A diverse influence of dissolved natural organic matter on light irradiance measurements in lakes

The total scalar irradiance of solar radiation, along with the subsequent attenuation of specific wavelengths, plays a significant role in various crucial processes within lake ecosystems. The extent of light irradiance influences primary production, thermal budgets, stratification, thermocline depths, and circulation patterns (Eloranta 1978; Read & Rose 2013; Thrane et al. 2014; Rohrlack et al. 2020). When sunlight enters the lake, it encompasses a range of wavelengths, from highly energetic ultraviolet (UV) radiation to less energetic infrared light. The attenuation of photosynthetically active radiation (PAR; 400–700 nm) affects both the transparency of lake water (Secchi depth, Z_SD) and the depths of the euphotic zone, which extend down to the compensation depth (Z_CD). Z_SD is commonly used to measure water transparency or clarity in situ and is typically interpreted as the depth at which 10% of PAR-light is still present (Preisendorfer 1986). Z_SD is interpreted by the human eye using a submersed Secchi disc. Z_CD is measured using a digital quantum sensor and represents the depth at where photosynthetic activity is in balance with respiration.

The attenuation of light is caused by both scattering and absorbance, ⁠. Scattering of PAR primarily occurs due to water molecules and particulate suspended matter. Particles able to scatter light in the water phase would be of both organic (i.e., algae; organic seston) and inorganic (i.e., colloids and clay; inorganic seston) origin (Kirk 1980; Bohren & Huffman 1998). On the other hand, the absorbance of PAR is largely influenced by the absorption of water molecules (Kirk 1980, 1985), autochthonous dissolved organic matter (detritus and algae) (Kirk 2011), and allochthonous-derived dissolved organic matter (DNOM) (Kirk 1976). Since both Z_SD and Z_CD are influenced by light scattering and the absorption of light by pigment systems (Brezonic 1978), Z_SD is often used in various conversions to estimate Z_CD in lakes, which typically varies among lakes from less than 1 to greater than 5 times Z_SD (Smetacek & Passow 1990). Z_SD and Z_CD are, however, influenced differently by substances that attenuate PAR (Koenigs & Edmundson 1991; Luhtala & Tolvanen 2013). Z_SD is primarily affected by light scattering (Kirk 1985). An increase in particles and turbidity suggests an underestimation of Z_CD when converting from Z_SD. On the other hand, the vertical attenuation coefficients for irradiance are strongly influenced by the light absorption of DNOM, specifically humic matter (Kirk 1976; Branco & Kremer 2005; Kostoglidis et al. 2005; Urtizberea et al. 2013). From this, an increased concentration of DNOM might suggest an overestimation of Z_CD when converting from Z_SD.

Regarding the light absorbing and light scattering parameters in Southeastern Norwegian lakes, allochthonous produced (catchment origin) DNOM is the one parameter that has changed a lot over the past few decades (Haaland et al. 2010; Riise et al. 2018). This is mainly due to climate change and acid rain, and concurrent variations in DNOM concentrations have been observed within large boreal and hemiboreal areas (Monteith et al. 2007, 2023; Riise et al. 2018; De Wit et al. 2023). Allochthonous DNOM exhibits strong light absorption capabilities in the UV range and shorter wavelengths of PAR (Steinberg 2003). This absorption is attributed to the molecular orbitals in DNOMs (dissolved organic matter) and their conjugated pigment systems (Shapiro 1957; Steinberg 2003), and also in complexation with ferrous iron in surface waters (Gjessing 1964; Poulin et al. 2014; Riise et al. 2023). Climate change is at present and in the future expected to be the most prominent driver for DNOM concentrations in European and North American lakes, including shifts in rainfall, sea-salt exposure and runoff patterns (Haaland et al. 2010; Weyhenmeyer et al. 2014; De Wit et al. 2016; Monteith et al. 2023), redox effects (Clark et al. 2006; Kritzberg & Ekström 2012; Monteith et al. 2023), temperature fluctuations (Freeman et al. 2001; Hytteborn et al. 2015; Haaland et al. 2018; Monteith et al. 2023), and due to changes in catchment properties such as vegetation cover and greening (Larsen et al. 2010; Finstad et al. 2016; Haaland et al. 2018). The decline in acid rain deposition in European and North American catchment soils has previously been regarded as a strong driver behind changes in DNOM concentrations over the past few decades (Forsberg & Petersen 1990; Monteith et al. 2023), for instance affecting changes in soil solution ionic strength (Evans et al. 2006; Monteith et al. 2007, 2023; Haaland et al. 2010).

Accurate assessment of light irradiance is important for understanding processes within lake ecosystems. We know that Z_SD is often used in various conversions for estimates of Z_CD in lakes, that DNOM has a diverse influence on light irradiance measurements and that DNOM concentrations have increased and is projected to increase further in concentration due to climate change. However, to which extent changes in DNOM concentration have affected the measurements of Z_CD and Z_SD differently remains unknown. From this, a sampling survey was performed in a lake district in Southeastern Norway, measuring light irradiance, well-known parameters affecting light irradiance (including DNOM), and also involving the use of integrated water-core samples.

Water transparency, represented by the Secchi depth (Z_SD), was determined using a 13 × 18 cm Secchi disk and a water scope following the method described by Preisendorfer (1986). Z_SD was calculated as the average of one descending and one ascending measurement. Measurements of the compensation depth (Z_CD) were done by measuring the quantum irradiance (Q) within the PAR range until Q dropped below 0.2 μmol m⁻² s⁻¹. Z_CD was determined as the depth at which 1% of downward PAR irradiance remained. A combination of a quantum sensor (LI-COR LI-192) and a light meter (LI-COR LI-250) was used for this purpose. To eliminate any potential shading effects, the quantum sensor was submerged 2 m away from the boat. If deviations between measurements exceeded 5%, the measurements were repeated from the beginning. Both measurements were carried out between 09:00 AM and 15:00 PM to minimize discrepancies caused by variations in sun altitude (Simon & Shanmugam 2013).

Spectrometric absorption measurements were conducted using a Perkin Elmer Lambda double-beam instrument equipped with a 50 mm quartz cuvette. The scans were conducted over 400–700 nm at a resolution of 1 nm. The absorption of DNOM was quantified at 400 nm (DNOM (m⁻¹)). To establish the absorption background attributed to water molecules, reverse osmosis ultrapure water was utilized. The concentration of dissolved organic carbon (DOC) was also used as a proxy measurement for the concentrations of DNOM and was determined using a Shimadzu TOC-V total carbon analyzer. The dissolved carbon fraction (DOC), obtained after filtration with a 0.45 μm filter, accounted for more than 95% of the total carbon fraction (TOC). True color unit (TCU) estimates were obtained using a platinum cobalt chloride color standard. Turbidity (measured in Formazin Nephelometric Units, FNU) was assessed using a HACH 2100AN IS turbidimeter. Seston, representing suspended particles, was measured by collecting filtrates on dried (at 105 °C) Whatman GF/C filters with a median retention particle size of 1.2 μm. The filters were subsequently heated at 450 °C for 2 h to separate seston into inorganic and organic fractions. Other chemical analyses were conducted following ISO standards (as indicated in Table 1). Statistical analysis of the data was performed using R, Minitab Statistical Software, and Matlab.

Water quality statistics for the 23 lakes sampled in Southeastern Norway are given in Table 1. Turbidity measurements, indicating scattered light, ranged from 0.3 to 28 FNU. The concentrations of total seston varied from 0.5 to over 15 mg L⁻¹, reflecting a range from non-turbid lakes to moderately turbid lakes. Hazen color units (TCU) revealed a diversity in water color, with values below 3 mg Pt L⁻¹ for clear water lakes and exceeding 100 mg Pt L⁻¹ for lakes with more pronounced coloration. Notably, there was a strong linear relationship observed between allochthonous DNOM and DOC (r² = 0.94), as well as between DOC and TCU (r² = 0.93). The measurements of compensation depth (Z_CD) and Secchi depth (Z_SD) exhibited a high correlation among the lakes (r² = 0.94), as expected. However, there were variations between lakes regarding the dominant factor influencing the attenuation coefficient for photosynthetically active radiation (k_d PAR). Approximately 70% of the lakes were primarily influenced by DNOM, while suspended matter played a dominant role in the remaining lakes.

The first branch, cluster_a, comprises parameters such as Secchi depth (Z_SD) and measures related to suspended matter, including inorganic seston and turbidity. Cluster_b encompasses chemical and physical parameters like conductivity, pH, and alkalinity. Notably, shifts in the concentrations of inorganic seston are observed when transitioning from lakes situated above the marine limit (ML) to those below it. Lakes located below the ML in Southeastern Norway tend to exhibit higher levels of dissolved inorganic ions (leading to increased conductivity) and often have greater inorganic buffer capacity (alkalinity) (Haaland et al. 2010). The concentration of inorganic suspended matter, particularly clay particles, affects Z_SD and is expected to have a more pronounced impact when moving below the ML (Kirk 1985). The second branch, cluster_c, includes nutrients, algae, and the organic fraction of seston. Within this cluster, there is a strong linear correlation between the organic fraction of seston and chlorophyll (Chl_a) concentrations (r² = 0.92), as well as total algal count (r² = 0.87). This suggests a relationship between the organic matter produced within the system (e.g., algae, cyanobacteria) and the measured particulate organic matter. Additionally, cluster_d within the same branch represents the influence of organic matter originating from catchment soils on the compensation depth (Z_CD). It indicates that Z_CD is substantially affected by organic matter derived from the surrounding catchment (allochthonous-derived DNOM). The robust linear relationship observed between allochthonous DNOM and DOC, as well as between DOC and Hazen color units (TCU), further supports the significant influence of allochthonous DNOM in this study.

One uncertainty in a transfer of measurements from Z_SD to Z_CD is that Z_SD is interpreted by human eyes, whereas Z_CD is measured using digital quantum sensors. The human trichromatic color vision has a higher spectral sensitivity in the mid-PAR-spectra (Soffer & Lynch 1999; Stockman & Sharpe 2000). Compared to the human color vision, a quantum sensor instrument strives to have a relatively flat sensitivity curve throughout the whole PAR-spectrum. Hence, the human eyes might, in comparison to a quantum sensor, be somewhat less capable of detecting variations in light absorbance within the blue end of the PAR-spectra in where DNOM absorb light. To some extent, this might explain why the measurement of Z_SD is considerably better described by inorganic seston and turbidity than by DNOM (r² = 0.74 vs 0.25), in comparison to the respective linear correlations for Z_CD (r² = 0.32 vs 0.72) (Table 2). From this, Z_CD and Z_SD are influenced to a diverse degree by different processes and sources (Figures 3 and 4), such as the leaching of DNOM from catchment soils, and catchment erosion and resuspension in lakes (particles, turbidity).

While some lakes in Norway have undergone less dramatic changes in DNOM concentrations, there has been a notable and statistically significant positive trend within the lake district and throughout a larger portion of Southern Norway (Monteith et al. 2007, 2023; Grennfelt et al. 2020). There has however not been a similar trend for turbidity (Haaland et al. 2010; Riise et al. 2018). Extensive ongoing monitoring networks in Norway on climate, atmospheric composition, and atmospheric deposition (Aas et al. 2022) have been used to identify parameters explaining the DNOM development in the lake district, of which acid rain and climate parameters such as air temperature and precipitation amount and intensity are important drivers (Haaland et al. 2006, 2010; De Wit et al. 2016; Monteith et al. 2023). Currently, sulfate emissions in Europe are low and comparable to levels recorded in the late 1890s or early 1900s (Grennfelt et al. 2020). Since the mid-1980s, acid deposition over the lake district has subsequently experienced a significant decrease (Riise et al. 2023). Furthermore, both air temperature and precipitation amount, and also numbers of episodes with high precipitation intensity, have increased over the previous decades in the lake district (Kuya et al. 2023). By employing even a moderately conservative scenario from the IPCC (Intergovernmental Panel on Climate Change; RCP4.5; stable/slightly increasing emissions until 2040; then reduced emissions), climate projections for the lake district still indicate higher temperatures and more rainfall in the lake district up until the year 2100 (Hanssen-Bauer et al. 2017; uncertainties in the climate projections related to future anthropogenic emissions, natural climate variations and variations between different climate models have here been taken into account). By incorporating the previous DNOM concentrations during the acid rain peak period in the mid-1980s and 1990s, and also the anticipated higher future DNOM concentrations due to climate change in the lake district, it is from our findings possible to give an estimate of both previous and expected future Z_CD:Z_SD ratios for the lakes within the lake district. During the peak acid rain period, DNOM concentrations were notably lower compared to present levels (Haaland et al. 2010). Compared to the present, DNOM concentrations were often just half or even just a quarter of the current concentration, and from that the median Z_CD:Z_SD ratios are estimated to have been approximately 30 and 60% higher than today, respectively (Figure 5). The Z_CD:Z_SD ratios within lakes are expected to change somewhat from day to day, and throughout the year as a result of natural weather fluctuations, seasonal variations, and variations in inputs of parameters influencing light absorbance and light scattering. However, apart from these expected short-term fluctuations, our findings hence indicate that the Z_CD:Z_SD ratios also have experienced a strong long-term decline in the lake district over the past few decades. Moreover, a further climate-driven increase in DNOM concentrations, that is expected to occur due to increased temperature and increased precipitation inside the lake district (Haaland et al. 2010; De Wit et al. 2016; Hanssen-Bauer et al. 2017), median Z_CD:Z_SD ratios in the lake district are estimated to further decline with approximately 10 and 25% compared to current levels if there were to be a doubling or quadrupling in the DNOM concentrations, respectively (Figure 5).

Two commonly employed light irradiance measurements in lakes are the Secchi depth (Z_SD) and the compensation depth (Z_CD). The Z_CD:Z_SD ratios in a lake district located in Southeastern Norway are estimated to have experienced a significant long-term decrease. The decrease can be attributed to a diverse influence of DNOM on these light irradiance measurements, in combination with long-term increasing concentrations of DNOM. As climate change continues to impact DNOM concentrations in the region, this trend is expected to persist. The Z_CD:Z_SD ratio in these lakes might hence be less stable than we have expected, and when estimating Z_CD using Z_SD measurements, one should be aware of this possible long-term change. Although our current set-up with water-core samples allows us to identify this issue, it is required to conduct additional research in both in situ and laboratory settings to address this topic in more detail.

Our deepest gratitude to late Assoc Prof Inggard Arne Blakar (Norwegian University of Life Sciences, NMBU) for valuable inputs on the topic and the in situ water-core sampling procedure.

All relevant data are included in the paper or its Supplementary Information.

The authors declare there is no conflict.