Ecosystems (2010) 13: 1006–1019 DOI: 10.1007/s10021-010-9370-1 Ó 2010 Springer Science+Business Media, LLC
Dissolved Organic Matter Characteristics Across a Subtropical Wetland’s Landscape: Application of Optical Properties in the Assessment of Environmental Dynamics Youhei Yamashita,1,2 Leonard J. Scinto,3 Nagamitsu Maie,1,4 and Rudolf Jaffe´1* 1
Southeast Environmental Research Center and Department of Chemistry and Biochemistry, Florida International University, Miami, Florida 33199, USA; 2Faculty of Environmental Earth Science, Hokkaido University, Sapporo, Hokkaido 060-0810, Japan; 3Southeast Environmental Research Center and Department of Earth and Environment, Florida International University, Miami, Florida 33199, USA; 4Department of Bio-Environmental Sciences, School of Veterinary Medicine, Kitasato University, Towada, Aomori 034-8628, Japan
ABSTRACT sively along the water flow path from high molecular weight, peat-soil and highly oxidized agricultural soilderived DOM to the north, to lower molecular weight, biologically produced DOM to the south. These results suggest that even though DOC concentration seems to be distributed conservatively, DOM sources and diagenetic processing can be dynamic throughout wetland landscapes. As such, EEM–PARAFAC clearly revealed that humicenriched DOM from the EAA is gradually replaced by microbial- and plant-derived DOM along the general water flow path, while additional humic-like contributions are added from marsh soils. Results presented here indicate that both hydrology and primary productivity are important drivers controlling DOM dynamics in large wetlands. The biogeochemical processes controlling the DOM composition are complex and merit further investigation.
Wetlands are known to be important sources of dissolved organic matter (DOM) to rivers and coastal environments. However, the environmental dynamics of DOM within wetlands have not been well documented on large spatial scales. To better assess DOM dynamics within large wetlands, we determined high resolution spatial distributions of dissolved organic carbon (DOC) concentrations and DOM quality by excitation–emission matrix spectroscopy combined with parallel factor analysis (EEM–PARAFAC) in a subtropical freshwater wetland, the Everglades, Florida, USA. DOC concentrations decreased from north to south along the general water flow path and were linearly correlated with chloride concentration, a tracer of water derived from the Everglades Agricultural Area (EAA), suggesting that agricultural activities are directly or indirectly a major source of DOM in the Everglades. The optical properties of DOM, however, also changed succes-
Key words: dissolved organic matter; dissolved organic carbon; fluorescence characteristics; excitation–emission matrix; parallel factor analysis; spatial distribution; wetlands; Everglades.
Received 24 March 2010; accepted 16 July 2010; published online 26 August 2010 *Corresponding author; e-mail:
[email protected]
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DOM Across a Subtropical Wetland’s Landscape
INTRODUCTION Substantial amounts of terrestrial dissolved organic matter (DOM) estimated at 0.25 Pg C y-1 are conveyed to coastal regions (Hedges and others 1997). Although these values are quite small compared to the oceanic DOM pool (700 Pg C, Hedges and others 1997), they are of the same order of magnitude as the annual production of semi-labile DOM in the open ocean (1.2 Pg C y-1; Hansell and Carlson 1998). Although a major fraction of terrestrial DOM is thought to be degraded photochemically and biologically in coastal regions, DOM plays an important role in riverine and coastal fluvial ecosystems by regulating light penetration (Frenette and others 2003; Hayakawa and Sugiyama 2008), maintaining pH through organic acid buffering capacity (Ceppi and others 1999; Garcı´a-Gil and others 2004), acting as a substrate for trace metal complexation (Yamashita and Jaffe´ 2008) and fueling the microbial loop (Hood and others 2009). In oligotrophic environments, a major fraction of macronutrients are known to occur as DOM-associated nitrogen and phosphorus, where, for example, greater than 90% of the total nitrogen and phosphorus in the Florida Coastal Everglades are in an organic form (Boyer and others 1997; Boyer 2006). Thus, knowledge of the environmental dynamics of DOM in terrestrial and coastal environments is essential for a better understanding of ecosystem function and biogeochemical cycling (Findlay and Sinsabaugh 2003; Battin and others 2008). However, our knowledge about the environmental dynamics of DOM on large spatial and long temporal scales remains limited. A significant limitation is the low sample throughput of analytical methods used for DOM characterization (for example, Maie and others 2006a). On the other hand, optical means for characterizing DOM allows for high sample throughput, that is, high sensitively, relatively inexpensive in comparison to other analytical techniques, and thus, recent advances in DOM characterization using optical properties have helped overcome these limitations (Jaffe´ and others 2008). In addition, this technique allows us to use real-time monitoring of CDOM with in situ instruments (for example, Spencer and others 2007). The relationships between riverine dissolved organic carbon (DOC) concentration and the percentage of wetlands within its catchment are often reported (Mulholland 2003 and references therein). In addition, recent studies reported the relationship between stream DOM quality/composition and the percentage of wetlands in a catchment, where greater contributions of soil-derived
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humic-like DOM were observed as the proportion of wetlands increased (Wilson and Xenopoulos 2009; Williams and others 2010). Such enhanced contributions of humic substances to DOM have been suggested to result in decreased biodegradability of DOM (Balcarczyk and others 2009; Fellman and others 2008; 2009). Thus, wetlands are a quantitatively and qualitatively important factor in the determination of DOM quality and quantity in streams, and consequently in coastal areas. However, little is known about the large scale environmental dynamics of DOM in freshwater wetlands, including source assessments and biogeochemical alteration and removal processes (Mladenov and others 2007a). The important contribution of humic-like DOM from wetlands to streams (Wilson and Xenopoulos 2009; Williams and others 2010) suggests that soils are major contributors to the DOM pool in wetlands. Conversely, exudation and leaching of DOM from aquatic plants and litter has also been considered an important source of wetland DOM (Maie and others 2006b; Mladenov and others 2007b; Osborne and others 2007; Larsen and others 2010). Although plant/litter-derived DOM has usually been considered labile or semi-labile compared to soil-derived DOM (Mladenov and others 2007b), some components of litter leachates seem to be resistant to rapid degradation (Mladenov and others 2007b). Spectroscopic and chemical characterization of fulvic acids, obtained from the Okavango Delta wetland system surface water and plant leachates, showed similar characteristics, suggesting a progressive enrichment of DOM by plantderived material occurs along the wetland’s flow path (Mladenov and others 2007a). Similarly, stable and radio-carbon isotopic signatures of DOM showed clear source changes along the flow path in northern Everglades wetlands (Wang and others 2002; Stern and others 2007). Thus, it has been proposed that DOM quality and quantity is dynamically altered with distance downstream within wetlands. High resolution mapping on spatial and temporal scales of DOM characteristics (quantity and quality) would be helpful in clarifying the alteration of DOM within these ecosystems. However, only a few such studies have been reported in the literature (Mladenov and others 2005). In this study, we present the spatial variability of DOC concentration and DOM quality across the Everglades landscape, one of the largest subtropical wetlands in the world. The main purpose of this study was to clarify changes in DOM quantity and
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quality along a broadly defined southerly water flow path and to determine factors controlling DOM quantity and quality within the Everglades. To achieve this purpose, water samples were collected across the freshwater Greater Everglades Ecosystem (GEE) as part of the U. S. Environmental Protection Agency (USEPA) Everglades Regional Environmental Monitoring and Assessment Program (R-EMAP) Phase III, and high sample throughput optical methods were applied to evaluate the high resolution spatial distribution of DOM quality. Thus, results presented here might be important not only for a better understanding of DOM dynamics in wetlands but also for providing base-line information of DOM dynamics in the GEE as an important biogeochemical parameter in the Everglades restoration plan (Scheidt and Kalla 2007).
SITE DESCRIPTION The original Everglades were the southern terminus of a large watershed (28,205 km2) that included the Kissimmee River, Lake Okeechobee, and the Everglades. Water seasonally overflowing the southern boundary of Lake Okeechobee moved southward toward Florida Bay in a continuous shallow free-flowing wetland that was the Everglades. Beginning in the early 1880s the Everglades was ditched, diked, and drained to promote agricultural and urban development. Thus, the original Everglades were transformed from a free-flowing wetland into a series of hydrologically isolated surface water impoundments known as Water Conservation Areas (WCAs). The purpose of the WCAs was largely to receive and store agricultural runoff from the Everglades Agricultural Area (EAA), to provide flood prevention for urban areas, to provide recreational benefits, and to supply water for the natural system requirements of Everglades National Park (ENP) (Light and Dineen 1994) (Figure 1). The drainage of the EAA exposed the naturally accumulated organic peat soils to the atmosphere allowing microbial oxidation and compaction and resulted in the loss of over 2 m of soil in some areas (Sklar and others 2005). The use of fertilizers in the EAA and runoff from developed areas added increased nutrients, most notably phosphorus, to the historically nutrient-poor downstream receiving WCAs (McCormick and others 2002). Notable effects have been an increase in the areal coverage of P-loving cattail (Typha spp.), and an increase in surficial soil P concentrations (Childers and others 2003). The reduction in the spatial extent of the original Everglades,
Figure 1. Sampling site locations in the Everglades wetlands. EAA Everglades Agricultural Area, LNWR Loxahatchee National Wildlife Refuge, WCA Water Conservation Area, ENP Everglades National Park, and SRS Shark River Slough.
ecological damage to large portions of the remaining Everglades, and the need for water supply to ENP and the developed areas of SE Florida prompted passage of the 1994 Everglades Forever Act (EFA) and the subsequent creation of the Comprehensive Everglades Restoration Plan (CERP) (Sklar and others 2005) in an attempt to partially undo past damage. DOM represents a significant pool of carbon, nitrogen and phosphorus in the Everglades ecosystem, and its environmental dynamics, which are expected to be impacted through CERP implementation, are still not well understood. Thus, the main objectives of this work are to shed light on the DOM dynamics of a large wetland on a spatial landscape scale.
METHODS Surface water samples were collected during the wet season (November 2005) at 118 sites stretching over approximately 5500 km2 of the GEE from the marshes located south and east of the EAA down to ENP, including WCA-1 (Loxahatchee National Wildlife Refuge—LNWR), WCA-2, and WCA-3 (Figure 1) as part of a larger and more inclusive ‘‘Everglades Ecosystem Assessment Phase III’’ a
DOM Across a Subtropical Wetland’s Landscape Regional Environmental Monitoring and Assessment Program (R-EMAP) conducted by USEPA Region 4 (Scheidt and Kalla 2007). The sampling design employed was probability-based and used a stratified random sampling design to assure sufficient samplings occurred in each sub-area permitting a quantitative analysis of environmental information across the spatial landscape scale and resulting in an average distribution of 1 sample per 47 km2 (Scheidt and Kalla 2007). The R-EMAP Project sampled several ecosystem compartments including soil, soil porewater, surface water, detrital layers, vegetation, and periphyton for a multitude of physicochemical parameters, some of which were used in correlation analysis in this study. Details of sampling and analytical procedures can be found in the EPA-related references including Scheidt and Kalla (2007) and Stober and others (2001). Sites were accessed by helicopter and samples were collected using pre-cleaned, brown Nalgene polyethylene bottles and stored on ice during transportation to the laboratory. In the laboratory, samples were filtered through pre-combusted GF/F filters and kept refrigerated (4°C) until analysis. DOC concentration was determined by hightemperature combustion with a Shimadzu TOCVCSH TOC analyzer. The UV–Vis absorption spectra were measured from 240 to 800 nm in a 0.01 m quartz-windowed cell using a Varian Cary 50 Bio. A blank scan (Milli-Q water) was subtracted from each sample spectrum. The blank subtracted spectra were baseline-corrected by subtracting average values ranging between 700 and 800 nm from the entire spectra, and then, converted to absorption coefficient, a (k) (m-1) as follows: aðkÞ ¼ 2:303AðkÞ=z where A(k) is absorbance provided by the spectrophotometer and z is the path length of the cuvette, that is, 1 cm. In the present study, the absorption coefficient at 350 nm (a350) was reported as a quantitative parameter of chromophoric DOM (CDOM). As a qualitative parameter of the absorbance spectra, the spectral ratio (SR) was calculated as the ratio of spectra slope (S) obtained from 275–295 nm and 350–400 nm, respectively (Helms and others 2008). The SR parameter has been proposed as an index of molecular weight (MW) of DOM with the SR value inversely related to the MW (Helms and others 2008). Excitation–emission matrix (EEM) spectra were obtained using a Horiba Jovin Yvon SPEX Fluoromax-3 spectrofluorometer according to procedures described by Maie and others (2006a) and Santı´n and others (2009). Inner-filter corrections were
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carried out for each EEM using their absorbance spectrum (McKnight and others 2001), and then, an EEM of Milli-Q water was subtracted from sample EEMs. The specific instrument components were also corrected with excitation and emission correction files supplied by the manufacturers. EEMs were then corrected to the area under the water Raman peak at 350 nm (measured daily) and converted to quinine sulfate units (QSU). The fluorescence index (FI) was estimated as the ratio of the fluorescence intensity at 470 to 520 nm emission excited at 370 nm (Cory and McKnight 2005; Maie and others 2006a). Parallel factor analysis (PARAFAC) was carried out for the evaluation of the EEM data set. PARAFAC statistically separates the complex EEM measured into its individual underlying fluorescent groups with specific excitation and emission spectra and provides both a qualitative (fluorescent groups) and quantitative (fluorescence intensity of each group) model of the data (Stedmon and Bro 2008). Thus, this technique may be ideally suited to detect small, but potentially significant vitiations in DOM composition in apparently similar aquatic environments. The approach of PARAFAC modeling to EEMs has been described in detail elsewhere (Stedmon and others 2003; Ohno and Bro 2006). The PARAFAC modeling was carried out in MATLAB (Mathworks, Natick, MA) with the DOMFluor toolbox (Stedmon and Bro 2008). For a better understanding of DOM environmental dynamics in the Everglades, we used a large number of samples obtained from the Florida Coastal Everglades including samples reported here for the PARAFAC modeling (n = 1394). After validation of the PARAFAC modeling, we obtained an eight component model (Table 1). Details for the spectral characteristics of these components can be found in Chen and others (2010). Spatial mapping of quantitative and qualitative parameters was carried out using inverse distance weighted methods in ArcGIS (ver. 9.3) software. Correlations (R) were determined using StatView 5.0. The differences in parameters between sampling area were determined by non-parametric Mann–Whitney U tests using StatView 5.0.
RESULTS Spatial Distribution of DOC Concentration and Optical Parameters The distribution of DOC showed spatial variation where DOC concentrations were highest adjacent to the canal in WCA-2A and lowest at the southern
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Table 1.
Characteristics of the Eight Components Derived from the Florida Coastal Everglades
Component
Excitation maximum
Emission maximum
Stedmon and Markager (2005)
Cory and McKnight (2005)
Assignment
C1 C2
