Nutrient reduction mitigated the expansion of cyanobacterial blooms caused by climate change in Lake Taihu according to Bayesian network models.

Although nutrient reduction has been used for lake eutrophication mitigation worldwide, the use of this practice alone has been shown to be less effective in combatting cyanobacterial blooms, primarily because of climate change. In addition, quantifying the climate change contribution to cyanobacterial blooms is difficult, further complicating efforts to set nutrient reduction goals for mitigating blooms in freshwater lakes. This study employed a continuous variable Bayesian modeling framework to develop a model to predict spring cyanobacterial bloom areas and frequencies (the responses) using nutrient levels and climatic factors as predictors. Our results suggested that both spring climatic factors (e.g., increasing temperature and decreasing wind speed) and nutrients (e.g., total phosphorus) played vital roles in spring blooms in Lake Taihu, with climatic factors being the primary drivers for both bloom areas and frequencies. Climate change in spring had a 90% probability of increasing the bloom area from 35 km2 to 180 km2 during our study period, while nutrient reduction limited the bloom area to 170 km2, which helped mitigate expansion of cyanobacterial blooms. For lake management, to ensure a 90% probability of the mean spring bloom areas remaining under 154 km2 (the 75th percentile of the bloom areas in spring), the total phosphorus should be maintained below 0.073 mg·L-1 under current climatic conditions, which is a 46.3% reduction from the current level. Our modeling approach is an effective method for deriving dynamic nutrient thresholds for lake management under different climatic scenarios and management goals.

Total phosphorus-precipitation and Chlorophyll a-phosphorus relationships of lakes and reservoirs mediated by soil iron at regional scale.

Phosphorus is a critical element determining trophic status and Chlorophyll a (Chl a) level in natural lakes and reservoirs, and total phosphorus (TP) concentrations can be predicted from data on phosphorus loading, hydraulic flushing rate and sedimentation. Due to their interactions with phosphorus, iron (hydr) oxides in suspended particles, originally derived from watershed soil, can strongly influence the phosphorus sedimentation and phosphorus bioavailability in water columns. Thus, the TP-precipitation relationship and the response of Chl a to TP are likely associated with watersheds soil iron. To test this assumption, we built hierarchical linear models for summer observation of natural lakes and reservoirs across a large geographic gradient. The intercepts and slopes of TP-precipitation relationships are higher in natural lakes than those in reservoirs, and these model coefficients exhibit latitudinal variations that are explained by the natural soil iron gradient. Soil iron, operating at a regional level, significantly mediates the effect of precipitation on TP concentration in both natural lakes and reservoirs, and drives the latitudinal variation in the Chl a-TP relationships for reservoirs. Our results imply that the increase in extreme precipitation events anticipated under future climate conditions may substantially mitigate eutrophication in tropical and subtropical reservoirs, but may worsen conditions in temperate lakes.

A Meta-Analysis on the Effect of Agricultural Conservation Practices on Nutrient Loss.

Conservation practices are widely used to reduce N and P loads from agricultural fields and minimize their impact on water quality, but research using field-scale data to model the national average impact of conservation practices for different forms of N and P is needed. Thus, we quantified the effects of conservation practices (grassed waterways, terraces, contour farming, filter strips, and riparian buffers) on total, particulate, and dissolved N and P runoff from farmlands. Specifically, we conducted a meta-analysis of the Measured Annual Nutrient loads from AGricultural Environments (MANAGE) database using propensity score matching and multilevel modeling to remove the influence of confounding factors. There is no best method for addressing this influence, so we applied two alternative methods because similar results increase confidence in our findings. Propensity score matching found that conservation practices reduced total P, particulate P, and particulate N loading by an average of 67, 83, and 67%, respectively. Multilevel modeling estimated reductions of 58, 76, and 64% for the same nutrients. Although the propensity score method only yields a mean rate of reduction, multilevel modeling further estimates the reduction for different subgroups (i.e., different crops and fertilizer application methods) when such groupings are feasible. The multilevel models indicated that conservation practices affected row crops the most (e.g., corn [ L.] and soybean [ (L.) Merr.]) and fields with injected or surface-applied fertilizers. Our analysis used field-scale data to estimate the average effectiveness of conservation practices in reducing N and P runoff, providing valuable insight for regional and national decision making.

Estimating ecological thresholds for phosphorus in the Everglades.

The Florida Everglades, a wetland of international importance, has been undergoing a significant shift in its native flora and fauna due to excessive total phosphorus (TP) loadings (an average of 147 t per annum from 1995to 2004) and an elevated mean TP concentration (69 microg L(-1) of TP in 2004) from agricultural runoff and Lake Okeechobee outflow despite the use of 16000 ha of stormwater treatment areas. Here, we present a Bayesian changepoint analysis of long-term experimental research and show that exceeding a surface water geometric mean TP threshold concentration of 15 microg L(-1) causes an ecological imbalance in algal, macrophyte, and macroinvertebrate assemblages as well as slough community structure. A phosphorus threshold for all trophic levels may be more realistic and protective when presented as a threshold zone (12-15 microg L(-1)) because estimates of uncertainty must be utilized to accurately define TP thresholds, which change with seasons and water depths. Most interior areas of the Everglades are currently at or below this threshold zone, but the exterior areas near inflow structures (except for the Everglades National Park) are presently receiving double or triple the proposed threshold. Our Bayesian approach, used hereto address ecological imbalance along nutrient gradients, is applicable to determining thresholds and stable states in other aquatic ecosystems.