THE EFFECTS of BIODEGRADATION and PHOTODEGRADATION on OPTICAL PROPERTIES of DISSOLVED ORGANIC MATTER in AQUATIC SYSTEMS a Thesi

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THE EFFECTS OF BIODEGRADATION AND PHOTODEGRADATION

ON OPTICAL PROPERTIES OF DISSOLVED ORGANIC MATTER

IN AQUATIC SYSTEMS

A Thesis

Presented to the faculty of the Department of Geology

California State University, Sacramento

Submitted in partial satisfaction of the requirements for the degree of

MASTER OF SCIENCE

Geology

Angela M. Hansen

FALL 2014

THE EFFECTS OF BIODEGRADATION AND PHOTODEGRADATION

ON OPTICAL PROPERTIES OF DISSOLVED ORGANIC MATTER

IN AQUATIC SYSTEMS

A Thesis

Angela M. Hansen

Approved by:

______, Committee Chair Timothy Horner, Ph.D.

______, Second Reader Tamara Kraus, Ph.D.

______, Third Reader Brian Pellerin, Ph.D.

______Date

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Student: Angela M. Hansen

I certify that this student has met the requirements for format contained in the University format manual, and that this thesis is suitable for shelving in the Library and credit is to be awarded for the thesis.

______, Department Chair ______Timothy Horner, Ph.D. Date

Department of Geology

Abstract

THE EFFECTS OF BIODEGRADATION AND PHOTODEGRADATION

ON OPTICAL PROPERTIES OF DISSOLVED ORGANIC MATTER

IN AQUATIC SYSTEMS

Angela M. Hansen

In the last decade, there has been increasing use of optical measurements to gain insight into dissolved organic matter (DOM) composition, and more specifically to identify DOM source in aquatic systems. However, there are few controlled studies which examine the effects of environmental processing on different sources of DOM. Here, DOM optical properties of five endmember sources–including peat soil, plant and algae leachates–were investigated following biological and photochemical degradation during a three-month incubation period. As microbial processing of DOM occurs independent of being in the photic zone, the effects of photoexposure were examined at various points along the biodegradation curve to simulate photodegradation occurring as microorganisms consumed and transformed the bioavailable DOM. Samples were analyzed for dissolved organic carbon (DOC) concentration, absorbance, and fluorescence.

Optical parameters commonly used to determine DOM composition were then analyzed to determine their effectiveness in discriminating original DOM source and in distinguishing between microbial and photochemical alteration. The qualitative optical parameters included

DOC-normalized absorbance values (SpA254, SpA280, SpA350, SpA370 SpA412, SpA440,

SpA488, SpA510, SpA532, SpA555); absorbance spectra slopes (S275-295, S290-350 and S350-400) and the UV slope ratio (SR); DOC-normalized fluorescence peaks (SpA, SpC, SpM, SpD, SpB, SpT,

SpN, SpZ), fluorescence peak ratios (C:M, C:T, C:A, A:T); fluorescence indices (FI, HIX, β:α,

BIX); and five components determined by Parallel Factor Analysis (PARAFAC; %C1-5).

While there was little change in DOC concentration in the soil leachate over the study period, DOC concentrations in plant and algae leachates decreased by over 70% within the first three days of biodegradation. This rapid loss of DOC in the plant and algal leachates suggests the majority of DOM leached from these materials is unlikely to persist in the environment, and thus is unlikely to make up a significant fraction of the DOM pool in most natural samples. This emphasizes the need to use the signature of processed DOM to identify original source material.

Individual qualitative optical parameters changed extensively as DOM composition was altered following both biodegradation and photodegradation, particularly in the plant and algal leachates. These changes frequently resulted in overlapping optical parameter values which made it impossible to identify original source material. In particular, the sometimes opposing effects of biological and photochemically-driven changes on DOM optical signature can confound source identification; for example, this effect of one degradation process masking the signal from the other was notably apparent for SUVA where values increased with biological degradation and decreased following photoexposure, suggesting that using this parameter alone can generate inconsistent and disparate conclusions about DOM composition and source.

In addition to examination of parameters individually, multivariate statistical analyses were used to determine whether used in combination, these parameters could identify unique optical signatures that could be linked to original DOM source even after exposed to biological and photochemical alteration. PCA demonstrated that when the suite of 30 parameters were combined, the optical signature of the materials did not fall out clearly by source and environmental processing; as was seen when examining the individual parameters, optical signatures of the different sources overlapped over time, with the effects of biodegradation and

photodegradation often acting in opposition. The trajectory in PCA space did however generally follow what is expected as DOM undergoes degradation: a shift from fresh-like to humic-like material. Discriminant analysis (DA) was used to identify which qualitative indicators are the most promising for distinguishing DOM source and processing. Of the 30 qualitative indicators evaluated, 17 were quantitatively determined by DA to be the most significant (p < 0.05): absorbance parameters included SUVA, SpA350, SpA412, S275-295, and S290-350, while fluorescence parameters included humic-like (SpC, SpM, SpD, SpZ) and fresh-like (SpB, SpT,

SpN) DOC-normalized fluorescence peaks as well as peak ratios (C:A, C:M) and indices (FI,

HIX, β:α). The classification of DOM source (soil, rice, cattail, tule, algae) was influenced most heavily by SpC, SpM, C:M, and HI, while the classification of DOM processing (biodegradation versus photoexposure) was influenced most by SpN, SpD, SpT and SpA350.

This dataset highlights the challenge of using optical properties to identify DOM source material because the effects of biodegradation and photodegradation, which in the natural environment can occur simultaneously, can lead to confounding results. Moreover, samples collected from the environment typically contain a mixture of DOM sources which have undergone different degrees of processing. In natural systems, multiple parameters and careful consideration should be taken when using optical properties to characterize DOM source.

______, Committee Chair Timothy Horner, Ph.D.

______Date

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ACKNOWLEDGEMENTS

I am grateful for the encouragement provided by the members of my thesis committee,

Dr. Tim Horner, Dr. Brian Pellerin and, especially Dr. Tamara Kraus, whose patience, guidance and encouragement helped me to complete this work. Thank you to Dr. Brian Bergamaschi, Jacob

Fleck and Bryan Downing for their critical comments and the educational opportunities they have provided. I would also like to thank Laurel Moll, Elizabeth Stumpner and Travis von Dessonneck for their many long hours on laboratory analyses and for providing resources that made this work possible. Lastly, I would like to thank my husband Chuck, and our children Rosemary and

Charles, for inspiring me and bringing so much joy into my life.

The U.S. Geological Survey California Water Science Center provided financial support for this project.

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TABLE OF CONTENTS

Page

Acknowlegements ...... viii

List of Tables ...... xi

List of Figures ...... xii

Chapter

INTRODUCTION ...... 1

MATERIALS AND METHODS ...... 6

Collection and Preparation of Source Material ...... 6

Biodegradation ...... 7

Photoexposure ...... 8

Analytical Measurements ...... 9

STATISTICAL ANALYSES ...... 12

Parallel Factor Analysis (PARAFAC) ...... 12

Additional Multivariate Analyses ...... 12

RESULTS AND DISCUSSION ...... 13

DOC Concentration ...... 13

DOC Composition ...... 15

Absorbance (SUVA, Spectral Slopes, Slope Ratio) ...... 15

SUVA (SpA254) ...... 15

Spectral Slopes (S275-295; S290-350; S350-400) ...... 16

Slope Ratio (SR: S275–295/S350–400) ...... 18

Fluorescence (Indices, Ratios, PARAFAC) ...... 19

Fluorescence Index (FI) ...... 19

Humification Index (HIX)...... 20

Freshness Index (β:α) ...... 21

Peak Ratios (C:T, A:T, C:A, C:M) ...... 22

PARAFAC Components (%) ...... 25

Fluorescence:absorbance ratio (RFE) ...... 27

Correlations between Parameters ...... 28

Multivariate statistical analyses ...... 30

Principle Component Analysis (PCA) ...... 30

Discriminant Analysis (DA) ...... 31

CONCLUSIONS AND RECOMMENDATIONS ...... 34

REFERENCES ...... 61

Tables Page

1. Compositionally based absorbance and fluorescence optical properties...... 39

2. Recent studies which used optical properties to identify shifts in DOM composition...... 40

3. Standard deviation of measurements calculated from replicate means (n=3)...... 41

4. Correlations matrix (n=45)...... 42

5. Discriminant analysis (DA) qualitative groupings by sample type and treatment...... 44

6. Optical parameters determined by DA to be the most significant (p < 0.05)...... 43

7. Parameters found to be useful by themselves at discriminating DOM source...... 45

Figures ...... Page

1A. Dissolved organic carbon (DOC) concentration (mg/L)...... 46

1B. Dissolved organic carbon (DOC) percent loss...... 46

2. Specific UVA absorbance at 254 nm (SUVA) values (L mg-C-1 m-1)...... 47

-1 3. Spectral slope S275-295 (nm )...... 47

-1 4. Spectral slope S290-350 (nm )...... 48

-1 5. Spectral slope S350-400 (nm )...... 48

6. UV Slope ratio S275-295: S350-400...... 49

7. Fluorescence index (FI)...... 49

8. Humification index (HI)...... 50

9. Freshness index (β:α)...... 50

10. Fluorescence peak ratio C:T...... 51

11. Fluorescence peak ratio A:T...... 51

12. Fluorescence peak ratio C:A...... 52

13. Fluorescence peak ratio C:M...... 52

14. Parallel Factor Analysis percent component 1 (PARAFAC %C1)...... 53

15. Parallel Factor Analysis percent component 2 (PARAFAC %C2)...... 53

16. Parallel Factor Analysis percent component 3 (PARAFAC %C3)...... 54

17. Parallel Factor Analysis percent component 4 (PARAFAC %C4)...... 54

18. Parallel Factor Analysis percent component 5 (PARAFAC %C5)...... 55

19. Relative fluorescence efficiency (RFE)...... 55

20. Principle Component Analysis (PCA) loadings plot...... 56

21. Principle Component Analysis (PCA) scores plot...... 58

22. Discriminant Analysis (DA) canonical plot...... 58

xii

23. Five principal fluorophores identified by Parallel Factor Analysis (PARAFAC)...... 59

24. Example excitation-emission matrix (EEM) ...... 60

xiii

INTRODUCTION

Dissolved organic matter (DOM) plays a central role in aquatic environments; not only is it a source of bioavailable organic carbon which impacts the food web, but it also attenuates light in the water column, and can mobilize and transport pollutants. While quantifying DOM amount by measuring DOC concentration is important, it is also important to characterize DOM composition because its chemical make-up determines how it reacts in the environment. For example, the presence of different compounds determines DOM lability and thus its contribution to the heterotrophic food web and its environmental persistence (Jaffe et al., 2008; Minor et al.,

2014). Similarly, a variable subset of compounds within the bulk DOM pool can react with chlorine to create carcinogenic compounds, or disinfection byproducts (DBPs), impacting its suitability for municipal use (e.g. Leenheer and Croue, 2003; Liang and Singer, 2003). In addition, a wide variety of studies have demonstrated that DOM composition can be used to determine the origin of DOM, which can help inform watershed management and predict future trends (e.g. Hood et al., 2005; Kraus et al., 2008, Carpenter et al., 2013).

DOM is operationally defined as the organic matter fraction that passes through a filter

(typically 0.3-0.7 µm), while that which is collected on the filter is defined as particulate organic matter (POM). The bulk DOM pool is comprised of a diverse array of molecules, which can be classified in various ways (Minor et al., 2014): for example by their size (low to high molecular weight), their functional groups (e.g. aromatic, aliphatic, anomeric, etc.), their hydrophobicity, or their elemental composition (C, N, H, O, etc.). Both DOM amount and composition varies spatially and temporally due not only to its proximity to source material but also to its exposure to environmental processing (McKnight et al., 2001; Jaffe et al., 2008; Kraus et al., 2008). While under some conditions sorption and the formation of colloids and even precipitation can transfer

DOM into the particulate pool (POM), the two main processes affecting DOM amount and

composition in aquatic environments are biodegradation and photodegradation (Kieber et al,

1990; Miller and Moran, 1997; Del Vecchio and Blough, 2002). Therefore the three main factors affecting DOM composition include (i) original source material, (ii) biodegradation, and (iii) photodegradation.

The sources of DOM to aquatic systems are frequently divided into three major categories: (i) allochthonous, terrestrial soil and plant material, (ii) autochthonous, algal or planktonic material, (iii) anthropogenic, manmade material (Mostofa et al., 2013). Natural waters contain a heterogeneous mixture of these source materials in varying degrees depending on the water body type; freshwater and coastal water are typically dominated by terrestrial-derived

DOM, while lakes and oceans are often dominated by algal and planktonic DOM (Coble, 1996,

1997; Huguet et al., 2009; Mostofa et al, 2009).

Biodegradation is the chemical decomposition of DOM by bacteria or other organisms, while photodegradation is the decomposition of molecules abiotically by irradiation. Both of these processes can lead to the conversion of DOM to inorganic compounds (i.e. CO2) and its subsequent loss from the water column (measured by the loss of DOC concentration), and to the alteration of DOM chemical structure (measured by a change in composition). Biodegradation occurs continuously independent of being in the photic zone, and typically leads to the rapid loss of labile, low molecular weight (LMW) aliphatic material, including proteins, carbohydrates, and organic acids (Kieber et al., 1990; Mopper et al., 1991; Miller and Zepp, 1995; Wetzel et al.,

1990, 1995; Moran and Zepp 1997). While microbial processing can lead to a significant loss of labile DOC and a relative increase in the recalcitrant fraction, it can also be accompanied by the production of high molecular weight (HMW) aromatic material, such as fulvic and humic acids, through alteration of existing compounds and/or in situ production of heterotrophic secondary production (Repeta et al., 2002; Stepanauskas et al., 2005). Photodegradation in aquatic

environments can significantly impact DOM cycling and alter its bioavailablility and fate by (i) chemically decomposing DOM from larger molecules to smaller labile photoproducts that are then removed from the DOM pool either by volatilization of carbon gases or by rapid microbial consumption (Mopper et al., 1991; Miller and Zepp, 1995), (ii) by reducing DOM bioavailability by transforming labile compounds to higher molecular weight refractory material (Benner and

Biddanda, 1998; Obernosterer et al., 1999) or (iii) by some degree of both depending upon the molecular structure of the DOM.

While there are many techniques available to characterize DOM (Minor et al., 2014), optical measurements are increasingly used to track DOM composition and to infer DOM source and processing due to the development of cheaper instrumentation that provides direct, rapid measurements that are faster and more affordable than molecular level analyses (Coble, 2007;

Hudson et al., 2007; Henderson et al., 2009; Fellman et al., 2010). The optically measureable, light absorbing fraction of DOM, is referred to as chromophoric (colored) dissolved organic matter (CDOM) (Stedmon et al., 2003). In addition to absorbing light, a fraction of CDOM also fluoresces when excited by light in the UV and visible spectrum, and this fluorescing pool is commonly referred to as FDOM.

The fluorescence maxima at certain excitation/emission (ex/em) wavelengths have been previously related to specific organic compounds (Coble et al., 1990; Mopper and Schultz, 1993;

Stedmon et al., 2003) and have been historically identified by lettered peak names (Coble, 1996)

(Figure 24). Fluorescence measurements are commonly used to identify two major DOM pools commonly referred to as (i) humic fractions and (ii) protein fractions (Mopper and Schultz, 1993;

Coble, 1996). Humic (degraded) material is generally associated with fluorescence Peaks A, C,

D, M, and recently-identified Peak Z (Fleck et al., 2014); while the protein-like fraction is generally associated with fluorescence in the lower UV region (Peaks B, T and N). However,

while the use of the term “protein-like” or “amino acid-like” primarily originates from the fact that the two aromatic proteins, tryptophan and tyrosine, fluoresce in this lower UV region when measured in pure form (Cory and McKnight, 2005), recent studies have clearly shown that other non-protein compounds fluoresce in the low-UV regions (Hernes and Benner, 2003; Coble, 2007;

Hernes et al., 2009). Specifically, undegraded polyphenols known to be present in vascular plant leachates fluoresce in this region (Beggs et al., 2011; Aiken, 2014). Therefore, these components may be more appropriately described as reflective of “fresh” organic matter and will thus be referred to hereafter as “fresh-like” DOM.

In addition to quantifying the absorbance and fluorescence at specific wavelengths, over the years a number of optical properties and indices have been developed to infer DOM composition and origin (Table 1). While these optical properties and indices have been used by many studies to infer DOM composition and thus its source and processing (e.g. Hood et al.,

2006; Jaffe et al., 2008; Fellman et al., 2010; Kraus et al., 2011), there are few controlled studies which examine the effects of photodegradation and biodegradation on these properties in order to improve our understanding of how optical signatures of natural samples can be interpreted (Table

2). Without a better understanding of how the optical signature of the bulk DOM pool in a water sample can be related to its original sources and the transformations that have affected its composition, we are limited in our ability to use this approach to study watershed sources of

DOM and predict its fate in the environment.

In this study, DOM optical properties of three endmember sources–including peat soil, plant and algal leachates–were investigated following biological and photochemical degradation during a three month incubation period. Soil, plant and algae materials were specifically chosen to represent DOM entering wetlands of the Sacramento-San Joaquin Bay Delta. The effects of photoexposure were examined at various points along the biodegradation curve to simulate

photodegradation occurring as microorganisms consumed and transformed the bioavailable

DOM. We feel this approach of irradiating biodegraded source material captured the coupled effect of simultaneous biodegradation and photodegradation occurring in nature because while biological alteration happens continuously, photochemically-driven changes occur only when

DOM is in the photic zone. Samples were analyzed for dissolved organic carbon (DOC) concentration, absorbance, and fluorescence.

MATERIALS AND METHODS

Collection and preparation of source material

This study was linked to a larger study examining DOM in wetlands located on subsided peat islands of the Sacramento-San Joaquin Delta (California, USA); therefore end-member sources common to this system (peat soil, wetland plants, and algae) were selected to represent primary sources of DOM entering the water column.

Peat soil was collected from Twitchell Island, located in the west-central part of

California’s Sacramento-San Joaquin Bay Delta. The soils on the island are classified as a Rindge mucky silt loam (euic, thermic Typic Medisaprists) formed primarily from tules and reeds, with minor contributions from mixed-origin alluvial deposits (Fleck et al., 2004). Soil was air dried, homogenized, and passed through a 2 mm sieve to remove large pieces of plant and mineral material, followed by oven drying at 60°C to constant weight. Three plant biomass samples

[white rice (Oryza sativa), tule (Schoenoplectus acutus), and cattail (Typha spp.)] were collected as described in Pellerin et al., 2010. Briefly, above ground plant material (including both leaves and stems) collected from the field was gently rinsed with organic-free de-ionized water, air dried, and stored sealed in plastic bags. Prior to leaching, plant material was cut into <2.5 cm pieces, homogenized, and oven-dried at 60°C to constant weight. Soil and plant leachates were prepared by adding approximately 5 g of dried biomass from each plant type and 1000 g of soil to

4 L of organic-free water. Samples were placed on a shaker for 4 hours at room temperature

(23°C). Following centrifugation to settle the particles, the supernatant was filtered through 0.3

μm glass fiber (GF/F) filters.

We also used a commercially available diatom (Thalassiosira weissflogii, 6-20 µm x 8-15

µm) commonly found in the Sacramento-San Joaquin Bay Delta, that was produced in a closed- system photobioreactor design that allows microalgae to be grown in laboratory-sterile conditions

(Reed Mariculture Inc., Campbell, CA). To extract DOM from the algae, the culture was frozen and thawed, then sonicated (to lyse cells) in a fluorinated ethylene propylene (FEP) Teflon® bottle. Following centrifugation for 20 min. at 2000 rpm, the supernatant was filtered through 0.3

µm GF/F filters.

The resulting soil, plant and algae leachates had DOC concentrations of 35 to

45 mg C L-1, and were refrigerated at 23°C prior to the start of the biodegradation and photoexposure experiments (started within 24 h).

Biodegradation

Because filtration removed not only particulate organic matter but also bacteria, soil, plant and algal leachates were inoculated with 3% (v/v) unfiltered surface water collected from the American River (CA, USA) to reintroduce a microbial decomposer community. The low

DOC concentration of the inoculum (approximately 5.0 mg C L-1) and low inoculum-to-sample ratio had no measureable effect on leachate DOC concentrations and composition.

Additionally, an inorganic nutrient solution composed of NH4Cl, KNO3 and KH2PO4 was added (0.1% of sample volume) to eliminate potential N and P limitation, resulting in final concentrations of 9.5 mM NH4Cl, 9.8 mM KNO3, and 2.0 mM KH2PO4. Source leachates with added inoculum and nutrients were then dispensed in triplicate to 1 L acid-washed, precombusted

(460°C), amber glass bottles. The 1 L source bottles were incubated in the dark at 21°C for 111 days and continuously aerated using filtered lab air to prevent anoxic conditions. Condensation traps were used to allow air to escape while minimizing sample loss from evaporation; lost volume (typically <2% of sample volume) was replaced with organic-free water before each subsample collection. On days 0, 3, 7, 14, 28 and 111, sub-samples (100 mL) were collected from each source bottle and vacuum ﬁltered through 0.3 μm GF/F ﬁlters before analysis.

Photoexposure

In addition to the subsample collected for biodegradation as previously described, a second 100 mL subsample was collected from each 1 L source bottle on days 3, 28, and 111 to examine the effects of biodegradation followed by photoexposure on DOC quantity and quality.

One set of samples was placed in pre-combusted 125 mL amber glass bottles and wrapped in aluminum foil before irradiation to serve as biodegradation-only, dark controls. The second set of biodegraded subsamples were placed in acid-washed 500 mL sealed optically transparent quartz tubes for photoexposure, as opposed to borosilicate glass containers that absorb UV light. The quartz tubes were placed on their side under irradiation to maximize the surface area of sample exposed; water depth in each tube was 5 cm. Both sets were irradiated for 4 hours in a solar simulator equipped with 12 ultraviolet UVA 340 fluorescent bulbs (Q-Lab) which provide a spectral shape most similar to that of natural sunlight in the critical short wavelength region of

295 nm to 365 nm, the most important wavelengths for environmental photoreactions involving

DOM (Stubbins et al., 2010). Light output (0.45 W m-2) from the solar simulator was verified using a hyperspectral radiometer (HyperOCR; Satlantic, NS, CAN). The four hours of solar simulator irradiation equates to approximately 13 hours of solar irradiance at latitude 38.1068N and longitude 121.6465W (Twitchell Island, CA), representing conditions at the Sacramento-San

Joaquin Bay Delta water surface in mid-July noonday sun (0.13 W m-2). Following light exposure, samples were vacuum ﬁltered through 0.3 μm GF/F ﬁlters prior to analysis.

All samples for DOC concentration were preserved by acidiﬁcation to approximately pH

2.0 with high purity H2SO4 and analyzed within 7 days, whereas absorbance spectra and fluorescence excitation emission matrices (EEMs) were run on unacidiﬁed samples within 8 h following filtration.

Analytical measurements

Measurements of DOC concentration and optical properties were performed at the U.S.

Geological Survey (USGS) Organic Matter Research Laboratory (OMRL) in Sacramento, CA.

DOC concentration (mg C L-1) was determined by high-temperature catalytic combustion using a

Shimadzu TOC-VCSH total organic carbon analyzer (Shimadzu Scientiﬁc Instruments,

Columbia, MD), according to a modified version of method EPA 415.3 (U.S. Environmental

Protection Agency, 2005). The accuracy and precision of the measurements were within 5% as indicated by an internal standard (caffeine), laboratory replicates, and matrix spikes. The long- term method detection limit for DOM concentration was 0.30 mg C L-1 based on three times the standard deviation of a low concentration standard measured over the annual cycle.

Absorption spectra and fluorescence matrices were simultaneously collected on filtered samples at room temperature (25°C) in an acid-cleaned 1 cm quartz cuvette using a spectrophotometer equipped with a CCD detector (Aqualog®; Horiba Instruments Inc., NJ,

USA). Excitation and absorbance scans were performed using a double-grating monochrometer, a

150 Watt Xenon lamp with a 5 nm bandpass and a 1-second integration time at wavelengths of

240-600 nm. Emission spectra were collected with a CCD at approximately 1.64 nm (4 pixel) intervals at wavelengths of 240-600 nm. To limit the effects of photobleaching during analysis, excitation and absorbance wavelengths are scanned from low to high energy (red to UV), reducing UV exposure of the sample. Spectral correction procedures included instrument correction, baseline correction, normalization to the daily water Raman peak area (Murphy,

2011), and the removal of Rayleigh scatter lines. Concentration-related inner filter effects were corrected as described by Gu and Kenny (2009).

Absorption spectra are expressed as absorption coefficients (a(λ), m−1). Samples with

A254 greater than 3.0 absorbance units (AU) were diluted and reanalyzed to ensure linearity in

the wavelengths of interest. Carbon-normalized (specific) absorbance was calculated for several wavelengths by dividing by the sample DOC concentration in order to make concentration- independent comparisons across sources. Here, because we make this calculation for a number of different wavelengths we use the abbreviation SpA350, where the number following the letter A denotes the absorbance wavelength (e.g. 350 nm). The specific absorbance at 254 nm (commonly referred to as SUVA, here equivalent to SpA254) has been shown to be a useful proxy for DOM aromatic content (Weishaar et al., 2003).

Concentration-independent relationships between the absorbance wavelengths have been shown to be useful in providing an estimation of DOM molecular weight (Helms et al., 2008), therefore spectral slopes were calculated in MatLab R2013b (MathWorks, Natick, Massachusetts,

USA) for several wavelength ranges (S275–295, S290–350, and S350–450) using non-linear least-squares curve fitting for each spectral range (Boss and Zaneveld, 2003; Del Vecchio and Blough, 2002); the slope ratio (Sr) was also calculated for the ultraviolet wavelength ranges S275–295:S290–350.

Fluorescence data are expressed in raman-normalized intensity units (RFU). Fluorescence data were normalized by DOC concentrations in order to compare fluorescence EEM shape across samples with differing concentrations, hereafter referred to as specific fluorescence (SpT,

SpC, etc). Four published fluorescent DOM compositional indicators were also calculated. The fluorescence index (FI) was calculated as the ratio of emission intensity at 470 nm to that at 520 nm at an excitation of 370 nm as an indicator of relative contribution of microbial versus terrestrial contribution to the DOM pool (Cory et al., 2010). The humification index (HIX) was calculated as the area under the emission spectra 435-480 nm divided by the peak area 300-345 nm + 435-480 nm, at excitation 254 nm as an indicator of source, diagenesis and sorptive capacity (Ohno, 2002; Ohno et al., 2008). The freshness index (β:α), an indicator of the contribution of fresh DOM originating from biological activity, was measured as the ratio of

emission intensity at 380 nm divided by the emission intensity maximum observed between 420 and 435 nm, obtained at excitation 310 nm (Parlanti et al., 2000; Wilson and Xenopoulos 2009) where β represents more recently derived DOM and α represents more decomposed DOM; a higher β:α value represents a higher proportion of fresh DOM. The biological index (BIX), modified from the β:α, is an indicator of autochthonous (microbial-derived) DOM, was obtained by dividing fluorescent intensity at ex308/em380 by intensity at ex308/em430 (Huguet et al.,

2009). Finally, relative fluorescence efficiency (RFE), an indicator of the relative amount of algal and non-algal DOM, was calculated as the ratio of fluorescence (ex370/em460) to absorbance at

370 nm (Downing et al., 2009).

The optical measurements were within quality control thresholds as indicated by laboratory standards (potassium dichromate and quinine sulfate) measured monthly, a standard reference material (Lipton® unsweetened iced tea) measured daily, and laboratory replicates measured approximately every 10 samples. Absorbance long-term method detection limits vary by wavelength, ranging from 0.002 AU at 600 nm to 0.001 AU at 240 nm based on three times the standard deviation of laboratory blanks. Fluorescence long-term method detection limits vary by excitation-emission pairs, ranging from 0.001 RFU throughout much of the EEM spectra to

0.03 RFU in the region of peak B based on three times the standard deviation of laboratory blanks over an annual cycle. Experimental blank controls were inoculated with the nutrient solution and

American River inoculum as described above; they were run in triplicate and measured under the same conditions as the biodegraded and photoexposed source material. Initial DOC concentrations were < 0.2 mg L-1 and optical measurements remained below laboratory reporting limit (LRL) for these samples.

STATISTICAL ANALYSES

Parallel Factor Analysis (PARAFAC)

In order to gain more information about DOM character, fluorescent EEMs were decomposed into unique fluorescent groups using Parallel Factor Analysis (PARAFAC) (Bro,

1997). The data consisted of 134 samples each with an array of 12,716 ex/em pairs including 187 emission and 68 excitation wavelengths. The data was evaluated by split-half analysis where it was split randomly in two halves, a calibration and validation array, each consisting of 67 samples. The PARAFAC algorithm was then applied stepwise to both arrays for 2-10 components. The five-component model was determined to be the best fit for this dataset after validation using four approaches: residual analysis, examination of spectral properties, split-half analysis and random initialization (Stedmon and Bro 2008) (Figure 23). The model used a non- negative constraint to reduce instrument noise and detection in low-fluorescing samples.

Additional Multivariate Analyses

Statistical analyses including correlations, principle component analysis (PCA), and discriminant analysis (DA), were performed using JMP version 11.0 (SAS Institute Inc. 2013).

The multivariate analyses were used to explore the multidimensional behavior of the variables

(optical parameters) and to quantify differences between source and environmental process. Data treatment consisted of averaging the three replicates, and for PCA and DA data were log- transformed. We used a correlation R2 value of 0.65 as a threshold to indicate whether measurements showed a strong relationship between parameters (R2>0.65), meaning they consistently changed across all five sources as they underwent environmental processing, or a poor correlation (R2<0.65) suggesting these parameters were not strongly linked, and thus were likely tracking distinct pools of DOM that changed independently during environmental processing.

RESULTS AND DISCUSSION

The focus of this study was to examine how the coupled effect of biodegradation and photodegradation influences DOM composition as measured by optical properties. The absorbance and fluorescence intensity is typically correlated with the DOC concentration, and we therefore expected the intensity of individual absorbance wavelengths, fluorescence peaks, and

PARAFAC component loadings to be positively correlated to DOC concentrations. However, the relative proportions of the different classes of compounds that make up the bulk DOM pool are expected to differ between sources and change with environmental processing. Therefore, after a brief discussion of DOC concentration, we focus on optical data that has either been carbon- normalized by dividing by DOC concentration (e.g. SUVA, SpA350, SpT, SpC), represents the ratio between different measurements (e.g. FI, HI, β:α), reflects the shape of the absorbance curve

(spectral slopes), or reports the relative proportions of different DOM fractions (% PARAFAC component loadings). All of these parameters herein are referred to as compositional or qualitative parameters; standard deviation (n=3) is provided for all results (Table 3).

DOC Concentration

We adjusted the amount of soil, plant and algal material leached per liter of water to target initial DOC concentrations of approximately 40 mg/L (Figure 1a). Within the first three days of biodegradation, DOC concentrations in the plant and algal leachates decreased to less than 10 mg-C L-1 (>75% loss; Figure 1b). In contrast, DOC concentrations in soil leachate decreased by only 6% during the first week. The rate of DOC loss due to biodegradation was lower over the remainder of the incubation; compared to initial concentrations, by day 111 DOC concentrations had decreased 91-97% in the plant and algal samples and by about 20% in the soil leachate.

The lower rate of DOC loss in the soil leachate compared to the plant and algal leachates is likely because DOM leached from soils is dominated by HMW material that has already undergone biodegradation, or humification, processes, thus leaving behind the more recalcitrant

DOM pool. Microbes and bacteria have transformed or consumed the bioavailable DOM, thus, labile LMW DOM typically makes up a small fraction of soil-derived DOM. In contrast, fresh plant and algal leachates contain a high proportion of LMW labile compounds; however vascular plants contain polyphenols, such as lignin and tannins, which are more difficult to degrade, while algae do not (Mostofa et al., 2013).

The dramatic loss of DOC due to biodegradation which occurred within the first 3 days in the plant and algal leachates, suggests the majority of DOM leached from these materials is highly labile and susceptible to rapid degradation in the environment. Therefore, this labile pool is unlikely to comprise a significant fraction of DOM in water samples collected from rivers and lakes because these waters typically have long residence times and ample opportunity for DOM degradation (Stepanauskas et al., 2005). In fact, bioavailable DOC is typically found to be far less than 90% in surface waters (Obernosterer and Benner, 2004; Stepanauskas et al., 2005; Fellman et al., 2009). Exceptions to this could include samples collected during algal blooms or from wetlands where there are high rates of freshly produced DOM entering the water column.

There was little to no measurable change (<3%) in DOC concentration following irradiation on days 3, 14 and 111.

DOC Composition

Absorbance (SUVA, Spectral Slopes, Slope Ratio)

SUVA (SpA254):

One of the most widely reported absorbance measurements used to characterize DOM composition is UV absorbance at 254 nm normalized to DOC concentration, commonly referred to as specific UVA or SUVA. The absorption of light at this wavelength per unit of carbon has been shown to be a useful proxy for DOM aromatic content (Weishaar et al., 2003) and can also be indicative of molecular weight (Chowdhury, 2013). SUVA values in surface waters typically range between 1.0 and 6.0 L mg-C -1 m-1; although higher values than 6.0 are reported for interstitial waters dominated by a strong terrestrial signature (Jaffe et al., 2008), these higher values are likely due to absorption at 254 nm from iron, colloids, or other constituents in the sample (Weishaar et al., 2003; Hudson et al., 2007).

In our study, initial SUVA values for the peat soil leachate was 3.0 L mg-C -1 m-1 (Figure

2), similar to previously reported values for DOM derived from peatlands (Olefeldt et al., 2013), reduced and oxidized peat soils (Chow et al., 2003) and agricultural peat soils of the central Delta

(Fujii et al., 1998; Bossio et al., 2006, Fleck et al., 2004, Henneberry et al., 2012). Initial SUVA values for the plant leachates and algal leachates were below 1.0 L mg-C -1 m-1, which is comparable to crop and aquatic plants leachate values reported by Pellerin et al. (2010). These initial low SUVA values for the plant and algal leachates reflect that a large portion of this newly leached DOM includes low molecular weight, aliphatic compounds that do not absorb at 254 nm.

As expected, SUVA values increased with biodegradation during the 111 day study in all of the sources (Figure 2); biodegradation preferentially removes aliphatic, low molecular weight

DOM leaving behind more humified, high molecular weight, aromatic-containing DOM that absorbs light (e.g. Moran et al., 2000; Obernosterer and Benner, 2004; Pellerin et al., 2010). The

only exception to this occurred on day 3 when SUVA values were higher relative to days 0 and 7 in rice, tule, and algae, but lower in soil. This may result from a transient DOM pool made up of degradation byproducts generated by bacterial consumption of the highly labile DOM that was then itself consumed and/or transformed (Stedmon and Cory, 2014). By Day 111, SUVA values for the 3 plant leachates were close to or even greater than the soil leachate (2.9 to 4.1), while algae-derived DOM remained distinctly low (1.7 L mg-C -1 m-1; Figure 2).

Compared to biodegradation alone, photoexposure of degraded DOM had less effect on

SUVA values especially during the first few weeks of incubation; even at day 14 SUVA values dropped less than 10% (0.2 L mg-C -1 m-1) in all samples following photoexposure. Changes in

SUVA values due to photoexposure were fairly consistent across DOM source over time, reducing it by 10-16% in all samples on day 111 (Figure 2).

Upon evaluation of the effects of long-term biodegradation of DOM, both with and without photoexposure, it is evident that SUVA values of plant-derived DOM begin to resemble soil-derived SUVA values by day 111, suggesting that using SUVA alone as an indicator of source might not be adequate for distinguishing between DOM derived from soil and plants.

However, even after 111 days of biodegradation with and without photoexposure, algae maintained low SUVA values (<1.7 L mg-1 m-1) that are only overlapping with fresh, unaltered plant-derived DOM.

Spectral Slopes (S275-295; S290-350; S350-400)

UV-VIS absorbance spectra decrease approximately exponentially with increasing wavelength (Twardowski et al., 2004), but the shape of these absorbance curves can vary due to differences in DOM source and response to biological and photochemical alteration. To extract further information from these spectra, concentration-independent relationships between the wavelengths (i.e. spectral slopes (S275-295) and slope ratio (SR) have been shown to be useful in

providing an estimation of DOM molecular weight; high slope values have been related to low molecular weight DOM and low aromaticity (Chin et al., 1994; Helms et al., 2008). Previous

-1 -1 studies have reported S275-295 values in the range of 0.020-0.030 nm and 0.010-0.020 nm for ocean and coastal waters respectively (Del Vecchio and Blough, 2002), 0.014-0.018 nm-1 for wetlands (Helms et al., 2008), and 0.018 nm-1 for terrestrial systems (Spencer et al., 2007).

Spectral slope values for the three wavelength ranges examined here (S275-295; S290-350;

S350-400) decreased during biodegradation in all sources with the exception of plant S290-350 values and algae S350-400 values which increased; soil slope values in all three wavelength ranges generally remained unchanged (Figures 3, 4 and 5). These decreases were likely related to the loss of the labile pool of LMW, aliphatic DOM. Markedly, the algal leachate S275-295 was initially very high (0.055 nm-1) in contrast to the plant and soil leachates (0.014-0.021 nm-1), but decreased rapidly in the first three days of biodegradation to 0.013 nm-1 and continued to resemble the plant leachates through the end of the experiment. The high S275-295 value for the algal leachate may be explained by the fact that algae does not contain HMW material like polyphenols, and the rapid early loss of the LMW fraction of the DOM pool implies rapid loss of this labile pool.

Light exposure increased S275-295 and S290-350 values in all five sources, indicating either (i) loss of higher molecular weight DOM due to disaggregation or bond cleavage or (ii) an increase in LMW photoproducts due to condensation reactions (Obernosterer et al., 1999; Stepanauskas et al., 2005). Previous studies reported an increase in these spectral slope values after irradiation and attributed it to the transformation of high-molecular weight dissolved lignin to highly oxidized low-molecular weight lignin photoproducts (Opsahl and Benner 1998; Obernosterer et al., 2004;

Helms et al., 2008). However, this does not explain the increase measured in the algae leachate which does not contain lignin. In contrast to spectral slope calculated for the lower UV

wavelengths, photoexposure decreased S350-400 values; this is also again consistent with the findings of Helms et al., 2008, as well as other studies (Benner and Biddanda, 1998; Obernosterer et al., 1999; Tranvik and Bertilsson, 2001), where the decrease was associated with phototransformation of LMW material into more humic substances.

Slope Ratio (SR: S275–295/S350–400)

The slope ratio SR (S275–295/S290–350) has been linked to shifts in DOM molecular weight and photobleaching (Helms et al., 2008), with steeper slope ratios reflective of greater amounts of low molecular weight compounds. Previous studies have reported SR values for a variety of aquatic environments including 0.76-1.79 in wetlands (Helms et al., 2008, Helms et al., 2013),

0.70-2.40 in lake waters (Zhang et al., 2009) and 1.60 in ocean water (Stubbins et al., 2012). In this study, initial SR values ranged between 0.47-0.81 for plant and soil leachates and generally showed little change following biodegradation (Figure 6). Initial algae SR values were an order of magnitude higher at 58.59. As noted earlier, the freshly leached algal leachate S275–295 was quite high (0.055) and the S350–400 was quite low (0.001) which resulted in this unusually high SR, however algal SR returned to commonly reported values (1.54) within 14 days.

Exposure to light increased SR in all sources by up to 100%. These considerable changes in SR following photoexposure were also observed by Helms et al., (2008) and Spencer et al.,

(2009), and have been attributed to a shift in DOM molecular weight from HMW to LMW compounds.

Following photoexposure, soil SR values remained distinctly lower than plant and algae values for all of the measured time points (0.95 vs. 1.11-1.42), suggesting that an SR value greater than 1.00 in natural waters could be used to indicate the DOM was primarily derived from plant or algal sources. However, in the absence of photoexposure an SR value less than 1.00 could be associated with any of these sources.

Fluorescence (Indices, Ratios, PARAFAC)

Fluorescence Index (FI)

The fluorescence index (FI) has been used in a wide range of studies to distinguish DOM derived from a terrestrial source (degraded plant and soil organic matter; lower values) from a microbial source (extracellular release and leachate from bacteria and algae; higher values)

(McKnight et al., 2001; Cory et al., 2007; Cory et al., 2010). FI values in natural waters typically range between 1.2 to 1.8 (e.g. Jaffe et al., 2008; Wilson and Xenopoulos, 2009; Cory et al., 2010;

Carpenter et al., 2013; Fleck et al., 2014; Helms et al., 2013).

The initial FI value for the peat soil leachate was 1.6 and showed little change with biodegradation (Figure 7). While initially plant and algal leachate FI values were similar to peat soil (1.6 to 1.9), these values increased with microbial processing, such that by day 111 they exceeded 2.0. Values for the algal leachates showed by far the greatest change over time with final values close to 3.5. The particularly high FI value for the algal leachate supports the idea that higher FI values can be used to indicate DOM derived from phytoplankton production in the water column that has undergone bacterial processing. Other studies reporting values that exceed the typical FI range of 1.2 to 1.8 have been observed in leachates from cyanobacteria intracellular organic matter (Korak et al., 2013) and incineration plants (Zhi-gang, 2009).

Although photoexposure did not greatly affect the FI values of the plant and algal leachates during the first week of biodegradation when there was rapid loss of the bioavailable

DOM pool, later on photoexposure reduced the FI values in these sources by about 20%, decreasing any values that exceed 2.0 to the more typically reported range of 1.6-1.8 (Figure 7).

A similar decrease in FI following photoexposure was also observed in the soil leachate reducing it by 13% from 1.6 to 1.4. This reduction due to photoexposure resulted in plant and algae FI values that were similar to the FI values of soil-derived DOM prior to photoexposure (1.6). This

reveals that photoexposure can mask the DOM source signal gleaned from the FI by making plant- and algal-derived DOM resemble that of soil-derived DOM.

Humification Index (HIX)

The humification index (HIX) has been used as an indicator of source, diagenesis and sorptive capacity (Zsolnay, 1999; Ohno, 2002) and is based on the idea that as humification of

DOM proceeds, the ratio of hydrogen to carbon decreases, shifting the emission spectra of the fluorescing molecules toward the longer wavelengths. Higher values indicate an increasing degree of humification. HIX values reported have ranged between 0.8-0.9 in rice field drainage waters (Fleck et al., 2014); 0.7-0.9 in freshwater (Chen et al., 2011); 0.6-0.8 in plant and soil leachates (Ohno, 2002); and 0.8-0.9 in commercial humic acid standards (Chen et al., 2011).

Previous studies have used the HIX to identify relationships between land use practices and climatic conditions and the export of aromatic compounds in naturally drained watersheds and determined that HIX values increased with the proportion of wetlands in a watershed (Wilson and

Xenopoulos 2009); this is consistent with the observation that wetlands are often associated with humic and structurally complex DOM (Mladenov et al., 2007).

At the start of the incubation, soil HIX values were distinctly higher than all other sources

(1.0 vs. 0.2-0.4), and these high values for soil remained unchanged during the 111 days of biodegradation (Figure 8). In contrast, HIX values in all other sources increased over time as microbial processing consumed the labile portion of the DOM pool: by day 111 values were 0.8-

0.9 for the plant and algal leachates.

Photoexposure had little to no effect on soil HIX (decreased < 2%), but decreased HIX by approximately 8-18% in plant and algae sources. This reduction increased the difference in HIX values between soil derived DOM and the other DOM sources (Figure 8).

Because the soil HIX remained distinctly higher than plant and algae HIX under both bio and phot exposure, these results suggest that if the HIX in natural waters is less than 0.9 one can infer that DOM is derived from relatively recent plant and/or algal inputs. However, additional soil samples should be included in future studies.

Freshness Index (β:α)

The freshness index (β:α) is associated with the contribution of recently produced DOM

(Parlanti et al., 2000; Wilson and Xenopoulos 2009), while the biological index (BIX) (Huguet et al., 2009), a modified and renamed variation of β:α, has been similarly described as an indicator for the presence of autochthonous (microbial-derived) DOM. Both of these parameters are obtained by nearly the same calculation; β:α is the ratio of emission intensity at 380 nm divided by the emission intensity maximum observed between 420 and 435 nm, obtained at excitation

310 nm, while BIX is obtained by dividing fluorescence intensity at ex308/em380 by intensity at ex308/em430. These indices are essentially the ratio of fresh-like DOM to humic-like DOM. In this study, β:α and BIX were very highly correlated (R2 = 0.97), While there is no clear indication for which parameter is more useful for DOM characterization, because the β:α was introduced first and has been more extensively cited we suggest that it be used going forward to provide consistency between studies. Therefore only results from β:α will be discussed in detail.

β:α values measured in this study ranged from about 0.5-0.8, which is similar to the previously reported values of 0.8-0.9 by Fleck et al., (2014) for rice field drainage waters (Figure

9). β:α in all plant leachates increased from 0.5-0.8 to 0.7-0.9 during the first three days of incubation, while algae decreased (from 0.8 to 0.7) and soil remained relatively unchanged (0.5).

Following this early trend, there was a general decrease in β:α in plant- and algal-derived DOM as they underwent further microbial processing, however the magnitude and rate of this decrease differed among sources.

The effects of photodegradation on the β:α varied depending on source and degree of microbial processing (e.g. Day 3 vs. 7 vs. 111). The clearest effect was seen on day 111, when photoexposure increased β:α values for plant and algal leachates but decreased soil values (Figure

9). The result of this was that following 111 days of biodegradation followed by photoexposure, soil-derived DOM had β:α values that were lower than the other sources by 20-60% (0.55 vs. 0.6-

0.8). The opposite response of β:α to irradiation for the soil-derived DOM, which is already highly degraded in the natural environment, versus that of the plant- and algal-derived DOM, demonstrates that even after more than three months of microbial processing fundamental differences remain between these DOM pools. Further, the β:α index, which is normally associated with microbial processing, is also clearly sensitive to photochemical alteration. Even in the absence of photoexposure, although β:α values tended to decrease over time as the DOM became by definition “less fresh”, values for algae- and plant-derived leachates were highly variable and overlapping.

It should be noted that these measured changes in β:α values following photoexposure is in contrast to Fleck et al., (2014), where this index exhibited little change after irradiation; however, samples in that study were collected from rice field drainage waters, and thus the DOM may have previously been exposed to photodegradation.

Peak Ratios (C:T, A:T, C:A, C:M)

There are several fluorescent peak ratios published in the literature, here we describe the four most commonly reported (C:T, A:T, C:A, C:M; Figures 10-13). Like the freshness and biological indices, the ratios of C:T and A:T are used to describe the relative amount of humic- like DOM versus fresh-like DOM, with higher values indicating a higher proportion of degraded material. Additionally these ratios have been found to provide good discrimination of DOM source derived from microbial processing in river and lake water (Baker et al., 2008).

There was a strong correlation between the C:T and A:T ratios (R2 = 0.94; Table 4).

Initial C:T ratios were 0.1-0.3 for plant and algal samples, while soil was much higher at 6.6

(Figure 10). After 111 days of biodegradation, C:T ratios in plant and algae increased considerably to 3.2-4.9, while soil increased slightly to 7.6. Photoexposure decreases C:T in all sources; on day 111, plants and algae were reduced 53-66% to 1.2-1.7. In contrast soil C:T reduction was only 30% and remained higher relative to plant and algae leachates (5.4), suggesting that if C:T is greater than approximately 5.0 in natural waters, then it has a greater relative contribution of soil-derived DOM.

As expected due to their high correlation, A:T ratios followed similar trends to C:T following both biodegradation (increase) and photoexposure (decrease). Initial A:T ratios were

0.2-0.3 and 0.1 for plant and algal samples, respectively, while soil was much higher at 11.4

(Figure 11). After 111 days of biodegradation, plant and algae samples had a greater than ten-fold increase to 2.7-3.9 and 4.1 respectively, while soil increased only 15% to 13.2. Photoexposure decreased A:T in all sources; on day 111, plants and algae were reduced to 1.7-1.9 (28-53%) and

2.1 (48%) respectively. In contrast soil A:T reduction was only 25% and remained nearly five times higher relative to plant- and algal-derived DOM, suggesting that if A:T is greater than 4.5 in natural waters, then it has a greater relative contribution of soil-derived DOM.

Although Peaks C and A are both commonly associated with humic-like material, they have been reported to vary independently, thus suggesting they represent decoupled pools of

DOM (Kothawala et al., 2012). In this dataset there was no clear indication that the intensity of the DOM fluorescence response for Peaks A and C were affected differently by biodegradation, however, photoexposure did result in a shift in the C:A ratio (Figure 12). The initial C:A ratio for plants and algae leachates undergoing biodegradation was distinctly higher than soil, ranging between 0.9-1.1 versus 0.6.

Following biodegradation alone, on days 3 and 7 relative to other days, there was a decrease in the C:A ratio in the plant- and algal-derived DOM (Figure 12), which resulted from a more rapid loss of Peak C fluorescence compared to Peak A during the initial period of incubation (data not shown). In contrast, by day 111, the percent loss of these two pools compared to initial conditions (day 0) was either similar resulting in no change in the C:A ratio

(rice, cattail), or was greater for Peak A than Peak C resulting in an increase in the C:A ratio (tule, algae). The soil C:A ratio remained largely unaffected by microbial processing.

Photodegradation lead to a decrease in the C:A ratio, particularly in the plant and algae leachates (Figure 12). This resulted from a greater percent loss of fluorescence intensity at Peak C versus Peak A (data not shown). As a result, exposure to light diminished the distinction between the C:A ratio of these different DOM sources. Nevertheless, the soil C:A ratio remained lower at

0.5 following photodegradation compared to the other sources, suggesting that a C:A ratio below

0.6 can be associated with terrestrial soil-derived DOM.

The ratio of Peaks C to M has been used to distinguish DOM derived from a terrestrial environment versus DOM derived from a marine environment (Burdige et al., 2004; Para et al.,

2010; Romera-Castillo et al., 2011; Helms et al., 2013). We found that soil C:M remained relatively unaffected by microbial processing or photoexposure (Figure 13). Initial plant leachate

C:M ranged from 1.2-2.2 with the rice leachate having the highest values. Initial algae leachate

C:M was lower than the plant and soil leachates at 0.8. After 111 days of biodegradation rice C:M was reduced the most (59% decrease), while the cattail and tule leachates were reduced by 20% and 35%, respectively. Algae C:M was reduced by 34% to 0.54, and thus remained distinctly lower than all other biodegraded samples. While on day 3 light exposure decreased the C:M ratio, on days 7 and 111 it increased C:M in all sources. The increase in C:M values following photoexposure resulted in overlap in C:M ratios across the different DOM sources, suggesting

that this fluorescence ratio is less promising at discriminating DOM origin in cases where both biological and photolytic processing is occurring simultaneously.

PARAFAC Components (%)

The combination of EEM fluorescence and parallel factor analysis (PARAFAC) has proven to be a promising tool for studying DOM (Bro, 1997), and has been widely applied in combination with other measurements to rapidly quantify and characterize DOM across a range of environments (e.g., Stedmon and Markeger, 2005; Fellman et al., 2008; Yamashita et al., 2008;

Kowalczuk et al., 2009; Zhang et al., 2009). The aim of PARAFAC is to distill the fluorescence signatures into distinct fluorescence components that are not restricted to a single excitation- emission pair (peak-picking). This point is emphasized by the fact that the PARAFAC components are not correlated to each other (Table 4). The five modeled fluorophores (CL1-CL5) identified in this data set represent previously identified peaks associated with different DOM pools (Figure 23; Stedmon et al., 2003; Cory and McKnight, 2005; Coble, 2007, Hudson et al.,

2007). Looking at the PARAFAC components we can see that they are not restricted to an explicit area of EEMs space, with the exception of component five (C5) which is mostly confined to the low UV region corresponding to peaks B and T; all other components are comprised of at least two distinct peaks. The lack of correlation between the PARAFAC components and the specific (DOC-normalized) fluorescence peaks (Table 4) supports the idea that the model identified unique fluorophores not represented by a single peak.

PARAFAC component loadings can be examined both by their absolute values (e.g. C1,

C2) which is a reflection of the intensity of fluorescence, and by the relative contribution to total fluorescence (e.g. %C1, %C2) which is a reflection of composition. As stated above, this study focuses on the percent loadings to see if they can help us distinguish between original DOM sources. Examination of how the percent component loadings changed when the different DOM

sources were exposed to biodegradation and photoexposure reveals that components 1 and 5 are best at distinguishing DOM origin, with component 3 showing some promise.

The contribution of C5 to the overall fluorescence response in the soil-derived DOM was nearly nonexistent (<1%), but was initially high in plants (57-60%) and algae (85%) supporting the idea that %C5 (centered around ex275/em335; Figure 23) is largely indicative of the fresh pool of DOM which fluoresces in the lower UV region (Figure 18). The swift decrease of %C5 over the first week of microbial degradation in the plant (27-50% decrease) and algal (60% decrease) leachates was due to the reduction in the presence of these fluorophores relative to total fluorescence, reflecting consumption of this highly labile fraction of DOM. This loss can be related to the loss of DOC (up to 70%) which occurred during this same time period (Figure 1a;

Figure 18). Following 111 days of biodegradation, %C5 was still present in the plant and algae leachates, but the trajectory followed a continuous decline indicating that over time these leachates will trend toward the soil-derived DOM value as they continue to degrade.

In contrast to the decrease in %C5 due to biodegradation, %C5 increased following photoexposure in all sources (49->100% increase). In this case, photoexposure had little to no effect on the absolute concentration of this pool (C5, data not shown), but rather the increase in the %C5 associated with photoexposure was due to preferential loss of other pools of DOM represented by C1-C4.

In contrast to %C5, %C1 was highest in soil (54-60%) relative to plants and algae (<1-

32%) under both biodegradation and photoexposure (Figure 14). Changes in %C1 following biodegradation differed among sources: Comparing initial leachate values to day 111, soil and tule remained unchanged; cattail and rice increased; and the algae decreased to below detection.

Photoexposure lead to an increase in %C1 due to a lower loss of C1 relative to overall fluorescence (data not shown) for all sources. While the increase in %C1 values following

photodegradation makes it difficult/impossible to distinguish between plant- and algal-derived

DOM, %C1 values following both bio and photodegradation remained distinctly higher in soil- derived DOM.

Component loadings 2, 3 and 4 showed more confounded effects following bio- and photo-processing. While %C3 had distinctly different values for soil (14%), plants (33-38%) and algae (62%) by the end of the incubation period, during the first week of biodegradation sources were overlapping; and following photoexposure all sources showed values similar to soil (7-20%)

(Figure 16). Values for %C2 and %C4 were particularly overlapping for the different leachates as they were exposed to bio- and photo-degradation, and thus these parameters do not appear to be useful on their own in distinguishing DOM source and treatment (Figures 15, 17).

Fluorescence:absorbance ratio (RFE)

Fluorescence:absorbance ratios, parameters also referred to as relative fluorescence efficiencies (RFEs), indicate what proportion of the DOM absorbance pool is fluorescing. It was suggested by Stewart and Wetzel (1980) that this ratio can be used as an indicator to distinguish a

DOM pool dominated by material of LMW versus HMW, with DOM of lower weight having greater fluorescence per unit UV absorbance (i.e. higher RFE). We investigated four different ratios: (FDOM/UV340 (Klinkhammer et al., 2000); FDOM/UV370 (Downing et al., 2009); Peak

C/UV340 (Stewart and Wetzel, 1980; Belzile and Guo, 2006; Lead et al., 2006; Romera-Castillo et al., 2011); Peak C/UV370) where FDOM is measured at ex370/em460; and found that they were all highly correlated (R2 > 0.88; data not shown). Thus we focused only on RFE calculated by Downing et al., (2009) as the ratio of FDOM/UV370.

Initial RFE for soil leachate was 37.6 and increased slightly by 7% to 40.1 after 111 days of biodegradation, while plant and algal leachates were initially much lower (5.1-8.2) and increased with biodegradation (15.9-33.2 for plants; 87.6 for algae) (Figure 19). Most notably,

between day 0 and day 111 the RFE for algae increased over 10-fold to a value of almost 90, exceeding the value for biodegraded soil (40.1). However, photoexposure reduced RFE in all leachates such that values overlapped by source and treatment. Based on these results, RFE values alone do not appear to provide information that can help distinguish between DOM sources.

The measured increase in RFE following biodegradation in all sources are in contrast to the expected decrease as biodegradation preferentially removes aliphatic, low molecular weight

DOM leaving behind more humified, high molecular weight, aromatic-containing DOM (i.e. lower RFE).

Correlations between Parameters

Correlations between individual qualitative parameters were examined to gain insight into how these measurements were, or were not, related. High correlation (R2>0.65) suggests the parameters are tracking similar pools of DOM that are similarly affected by biodegradation and photoexposure (Table 4). A lower correlation (R2<0.65) suggests they are tracking unique pools that are affected differently by biodegradation and/or photoexposure.

High correlation was observed among specific (DOC-normalized) absorbance data within their respective regions of the light spectrum [i.e. ultraviolet (UV), R2=0.70-0.98; and visible

(VIS), R2=0.72-1.00)]. The poor correlation (R2<0.61) between the lower UV (254-370 nm) and higher VIS wavelengths (412-555 nm) was expected, as the wavelengths at which an organic molecule absorbs light are determined by differences in their chemical structure; thus these regions appear to be tracking different, albeit overlapping, pools of DOM. All spectral slope values (S275-295; S290-350; S350-400; Sr) showed poor correlation with each other and with all other parameters indicating they are tracking different pools of DOM.

Similar to absorbance where wavelengths in proximity to one another are correlated, the humic-like peaks (spA, spC, spM, spD, SpZ; R2=0.77-0.90) are strongly correlated to each other and the fresh-like peaks (SpB, SpT; R2=0.65) are similarly auto-correlated, which indicates within these two group that these parameters are tracking largely overlapping pools of DOM.

However, the poor correlation between parameters associated with humic-like material and those associated with fresh-like material upholds the notion that that these fluorescence regions are tracking different pools of DOM.

We expected to see stronger correlations between SUVA, FI, and HIX as these parameters all have been linked to molecular weight, aromaticity and bioavailability (Hayase and

Tsubota, 1985; Carder et al., 1989; Weishaar et al., 2003; Helms et al., 2008; Spencer et al.,

2009), but our results suggest these parameters are not redundant (R2<0.53). None of the fluorescent peak ratios (C:T, A:T, A:C, C:M) or β:α, which focuses on ratios of humic to fresh material, showed strong relationships with any of the other qualitative parameters, with the exception of C:T and A:T (R2=0.94, also discussed above), and the HIX with C:T (R2=0.73).

As discussed above, the five PARAFAC components were not highly correlated with any specific fluorescence peaks, confirming the idea that this statistical approach identified unique fluorophores not represented by a single peak. There was no strong correlations (R2>0.65) between the percent component loadings and any of the other qualitative parameters, with the following exceptions: %C1 was highly correlated (R2>0.79) to fluorescence peak ratio A:T; %C5 was highly negatively correlated to the HIX (R2>0.94; Table 4) and to specific-fluorescence peaks associated with humic-like material (R2=0.67-0.80). RFE showed no strong relationship with any other parameters.

Multivariate Statistical Analyses

Principle component analysis (PCA)

While the above discussion focused on examination of each parameter separately, or links between two parameters, a major objective of this study was to determine how and in what combination these parameters would help us discriminate between DOM source and processing.

We therefore investigated the ability of all of these qualitative parameters to distinguish original

DOM source material following biological processing and photoexposure using two multivariate statistical analyses: principle component analysis (PCA) and discriminant analysis (DA).

PCA was run on 30 absorbance and fluorescence parameters; the five PARAFAC components were not included in either PCA or DA because, unlike all of the other parameters, the components we identified are unique to this set of samples. This issue has been raised by several authors, who have highlighted the need for a reproducible, global PARAFAC model that identifies fixed fluorescent components (Murphy et al., 2011). Graphical representations of PCA output enables us to visualize how samples relate to each other based on categories of interest, which in our case includes source (peat soil, rice, cattail, tule, algae), treatment (biodegradation versus photoexposure), and time (T0 through T111).

Together, principle components 1 and 2 (PC1 and PC2, respectively) explained 71% of the total variance in the dataset (Figure 20). PC1, which explained 48.6% of the total variance, showed strong positive loadings for parameters associated with humic-like (e.g. SpC, SpD, SpZ) and HMW, aromatic moities (e.g. SUVA, SpA280). PC2, which explained 22.4% of the total variance, showed strong positive loadings for parameters representing fresh-like material (SpB,

SpT, β:α) and generally can be interpreted as being a factor associated with labile proteins and amino acids.

The scores plot for the 45 samples highlights the shift in DOM quality in the five sources over time (Figure 21). The soil leachate exhibited a high positive score on the PC1 axis and a high negative score on PC2, indicating this source is associated with the presence of HMW, aromatic compounds which further supports the notion that this component is linked to more degraded DOM. This idea was supported by little to no loss of DOC in the soil leachate over time during the incubation experiment, which confirms that these samples contained little to no fresh/labile DOM even at T0.

Initial (T0) plant and algae sources had a high negative PC1 loading indicating the predominance of fresh, LMW, low aromatic-containing, labile DOM. By day 111 these leachates shifted to a high positive PC1 loading, indicating loss of this DOM fraction and/or increases in the more degraded, humic fractions of DOM. This trajectory followed what is expected as DOM undergoes degradation: a shift from fresh-like to humic-like material (Figure 21). However, in most cases the effects of photoexposure caused the signature of the plant- and algal-derived DOM to look less degraded, as they shifted to lower PC1 values, suggesting their composition resembled DOM from earlier times. For example, the photoexposed day 111 plant and algae

DOM exhibited similar PC1 and PC2 loadings to the day 28 plant and algae sources (Figure 21).

This further illustrates the complexity in interpreting DOM quality when it has undergone the simultaneous effects of biodegradation and photoexposure.

Discriminant analysis (DA)

Unlike PCA where the primary aim is dimension reduction resulting in the clustering of similar objects based on correlating variables, discriminant analysis (DA) is a classification method used to predict the classification of a sample based on known responses. DA allocates an individual sample to a designated group on the basis of its measurements or properties by maximizing between-group variance relative to within-group variance. Analysis of these spatial

relationships allows for the identification of the most important discriminating variables that lead to proper assignment of a sample to a designated group. Two matrices (variance and covariance) are then compared by multivariate analysis of variance (MANOVA) to determine the most significant differences between the groups with respect to all variables. When statistically significant group means have been identified, classification of variables is carried out, canonical coefficients (functions) are assigned with function one providing the most overall discrimination between groups, function two providing the second most, etc. When the functions are plotted, objects that retain similar variances in the selected variables will have similar discriminant scores and thus, will cluster together into pre-identified groups; DA output then informs on the success of an object being assigned to these groups.

Because our goal was to predict the classification of source material (soil, rice, cattail, tule, algae) and treatment (biodegradation, photoexposure) based on known responses (30 optical parameters) we chose to designate 10 different groups: Group 1 is biodegraded soil; Group 2 is photoexposed soil; Group 3 is biodegraded rice; Group 4 is photoexposed rice; Group 5 is biodegraded cattail; Group 6 is photoexposed cattail; Group 7 is biodegraded tule; Group 8 is photoexposed tule; Group 9 is biodegraded algae; Group 10 is photoexposed algae (Table 5). The forward stepwise selection method for inclusion of variables was adopted, and the tolerance level was set at 0.05.

The 17 optical parameters presented in Table 6 were quantitatively determined to be the most significant (p < 0.05) parameters in distinguishing between DOM source and environmental processing; the remaining 13 parameters were not found to significantly contribute to this model.

The discriminant plot of the standardized canonical shows clear horizontal separation of the soil leachate (Groups 1, 2) from the plant and algae leachates (Groups 3-10) in the first canonical variable (Can1) (Figure 22). Thus Can1 quantifies the degree to which the soil and remaining

sources differ, which we attribute to differences in DOM composition. Can1 accounted for the majority (46.5%) of the overall variance in DOM composition and was highly significant

(p<0.0001), while Can2 accounted for a smaller variance (32.9%), but still remained highly significant (p<0.0001) and resulted in a distinct vertical separation of the biodegraded samples

(Groups 1, 3, 5, 7, 9) from those that had undergone photoexposure (Groups 2, 4, 6, 8, 10).

The biplot rays display which parameters have the most influence on maximizing between-group variance while minimizing within group variance (Figure 22). Here the classification of DOM source (soil, rice, cattail, tule, algae) is influenced most heavily by SpC,

C:M, SpM and HI, while the classification of DOM processing (biodegradation vs. photoexposure) is influenced most by SpN, SpD, SpT and SpA350.

Twelve of the 17 statistically significant qualitative indicators identified by DA were fluorescence properties, and included nearly all of the DOC-normalized specific fluorescence peaks, with the exception of SpA, while only three of the absorbance wavelengths were found to be significant suggesting that the fluorescence measurements contain more information that reveals DOM original source material. Less surprising was the DA selection of absorbance and fluorescence ratios and indices which were originally developed to characterize compositional shifts in DOM (Table 6).

Although individual optical properties changed extensively as DOM composition was altered following both biodegradation and photodegradation, particularly in the plant and algal leachates, these changes frequently resulted in overlapping optical parameter values which made it impossible to identify original source material. Results from DA demonstrate that qualitative optical parameters are more successful when evaluated in combination, rather than individually, to identify unique optical signatures that could be linked to original DOM source even after extensive biological and photochemical alteration.

CONCLUSIONS AND RECOMMENDATIONS

The goal of this study was to better understand how commonly used optical properties, whether individually or in combination, can be used to infer DOM source. Under controlled- laboratory conditions where specific sources (peat soil, plants, and algae) were exposed to biodegradation and photodegradation, we determined which parameters retained a distinct signature that could be attributed to original source, and which parameters showed overlap between sources. The results highlight the challenge of interpreting DOM source material when confounding environmental processes impact qualitative indicators. Careful consideration should be taken when characterizing DOM that has undergone environmental processing in natural waters, as it was clear that not all qualitative parameters investigated here were successful in extricating one signal (biological versus photochemical) from another or in consistently discriminating among source material. However, some interesting and potentially informative trends were observed in this study.

Highly labile DOM leached from plants and algae was consumed very rapidly indicating this material is not likely to persist in the environment, and thus except under specific conditions is not expected to make up a significant fraction of the DOM pool in natural samples. Based on results from this study, the presence of fresh labile material leached from plants and algae can be identified by the following parameter values: SUVA<2.5 L mg-C-1 m-1; HIX<0.9; C:T<5.0; and

A:T<10.0. In contrast, soil-derived DOM optical properties were much more stable, as this material has already undergone long residence time in the environment where it has been exposed to microbial processing. However photoexposure does change the optical signature of soil- derived DOM. Qualitative indicators that are most sensitive to identifying photodegraded soil- derived DOM include: C:T>5.0; A:T>10.0; freshness index (β:α)<0.5.

In the natural environment, biodegradation and photoexposure can happen simultaneously. The sometimes opposing effects of biological and photochemically-driven changes in DOM composition may confound source identification as seen in this dataset. For example biodegradation increased SUVA values while photoexposure decreased SUVA values.

This effect of one degradation process masking the signal from the other was also observed in

S275-295, FI, HIX, C:A, C:T, A:T and RFE suggesting that using these parameters alone can generate inconsistent and disparate results. Despite the significant changes in DOM composition following biological and photodegradation, seven qualitative parameters were identified that were useful in resolving between DOM derived from peat soil versus from plant and algae source material throughout the 111 days of environmental processing. Based on this dataset, thresholds unique to soil relative to plant and algae were established for each of these parameters (Table 7).

This study lent itself well to multivariate statistical analyses such as PARAFAC, PCA and discriminant analysis (DA) as these modeling techniques can reveal meaningful information from structurally complex datasets. Although the five PARAFAC components identified in this study appear to be representative of those commonly found in aquatic systems, we feel that a larger data set that includes a wider range of DOM sources should be assembled to create a global

PARAFAC model. The five components we identified are useful within this dataset, however lack of a global model means individual data sets produce unique sets of components, making it difficult to compare results across studies. While the 13-component model introduced by Cory and McKnight (2005) attempted to do this, we feel that the samples used in that study also did not suitably represent natural DOM from a range of sources, and did not take into consideration changes associated with environmental processing.

PCA demonstrated that when 30 absorbance and fluorescence parameters were combined, the optical signature of the materials did not fall out clearly by source and

environmental processing; as was seen when examining the individual parameters, optical signatures of the different sources overlapped over time, with the effects of biodegradation and photodegradation often acting in opposition. The trajectory in PCA space did however generally follow what is expected as DOM undergoes degradation: a shift from fresh-like to humic-like material.

Discriminant analysis (DA) was used to identify which qualitative indicators are the most promising for distinguishing DOM source and processing. Of the 30 qualitative indicators modeled, 17 were quantitatively determined by DA to be the most significant (p < 0.05): absorbance parameters included SUVA, SpA350, SpA412, S275-295, and S290-350, while fluorescence parameters included humic-like (SpC, SpM, SpD, SpZ) and fresh-like (SpB, SpT,

SpN) DOC-normalized fluorescence peaks as well as peak ratios (C:A, C:M) and indices (FI,

HIX, β:α).

Future recommendations for investigation include expanding the suite of DOM endmember source material. Here, the sources of DOM (peat soil, tule, rice, cattail, algae (T.

Weisfloggii) were chosen in order to relate these results to DOM in surface waters of wetlands in the Sacramento-San Joaquin Delta. Clearly there are other important sources of DOM to aquatic systems (e.g. trees, submergent vegetation, organic matter from mineral soils, and other types of pelagic and benthic algae), which we expect will have different initial DOM composition and thus optical properties than the limited five sources included in this study. In addition, anthropogenic sources of DOM (e.g. wastewater, urban run-off) represent a significant fraction of the bulk DOM pool in many systems, and also should be studied. The intensity and duration of light exposure should also be examined more closely to gain insight into how radiation photochemically alters DOM, thus impacting its bioavailability. Additionally, modifying the source treatment by performing simultaneous, sequential, and/or alternating combinations of

degradation processes (e.g. photo+bio, bio+photo+bio+photo, etc.) could elucidate which fractions of DOM are bioreactive versus those that are photoreactive as in Obernosterer and

Benner (2004). It is also important to emphasize that there are other factors that can affect optical properties, such as nonlinear mixing behavior of different DOM sources, and variability in the fluorescence signature resulting from changes in solution chemistry (Yang and Hur, 2014).

Future studies which examine how optical properties of these highly varied end-member sources of DOM change as they are exposed to microbial and photolytic processing will further our understanding of how to interpret optical measurements of water samples collected in the environment made-up of a mixture of these sources which have undergone variable degrees of microbial and photolytic processing.

TABLES

0.8

0.7

0.9

0.8

1.7

2.1

1.9

1.5

25.9

1.42

0.013

0.020

0.018

Weiss.

9.9

0.6

0.7

1.0

0.8

1.4

1.8

1.7

3.1

Rice

1.19

0.014

0.013

0.017

9.3

0.8

0.7

1.0

0.8

1.5

1.9

1.6

3.7

Tule

1.11

0.013

0.015

0.8

0.7

1.2

0.7

1.2

1.7

1.8

2.4

T111 (BIO+PHOTO) T111

17.5

1.24

0.014

0.018

0.017

Cattail

0.5

0.9

1.0

0.5

5.4

1.4

2.9

Soil

31.3

10.0

0.95

0.017

0.018

0.017

0.6

0.9

0.5

1.2

4.9

4.1

3.4

1.7

87.6

0.71

0.015

0.016

0.011

Weiss.

0.6

0.8

0.9

1.1

4.2

3.9

2.1

3.6

Rice

16.7

0.79

0.015

0.011

0.012

0.8

1.2

3.2

2.7

2.1

4.1

Tule

15.9

0.67

0.014

0.012

0.010

T111 (BIO) T111

0.6

0.8

0.9

1.0

3.4

3.5

2.2

2.9

33.2

0.64

0.017

0.015

0.011

Cattail

0.5

1.0

0.6

7.6

1.6

3.2

Soil

40.1

13.2

0.68

0.022

0.017

0.015

7.3

0.8

0.2

0.8

1.0

0.1

1.6

0.8

58.59

0.001

0.017

0.055

Weiss.

5.1

0.5

0.3

2.2

1.1

0.3

0.2

1.9

0.3

Rice

0.81

0.026

0.005

0.021

8.2

0.5

0.3

1.3

0.9

0.2

1.9

0.5

Tule

0.58

0.028

0.011

0.016

T0 (Initial) T0

8.2

0.8

0.4

1.2

1.0

0.3

1.8

0.5

0.47

0.030

0.011

0.014

Cattail

0.5

1.0

0.6

6.6

1.6

2.9

Soil

37.6

11.4

0.70

0.022

0.017

0.015

Reference

Downing al. (2009) et

(2009)

Wilson and Xenopoulos

Parlanti et al. Parlanti(2000); et

Ohno (2002)

(2011); al. (2013) et Helms

Romera-Castillo et al. Romera-Castillo et

Para et al. Para(2010); et

Burdige et al. (2004);Burdige et

Cory et al. (2010)Cory et

Baker et al. (2008); et Baker

Baker et al. (2008) et Baker

Cory et al. (2010)Cory et

McKnight et al. (2001);McKnight et

Helms et al. (2008) et Helms

(2002)

Blough and Vecchio Del

Helms et al. (2008) et Helms

Weishaar al. (2003) et

Purpose

biological and photochemical exposure; T111 (BIO) data for samples measured following 111 111 following measured samples fordata (BIO) T111 exposure; photochemical and biological

Description Description

amount of algal and non-algal DOM.

RFE isRFE an indicator relative of the

higher proportion of fresh DOM.

with higher values representing a

indicator of recently produced DOM,

The freshnessThe index is (β:α) an

degree of humification.degree

Higher values indicate an increasing

content or extent of humification. orcontent extent

Indicator of humic substance

fluorescence in a sample.

humic-like versus protein-like

An indicationAn amount of of the

fluorescence in a sample.

humic-like versus protein-like

An indicationAn amount of of the

fluorescence in a sample.

humic-like versus protein-like

An indicationAn amount of of the

fluorescence in a sample.

humic-like versus protein-like

An indicationAn amount of of the

microbial sources DOM pool. the to

contribution of terrestrial and

Shown identify to relative the

generally increase upon irradiation.

DOM molecular andweight to

Shown to be positivelyShown be to correlated to

and/or decreasing aromaticity.

low molecular materialweight

Typically higher S values indicates

and/or decreasing aromaticity.

low molecular materialweight

Typically higher S values indicates

and/or decreasing aromaticity.

low molecular materialweight

Typically higher S values indicates

content.

associated with greater aromatic

Typically a higher number is

Absorbance per unit carbon.

350-400.

275-294:

Calculation

absorbance at 370 nm.

ex370/em460 (FDOM) to

The ratioThe of fluorescence at

and 435 at nm excitation 310 nm.

emission intensity 420 between

380 divided nm maximum by the

The ratioThe of emission intensity at

at 254 ex nm.

area 300-345 435-480 + nm nm,

435-480 divided nm peak by the

The area The spectra em under the

to Peakto (ex300/em390) M intensity.

The ratioThe of Peak C (ex340/em440)

to Peak to (ex260/em450) A intensity.

The ratioThe of Peak C (ex340/em440)

to Peakto (ex275/em304) T intensity.

The ratioThe of Peak C (ex340/em440)

to Peakto (ex275/em304) T intensity.

The ratioThe of Peak (ex260/em450) A

nm andnm 520 obtained nm, at 370. ex

The ratioThe wavelengths of em at 470

UV slopeUV ratio S

over the wavelengthover range. the

function absorption the to spectrum

Nonlinear fit of an exponential

over the wavelengthover range. the

function absorption the to spectrum

Nonlinear fit of an exponential

over the wavelengthover range. the

function absorption the to spectrum

Nonlinear fit of an exponential

DOC concentration.

Absorbance at 254 divided nm by

)

-1

)]

(nm

-1

)

-1

350-400

(nm

Compositionally based absorbance and fluorescence optical properties of the five different leachates. T0 (initial) data for for data (initial) T0 leachates. different five the of properties optical fluorescence and absorbance based Compositionally

):S

-1

at 254 nm

350-400

290-350

275-295

(nm

Spectral Slope

Efficiency (RFE)

Peak Ratio (C:T)

Peak Ratio (A:T)

Peak Ratio (C:A)

Peak Ratio (C:M)

UV SlopeUV Ratio (SR)

[SUVA (L mg-C (L [SUVA

Freshness Index (β:α)

Relative Fluorescence

Flourescence Index (FI)

Specific absorbance UV

Humification Index (HIX)

275-295

Absorbance measurementsAbsorbance S

Fluorescence measurements

Table 1: Table to prior zero day on made measurements by followed of biodegradation days 111 following measured samples for data (BIO+PHOTO) T111 and of biodegradation; days photoexposure.

Table 2: Recent studies which used optical properties to identify shifts in DOM composition due to biological and/or photochemical degradation and thus infer source and environmental processing. This study is the only one we are aware of that examined biodegradation followed by photoexposure of biodegraded source material.

Source Material Treatment Reference Soil, plant and algae leachates Biodegradation followed by photoexposure of This study biodegraded source material Agricultural drainage water Photodegradation only Fleck et al., 2014 Ocean water Photodegradation only Helms et al., 2013 Lake and river water Photodegradation only Zhang et al., 2013 Gulf of Mexico and delta water Photodegradation only Shank and Evans, 2011 Crop and aquatic macrophyte leachates Biodegradation only Pellerin et al., 2010 River water Photodegradation only Spencer et al., 2009 Pond and drainage water Biodegradation and photodegradation independently Diaz et al., 2008 Soil interstitial waters Biodegradation only Fellman et al., 2008 River, swamp, Chesapeake Bay water Photodegradation only Helms et al., 2008 River and wetland Biodegradation and photodegradation independently Brooks et al., 2007 Streams Photodegradation only Larson et al., 2007 River, Chesapeake Bay water Photodegradation only Minor et al., 2007 River water Photodegradation only Mostofa et al., 2007 Lake water, pond and marsh water Photodegradation only Winter et al., 2007 Bay water (mesocosm) Photodegradation followed by biodegradation of Stedmon and Markager, 2005b photodegraded source material Chesapeake Bay and ocean water Photodegradation only Del Vecchio and Blough, 2002 Lake and bog water Photodegradation only Osburn et al., 2001 Lake water Photodegradation only Bertilsson and Tranvik, 2000 Estuary water Photodegradation followed by biodegradation of Moran et al., 2000 photodegraded source material Estuary water (mesocosm) Photodegradation only Whitehead et al., 2000 Seawater Photodegradation followed by biodegradation of Obernosterer et al., 1999 photodegraded source material Lake water Biodegradation and photodegradation independently Reche et al., 1999 River and ocean water Photodegradation only Opsahl and Benner, 1998

Table 3: Standard deviation of measurements calculated from replicate means (n=3).

Parameter Time Treatment Soil Cattail Tule Rice Weiss. Parameter Time Treatment Soil Cattail Tule Rice Weiss. DOC (mg-C L-1) 0 BIO 1.05E+00 8.24E-01 4.19E-01 2.14E-01 6.84E-01 Peak Ratio (A:T) 0 BIO 1.35E-01 1.66E-03 7.85E-04 2.30E-03 6.49E-04 3 BIO 4.88E-01 3.97E-01 1.67E-01 3.93E-01 1.34E-01 3 BIO 5.12E-01 4.76E-02 1.01E-01 1.94E-02 3.20E-02 3 BIO+PHOTO 2.18E-01 3.73E-01 8.51E-02 2.78E-01 6.30E-01 3 BIO+PHOTO 6.23E-01 1.20E-02 1.03E-03 2.42E-02 5.15E-03 7 BIO 4.04E-01 1.27E-01 3.20E-01 1.80E-01 3.14E-01 7 BIO 7.70E-02 1.48E-02 2.62E-02 3.16E-02 7.47E-03 14 BIO 2.94E-01 2.45E-01 1.23E-01 1.99E-01 1.21E-01 14 BIO 3.32E-01 2.20E-02 9.83E-02 1.42E-02 6.06E-02 14 BIO+PHOTO 6.06E-01 1.55E-01 4.56E-02 2.44E-01 2.02E-01 14 BIO+PHOTO 6.14E-01 2.65E-02 5.71E-02 2.27E-02 5.51E-02 28 BIO 5.41E-01 6.27E-02 9.51E-02 1.79E-01 6.13E-03 28 BIO 1.78E-01 4.66E-02 6.80E-02 6.16E-02 8.58E-02 111 BIO 1.11E+00 4.01E-02 4.75E-02 8.56E-02 1.85E-01 111 BIO 1.47E-01 9.26E-02 1.72E-01 1.25E-01 1.05E-01 111 BIO+PHOTO 3.42E-01 1.60E-02 6.32E-02 7.23E-02 1.67E-01 111 BIO+PHOTO 2.34E+00 6.62E-01 6.50E-02 5.68E-01 1.01E-01 SUVA (L mg-C-1 m-1) 0 BIO 5.60E-02 1.10E-02 3.92E-03 1.09E-03 1.23E-02 Peak Ratio (C:A) 0 BIO 6.85E-04 2.39E-03 3.17E-03 4.63E-03 7.31E-03 3 BIO 4.04E-02 1.87E-02 2.23E-01 6.76E-02 1.27E-02 3 BIO 6.44E-04 1.41E-02 3.80E-03 2.28E-02 2.48E-02 3 BIO+PHOTO 1.85E-02 2.20E-02 3.50E-02 2.95E-02 5.87E-02 3 BIO+PHOTO 2.30E-03 6.69E-03 8.28E-03 1.83E-02 9.24E-02 7 BIO 4.92E-02 3.41E-02 1.03E-01 4.12E-02 3.78E-02 7 BIO 1.75E-03 7.01E-03 2.73E-03 7.47E-03 1.49E-02 14 BIO 1.11E-02 3.75E-02 1.03E-01 7.09E-02 2.53E-02 14 BIO 1.23E-03 6.42E-03 1.81E-02 6.63E-02 1.09E-03 14 BIO+PHOTO 4.25E-02 2.47E-02 2.97E-02 5.31E-02 4.69E-02 14 BIO+PHOTO 1.12E-03 2.81E-03 2.69E-02 1.51E-02 7.74E-03 28 BIO 2.80E-02 4.98E-02 8.66E-02 1.16E-01 2.47E-02 28 BIO 1.74E-03 8.78E-03 1.24E-02 4.31E-03 1.80E-02 111 BIO 1.22E-01 1.58E-01 2.21E-01 1.43E-01 7.40E-02 111 BIO 1.76E-04 8.84E-03 5.97E-03 1.99E-02 1.89E-02 111 BIO+PHOTO 4.38E-02 1.28E-01 1.51E-01 4.21E-02 4.36E-02 111 BIO+PHOTO 2.40E-03 3.75E-02 4.65E-04 3.75E-03 1.35E-02 Spectral Slope 0 BIO 1.08E-04 1.50E-05 3.43E-05 6.76E-05 1.97E-04 Peak Ratio (C:M) 0 BIO 7.86E-03 2.87E-03 3.35E-03 9.12E-03 8.45E-03 -1 S275-295 (nm ) 3 BIO 1.26E-04 1.60E-03 6.60E-04 7.09E-05 6.21E-05 3 BIO 8.16E-03 6.86E-03 1.34E-02 9.54E-03 6.27E-03 3 BIO+PHOTO 1.69E-04 3.11E-04 1.62E-04 7.69E-05 1.94E-04 3 BIO+PHOTO 8.67E-03 8.01E-03 9.62E-03 1.32E-02 6.53E-03 7 BIO 7.63E-04 1.81E-04 1.53E-04 4.94E-04 6.90E-05 7 BIO 6.37E-03 1.01E-02 9.66E-03 8.69E-03 5.29E-03 14 BIO 1.64E-04 9.81E-05 3.39E-05 1.76E-04 1.38E-04 14 BIO 6.08E-03 5.67E-05 1.50E-02 5.23E-02 1.03E-02 14 BIO+PHOTO 1.61E-04 1.52E-04 4.63E-04 4.91E-04 6.71E-04 14 BIO+PHOTO 6.46E-03 1.64E-02 5.46E-03 2.32E-02 5.09E-03 28 BIO 2.10E-04 2.75E-04 1.04E-04 1.28E-04 3.69E-05 28 BIO 4.32E-03 7.14E-03 1.56E-02 8.32E-03 1.84E-02 111 BIO 5.51E-05 4.81E-04 2.97E-04 2.14E-04 5.85E-04 111 BIO 6.34E-03 6.50E-03 1.25E-02 1.02E-03 1.60E-03 111 BIO+PHOTO 4.95E-05 5.63E-04 2.87E-04 3.47E-04 3.11E-04 111 BIO+PHOTO 4.29E-03 1.50E-01 2.60E-02 1.81E-02 1.64E-02 Spectral Slope 0 BIO 1.09E-04 2.31E-05 5.40E-05 3.31E-05 7.85E-05 Relative Fluorescence 0 BIO 5.78E-01 6.82E-02 9.57E-02 8.17E-02 7.37E-02 -1 S290-350 (nm ) 3 BIO 1.80E-04 7.72E-05 1.87E-04 8.77E-05 1.11E-04 Efficiency (RFE) 3 BIO 2.14E+00 8.05E-01 1.59E+00 6.24E-01 3.10E-01 3 BIO+PHOTO 1.02E-04 1.86E-04 7.03E-05 2.06E-04 1.81E-04 3 BIO+PHOTO 6.62E-01 6.74E-01 8.51E-02 4.48E-01 1.53E-01 7 BIO 1.40E-04 2.84E-04 1.56E-04 2.76E-04 2.01E-04 7 BIO 9.90E-01 9.57E-01 2.10E-01 2.39E-01 1.11E+00 14 BIO 3.86E-05 1.74E-04 3.46E-04 3.73E-05 2.23E-04 14 BIO 1.50E-01 3.35E-01 1.10E+00 2.14E-01 2.15E+00 14 BIO+PHOTO 2.57E-05 6.25E-05 2.47E-04 2.14E-04 2.42E-04 14 BIO+PHOTO 1.96E-01 6.78E-02 2.31E-01 2.27E-01 6.03E-01 28 BIO 1.28E-04 1.31E-04 6.08E-05 5.53E-05 3.20E-04 28 BIO 7.21E-01 4.01E-01 3.71E-01 2.72E-01 4.00E+00 111 BIO 4.51E-05 1.86E-04 5.97E-04 3.07E-04 1.25E-04 111 BIO 2.22E-01 2.37E+00 1.46E+00 4.34E-01 2.58E+00 111 BIO+PHOTO 7.46E-05 1.98E-04 3.13E-04 2.88E-05 2.60E-04 111 BIO+PHOTO 4.85E-01 2.13E+00 5.41E-01 1.06E-01 1.78E-01 Spectral Slope 0 BIO 3.68E-04 1.91E-04 3.06E-04 4.41E-04 4.23E-05 PARAFAC %C1 0 BIO 1.80E+01 3.51E-02 2.01E-02 1.09E-01 4.02E-02 -1 S350-400 (nm ) 3 BIO 2.62E-04 4.79E-05 1.87E-03 2.52E-04 2.52E-05 3 BIO 4.95E-01 1.05E+00 1.32E+00 2.86E-01 9.83E-01 3 BIO+PHOTO 1.40E-04 3.64E-04 8.87E-05 8.61E-04 1.41E-04 3 BIO+PHOTO 4.13E-01 3.48E-01 1.83E-01 4.91E-01 3.05E-01 7 BIO 1.16E-03 3.75E-04 1.40E-04 4.66E-04 2.94E-04 7 BIO 6.59E-02 1.41E-01 2.15E-01 5.54E-01 2.08E-01 14 BIO 1.06E-04 4.49E-04 1.11E-03 1.35E-04 4.48E-04 14 BIO 6.55E-02 2.49E-01 2.47E-01 3.97E-01 6.18E-01 14 BIO+PHOTO 1.40E-05 1.24E-04 3.39E-04 4.01E-04 1.52E-04 14 BIO+PHOTO 2.06E-01 3.85E-01 5.94E-01 3.36E-01 2.78E-01 28 BIO 1.25E-04 3.90E-04 3.07E-04 1.77E-04 9.19E-04 28 BIO 1.02E-01 2.55E-01 3.04E-01 6.73E-02 1.19E+00 111 BIO 2.52E-05 4.42E-04 9.50E-04 2.67E-04 2.97E-04 111 BIO 9.72E-02 3.84E-01 9.24E-01 5.82E-01 0.00E+00 111 BIO+PHOTO 1.70E-04 3.89E-04 2.41E-04 2.24E-04 3.23E-04 111 BIO+PHOTO 1.05E+00 5.02E+00 9.92E-01 3.21E+00 1.16E-01 UV Slope Ratio (SR) 0 BIO 1.31E-02 3.21E-03 5.21E-03 1.18E-02 2.50E+00 PARAFAC %C2 0 BIO 4.44E+00 1.05E-02 1.01E-02 1.07E-02 3.22E-03 -1 -1 S275-295 (nm ):S350-400 (nm ) 3 BIO 1.30E-02 7.94E-02 1.43E-01 9.46E-03 1.72E+00 3 BIO 1.25E-01 5.43E-01 1.72E+00 6.96E-01 3.00E-01 3 BIO+PHOTO 7.85E-03 4.43E-02 8.03E-03 7.42E-02 2.87E-01 3 BIO+PHOTO 5.79E-02 4.99E-01 3.13E-01 3.59E-01 1.51E-01 7 BIO 4.15E-03 1.59E-02 3.35E-03 4.30E-02 2.87E-01 7 BIO 4.64E-02 4.77E-01 6.76E-01 4.95E-01 9.82E-01 14 BIO 5.09E-03 1.80E-02 5.92E-02 1.56E-02 7.53E-02 14 BIO 3.08E-02 4.53E-01 1.03E+00 4.56E-01 5.38E-01 14 BIO+PHOTO 9.40E-03 1.50E-02 1.75E-02 2.38E-02 3.67E-02 14 BIO+PHOTO 1.23E-01 3.16E-01 5.27E-01 2.75E-01 5.04E-01 28 BIO 1.26E-02 2.98E-02 9.59E-03 3.19E-03 7.27E-02 28 BIO 1.41E-01 3.63E-01 3.35E-02 4.90E-01 4.26E-01 111 BIO 2.86E-03 1.96E-02 2.40E-02 2.67E-03 5.20E-02 111 BIO 3.00E-02 3.04E-01 1.73E-01 5.07E-01 1.70E-01 111 BIO+PHOTO 1.10E-02 1.91E-02 8.24E-03 5.76E-03 6.12E-02 111 BIO+PHOTO 3.85E-01 2.89E+00 3.92E-01 1.34E+00 3.80E-01 Fluorescence Index (FI) 0 BIO 3.86E-03 2.85E-03 1.66E-02 8.17E-03 1.05E-02 PARAFAC %C3 0 BIO 4.67E+00 3.61E-02 2.52E-02 2.48E-02 1.07E-02 3 BIO 5.41E-02 1.62E-02 1.09E-02 2.37E-02 1.35E-02 3 BIO 3.28E-01 6.85E-01 1.15E+00 1.20E-01 3.00E-01 3 BIO+PHOTO 9.99E-04 1.21E-02 2.76E-02 5.81E-02 9.47E-03 3 BIO+PHOTO 3.08E-02 1.73E-01 2.89E-02 1.29E-01 2.42E-01 7 BIO 3.30E-03 6.75E-03 9.56E-03 2.59E-02 1.21E-01 7 BIO 2.83E-02 2.54E-01 8.47E-02 2.04E-01 3.10E-01 14 BIO 9.12E-03 6.37E-03 1.15E-02 1.84E-02 5.61E-02 14 BIO 3.41E-02 3.74E-01 1.12E+00 1.01E+00 8.12E-01 14 BIO+PHOTO 2.14E-03 1.11E-02 6.76E-03 2.59E-02 2.74E-02 14 BIO+PHOTO 1.87E-01 1.71E-01 5.93E-01 2.81E-01 8.02E-01 28 BIO 6.26E-03 2.08E-02 1.57E-02 2.21E-02 9.80E-02 28 BIO 6.27E-02 6.89E-01 7.24E-01 4.72E-01 1.45E+00 111 BIO 8.22E-03 1.81E-02 1.17E-02 1.65E-02 2.83E-02 111 BIO 4.43E-02 3.02E-01 9.67E-01 1.12E+00 1.70E-01 111 BIO+PHOTO 4.44E-03 4.62E-02 7.55E-03 4.31E-03 2.02E-02 111 BIO+PHOTO 3.41E-01 4.46E+00 1.50E-01 2.12E+00 5.38E-01 Humification Index (HIX) 0 BIO 3.64E-04 2.69E-04 3.47E-04 1.65E-03 5.85E-04 PARAFAC %C4 0 BIO 6.22E+00 4.74E-02 3.35E-02 1.54E-02 1.74E-02 3 BIO 1.49E-03 2.74E-02 4.76E-02 1.32E-02 5.52E-03 3 BIO 1.42E-01 1.47E-01 1.66E+00 7.62E-01 6.68E-01 3 BIO+PHOTO 2.90E-04 1.00E-02 3.37E-03 9.55E-03 4.04E-03 3 BIO+PHOTO 3.38E-01 3.35E-01 1.71E-01 4.16E-01 4.24E-02 7 BIO 1.43E-03 5.50E-03 5.03E-03 7.99E-03 3.38E-03 7 BIO 2.06E-02 8.11E-02 3.12E-01 1.11E+00 5.71E-01 14 BIO 1.56E-03 3.68E-03 2.88E-02 2.30E-03 1.08E-02 14 BIO 5.92E-02 2.23E-01 1.86E+00 8.81E-01 8.99E-01 14 BIO+PHOTO 5.60E-03 4.73E-03 1.07E-02 5.57E-03 1.86E-02 14 BIO+PHOTO 3.64E-01 3.00E-01 8.45E-01 8.83E-01 1.12E+00 28 BIO 5.04E-04 3.09E-03 7.16E-03 5.51E-03 3.02E-03 28 BIO 9.57E-02 2.03E-01 6.14E-01 5.12E-01 1.11E+00 111 BIO 1.47E-04 1.02E-02 6.86E-03 6.74E-03 4.51E-03 111 BIO 4.26E-02 1.38E+00 9.13E-01 4.02E-01 1.02E+00 111 BIO+PHOTO 8.84E-03 8.62E-02 1.54E-02 5.17E-02 1.16E-02 111 BIO+PHOTO 6.02E-01 5.55E+00 3.60E-01 3.34E-01 1.47E+00 Freshness Index (β:α) 0 BIO 2.75E-03 6.59E-04 3.27E-03 1.10E-03 7.02E-03 PARAFAC %C5 0 BIO 4.52E-02 4.73E-02 4.23E-02 9.81E-02 4.61E-02 3 BIO 2.88E-03 2.25E-02 9.96E-03 7.24E-03 8.12E-03 3 BIO 1.43E-01 2.18E+00 5.80E+00 1.53E-01 2.33E-01 3 BIO+PHOTO 6.69E-03 3.41E-03 1.95E-03 1.67E-02 1.33E-02 3 BIO+PHOTO 2.44E-02 1.07E+00 4.08E-01 2.71E-01 2.48E-01 7 BIO 3.59E-03 5.77E-03 1.18E-02 2.30E-02 1.91E-02 7 BIO 0.00E+00 6.55E-01 6.42E-01 5.52E-01 1.01E+00 14 BIO 4.88E-03 1.90E-03 2.29E-02 3.55E-03 1.92E-02 14 BIO 1.65E-01 5.25E-01 4.05E+00 1.11E+00 1.63E+00 14 BIO+PHOTO 6.95E-03 3.45E-03 3.02E-02 1.26E-02 2.16E-02 14 BIO+PHOTO 7.71E-01 6.53E-01 2.03E+00 6.37E-01 2.18E+00 28 BIO 9.46E-04 3.01E-03 2.43E-02 7.41E-03 1.95E-02 28 BIO 0.00E+00 4.17E-01 4.91E-01 1.09E+00 2.10E-01 111 BIO 1.24E-03 1.14E-02 2.81E-02 3.37E-03 3.63E-03 111 BIO 0.00E+00 1.38E+00 7.98E-01 6.79E-01 8.39E-01 111 BIO+PHOTO 1.08E-02 1.37E-01 3.56E-02 4.24E-02 8.31E-03 111 BIO+PHOTO 1.17E+00 6.80E+00 1.16E+00 6.39E+00 2.23E+00 Peak Ratio (C:T) 0 BIO 7.91E-02 1.08E-03 1.01E-03 1.44E-03 8.33E-05 3 BIO 2.98E-01 4.02E-02 8.66E-02 7.87E-03 9.50E-03 3 BIO+PHOTO 3.53E-01 5.02E-03 2.54E-03 3.23E-03 6.49E-02 7 BIO 4.08E-02 1.33E-02 1.62E-02 2.70E-02 1.98E-02 14 BIO 1.80E-01 2.73E-02 1.05E-01 7.77E-02 6.06E-02 14 BIO+PHOTO 3.15E-01 1.57E-02 3.88E-02 2.08E-02 3.96E-02 28 BIO 8.04E-02 5.64E-02 8.63E-02 6.05E-02 9.43E-02 111 BIO 8.33E-02 6.56E-02 2.17E-01 1.72E-01 5.90E-02 111 BIO+PHOTO 1.25E+00 5.12E-01 5.01E-02 4.36E-01 1.09E-01

RFE

-0.13

0.97

BIX

-0.09

0.48

HIX

-0.18

-0.14

0.25

0.00

0.01

0.00

0.37

0.63

A:T

-0.40

-0.34

-0.06

0.00

0.08

0.12

0.40

C:A

-0.06

-0.25

normalized normalized

0.50

0.73

0.00

0.94

C:T

-0.39

-0.32

-0.11

0.00

C:M

-0.11

-0.08

-0.09

-0.10

-0.01

C:M

0.16

0.11

0.00

0.02

0.03

-0.46

-0.94

-0.62

-0.72

%C5 %C5

0.06

0.00

0.03

0.24

0.01

0.07

0.11

0.01

-0.42

%C4 %C4

0.30

0.00

0.01

0.12

0.71

0.00

0.53

0.02

0.15

-0.17

-0.14

%C3

(red); relative fluorescence fluorescence relative (red);

0.21

0.01

0.48

0.00

0.16

0.19

0.08

0.06

-0.06

-0.24

-0.43

%C2

0.10

0.49

0.79

0.63

0.02

0.13

-0.34

-0.33

-0.26

-0.56

-0.44

-0.15

%C1 %C1

0.31

0.59

0.04

0.24

0.00

0.37

0.45

0.23

0.31

0.11

SpZ

-0.02

-0.01

-0.07

-0.63

SpZ

0.12

0.01

0.02

0.14

0.02

0.04

0.05

0.09

0.30

0.17

0.08

0.00

0.57

-0.08

-0.17

SpN

compositionally based parameters across the across based parameters compositionally

0.26

0.21

0.00

0.08

0.25

0.00

0.21

SpT

-0.10

-0.26

-0.39

-0.38

-0.01

-0.03

-0.35

-0.01

SpT

>0.65), while cells highlighted green indicate poor poor indicate green highlighted cells while >0.65),

0.20

0.14

0.00

0.03

0.47

0.03

0.65

-0.20

-0.41

-0.43

-0.01

-0.20

-0.02

-0.07

-0.35

-0.06

SpB

Column heading colors represent optical property property optical represent colors heading Column

0.47

0.76

0.00

0.59

0.71

0.31

0.12

0.43

0.33

0.80

0.41

-0.13

-0.08

-0.02

-0.05

-0.80

-0.08

-0.17

SpD

0.40

0.70

0.02

0.49

0.00

0.66

0.41

0.21

0.19

0.25

0.82

0.48

0.87

-0.13

-0.08

-0.03

-0.76

-0.08

-0.19

SpM

0.60

0.65

0.15

0.40

0.03

0.62

0.26

0.43

0.18

0.12

0.72

0.39

0.77

0.90

-0.16

-0.10

-0.08

-0.67

-0.09

-0.17

SpC

0.55

0.79

0.00

0.83

0.93

0.19

0.07

0.22

0.52

0.58

0.24

0.85

0.84

0.78

(purple); fluorescence peak ratios peak fluorescence (purple);

SpA

-0.31

-0.24

-0.07

-0.02

-0.79

-0.23

-0.33

SpA

0.04

0.06

0.01

0.14

0.00

0.02

0.03

-0.03

-0.14

-0.02

-0.03

-0.04

-0.03

-0.08

-0.02

-0.05

-0.06

-0.09

-0.08

-0.07

-0.05

relationships between all all between relationships

0.04

0.03

0.00

0.17

0.15

0.32

0.09

0.15

0.03

0.00

0.07

0.08

0.05

0.13

400

-0.23

-0.21

-0.02

-0.07

-0.02

-0.05

-0.10

-0.31

400

S350-

0.25

0.00

0.20

0.26

0.22

0.00

0.11

0.28

0.06

0.02

0.12

0.10

0.07

0.21

0.00

350

-0.01

-0.27

-0.07

-0.15

-0.02

-0.05

-0.07

350

S290-

0.00

0.24

0.00

0.02

0.59

0.04

295

-0.08

-0.20

-0.05

-0.01

-0.03

-0.33

-0.18

-0.15

-0.28

-0.14

-0.18

-0.17

-0.08

-0.13

295

values for for values

S275-

0.08

0.09

0.01

0.17

0.10

0.16

0.08

0.17

0.22

0.08

0.10

0.06

0.10

0.08

0.00

-0.04

-0.06

-0.01

-0.05

-0.02

-0.07

-0.02

-0.08

-0.07

-0.11

A555

0.08

0.09

0.01

0.00

0.16

0.10

0.15

0.09

0.18

0.23

0.08

0.10

0.07

0.11

0.08

0.00

1.00

-0.04

-0.05

-0.01

-0.04

-0.03

-0.06

-0.02

-0.07

-0.06

-0.11

A532

0.08

0.09

0.02

0.00

0.15

0.11

0.15

0.10

0.20

0.23

0.07

0.09

0.08

0.12

0.09

0.00

0.99

1.00

PARAFAC components PARAFAC

-0.04

-0.01

-0.05

-0.03

-0.06

-0.02

-0.07

-0.06

-0.12

A510

0.07

0.08

0.03

0.00

0.14

0.00

0.13

0.16

0.11

0.23

0.25

0.06

0.07

0.11

0.15

0.11

0.01

0.98

0.99

1.00

-0.02

-0.03

-0.05

-0.04

-0.02

-0.06

-0.05

-0.13

A488

highlighted red indicate strong correlation (R correlation strong indicate red highlighted

0.05

0.06

0.08

0.00

0.13

0.00

0.15

0.20

0.17

0.27

0.03

0.02

0.15

0.20

0.17

0.02

0.93

0.94

0.95

0.96

-0.01

-0.08

-0.10

-0.02

-0.01

-0.10

-0.04

-0.13

A440

percent

0.04

0.05

0.09

0.00

0.13

0.00

0.15

0.21

0.19

0.26

0.27

0.03

0.02

0.15

0.20

0.17

0.03

0.00

0.87

0.88

0.90

0.98

-0.01

-0.11

-0.10

-0.02

-0.14

-0.05

-0.13

A412

values values

; negative numbers indicate a negative correlation negative a indicate numbers ;negative 2

0.00

0.15

0.00

0.01

0.08

0.05

0.19

0.16

0.15

0.00

0.38

0.32

0.01

0.27

0.35

0.28

0.11

0.80

0.81

0.83

0.86

0.90

0.89

-0.04

-0.19

-0.04

-0.01

-0.05

-0.18

A370

normalized absorbance (orange); absorbance spectral slopes and UV slope ratio (green); DOC (green); ratio slope UV and slopes spectral absorbance (orange); absorbance normalized

=45)

0.00

0.21

0.00

0.04

0.06

0.10

0.24

0.16

0.01

0.47

0.37

0.00

0.37

0.46

0.36

0.18

0.00

0.72

0.74

0.76

0.80

0.83

0.80

0.98

-0.03

-0.26

-0.07

-0.03

-0.20

A350

<0.65).

0.06

0.43

0.23

0.00

0.33

0.25

0.07

0.27

0.17

0.59

0.39

0.61

0.66

0.49

0.43

0.01

0.04

0.46

0.49

0.51

0.56

0.60

0.57

0.77

0.85

-0.02

-0.01

-0.03

-0.47

-0.01

-0.02

-0.08

-0.14

A280

0.09

0.52

0.39

0.48

0.21

0.03

0.29

0.33

0.54

0.29

0.66

0.68

0.50

0.55

0.03

0.09

0.29

0.32

0.34

0.38

0.44

0.41

0.61

0.70

0.96

-0.07

-0.05

-0.04

-0.03

-0.02

-0.56

-0.07

-0.08

-0.06

-0.08

A254

(SUVA)

RFE

BIX

HIX

A:T

C:A

C:T

C:M

%C5 %C5

%C4 %C4

%C3

%C2

%C1 %C1

SpZ

SpN

SpT

SpB

SpD

SpM

SpC

SpA

S350-400

S290-350

S275-295

SpA555

SpA532

SpA510

SpA488

SpA440

SpA412

SpA370

SpA350 SpA280

SpA254

Table 4: The correlations matrix displays displays matrix correlations The 4:Table ( set fullsample DOC categories: (blue); peaks fluorescence (yellow). efficiency (R correlation

Table 5: Discriminant analysis (DA) qualitative groupings by sample type and treatment.

Group Source Treatment 1 Soil BIO 2 Soil BIO+PHOTO 3 Rice BIO 4 Rice BIO+PHOTO 5 Cattail BIO 6 Cattail BIO+PHOTO 7 Tule BIO 8 Tule BIO+PHOTO 9 Weiss. BIO 10 Weiss. BIO+PHOTO

Table 6: The 17 optical parameters quantitatively determined by Discriminant Analysis to be the most significant (p < 0.05) in distinguishing between DOM source and environmental processing. See text for details.

Parameter p- value SUVA 0.003 SpA350 0.001 SpA412 0.003 S275-295 0.001 S290-350 <0.0001 SpC <0.0001 SpM <0.0001 SpD 0.002 SpB 0.001 SpT <0.0001 SpN <0.0001 SpZ <0.0001 C:M <0.0001 C:A <0.0001 FI 0.027 HI <0.0001 β:α <0.0001

Table 7: Parameters that were found to be useful by themselves at discriminating DOM source in this study. Threshold values and the relationship of soil relative to plants and algae were established from day 111 soil results that underwent biodegradation and photoexposure.

Discriminating Parameter Threshold Soil relative to plants and algae

Spectral Slope S350-400 (nm-1) 0.025 Soil > plants and algae

Peak Ratio (A:T) 10.0 Soil > plants and algae

Peak Ratio (C:T) 5.0 Soil > plants and algae

Peak Ratio (C:A) 0.5 Soil < plants and algae

Humification Index (HIX) 0.9 Soil > plants and algae

PARAFAC %C1 0.5 Soil > plants and algae

PARAFAC %C5 0.1 Soil < plants and algae

FIGURES

Figure 1: Dissolved organic carbon (DOC) concentration (mg/L) (A) and percent loss (B) over time for the five different DOM sources: soil, rice, cattail, tule, and algae (Weiss.). Solid lines connect data collected on days 0, 3, 7, 14, 28 and 111 following biodegradation (Bio), while dotted lines connect data for biodegraded samples that were photoexposed (Photo) on days 3, 14, and 111.

Figure 2: Specific UVA absorbance at 254 nm (SUVA) values (L mg-C-1 m-1) over time. See Figure 1 caption for details.

-1 Figure 3: Spectral slope S275-295 (nm ) over time following biological and photochemical exposure. See Figure 1 caption for details.

-1 Figure 4: Spectral slope S290-350 (nm ) over time following biological and photochemical exposure. See Figure 1 caption for details.

-1 Figure 5: Spectral slope S350-400 (nm ) over time following biological and photochemical exposure. See Figure 1 caption for details.

Figure 6: UV Slope ratio S275-295: S350-400 over time following biological and photochemical exposure. See Figure 1 caption for details.

Figure 7: Fluorescence index (FI) over time following biological and photochemical exposure. See Figure 1 caption for details.

Figure 8: Humification index (HI) over time following biological and photochemical exposure. See Figure 1 caption for details.

Figure 9: Freshness index (β:α) over time following biological and photochemical exposure. See Figure 1 caption for details.

Figure 10: Fluorescence peak ratio C:T over time following biological and photochemical exposure. See Figure 1 caption for details.

Figure 11: Fluorescence peak ratio A:T over time following biological and photochemical exposure. See Figure 1 caption for details.

Figure 12: Fluorescence peak ratio C:A over time following biological and photochemical exposure. See Figure 1 caption for details.

Figure 13: Fluorescence peak ratio C:M over time following biological and photochemical exposure. See Figure 1 caption for details.

Figure 14: Parallel Factor Analysis percent component 1 (PARAFAC %C1) over time following biological and photochemical exposure. See Figure 1 caption for details.

Figure 15: Parallel Factor Analysis percent component 2 (PARAFAC %C2) over time following biological and photochemical exposure. See Figure 1 caption for details.

Figure 16: Parallel Factor Analysis percent component 3 (PARAFAC %C3) over time following biological and photochemical exposure. See Figure 1 caption for details.

Figure 17: Parallel Factor Analysis percent component 4 (PARAFAC %C4) over time following biological and photochemical exposure. See Figure 1 caption for details.

Figure 18: Parallel Factor Analysis percent component 5 (PARAFAC %C5) over time following biological and photochemical exposure. See Figure 1 caption for details.

Figure 19: Relative fluorescence efficiency (RFE) over time following biological and photochemical exposure. See Figure 1 caption for details.

Figure 20: Principle Component Analysis (PCA) loadings plot for 30 of the compositionally based absorbance and fluorescence parameters (see Table 1). See text for details.

Figure 21: Principle Component Analysis (PCA) scores plot. Points represent replicate means (n=3) for each source, day, and treatment; Colors represent treatment (red, biodegradation; blue, photoexposure of biodegraded sources); Letters represent source [S, soil; R, rice; C, cattail; T, tule; W, Weiss. (algae)]; Numbers represent incubation day (0, 3, 7, 14, 28, 111). Large ellipses indicate identifiable sample groupings associated primarily with biodegradation. Photoexposed day 111 plant and algae DOM (far right elipse) exhibits similar PC1 and PC2 loadings to the day 28 biodegraded only plant and algae sources.

iplot rays rays iplot

while while

).B

Inner ellipse ellipse Inner

oints represent represent oints

Weiss.

; Group assignments (in (in assignments ; Group

group variance variance group

, tule; Purple, Purple, tule; ,

P to indicate samples that were also photodegraded; photodegraded; also were that samples indicate to P

and

plot of the standardized canonical coefficients. canonical thestandardized of plot

uter ellipse represents 50% confidence region. region. confidence 50% represents ellipse uter

nalysis (DA) nalysis

for each source, day, and treatment; Numbers indicate days indicate Numbers treatment; and day, source, each for

=3)

iscriminant iscriminant

followed by a B indicate biodegradation indicate B a by followed

Figure 22: D 22: Figure region; confidence 95% represents ( means replicate black) Orange cattail; Green, rice; soil; Blue, (Red, source represent Colors between maximizing on influence the most have parameters which display variance. within group minimizing

dissolved dissolved

model for for model

)

PARAFAC

(algae)

Weiss.

(peat soil, tule, rice, cattail, cattail, rice, tule, soil, (peat

source material source

fluorophores identified in the Parallel Factor Analysis ( Analysis Factor Parallel the in identified fluorophores

member

end

23: Five principal Five 23:

Figure Figure matter organic

Figure 24: Example excitation-emission matrix (EEM) displaying commonly used, previously identified peak locations. Humic (degraded) material is generally associated with fluorescence Peaks A, C, D, M, and recently-identified Peak Z (Fleck et al., 2014); while the fresh-like (a.k.a. protein-like) fraction is generally associated with fluorescence in the lower UV region (Peaks B, T and N).

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