Sustained stoichiometric imbalance and its ecological consequences in a large oligotrophic lake

Abstract

Considerable attention is given to absolute nutrient levels in lakes, rivers, and oceans, but less is paid to their relative concentrations, their nitrogen:phosphorus (N:P) stoichiometry, and the consequences of imbalanced stoichiometry. Here, we report 38 y of nutrient dynamics in Flathead Lake, a large oligotrophic lake in Montana, and its inflows. While nutrient levels were low, the lake had sustained high total N: total P ratios (TN:TP: 60 to 90:1 molar) throughout the observation period. N and P loading to the lake as well as loading N:P ratios varied considerably among years but showed no systematic long-term trend. Surprisingly, TN:TP ratios in river inflows were consistently lower than in the lake, suggesting that forms of P in riverine loading are removed preferentially to N. In-lake processes, such as differential sedimentation of P relative to N or accumulation of fixed N in excess of denitrification, likely also operate to maintain the lake's high TN:TP ratios. Regardless of causes, the lake's stoichiometric imbalance is manifested in P limitation of phytoplankton growth during early and midsummer, resulting in high C:P and N:P ratios in suspended particulate matter that propagate P limitation to zooplankton. Finally, the lake's imbalanced N:P stoichiometry appears to raise the potential for aerobic methane production via metabolism of phosphonate compounds by P-limited microbes. These data highlight the importance of not only absolute N and P levels in aquatic ecosystems, but also their stoichiometric balance, and they call attention to potential management implications of high N:P ratios.

Keywords: ecosystem; limnology; nitrogen; phosphorus; stoichiometry.

Fig. 1.

(A–C) Biweekly or monthly concentrations of (A) TN, (B) TP, and (C) the TN:TP stoichiometric ratio (molar) in integrated samples of the upper 30 m of Flathead Lake from 1983 to 2019 (note natural log scale). GAMs were used to assess trends in the time series data, with solid black lines indicating the fitted model and gray shading indicating model error.

Fig. 2.

(A–C) Annual riverine loading for (A) TN, (B) TP, and (C) TN:TP loading ratios (molar) since 1983. Inputs from the Flathead River dominate both the riverine hydrologic and nutrient loading to the lake. The dynamics of lake TN:TP ratio and associated GAM are shown in the upper dotted line to ease comparison.

Fig. 3.

P primarily limited Flathead Lake phytoplankton growth during summer, as estimated from factorial enrichment of N and P in six 5-d experiments testing response of chlorophyll-a concentration. (A) Raw data for three experiments in 2018 (Expt 1: 18 June; Expt 2: 2 July; Expt 3: 9 July) and 2019 (Expt 4: 24 June; Expt 5: 1 July; Expt 6: 8 July) (note log transformation of y axis). Lines connect means of the +P treatments. (B) Predicted values based on a mixed-effects linear model, with intercept as a random effect and N and P effects as fixed for all data combined. Model structure is $Y_{i,j}={\beta }_{0,j}+{\beta }_1{N}_{i,j}+{\beta }_2{P}_{i,j }+{\beta }_3{N}_{i,j}{P}_{i,j }+{ϵ}_{i,j}$ where $Y_{i,j}$ is ln (chlorophyll-a concentration) in replicate i in experiment j. $N_{i,j}$ and $P_{i,j}$ are dummy variables for N and P addition, and ${ϵ}_{i,j}$ is independent and identically distributed error. Parameter estimates (±SE) are P effect, ${\beta }_2$= 0.49 ± 0.067; N effect, ${\beta }_1$ = 0.02 ± 0.067; and NP interaction, ${\beta }_3$ = 0.39 ± 0.096. Overall, P addition increased chlorophyll-a when added alone or with N, but N addition only had an effect when added with P (B).

Fig. 4.

(A–C) Average (A) seston C concentrations and (B) C:P and (C) N:P ratios (molar) at 5-, 50-, and 90-m depth during summer (June to mid-September) 2016 to 2019. Error bars indicate one SEM of five sampling dates within each year. Note that x axes in B and C are natural log-transformed. The gray bar in B indicates the range of values (200 to 300) for the threshold elemental ratio, above which Daphnia P limitation is predicted to occur. The dotted lines in B and C indicate the Redfield ratios for C:P (106) and N:P (16), respectively.

Fig. 5.

Daphnia relative growth rate (g) response to seston concentration depended on both seston concentration and seston C:P ratio in Flathead Lake. Regression model was g = −0.123 + 0.256ln(C) + 0.073P (R² = 0.92), where C is the seston concentration, and P is a categorical value contrasting the control and P-enriched treatments. That is, this model showed that P enrichment of seston increased growth rate by 0.073 d⁻¹ (CI 0.40 to 0.98 d⁻¹) compared to unenriched seston, independent of food quantity. Note log-scaled x axis.

Fig. 6.

Time-course experiment showing phosphate suppression of methane production by planktonic methylphosphonic acid use in Flathead Lake (August 2018). Experimental treatments were unamended (circles) or amended with 106 µmol C L⁻¹ as glucose, 16 µmol L⁻¹ nitrate (as a source of N), and either 1 µmol L⁻¹ PO₄³⁻ (triangles), 1 µmol L⁻¹ MPn (squares), or 0.5 µmol L⁻¹ PO₄³⁻ + 0.5 µmol L⁻¹ MPn (diamonds).