Light control of the productivity of aquatic ecosystems
A. Cózar Área de Ecología, Facultad de Ciencias del Mar, University of Cádiz, 11510 Puerto Real, Cádiz, Spain
Abstract
The role of nutrients in the control of productivity of aquatic ecosystems has been deeply studied in the past century. The role of light, however, remains less well understood despite the fact that light often becomes the main controlling factor of the aquatic ecosystems. The theoretical bias between nutrient and light control may have arisen due to the complexity in modelling the light environment of aquatic ecosystems (e.g., spatial-temporal variability of algal exposure, competing presence of optically active abiotic components, negative feedback of algal auto-shading). In the present work, we develop an ecosystem-specific model to determine the carrying capacity of algae from the light-biomass conversion efficiency. The feasibility of this method was demonstrated on two diverse ecosystems, the phytoplankton community of the Lake Victoria (East Africa) and the microphytobenthos community of the lacustrine system of the Ibera wetlands (South America). The relationship between maximum supportable algal biomass and light availability, mixing depth and background light attenuation was also determined. Such information has important implications on the investigation, modelling and management of the aquatic ecosystems Keywords: aquatic productivity, photosynthesis, light control, euphotic depth, Lake Victoria, optical modelling.
The role of nutrients in the control of algal biomass has been thoroughly researched in the past century. The role of light, however, remains less well understood despite the fact that light is often the controlling factor of algal biomass. In most benthic ecosystems or many eutrophic pelagic environments, the nutrient requirements of the algal populations are fully satisfied. In such situations, algal populations will grow until a steady state where light conditions are limiting. Therefore, a characteristic carrying capacity of algal biomass will correspond to a specific light availability just as a maximum supportable biomass may be calculated from a nutrient availability [1]. The theoretical bias towards light control may have arisen due to the complexity in modelling the light environment in aquatic ecosystems. The main challenges are the spatial-temporal variability of light within the water column, the competition for light with abiotic components and the negative feedback of algal auto-shading [2, 3]. Talling [4] and Reynolds [5] made the first attempts to calculate phytoplankton carrying capacity by using euphotic depth, the depth at which the downwelling solar irradiance falls to 1% of that just below the surface. In this way, however, the carrying capacity is independent of light supply. Recently, Huisman [6] developed a mechanistic approach based on the concept of critical light intensity, that is, the steady state light intensity that leaves the mixed layer [2]. However, this critical light intensity is invariably zero whenever the euphotic depth is smaller than the mixing depth, a common occurrence in light-limited ecosystems. We believe there is a fundamental need to model algal biomass by considering the spatial-temporal integration of the solar irradiance within a volume (or surface) in which the primary producers are distributed [7]. Existing theory focuses on mechanistic models to determine the light-controlled carrying capacity based upon the equilibrium between net photosynthetic gains and the net losses of the population [6, 8]. However, this dynamic equilibrium does not provide a workable basis on which to analyze real ecosystems. While in the laboratory, the photosynthetic response of algal populations to irradiance can be measured through photosynthesis-irradiance (P-I) curves. However, the integration of this function over space and time neglects the real situation of planktonic algae, which cannot maintain a constant position in space and are exposed to fluctuating levels of irradiance related to the exponential decay of the incident irradiance with depth [9]. Complex loss processes such as marine or lake “snow” formation or feces production by grazing also need to be considered [8]. Theoretical models derived from the production-losses balance agree qualitatively with real data and contribute significantly to the understanding of algal dynamics, but produce limited quantitative results [3]. Secondly, they require advanced computation techniques that hamper the expansion of these advances among the researcher and manager communities We develop a complementary ecosystem-specific approach where light-controlled carrying capacity is directly derived from an efficiency coefficient of light-biomass conversion.
Using different methodological approaches, Ryther [10] and Talling [4] reached the conclusion that, in nutrient replete conditions, aerial algal production is linearly related to the aerial biomass multiplied by a term linked to light availability (light extinction coefficient). More recently, this algorithm was used to estimate oceanic production from remote sensing data [11]. The total amount of photosynthetic available radiation (PAR) available in a water column (Q’
t) may be approximated by: [7]:
KcIQ o
t ⋅='
where Io is the incident PAR on the water surface, K is the vertical attenuation coefficient for PAR and c is the speed of the light in the medium. This expression considers that no light leaves the mixed layer. Using the Lambert-Beer’s law to describe the vertical light gradient, the quantity of available light that exceeds the mixing depth (d) would be:
dKod e
KcIQ ⋅−⋅⋅
=
Thus, the total amount of PAR available to the phytoplankton cells circulating within the mixed layer (Qt) will be:
( )dKot e
KcIQ ⋅−−⋅⋅
= 1 (1)
and the total amount of light available to a phytobenthic community (Qtb) at a specific bottom depth (b) will be:
bKotb e
KcIQ ⋅−⋅⋅
= (2)
The aerial steady-state biomass of any phytoplankton community (W*) will vary with Qt depending on the light-biomass conversion efficiency (ψ) of the community as:
min* QQW t ⋅−⋅= ψψ (3)
where Qmin is the minimum light requirement to permit algal biomass. The conversion efficiency term (ψ, g-chl einstein-1) considers the ratio of energy
stored in the ecosystem as steady-state biomass to the solar energy available. The effects of the incident light intensity, light attenuation and mixing depth on the steady-state biomass of the phytoplankton community can be described as:
( ) min* 1 Qe
KcIW dKo ⋅−−⋅
⋅⋅
= ⋅− ψψ (4)
From this equation, it would appear that W* will increase unlimitedly with PAR availability (Qt). However, increases in phytoplankton biomass will increase attenuation (K), thereby reducing Qt. This negative feedback prevents unlimited phytoplankton growth. For the phytobenthos, the unlimited increase of biomass with Qtb is inappropriate due to self-shading effects. The light-controlled carrying capacity for phytobenthos (W*
b) reaches a plateau when the bottom is covered being described by a logarithmic function as:
( ) ( ) ( )minmin* lnlnlnln Qe
KcIQQW bKo
tbb ⋅−
⋅
⋅⋅=⋅−⋅= ⋅− αααα (5)
where α is the logarithmic slope of the function. The value of light-biomass conversion efficiency for phytobenthos (ψb) must be estimated at low superficial densities, that is, in the absence of intra-specific competition. At these conditions, the slope of the logarithmic curve is maximal and equals to ψb. The calculated carrying capacity for phytoplankton is useful for ecosystem analysis once measurements of K and biomass have been obtained. Using equation 4, it is possible to determine how far a phytoplankton community is from the condition of light-limitation. However, to model how variations in the concentrations of the optically active components will effect the algal carrying capacity, it is necessary to separate the total attenuation due to phytoplankton and non phytoplankton components as:
bgKwkK +⋅= (6) where k the specific light attenuation coefficient of the phytoplankton, w is the volumetric biomass of phytoplankton and Kbg is the total background turbidity. Substituting Eq. 6 into Eq. 4 and rearranging:
( )min**
* *
QeK
dWkc
I
Kd
Wkc
IW dKWk
bg
o
bg
o bg ⋅−⋅
+⋅⋅
⋅−
+⋅⋅
⋅= ⋅+⋅− ψψψ (7)
where biomass carrying capacity is a function of incident PAR, mixing depth, aerial phytoplankton biomass and the concentration of the non-phytoplankton water column components. This relation must be resolved iteratively due to the presence of W* in the exponent of Euler’s number.
Figure 1: Relationship between the light availability and the aerial concentration of algal biomass in a set of 277 sampling sites in Lake Victoria inshore water (a) and a set of 54 samples in the bottom of lakes of Esteros del Iberá wetland (b). The lines were fitted by least-square regression to estimate of the light-biomass conversion efficiency (ψ) and the minimum light requirement to sustain the algal community (Qmin). Data points included in the regressions of this upper limit are marked with white center. All points non-included in the regressions were further than 2.5·10-13 units from the phytoplanktonic upper limit and further than
3.5·10-13 units in the phytobenthic upper limit. Lake Victoria phytoplankton: ψ = 0.29·1012 g-chl einstein-1, Qmin = 6.42·10-14 einstein m-2 and R2 = 0.9224 (P<0.001). Esteros del Iberá microphytobenthos: ψb = 1.19·1012 g-chl einstein-1, Qmin = 0.02·10-
14 einstein m-2 and R2 = 0.9537 (P<0.001). Displacement patterns of algal populations reaching the light-controlled carrying capacity are shown with grey dashed lines. In Lake Victoria, simulated phytoplankton population increases the biomass from 12 to 40 mg-chl m-3 (incident light, Io = 54 einstein m-2 d-1; background turbidity, Kbg = 0.3 m-1; specific light attenuation coefficient of the phytoplankton, k = 0.019 m2 mg-chl-1; mixing depth, d = 20 m). In Esteros del Iberá, simulated microphytobenthos population increases the biomass from 0.3 to 4.2 mg-chl m-2 (incident light, Io = 35 einstein m-2 d-1; overall vertical attenuation, K = 1.0 m-1; bottom depth, b = 1.5 m).
3 Sampling
Three surveys (2002-2004) were performed along the Ugandan and Kenyan coast (within 15 km from the coast) for a total of 277 sampling sites covering all major inshore areas types. In the lacustrine system of Esteros del Iberá wetland, 6 sites (mean depth, 2.0 m) were sampled regularly in nine dates during a whole seasonal cycle (1999-2000). Incident solar photosynthetic available radiation (PAR) was measured 3 m above the water surface. Vertical profiles of temperature (Hydrolab probe) and solar radiation (PAR waveband, PUV 514-Biospeherical Instrument) and Secchi depth were measured at each sampling site. Water samples were taken at 0.5 m and 2.0m (only in Esteros del Iberá). Chlorophyll-a (chl), total phosphorous, total nitrogen, dissolved organic matter and soluble reactive silicon concentrations were measured. In Esteros del Iberá, sediment samples (30 cm2 x 1 cm) were also taken from the first centimetre of the bottom of the lakes. Chlorophyll-a concentrations and percentage in weight of organic matter in the sediment were measured. Mixing depth was defined graphically by the intersection of trend lines fitted to the thermal profiles, one through the upper part of the epilimnion and the second through the metalimnion [12] Vertical light attenuation coefficient was determined using the irradiance profiles in Lake Victoria and indirectly-estimated from Secchi disk and chlorophyll-a concentration measurements [9] in Esteros del Iberá. Chlorophyll-a concentrations were measured using a calibrated portable fluorimeter (Turner) in Lake Victoria and using standard spectrophotometric methods [13] in Esteros del Iberá. In the sediment samples, chlorophyll analysis included centrifugation after the pigment extraction in acetone. Nutrient analysis (phosphorus, nitrogen and silicon) were performed through spectrophotometry following APHA standard methods (1992). Dissolved organic matter was estimated in the filtered samples (GV Millipore 22 µm filter) through the 272 nm-absorbance after gravimetric calibration [14].
Figure 2: Effect of mixing depth (d) and background turbidity (Kbg) on the light-controlled carrying capacity of the phytoplankton community of the Lake Victoria inshore waters (a). Effect of depth (b) and vertical light attenuation coefficient (K) on the light-controlled carrying capacity of the microphytobenthos community of the lakes of Esteros del Iberá wetland (b). The solar flux densities in the tropical Lake Victoria vary slightly throughout the year with an averaged daily irradiance of 650 µEinstein s-1 m-2, while the monthly-averaged daily irradiance in Esteros del Iberá ranges from 200 to 800 µEinstein s-1 m-2. In Lake Victoria, K was empirically break down into the sum of Kbg and the attenuation due to the
phytoplankton (k·w) through a multiple regression (R2 = 0.73, P < 0.0001). Kbg was decomposed on a term depending on the dissolved organic matter concentration (DOM) and constant term due to other abiotic components. Wetlands fringing much of the Lake Victoria shoreline release considerable DOM, intervening significantly on K. The attenuation term due to the phytoplankton depend on the specific light attenuation coefficient of the phytoplankton (k) and the volumetric concentration of chlorophyll (w). The estimated value of k (0.019 m2 mg-chl-1) adequately matches within the k range observed in nature [7].
4 Results
The estimation of ψ was made using a large set of field measurements of algal biomass concentrations (W) and vertical underwater light profiles from each study area. In a scatter plot of W versus the underwater light availability (Q, sensu Kirk [7]), the light-limited algal carrying capacity corresponds to the upper limit of the dataset (Figure 1). This upper limit describes the maximum algal concentration possible at each Q. Algal concentrations that digress from this limit have either not reached their maximum light-limited steady state or are limited by other factors such as nutrients or grazing. The method was tested on the data set from the phytoplankton community of the Lake Victoria inshore waters (East Africa) and the microphytobenthos community of the lacustrine system of Esteros del Iberá (South America). For the tropical phytoplankton community, ψ was determined to be 0.29·1012 g-chl einstein-1, while for the subtropical microphytobenthos, ψb was 1.19·1012 g-chl einstein-1. Both ψ and Qmin demonstrated the higher efficiency and lower light requirement of benthic algae compared to pelagic algae [15].
5 Conclusion
While ψ is an ecosystem-specific parameter, it is easily determined from data that is commonly obtained in aquatic ecosystem investigations and can serve as the cornerstone in resolving the complex role of light in the control of algal biomass concentrations. With knowledge of the incident light flux, it is possible to determine the maximum supportable limit of biomass and the impact that changes in mixing depth and background light attenuation (due to non-phytoplankton components) may have on the steady-state concentrations of algae (Figure 2). The biomass supported by any ecosystem has to be within the envelopes simultaneously enclosed by both energy (light-controlled) and resource (nutrient-controlled) capacities [1]. Such information has important implications on the investigation, modelling and management of aquatic ecosystems.
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