change drivers (climate, atmospheric N deposition, elevated atmospheric CO2 and disturbance) are indicated by the thick-bordered boxes. The box containing plants, consumers and detritivores is used to indicate that each of these groups is directly affected by climate and disturbance. For simplicity, the contributions of plant enzymes to the soil extracellular enzyme pool have been omitted.
and soil faunal communities (Fig. 1 e dotted lines). The goal of this paper is to explore trends in EEA responses to warming and altered precipitation in the context of climate change experiments. Furthermore, it will examine studies of interactions between EEA responses to climate change and other important global change factors, such as elevated atmospheric CO2, increased atmospheric N deposition and changes in disturbance regimes, including fire cycles and extreme climate events. EEA responses to climate change will be interpreted in the context of the conceptual framework illustrated in Fig. 1, in order to evaluate the potential role of EEA in enhancing our understanding of soil and ecosystem responses to climate change. 2. EEA responses to climate warming 2.1. Critical review of approaches used in warming experiments Numerous techniques have been developed for administering warming treatments, ranging from controlled environment experiments to field experiments involving open top chambers, greenhouses, retractable passive warming curtains, snow removal, heated coils/fluid filled tubes inserted into soil or overhead infrared heaters (see review by Shen and Harte, 2000). While often dictated by financial, logistical or spatial constraints, the selection of a given warming technique has important implications for the interpretation of EEA responses. For example, while the small size and rapid growth of microorganisms allows for meaningful microbial community level warming responses to be obtained from soil microcosms under controlled conditions in growth chambers, in these experiments it is difficult to examine potential interactions of EEA with other important ecosystem components (e.g. plants) over long time scales. In other words, as with controlled environment experiments in general (Newman et al., 2011), while these soil temperature manipulations are useful for providing a clear examination of specific mechanisms, the tradeoff is that they lack a high degree of realism or external validity. In contrast, in field experiments, the tradeoff of increased realism is generally one of decreased mechanistic understanding of EEA responses. Nevertheless, field experiments are also frequently challenged by shortcomings in spatial and temporal scale when assessing EEA
responses to climate change. For example, in mature forests, there are no viable options for warming tree canopies. Likewise, given the high cost of running infrastructure such as electric heaters in the field (Kimball et al., 2008), multiple treatment levels have been uncommon in these experiments, reducing the ability to assess possible non-linearities in EEA responses to variation in the magnitude of warming. When plots are warmed in the field, mobile organisms such as herbivores can also choose to feed preferentially in either warmed plots or the surrounding matrix, biasing plant warming responses (Moise and Henry, 2010), and potentially affecting EEA. Comparing among field warming techniques, passive warming using open top chambers and greenhouses is limited with respect to the maximum effect size on soil warming, and these methods can introduce artifacts by blocking rain, wind or animals (Marion et al., 1997). In addition, this infrastructure does not provide a simulation of warming over winter in snow-covered regions, where soil microorganisms may be vulnerable to increased soil frost in a warmer climate as a result of decreased snow cover (i.e. decreased insulation of soil from air) and subsequent exposure to cold air temperatures at night or during cold spells (Groffman et al., 2001). Alternatives that have been used to simulate climate warming over winter include snow removal, heated soil wires, fluid-filled pipes and overhead heaters. Snow removal (which simulates increased snow melt in a warmer climate) and heated wires are frequently used in forest systems, although these methods decouple soil warming from possible aboveground warming responses, such as changes in plant litter quality, that could affect EEA. The effects of snow removal experiments on microbial activity and EEA must also be interpreted with caution, given that extreme soil freezing can occur when snow removal coincides with extremely cold air temperatures, potentially exaggerating frost effects; thus, snow removal may best simulate reduced precipitation rather than warming (Henry, 2007). The installation of heating wires can disturb soil over the short term (Shen and Harte, 2000), and a source of electricity is required. Likewise, infrared overhead heaters require access to electricity, and the high running costs potentially limit the continuation of warming over the long term, such that the cumulative effects of warming on EEA responses that occur via long term changes in
H.A.L. Henry / Soil Biology & Biochemistry 56 (2013) 53e59
plant species composition and soil organic matter cannot be addressed. 2.2. Effects of warming on potential and in situ EEA in field experiments A main focus of EEA assays in the context of climate warming studies has been the potential contribution of warming to changes in atmospheric CO2 via enhanced soil organic matter decomposition. Mass flow models of C often assume that C flow is linked to warming via both temperature dependent microbial activity, which drives enzyme production, and the direct temperature dependence of enzyme activity in the soil (e.g. Bengtson and Bengtsson, 2007). Soil samples collected from warming experiments are typically analyzed for potential EEA at a single incubation temperature, which is useful because it provides a relative measure of changes in enzyme pool sizes in response to warming (i.e. it accounts for the factors responsible for changes in enzyme production, represented by the dashed and dotted lines in Fig. 1). Nevertheless, the temperature dependence of enzyme activity in the field (solid line in Fig. 1) is not addressed (Wallenstein et al., 2011). However, potential EEA can be measured over a range of temperatures to explore the temperature dependence of enzyme activity (Koch et al., 2007), and such data have been used, for example by Wallenstein et al. (2009), to model EEA in situ. The latter study revealed that overall, temperature was the strongest factor driving low in situ b-glucosidase activity in Arctic soils, but that N limitation may have also constrained enzyme activity over summer. Microbial activity can also decrease in response to warming when warming decreases soil moisture (Allison and Treseder, 2008). Traditional EEA assays conducted using soil slurries can address the effects of moisture limitation on changes in enzyme pool sizes, but they do not address the direct effects of soil moisture limitation on EEA in situ; however, a new technique developed by Steinweg (2011), in which a fluorogenic substrate is added directly to soil at a range of soil moistures and then later extracted, can potentially provide such data. For the latter study, even though moisture limitation decreased the b-glucosidase pool size, the in situ activity of this enzyme in dry plots was more responsive to increases in soil moisture than that of ambient plots. In addition, when combining the in situ temperature and moisture sensitivity models, temperature exerted the dominant control on enzyme activity, except when soil moisture was low, in which case the in situ activity predicted by temperature was hampered by moisture limitation. A potential shortcoming of this novel method is a reduced mixing of enzymes with the fluorogenic substrates in dry soils, although this mechanism may reflect the constraints of substrate diffusion in situ (Steinweg, 2011). In contrast to water limitation of in situ EEA in well-drained soils, in anaerobic peatland soils, a reduction in the water table depth caused by warming, and the resulting increase in oxygen availability, increased phenol oxidase activity by an order of magnitude (Freeman et al., 2001).
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In field experiments, the potential activities of both hydrolases and oxidative enzymes often have not responded significantly to warming treatments, as observed in Mediterranean shrubland (Sardans et al., 2007), annual grassland (Gutknecht et al., 2010) and temperate old fields (Bell et al., 2010; Kardol et al., 2010) (Table 1). However, in all of these studies, soil warming effects were relatively subtle (approximately 1 C). In particular, in experiments using overhead heaters, the observed soil warming relative to expected values can be low as a result of wind reducing the thermal radiation efficiency of the heaters (Kimball et al., 2008), and insulation of the soil by plant biomass and litter (Hutchison and Henry, 2010). Newer generations of warming experiments using more effective heating arrays may reveal more extreme effects on EEA. Nevertheless, site to site variation in warming effects on EEA also may contribute to variation among studies, as observed for invertase and sulfatase activity in sub-alpine forest soils (Xu et al., 2010). Given that potential EEA measured at a single temperature reveals the indirect effects of warming on enzyme activity via changes in enzyme pool sizes, it can be expected to vary in response to changes in enzyme turnover or production, with the latter influenced by changes in microbial biomass and community composition, or by changes in production at the level of individual microorganisms. When warming effects on EEA have been significant, there has been variation in whether the effects are significant based on total EEA (expressed per unit soil mass), versus changes in specific activity (expressed per unit of soil organic matter or microbial biomass). For example, in an annual grassland, warming effects on the activities of several hydrolase enzymes (a-glucosidase, N-acetyl-glucosaminidase and phosphatase) expressed per unit of microbial biomass were significant, whereas effects on the activities of these enzymes expressed per unit soil mass were not (Gutknecht et al., 2010). Such a result implies changes in microbial enzyme production independent of changes in microbial biomass. In contrast, in a heathland system, the activities of hydrolase enzymes increased in response to warming when expressed per unit SOM, but not when expressed per unit of microbial biomass (Sowerby et al., 2005). Microbial biomass also increased in response to warming, which indicated that the EEA response expressed per unit if SOM was driven primarily by microbial biomass. The latter observation was consistent with the finding that there was no significant variation among enzymes with respect to warming effects, even though the enzymes assayed (b-glucosidase, sulphatase, phosphatase and exopeptidase) were selected to target different nutrient cycles. Nevertheless, in the same study, the relationships between enzyme activities, SOM and microbial biomass differed among heathland sites. The distinction between total and specific EEA is important when using EEA to assess the contribution of warming to shifts in microbial nutrient demand. In particular, given the close association between soil microorganisms and plant roots, it is possible in some cases that changes in total EEA in response to climate change treatments merely reflect changes in root biomass. The latter trend was evident in an annual grassland
Table 1 Description of studies examining responses of potential EEA to warming treatments in the field. Bold letters in the final column denote enzymes that featured significant responses in activity on a per gram soil basis ([ e increased activity; Y e decreased activity). Study
Ecosystem
Treatment
Enzymes examined and responses
Sardans et al. (2007) Allison and Treseder (2008) Kardol et al. (2010) Xu et al. (2010) Henry et al. (2005) Gutknecht et al. (2010) Bell et al. (2010)
Mediterranean shrubland Boreal forest Temperate old field Spruce forest Annual grassland Annual grassland Temperate old field
Passive nightime warming curtains Passive warming greenhouses Open top chambers Open top chambers Overhead heaters Overhead heaters Overhead heaters
PT (rhizosphere) BG, GAP, NAG, PPO AG, BG, BXY, CBH, NAG, PPO, PO, PT, ST IN[, UR[ AG, BG, BX, CBH, NAG, PO þ PPO, PT AG, BG, BX, CBH, NAG, PT AG, BG, BX, CBH, NAG, PO, PPO, PT
Enzyme abbreviations: AG e a-glucosidase, BG e b-glucosidase, BX e b-xylosidase, CBH e cellobiohydrolase, GAP e glycine-aminopeptidase, IN e invertase, NAG e N-acetylglucosaminidase, PPO e polyphenol oxidase, PO e peroxidase, PT e phosphatase, ST e sulfatase, UR e urease.
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soil, where the responses of all hydrolases (polysaccharide degrading enzymes and phosphatase) to the climate change treatments were strongly correlated to each other and to changes in root biomass (Henry et al., 2005).
a EEA
3. EEA responses to altered precipitation 3.1. Review of approaches used in precipitation experiments
dry
Precipitation treatments are typically conducted in the field using either rainout shelters combined with water addition (Knapp et al., 2002), partial rainout shelters, retractable curtains (Toberman et al., 2008) or snow fences (Nobrega and Grogan, 2007). For a given region, climate projections can vary from increased drought to increased rainfall depending on the model that is used (IPCC, 2007), which can complicate the selection of precipitation treatments to simulate future soil conditions. Furthermore, treatments can be designed to vary the total amount, seasonal duration and temporal distribution of precipitation, and all of these factors can potentially affect soil microbial activity (Knapp et al., 2002).
anaerobic
b EEA
dry
mesic
wet
very dry
dry
wet
c
3.2. Effects of precipitation manipulation on potential and in situ EEA in field experiments In comparison with warming, the effects of water manipulation on the potential activities of both hydrolases and oxidative enzymes in field experiments have typically been large (e.g. Sardans et al., 2007; Kardol et al., 2010), although there has been variation among studies, with EEA responding strongly to drought (e.g. Sardans and Penuelas, 2005), not responding to drought (Yavitt et al., 2004) and responding to heavy rain instead of drought (Kreyling et al., 2008) (Table 2). Given the hypothetical quadratic response of EEA to soil moisture ranging from water-logged sites to dry soils (Fig. 2a), which is consistent with heathland data from Toberman et al. (2008), the context dependence of these results might be explained in part by variation among systems and years in soil moisture at the start of the water manipulation. Specifically, water drawdown in water saturated anaerobic soil can stimulate enzyme activity, whereas further drying can reduce enzyme activity by increasing water limitation (Fig. 2a). Similarly, in welldrained sites where precipitation is abundant, water addition may have less of an effect on EEA in wet years, whereas in dry sites, drought effects on EEA may be minimal (Fig. 2b and c). The latter mechanism can explain the pattern of the most severe drought effects on hydrolase enzyme activities being present in the northern, least moisture limited sites, in European heathlands (Sowerby et al., 2005). In agricultural systems, the addition of plant residues can also interact with moisture effects on EEA, as observed when the combination of increased moisture and the addition of residue from an oat-legume cover crop resulted in increased protease, b-glucosidase, glucosaminidase and exocellulase
EEA
Fig. 2. Hypothetical variation in EEA along moisture gradients in a) a poorly-drained soil, b) a well-drained soil receiving moderate to high mean annual precipitation, and c) an arid soil. The dashed lines and arrows represent changes in soil moisture in response to rainfall exclusion (a and c) or water addition treatments (b). In a), the direction of the EEA response varies depending on the initial soil moisture. In b) and c), the initial soil moisture is positioned such that the treatment effects on EEA are very mild.
activities, whereas in unamended soil, enzyme activities were little affected by soil moisture (Geisseler et al., 2011). The latter result led the authors to hypothesize that potential enzyme activities may be decoupled from moisture availability when substrates are limited.
4. Interaction of EEA responses to climate change with other factors 4.1. Interaction with season and year Even when they are statistically significant, the magnitude of EEA responses to climate change treatments can be low relative to seasonal variation in EEA (see review by Weedon et al., 2011) or to interannual variation in EEA (Gutknecht et al., 2010). Moreover,
Table 2 Description of studies examining responses of potential EEA to water manipulation treatments in the field. Bold letters in the final column denote enzymes that featured significant responses in activity on a per gram soil basis ([ e increased activity; Y e decreased activity). Study
Ecosystem
Treatment
Enzymes examined and responses
Sardans and Penuelas (2005) Kardol et al. (2010) Sardans et al. (2007) Toberman et al. (2008) Yavitt et al. (2004) Henry et al. (2005) Kreyling et al. (2008) Gutknecht et al. (2010)
Mediterranean oak forest Temperate old field Mediterranean shrubland Upland heathland Moist lowland tropical forest Annual grassland Temperate grassland and heathland Annual grassland
Runoff and rainfall exclusion Open top chambers Retractable rain curtains Retractable rain curtains Water addition during drought Water addition Rainout shelters, water addition Water addition
BGY, PRY, PTY, URY AG, BG, BXY, CBH, NAG, PO, PPOY, PT, ST PTY (rhizosphere) PPOY PT, ST AGY, BGY, BXY, CBHY, NAGY, PO D PPOY, PTY BG, BX, CBH, NAG[ (water addition), PT AGY, BGY, BXY, CBHY, NAGY, PTY
Enzyme abbreviations: AG e a-glucosidase, BG e b-glucosidase, BX e b-xylosidase, CBH e cellobiohydrolase, NAG e N-acetyl-glucosaminidase, PPO e polyphenol oxidase, PO e peroxidase, PR e protease, PT e phosphatase, ST e sulfatase, UR e urease.
H.A.L. Henry / Soil Biology & Biochemistry 56 (2013) 53e59
there is the potential for climate change effects to interact with seasonal and interannual variation in EEA. For example, in a rainfall and runoff exclusion experiment in a Mediterranean forest, treatment effects on acid phosphatase activity were significant over autumn, winter and spring, but not over summer (Sardans et al., 2008). Such a seasonal pattern of responses would obscure moisture effects on EEA if soil sampling only coincided with an annual summer plant harvest, as occurs for some long term climate change experiments. Similarly, in a temperate forest soil, seasonal variation in warming effects on protease activity were observed, with both warming and protein addition effects significant in spring, but only protein addition significant in summer (Brzostek and Finzi, 2011). The latter result led the authors to infer that substrate limitation may constrain EEA responses to climate warming. In a temperate old field soil, fine scale temporal variability in potential activities (i.e. sampling at 2e3 day intervals) was low for phosphatase, N-acetyl-glucosaminidase and b-glucosidase over summer, despite large variability in soil moisture and temperature within this season (Bell and Henry, 2011). Such a result could reflect the stabilization of enzymes on soil particles (Burns, 1982), as opposed to a constant rate of production and turnover, although differing rates of production and turnover could also lead to a balance between the two processes. Nevertheless, in the same study, phenol oxidase activity exhibited high temporal variability over summer. These results demonstrate the need to further examine the balances between enzyme production, turnover and stabilization that govern EEA responses to climate change. 4.2. Interaction with elevated atmospheric CO2 and increased atmospheric N deposition Potential interactions between climate change effects on EEA and elevated CO2 are important to consider, given that global warming and rising atmospheric CO2 concentrations are closely linked, and both factors have a strong influence on root exudation and plant litter inputs to soil (Fig. 1). Likewise, in many temperate, tropical and sub tropical regions, atmospheric N deposition will continue to rise substantially over the next 40 years (Galloway et al., 2004), with direct effects on both plants and soil microorganisms (Fig. 1). When the effects of all of these factors on the potential activities of hydrolytic and oxidative enzymes were examined simultaneously in an annual grassland soil, there were few significant interactions among CO2 or N addition with warming or precipitation, despite the significance of the main effects (Henry et al., 2005; Menge and Field, 2007). Likewise, despite significant interactions between climate manipulations and elevated CO2 in a temperate old field, water had the largest effect on the potential activities of hydrolytic and oxidative enzymes (Kardol et al., 2010). Overall, as a result of the multiplicative costs of conducting multifactorial field experiments, and the high cost of administering elevated CO2 treatments in the field, the interactive effects of multiple global change factors on EEA remain understudied. Therefore, the null results encountered to date may not adequately reflect the general importance of these interactions in affecting EEA. 4.3. Interaction with ecosystem disturbances (fire and extreme climate events) Climate change can indirectly affect extracellular enzyme production by altering disturbance regimes (Fig. 1). For example, climate change is expected to alter the frequency and intensity of disturbances such as fire (Flannigan et al., 2000). In an annual grassland, fire significantly affected the potential activities of
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hydrolases two years after burning, and while this effect interacted with elevated CO2 (both factors decreased EEA, but their effects were not additive), it did not interact with warming or water addition, and by the third year after burning, the effects of fire on EEA were no longer present (Gutknecht et al., 2010). However, in systems such as boreal forests, which feature much slower plant species turnover, an increased fire frequency could result in a larger fraction of the landscape being present in earlysuccessional stages. Such a projection prompted Allison et al. (2010) to measure the responses of hydrolase and phenol oxidase activities to warming in early successional boreal sites as a proxy for assessing future warming effects at the landscape level. Similar to fire, disturbance caused by extreme climate events such as frosts can potentially alter the successional trajectories of plant communities (Jentsch et al., 2007), affecting EEA indirectly over the long term.
5. Indirect effects of climate change on extracellular enzyme production e biotic feedbacks In Section 2 above, the distinction was made between the direct effects of climate on soil enzyme activity in situ and the indirect effects of climate mediated through changes in soil enzyme pool sizes, with the latter being revealed by measures of potential EEA. However, as displayed in the conceptual model in Fig. 1, there is a wide variety of mechanisms whereby climate change can indirectly affect EEA, ranging from the direct effects of climate on microbial enzyme producers (dashed line in Fig. 1) to the effects of climate (possibly via disturbance) on the plants, consumers and detritivores that influence microbial enzyme producers (dotted lines in Fig. 1). While considerable attention has been paid to EEA responses to climate change in the context of changes in soil microbial and individual plant function, longer term changes in plant species composition may ultimately have the largest effects on soil EEA (Kardol et al., 2010). An example is provided by the increased range of dwarf mistletoe (genus Arceuthobium) with warming, and the observation that infection of Pinus contorta by this holo-parasitic plant drastically increased the potential activities of laccase, lignin peroxidise, cellulose and manganese peroxidise in soil (Cullings and Hanely, 2010). Similarly, in contrast to the simplified conceptual framework displayed in Fig. 1, the soil bacteria and fungi that produce extracellular enzymes reside near the base of complex food webs; as described by Coleman et al. (2004), bacterial and fungal feeding nematodes, protozoa, and arthropods are themselves fed upon by predatory nematodes and micro, meso and macroarthropods, and soil microorganisms are further influenced by the activities of saprophagous arthropods or ecosystem engineers, such as ants and earthworms. Any of these soil fauna can be affected either directly or directly by climate change. Although it is intractable to study the simultaneous effects of all possible changes in plant and animal populations on EEA with climate change, insights into the relative strengths of direct versus indirect effects can be obtained by observing variation in EEA under different types of plant cover, or in the context of changes in soil fauna (e.g. correlations between EEA and soil nematode responses in Kardol et al., 2010). With respect to the latter, the application of soil enzyme and faunal community indices as indicators of changes in soil quality under contrasting management practices has increased over the last decade (Garcia-Ruiz et al., 2009). Nevertheless, beyond these studies that correlate plant and faunal species composition with soil EEA among sites, controlled experiments are needed that explore EEA responses to direct manipulations of plant and animal communities assigned randomly within a common soil type.
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Despite a focus in climate change studies on the role of EEA in regulating CO2 production, changes in EEA can also feed back on plant growth and species composition, particularly by modifying the availability of mineral nutrients. A proposed model of plante soil feedbacks in response to climate warming is that of shrub expansion in the Arctic, whereby changes in soil microclimate and litter quality brought about by an increased proportion of shrubs relative to graminoids results in reduced soil N availability over summer, further reducing the competitive abilities of the graminoids (Wookey et al., 2009). Do EEA assays provide valuable mechanistic information regarding such influential plantesoil feedbacks? In the case of N cycling, which constrains primary production across most terrestrial systems (LeBauer and Treseder 2008), the interpretation of EEA must be performed with caution. In particular, all of the commonly assayed extracellular enzymes associated with N acquisition (i.e. protease, N-acetylglucosaminidase, aminopeptidases, urease, amidase) also function as C acquiring enzymes, and therefore may not be directly coupled to microbial N demand. However, the assumption that N acquisition is the primary benefit of these enzymes activities may not be unreasonable, given the high metabolic cost of protein degradation relative to the degradation of cellulose and starch. 6. Conclusions Overall, despite the observation that responses of EEA to warming and precipitation treatments in field experiments have been context dependent and at times idiosyncratic, it is evident that climate change can have a strong influence on soil EEA, both directly and indirectly. Although few compelling data have been available to date, interactions with other global change factors may also play an important role in modulating EEA responses to climate change. Future challenges involve extending studies of potential EEA to address EEA responses to climate change in situ, where the temperature dependence of EEA, moisture effects on enzyme diffusion and substrate availability are all critical factors. The technique of incubating soils with fluorogenic substrates over a range of temperatures and soil moistures in the laboratory remains promising for obtaining data to parameterize models of EEA response to climate change in situ. As the proximate agent of organic matter decomposition in soil (Sinsabaugh et al., 2008) extracellular enzymes represent a key link in feedbacks between climate, ecosystems and atmospheric CO2 concentrations. Nevertheless, both the potential and limitations of using EEA dynamics to understand soil and ecosystem responses to climate change are dictated by our understanding of the mechanisms underlying EEA responses. The contributions of changes in above and belowground food web dynamics and changes in plant species composition to EEA climate change responses remain complex, but such factors must be considered when assessing the mechanisms driving changes in microbial enzyme production. Moreover, enzyme production is only one factor that determines enzyme pool sizes, and further insights into the mechanisms underlying changes in enzyme stabilization and turnover in response to climate change are needed. Acknowledgements This manuscript was based on a plenary talk presented at the 4th Enzymes in the Environment: Activity, Ecology, & Applications conference in Bad Nauheim, Germany. I thank R. Dick, M. Wallenstein, M. Weintraub and two anonymous reviewers for helpful feedback, and an NSERC Discovery Grant for funding support.
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Bengtson, P., Bengtsson, G., 2007. Rapid turnover of DOC in temperate forests accounts for increased CO2 production at elevated temperatures. Ecology Letters 10, 783e790. Brzostek, E.R., Finzi, A.C., 2011. Substrate supply, fine roots, and temperature control proteolytic enzyme activity in temperate forest soils. Ecology 92, 892e902. Burns, R.G., 1982. Enzyme-activity in soil e location and a possible role in microbial ecology. Soil Biology & Biochemistry 14, 423e427. Coleman, D.C., Crossley, D.A., Hendrix, P.F., 2004. Fundamentals of Soil Ecology. Elsevier Academic Press, San Diego, CA. Cullings, Ken., Hanely, J., 2010. Dwarf mistletoe effects on soil basidiomycete community structure, soil fungal functional diversity, and soil enzyme function: implications for climate change. Soil Biology & Biochemistry 42, 1976e1981. Flannigan, M.D., Stocks, B.J., Wotton, B.M., 2000. Climate change and forest fires. Science of the Total Environment 262, 221e229. Freeman, C., Ostle, N., Kang, H., 2001. An enzymic ‘latch’ on a global carbon store e a shortage of oxygen locks up carbon in peatlands by restraining a single enzyme. Nature 409, 149. Galloway, J.N., Dentener, F.J., Capone, D.G., Boyer, E.W., Howarth, R.W., Seitzinger, S.P., Asner, G.P., Cleveland, C.C., Green, P.A., Holland, E.A., Karl, D.M., Michaels, A.F., Porter, J.H., Townsend, A.R., Vorosmarty, C.J., 2004. Nitrogen cycles: past, present, and future. Biogeochemistry 70, 153e226. Garcia-Ruiz, R., Ochoa, V., Vinegla, B., Hinojosa, M.B., Pena-Santiago, R., Liebanas, G., Linares, J.C., Carreira, J.A., 2009. Soil enzymes, nematode community and selected physico-chemical properties as soil quality indicators in organic and conventional olive oil farming: influence of seasonality and site features. Applied Soil Ecology 41, 305e314. Geisseler, D., Horwath, W.R., Scow, K.M., 2011. Soil moisture and plant residue addition interact in their effect on extracellular enzyme activity. Pedobiologia 54, 71e78. Groffman, P.M., Driscoll, C.T., Fahey, T.J., Hardy, J.P., Fitzhugh, R.D., Tierney, G.L., 2001. Colder soils in a warmer world: a snow manipulation study in a northern hardwood forest ecosystem. Biogeochemistry 56, 135e150. Gutknecht, J.L.M., Henry, H.A.L., Balser, T.C., 2010. Inter-annual variation in soil extra-cellular enzyme activity in response to simulated global change and fire disturbance. Pedobiologia 53, 283e293. Henry, H.A.L., Juarez, J.D., Field, C.B., Vitousek, P.M., 2005. Interactive effects of elevated CO2, N deposition and climate change on extracellular enzyme activity and soil density fractionation in a California annual grassland. Global Change Biology 11, 1808e1815. Henry, H.A.L., 2007. Soil freeze-thaw cycle experiments: trends, methodological weaknesses and suggested improvements. Soil Biology & Biochemistry 39, 977e 986. Hutchison, J.S., Henry, H.A.L., 2010. Additive effects of warming and nitrogen deposition in a temperate old field: plant productivity and the importance of winter. Ecosystems 13, 661e672. Intergovernmental Panel on Climate Change (IPCC), 2007. Contribution of working group I to the fourth assessment report of the IPCC: summary for policymakers. Cited online: http://www.ipcc.ch. Jentsch, A., Kreyling, J., Beierkuhnlein, C., 2007. A new generation of climate-change experiments: events, not trends. Frontiers in Ecology and the Environment 5, 365e374. Kardol, P., Cregger, M.A., Campany, C.E., Classen, A.T., 2010. Soil ecosystem functioning under climate change: plant species and community effects. Ecology 91, 767e781. Kimball, B.A., Conley, M.M., Wang, S., Lin, X., Luo, C., Morgan, J., Smith, D., 2008. Infrared heater arrays for warming ecosystem field plots. Global Change Biology 14, 309e320. Knapp, A.K., Fay, P.A., Blair, J.M., Collins, S.L., Smith, M.D., Carlisle, J.D., Harper, C.W., Danner, B.T., Lett, M.S., McCarron, J.K., 2002. Rainfall variability, carbon cycling, and plant species diversity in a mesic grassland. Science 298, 2202e2205. Koch, O., Tscherko, D., Kandeler, E., 2007. Temperature sensitivity of microbial respiration, nitrogen mineralization, and potential soil enzyme activities in organic alpine soils. Global Biogeochemical Cycles 21, GB4017. Kreyling, J., Beierkuhnlein, C., Elmer, M., Pritsch, K., Radovski, M., Schloter, M., Wollecke, J., Jentsch, A., 2008. Soil biotic processes remain remarkably stable
H.A.L. Henry / Soil Biology & Biochemistry 56 (2013) 53e59 after 100-year extreme weather events in experimental grassland and heath. Plant and Soil 308, 175e188. LeBauer, D.S., Treseder, K.K., 2008. Nitrogen limitation of net primary productivity in terrestrial ecosystems is globally distributed. Ecology 89, 371e379. Marion, G.M., Henry, G.H.R., Freckman, D.W., Johnstone, J., Jones, G., Jones, M.H., Levesque, E., Molau, U., Molgaard, P., Parsons, A.N., Svoboda, J., Virginia, R.A., 1997. Open-top designs for manipulating field temperature in high-latitude ecosystems. Global Change Biology 3, 20e32. Menge, D.N.L., Field, C.B., 2007. Simulated global changes alter phosphorus demand in annual grassland. Global Change Biology 13, 2582e2591. Moise, E.R.D., Henry, H.A.L., 2010. Like moths to a streetlamp: exaggerated animal densities in plot-level global change field experiments. Oikos 119, 791e795. Newman, J.A., Anand, M., Henry, H.A.L., Hunt, S., Gedalof, Z., 2011. Climate Change Biology. CAB International, Cambridge, MA. Nobrega, S., Grogan, P., 2007. Deeper snow enhances winter respiration from both plant-associated and bulk soil carbon pools in birch hummock tundra. Ecosystems 10, 419e431. Sardans, J., Penuelas, J., 2005. Drought decreases soil enzyme activity in a Mediterranean Quercus ilex L. forest. Soil Biology & Biochemistry 37, 455e461. Sardans, J., Peñuelas, J., Estiarte, M., 2007. Seasonal patterns of root-surface phosphatase activities in a Mediterranean shrubland. Responses to experimental warming and drought. Biology and Fertility of Soils 43, 779e786. Sardans, J., Peñuelas, J., Ogaya, R., 2008. Experimental drought reduced acid and alkaline phosphatase activity and increased organic extractable P in soil in a Quercus ilex Mediterranean forest. European Journal of Soil Biology 44, 509e 520. Shen, K.P., Harte, J., 2000. Ecosystem climate manipulations. In: Sala, O.E., Jackson, R.B., Mooney, H.A., Howarth, R.W. (Eds.), Methods in Ecosystem Science. Springer, New York, pp. 353e369. Sinsabaugh, R.L., Lauber, C.L., Weintraub, M.N., Ahmed, B., Allison, S.D., Crenshaw, C., Contosta, A.R., Cusack, D., Frey, S., Gallo, M.E., Gartner, T.B., Hobbie, S.E., Holland, K., Keeler, B.L., Powers, J.S., Stursova, M., Takacs-Vesbach, C., Waldrop, M.P., Wallenstein, M.D., Zak, D.R., Zeglin, L.H., 2008. Stoichiometry of soil enzyme activity at global scale. Ecology Letters 11, 1252e1264. Sinsabaugh, R.L., Moorhead, D.L., 1994. Resource-allocation to extracellular enzymeproduction e a model for nitrogen and phosphorus control of litter decomposition. Soil Biology & Biochemistry 26, 1305e1311.
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Sowerby, A., Emmett, B., Beier, C., Tietema, A., Peñuelas, J., Estiarte, M., Van Meeteren, M.J.M., Hughes, S., Freeman, C., 2005. Microbial community changes in heathland soil communities along a geographical gradient: interaction with climate change manipulations. Soil Biology & Biochemistry 37, 1805e1813. Steinweg, J.M., 2011. Estimating in situ enzymes activity using continuous field soil moisture and temperature data, in: Sensitivity of microbial community physiology to soil moisture and temperature in an old field ecosystem. Ph.D. thesis, Colorado State University, Fort Collins, CO. Toberman, H., Evans, C.D., Freeman, C., Fenner, N., White, M., Emmett, B.A., Artz, R.R.E., 2008. Summer drought effects upon soil and litter extracellular phenol oxidase activity and soluble carbon release in an upland Calluna heathland. Soil Biology & Biochemistry 40, 1519e1532. Wallenstein, M.D., Allison, S., Ernakovich, J., Steinweg, J.M., Sinsabaugh, R., 2011. Controls on the temperature sensitivity of soil enzymes: a key driver of in-situ enzyme activity rates. In: Shukla, G., Varma, A. (Eds.), Soil Enzymology. Soil Biology, vol. 22, pp. 245e258. Wallenstein, M.D., McMahon, S.K., Schimel, J.P., 2009. Seasonal variation in enzyme activities and temperature sensitivities in Arctic tundra soils. Global Change Biology 15, 1631e1639. Wallenstein, M.D., Weintraub, M.N., 2008. Emerging tools for measuring and modeling the in situ activity of soil extracellular enzymes. Soil Biology & Biochemistry 40, 2098e2106. Weedon, J.T., Aerts, R., Kowalchuk, G.A., van Bodegom, P.M., 2011. Enzymology under global change: organic nitrogen turnover in alpine and sub-Arctic soils. Biochemical Society Transactions 39, 309e314. Wookey, P.A., Aerts, R., Bardgett, R.D., Baptist, F., Brathen, K.A., Cornelissen, J.H.C., Gough, L., Hartley, I.P., Hopkins, D.W., Lavorel, S., Shaver, G.R., 2009. Ecosystem feedbacks and cascade processes: understanding their role in the responses of Arctic and alpine ecosystems to environmental change. Global Change Biology 15, 1153e1172. Xu, Z.F., Hu, R., Xiong, P., Wan, C.A., Cao, G., Liu, Q., 2010. Initial soil responses to experimental warming in two contrasting forest ecosystems, Eastern Tibetan Plateau, China: nutrient availabilities, microbial properties and enzyme activities. Applied Soil Ecology, 291e299. Yavitt, J.B., Wright, S.J., Wieder, R.K., 2004. Seasonal drought and dry-season irrigation influence leaf-litter nutrients and soil enzymes in a moist, lowland forest in Panama. Austral Ecology 29, 177e188.
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Review
Reprint of “Soil extracellular enzyme dynamics in a changing climate”q Hugh A.L. Henry* Department of Biology, University of Western Ontario, London, Ontario N6A 5B7, Canada
a r t i c l e i n f o
a b s t r a c t
Article history: Received 16 August 2011 Received in revised form 1 November 2011 Accepted 21 December 2011 Available online 15 November 2012
Assays for extracellular enzyme activity (EEA) have become a common tool for studying soil microbial responses in climate change experiments. Nevertheless, measures of potential EEA, which are conducted under controlled conditions, often do not account for the direct effects of climate change on EEA that occur as a result of the temperature and moisture dependence of enzyme activity in situ. Likewise, the indirect effects of climate on EEA in the field, that occur via effects on microbial enzyme producers, must be assessed in the context of potential changes in plant and soil faunal communities. Here, EEA responses to warming and altered precipitation in field studies are reviewed, with the goal of evaluating the role of EEA in enhancing our understanding of soil and ecosystem responses to climate change. Seasonal and interannual variation in EEA responses to climate change treatments are examined, and potential interactions with elevated atmospheric CO2, increased atmospheric N deposition and changes in disturbance regimes are also explored. It is demonstrated that in general, soil moisture manipulations in field studies have had a much greater influence on potential EEA than warming treatments. However, these results may simply reflect the low magnitude of soil warming achieved in many field experiments. In addition, changes in plant species composition over the longer term in response to warming could strongly affect EEA. Future challenges involve extending studies of potential EEA to address EEA responses to climate change in situ, and gaining further insights into the mechanisms, such as enzyme production, stabilization and turnover, that underlie EEA responses. Ó 2012 Elsevier Ltd. All rights reserved.
Keywords: Climate warming Extracellular enzyme activity Precipitation
1. Introduction Over the last decade, assays for extracellular enzyme activity (EEA) have become an increasingly common tool for examining soil microbial responses in climate change experiments (Weedon et al., 2011). Coupled with these assays being relatively easy to perform and inexpensive, they provide a useful integrative measure of microbial activity that complements other soil carbon and nutrient analyses (Allison et al., 2007). Such measures are critical for exploring the mechanisms whereby soil organic matter decomposition may respond to climate change, driving feedbacks between climate, ecosystems and atmospheric CO2 concentrations (Bengtson and Bengtsson, 2007). Extracellular enzymes are the “proximate agents of organic matter decomposition,” and key
DOI of original article: 10.1016/j.soilbio.2011.12.026. An error resulted in this article appearing in the wrong issue. The article is reprinted here for the reader’s convenience and for the continuity of the special issue. For citation purposes, please use the original publication details: Hugh A.L. Henry: Soil extracellular enzyme dynamics in a changing climate, 47C, pp. 53e59. * Tel.: þ1 519 661 2111x81548; fax: þ1 519 661 3935. E-mail address: [email protected]. q
0038-0717/$ e see front matter Ó 2012 Elsevier Ltd. All rights reserved. http://dx.doi.org/10.1016/j.soilbio.2012.10.022
enzymatic reactions include those involved in the degradation of cellulose and lignin, those that hydrolyze reservoirs of organic N such as proteins, chitin and peptidoglycan, and those that mineralize P from nucleic acids, phospholipids and other ester phosphates (Sinsabaugh et al., 2008). When these suites of enzymes are examined simultaneously, EEA can be used to infer shifts in microbial demand for carbon (including labile versus recalcitrant forms), nitrogen and phosphorus (Sinsabaugh and Moorhead, 1994). Despite these potential advantages, when shifts in EEA occur in response to climate change treatments, the underlying mechanisms can be unclear, with the direct effects of climate change treatments confounded with possible indirect effects (Kardol et al., 2010; Weedon et al., 2011). Specifically, measures of potential EEA, which are conducted under controlled conditions in the laboratory, often do not account for the direct effects of climate on enzyme activity in situ (Fig. 1 e solid line) (Wallenstein and Weintraub, 2008). Moreover, with respect to the indirect effects of climate on EEA, the direct effects of climate on enzyme production that occur via changes in microbial activity and community composition (Fig. 1 e dashed lines) are potentially confounded with or fail to properly account for the indirect effects of climate on soil microorganisms that occur via changes in plant
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climate change
soil microorganisms
extracellular enzymes
N deposition
consumers
plants
CO2 atm
litter and SOM
disturbance
detritivores
Fig. 1. Conceptual framework outlining the distinctions among direct effects of climate on enzyme activity in situ (solid line), the effects of climate on enzyme production that occur via changes in microbial activity and community composition (dashed lines) and the indirect effects of climate on soil microorganisms (dotted lines). Global change drivers (climate, atmospheric N deposition, elevated atmospheric CO2 and disturbance) are indicated by the thick-bordered boxes. The box containing plants, consumers and detritivores is used to indicate that each of these groups is directly affected by climate and disturbance. For simplicity, the contributions of plant enzymes to the soil extracellular enzyme pool have been omitted.
and soil faunal communities (Fig. 1 e dotted lines). The goal of this paper is to explore trends in EEA responses to warming and altered precipitation in the context of climate change experiments. Furthermore, it will examine studies of interactions between EEA responses to climate change and other important global change factors, such as elevated atmospheric CO2, increased atmospheric N deposition and changes in disturbance regimes, including fire cycles and extreme climate events. EEA responses to climate change will be interpreted in the context of the conceptual framework illustrated in Fig. 1, in order to evaluate the potential role of EEA in enhancing our understanding of soil and ecosystem responses to climate change. 2. EEA responses to climate warming 2.1. Critical review of approaches used in warming experiments Numerous techniques have been developed for administering warming treatments, ranging from controlled environment experiments to field experiments involving open top chambers, greenhouses, retractable passive warming curtains, snow removal, heated coils/fluid filled tubes inserted into soil or overhead infrared heaters (see review by Shen and Harte, 2000). While often dictated by financial, logistical or spatial constraints, the selection of a given warming technique has important implications for the interpretation of EEA responses. For example, while the small size and rapid growth of microorganisms allows for meaningful microbial community level warming responses to be obtained from soil microcosms under controlled conditions in growth chambers, in these experiments it is difficult to examine potential interactions of EEA with other important ecosystem components (e.g. plants) over long time scales. In other words, as with controlled environment experiments in general (Newman et al., 2011), while these soil temperature manipulations are useful for providing a clear examination of specific mechanisms, the tradeoff is that they lack a high degree of realism or external validity. In contrast, in field experiments, the tradeoff of increased realism is generally one of decreased mechanistic understanding of EEA responses. Nevertheless, field experiments are also frequently challenged by shortcomings in spatial and temporal scale when assessing EEA
responses to climate change. For example, in mature forests, there are no viable options for warming tree canopies. Likewise, given the high cost of running infrastructure such as electric heaters in the field (Kimball et al., 2008), multiple treatment levels have been uncommon in these experiments, reducing the ability to assess possible non-linearities in EEA responses to variation in the magnitude of warming. When plots are warmed in the field, mobile organisms such as herbivores can also choose to feed preferentially in either warmed plots or the surrounding matrix, biasing plant warming responses (Moise and Henry, 2010), and potentially affecting EEA. Comparing among field warming techniques, passive warming using open top chambers and greenhouses is limited with respect to the maximum effect size on soil warming, and these methods can introduce artifacts by blocking rain, wind or animals (Marion et al., 1997). In addition, this infrastructure does not provide a simulation of warming over winter in snow-covered regions, where soil microorganisms may be vulnerable to increased soil frost in a warmer climate as a result of decreased snow cover (i.e. decreased insulation of soil from air) and subsequent exposure to cold air temperatures at night or during cold spells (Groffman et al., 2001). Alternatives that have been used to simulate climate warming over winter include snow removal, heated soil wires, fluid-filled pipes and overhead heaters. Snow removal (which simulates increased snow melt in a warmer climate) and heated wires are frequently used in forest systems, although these methods decouple soil warming from possible aboveground warming responses, such as changes in plant litter quality, that could affect EEA. The effects of snow removal experiments on microbial activity and EEA must also be interpreted with caution, given that extreme soil freezing can occur when snow removal coincides with extremely cold air temperatures, potentially exaggerating frost effects; thus, snow removal may best simulate reduced precipitation rather than warming (Henry, 2007). The installation of heating wires can disturb soil over the short term (Shen and Harte, 2000), and a source of electricity is required. Likewise, infrared overhead heaters require access to electricity, and the high running costs potentially limit the continuation of warming over the long term, such that the cumulative effects of warming on EEA responses that occur via long term changes in
H.A.L. Henry / Soil Biology & Biochemistry 56 (2013) 53e59
plant species composition and soil organic matter cannot be addressed. 2.2. Effects of warming on potential and in situ EEA in field experiments A main focus of EEA assays in the context of climate warming studies has been the potential contribution of warming to changes in atmospheric CO2 via enhanced soil organic matter decomposition. Mass flow models of C often assume that C flow is linked to warming via both temperature dependent microbial activity, which drives enzyme production, and the direct temperature dependence of enzyme activity in the soil (e.g. Bengtson and Bengtsson, 2007). Soil samples collected from warming experiments are typically analyzed for potential EEA at a single incubation temperature, which is useful because it provides a relative measure of changes in enzyme pool sizes in response to warming (i.e. it accounts for the factors responsible for changes in enzyme production, represented by the dashed and dotted lines in Fig. 1). Nevertheless, the temperature dependence of enzyme activity in the field (solid line in Fig. 1) is not addressed (Wallenstein et al., 2011). However, potential EEA can be measured over a range of temperatures to explore the temperature dependence of enzyme activity (Koch et al., 2007), and such data have been used, for example by Wallenstein et al. (2009), to model EEA in situ. The latter study revealed that overall, temperature was the strongest factor driving low in situ b-glucosidase activity in Arctic soils, but that N limitation may have also constrained enzyme activity over summer. Microbial activity can also decrease in response to warming when warming decreases soil moisture (Allison and Treseder, 2008). Traditional EEA assays conducted using soil slurries can address the effects of moisture limitation on changes in enzyme pool sizes, but they do not address the direct effects of soil moisture limitation on EEA in situ; however, a new technique developed by Steinweg (2011), in which a fluorogenic substrate is added directly to soil at a range of soil moistures and then later extracted, can potentially provide such data. For the latter study, even though moisture limitation decreased the b-glucosidase pool size, the in situ activity of this enzyme in dry plots was more responsive to increases in soil moisture than that of ambient plots. In addition, when combining the in situ temperature and moisture sensitivity models, temperature exerted the dominant control on enzyme activity, except when soil moisture was low, in which case the in situ activity predicted by temperature was hampered by moisture limitation. A potential shortcoming of this novel method is a reduced mixing of enzymes with the fluorogenic substrates in dry soils, although this mechanism may reflect the constraints of substrate diffusion in situ (Steinweg, 2011). In contrast to water limitation of in situ EEA in well-drained soils, in anaerobic peatland soils, a reduction in the water table depth caused by warming, and the resulting increase in oxygen availability, increased phenol oxidase activity by an order of magnitude (Freeman et al., 2001).
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In field experiments, the potential activities of both hydrolases and oxidative enzymes often have not responded significantly to warming treatments, as observed in Mediterranean shrubland (Sardans et al., 2007), annual grassland (Gutknecht et al., 2010) and temperate old fields (Bell et al., 2010; Kardol et al., 2010) (Table 1). However, in all of these studies, soil warming effects were relatively subtle (approximately 1 C). In particular, in experiments using overhead heaters, the observed soil warming relative to expected values can be low as a result of wind reducing the thermal radiation efficiency of the heaters (Kimball et al., 2008), and insulation of the soil by plant biomass and litter (Hutchison and Henry, 2010). Newer generations of warming experiments using more effective heating arrays may reveal more extreme effects on EEA. Nevertheless, site to site variation in warming effects on EEA also may contribute to variation among studies, as observed for invertase and sulfatase activity in sub-alpine forest soils (Xu et al., 2010). Given that potential EEA measured at a single temperature reveals the indirect effects of warming on enzyme activity via changes in enzyme pool sizes, it can be expected to vary in response to changes in enzyme turnover or production, with the latter influenced by changes in microbial biomass and community composition, or by changes in production at the level of individual microorganisms. When warming effects on EEA have been significant, there has been variation in whether the effects are significant based on total EEA (expressed per unit soil mass), versus changes in specific activity (expressed per unit of soil organic matter or microbial biomass). For example, in an annual grassland, warming effects on the activities of several hydrolase enzymes (a-glucosidase, N-acetyl-glucosaminidase and phosphatase) expressed per unit of microbial biomass were significant, whereas effects on the activities of these enzymes expressed per unit soil mass were not (Gutknecht et al., 2010). Such a result implies changes in microbial enzyme production independent of changes in microbial biomass. In contrast, in a heathland system, the activities of hydrolase enzymes increased in response to warming when expressed per unit SOM, but not when expressed per unit of microbial biomass (Sowerby et al., 2005). Microbial biomass also increased in response to warming, which indicated that the EEA response expressed per unit if SOM was driven primarily by microbial biomass. The latter observation was consistent with the finding that there was no significant variation among enzymes with respect to warming effects, even though the enzymes assayed (b-glucosidase, sulphatase, phosphatase and exopeptidase) were selected to target different nutrient cycles. Nevertheless, in the same study, the relationships between enzyme activities, SOM and microbial biomass differed among heathland sites. The distinction between total and specific EEA is important when using EEA to assess the contribution of warming to shifts in microbial nutrient demand. In particular, given the close association between soil microorganisms and plant roots, it is possible in some cases that changes in total EEA in response to climate change treatments merely reflect changes in root biomass. The latter trend was evident in an annual grassland
Table 1 Description of studies examining responses of potential EEA to warming treatments in the field. Bold letters in the final column denote enzymes that featured significant responses in activity on a per gram soil basis ([ e increased activity; Y e decreased activity). Study
Ecosystem
Treatment
Enzymes examined and responses
Sardans et al. (2007) Allison and Treseder (2008) Kardol et al. (2010) Xu et al. (2010) Henry et al. (2005) Gutknecht et al. (2010) Bell et al. (2010)
Mediterranean shrubland Boreal forest Temperate old field Spruce forest Annual grassland Annual grassland Temperate old field
Passive nightime warming curtains Passive warming greenhouses Open top chambers Open top chambers Overhead heaters Overhead heaters Overhead heaters
PT (rhizosphere) BG, GAP, NAG, PPO AG, BG, BXY, CBH, NAG, PPO, PO, PT, ST IN[, UR[ AG, BG, BX, CBH, NAG, PO þ PPO, PT AG, BG, BX, CBH, NAG, PT AG, BG, BX, CBH, NAG, PO, PPO, PT
Enzyme abbreviations: AG e a-glucosidase, BG e b-glucosidase, BX e b-xylosidase, CBH e cellobiohydrolase, GAP e glycine-aminopeptidase, IN e invertase, NAG e N-acetylglucosaminidase, PPO e polyphenol oxidase, PO e peroxidase, PT e phosphatase, ST e sulfatase, UR e urease.
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soil, where the responses of all hydrolases (polysaccharide degrading enzymes and phosphatase) to the climate change treatments were strongly correlated to each other and to changes in root biomass (Henry et al., 2005).
a EEA
3. EEA responses to altered precipitation 3.1. Review of approaches used in precipitation experiments
dry
Precipitation treatments are typically conducted in the field using either rainout shelters combined with water addition (Knapp et al., 2002), partial rainout shelters, retractable curtains (Toberman et al., 2008) or snow fences (Nobrega and Grogan, 2007). For a given region, climate projections can vary from increased drought to increased rainfall depending on the model that is used (IPCC, 2007), which can complicate the selection of precipitation treatments to simulate future soil conditions. Furthermore, treatments can be designed to vary the total amount, seasonal duration and temporal distribution of precipitation, and all of these factors can potentially affect soil microbial activity (Knapp et al., 2002).
anaerobic
b EEA
dry
mesic
wet
very dry
dry
wet
c
3.2. Effects of precipitation manipulation on potential and in situ EEA in field experiments In comparison with warming, the effects of water manipulation on the potential activities of both hydrolases and oxidative enzymes in field experiments have typically been large (e.g. Sardans et al., 2007; Kardol et al., 2010), although there has been variation among studies, with EEA responding strongly to drought (e.g. Sardans and Penuelas, 2005), not responding to drought (Yavitt et al., 2004) and responding to heavy rain instead of drought (Kreyling et al., 2008) (Table 2). Given the hypothetical quadratic response of EEA to soil moisture ranging from water-logged sites to dry soils (Fig. 2a), which is consistent with heathland data from Toberman et al. (2008), the context dependence of these results might be explained in part by variation among systems and years in soil moisture at the start of the water manipulation. Specifically, water drawdown in water saturated anaerobic soil can stimulate enzyme activity, whereas further drying can reduce enzyme activity by increasing water limitation (Fig. 2a). Similarly, in welldrained sites where precipitation is abundant, water addition may have less of an effect on EEA in wet years, whereas in dry sites, drought effects on EEA may be minimal (Fig. 2b and c). The latter mechanism can explain the pattern of the most severe drought effects on hydrolase enzyme activities being present in the northern, least moisture limited sites, in European heathlands (Sowerby et al., 2005). In agricultural systems, the addition of plant residues can also interact with moisture effects on EEA, as observed when the combination of increased moisture and the addition of residue from an oat-legume cover crop resulted in increased protease, b-glucosidase, glucosaminidase and exocellulase
EEA
Fig. 2. Hypothetical variation in EEA along moisture gradients in a) a poorly-drained soil, b) a well-drained soil receiving moderate to high mean annual precipitation, and c) an arid soil. The dashed lines and arrows represent changes in soil moisture in response to rainfall exclusion (a and c) or water addition treatments (b). In a), the direction of the EEA response varies depending on the initial soil moisture. In b) and c), the initial soil moisture is positioned such that the treatment effects on EEA are very mild.
activities, whereas in unamended soil, enzyme activities were little affected by soil moisture (Geisseler et al., 2011). The latter result led the authors to hypothesize that potential enzyme activities may be decoupled from moisture availability when substrates are limited.
4. Interaction of EEA responses to climate change with other factors 4.1. Interaction with season and year Even when they are statistically significant, the magnitude of EEA responses to climate change treatments can be low relative to seasonal variation in EEA (see review by Weedon et al., 2011) or to interannual variation in EEA (Gutknecht et al., 2010). Moreover,
Table 2 Description of studies examining responses of potential EEA to water manipulation treatments in the field. Bold letters in the final column denote enzymes that featured significant responses in activity on a per gram soil basis ([ e increased activity; Y e decreased activity). Study
Ecosystem
Treatment
Enzymes examined and responses
Sardans and Penuelas (2005) Kardol et al. (2010) Sardans et al. (2007) Toberman et al. (2008) Yavitt et al. (2004) Henry et al. (2005) Kreyling et al. (2008) Gutknecht et al. (2010)
Mediterranean oak forest Temperate old field Mediterranean shrubland Upland heathland Moist lowland tropical forest Annual grassland Temperate grassland and heathland Annual grassland
Runoff and rainfall exclusion Open top chambers Retractable rain curtains Retractable rain curtains Water addition during drought Water addition Rainout shelters, water addition Water addition
BGY, PRY, PTY, URY AG, BG, BXY, CBH, NAG, PO, PPOY, PT, ST PTY (rhizosphere) PPOY PT, ST AGY, BGY, BXY, CBHY, NAGY, PO D PPOY, PTY BG, BX, CBH, NAG[ (water addition), PT AGY, BGY, BXY, CBHY, NAGY, PTY
Enzyme abbreviations: AG e a-glucosidase, BG e b-glucosidase, BX e b-xylosidase, CBH e cellobiohydrolase, NAG e N-acetyl-glucosaminidase, PPO e polyphenol oxidase, PO e peroxidase, PR e protease, PT e phosphatase, ST e sulfatase, UR e urease.
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there is the potential for climate change effects to interact with seasonal and interannual variation in EEA. For example, in a rainfall and runoff exclusion experiment in a Mediterranean forest, treatment effects on acid phosphatase activity were significant over autumn, winter and spring, but not over summer (Sardans et al., 2008). Such a seasonal pattern of responses would obscure moisture effects on EEA if soil sampling only coincided with an annual summer plant harvest, as occurs for some long term climate change experiments. Similarly, in a temperate forest soil, seasonal variation in warming effects on protease activity were observed, with both warming and protein addition effects significant in spring, but only protein addition significant in summer (Brzostek and Finzi, 2011). The latter result led the authors to infer that substrate limitation may constrain EEA responses to climate warming. In a temperate old field soil, fine scale temporal variability in potential activities (i.e. sampling at 2e3 day intervals) was low for phosphatase, N-acetyl-glucosaminidase and b-glucosidase over summer, despite large variability in soil moisture and temperature within this season (Bell and Henry, 2011). Such a result could reflect the stabilization of enzymes on soil particles (Burns, 1982), as opposed to a constant rate of production and turnover, although differing rates of production and turnover could also lead to a balance between the two processes. Nevertheless, in the same study, phenol oxidase activity exhibited high temporal variability over summer. These results demonstrate the need to further examine the balances between enzyme production, turnover and stabilization that govern EEA responses to climate change. 4.2. Interaction with elevated atmospheric CO2 and increased atmospheric N deposition Potential interactions between climate change effects on EEA and elevated CO2 are important to consider, given that global warming and rising atmospheric CO2 concentrations are closely linked, and both factors have a strong influence on root exudation and plant litter inputs to soil (Fig. 1). Likewise, in many temperate, tropical and sub tropical regions, atmospheric N deposition will continue to rise substantially over the next 40 years (Galloway et al., 2004), with direct effects on both plants and soil microorganisms (Fig. 1). When the effects of all of these factors on the potential activities of hydrolytic and oxidative enzymes were examined simultaneously in an annual grassland soil, there were few significant interactions among CO2 or N addition with warming or precipitation, despite the significance of the main effects (Henry et al., 2005; Menge and Field, 2007). Likewise, despite significant interactions between climate manipulations and elevated CO2 in a temperate old field, water had the largest effect on the potential activities of hydrolytic and oxidative enzymes (Kardol et al., 2010). Overall, as a result of the multiplicative costs of conducting multifactorial field experiments, and the high cost of administering elevated CO2 treatments in the field, the interactive effects of multiple global change factors on EEA remain understudied. Therefore, the null results encountered to date may not adequately reflect the general importance of these interactions in affecting EEA. 4.3. Interaction with ecosystem disturbances (fire and extreme climate events) Climate change can indirectly affect extracellular enzyme production by altering disturbance regimes (Fig. 1). For example, climate change is expected to alter the frequency and intensity of disturbances such as fire (Flannigan et al., 2000). In an annual grassland, fire significantly affected the potential activities of
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hydrolases two years after burning, and while this effect interacted with elevated CO2 (both factors decreased EEA, but their effects were not additive), it did not interact with warming or water addition, and by the third year after burning, the effects of fire on EEA were no longer present (Gutknecht et al., 2010). However, in systems such as boreal forests, which feature much slower plant species turnover, an increased fire frequency could result in a larger fraction of the landscape being present in earlysuccessional stages. Such a projection prompted Allison et al. (2010) to measure the responses of hydrolase and phenol oxidase activities to warming in early successional boreal sites as a proxy for assessing future warming effects at the landscape level. Similar to fire, disturbance caused by extreme climate events such as frosts can potentially alter the successional trajectories of plant communities (Jentsch et al., 2007), affecting EEA indirectly over the long term.
5. Indirect effects of climate change on extracellular enzyme production e biotic feedbacks In Section 2 above, the distinction was made between the direct effects of climate on soil enzyme activity in situ and the indirect effects of climate mediated through changes in soil enzyme pool sizes, with the latter being revealed by measures of potential EEA. However, as displayed in the conceptual model in Fig. 1, there is a wide variety of mechanisms whereby climate change can indirectly affect EEA, ranging from the direct effects of climate on microbial enzyme producers (dashed line in Fig. 1) to the effects of climate (possibly via disturbance) on the plants, consumers and detritivores that influence microbial enzyme producers (dotted lines in Fig. 1). While considerable attention has been paid to EEA responses to climate change in the context of changes in soil microbial and individual plant function, longer term changes in plant species composition may ultimately have the largest effects on soil EEA (Kardol et al., 2010). An example is provided by the increased range of dwarf mistletoe (genus Arceuthobium) with warming, and the observation that infection of Pinus contorta by this holo-parasitic plant drastically increased the potential activities of laccase, lignin peroxidise, cellulose and manganese peroxidise in soil (Cullings and Hanely, 2010). Similarly, in contrast to the simplified conceptual framework displayed in Fig. 1, the soil bacteria and fungi that produce extracellular enzymes reside near the base of complex food webs; as described by Coleman et al. (2004), bacterial and fungal feeding nematodes, protozoa, and arthropods are themselves fed upon by predatory nematodes and micro, meso and macroarthropods, and soil microorganisms are further influenced by the activities of saprophagous arthropods or ecosystem engineers, such as ants and earthworms. Any of these soil fauna can be affected either directly or directly by climate change. Although it is intractable to study the simultaneous effects of all possible changes in plant and animal populations on EEA with climate change, insights into the relative strengths of direct versus indirect effects can be obtained by observing variation in EEA under different types of plant cover, or in the context of changes in soil fauna (e.g. correlations between EEA and soil nematode responses in Kardol et al., 2010). With respect to the latter, the application of soil enzyme and faunal community indices as indicators of changes in soil quality under contrasting management practices has increased over the last decade (Garcia-Ruiz et al., 2009). Nevertheless, beyond these studies that correlate plant and faunal species composition with soil EEA among sites, controlled experiments are needed that explore EEA responses to direct manipulations of plant and animal communities assigned randomly within a common soil type.
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Despite a focus in climate change studies on the role of EEA in regulating CO2 production, changes in EEA can also feed back on plant growth and species composition, particularly by modifying the availability of mineral nutrients. A proposed model of plante soil feedbacks in response to climate warming is that of shrub expansion in the Arctic, whereby changes in soil microclimate and litter quality brought about by an increased proportion of shrubs relative to graminoids results in reduced soil N availability over summer, further reducing the competitive abilities of the graminoids (Wookey et al., 2009). Do EEA assays provide valuable mechanistic information regarding such influential plantesoil feedbacks? In the case of N cycling, which constrains primary production across most terrestrial systems (LeBauer and Treseder 2008), the interpretation of EEA must be performed with caution. In particular, all of the commonly assayed extracellular enzymes associated with N acquisition (i.e. protease, N-acetylglucosaminidase, aminopeptidases, urease, amidase) also function as C acquiring enzymes, and therefore may not be directly coupled to microbial N demand. However, the assumption that N acquisition is the primary benefit of these enzymes activities may not be unreasonable, given the high metabolic cost of protein degradation relative to the degradation of cellulose and starch. 6. Conclusions Overall, despite the observation that responses of EEA to warming and precipitation treatments in field experiments have been context dependent and at times idiosyncratic, it is evident that climate change can have a strong influence on soil EEA, both directly and indirectly. Although few compelling data have been available to date, interactions with other global change factors may also play an important role in modulating EEA responses to climate change. Future challenges involve extending studies of potential EEA to address EEA responses to climate change in situ, where the temperature dependence of EEA, moisture effects on enzyme diffusion and substrate availability are all critical factors. The technique of incubating soils with fluorogenic substrates over a range of temperatures and soil moistures in the laboratory remains promising for obtaining data to parameterize models of EEA response to climate change in situ. As the proximate agent of organic matter decomposition in soil (Sinsabaugh et al., 2008) extracellular enzymes represent a key link in feedbacks between climate, ecosystems and atmospheric CO2 concentrations. Nevertheless, both the potential and limitations of using EEA dynamics to understand soil and ecosystem responses to climate change are dictated by our understanding of the mechanisms underlying EEA responses. The contributions of changes in above and belowground food web dynamics and changes in plant species composition to EEA climate change responses remain complex, but such factors must be considered when assessing the mechanisms driving changes in microbial enzyme production. Moreover, enzyme production is only one factor that determines enzyme pool sizes, and further insights into the mechanisms underlying changes in enzyme stabilization and turnover in response to climate change are needed. Acknowledgements This manuscript was based on a plenary talk presented at the 4th Enzymes in the Environment: Activity, Ecology, & Applications conference in Bad Nauheim, Germany. I thank R. Dick, M. Wallenstein, M. Weintraub and two anonymous reviewers for helpful feedback, and an NSERC Discovery Grant for funding support.
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