Strong seasonal dependency was observed in the temperature sensitivities (Q 10 ) of hydrolytic and
oxidative enzymes, whereas moisture sensitivity of β-glucosidase activities remained stable over the year. The range of measured enzyme Q 10 values was similar irrespective of spatial scale,
indicating a consistency of temperature sensitivities of these enzymes at large scales. Enzymes catalyzing the recalcitrant SOC pool exhibited higher temperature sensitivities than enzymes catalyzing the labile pool; because the recalcitrant C pool is relatively large, this could be important for understanding SOC sensitivity to predicted global warming. Response functions were used to model temperature-based and temperature and moisture-based in situ enzyme potentials to characterize seasonal variations in SOC decomposition. In situ enzyme potential explained measured soil respiration fluxes more efficiently than the commonly used temperature-respiration function, supporting the validity of our chosen modelling approach. As shown in the incubation experiment, increasing temperature stimulated respiration but decreased the total biomass of bacteria and fungi irrespective of substrate complexity, indicating strong stress responses by both over short time scales. This response did not differ between study areas and land-uses, indicating a dominant role of temperature and substrate quality in controlling microbial SOC decomposition. Temperature strongly influenced the responses of microbial groups exhibiting different life strategies under varying substrate quality availability; with soil warming, the abundance of oligotrophs (fungi and gram-positive bacteria) decreased, whereas copiotrophs (gram-negative) increased under labile C substrate conditions. Such an interactive effect of soil temperature and substrate quality was also visible at the taxon level, where copiotrophic bacteria were associated with labile C substrates and oligotrophic bacteria with recalcitrant substrates. Which physicochemical and biological factors might explain the observed alterations in microbial communities and their functions in response to climate change drivers at the regionalscale was investigated in the third study. Here, it was shown that the soil C:N ratio exerted scale-dependent control over soil basal respiration, whereas microbial biomass explained soil basal respiration independent of spatial scale. Factors explaining the temperature sensitivity of soil respiration also differed by spatial scale; extractable organic C and soil pH were important only at the landscape scale, whereas soil texture as a control was independent of spatial scale.
rate-limiting step of soilorganicmatterdecomposition (Schimel & Weintraub 2003). It has been shown that varying C and N availability affect extracellular enzyme activities (Gallo et
al. 2004, Allison & Vitousek 2005, Sinsabaugh et al. 2008). It is, however, not completely
clear, whether this is caused by changes in microbial metabolism or by microbial community dynamics. It has been suggested that the production of specific enzymes to acquire C, N and P would increase when assimilable nutrients are scarce and complex substrates are present (‘economical’ regulation on organism level) (Allison & Vitousek 2005, DeAngelis et al. 2008, Geisseler & Horwath 2009). However, as discussed above, the response of enzyme produc- tion to varying nutrients may also be controlled by changes in microbial community compo- sition. For example, N has been found to increase enzyme activities in low lignin litter, whereas it supressed ligninolytic enzyme activities in high lignin litters (Carreiro et al. 2000) . The reduced ligninolytic enzyme activity at high N availability may be caused either by sup- pressed enzyme production at the organism level or by a community shift, caused by a com- petitive disantvantage of the microbial group specialised on producing ligninolytic enzymes in high lignin litter. The latter would point to a strong control of the microbial community composition on the functional response to N addition. It is likely, however, that the overall regulation of exoenzyme activity by varying C and N input may be a combination of both, regulation of microbial metabolism and microbial community dynamics. Enzymes produced by a wide range of microorganisms (e.g. protease) may be regulated at a physiological level (Sinsabaugh et al. 2002, DeAngelis et al. 2008, Geisseler & Horwath 2008), whereas enzymes that are produced by specialized microbial taxa (e.g. ligninases, cellulases) may be affected to a larger extent by changes in microbial community composition resulting from different nutrient limitations. A vivid example for the close coupling between microbial community composition, resource availability and extracellular enzyme activities is the microbial succes- sion that occurs during litter degradation. At the beginning of litter decomposition when leachates consisting of low molecular weight compounds (e.g. sugars, amino acids) are still present, the microbial community is dominated by fast growing bacteria. Only with time, when easily available compounds get exhausted, bacteria are replaced by slow-growing fungi which are able to produce enzymes necessary to degrade lignin and other complex compounds of the decomposing leaf and the accumulated dead microbial biomass (Hat- tenschwiler et al. 2005).
3.1 Model verification at site and regional levels With the optimized parameters, MIC-TEM reproduces the carbon dynamics well for alpine tundra, boreal forest, tem- perate coniferous forest, temperate deciduous forest, grass- lands, and wet tundra with R 2 ranging from 0.70 for Ivotuk to 0.94 for the Bartlett Experimental Forest (Fig. S3, Table S3). In general, the model performs better for forest ecosystems than for tundra ecosystems. The temporal NPP from 2001 to 2010 simulated by MIC-TEM and TEM was compared with MODIS NPP data (Fig. S4). Pearson correlation coef- ficients are 0.52 (MIC-TEM and MODIS) and 0.34 (TEM and MODIS). NPP simulated by MIC-TEM showed higher spatial correlation coefficients with MODIS data than TEM (Fig. S5). By considering more detailed microbial activities, the heterotrophic respiration is more adequately simulated using the MIC-TEM. The simulated differences in soil de- composition result in different levels of soil-available nitro- gen, which influences the nitrogen uptake by plants, the rate of photosynthesis, and NPP. The spatial correlation coeffi- cient between NPP simulated by MIC-TEM and MODIS is close to 1 in most study areas, suggesting the reliability of MIC-TEM at the regionalscale.
uration level of directly available C also affects enzyme pro- duction. Enzyme production per unit of microbial biomass decreases with increasing available C (see Eq. 53), e.g., via catabolic repression of enzyme synthesis by the product of the reaction. This also corresponds to the fact that the frac- tion of cheaters – microbes that do not produce enzymes – increases with increasing available C. Cheaters were added as an explicit microbial functional group in an individual- based micro-scalemicrobial community model with the ex- plicit positioning of microbes to access substrate (Kaiser el al., 2015). Such an approach is only applicable in a micro- scale model, as the coexistence of cheaters and enzyme- producing microbes is only sustainable in heterogeneous en- vironments. In non-spatially explicit zero-dimensional mod- els, like ORCHIMIC, which assume a homogeneous envi- ronment, cheaters will always have a competitive advantage over other microbes in taking up C and N while not having to invest in enzyme production. This will eventually drive enzyme-producing MFTs to extinction at steady state (Alli- son, 2005); the model will not produce enzymes anymore and all microbes will die in the end. With the dynamic enzyme production mechanism described in Eqs. (51)–(55), cheaters can be included in ORCHIMIC in a possible coexistence with non-cheater microbes in the model, although cheaters are not parameterized in an explicit way as a separate MFT group.
A resource for urban and rural gardeners, small farmers, turfgrass managers and large-scale producers
“Soil is a living entity: the crucible of life, a seething foundry in which matter and energy are in constant flux and life is continually created and destroyed.” — Daniel Hillel, Out of Earth, 1991.
The mineral matter is made of sand, silt and clay size particles—the basic texture of the soil. The soil water contains dissolved minerals and is the main source of water and nutrients for plants. The air in the soil is needed for plant roots and soil microorganisms to obtain oxygen. Organicmatter includes plant and animal materials in various stages of decomposition. Some soil scientists think of living plant roots and soil microorganisms as part of the soilorganicmatter. Dead animal and plant matter begin to decompose as soon as they are added to the soil. Eathworms, beetles, springtails, and collembola, the macro (large) to meso (medium) fauna, begin to break large pieces of debris into smaller pieces. At the same time, the microbial population increases rapidly. The microorganisms consume the animal and plant remains and then die, adding themselves to the organicmatter. Some organicmatter is more readily decomposed than others. The end product of decomposition is humus—dark brown or black organicmatter that is highly resistant to further decomposition.
GF/F), placed on ice, and frozen until analysis. The next leachate was added after specific conductivity declined to a stable background value.
2.3.3 Chemical analysis and fluorescence
Samples from the uptake experiments were analyzed for concentration of Cl- and DOC. Samples of ambient stream water as well as diluted aliquots of each leachate were analyzed for DOC, total dissolved N (TDN), ammonium (NH 4 +), nitrate (NO 3 ), and total dissolved P (TDP). Chloride and NO 3 - concentrations were measured on an ion chromatograph (Dionex ICS 2100, AS18 column, Thermo Fisher Scientific) with limits of quantification (LOQ) of 0.03 mg Cl/L and 0.5 gg NO 3 - -N/L. DOC concentration was measured as non-purgeable organic C by non- dispersive, infrared gas analysis following combustion on a total organic C analyzer (TOC-L CPH, Shimadzu Scientific Instruments, LOQ = 0.1 mg C/L) connected to a TN module with detection of N by chemiluminescence (TNM-L, LOQ = 0.02 mg N/L). NH 4 + was measured by automated colorimetry (Smartchem 170, Westco Scientific Instruments, LOQ = 0.01 mg N/L) using the phenol hypochlorite method (Solorzano 1969). TDP was measured following persulfate digestion using the molybdate blue method (Murphy and Riley 1962) on a
The role of soilorganicmatter in agroecosystem Ante Bubalo
Organicmatter is an important factor in preservation of the global ecosystems and its presence in the soil is of crucial importance for the smooth running of several key soil functions. As the source of plant nutrients and the primary factor of soil structure, the role of organicmatter in the agroecosystem is reflected through the influence on physical, chemical and biological properties of the soil, the cycle of plant nutrients, mineralization process, sequestration of the nutrients, degradation of pollutants in the soil, control of the species and number of organisms in the soil, CO 2 etc. Reduction of the stock of organicmatter in soil by poor agricultural practice has also led to decrease in crop yield and biodiversity. Over the past few decades human activity has reduced the content of organicmatter and organic carbon in the soil causing many harmful effects like erosion, decrease of the soil vitality and intensified pest attack. Microorganisms play an important role in many vital processes that take place in the soil and it is of utmost importance to preserve soil biodiversity. There is a need for stronger control of the implementation of a set of activities that will reduce the losses of organicmatter and thereby halt the process of destroying biodiversity. There is a set of activities which help in the preservation and increase of soilorganicmatter such as compost usage, reduced soil treatment, increase in biomass production and green fertilization.
The soilmicrobial biomass behavior is also governed by ratio of carbon and nitrogen (C/N ratio). Fresh residues are relatively rich in carbon compared with nitrogen (C/N>20). Thus, during decomposition, soilmicrobial utilize reduced carbon as a respiratory substrate while accumulating carbon in the walls of their bodies (microbial biomass), these process is known as imobilization. In this process, N from organic residues, ammonium and nitrate ions from soil are also immobilized to microbial biomass. Imobilization is particularly evident during residues decomposition with high C/N ratio, favoring increase in microbial biomass, conform reported by TU et al. (2006), which examined how different regimes of organic management impact microbial biomass and activities, and determined how the resulting changes in microbial activities influence nutrient (N) availability for plants. The organic substrates used included composted cotton gin trash, animal manure and rye/vetch green manure. The results observed by authors showed that microbial biomass and microbial activity were generally higher in organic than in conventional managed soils, with cotton gin trash (higher C/N ratio) as the most effective. Straw mulching further enhanced microbial biomass, activity, and potential N availability by 42, 64, and 30%, respectively, relative to non-mulched soils, likely per improving C and water availability for soil microbes.
We performed simulations with the parameterized model to test whether the mixing of soil horizons, which may occur when sampling is done by depth rather than by horizon, influences the patterns shown in Figs. 1 , 2 and 4 . Mixing caused some systematic deviations; %N and %P values in mixed samples fell below the central trend of Fig. 1 , while N:C and P:C values fell below the model trend in Fig. 4 . However there was no deviation from the modelled P:C versus N:C trend of Fig. 2 . Inspection of data for samples from identified horizons showed that the largest deviations would occur for forest soils with O horizons overlying mineral horizons (mostly A, some E). Taking results for Swiss forest soils (data set SD_07 in Table S1), the most extreme differences in C concentration are found for an O horizon with c. 35 %C and an underlying mineral horizon with c. 1 %C. More typically, the concentrations are 35 and 5 %C respectively. We simulated these two cases using the model (Fig. S4). The results for the first pair of horizons show appreciable deviations for the modelled line, although within the data scatter,
The soil sampling was undertaken between July 2004 and March 2006 comprising the collection of a sample of topsoil from a site in every other square kilometre of the Irish National Grid, by simple random selection within each square, subject to the avoidance of roads, tracks, railways, urban areas and other seriously disturbed ground. This was part of the Tellus survey of Northern Ireland http://www.bgs.ac.uk/gsni/tellus/.There were 6862 sample sites in total. At each site soil was taken with a hand auger from between depths of 5 and 20 cm from five holes at the corners and centre of a square with a side of length 20 m and combined to form a bulked sample. All soil samples were air-dried in a dedicated temperature controlled oven at 30º C for between 2 and 3 days, disaggregated and sieved to less than 2 mm. From each a 50-g sub-sample was ground in an agate planetary ball mill. Loss on ignition (450ºC) was determined for the air-dried disaggregated fraction. These values were multiplied by 0.58 to give percent SOC equivalents. Replicate analyses were done to ensure accuracy and repeatability of results. The differences between replicate analyses were small. The SOC values from these 6862 soil sample data from the Tellus survey had a positively skewed distribution (Figure 2d) with a skew of 1.99 which was reduced to 0.94 upon log transformation. When these Tellus soil sample data were used in regression kriging logSOC was used. The SOC values from the Tellus survey points are shown in log form in Figure 3a to enable visual distinction given the large range of SOC values in Northern Ireland. A prediction set of 3000 samples was selected randomly and the other samples (n=3862) were used for validation.
Microorganisms in permafrost are considered psychrotolerant — that is, they can grow and reproduce in a subzero environment (Wilhelm et al., ZLKZ). In recent decades, high-throughput DNA sequencing data from soil microorganisms of the permafrost region have become available (Mackelprang et al., ZLKK; Taş et al., ZLKc; Yergeau et al., ZLKL). Surviving at a low temperature is challenging for bacteria. Therefore, they have developed a set of specific proteins to adapt to the cold, such as cold-shock proteins and proteins regulating membrane fluidity (reviewed by Jansson & Taş ZLKc). Nonetheless, microbial abundance and diversity in permafrost remain lower than those in the active layer (Steven et al., ZLLb; Wilhelm et al., ZLKK). Thus, permafrost thaw may increase microbial abundance and reshape the microbial community and functions. In addition, vegetation removal following a fire can considerably restructure the microbial community composition, selecting taxa clades better adapted to energy-limited environments (Fierer et al., ZLLb). Although the response of the microbial community to fire and warming has garnered considerable interest (Day et al., ZLK]; Taş et al., ZLKc; Woodcroft et al., ZLKX; Yuan et al., ZLKX), knowledge of the impact of fire on permafrost microbial communities remains scarce given the heterogeneity of permafrost and the complexity of diverse fire-induced environments (Carson and Zeglin, ZLKX; Sun et al., ZLKc).
Microorganisms are the source of many enzymes necessary for biochemical processes in soil, and are the driving agent for organicmatter turnover. In most situations, fungi constitute the bulk of the microbial community in soil. The bacteria often occur as the secondary population, and the actinomycetes form a minor component. Under anaerobic conditions, bacteria play an important role in the decomposition of soilorganicmatter. However, anaerobic bacteria operate at low rates in both decomposition and synthesis. Usually, a small portion of the microbial population is active at any one time, while the remaining is in dormant state due to the restriction of inadequate substrate supply or unfavourable environmental conditions.
abies) monoculture (Navratil et al., 2007). Altitude of the site is ranges between 829 and 949 m above sea level with a mean slope gradient of 11.5%. The region was not glaciated during Wisconsinan time, and soils are developed from residuum bedrock. Soils in the catchment are Dystric Cambisols. The catchment is drained by a perennial stream that begins at about 900 m above sea level. Lysina represents sites with acid-vulnerable soil and water environment due to base-poor rock (Kram et al., 2012). The main focus is on description of long-term hydro- biogeochemical patterns in the magnesium-poor and acid-sensitive Lysina catchment. Research activities have started in 1988 and include among others: study of element fluxes and pools, wet and dry deposition, internal recycling in trees, soil exchange processes, chemical weathering, nutritional status of trees and toxic metals speciations, modeling predictions of hydrologic, hydro-chemical and soil chemical status.
Soilorganicmatter (SOM) is related to the productivity of a soil. Because of this fact, maintaining SOM is an objective of many sustainable crop production systems. However, SOM tests are difficult to interpret by the laboratory that performs the analysis and meaningless for most growers. In the Southern U.S., 11 of the 13 state-supported public soil testing laboratories offer a SOM test upon request. North Carolina Department of Agriculture offers a "humic matter" test as an alternative. None of the public labs offers SOM as part of a standard soil fertility test, and none offers an interpretation for the grower. There is a reason for this omission. What does the test tell a farmer, a homeowner, a gardener, or a crop advisor about soil or crop management? Unlike the interpretation of soil pH or extractable soil P or K levels, there is no simple interpretation for SOM levels.
Although soils are considered as major carbon stores, rapid oxidation of soilorganic carbon can contribute to CO 2 evolution and global warming on a large scale. Generally, microbial and climatic factors are thought to be mainly responsible for such oxidative losses. Another probable factor is photodegradation by sunlight. Cultivated soils of the tropics are left barren for a greater part of the year particularly during summer when sunlight is at its peak intensity. This could cause photodecomposition of soilorganic constituents and account for rapid losses of soilorganic carbon. Studies showed that 2-14% of organic carbon in soils could be oxidized within 3 years by sunlight. This amounts to 5000-47,000 kg of CO 2 for every hectare of soil. Oxidation is not only due to the effect of light itself but also due to the heating caused by sunlight. Oxidative losses are higher in soils with higher levels of organic carbon and in soils of higher pH. It is suggested that covering soils with mulches or green cover during the fallow period in summer may be adopted to reduce photodegradative CO 2 losses from soils.
Concerns about SOM destabilization with climate change have generated increased urgency within the discipline in re- cent decades (Kirschbaum, 1995; Bradford, 2013; Billings and Ballantyne, 2013). Soil-focused literature is now replete with papers empirically describing temperature, moisture, or nutrient concentration effects on different SOM decay pro- cesses (e.g., Craine et al., 2010; Wagai et al., 2013; Man- zoni et al., 2012b; Tiemann and Billings, 2011a; Moyano et al., 2013). From these and related efforts, we have gained an appreciation for the apparent relevance of the carbon (C) quality hypothesis, which states that slowly decompos- ing SOM is more sensitive, in a relative sense, to tempera- ture changes than SOM that decays more quickly (Bosatta and Ågren, 1999). However, this response is not evident in some soils (Laganiere et al., 2015). We also have learned that historic conditions serve as a meaningful driver of con- temporary biogeochemical responses to varying conditions in soils (Evans and Wallenstein, 2012). We have appreciated the tremendous diversity of soilmicrobial communities and their rapidly varying composition as environmental condi- tions vary (Howe et al., 2014; Billings and Tiemann, 2014). There is growing recognition of an apparent lack of inher- ent recalcitrance of many SOM pools previously thought to be relatively stable, particularly those at depth (Fontaine et al., 2007; Schmidt et al., 2011), prompting considerations that temperature sensitivity may not vary with depth as much as previously thought. Recent modeling efforts, particularly those focusing on temperature and nutrient availability as drivers of microbial behavior, also have enhanced our ability to identify key factors important to SOM fate in a changing environment (e.g., Manzoni et al., 2012a).
legume cover crops are applied as the N source for following crops, cover crop properties (e.g., N percentage, C-to-N ratio, lignin content, and biomass), which determine the plant available N, are often regarded as the primary criteria for choosing legume species (Salmeron et al., 2011). Besides, competitive ability to weeds (Den Hollander et al., 2007) and pathogen resistance are important criteria as well, especially for organic systems where weeds and pests are mainly controlled by natural means. Higher seeding rate could stimulate higher cover crop dry mass, increase N availability, reduce N leaching, and suppress weed invasion; however, excessive seeding can cause harsh competition and be costly (Boyd et al., 2009; Brennan and Boyd, 2012; Brennan et al., 2009). Generally, broadcast seeding performed better in increasing cover crop biomass than no-till drill, although the effect was depended on climate conditions (Fisher et al., 2011). While fertilization is an optional management
Continuous cultivation of potato (Solanum tuberosum L.) in monoculture systems represents the greatest factor deteriorating soilorganicmatter (SOM) in smallholder farms. With an aim to breaking this norm, a 2-year ﬁ eld trial intercropping potato with two legumes: lima bean (Phaseolus lunatus) and dolichos (Lablab purpureus), was conducted in the upper-midland (1552 meters above sea level (masl.)), lower-highland (1854 masl.) and upper- highland (2552 masl.) agro-ecologies of Kenya. Residues from each cropping system were quanti ﬁ ed at the end of each season and incorporated back into the soil at start of the subsequent season. A combined physical and density fractionation was used to separate the soil in macro-aggregates (> 250 μ m), micro-aggregates (250 – 50 μ m) and silt plus clay fractions (< 50 μ m), while SOM was partitioned into labile (density of 1.65 to 1.85 g cm −3 ) and stable (2.60 g cm −3 ) fractions. Microbial biomass contents were determined by chloroform fumigation while enzymatic activities were assessed by hydrolyses of ﬂ uorescein diacetate and dehydrogenase. Compared to sole potato, intercropping increased the contents of light fraction organicmatter by 12 – 28%, dissolved organicmatter by 7–21% and microbial biomass by 15–38%, thus stimulating enzyme activities. Trends in soilmicrobial respiration followed those of enzyme activity and were 20 – 34% higher in intercropping than in sole potato. Intercropping ensured high residue returns which got short-term residence within the macro- aggregates, thus ensuring steady supply of substrates to the soil microbes. These results a ﬃ rm legume inter- cropping as a possible entry point to restoring the impoverished soil quality in smallholder potato farming systems.
Mangalassery, S. and Mooney, Sacha J. and Sparkes, D.L. and Fraser, W.T. and Sjögersten, Sofie (2015) Impacts of zero tillage on soil enzyme activities,
microbial characteristics and organicmatter functional chemistry in temperate soils. European Journal of Soil Biology, 68 . pp. 9-17. ISSN 1164-5563