Ground cover and organic nutrient management practices altering the denitrifier community in an organic apple orchard soil

Final Report for GS13-123

Project Type: Graduate Student
Funds awarded in 2013: $11,000.00
Projected End Date: 12/31/2015
Grant Recipient: University of Arkansas
Region: Southern
State: Arkansas
Graduate Student:
Major Professor:
Dr. Mary Savin
University of Arkansas
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Project Information

Summary:

Molecular analysis complemented investigation of the long-term changes in microbial communities and soil nutrients of an organic apple orchard receiving annual additions of ground cover and fertilizer treatments. Seven years of compost and wood chip applications resulted in the greatest soil organic matter (OM), and richest and most diverse denitrifier communities. However, dissolved organic carbon, OM, microbial biomass, and range-weighted richness of denitrifiers revealed different interactions among fertilizers and ground cover combinations. It is necessary to understand how those interactions affect the soil microbial community to properly manage for decomposition and nutrient cycling and to build soil quality.

Introduction

The purpose of this project is to provide organic fruit growers in the mid-southern U.S. useful information about how ground cover and organic fertilizer management practices affect N availability by understanding the impacts of practices on the microbial community and soil health. Microbial activity and the soil nutrient cycling services microbes provide play a significant role in healthy soil functioning. Excess NO3 can be leached out of the soil profile to groundwater or reduced to nitric oxide (NO), nitrous oxide (N2O), or dinitrogen (N2) during denitrification. Determining how repeated annual applications of ground covers and organic fertilizers have changed the denitrifier community will provide insight into the fate of N and ultimately the sustainability of these treatments.

Traditional analyses of samples collected beginning 2007 (organic matter (OM), size of N pools, microbial biomass, and enzyme activities) indicate that while microbial biomass and soil OM have increased from years of additions, treatments are differentiating in terms of dissolved organic C (DOC) and inorganic N. These analyses do not provide insight into the microbial community composition and thus provide an incomplete picture. Molecular techniques provide another tool and approach to open the “black box of microbial ecology” which will allow for unraveling of mechanisms responsible for processes underlying varying conditions. There is potential for denitrification to occur, especially in the treatments receiving compost (increased microbial biomass, organic C, and nitrate (NO3) concentrations) and in other ground covers, depending on the nutrient source.

Denitrification is a multiple-step pathway that ultimately reduces NO3 to N2, by nitrate, nitrite, nitric oxide, and nitrous oxide reductases (Zumpft, 1997). Genes code for the enzymes that catalyze these reductions. To gain insight into the community diversity and the relative contribution of organisms to this functional potential, denitrification genes can be analyzed. In this study, we were able to successfully target nirK coding for the nitrite reductase to better understand the community diversity and potential to contribute to terrestrial N loss. The nirK gene is a gene in the denitrification pathway that has been shown to work well in environmental samples using denaturant gradient gel electrophoresis (DGGE) (Throbäck et al., 2004).

Project Objectives:

1) Determine changes in the soil microbial community composition in response to seven years of annual ground cover and nutrient amendments to an organically managed apple orchard.

 

2) Determine if different annual ground cover and nutrient amendments result in various lengths of time before treatment effects are detected and differentiated at the 10-30 cm soil depth.

 

3) Determine if annual ground cover and nutrient amendments to an organically managed apple orchard have altered denitrification potentials.

Cooperators

Click linked name(s) to expand
  • Jade Ford

Research

Materials and methods:

Experimental Design

The 0.30-ha organic apple orchard used in this experiment is located at the University of Arkansas Main Agriculture Experiment and Extension Center in Fayetteville, Arkansas (36°N, 94°W). Enterprise cultivar apple trees with M26 rootstock were planted in 2006 on Captina (Fine-silty, siliceous, active, mesic Typic Fragiudult) and Pickwick (Fine-silty, mixed, semiactive, thermic Typic Hapludult) silt-loam soils (NRCS, 2014). Before planting, the area was tilled and leveled and lime and manure were added to adjust pH and organic matter. Soil properties at the beginning of the experiment in 2006 are shown in Table 1. The ground covers included urban compost (C), white shredded paper (P), wood chips (W), and a mow-and-blow control (M). Each ground cover treatment was applied to the surrounding tree area (2 x 2 m²) and two guard trees every April at a depth of 7.5-12 cm. Each ground cover also received composted poultry litter or commercial pelletized organic fertilizer at a rate of 50 g of N per tree per year of tree age, or no fertilizer (control). Average carbon, nitrogen, phosphorus and potassium concentrations for ground covers and fertilizers are shown in Table 2.

 

Soil Sampling, Storage and Characterization

Samples were collected annually in March and May from 0-10 and 10-30 cm depths. A sterilized soil probe was used to obtain the cores from sampling depths and soils were stored in sterile bags. A composite sample was obtained by collecting 8 cores randomly at least 15 cm from the trunk and within 60 cm between trees in a row and 45 cm between rows. Soil temperature at 10 cm depth was measured around each tree at the time of sampling. Soils were immediately placed on ice in the field, stored at 4°C upon return to the laboratory, sieved through a sterilized 2-mm sieve, and stored moist at 4°C with a subsample frozen at -80°C until extracted and analyzed.

Gravimetric soil water content was determined from soil (10 g) oven dried at 105? C for at least 24 hr until a constant weight was reached. All soil properties are expressed per gram of oven-dry soil. Electric conductivity (EC) and pH of the soil were measured potentiometrically using 1:2 soil-to-water ratio. Organic matter content was determined using loss-on-ignition (6 hr at 550 oC).

 

Extractable C and N, Microbial Biomass C and N and Total C and N

Microbial biomass C and N were measured using chloroform-fumigation extraction (Vance et al., 1987). Unfumigated and 24-hr chloroform-fumigated soil samples were extracted at 1:5 ratio (wt:vol) in 0.5 M K2SO4, shaken for 30 min, and filtered through Whatman #42 filters. A Shimadzu TOC-V PC-controlled total organic carbon and attached total N analyzer (Shimadzu, Columbia, MD) was used to determine the dissolved organic carbon (DOC), and dissolved total nitrogen (DTN) solution concentrations and microbial biomass was calculated from the difference in C and N concentrations between fumigated and unfumigated samples.

A single extraction approach (Jones and Willet 2006) was used to calculate DOC, DTN, nitrate-N (NO3-N), and ammonium-N (NH4+-N) per g dry soil from unfumigated soil samples. Concentrations of NH4+-N and NO3-N were determined colorimetrically using a Skalar segmented-flow autoanalyzer (Skalar Inc., Norcross, GA). The salicylate hypochlorite procedure was used to measure NH4+-N (Mulvaney 1996). Using a modified Greiss-Illosvay procedure, NO3-N was determined by utilizing Cd/Cu reduction of NO3 to NO2 (Mulvaney 1996). Nitrate-N and ammonium-N were summed to calculate inorganic N (Ni), and dissolved organic nitrogen (DON) was calculated by subtracting Ni from DTN (Jones and Willet, 2006).

 

PCR

DNA was extracted from soil (~500 mg) using the NucleoSpin Soil DNA Extraction Kit (Clontech Inc., Mountain View, CA) according to manufacturer’s protocol. Extracted DNA was quantified using spectrophotometry (ND2000, Thermo Fisher Scientific Inc., Waltham, MA). The nirK gene fragment was amplified with primers F1aCu [ATC ATG GT(C/G) CTG CCG CG] and R3Cu [GCC TCG ATC AG (A/G) TTG TGG TT] with a 33-bp GC-clamp (5’ GGC GGC GCG CCG CCC GCC CCG CCC CCG TCG CCC 3’) (Hallin, 1999; Throbäck et al., 2004). Reactions (25 µl) contained a final concentration of 1X PCR buffer (10 mM tris- HCl, 50 mM KCl, 0.01% (wt:vol) gelatin) 1.5 mM MgCl2, 200 µM each dNTP, 600 ng/µL BSA, 0.5 µM of each primer, 1.25 units of Taq polymerase (GoTaq®, Promega, Madison, WI) and 1 µl of 5 ng µL-1 template DNA for 0-10 cm samples. A PTC-200 DNA Engine (MJ Research Inc., Waltham, MA) thermal cycler was used to carry out PCR reactions. The following conditions were determined experimentally to optimize target amplification: initial denaturation   94 ?C for 2 min, 30 cycles of 94?C for 30 sec, 59?C for 45 sec, 72?C for 45 sec, and final extension 72?C for 7 min.

Amplification was confirmed by gel electrophoresis in 1.5% agarose gels which were digitally pictured with a Kodak EDAS 290 system and ID software package (Kodak, New Haven, CT). DNA mass standards (Bio Rad Laboratories, Hercules, CA) were used with each gel to confirm distance of migration and determine DNA concentration.

 

DGGE

The PCR amplified products (~ 20 µl) were loaded onto polyacrylamide DGGE gels for community profile creation. Protocols for F1aCu:R3Cu from Throbäck et al. (2004) were modified to suit the samples being analyzed. Vertical gels 1.0-mm thick containing 7% polyacrylamide (acrylamide:bisacrylamide ratio of 37.5:1) were electrophoresed in 1.5X TAE buffer (40 mM Tris-acetate and 1 mM EDTA, pH 8.0) at 90V and 60?C for 16 hrs in a D-code system (Bio Rad Laboratories, Hercules, CA). Linear gradients were created using 45% and 75% denaturant solutions (100% equal to 7 M urea and 40% deionized formamide). Gels were stained for 20 min with SYBR Green and digitally pictured using a Kodak EDAS 290 system and ID software package (Kodak, New Haven, CT).

Digital pictures of the gels were imported to Gel Compar II (Applied Maths Inc., Austin, TX) to analyze the presence or absence of bands and migration distances. Band detection and lane width were set to default values, with the exception of disk size to subtract background which was set to 10.0%. Software determination values for migration distances of detected bands were manually converted into a presence-absence table, where 0 designated the absence of a band, and 1 designated the presence of a band. A 3% optimization and 0.5 position tolerance were selected for the band matching settings. Unweighted pair group method with average linkage (UPGMA) cluster analysis and the dice similarity coefficient were used to create dendrograms. Total band number per lane represent species richness (R), and band intensities were normalized by dividing the individual band intensity by the greatest intensity on the gel to reduce potential differences due to staining or picture quality.

In addition to the traditional diversity indices (Shannon-Weaver and Simpson’s diversity indices), a more recent approach to community analysis was also used, calculating range-weighted richness (Rr) and functional organization (Fo) according to Marzorati et al. (2008). Range-weighted richness is a calculation that considers the width of the gradient used in DGGE and is considered to be related to the quality of environment for the microorganisms. The expectation is that a wider range in gradient is needed to capture a larger amount of genetic variability.

The functional organization analysis uses Pareto-Lorenz evenness curves (Lorenz, 1905) to plot DGGE data to determine the distribution of species in a community or the distribution of band intensity within a lane. The cumulative proportion of abundances (intensity) is plotted on the y-axis and the cumulative proportion of species (bands) is plotted on the x-axis. The 20% vertical axis line is used to score each curve. A 25% curve would represent a community with high evenness and low functionality. A 45% curve represents communities that are balanced, because some species are present in high numbers, but the majority of the species are present in decreasing amounts. This structure would be best suited to handle disruptions to the system. An 80% curve represents a community with few dominant species and many species present at low proportion; this community type can be highly functional under current conditions but is susceptible to changes in the environment.

 

Statistical Analyses

An analysis of variance (ANOVA) using SAS (version 9.4, SAS Institute Inc., Cary, NC) was performed to determine the effects of ground cover and fertilizer treatments and year on measured variables. The 0-10 cm and 10-30 cm depths were analyzed separately. The design was a 4 x 3 randomized complete block with three replications, which was treated as the whole plot portion with a split plot for year. During the DGGE analysis, some replications in the 0-10 cm depth were excluded because of low quality results, resulting in uneven sample sizes and a large number of least significant differences (LSD) to compare treatment means. To simplify the explanation of treatment effects, the most conservative LSD for each factor level was chosen to perform mean separations. Unless specifically noted in tables, significant differences at the whole plot level encompass differences at the split plot level. In the 10-30 cm depth, some DNA samples did not amplify well or at all during PCR, resulting in treatment combinations and/or blocks with only one replication for DGGE related measurements. Here an analysis of variance (ANOVA) was performed to determine the effects of ground cover and year on diversity indices excluding blocks and fertilizer.

Research results and discussion:

0-10 cm Soil Depth

There was a main effect of ground cover on pH (P = 0.0007, Table 3). The soil pH was highest in the paper treatment, followed by compost, with lower and similar soil pH under wood chips and in the mow-and-blow treatments (Table 4). Nitrate-N (NO3-N) concentrations were also affected by ground cover (P = 0.0256, Table 3) with concentrations highest in compost and wood chips (Table 4). Nitrate-N concentration in the mow-and-blow was not different from soil receiving wood chips, while soil nitrate-N concentration with paper was significantly lower than with wood chips. A main effect of year was observed for EC, water content, Bio N, NH4+-N, and NO3-N, which were all greater in 2013 than in 2007 (Tables 3 and 5).

There was a significant ground cover by fertilizer effect on DOC, Bio C, Bio N and OM (Table 3). Compost in combination with any fertilizer resulted in more DOC than any other treatment combination (Table 6). However, in the compost treatment, poultry litter had a negative effect on microbial biomass C concentrations and soil organic matter, with measurements lower than the no fertilizer control. Commercial fertilizer significantly increased DOC, Bio C, Bio N and OM in soil receiving wood chips compared to the no fertilizer control in that ground cover. Poultry litter fertilizer increased DOC, Bio N, and OM, but not Bio C in soil receiving wood chips compared to the no fertilizer control in that ground cover. There were no differences observed in mow-and-blow or paper treatments in response to fertilizers with the exception of Bio N in paper treatments increasing compared to the control with the addition of poultry litter and commercial fertilizer. Microbial biomass C and N followed the same numerical trends as each other in response to fertilizers across ground covers although differences were not always significant.

The interaction of ground cover and fertilizer had a significant effect on many of the diversity indices (Table 7). Richness was greater in communities where compost was applied in combination with any of the three fertilizer treatments compared to the other three ground covers in the absence of fertilizer (Table 8). Richness increased significantly in soil receiving commercial fertilizer and wood chips or the mow-and-blow compared to the absence of fertilizer, but not paper, and it decreased in the compost treatment compared to the absence of fertilizer. Soil receiving wood chips was the only treatment to increase in both richness and Shannon-Weaver diversity (H) in the presence of poultry litter or commercial fertilizer compared to the soil in that ground cover but the absence of fertilizer. Shannon –Weaver index of equitability (J) did not change much with fertilizer within a ground cover except with the mow-and-blow where, although richness increased, J decreased with commercial fertilizer compared to the absence of fertilizer. Functional organization did not show many large differences; however, Fo was lower in soil with poultry litter and paper compared to commercial fertilizer and paper.

There was a significant fertilizer by year interaction (Table 7). Fertilizer had a short-term effect on richness with commercial fertilizer increasing richness compared to no fertilizer and poultry litter in 2007 (Table 9). By 2013, richness increased such that it was greater than measured in 2007 and was similar across fertilizer treatments.

Ground cover treatments had varying effects on dissolved organic carbon (DOC), dissolved organic nitrogen (DON), microbial biomass carbon (Bio C), and organic matter (OM) depending on year (Table 3). Dissolved organic carbon showed a short-term response to ground cover in the compost treatment in 2007, measuring about twice the concentration as found in other ground covers (74 mg C g-1 compared to 32 – 44 mg C g-1; Table 10). By 2013, ground covers, with the exception of the mow-and-blow, increased DOC from the 2007 values, with largest concentrations continuing to be measured in the compost treatment. In contrast to DOC, DON decreased significantly through time in all ground covers except compost, which was greater in DON than other ground covers in both years. Microbial biomass C was lower in 2013 than 2007 in mow-and-blow and paper treatments, decreasing by about half in each treatment. Microbial biomass carbon did not vary by year with the addition of compost or wood chips. Organic matter increased over time regardless of ground cover treatment. There was an increase of organic matter over time in compost from 1.84 % in 2007 to the greatest overall organic matter of 5.29 %. Conversely, mow-and-blow control and paper increased to a lesser extent and was significantly lower in OM than in the wood chips and compost treatments in 2013.

In addition to the significant interactions of fertilizer and ground cover and fertilizer and year, all seven ecological indices were also significantly affected by the interaction of ground cover and year (Table 7). Species richness (R) was greatest in 2013 in soil receiving compost and wood chips compared to the other ground cover treatments in 2013, and R in those two ground covers increased significantly compared to richness in each respective ground cover in 2007 (Table 11). Shannon-Weaver index of diversity (H) in 2013 progressed from greatest to least in the order of compost ≥ wood chips ≥ paper ≥ mow-and-blow control with diversity in wood chips significantly increasing from among the lowest diversity in 2007 to among the highest diversity in 2013. Equitability either did not change through time or, in the wood chips treatment, decreased. Compost and paper were more even (J) than mow-and-blow and wood chips in 2013. The community in the compost treatment was more diverse than in mow-and-blow and wood chips in 2007 and was more diverse than in mow-and-blow and paper treatments in 2013. Simpson index of diversity (D) was affected similarly in 2007; communities where compost was applied had greater Simpson’s index value than other ground covers. The community in the wood chip treatment was only similar in Simpson’s index value to that in compost in 2013. Simpson’s diversity ranged in order from compost = wood chips > paper ≥ mow-and-blow control.

While richness increased markedly in the wood chips treatment, communities in 2007 were more even than 2013, according to both Shannon’s index of equitability (J) and Simpson’s index of equitability (E) (Table 11). Simpson’s index of equitability did not change through time in paper and the mow-and-blow control, but it decreased in compost and wood chips. Communities in compost and wood chips were more evenly distributed (E) than in mow-and-blow or paper treatments in 2007. Conversely, communities in paper showed greater evenness (E) than compost or wood chips in 2013. Mow-and-blow and paper treatments did not alter communities from 2007 and 2013 in calculations of the Shannon and Simpson indices. In 2007, compost communities had lower functional diversity than other communities. Functional organization (more species at higher abundances) increased from 2007 to 2013 in soil with compost, mow-and-blow and wood chips, but decreased during that time in soil from the paper treatment.

There was a ground cover by fertilizer by year effect on range-weighted richness (Rr) (P = 0.0069, Table 6). The only difference in Rr in 2007 was soils where compost was combined with poultry litter or no fertilizer was significantly greater than the same fertilizer treatment in the wood chips ground cover treatment (Table 12). The poultry litter with wood chip combination and compost with no fertilizer control combination were similar in 2013 and had the greatest range-weighted richness measured. Regardless of fertilizer, both compost and wood chip communities had greater range-weighted richness in 2013 than in 2007. Range-weighted richness did not vary in mow-and-blow and paper communities within a fertilizer combination between 2007 and 2013.

 

10-30 cm Soil Depth

A main effect of year was observed for multiple soil properties (Table 13). Soil OM and ammonium-N (NH4+-N) concentrations increased through time (Table 14). Microbial biomass carbon and nitrogen concentrations were significantly lower in 2013, with a large difference (56.6 mg C g-1) observed in Bio C over time (Table 14). Water content was also lower in 2013 than in 2007 (Table 14). There was a main effect of ground cover on organic matter content (P = 0.0445, Table 13) ranging in order from compost (1.78 %) ≥ wood chips (1.61 %) > paper (1.56 %) ≥ mow-and-blow control (1.46 %).

There was a ground cover by year effect on electrical conductivity (EC), pH, DOC, DON, and NO3-N (Table 13). There were no differences in EC among ground cover treatments in 2007 (Table 15). Electrical conductivity increased in all ground cover treatments through time such that in 2013 EC was highest in compost followed by wood chips, then paper, and finally the mow-and-blow control. The soil pH was similar in the paper and compost treatments in 2007, which was higher than in soils with mow-and -blow and wood chip additions. Compost, paper and wood chip additions all increased soil pH over time. Soil receiving paper had the highest pH in 2013, followed by compost and wood chips which were similar and higher in pH than the mow-and-blow. The only significant change in DOC over time within a ground cover was an increase with the addition of compost. There was both a short and long-term response in DOC in soils with compost addition, which increased DOC concentrations compared to mow-and-blow and paper additions in 2007 and in 2013. In 2007, there were no differences in DON concentrations. Compost, paper and wood chip additions all increased DON concentrations in soils over time, but DON concentrations were greater with compost applications compared to all other ground covers in 2013. Ground cover additions did not result in significantly different NO3-N concentrations in 2007. Compost followed by wood chips increased NO3-N through time and those treatments had higher concentrations in 2013 than soils with mow-and-blow and paper treatments.

Fertilizer and ground cover interactions had significant effects on DON and pH (Table 13). Soil DON concentrations were higher without the addition of fertilizer within all four ground cover treatments (Table 16). Wood chip additions in combination with poultry litter produced higher concentrations of DON than wood chips with commercial fertilizer. Although the same pattern of fertilizer effects on DON concentrations was present in other ground cover treatments, differences were not significant. Soil pH was highest with the addition of paper in the absence of fertilizer directly followed by commercial fertilizer. Compost and paper applied with any fertilizer had higher soil pH than all wood chips and mow-and-blow treatment combinations.

Fertilizer addition had significant effects on soil DON and NO3-N concentrations over time (Table 14). There were no differences in DON or NO3-N concentrations in 2007 among fertilizer treatments. In 2013, DON concentration was greatest in soils with no fertilizer addition, increasing 23.7 mg N g-1 from 2007 (Table 17), while the DON concentrations with commercial fertilizer and poultry litter were about 20 and 40%, respectively, of the value measured in the absence of fertilizer. Nitrate-N was greater in 2013 than 2007 and was greater in the presence, as opposed to the absence, of fertilizer.

There were no significant interactions or main effects of ground cover, fertilizer or year on the ecological indices calculated from the DGGE profiles (Table 18). Only 25 and 23 measurements were useable in 2007 and 2013, respectively, out of 36, limiting ability to detect significance in treatment effects. Richness, ranged from 24.43 to 35.17 in the 10-30 cm depth, in comparison, richness ranged from 22.2 to 45.0 in the 0-10 cm depth (Tables 9 and 19). On average, lower but not drastically different diversity index values were observed in the 10-30 depth than in 0-10 cm (Tables 9 and 19). Results may be indicating greater spatial variability in the movement of ground cover and fertilizer treatment effects below the surface 10 cm, making it more difficult at our sample size to detect treatment effects.

Literature Cited

Dandie, C.E., S. Wertz, C.L. Leclair, C. Goyer, D.L. Burton, C.L. Patten, B.J. Zebarth, and J.T. Trevors. 2011. Abundance, diversity, and functional gene expression of denitrifier communities in adjacent riparian and agricultural zones. FEMS Microbial Ecology 77:69-82.

 

Fischer, S.G., and L.S. Lerman. 1983. DNA fragments differing by single base-pair substitutions are separated in denaturing gradient gels: correspondence with melting theory. Proceedings of the National Academy of Sciences 80:1579–1583.

 

Hallin, S., C. M. Jones, M. Schloter, and L. Philippot. 2009. Relationship between N-cycling communities and ecosystem functioning in a 50-year-old fertilization experiment. The ISME Journal 3:597–605.

 

Jones, D.L., and V.B. Willett. 2006. Experimental evaluation of methods to quantify dissolved organic nitrogen (DON) and dissolved organic carbon (DOC) in soil. Soil Biology and Biochemistry 38:991–999.

 

Lorenz, M. O. 1905. Methods of measuring the concentration of wealth. Publications of the American Statistical Association. Vol. 9 (New Series, No. 70) 209-219.

 

Marzorati, M., L. Wittebolle, N. Boon, D. Daffonchio, and W. Verstraete. 2008. How to get more out of molecular fingerprints: practical tools for microbial ecology. Environmental Microbiology 10(6):1571-81

 

Mulvaney, R.L. 1996. Nitrogen: inorganic forms. In: Methods of Soil Analysis, Part 3: Chemical Methods. Soil Science Society of America, Inc. Madison, WI. Pp.1123-1184.

 

Muyzer, G., and K. Smalla. 1998. Application of denaturing gradient gel electrophoresis (DGGE) and temperature gradient gel electrophoresis (TGGE) in Microbial Ecology. Antonie Van Leeuwenhoek 73:127–141.

 

Natural Resources Conservation Service (NRCS). 2014. Web Soil Survey. Natural Resources Conservation Service, United States Department of Agriculture. Available at http://websoilsurvey.nrcs.usda.gov/app/ (verified 5 October 2015).

 

Rom, C.R., M.E. Garcia, J. McAfee, H. Friedrich, D.T. Johnson, J. Popp and M. Savin. 2010. The effects of groundcover management and nutrient source during organic orchard establishment. Acta Horticulturae 873: 105-113.

 

Throbäck, I. N., K. Enwall, A.A. Jarvis, and S. Hallin. 2004. Reassessing PCR primers targeting nirS, nirK and nosZ genes for community surveys of denitrifying bacteria with DGGE. FEMS Microbiology Ecology 49:401–417.

 

Vance E. D., P. C. Brookes, and D. S. Jenkinson. 1987. Microbial biomass measurements in forest soils: the use of the chloroform fumigation-incubation method in strongly acid soils. Soil Biology and Biochemistry 19:697-702.

 

Zumft, W. G. 1997. Cell biology and molecular basis of denitrification. Microbiology and molecular biology reviews 61(4):533-616.

 

Zumpft, W.G., A Dreusch, S. Lochelt, H. Cuypers, B. Friedrich, and B. Schneider. 2005. Derived amino acid sequences of the nosZ Gene (respiratory N2O reductase) from Alcaligenes eutrophus, Pseudomonas aeruginosa and Pseudomonas stutzeri reveal potential copper-binding residues. European Journal of Biochemistry 208:31–40.

 

 

Participation Summary

Educational & Outreach Activities

Participation Summary

Education/outreach description:

  1. Soil microbial and nutrient responses to seven years of ground cover management, Jade Ford, University of Arkansas, Fayetteville, AR, MS Thesis in progress.
  2. Ford, J, and M. Savin. 2015. Long term effects of organic orchard ground cover and fertilizer management on soil denitrifier community diversity. To be submitted to Appl. Soil Ecol. Publication in progress.
  3. Ford, J.N., M. Savin, and C.R. Rom. 2014. Denitrifier community response to seven years of ground cover and nutrient management practices in an organic apple orchard soil. In 2014 Annual Meeting Program. ASA, CSSA, and SSSA, Madison, WI. Available at https://scisoc.confex.com/scisoc/2014am/webprogram/Session13347.html (accessed 12/19/14).
  4. Savin, M.C. 2013. The impacts of organic apple production practices on soil. 32nd Annual Horticulture Industries Show, Horticulture Production & Food Safety: Making Good During Tough Times. Fort Smith, AR, Jan. 11-12.
  5. Ford, J., M.C. Savin, C. Rom, and J. McAfee. 2013. Mineralization and nitrification in soil altered by ground cover and nutrient source in an organic apple orchard. In 2013 Annual Meeting Program. ASA, CSSA, and SSSA, Madison, WI. Available at https://scisoc.confex.com/scisoc/2013am/webprogram/Paper79973.html [Accessed 12/19/13].

Project Outcomes

Project outcomes:

In 2001, a survey of local famers identified a need for reliable, regionally appropriate, and scale-neutral technology. Surveys indicated the growers were specifically interested in ground cover and weed management as well as nutrition recommendations (Rom et al., 2010). An experimental organic apple orchard was established in 2006, using SARE funds. The ground covers and fertilizers for applications were obtained locally and created a new use from “waste” items, contributing to the sustainability of the project.

Soil is the foundation of a healthy sustainable system, a physically and chemically complex matrix supporting a dynamic biological community. In contrast to annually tilled row crops, orchard soils are relatively undisturbed. A challenge in perennial systems involves determining how orchard soils respond to repeated annual additions of organic nutrient containing materials and decompose and build soil organic matter without promoting N losses. Orchards have been better studied in the northeastern and northwestern U.S., but the soils, climate, and pest pressures are different from those in the south, and producers in the south need regionally appropriate recommendations.

These results are indicating the short-term responses in microbial activity and organic matter additions from compost (treatment differences in 2007, one year after initiating treatments), but are also showing the long-term changes in communities and soil, in particular with wood chip treatments and compost. Compost and wood chips added most organic matter and had the greatest effect on microbial biomass of all ground covers. All ground covers increased organic matter after seven years of applications and impacted other soil properties and the microbial community. We are learning how ground covers such as wood chips respond in the long-term with the addition of fertilizer to build soil organic matter and rich, diverse soil denitrifier communities, but that poultry litter additions have the opposite response with compost additions.

Data analysis is continuing in order to fully assess denitrifier potential, community diversity and soil nitrogen concentrations. Because changes are of different magnitude and direction, we will be able to better manage perennial systems for healthy soils by understanding the interactions fertilizers and ground covers have on microbes. Microorganisms are the primary agents responsible for nutrient cycling. Furthermore, we continue to work with our collaborators to relate management impacts on soil microbial communities to impacts of treatments on tree health and pest management for comprehensive recommendations of organic orchards in the mid-southern U.S.

Farmer Adoption

Results of this project are being analyzed and written for a graduate thesis. They will be published and made available to the public to increase scientific understanding and to aid in ability to manage perennial systems in the mid-Southern U.S. Preliminary results have already been presented at two international scientific meetings, one regional producer meeting, and one local meeting in Fayetteville, AR. The orchard is used each semester in undergraduate laboratory courses to enhance hands-on learning. The public has been invited to field days and workshops in the orchard. Molecular diversity of microbial community data are complementing other data gathered from the orchard that are providing our research group with a more complete understanding of the organic orchard for systems management.

Recommendations:

Areas needing additional study

Continued analysis of microbial communities using molecular approaches to gain insight into the functional ecology of perennial systems is needed. Investigation of responses to interactions of fertilizer and ground cover require further investigation. Methods and approaches that untangle mechanisms and organisms within the black box of microbial ecology will allow us to understand how organisms respond to management and thus be better positioned to manage perennial systems for fertility. Our experimental design did not include changes in ground cover and nutrient application rates, which would have been beneficial from a practical standpoint and need investigation for producers. Also, a constant challenge in the established orchard was weed control. Addition of alternative cultural methods of weed control and how those interact with ground cover applications needs investigation as it is a real and pressing problem for orchard management. Implementing strategies such as tillage for weed control will have profound effects on decomposition of ground covers and fertilizers in response to physical disturbance. Finally, incorporation of more trophic levels of the food web in the investigation of the effects of ground cover management on soil biology should be included to comprehensively understand biological effects, and that understanding could contribute to both fertility and soil health management and pest control.

Any opinions, findings, conclusions, or recommendations expressed in this publication are those of the author(s) and do not necessarily reflect the view of the U.S. Department of Agriculture or SARE.