Land application of poultry manure and its influence on spectrofluorometric characteristics of dissolved organic matter

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Land application of poultry manure and its influence on spectrofluorometric characteristics of dissolved organic matter Shatrughan Singh a , Sudarshan Dutta b , Shreeram Inamdar b,∗ a b

Department of Geological Sciences, University of Delaware, Newark, DE 19716, USA Department of Plant and Soil Sciences, University of Delaware, Newark, DE 19716, USA

a r t i c l e

i n f o

Article history: Received 23 December 2013 Received in revised form 10 April 2014 Accepted 14 April 2014 Available online xxx Keywords: Dissolved organic matter (DOM) Excitation emission matrices (EEMs) UV absorbance Fluorescence spectroscopy Poultry manure Storm events Agricultural watershed

a b s t r a c t Land application of manure is a common practice that is used to supplement nutrients from fertilizers as well as to reuse and recycle waste in agricultural watersheds. Excess application of manure can however result in elevated exports of organic and inorganic nutrients in runoff. We evaluated the concentration and composition of dissolved organic matter (DOM) in runoff from cropland (corn) receiving poultry manure. Manure was applied once every three years at the rate of 9 Mg ha−1 in early spring and was incorporated into the soil during application. Surface runoff and soil water sampling was performed for eight natural storm events with one storm event prior to manure application. Samples were collected from the field edge, upland and lowland riparian zones and a receiving stream. Concentrations of dissolved organic carbon (DOC) were highest at the field edge (mean: 94 mg L−1 ) and then declined sharply for the riparian and stream locations. Temporally, DOC concentrations in field runoff were highest for the first storm event following manure application and then declined quickly over the next 1–3 weeks. DOM composition in runoff following manure application had low aromaticity and a microbial/tryptophan-like character. These characteristics evolved with time toward more aromatic, more humic, and a terrestriallike DOM composition. The decrease in runoff DOM was attributed to sorption and microbial degradation. Our observations suggest that while concentrations of DOM can be low in manure runoff, a short period (1–3 weeks) following manure application could be an environmentally sensitive and vulnerable period for runoff water quality. © 2014 Elsevier B.V. All rights reserved.

1. Introduction Land application of animal wastes is an important practice in many agricultural landscapes across the US. Animal manures provide an important source of nutrients for crops and can be used to supplement inputs from synthetic fertilizers. In addition, land application of manures allows reuse and recycling of the waste, a useful practice for states like Delaware which has a surplus of poultry manure (Dutta et al., 2012a,b; Pote et al., 2011; Sims, 1987). While the benefits of appropriately-applied and timed manure application are apparent, over-application and loss of manure with runoff can pose a threat to water quality (EPA, 2013). Runoff exports of inorganic nutrients like nitrogen and phosphorus from agricultural lands receiving manure application have been shown to enhance algal growth and eutrophication in aquatic ecosystems

∗ Corresponding author. Tel.: +1 302 831 8877. E-mail address: [email protected] (S. Inamdar).

(Diaz et al., 2010; EPA, 2013; Pote et al., 2011, 2003). Similarly, increasing attention is also being paid to emerging contaminants such as hormones and antibiotics in manure runoff (Dutta et al., 2012b; Hanselman et al., 2003; Lee et al., 2007). In contrast, few studies have investigated the impacts of organic constituents of manure such as dissolved organic carbon (DOC) and nitrogen (DON) and other humic and bioavailable constituents. These organic constituents can not only contribute to water quality degradation but can also impact a suite of other ecological processes and functions in aquatic ecosystems (Aitkenhead-Peterson et al., 2003; Bolan et al., 2011). Elevated organic C and N constituents can contribute to eutrophication of receiving surface waters (Seitzinger et al., 2002). Not surprisingly then, Stanley et al. (2012) have called for the need to pay greater attention to these organic constituents especially in landscapes impacted by human activities. The use of spectrofluorometric techniques has been valuable for characterizing the composition of dissolved organic matter (DOM) (Cory et al., 2011; Fellman et al., 2010). These techniques have been successful in discriminating DOM into humic, aromatic

http://dx.doi.org/10.1016/j.agee.2014.04.019 0167-8809/© 2014 Elsevier B.V. All rights reserved.

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and labile constituents and thus providing a better estimate of the water quality impacts of DOM (Fellman et al., 2010). Many of these studies have however been conducted in forested ecosystems (Inamdar et al., 2012, 2011) and their use in agroecosystems has only recently gained momentum (Baker, 2002; Dalzell et al., 2011; Graeber et al., 2012; Hunt and Ohno, 2007; Petrone et al., 2011; Vidon et al., 2008). Agricultural practices can dramatically alter the DOM response from watersheds. These practices include type and intensity of tillage, irrigation, types of crops grown and the harvesting practices adopted, use of synthetic and organic fertilizers including manure and other animal wastes, hydrologic modification through tile drainage and ditching, and alterations of riparian and wetland ecosystems (Stanley et al., 2012). The impact of these agricultural practices on watershed exports and composition of DOM has been mixed since some of the practices increase the supply/input of DOM in agricultural soils whereas others decrease the supply of C (e.g., tillage; Bolan et al., 2011; Stanley et al., 2012). Land application of manure can increase the organic matter and content of agricultural soils and therefore influence the amounts and character of DOM (Hunt and Ohno, 2007; Naden et al., 2010; Old et al., 2012). Most of these studies report an increase in the bioavailability of DOM through an increase in the tryptophan-like character of DOM (Naden et al., 2010; Old et al., 2012). However, many of the studies have been performed at laboratory and/or experimental plot scales. Studies are needed that investigate DOM under typical cropland settings where the seasonal timing, methods, and the rate of manure application are dictated by the agronomic needs of the crop. Our overall objective in this study was to determine how land application of poultry manure influences the concentration and spectrofluorometric composition of DOM in runoff and if this poses any threat to water quality. This work was conducted in a “working” cropland watershed on the coastal plain soils of Delaware (DE) and was part of a larger study that investigated manure-derived concentrations of hormones and antibiotics in runoff (Dutta et al., 2012b). Poultry manure was applied on the cropland by the farmer in early spring (April, 2010) prior to planting of crop. This timing of manure application is typical for agricultural lands in coastal DE. Runoff sampling for DOM was performed before and after manure application for multiple natural storm events from March through July 2010. Surface runoff and soil water samples were collected from the cropland edge, upper and lower riparian locations and a receiving stream. DOM composition of runoff samples was characterized using ultraviolet (UV) and fluorescence metrics. In addition to DOM, we simultaneously evaluated nitrate-N and ammonium-N concentrations in runoff and surficial soils following the approach of Naden et al. (2010). Elevated concentrations of ammonium-N in runoff from land receiving manure can be indicators of contamination from fresh manure (Naden et al., 2010). Ammonium concentrations in runoff can however decline with time because of nitrification and soil sorption and thus are indicative of transformation or ageing of manure. The shifts in DOM concentration and composition were evaluated in light of these changes in inorganic N. Specific questions that were addressed were:

(1). How does DOM in agricultural runoff change with time after manure application? (2). How does the concentration and composition of DOM change with landscape positions (field edge, riparian and stream locations)? (3). How does DOM from poultry manure compare against other agricultural sources and what are the broader environmental implications?

Fig. 1. (a) Location of study site in Delaware (inset). (b) Aerial view of sampling locations: field edge (FE1, FE2, and FE3), upland riparian (UL), lowland riparian (LR) and stream (ST). (c) Schematic illustrating the sampling locations along the hillslope transect (not to scale). (d) Schematic of sampling nests with the surface and subsurface flow samplers. Dashed lines indicate the screened portion of the PVC pipe where the runoff entered while the lower solid portion of the pipe is where the runoff was collected.

2. Site description and methods 2.1. Site description The study site and sampling locations have previously been described in Dutta et al. (2012b). Briefly, the study watershed is located near Middletown in New Castle County, Delaware (39.43◦ N, 75.67◦ W; Fig. 1). The watershed includes a 10 ha cropland that drains toward a riparian forest along the northwestern edge (Fig. 1). Average annual precipitation for New Castle County is 1130 mm (USDA-SCS, 1970). Precipitation during the summer is associated with low-pressure systems from the south that produce highintensity convective storm events. Rainfall data was available from a climate station located in Middletown, Delaware (DEOS, 2012) within 3 km of the study site. Average annual temperature is 54 ◦ F (12 ◦ C) with maximum temperatures occurring during the latter part of July. Corn (Zea mays L.) is the primary crop on the agricultural fields with wheat as a cover crop during the winter. In 2010, corn was planted during the first week of May with harvest during the month of September. The cropland has received conventional tillage every year for more than 5 years (as of 2010). Raw poultry manure has been applied to the fields once every 3 years, is typically applied only in spring, and is incorporated into the surface soil (5–10 cm) during application using a mechanical spreader. In 2010, manure was applied on April 10 at the rate of 9 Mg ha−1 (air-dry weight). This cropland did not have tile drainage. Runoff sampling “nests” were established at the field edge (FE), and at the upland (UR) and lowland riparian (LR) forest/wetland locations (Fig. 1). Each nest was composed of two PVC (13 cm diameter, 46 cm length) pipes—one for surface water (screened for a length of 15 cm above the soil surface with a lid on top) and the

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Table 1 Attributes for sampled rainfall events for the study period March–July 2010. Event no.

Date

Days after manure application

Total rainfall (mm)

Maximum event rainfall intensity (mm h−1 )

Rain duration (h)

1 2 3 4 5 6 7 8

March 28–29 April 13–14 April 24–27 May 11–12 May 17–19 June 9–10 June 22–23 July 9–12

NA* 4 17 32 39 61 74 93

35.6 5.8 39.4 13.5 25.7 4.3 19.8 62.5

10.7 1.8 12.2 3.8 2.8 2.8 15.2 5.3

15 7 54 31 28 5 2 83

Farmer applied the manure on April 10, 2010, i.e., 12 days after this event. * NA is not applicable.

other for soil water or subsurface flow, hereafter referred to as soil water (screened at 5–25 cm below the soil surface; see Fig. 1). Two of the field edge nests were located along the cropland-forest edge while the third was located at the edge of a grassed waterway (Fig. 1). The UR sampler was within the riparian zone but above the valley bottom whereas the LR sample was in the valley bottom. The soil at the LR location was wet for the duration of the study period indicating that some of the “soil water” was likely shallow groundwater upwelling at this location. Surface water samples for the stream (ST, Fig. 1) were collected manually following storms. All water samples from the sampling nests were bulk samples collected following storm events. The first set of water samples were collected following a rain event on March 29, 2010 (Fig. 2) prior to manure application and thus provide an estimate of the background concentrations. Thereafter, following poultry manure application on April 10, sampling was performed for a total of seven natural storm events of varying magnitude, intensity, and duration (Fig. 2 and Table 1) extending through July 2010. The sampling scheme and collection was defined and prioritized by the volumetric needs of the hormone and antibiotic sampling (Dutta et al., 2012b). Thus, while we did collect samples for DOM analyses for a majority of dates and locations there were some dates and locations where sufficient sample volume for DOM analysis was not available. We also recognize that it would have been preferable to have replicates for each sampling location to characterize the spatial variability of DOM (as we have indeed done for our other DOM studies—Inamdar et al., 2012). For the field edge location, data were averaged from all three locations (FE 1–3) (Fig. 1).

Fig. 2. Rainfall amounts (mm) and sampled runoff events during March–August 2010 (indicated by filled circles). Manure application occurred on April 10, 2010. The first runoff event sampled was prior to manure application on March 29.

2.2. Sample processing and chemical analysis All water samples were filtered through a 0.45 micron filter paper (Millipore Inc., Billerica, MA, USA) within 24 h of collection and stored at 4 ◦ C. Samples were stored in 40 ml amber glass vials prior to UV and fluorescence measurements. DOC concentrations were determined at the University of Delaware Soils laboratory using a Tekmar–Dohrmann Phoenix 8000 total organic carbon analyzer. In addition, inorganic N concentrations (NH4 –N and NO3 –N) were also determined for the water samples to evaluate them against DOC concentrations. Inorganic N was determined using BRAN + LUEBBE method no. US 696D-82X.

2.3. Spectroscopic analysis The EEMs of water samples were measured on a FluoroMax-3P fluorometer (Horiba Jobin Yvon Inc.; NJ, USA) with the excitation and emission wavelengths ranging from 240 to 450 nm (10 nm interval) and 300 to 550 nm (2 nm interval), respectively. Factorysupplied correction factors were applied to the scans to correct for instrument bias. The inner filter effects (IFEs) were corrected by measuring the UV–visible absorption spectra of the sample (McKnight et al., 2001) on a UV–visible single beam spectrophotometer (UVmini-1240; Shimadzu, MD, USA) from 190 to 1100 nm at 1.0-nm increments. Each EEM sample was corrected for Raman scattering and background signal by subtracting the EEM of a particle-free nanopure water (Barnstead nanopure water purification systems; Thermo Fisher Scientific Inc., MA) blank with a resistivity setting of 18.2 M. EEM scans were also normalized by dividing them by the Raman peak intensity of nanopure water blank at an excitation and emission wavelength pair of 350/397 nm to report in Raman Units (R.U.; nm−1 ) (Lawaetz and Stedmon, 2009). Finally, the EEMs were multiplied by the dilution factor (if samples were diluted) to obtain the fluorescence intensity for the original undiluted sample (Singh et al., 2010, 2013). The corrected EEMs (total = 46) were exported in MATLAB® 7.12 (MathWorks Inc., Natick, MA, USA) for PARAFAC modeling with the DOMFluor toolbox (ver. 1.7; Feb. 2009). PARAFAC modeling decomposes EEMs into distinct fluorophores (Stedmon et al., 2003; Stedmon and Bro, 2008). The PARAFAC model decomposed EEMs into four components (C1–C4) which accounted for 99% of the total variance in the data set. The fluorescence intensity of each component was expressed by Fmax (R.U., i.e., Raman units). Fmax provides a general estimate of the concentrations of each component (Stedmon and Markager, 2005). All of the four components (Table 2) have previously been identified and described in literature (Table 2). The component C1 has two excitation peaks at Ex < 250 (340) nm and a single emission peak at Em = 482 nm (Table 2). This fluorescent component can be ascribed to the allochthonous transport of terrestrial humic-like materials. The component C1 also resembles a mixture

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Table 2 PARAFAC modeled fluorescence components of DOM for this study and their comparison against those reported in the literature. Components (Ex/Em)

I

II

III

IV

V

VI

VII

Tentative DOM composition/sources

C1 (<250–340/482)

C3

C2

C1

C3

C1

C1

C2

C2 (320/402)

C4

C3

C2

C5

C2

C2

C6

C3 (270/314)

–

C5

–

–

C7

C3

C7

C4 (280/346)

C5

C4

C5

C6

C6

–

C5

Terrestrial humic-like. Soil derived DOM, common with agricultural and urban land use Microbial humic-like. Anthropogenic origin found in wastewaters and agricultural land where manure as fertilizers has been used Protein-like (Tyrosine-like) DOM. Common in groundwater sources. Found in relatively low abundance in wastewater treatment plant outflows and sewerage outfalls Protein-like (Tryptophan-like) DOM. Found in wastewater, industrial and livestock wastes, reported in animal manure and inorganic fertilizer applied croplands

I: Stedmon et al. (2003); II: Ohno and Bro (2006); III: Williams et al. (2010); IV: Abe et al. (2011); V: Murphy et al. (2011); VI: Zhang et al. (2011); VII: Graeber et al. (2012).

of previously identified peaks ‘A’ and ‘C’ (Coble et al., 1998). The predominance of this component has been noticed in many studies in terrestrial environments and in agricultural fields (Stedmon et al., 2003; Abe et al., 2011). The component C2 has a single excitation and emission peak at Ex/Em = 320/402 nm. This component has similar spectra to microbial humic-like materials as reported in previous studies (Table 2). The presence of this component has been found in animal farmyard wastes, industrial and municipal wastes, and in agriculture fields where animal manure has been used as fertilizers (Baker, 2002; Stedmon and Markager, 2005). We attribute the origin of this component to poultry manure application and relate its presence with microbially produced humic-like DOM materials (Stedmon and Markager, 2005). The component C3 closely resembles the fluorescence spectra of protein-like (tyrosine-like) materials. This component has a peak at Ex/Em = 270/314 nm. This component has been reported in many different aquatic environments and may be associated with autochthonous production and degradation of DOM (Table 2; Santín et al., 2009; Yamashita et al., 2008). The component C4 resembles protein-like (tryptophan-like) organic matter with peak at Ex/Em = 280/346 nm. Studies in agricultural watersheds have associated this fluorescence peak with animal manure applications (Baker, 2002; Naden et al., 2010; Old et al., 2012). Baker (2002) found elevated levels of protein-like (tryptophan-like) DOM fluorescence with farm wastes, municipal wastes, and wastewater treatment outflows. Likewise, Ohno and Bro (2006) have found elevated percentage contributions of this component in laboratory experiments with animal manures. Following Weishaar et al. (2003), the specific UV absorbance (SUVA254 ) was determined by the ratio of UV absorbance at 254 nm and the DOC concentration (mg L−1 ). The humification index (HIX) was calculated as the ratio of the integrated fluorescence intensity from 435 to 480 nm to the summation of two fluorescence regions (300 to 345 nm and 435 to 480 nm) (Ohno, 2002). HIX values ranged from 0 to 1 with higher values indicating more humic DOM. The fluorescence index (FI) was calculated as the ratio of fluorescence emission intensity at 470 to that at 520 nm at an excitation wavelength of 370 nm (Cory and McKnight, 2005; Cory et al., 2010). This index allows for discrimination between terrestrial (<1.5) and microbial (>1.6) sources of DOM (McKnight et al., 2001). The spectral slopes in two UV spectral regions (shorter UV, S1: 275–295 nm and longer UV, S2: 350–400 nm) were calculated as a linear fit to logarithmically transformed absorption spectra. Following these measurements, spectral slope ratios were calculated as SR = S1/S2. This ratio is inversely related to DOM molecular weight (MW) with low values of SR indicating high MW and vice-versa (Helms et al., 2008).

2.4. Sampling of raw poultry manure and cropland soils Random grab samples of raw solid poultry manure were collected in mid-March from the manure pile that was stacked on the cropland to air-dry prior to its application. In addition, surficial (0–10 cm) soil samples were also collected from the three field edge locations following each storm event prior to and after manure application. These field edge soil samples were composited into one sample and analyzed at the University of Delaware soils laboratory on an Elementaar VarioMax CN by following Dumas method and reported as % C and % N.

2.5. Statistical analysis Comparison between landscape positions and between runoff events were tested using non-parametric Wilcoxon rank sum test for each pair on DOM parameters at p ≤ 0.10 unless stated otherwise. Non-parametric tests were used since the sample size was small and did not meet parametric test assumptions. All the statistical analyses were performed in JMP® Pro 10.0.2 (SAS Institute Inc., Cary, NC) or MATLAB® 7.12 (MathWorks Inc., Natick, MA).

3. Results 3.1. Changes in surface runoff and soil water DOM with time after manure application DOM concentrations and composition changed substantially with time following poultry manure application (Figs. 3–8). The overall temporal trends were: (a) the DOC concentrations were highest for the April 14 event and then declined dramatically with time; (b) the DOM metrics that revealed the largest changes were SUVA, SR , and FI; (c) SUVA values were lowest following the April 14 storm event indicating low aromaticity; (d) SR values were highest at the riparian locations for the event of April 14 and then declined indicating that DOM changed from low molecular weight to high molecular weight constituents with time; (e) elevated FI values for the riparian locations for the April 14 event suggested that DOM was more microbial in nature immediately after manure application and then evolved toward a more terrestrial character with time; (f) among the PARAFAC components, the tryptophan-like component C4 was highest for the storm immediately after manure application (April 14 event) and then declined with time; (g) the magnitude of the storm events did not appear to have a substantial influence on DOM concentrations since large events occurring later in time did not produce significant increases in runoff DOM; and (h) inorganic N constituents also displayed sharp changes with time

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Fig. 3. DOC concentration, dissolved organic matter indices (SUVA254 , HIX, SR , and FI), PARAFAC components (C1, C2, and C4), and inorganic N concentrations (NH4 –N and NO3 –N) in surface runoff waters at the field edge (FE) location for sampled events (event dates–month/day on x axis).

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Fig. 4. DOC concentration, dissolved organic matter indices (SUVA254 , HIX, SR , and FI), PARAFAC components (C1, C2, and C4), and inorganic N concentrations (NH4 –N and NO3 –N) in surface runoff waters at the upland riparian (UR) location for sampled events (event dates–month/day on x axis).

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Fig. 5. DOC concentration, dissolved organic matter indices (SUVA254 , HIX, SR , and FI), PARAFAC components (C1, C2, and C4), and inorganic N concentrations (NH4 –N and NO3 –N) in surface runoff waters at the lowland riparian (LR) location for sampled events (event dates–month/day on x axis).

Fig. 6. DOC concentration, dissolved organic matter indices (SUVA254 , HIX, SR , and FI), PARAFAC components (C1, C2, and C4), and inorganic N concentrations (NH4 –N and NO3 –N) in surface runoff waters at the stream (ST) location for sampled events (event dates–month/day on x axis).

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Fig. 7. DOC concentration, dissolved organic matter indices (SUVA254 , HIX, SR , and FI), PARAFAC components (C1, C2, and C4), and inorganic N concentrations (NH4 –N and NO3 –N) in soil waters at the upland riparian (URSW) location for sampled events (event dates–month/day on x axis).

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Fig. 8. DOC concentration, dissolved organic matter indices (SUVA254 , HIX, SR , and FI), PARAFAC components (C1, C2, and C4), and inorganic N concentrations (NH4 –N and NO3 –N) in soil waters at the lowland riparian (LRSW) location for sampled events (event dates–month/day on x axis).

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– FE-LR FE-LR, UR-LR – FE-LR FE-LR, LR-ST FE-LR, FE-ST, UR-LR FE-LR – – – 35.64 (6) 2.25 (6) 0.08 (7) 0.29 (7) 0.08 (7) 0.13 (7) 0.15 (7) 0.23 (7) 0.13 (7) 2.22 (7) 1.97 (6) ± ± ± ± ± ± ± ± ± ± ± 41.19 3.62 0.66 0.52 1.42 0.40 0.33 0.72 0.19 2.24 1.21 32.27 (7) 0.72 (7) 0.11 (7) 0.16 (7) 0.20 (7) 0.11 (7) 0.10 (7) 0.27 (7) 0.11 (7) 1.13 (7) 1.25 (7) ± ± ± ± ± ± ± ± ± ± ± 22.29 2.12 0.68 0.71 1.43 0.45 0.36 0.59 0.21 0.75 2.11 28.18 (3) 3.13 (3) 0.11 (4) 0.36 (4) 0.07 (4) 0.11 (4) 0.14 (4) 0.39 (4) 0.17 (4) 0.10 (2) 2.17 (2) ± ± ± ± ± ± ± ± ± ± ± 34.61 3.29 0.62 0.66 1.45 0.34 0.27 0.61 0.21 0.88 3.33 **

*

Data represented as mean ± std. dev. (N), where N = number of observations over study period. Sign. diff. are observed at significance level = 0.1 using Wilcoxon rank sum test on all pairs.

30.90 (7) 2.08 (7) 0.05 (7) 0.52 (6) 0.11 (7) 0.06 (7) 0.07 (7) 0.25 (7) 0.09 (7) 1.01 (6) 2.63 (6) ± ± ± ± ± ± ± ± ± ± ± 22.42 4.90 0.67 0.36 1.39 0.47 0.35 0.61 0.27 1.33 2.92 9.02 (3) 0.57 (3) 0.04 (3) 0.20 (3) 0.34 (3) 0.06 (3) 0.06 (3) 0.08 (3) 0.15 (3) 2.01 (3) 2.87 (3) ± ± ± ± ± ± ± ± ± ± ± 18.10 2.48 0.79 0.81 1.54 0.50 0.42 0.37 0.22 1.74 2.64 140.31 (8) 1.47 (8) 0.07 (12) 0.37 (12) 0.13 (12) 0.08 (12) 0.11 (12) 0.22 (12) 0.12 (12) 40.83 (9) 3.03 (9) ± ± ± ± ± ± ± ± ± ± ± 94.62 2.06 0.74 0.66 1.52 0.43 0.46 0.39 0.25 26.65 2.67 DOC (mg C L−1 ) SUVA254 HIX SR FI C1 C2 C3 C4 NH4 –N (mg N L−1 ) NO3 –N (mg N L−1 )

Lowland riparian soil water (LRSW) Stream (ST)

Upland riparian soil water (URSW) Soil water

Upland riparian (UR)

Lowland riparian (LR) Surface water

When mean values of DOM (including all events; Table 3) for surface runoff were compared across the four landscape positions, significant differences were observed for SUVA254 , HIX, FI, and PARAFAC model components C1–C3. We recognize that the large temporal variability in DOM across the sampled locations likely undercuts the comparison of mean values for DOM. Among positions the largest differences were recorded between the field edge (FE) and the lowland riparian (LR) position. Mean DOC concentrations (Table 3) in surface runoff were highest at the field edge but were not significantly different from the other locations. SUVA, HIX, and FI values for surface runoff were significantly different between the field edge and the lowland riparian location, indicating that the DOM at the field-edge location was less aromatic, more humic and

Field edge (FE)

3.2. Differences in DOM with landscape position

Parameter

which however differed slightly across the landscape positions. Specific changes for individual locations are described below. The largest temporal change in surface runoff DOC concentrations was seen at the field edge location when concentrations in excess of 300 mg L−1 for April 14 dropped sharply to less than 50 mg L−1 just 13 days later. The event of April 14 was fairly small with only 5.8 mm of rainfall (Table 1). While DOC data were not available for the event prior to manure application (March 29), UV254 absorbance for field-edge runoff for the March 29 event (29.0 m−1 ) was lower than the value for the April 14 event (337.9 m−1 ). This suggests that DOC concentrations in runoff prior to manure application were very low (since our data indicated a strong positive correlation between DOC concentrations and UV values; not included here). Both C2 and C4 model components were highest immediately after manure application and then declined with time. Concentrations for NH4 –N and NO3 –N dropped sharply between April 14 and 27 events, although NO3 –N rebounded for the June 10 event. No surface runoff or soil water sample was available for the March 29 event for the riparian locations (upland and lowland). Only three event samples were available for surface runoff at the upland riparian zone (Fig. 4), however, SR and FI values and inorganic N concentrations for these events decreased dramatically between the April 14 and 27. In comparison to the upland riparian location, more data on surface runoff was available at the lowland riparian location (Fig. 5) which revealed a gradual increase in SUVA values (and aromatic DOM character) with time after manure application. SR and FI values for this location followed the broader trend of a shift in DOM from microbial, low molecular weight DOM for the April 14 event to terrestrial, larger molecular weight DOM for subsequent events. Unlike the field edge location however, NH4 –N and NO3 –N concentrations at the lowland riparian location followed opposing trends. While NO3 –N decreased for the April 14–27 events, NH4 –N concentrations remained low with a slight increase for the June 10 event. Overall, soil water DOM for upland and lowland riparian locations (Figs. 7 and 8) displayed similar temporal trends. Both of these locations displayed gradual decreasing trends in C2 and C4 fluorescence components following manure application which were not as pronounced for surface runoff samples. FI and SR values also decreased with time indicating a shift toward terrestrial, higher molecular weight DOM. The soil water inorganic N values for the lowland riparian location however revealed contrasting trends with increasing NH4 –N values but very low NO3 –N concentrations. This was likely because of water logged, anoxic conditions at this location that favored NO3 –N loss via denitrification and NH4 –N accumulation because of negligible nitrification. Stream surface water samples were only available for four events and unlike other locations, did not reveal any clear or consistent temporal trends in DOM.

Sign. diff.**

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Table 3 Mean values and standard deviations of DOM and inorganic N parameters for surface runoff and soil water measured at the four landscape positions.

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4. Discussion 4.1. DOM changes with time after poultry manure application

Fig. 9. Concentrations of soil C and N with time before and after manure application on April 10. Soil samples were collected following storm events (event dates—month/day on x axis).

more microbial in nature than DOM at the lowland riparian location. Mean concentrations for NH4 –N in surface runoff displayed greater variability among the landscape positions than corresponding values for NO3 –N. Surface water and soil water DOM could be compared only for the riparian locations. No soil water samples were collected at the field edge. Soil water concentrations for DOC were not significantly different from the surface water values (Table 3).

3.3. Changes in cropland soil C and N with time after manure application Similar to the dissolved species, C and N contents for cropland soil revealed large changes with time (Fig. 9). The % C and % N contents and the concentrations of NH4 –N and NO3 –N (mg/kg) in cropland soil prior to manure application (March 29) were very low. These concentrations then increased to a maximum following the storm event of April 14, but then declined very rapidly following the next two events (April 27 and May 12). Approximately, within a month of manure application the soil C and N concentrations had dropped back to their pre-manure levels. The ratio of NH4 –N to NO3 –N varied from a high of 1.67 on April 14 to 0.03 by the end of the study. Similarly, C:N ratios for the cropland soils varied from 6.6 to 8.2 for the sampled events. The C and N contents for the raw poultry manure (Fig. 9; dry weight basis) were also high but less than the maximum values recorded for soil C (30.39%), N (4.16%) and NO3 –N (2410 mg/kg). This could be attributed to variability of samples collected from the large manure pile (we could not recover samples from deep inside the manure pile). The values for NH4 –N were however comparable for the two sample types (maximum soil NH4 –N = 3999 mg/kg).

This study revealed dramatic increases in runoff DOC concentrations and changes in DOM character immediately after manure application. This was despite the fact that the storm event that occurred four days after manure application was fairly small. Equally significant were the sharp decreases in DOC concentrations and changes in DOM within a few weeks after manure application. Runoff DOM immediately following manure application (April 14) had low aromaticity (SUVA254 ) and had a microbial and tryptophan-like character. These DOM characteristics evolved quickly with time toward more aromatic, more humic, high molecular weight, and terrestrial-like composition. It is notable that these temporal changes in DOM were observed for both surface runoff and soil water. These DOM patterns were further supported by comparable changes in soil concentrations of C and N (Fig. 9). Similar temporal changes in DOM have also been reported by the handful of agricultural studies that have evaluated the influence of manure application on runoff DOM. Pezzolla et al. (2013) found that DOC concentrations in surficial soils (0–20 cm) were very high (116–225 mg L−1 ) 0–7 days after poultry manure application but then declined rapidly beyond 14 days. Naden et al. (2010) working in intensively-farmed grasslands in United Kingdom evaluated changes in DOM from plots subject to application of dairy farm slurry. They reported elevated runoff concentrations of tryptophan-like DOM for a small storm event that occurred within 3–5 days of slurry application. In contrast, DOM concentrations were muted for a larger storm that occurred 3–5 weeks later. Similar to our observations, Naden et al. (2010) also found elevated NH4 –N concentrations in runoff for the first storm event which declined for the larger subsequent event. The subsequent event, however, yielded elevated NO3 –N concentrations leading them to suggest that there was some transformation of N species with time (Naden et al., 2010). Naden et al. (2010) attributed the quick (within 2–3 weeks of manure application) preferential loss of tryptophan-like DOM to sorption and/or microbial breakdown. Similarly, Zhang et al. (2011) found a rapid increase in water-extractable C and N concentrations after poultry manure application at the rate of 11 Mg ha−1 (a rate slightly greater than that used for our study). Hunt and Ohno (2007) reported an increase in HIX values and a decrease in the tryptophanlike DOM within just 10 days of poultry manure application. Hunt and Ohno (2007) attributed the decrease in tryptophanlike DOM to degradation and the increase in HIX to the release of higher molecular weight and more aromatic DOM moieties in solution. Other processes that could alter DOM concentrations and composition could include photodegradation and oxidation (Kalbitz et al., 2000; Bolan et al., 2011), although Naden et al. (2010) suggested that photodegradation was likely not happening at their study site. We suspect that DOM sorption to soils could be especially important at our site considering that manure was incorporated into the topsoil during application. This allowed for a greater contact of manure DOM with sorption surfaces in the soil. This agronomic practice of incorporation likely reduced the exports of both DOM and NH4 –N with runoff and volatilization, respectively. Microbial degradation could have also played an important role in the decrease of DOM at our site considering that fluorescence measurements indicated a pronounced microbial character for the manure-derived DOM. Photodegradation was likely not a significant process in our study since manure was incorporated into the soil during application. Our observations also concurred with previous studies (e.g., Naden et al., 2010) in that the timing of the

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Table 4 Comparisons of manure-derived mean DOM values from this study versus DOM derived from manure and non-manure sources in other agricultural studies. Reference

Location

Site Description

Dalzell et al. (2011)

Central Minnesota, USA

Vidon et al. (2008)

Central Indiana, USA

Corn–soybean row crop with tile drainage. Concentrations for field, ditch, stream and river runoff Corn–soybean cropland; watershed A—stream runoff

Warrner et al. (2009)

Benton County, Indiana, USA

Hernes et al. (2008)

Sacramento River valley, California, USA

Dutta et al. (2012a)

New Castle County, Delaware, USA

This study

New Castle County, Delaware, USA

Hunt and Ohno (2007)

Laboratory study, USA

Corn–soybean row cropland; stream water concentrations Agricultural (60%) watershed (425 km2 ) with rice, orchards, row crops and pasture

DOC (mgC L−1 )

SUVA254 (L mg−1 m−1 )

HIX

FI

2.39–3.05

–

1.35–1.54

Baseflow: 4.78 (±1.39)

1.35 (±0.39)

–

1.37 (±0.03)

Average storm values: 4.45–8.80 2–5

2.1–2.9 0.8–2.8

Summer storms: 5.0–7.2

Summer storm mean: 3.46

Row-crop agriculture 2.5–9.3 (Table 2 in reference)

Winter baseflow: 2.0–3.0 Cropland receiving manure application Experimental plots Mean values (12 × 5 m) with tillage and poultry manure treatments. Surface runoff following storm events (April–July). No till: 2.1 No till + poultry manure at 23 Mg/ha: 8.26 Corn cropland 18.1–94.6 (from Table 3 in this study) receiving poultry manure. Mean surface runoff values for field, riparian and stream locations (March–July) Manure extracts Fresh and decomposed 957 [987] DOM extracts from poultry manure; values in “[]” are post decomposition

1.26–1.36 –

–

No till: 2.0 No till + poultry manure at 23 Mg/ha: 3.18 2.06–4.90 (1.92–3.39)*

1.82–3.84 (0.62–0.79)**

1.39–1.54

2.44* [0.76]

2.06 [3.21]

–

Winter mean: 2.70

*

SUVA calculated using UV wavelength measured at 280 nm. HIX calculated in this study using equation given by Ohno (2002), however, for comparison with other studies for this table, HIX using Zsolnay et al. (1999) was also computed. **

storm event (after manure application) was an important factor in influencing the runoff DOM concentrations. 4.2. DOM changes with landscape positions We recognize at the outset here that the evaluation of spatial, landscape level changes in DOM for our study were likely to have been affected by the limited sampling locations (three for field edge and one each for the riparian and stream locations). Additionally, there was large variability in DOM with time which further complicated the spatial changes in DOM with landscape positions. Broadly, two key spatial trends emerge from our data in Table 3—(a) DOC concentrations decreased sharply and DOM became more humic and aromatic as surface runoff moved from the field edge to the upland riparian location; and (b) there were subtle changes in DOM as runoff moved from the lowland riparian location to the stream. We attribute the first change in runoff DOM to substantial infiltration of DOM-rich cropland runoff as it entered the riparian forest followed by removal and retention of manure-derived DOM in riparian soils. Previous studies have shown that sorption and removal of DOM can happen quickly as it comes in contact with mineral soils (Bolan et al., 2011; Inamdar et al., 2012; Kalbitz et al.,

2000). This rationale is also supported by the sharp drop in NH4 –N concentrations (Table 3). Grassed waterways and riparian forest zones have been shown to reduce nutrient concentrations (nitrogen and phosphorus) through infiltration, sediment deposition (Veum et al., 2009), and sorption and the same mechanisms likely extend to DOM. The second smaller change in DOM between the lowland riparian location and the stream can be attributed to leaching of DOM from the valley-bottom forest sources themselves. While there appears to be some expression of manure-derived DOM at the lowland riparian location immediately after manure application (April 14, Figs. 5 and 8) the DOM character quickly evolves toward that of the forest and riparian soils. Overall, these observations suggest that the riparian forest and grassed waterway acted as a buffer and prevented the DOM-rich cropland runoff from reaching the stream. 4.3. Comparison of manure-derived DOM versus other agricultural sources of DOM We compared our DOM results with a variety of other agricultural studies (Table 4) including lands primarily in row-crop agriculture (Dalzell et al., 2011; Hernes et al., 2008; Vidon et al.,

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2008; Warrner et al., 2009), croplands receiving manure application (Dutta et al., 2012a and this study) and laboratory studies that have investigated DOM extracts from various manure sources (Hunt and Ohno, 2007). While there is considerable variation in DOC concentrations among the selected studies, it is apparent that landscapes receiving manure application produce higher concentrations of DOM in runoff (Table 4). It should be noted that only mean values are reported in Table 4 and the range of DOM values is even wider. DOC concentrations and SUVA values are also influenced by hydrologic conditions—with higher concentrations associated with stormflow and this needs to be considered when making such comparisons. DOC concentrations measured in this study were more than twice the values reported for row-crop agriculture sites in the mid-west and western US (Table 4). In contrast, the DOC concentrations for extracts derived purely from manure (e.g., Hunt and Ohno, 2007) are considerably higher, highlighting the potential of manure as a significant DOM source. As opposed to DOC concentrations, the differences for SUVA and HIX between manure and non-manure agricultural sources (Table 4) are not as marked. However, this could be because of the large variability in these metrics and the fact that we compared mean values. Differences in DOM composition between manure and nonmanure agricultural sources have especially been noted for DOM fluorescence (Baker, 2002; Ohno and Bro, 2006; Hunt and Ohno, 2007; Naden et al., 2010; Old et al., 2012). These studies report that the ratio of tryptophan-like to fulvic/humic-like fluorescence (TI:FI) for animal manures is distinct from non-manure sources and that this metric can be used as reliable tracer for animal waste pollution (Baker, 2002; Naden et al., 2010). While the TI:FI ratios of concentrated animal waste (direct extracts or sample collected close to the source) have been found to be fairly high (2–5 or higher; Baker, 2002; Naden et al., 2010; Old et al., 2012) these ratios are lower (∼1 or lower) for diluted manure runoff or runoff collected at outlets of watersheds impacted by manure application (e.g., Old et al., 2012). Our values for TI:FI computed using the ratio of the C4 (tryptophan-like) and the C1 (humic-like) component varied between 0.3 (pre-manure application) and 1.0 (immediately post manure application). We speculate that our TI:FI values were on the lower side because of the incorporation of manure in the soil and the loss of the fluorescence signal to sorption and microbial degradation. Despite the low TI:FI values our results suggest that manure application can enhance the contents of tryptophan-like DOM in runoff. Elevated concentrations of tryptophan-like DOM have been linked to greater bioavailability of DOM (Fellman et al., 2009; Williams et al., 2010) and could have implications for water quality.

5. Conclusions Results from this study have important implications for water quality and environmental protection of aquatic ecosystems as well as the long-term sustainability of land-application of animal manure as an agricultural practice. Our observations suggest that exports of DOM with runoff can be low in watersheds where manure is incorporated into the soil and is applied once every three years. While DOC concentrations were elevated at the field edge and the DOM was labile, the values recorded in the stream were considerably lower. However, an observation of concern is that the timing of manure application in early spring and a short period thereafter (1–3 weeks) can be an environmentally sensitive and vulnerable period for water quality. Storms immediately after manure application could result in elevated DOM concentrations in runoff and large exports of manure-derived DOM and nutrients to aquatic ecosystems. The timing of this export could be especially detrimental to aquatic communities considering the

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sensitive life stages of aquatic biota in the spring. This will be especially important considering that future climate change forecasts for the northeast and the mid-Atlantic US indicate increased annual precipitation, warmer and wetter spring conditions, and increasing intensity of storms (Karl et al., 2009). Such changes could pose additional challenges for water quality and the sustainable use of manure in agricultural watersheds.

Acknowledgments This study was funded through a grant from the United States Department of Agriculture (USDA, Grant No.2009-02424). Any opinions, conclusions, or recommendations expressed in this material are those of the authors and do not necessarily reflect the views of the USDA. We thank the St. Andrews School at Middletown, DE and the farmers for providing access to the agricultural land. The support of graduate students including Gurbir Singh, Rachael Vaicunas, and Weinan Pan for setup and sampling is also recognized. The support of Dr. J. Tom Sims and Karen Gartley is also much appreciated. We thank the editor and the reviewers for their constructive comments which helped strengthen this manuscript.

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Please cite this article in press as: Singh, S., et al., Land application of poultry manure and its influence on spectrofluorometric characteristics of dissolved organic matter. Agric. Ecosyst. Environ. (2014), http://dx.doi.org/10.1016/j.agee.2014.04.019