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Browning of Boreal Freshwaters Coupled to Carbon-Iron Interactions along the Aquatic Continuum

Browning of Boreal Freshwaters Coupled to Carbon-Iron Interactions along the Aquatic Continuum The color of freshwaters, often measured as absorbance, influences a number of ecosystem services including biodiversity, fish production, and drinking water quality. Many countries have recently reported on increasing trends of water color in freshwaters, for which drivers are still not fully understood. We show here with more than 58000 water samples from the boreal and hemiboreal region of Sweden and Canada that absorbance of filtered water (a ) co-varied with dissolved organic carbon (DOC) concentrations (R = 0.85, P,0.0001), but that a relative to DOC is increased by the presence of iron (Fe). We found that concentrations of Fe significantly declined with increasing water retention in the landscape, resulting in significantly lower Fe concentrations in lakes compared to running waters. The Fe loss along the aquatic continuum corresponded to a proportional loss in a , suggesting a tight biogeochemical coupling between colored dissolved organic matter and Fe. Since water is being flushed at increasing rates due to enhanced runoff in the studied regions, diminished loss of Fe along the aquatic continuum may be one reason for observed trends in a , and in particular in a /DOC 420 420 increases. If trends of increased Fe concentrations in freshwaters continue, water color will further increase with various effects on ecosystem services and biogeochemical cycles. Citation: Weyhenmeyer GA, Prairie YT, Tranvik LJ (2014) Browning of Boreal Freshwaters Coupled to Carbon-Iron Interactions along the Aquatic Continuum. PLoS ONE 9(2): e88104. doi:10.1371/journal.pone.0088104 Editor: Tomoya Iwata, University of Yamanashi, Japan Received October 29, 2013; Accepted January 8, 2014; Published February 5, 2014 Copyright:  2014 Weyhenmeyer et al. This is an open-access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited. Funding: Financial support was received from the Swedish Research Council (VR) and the Swedish Research Council for Environment, Agricultural Sciences and Spatial Planning (Formas). This work is part of and profited from the networks financed by Nordforsk (CRAICC and DomAQUA) and the Norwegian Research Council (Norklima ECCO). The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript. Competing Interests: The authors declare that we no competing interests exist. * E-mail: [email protected] strongly positively related to a /DOC ratios. Since a /DOC Introduction 420 420 ratios have previously been shown to decrease along the aquatic During the last decade there have been several reports of continuum [12,13] we further hypothesized that decreases in a / increasing water color in the Northern Hemisphere, first reviewed DOC are related to Fe concentration decreases along the aquatic by [1] and later confirmed by various other studies, e.g. [2–4]. The continuum. Along the aquatic continuum we had data from small trends have frequently been attributed to increasing dissolved headwater streams, non-headwater streams, lakes, large lakes, and organic carbon (DOC) concentrations, resulting from changes in river mouths. both climate and atmospheric deposition [5]. Recently, also the importance of increasing iron (Fe) concentrations have been Material and Methods pointed out as a possible driver for water color increases [6,7]. Fe and DOC are not independent from each other since Fe can form Databases stable complexes with DOC [8]. Such complexes turn waters into In this study we used 58888 Swedish water samples from 6339 a dark, brownish color, with a pronounced effect on absorbance lakes, including Sweden’s three largest lakes Va¨nern, Va¨ttern and measures [6,9,10]. Ma¨laren, 209 streams, including 11 small headwater stream sites In a recent laboratory study [11], it has been shown that and 52 river mouths. The water systems are distributed all over addition of Fe to DOC solutions resulted in a linear increase in the Sweden, and represent waters of the boreal and hemiboreal light absorption at a wavelength of 410 nm. This linear increase region. Most of the 6339 lakes are small (median lake area: 0.16 continued until a maximum Fe binding capacity to dissolved km ), shallow (median mean lake depth: 3.2 m) and nutrient poor organic matter was reached and Fe precipitated _ENREF_33[11]. (median total phosphorus concentration: 11 mgL ) lakes with a Thus, apart from a DOC effect on absorbance, Fe has an additive median pH of 6.7. All data are from a water depth of 0.5 m and effect on absorbance until dissolved organic matter becomes have been sampled and analyzed by the laboratory of the saturated. How frequent an additive Fe effect on absorbance in Department of Aquatic Sciences and Assessment at the Swedish natural waters occurs is not known yet. We therefore used data on University of Agricultural Sciences according to standard limno- Fe, DOC and absorbance at 420 nm (a ) from more than 58000 logical methods. A detailed method description and all data can water samples of the Swedish and Canadian boreal and freely be downloaded at http://webstar.vatten.slu.se/db.html. hemiboreal region and analyzed how Fe contributes to a The data have been derived during the past 30 years. Most relative to DOC. We hypothesized that Fe concentrations are water systems were sampled more than once, and 66 water systems PLOS ONE | www.plosone.org 1 February 2014 | Volume 9 | Issue 2 | e88104 Water Color Changes and the Role of Iron had monthly Fe, DOC and absorbance data available, in lakes at headwater streams, additional data on 18 water physical and least during the ice-free season (usually May to October) since chemical variables as well as 21 GIS derived catchment variables. 1996. These 66 water systems comprised 21 lakes, 11 streams and The variables, that were also available for 66 water systems with 34 river mouths. Apart from time series we had 7196 water complete time series, included water temperature, pH, alkalinity, samples that originated from large-scale lake inventories during conductivity, calcium, magnesium, sodium, potassium, chloride, autumns between 2000 and 2012, taken at 0.5 m when the water sulfate, ammonium-nitrogen, nitrate-nitrogen, total nitrogen, total phosphorus, reactive silica, manganese, size of catchment area, column was mixed at water temperatures around 4uC. More information on these large-scale lake inventories can be found at site-specific altitude, site-specific annual precipitation (average 1961–1990), site-specific annual mean air temperature (average http://webstar.vatten.slu.se/db.html. 1961–1990), site-specific growing season length (average 1961– In addition to the Swedish data we also used a dataset (247 1990), site-specific annual global radiation (average 1961–1990), water samples) of 30 Canadian boreal lakes to verify our results. and percentage of grass, other cultured land, coniferous forest, The Canadian data as well as methods are available in [14]. coniferous forest on wetland, pasture, mixed forest, mixed forest Finally, we also used a database on meteorological variables, on wetland, exploited land, clear-cut, deciduous, urban, agricul- available at http://www.smhi.se. In this database, named climate ture, open wetland, other vegetation and lake surface cover in the indicators, 10-year running means of annual precipitation, air catchment area. In this study we used the percentage of lake temperature and growing season length based on data from surface cover in the catchment area (% Water) as a proxy for water meteorological stations across entire Sweden are available. retention in the landscape. We justify this approach by a significant relationship between calculated water retention in the Variables Swedish landscape and % Water (R = 0.27, P,0.0001, n = 1419 For all 58888 water samples we had data on total iron, total based on data published by [12]). organic carbon and on absorbance of 0.45 mm filtered water at 420 nm in a 5-cm cuvette (AbsF ). Although iron and 420nm/5cm Statistics organic carbon were measured as total concentrations they are in All statistical tests, run in JMP, version 10.0, considered the this study considered as dissolved. This assumption is based on non-normal distribution of the data material by using log- previous investigations where it was shown that in Swedish boreal transformations for linear relationships and by applying non- waters particulate organic carbon is negligible as it only accounts parametric tests. Tests we used were: A) Simple linear relation- for less than 5% of the total organic carbon [15]. To further ships. When the data were non-normally distributed according to strengthen the assumption of negligible particulate matter a Shapiro-Wilk test we log-transformed the data which in all cases influence on iron and organic carbon measurements in Swedish was successful in receiving normally distributed data. B) Partial boreal waters we compared absorbance of filtered and unfiltered least squares regression models (PLS). The PLS allowed to predict water at 420 nm, which we had available for 46787 out of the a and a /DOC by a variety of water and catchment variables. 420 420 58888 water samples. We received a very good correspondence We chose PLS because of the method’s insensitivity to X-variable’s (R = 0.83, P,0.0001, n = 46787) and a slope of 1.2. The slope interdependency and the insensitivity to deviations from normality exceeded 1 at lowest iron and organic carbon concentrations but [18]_ENREF_2. PLS is commonly used to find fundamental approached 1.0 at high concentrations of both iron and organic relations between two matrices (X and Y) where the variance in X carbon. Thus, in Swedish boreal waters high iron and organic is taken to explain the variance in Y. In PLS, X-variables are carbon concentrations occurred when particulate matter in the ranked according to their relevance in explaining Y, commonly water samples was absent. Consequently, we considered the and also in this study expressed as VIP-values [18]. The higher the influence of particulate matter on iron and organic carbon VIP values are the higher is the contribution of an X-variable to measurements negligible and used the abbreviations Fe and DOC the model performance. VIP-values exceeding 1 are considered as throughout the text. We, however, chose the absorbance ratio important X-variables. In this study, we restricted our discussions between unfiltered and filtered water at 420 nm as a variable to to very important X-variables, i.e. variables that had VIP values account for variations in particulate matter in our water samples. exceeding 1.8. The PLS modeling approach was applied for We converted AbsF data to the Napierian absorption 420nm/5cm median values of 5837 water systems for which a variety of water coefficient as recommended by [16], according to: and catchment variables were available. C) Standard least squares models. Standard least squares models are special cases of PLS AbsF (10) 420nm=5cm where single Y-variables are predicted. The models allow an a ~ ð1Þ L immediate graphical comparison between predicted and measured values. We used these models for predictions of a and a / 21 420 420 where a is the Napierian coefficient in m , AbsF is 420 420nm/5cm DOC with DOC, Fe and a /a as input variables. 420unfiltered 420filtered the measured absorbance of filtered water, ln(10) is the natural D) Wilcoxon-test. The Wilcoxon test is a non-parametric test for logarithm of 10 and L is the optical path-length in m. For the group comparison. We applied this test for a comparison of Canadian data we had to use an additional transformation as variables between headwater streams, non-headwater streams, absorbance of filtered water was measured at 440 nm in a 10-cm lakes, large lakes and river mouths. E) Mann-Kendall trend cuvette (AbsF ). For the transformation we used the 440nm/10cm analyses. The non-parametric Mann-Kendall test [19] gives a following equation according to [17]: measure whether long-term changes of a variable are significant (P,0.05) or not (P$0.05). We applied Mann-Kendall tests on : : annual mean values of variables that came out as significant in the AbsF 1:402 : 440nm=10cm 0:0169 20 AbsF ~ ð2Þ 420nm=5cm PLS modelling approach (see test B described above). For the analyses we used the data from the 66 water systems with complete monthly time series. F) De-trending methods. To assess a Fe- Apart from Fe, DOC and a we had, for 5837 waters independent DOC effect on a we de-trended a by Fe, i.e. we 420 420 420 comprising 5664 lakes, 6 small headwater streams and 167 non- used the residuals of a linear relationship between log Fe and log PLOS ONE | www.plosone.org 2 February 2014 | Volume 9 | Issue 2 | e88104 Water Color Changes and the Role of Iron a and related these residuals to DOC concentrations. Likewise we assessed the DOC-independent Fe influence on a by relating the residuals of a log DOC- log a relationship to Fe. For model results we restricted ourselves to report on R values since they were equal to R adjusted values when we considered the first two decimals. Results Variations in a and main drivers The median a of 58888 Swedish water samples was 21 th 21 th 5.58 m (5 percentile: 0.83 m and 95 percentile: 22.15 m ). Highest a values were observed in streams (median: 6.40 m ) and lowest in large lakes (median: 1.86 m ). Using partial least squares analysis to predict variations in a across 5837 waters for which we had complete catchment and water physico-chemical data available (21 and 18 variables, respectively; see methods) we found that DOC, Fe, pH and Si were most influential in explaining a variations (highest VIP values, all exceeding 1.8, in a partial least squares analysis). From the catchment variables the percentage of coniferous forest and the percentage of lake surface cover in the catchment came out as most influential for a variations (VIP value 1.6 and 1.3, respectively). The strongest relationship of a to a single variable was achieved for DOC (linear relationship on log-transformed data: R = 0.82, P,0.0001, n = 5837). Also Fe was highly significantly related to a (linear relationship on log-transformed data: R = 0.73, P,0.0001, n = 5837). Considering both DOC and Fe as input variables in a standard least squares model we were able to explain 89% of a variations across the 5837 water systems, and 86% when we used all available DOC and Fe data from 58888 water samples. For the model performance, both DOC and Fe made significant contributions (P,0.0001, n = 58888). When the influence of Fe was separated from the DOC signal on a by linear de-trending (see method F in method part) we found that DOC could only explain 38% of a from which the Fe signal had been removed (linear relationship: R = 0.38, P,0.0001, n = 58888). Likewise the Fe contribution to a from which the DOC signal had been removed was reduced to 25% (P,0.0001, n = 58888). Examining the residuals of the standard least squares a model with DOC and Fe as input variables we found them highly negatively related to the amount of particulate matter in the water, here defined as the absorbance ratio between unfiltered and filtered water at 420 nm (linear relationship: R = 0.47, P,0.0001, n = 46787). Adding the influence of particulate matter as input variable in the a model we were able to predict as much as 92% of a variations across various temporal and spatial scales Figure 1. Prediction of absorbance (a ) by dissolved organic (Fig. 1a). All three input variables had a highly significant influence carbon (DOC), iron (Fe) and particulate matter (particles) for on the model performance (Fig. 1b–c). Without particulate matter 46787 Swedish water samples. Particulate matter was assessed by the absorbance ratio between unfiltered and filtered water (see the model performance decreased to R = 0.85, P,0.0001, methods). 92% of the a variations could be explained by the simple n = 46787. (0.73+0.76?lnDOC+0.38?ln- standard least squares model (panel A; a =e Fe20.83?lnParticles) ) where all three input variables made a significant Variations in a /DOC and main drivers 420 contribution to the model performance, here shown by model leverage Although DOC and a co-varied well we observed large plots (panels B–D). Removing the input variable particles from the model, the model performance decreased to R = 0.85, P,0.0001, variations in a /DOC between 58888 Swedish water samples, th th n = 46787. Using only DOC as input variable the model performance ranging from 0.22 (5 percentile) to 1.12 (95 percentile) with a was R = 0.73, P,0.0001, n = 46787. median of 0.69. Variations in a /DOC were best explained by doi:10.1371/journal.pone.0088104.g001 Fe, pH and Si (highest VIP values, all exceeding 1.8, in a partial least squares analysis using 38 water and catchment variables from concentrations .5mg L a and DOC approached a 1:1 ratio 5837 waters as input variables). Taking all available 58888 water (Fig. 2a). The equation of the logarithmic relationship between Fe samples into consideration Fe showed a positive relationship to and a /DOC from the Swedish lakes was also valid for a set of a /DOC. The relationship was logarithmic, with fastest changes 21 Canadian lakes (Fig. 2b). in a /DOC at Fe concentrations below 1 mg L (Fig. 2a). At Fe PLOS ONE | www.plosone.org 3 February 2014 | Volume 9 | Issue 2 | e88104 Water Color Changes and the Role of Iron Figure 2. Relationships between iron (Fe) and the carbon specific absorbance (a /DOC) based on all available data from Swedish lakes, streams and river mouths (panel A) and confirmed by data from Canadian lakes (panel B). In panel B we predicted a /DOC by using the regression equation of panel A and obtained the regression line which is shown. Note the different scales between panel A and B. doi:10.1371/journal.pone.0088104.g002 Fe and DOC along the aquatic continuum and effects on Fe and DOC concentrations co-varied generally well, both in Swedish and Canadian waters (linear relationship on log- Figure 3. Iron (Fe), dissolved organic carbon (DOC), absor- transformed data: R = 0.44, P,0.0001, n = 58888 and bance (a ), Fe/DOC and a /DOC ratios in relation to the 420 420 R = 0.58, P,0.0001, n= 247, respectively). The co-variation was percentage of lake surface area in the catchment area (% strongest within and between small headwater streams (linear Water). For the figure, site-specific long-term median data of 5837 different lakes and streams were used. Taking the median of each of the relationship on log-transformed data: R = 0.65, P,0.0001, 11% Water categories and applying a simple exponential decay along n = 1421), and weakest within and between river mouth waters the % Water gradient we received highly significant results (P,0.0001, (linear relationship on log-transformed data: R = 0.27, P,0.0001, 2 2 n = 11; R = 0.78 for Fe/DOC in panel A, R = 0.84 for a /DOC in panel B, 2 2 2 n = 11667). The slopes between the Fe-DOC relationships varied R = 0.95 for Fe in panel C, R = 0.89 for a in panel D and R = 0.88 for substantially along the aquatic continuum, also reflected by DOC in panel E). doi:10.1371/journal.pone.0088104.g003 significant differences in Fe/DOC ratios between lakes and running waters (Wilcoxon-test: P,0.0001). Median Fe/DOC ratios in headwater streams, non-headwater streams and river Fe, DOC and a temporal changes mouths had a value of 0.05 while the median value for lakes was Analyzing time series of Fe, DOC and a from 66 water (34 0.03 and for large lakes as low as 0.01. Thus, lakes contained less river mouths, 21 lakes and 11 streams) since 1996 we found Fe in proportion to DOC compared to running waters. Also significantly increasing trends for DOC in 43 waters, for Fe in 29 absolute Fe concentrations were lower in lakes, and we found waters and for a in 25 waters (Mann-Kendall: P,0.05; Fig. 5). significantly lower Fe concentrations in lakes and large lakes None of the water systems showed significantly decreasing trends compared to headwater streams, non-headwater streams and river in Fe, DOC and a . In 13 waters we observed significantly mouths (Wilcoxon-each-pair-test: P,0.0001). Along with lower Fe increasing trends in Fe/DOC (Mann-Kendall: P,0.05). In 8 of in lakes also a was at low levels. The DOC-specific absorbance, 420 these waters also a significantly increased (Mann-Kendall: i.e. a /DOC, showed similar patterns as Fe/DOC: highest in 420 P,0.05). Significant trends in a /DOC were rare for this time streams and lowest in lakes, in particular large lakes. Relating Fe, period, only occurring in 6 waters (Mann-Kendall: P,0.05). Apart DOC and a to the percentage of lake surface cover in the 420 from Fe, DOC and a trends, we found significantly increasing catchment area we found a highly significant negative relationship trends also for the variables that were most important for a (Fig. 3). The Fe and a decrease with increasing % Water was variations: Si showed significantly increasing trends in 43 waters faster than for DOC, resulting in significantly decreasing a / 420 (Fig. 5), pH in 10 waters, and a /a in 10 waters 420unfiltered 420filtered DOC and Fe/DOC ratios with increasing % Water (Fig. 3). The (Mann-Kendall: P,0.05). At the same time as Fe, DOC and a decreases in Fe and a along the % Water were proportionally increased in Swedish freshwaters, also Sweden-specific long-term similar in size (Fig. 4). running means of precipitation and growing season length PLOS ONE | www.plosone.org 4 February 2014 | Volume 9 | Issue 2 | e88104 Water Color Changes and the Role of Iron Discussion Additive Fe effects on a As shown in earlier studies (e.g. [20–22]), our analyses of more than 58000 water samples from the Swedish and Canadian boreal and hemiboreal region confirmed that a co-varied strongest with DOC concentrations, suggesting that DOC is the overall main driver for water color in boreal waters. Although strong, the DOC-a relationship still exhibited considerable variation across temporal and spatial scales. We attribute the variability in a / DOC ratios to an additive effect of Fe on a , as indicated by a substantial model improvement with inclusion of Fe as indepen- dent variable. Figure 4. Decreasing iron (Fe), dissolved organic carbon (DOC) An additive Fe effect on absorbance, apart from a DOC effect, and absorbance (a ) with increasing percentage of lake has earlier been related to Fe-DOC complexation where highest surface area in the catchment area (% Water). The figure shows the predicted values of Fe, DOC and a from the simple exponential absorbance was reached when Fe was bound to DOC [10,23]. decay functions along the % Water gradient presented in Fig. 3. Fe and The strong co-variation between Fe and DOC in our waters, in a decline equally fast with increasing % Water. The Fe and a 420 420 particular in headwaters, suggests that Fe-DOC complexation is decline is substantially faster than the decline of DOC. % Water can be ubiquitous. Laboratory studies have shown that Fe-DOC com- seen as a proxy for water retention in the landscape (see methods). plexation will reach a plateau when dissolved organic matter is doi:10.1371/journal.pone.0088104.g004 saturated with Fe, with no further Fe-DOC binding and no further increases in carbon specific absorbance occurring when additional significantly increased during 1996 to 2012 (Mann-Kendall: Fe is added [11]. Using waters from a humic lake in the P,0.001; Fig. 5). There was no significant trend in long-term laboratory, [10] found that Fe and carbon specific absorbance running means of air temperatures across Sweden during this time showed a strong positive relationship up to 1 mg L Fe. At higher period (Mann-Kendall: P.0.05). Fe concentrations, increases in carbon specific absorbance became small. [10] used a quadratic function to describe the relationship between Fe and carbon specific absorbance. We used a here a logarithmic function since we suggest that a /DOC reaches a constant value along a Fe concentration gradient when DOC is saturated with Fe. The threshold value of 1 mg L Fe as a breakpoint for a substantial additive effect of Fe (apart from the DOC effect) on absorbance, seems to hold even for boreal waters in general as we found relatively constant a /DOC ratios when Fe exceeded 1 mg L (Fig. 2a and b). Most of the boreal waters analyzed in this study had Fe concentrations less than 1 mg L , suggesting that Fe increases will result in a /DOC increases in many freshwaters of the boreal and hemiboreal region. Provided that variations in a /DOC are influenced by Fe- DOC complexation with highest ratios when Fe is bound to DOC, we expect pH to play a major role for a /DOC variations due to a strong pH effect on Fe complexation [8]. This expectation was supported by a significant pH effect on a /DOC in our PLS models. Based on our results we suggest that water color is primarily driven by DOC but that Fe when it is bound to DOC will cause additional browning of waters. Lakes as Fe sinks and effects on a When Fe and DOC are imported from soils into waters they are usually tightly coupled, in this study indicated by highly significant Fe and DOC relationships in headwaters (R = 0.65, P,0.0001). In headwaters Fe, DOC and a reached maximum values while they all declined with increasing % Water in the catchment (Fig. 3), which we use here as a proxy for water retention in the landscape (see methods). We suggest that decreases in Fe, DOC and a along the aquatic continuum are a result of several Fe and DOC Figure 5. Temporal development of dissolved organic carbon transformation processes during transport from land to sea: (DOC), absorbance (a ), iron (Fe) and reactive silica (Si) in Swedish freshwaters and changes in long-term annual precip- phototransformation [24,25], flocculation and burial in lake itation across Sweden since 1996. The DOC, a , Fe and Si data 420 sediments [15], microbial degradation [26] and dilution by inputs (panels A–D) are based on annual mean values from 66 lakes, streams of waters from other sources that frequently enter downstream and river mouths for which complete monthly time series were systems [12] and that might be poor in DOC and Fe. We found available. Thus, for each year, 66 data points have been used for the that lakes were particularly efficient at removing Fe and a , percentile calculations. For panel E, 10-year running means of data from resulting in decreased Fe/DOC and a /DOC ratios. Since the entire Sweden have been used (see methods). doi:10.1371/journal.pone.0088104.g005 decline in Fe and a in relation to DOC along the % Water PLOS ONE | www.plosone.org 5 February 2014 | Volume 9 | Issue 2 | e88104 Water Color Changes and the Role of Iron gradient was proportionally equal in size we suggest that an a decrease during water transport through the landscape is a result of a Fe loss in lakes. Fe in lakes can be lost by flocculation and sedimentation processes which has been shown to affect a [15]. Fe flocculation and sedimentation processes can result in a selective Fe loss in comparison to DOC as recently reported and discussed for the large Swedish lake Ma¨laren [7]. That sedimen- tation of Fe complexes takes places in lakes finds also evidence in a recent study by [27] who frequently detected Fe-OC complexes in all kinds of sediments around the globe. We suggest that Fe-DOC complexes that have been exported from soils are lost along the aquatic continuum. This suggestion is supported by a study of [28] who found that in Swedish river mouths waters up to 99% of dissolved Fe occurred as ferrihydrite which is rarely bound to organic matter [29]. Less frequent occurrence of Fe-DOC complexes in river mouths waters might explain why our Fe- DOC relationships became weaker along the aquatic continuum. Decreases in a /DOC along the aquatic continuum have been observed earlier [13]. It was suggested that the selective a loss in comparison to DOC is a result of DOC transformation processes during transport from land to sea. Here we relate the Figure 6. Fate of iron (Fe), dissolved organic carbon (DOC) and a /DOC decline along the aquatic continuum for the first time absorbance (a ) along the aquatic continuum under normal to Fe losses in lakes. In [7] it was shown that in the large lake wet conditions (panel A) and in a wetter climate (panel B). Ma¨laren Fe decreased 6.3 times faster than imported DOC. We When water travels from headwaters to river mouths and passes lakes found here that Fe decreased on average only 2.3 times faster than Fe, DOC and a all decline (compare Fig. 3 and Fig. 4). It is suggested DOC along a water retention time gradient (Fig. 3). This that a concomitant Fe, DOC and a decline in surface waters of lakes is a result of Fe-OC complexes that can flocculate and reach bottom discrepancy may result from the fact that water retention of a waters and sediments (panel A). In a wetter climate with a consequent single lake ecosystem is not comparable to water retention in the faster flushing of waters through lakes the settling of Fe-OC complexes landscape [12], in particular not since we use here % Water as a towards bottom waters and sediments becomes less efficient and Fe- proxy for water retention in the landscape. In addition, most of OC complexes reach downstream waters, where they cause strong our study lakes were small unproductive shallow lakes with declines in a (panel B). The conceptual figure assumes that Fe-OC frequent events of sediment resuspension [30] where the burial complexes mainly originate from soils. doi:10.1371/journal.pone.0088104.g006 capacity of Fe might be limited. quality changes, in particular a change towards less colored DOC. Increasing Fe contribution to a on a temporal scale DOC becomes less colored towards deeper soil layers where DOC Like [6] we found significant increases in DOC, Fe and a . [6] is more extensively processed [31]. These deeper soil layers are proposed a number of explanations why Fe concentrations and reached by groundwater. Since we found significant increases in Si thereby a in Swedish waters might increase, one being climate which is a mineralization product and an indicator of groundwater change induced increases in anoxic conditions in organic soils. inputs [32] we attribute increases in less colored DOC to an Changes of processes along the aquatic continuum were not a increased export of DOC from deeper soil layers, probably from focus of their study and consequently not taken into consideration. mineral soil layers that are rich in both Si and Fe. The increase in We propose here that changes in Fe and consequently in a DOC exports from deeper soil layers might be caused by the might indeed be related to increasing Fe soil exports but that increase in long-term precipitation (Fig. 5). The significance of Si changes in the Fe processing along the aquatic continuum also on a was not only detectable on a temporal scale but also on a need attention. We found that Fe and a losses along the aquatic spatial scale: using PLS, Si was one of the most important variables continuum decrease with decreasing water retention in the explaining a . Thus, understanding a changes requires an landscape (Fig. 4). Especially lakes played a central role for Fe 420 420 understanding of DOC sources that determine the proportions and a losses along the aquatic continuum. We suggest that faster between colored and uncolored DOC. water flushing through lakes due to increased precipitation as In case less colored DOC presently increases as suggested observed across Sweden (Fig. 5) will result in higher Fe and a in downstream water systems compared to normal wet years (Fig. 6). above, we attribute a /DOC increases to Fe concentration increases. As discussed above climate change induced decreases in According to our study, lakes are efficient in removing Fe from the water column. Thus, lakes function not only as efficient DOC sinks the efficiency of Fe transformation processes along the aquatic continuum might be one explanation for Fe concentration [30] but probably also as efficient Fe sinks which has effects on a , in particular on a /DOC. If Fe is lost in lakes in form of Fe- increases but increased Fe soil exports are also highly likely. We 420 420 DOC complexes then faster water flushing through the landscape argue, like we did for DOC quality, that due to a long-term would imply less time for sedimentation of Fe-DOC complexes in precipitation increase and a longer growing season length deeper lakes with consequent more Fe-DOC complexes reaching the sea soil layers that are usually rich in Fe and Si are drained. This (Fig. 6). argumentation corresponds to the results of [33] who reported on From our observed widespread increasing DOC trends across increased Fe exports from soils with increasing wetness. Since we Swedish freshwaters we expected more significant a increases in also found a significant increase in particulate matter, i.e. in the waters. According to our results a increases were mainly a /a , we suggest that water flushing through soils 420 420unfiltered 420filtered restricted to waters in which also Fe increased. Significant DOC has increased. We further suggest that podzolization plays an trends that obviously did not affect a might be a result of DOC important role for the fate of Fe. Podzolization is a process where PLOS ONE | www.plosone.org 6 February 2014 | Volume 9 | Issue 2 | e88104 Water Color Changes and the Role of Iron Fe is complexed with dissolved organic matter and transported proportions have been quantified we will be able to fully downward in the soil profile [34]. If these deeper soil profiles are understand how water color will respond to further environmental flushed Fe-DOC complexes will be exported from soils into surface changes. waters. Podzolization is especially strong beneath conifers [34], which might explain why the percentage of coniferous forest in the Acknowledgments catchment area came out as the most important catchment Many thanks go to the Swedish Environmental Protection Agency and the variable in our a model. staff of the laboratory of the Dept. of Aquatic Sciences and Assessment for Finally, Fe increases might also be a result of mineralization rate financing, sampling and analyzing thousands of water, and to the Swedish increases as a response to the longer growing seasons. Like runoff Meteorological and Hydrological Institute for making meteorological data changes, mineralization rate changes would also result in freely available. We are also thankful to Jakob Nisell and Roger Mu¨ller for concomitant Fe and Si changes, as we observed in this study. providing GIS data, to Karsten Kalbitz for fruitful discussions and to John We conclude that DOC and Fe soil exports as well as DOC and Pastor for constructive comments. Fe transformation processes during transport from land to sea need to be considered to understand why many freshwaters are Author Contributions browning. Brownish waters influence a number of ecosystem Conceived and designed the experiments: GW. Performed the experi- services including biodiversity [35], fish production [36], and ments: GW. Analyzed the data: GW YP LT. Contributed reagents/ drinking water quality [37]. Future studies on proportions between materials/analysis tools: GW YP LT. Wrote the paper: GW YP LT. colored and uncolored DOC and between dissolved monomeric inorganic and colloidal Fe are strongly needed. First when these References 1. 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Kritzberg ES, Ekstro¨m SM (2012) Increasing iron concentrations in surface dissolved organic carbon in regulating the UV transparency of three lakes on the waters - a factor behind brownification? Biogeosciences 9: 1465–1478. Pocono Plateau. Limnology and Oceanography 42: 239–249. 7. Kohler SJ, Kothawala D, Futter MN, Liungman O, Tranvik L (2013) In-Lake 25. Va¨ha¨talo AV, Salonen K, Munster U, Ja¨rvinen M, Wetzel RG (2003) Processes Offset Increased Terrestrial Inputs of Dissolved Organic Carbon and Photochemical transformation of allochthonous organic matter provides Color to Lakes. Plos One 8. bioavailable nutrients in a humic lake. Archiv fu¨r Hydrobiologie 156: 287–314. 8. Maranger R, Pullin MJ (2003) Elemental complexation by dissolved organic 26. Sondergaard M, Middelboe M (1995) A cross-system analysis of labile dissolved matter in lakes: implications for Fe speciation and the bioavailability of Fe and P. organic-carbon. Marine Ecology Progress Series 118: 283–294. In: Findlay SEG, Sinsabaugh RL, editors. Aquatic ecosystems: Interactivity of 27. Lalonde K, Mucci A, Ouellet A, Gelinas Y (2012) Preservation of organic matter dissolved organic matter. San Diego: Academic Press. in sediments promoted by iron. Nature 483: 198–200. 9. Canfield DE, Linda SB, Hodgson LM (1984) Relations between color and some 28. Wallstedt T, Bjorkvald L, Gustafsson JP (2010) Increasing concentrations of limnological characteristics of Florida lakes. Water Resources Bulletin 20: 323– arsenic and vanadium in (southern) Swedish streams. Applied Geochemistry 25: 1162–1175. 10. Maloney KO, Morris DP, Moses CO, Osburn CL (2005) The role of iron and 29. Neal C, Lofts S, Evans CD, Reynolds B, Tipping E, et al. (2008) Increasing iron dissolved organic carbon in the absorption of ultraviolet radiation in humic lake concentrations in UK upland waters. Aquatic Geochemistry 14: 263–288. water. Biogeochemistry 75: 393–407. 11. 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Wold S, Sjostrom M, Eriksson L (2001) PLS-regression: a basic tool of increased precipitation? Aquatic Sciences 66: 231–238. chemometrics. Chemometrics and Intelligent Laboratory Systems 58: 109–130. PLOS ONE | www.plosone.org 7 February 2014 | Volume 9 | Issue 2 | e88104 http://www.deepdyve.com/assets/images/DeepDyve-Logo-lg.png PLoS ONE Unpaywall

Browning of Boreal Freshwaters Coupled to Carbon-Iron Interactions along the Aquatic Continuum

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Abstract

The color of freshwaters, often measured as absorbance, influences a number of ecosystem services including biodiversity, fish production, and drinking water quality. Many countries have recently reported on increasing trends of water color in freshwaters, for which drivers are still not fully understood. We show here with more than 58000 water samples from the boreal and hemiboreal region of Sweden and Canada that absorbance of filtered water (a ) co-varied with dissolved organic carbon (DOC) concentrations (R = 0.85, P,0.0001), but that a relative to DOC is increased by the presence of iron (Fe). We found that concentrations of Fe significantly declined with increasing water retention in the landscape, resulting in significantly lower Fe concentrations in lakes compared to running waters. The Fe loss along the aquatic continuum corresponded to a proportional loss in a , suggesting a tight biogeochemical coupling between colored dissolved organic matter and Fe. Since water is being flushed at increasing rates due to enhanced runoff in the studied regions, diminished loss of Fe along the aquatic continuum may be one reason for observed trends in a , and in particular in a /DOC 420 420 increases. If trends of increased Fe concentrations in freshwaters continue, water color will further increase with various effects on ecosystem services and biogeochemical cycles. Citation: Weyhenmeyer GA, Prairie YT, Tranvik LJ (2014) Browning of Boreal Freshwaters Coupled to Carbon-Iron Interactions along the Aquatic Continuum. PLoS ONE 9(2): e88104. doi:10.1371/journal.pone.0088104 Editor: Tomoya Iwata, University of Yamanashi, Japan Received October 29, 2013; Accepted January 8, 2014; Published February 5, 2014 Copyright:  2014 Weyhenmeyer et al. This is an open-access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited. Funding: Financial support was received from the Swedish Research Council (VR) and the Swedish Research Council for Environment, Agricultural Sciences and Spatial Planning (Formas). This work is part of and profited from the networks financed by Nordforsk (CRAICC and DomAQUA) and the Norwegian Research Council (Norklima ECCO). The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript. Competing Interests: The authors declare that we no competing interests exist. * E-mail: [email protected] strongly positively related to a /DOC ratios. Since a /DOC Introduction 420 420 ratios have previously been shown to decrease along the aquatic During the last decade there have been several reports of continuum [12,13] we further hypothesized that decreases in a / increasing water color in the Northern Hemisphere, first reviewed DOC are related to Fe concentration decreases along the aquatic by [1] and later confirmed by various other studies, e.g. [2–4]. The continuum. Along the aquatic continuum we had data from small trends have frequently been attributed to increasing dissolved headwater streams, non-headwater streams, lakes, large lakes, and organic carbon (DOC) concentrations, resulting from changes in river mouths. both climate and atmospheric deposition [5]. Recently, also the importance of increasing iron (Fe) concentrations have been Material and Methods pointed out as a possible driver for water color increases [6,7]. Fe and DOC are not independent from each other since Fe can form Databases stable complexes with DOC [8]. Such complexes turn waters into In this study we used 58888 Swedish water samples from 6339 a dark, brownish color, with a pronounced effect on absorbance lakes, including Sweden’s three largest lakes Va¨nern, Va¨ttern and measures [6,9,10]. Ma¨laren, 209 streams, including 11 small headwater stream sites In a recent laboratory study [11], it has been shown that and 52 river mouths. The water systems are distributed all over addition of Fe to DOC solutions resulted in a linear increase in the Sweden, and represent waters of the boreal and hemiboreal light absorption at a wavelength of 410 nm. This linear increase region. Most of the 6339 lakes are small (median lake area: 0.16 continued until a maximum Fe binding capacity to dissolved km ), shallow (median mean lake depth: 3.2 m) and nutrient poor organic matter was reached and Fe precipitated _ENREF_33[11]. (median total phosphorus concentration: 11 mgL ) lakes with a Thus, apart from a DOC effect on absorbance, Fe has an additive median pH of 6.7. All data are from a water depth of 0.5 m and effect on absorbance until dissolved organic matter becomes have been sampled and analyzed by the laboratory of the saturated. How frequent an additive Fe effect on absorbance in Department of Aquatic Sciences and Assessment at the Swedish natural waters occurs is not known yet. We therefore used data on University of Agricultural Sciences according to standard limno- Fe, DOC and absorbance at 420 nm (a ) from more than 58000 logical methods. A detailed method description and all data can water samples of the Swedish and Canadian boreal and freely be downloaded at http://webstar.vatten.slu.se/db.html. hemiboreal region and analyzed how Fe contributes to a The data have been derived during the past 30 years. Most relative to DOC. We hypothesized that Fe concentrations are water systems were sampled more than once, and 66 water systems PLOS ONE | www.plosone.org 1 February 2014 | Volume 9 | Issue 2 | e88104 Water Color Changes and the Role of Iron had monthly Fe, DOC and absorbance data available, in lakes at headwater streams, additional data on 18 water physical and least during the ice-free season (usually May to October) since chemical variables as well as 21 GIS derived catchment variables. 1996. These 66 water systems comprised 21 lakes, 11 streams and The variables, that were also available for 66 water systems with 34 river mouths. Apart from time series we had 7196 water complete time series, included water temperature, pH, alkalinity, samples that originated from large-scale lake inventories during conductivity, calcium, magnesium, sodium, potassium, chloride, autumns between 2000 and 2012, taken at 0.5 m when the water sulfate, ammonium-nitrogen, nitrate-nitrogen, total nitrogen, total phosphorus, reactive silica, manganese, size of catchment area, column was mixed at water temperatures around 4uC. More information on these large-scale lake inventories can be found at site-specific altitude, site-specific annual precipitation (average 1961–1990), site-specific annual mean air temperature (average http://webstar.vatten.slu.se/db.html. 1961–1990), site-specific growing season length (average 1961– In addition to the Swedish data we also used a dataset (247 1990), site-specific annual global radiation (average 1961–1990), water samples) of 30 Canadian boreal lakes to verify our results. and percentage of grass, other cultured land, coniferous forest, The Canadian data as well as methods are available in [14]. coniferous forest on wetland, pasture, mixed forest, mixed forest Finally, we also used a database on meteorological variables, on wetland, exploited land, clear-cut, deciduous, urban, agricul- available at http://www.smhi.se. In this database, named climate ture, open wetland, other vegetation and lake surface cover in the indicators, 10-year running means of annual precipitation, air catchment area. In this study we used the percentage of lake temperature and growing season length based on data from surface cover in the catchment area (% Water) as a proxy for water meteorological stations across entire Sweden are available. retention in the landscape. We justify this approach by a significant relationship between calculated water retention in the Variables Swedish landscape and % Water (R = 0.27, P,0.0001, n = 1419 For all 58888 water samples we had data on total iron, total based on data published by [12]). organic carbon and on absorbance of 0.45 mm filtered water at 420 nm in a 5-cm cuvette (AbsF ). Although iron and 420nm/5cm Statistics organic carbon were measured as total concentrations they are in All statistical tests, run in JMP, version 10.0, considered the this study considered as dissolved. This assumption is based on non-normal distribution of the data material by using log- previous investigations where it was shown that in Swedish boreal transformations for linear relationships and by applying non- waters particulate organic carbon is negligible as it only accounts parametric tests. Tests we used were: A) Simple linear relation- for less than 5% of the total organic carbon [15]. To further ships. When the data were non-normally distributed according to strengthen the assumption of negligible particulate matter a Shapiro-Wilk test we log-transformed the data which in all cases influence on iron and organic carbon measurements in Swedish was successful in receiving normally distributed data. B) Partial boreal waters we compared absorbance of filtered and unfiltered least squares regression models (PLS). The PLS allowed to predict water at 420 nm, which we had available for 46787 out of the a and a /DOC by a variety of water and catchment variables. 420 420 58888 water samples. We received a very good correspondence We chose PLS because of the method’s insensitivity to X-variable’s (R = 0.83, P,0.0001, n = 46787) and a slope of 1.2. The slope interdependency and the insensitivity to deviations from normality exceeded 1 at lowest iron and organic carbon concentrations but [18]_ENREF_2. PLS is commonly used to find fundamental approached 1.0 at high concentrations of both iron and organic relations between two matrices (X and Y) where the variance in X carbon. Thus, in Swedish boreal waters high iron and organic is taken to explain the variance in Y. In PLS, X-variables are carbon concentrations occurred when particulate matter in the ranked according to their relevance in explaining Y, commonly water samples was absent. Consequently, we considered the and also in this study expressed as VIP-values [18]. The higher the influence of particulate matter on iron and organic carbon VIP values are the higher is the contribution of an X-variable to measurements negligible and used the abbreviations Fe and DOC the model performance. VIP-values exceeding 1 are considered as throughout the text. We, however, chose the absorbance ratio important X-variables. In this study, we restricted our discussions between unfiltered and filtered water at 420 nm as a variable to to very important X-variables, i.e. variables that had VIP values account for variations in particulate matter in our water samples. exceeding 1.8. The PLS modeling approach was applied for We converted AbsF data to the Napierian absorption 420nm/5cm median values of 5837 water systems for which a variety of water coefficient as recommended by [16], according to: and catchment variables were available. C) Standard least squares models. Standard least squares models are special cases of PLS AbsF (10) 420nm=5cm where single Y-variables are predicted. The models allow an a ~ ð1Þ L immediate graphical comparison between predicted and measured values. We used these models for predictions of a and a / 21 420 420 where a is the Napierian coefficient in m , AbsF is 420 420nm/5cm DOC with DOC, Fe and a /a as input variables. 420unfiltered 420filtered the measured absorbance of filtered water, ln(10) is the natural D) Wilcoxon-test. The Wilcoxon test is a non-parametric test for logarithm of 10 and L is the optical path-length in m. For the group comparison. We applied this test for a comparison of Canadian data we had to use an additional transformation as variables between headwater streams, non-headwater streams, absorbance of filtered water was measured at 440 nm in a 10-cm lakes, large lakes and river mouths. E) Mann-Kendall trend cuvette (AbsF ). For the transformation we used the 440nm/10cm analyses. The non-parametric Mann-Kendall test [19] gives a following equation according to [17]: measure whether long-term changes of a variable are significant (P,0.05) or not (P$0.05). We applied Mann-Kendall tests on : : annual mean values of variables that came out as significant in the AbsF 1:402 : 440nm=10cm 0:0169 20 AbsF ~ ð2Þ 420nm=5cm PLS modelling approach (see test B described above). For the analyses we used the data from the 66 water systems with complete monthly time series. F) De-trending methods. To assess a Fe- Apart from Fe, DOC and a we had, for 5837 waters independent DOC effect on a we de-trended a by Fe, i.e. we 420 420 420 comprising 5664 lakes, 6 small headwater streams and 167 non- used the residuals of a linear relationship between log Fe and log PLOS ONE | www.plosone.org 2 February 2014 | Volume 9 | Issue 2 | e88104 Water Color Changes and the Role of Iron a and related these residuals to DOC concentrations. Likewise we assessed the DOC-independent Fe influence on a by relating the residuals of a log DOC- log a relationship to Fe. For model results we restricted ourselves to report on R values since they were equal to R adjusted values when we considered the first two decimals. Results Variations in a and main drivers The median a of 58888 Swedish water samples was 21 th 21 th 5.58 m (5 percentile: 0.83 m and 95 percentile: 22.15 m ). Highest a values were observed in streams (median: 6.40 m ) and lowest in large lakes (median: 1.86 m ). Using partial least squares analysis to predict variations in a across 5837 waters for which we had complete catchment and water physico-chemical data available (21 and 18 variables, respectively; see methods) we found that DOC, Fe, pH and Si were most influential in explaining a variations (highest VIP values, all exceeding 1.8, in a partial least squares analysis). From the catchment variables the percentage of coniferous forest and the percentage of lake surface cover in the catchment came out as most influential for a variations (VIP value 1.6 and 1.3, respectively). The strongest relationship of a to a single variable was achieved for DOC (linear relationship on log-transformed data: R = 0.82, P,0.0001, n = 5837). Also Fe was highly significantly related to a (linear relationship on log-transformed data: R = 0.73, P,0.0001, n = 5837). Considering both DOC and Fe as input variables in a standard least squares model we were able to explain 89% of a variations across the 5837 water systems, and 86% when we used all available DOC and Fe data from 58888 water samples. For the model performance, both DOC and Fe made significant contributions (P,0.0001, n = 58888). When the influence of Fe was separated from the DOC signal on a by linear de-trending (see method F in method part) we found that DOC could only explain 38% of a from which the Fe signal had been removed (linear relationship: R = 0.38, P,0.0001, n = 58888). Likewise the Fe contribution to a from which the DOC signal had been removed was reduced to 25% (P,0.0001, n = 58888). Examining the residuals of the standard least squares a model with DOC and Fe as input variables we found them highly negatively related to the amount of particulate matter in the water, here defined as the absorbance ratio between unfiltered and filtered water at 420 nm (linear relationship: R = 0.47, P,0.0001, n = 46787). Adding the influence of particulate matter as input variable in the a model we were able to predict as much as 92% of a variations across various temporal and spatial scales Figure 1. Prediction of absorbance (a ) by dissolved organic (Fig. 1a). All three input variables had a highly significant influence carbon (DOC), iron (Fe) and particulate matter (particles) for on the model performance (Fig. 1b–c). Without particulate matter 46787 Swedish water samples. Particulate matter was assessed by the absorbance ratio between unfiltered and filtered water (see the model performance decreased to R = 0.85, P,0.0001, methods). 92% of the a variations could be explained by the simple n = 46787. (0.73+0.76?lnDOC+0.38?ln- standard least squares model (panel A; a =e Fe20.83?lnParticles) ) where all three input variables made a significant Variations in a /DOC and main drivers 420 contribution to the model performance, here shown by model leverage Although DOC and a co-varied well we observed large plots (panels B–D). Removing the input variable particles from the model, the model performance decreased to R = 0.85, P,0.0001, variations in a /DOC between 58888 Swedish water samples, th th n = 46787. Using only DOC as input variable the model performance ranging from 0.22 (5 percentile) to 1.12 (95 percentile) with a was R = 0.73, P,0.0001, n = 46787. median of 0.69. Variations in a /DOC were best explained by doi:10.1371/journal.pone.0088104.g001 Fe, pH and Si (highest VIP values, all exceeding 1.8, in a partial least squares analysis using 38 water and catchment variables from concentrations .5mg L a and DOC approached a 1:1 ratio 5837 waters as input variables). Taking all available 58888 water (Fig. 2a). The equation of the logarithmic relationship between Fe samples into consideration Fe showed a positive relationship to and a /DOC from the Swedish lakes was also valid for a set of a /DOC. The relationship was logarithmic, with fastest changes 21 Canadian lakes (Fig. 2b). in a /DOC at Fe concentrations below 1 mg L (Fig. 2a). At Fe PLOS ONE | www.plosone.org 3 February 2014 | Volume 9 | Issue 2 | e88104 Water Color Changes and the Role of Iron Figure 2. Relationships between iron (Fe) and the carbon specific absorbance (a /DOC) based on all available data from Swedish lakes, streams and river mouths (panel A) and confirmed by data from Canadian lakes (panel B). In panel B we predicted a /DOC by using the regression equation of panel A and obtained the regression line which is shown. Note the different scales between panel A and B. doi:10.1371/journal.pone.0088104.g002 Fe and DOC along the aquatic continuum and effects on Fe and DOC concentrations co-varied generally well, both in Swedish and Canadian waters (linear relationship on log- Figure 3. Iron (Fe), dissolved organic carbon (DOC), absor- transformed data: R = 0.44, P,0.0001, n = 58888 and bance (a ), Fe/DOC and a /DOC ratios in relation to the 420 420 R = 0.58, P,0.0001, n= 247, respectively). The co-variation was percentage of lake surface area in the catchment area (% strongest within and between small headwater streams (linear Water). For the figure, site-specific long-term median data of 5837 different lakes and streams were used. Taking the median of each of the relationship on log-transformed data: R = 0.65, P,0.0001, 11% Water categories and applying a simple exponential decay along n = 1421), and weakest within and between river mouth waters the % Water gradient we received highly significant results (P,0.0001, (linear relationship on log-transformed data: R = 0.27, P,0.0001, 2 2 n = 11; R = 0.78 for Fe/DOC in panel A, R = 0.84 for a /DOC in panel B, 2 2 2 n = 11667). The slopes between the Fe-DOC relationships varied R = 0.95 for Fe in panel C, R = 0.89 for a in panel D and R = 0.88 for substantially along the aquatic continuum, also reflected by DOC in panel E). doi:10.1371/journal.pone.0088104.g003 significant differences in Fe/DOC ratios between lakes and running waters (Wilcoxon-test: P,0.0001). Median Fe/DOC ratios in headwater streams, non-headwater streams and river Fe, DOC and a temporal changes mouths had a value of 0.05 while the median value for lakes was Analyzing time series of Fe, DOC and a from 66 water (34 0.03 and for large lakes as low as 0.01. Thus, lakes contained less river mouths, 21 lakes and 11 streams) since 1996 we found Fe in proportion to DOC compared to running waters. Also significantly increasing trends for DOC in 43 waters, for Fe in 29 absolute Fe concentrations were lower in lakes, and we found waters and for a in 25 waters (Mann-Kendall: P,0.05; Fig. 5). significantly lower Fe concentrations in lakes and large lakes None of the water systems showed significantly decreasing trends compared to headwater streams, non-headwater streams and river in Fe, DOC and a . In 13 waters we observed significantly mouths (Wilcoxon-each-pair-test: P,0.0001). Along with lower Fe increasing trends in Fe/DOC (Mann-Kendall: P,0.05). In 8 of in lakes also a was at low levels. The DOC-specific absorbance, 420 these waters also a significantly increased (Mann-Kendall: i.e. a /DOC, showed similar patterns as Fe/DOC: highest in 420 P,0.05). Significant trends in a /DOC were rare for this time streams and lowest in lakes, in particular large lakes. Relating Fe, period, only occurring in 6 waters (Mann-Kendall: P,0.05). Apart DOC and a to the percentage of lake surface cover in the 420 from Fe, DOC and a trends, we found significantly increasing catchment area we found a highly significant negative relationship trends also for the variables that were most important for a (Fig. 3). The Fe and a decrease with increasing % Water was variations: Si showed significantly increasing trends in 43 waters faster than for DOC, resulting in significantly decreasing a / 420 (Fig. 5), pH in 10 waters, and a /a in 10 waters 420unfiltered 420filtered DOC and Fe/DOC ratios with increasing % Water (Fig. 3). The (Mann-Kendall: P,0.05). At the same time as Fe, DOC and a decreases in Fe and a along the % Water were proportionally increased in Swedish freshwaters, also Sweden-specific long-term similar in size (Fig. 4). running means of precipitation and growing season length PLOS ONE | www.plosone.org 4 February 2014 | Volume 9 | Issue 2 | e88104 Water Color Changes and the Role of Iron Discussion Additive Fe effects on a As shown in earlier studies (e.g. [20–22]), our analyses of more than 58000 water samples from the Swedish and Canadian boreal and hemiboreal region confirmed that a co-varied strongest with DOC concentrations, suggesting that DOC is the overall main driver for water color in boreal waters. Although strong, the DOC-a relationship still exhibited considerable variation across temporal and spatial scales. We attribute the variability in a / DOC ratios to an additive effect of Fe on a , as indicated by a substantial model improvement with inclusion of Fe as indepen- dent variable. Figure 4. Decreasing iron (Fe), dissolved organic carbon (DOC) An additive Fe effect on absorbance, apart from a DOC effect, and absorbance (a ) with increasing percentage of lake has earlier been related to Fe-DOC complexation where highest surface area in the catchment area (% Water). The figure shows the predicted values of Fe, DOC and a from the simple exponential absorbance was reached when Fe was bound to DOC [10,23]. decay functions along the % Water gradient presented in Fig. 3. Fe and The strong co-variation between Fe and DOC in our waters, in a decline equally fast with increasing % Water. The Fe and a 420 420 particular in headwaters, suggests that Fe-DOC complexation is decline is substantially faster than the decline of DOC. % Water can be ubiquitous. Laboratory studies have shown that Fe-DOC com- seen as a proxy for water retention in the landscape (see methods). plexation will reach a plateau when dissolved organic matter is doi:10.1371/journal.pone.0088104.g004 saturated with Fe, with no further Fe-DOC binding and no further increases in carbon specific absorbance occurring when additional significantly increased during 1996 to 2012 (Mann-Kendall: Fe is added [11]. Using waters from a humic lake in the P,0.001; Fig. 5). There was no significant trend in long-term laboratory, [10] found that Fe and carbon specific absorbance running means of air temperatures across Sweden during this time showed a strong positive relationship up to 1 mg L Fe. At higher period (Mann-Kendall: P.0.05). Fe concentrations, increases in carbon specific absorbance became small. [10] used a quadratic function to describe the relationship between Fe and carbon specific absorbance. We used a here a logarithmic function since we suggest that a /DOC reaches a constant value along a Fe concentration gradient when DOC is saturated with Fe. The threshold value of 1 mg L Fe as a breakpoint for a substantial additive effect of Fe (apart from the DOC effect) on absorbance, seems to hold even for boreal waters in general as we found relatively constant a /DOC ratios when Fe exceeded 1 mg L (Fig. 2a and b). Most of the boreal waters analyzed in this study had Fe concentrations less than 1 mg L , suggesting that Fe increases will result in a /DOC increases in many freshwaters of the boreal and hemiboreal region. Provided that variations in a /DOC are influenced by Fe- DOC complexation with highest ratios when Fe is bound to DOC, we expect pH to play a major role for a /DOC variations due to a strong pH effect on Fe complexation [8]. This expectation was supported by a significant pH effect on a /DOC in our PLS models. Based on our results we suggest that water color is primarily driven by DOC but that Fe when it is bound to DOC will cause additional browning of waters. Lakes as Fe sinks and effects on a When Fe and DOC are imported from soils into waters they are usually tightly coupled, in this study indicated by highly significant Fe and DOC relationships in headwaters (R = 0.65, P,0.0001). In headwaters Fe, DOC and a reached maximum values while they all declined with increasing % Water in the catchment (Fig. 3), which we use here as a proxy for water retention in the landscape (see methods). We suggest that decreases in Fe, DOC and a along the aquatic continuum are a result of several Fe and DOC Figure 5. Temporal development of dissolved organic carbon transformation processes during transport from land to sea: (DOC), absorbance (a ), iron (Fe) and reactive silica (Si) in Swedish freshwaters and changes in long-term annual precip- phototransformation [24,25], flocculation and burial in lake itation across Sweden since 1996. The DOC, a , Fe and Si data 420 sediments [15], microbial degradation [26] and dilution by inputs (panels A–D) are based on annual mean values from 66 lakes, streams of waters from other sources that frequently enter downstream and river mouths for which complete monthly time series were systems [12] and that might be poor in DOC and Fe. We found available. Thus, for each year, 66 data points have been used for the that lakes were particularly efficient at removing Fe and a , percentile calculations. For panel E, 10-year running means of data from resulting in decreased Fe/DOC and a /DOC ratios. Since the entire Sweden have been used (see methods). doi:10.1371/journal.pone.0088104.g005 decline in Fe and a in relation to DOC along the % Water PLOS ONE | www.plosone.org 5 February 2014 | Volume 9 | Issue 2 | e88104 Water Color Changes and the Role of Iron gradient was proportionally equal in size we suggest that an a decrease during water transport through the landscape is a result of a Fe loss in lakes. Fe in lakes can be lost by flocculation and sedimentation processes which has been shown to affect a [15]. Fe flocculation and sedimentation processes can result in a selective Fe loss in comparison to DOC as recently reported and discussed for the large Swedish lake Ma¨laren [7]. That sedimen- tation of Fe complexes takes places in lakes finds also evidence in a recent study by [27] who frequently detected Fe-OC complexes in all kinds of sediments around the globe. We suggest that Fe-DOC complexes that have been exported from soils are lost along the aquatic continuum. This suggestion is supported by a study of [28] who found that in Swedish river mouths waters up to 99% of dissolved Fe occurred as ferrihydrite which is rarely bound to organic matter [29]. Less frequent occurrence of Fe-DOC complexes in river mouths waters might explain why our Fe- DOC relationships became weaker along the aquatic continuum. Decreases in a /DOC along the aquatic continuum have been observed earlier [13]. It was suggested that the selective a loss in comparison to DOC is a result of DOC transformation processes during transport from land to sea. Here we relate the Figure 6. Fate of iron (Fe), dissolved organic carbon (DOC) and a /DOC decline along the aquatic continuum for the first time absorbance (a ) along the aquatic continuum under normal to Fe losses in lakes. In [7] it was shown that in the large lake wet conditions (panel A) and in a wetter climate (panel B). Ma¨laren Fe decreased 6.3 times faster than imported DOC. We When water travels from headwaters to river mouths and passes lakes found here that Fe decreased on average only 2.3 times faster than Fe, DOC and a all decline (compare Fig. 3 and Fig. 4). It is suggested DOC along a water retention time gradient (Fig. 3). This that a concomitant Fe, DOC and a decline in surface waters of lakes is a result of Fe-OC complexes that can flocculate and reach bottom discrepancy may result from the fact that water retention of a waters and sediments (panel A). In a wetter climate with a consequent single lake ecosystem is not comparable to water retention in the faster flushing of waters through lakes the settling of Fe-OC complexes landscape [12], in particular not since we use here % Water as a towards bottom waters and sediments becomes less efficient and Fe- proxy for water retention in the landscape. In addition, most of OC complexes reach downstream waters, where they cause strong our study lakes were small unproductive shallow lakes with declines in a (panel B). The conceptual figure assumes that Fe-OC frequent events of sediment resuspension [30] where the burial complexes mainly originate from soils. doi:10.1371/journal.pone.0088104.g006 capacity of Fe might be limited. quality changes, in particular a change towards less colored DOC. Increasing Fe contribution to a on a temporal scale DOC becomes less colored towards deeper soil layers where DOC Like [6] we found significant increases in DOC, Fe and a . [6] is more extensively processed [31]. These deeper soil layers are proposed a number of explanations why Fe concentrations and reached by groundwater. Since we found significant increases in Si thereby a in Swedish waters might increase, one being climate which is a mineralization product and an indicator of groundwater change induced increases in anoxic conditions in organic soils. inputs [32] we attribute increases in less colored DOC to an Changes of processes along the aquatic continuum were not a increased export of DOC from deeper soil layers, probably from focus of their study and consequently not taken into consideration. mineral soil layers that are rich in both Si and Fe. The increase in We propose here that changes in Fe and consequently in a DOC exports from deeper soil layers might be caused by the might indeed be related to increasing Fe soil exports but that increase in long-term precipitation (Fig. 5). The significance of Si changes in the Fe processing along the aquatic continuum also on a was not only detectable on a temporal scale but also on a need attention. We found that Fe and a losses along the aquatic spatial scale: using PLS, Si was one of the most important variables continuum decrease with decreasing water retention in the explaining a . Thus, understanding a changes requires an landscape (Fig. 4). Especially lakes played a central role for Fe 420 420 understanding of DOC sources that determine the proportions and a losses along the aquatic continuum. We suggest that faster between colored and uncolored DOC. water flushing through lakes due to increased precipitation as In case less colored DOC presently increases as suggested observed across Sweden (Fig. 5) will result in higher Fe and a in downstream water systems compared to normal wet years (Fig. 6). above, we attribute a /DOC increases to Fe concentration increases. As discussed above climate change induced decreases in According to our study, lakes are efficient in removing Fe from the water column. Thus, lakes function not only as efficient DOC sinks the efficiency of Fe transformation processes along the aquatic continuum might be one explanation for Fe concentration [30] but probably also as efficient Fe sinks which has effects on a , in particular on a /DOC. If Fe is lost in lakes in form of Fe- increases but increased Fe soil exports are also highly likely. We 420 420 DOC complexes then faster water flushing through the landscape argue, like we did for DOC quality, that due to a long-term would imply less time for sedimentation of Fe-DOC complexes in precipitation increase and a longer growing season length deeper lakes with consequent more Fe-DOC complexes reaching the sea soil layers that are usually rich in Fe and Si are drained. This (Fig. 6). argumentation corresponds to the results of [33] who reported on From our observed widespread increasing DOC trends across increased Fe exports from soils with increasing wetness. Since we Swedish freshwaters we expected more significant a increases in also found a significant increase in particulate matter, i.e. in the waters. According to our results a increases were mainly a /a , we suggest that water flushing through soils 420 420unfiltered 420filtered restricted to waters in which also Fe increased. Significant DOC has increased. We further suggest that podzolization plays an trends that obviously did not affect a might be a result of DOC important role for the fate of Fe. Podzolization is a process where PLOS ONE | www.plosone.org 6 February 2014 | Volume 9 | Issue 2 | e88104 Water Color Changes and the Role of Iron Fe is complexed with dissolved organic matter and transported proportions have been quantified we will be able to fully downward in the soil profile [34]. If these deeper soil profiles are understand how water color will respond to further environmental flushed Fe-DOC complexes will be exported from soils into surface changes. waters. Podzolization is especially strong beneath conifers [34], which might explain why the percentage of coniferous forest in the Acknowledgments catchment area came out as the most important catchment Many thanks go to the Swedish Environmental Protection Agency and the variable in our a model. staff of the laboratory of the Dept. of Aquatic Sciences and Assessment for Finally, Fe increases might also be a result of mineralization rate financing, sampling and analyzing thousands of water, and to the Swedish increases as a response to the longer growing seasons. Like runoff Meteorological and Hydrological Institute for making meteorological data changes, mineralization rate changes would also result in freely available. We are also thankful to Jakob Nisell and Roger Mu¨ller for concomitant Fe and Si changes, as we observed in this study. providing GIS data, to Karsten Kalbitz for fruitful discussions and to John We conclude that DOC and Fe soil exports as well as DOC and Pastor for constructive comments. Fe transformation processes during transport from land to sea need to be considered to understand why many freshwaters are Author Contributions browning. Brownish waters influence a number of ecosystem Conceived and designed the experiments: GW. Performed the experi- services including biodiversity [35], fish production [36], and ments: GW. Analyzed the data: GW YP LT. Contributed reagents/ drinking water quality [37]. Future studies on proportions between materials/analysis tools: GW YP LT. Wrote the paper: GW YP LT. colored and uncolored DOC and between dissolved monomeric inorganic and colloidal Fe are strongly needed. First when these References 1. 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