The dual synchronizing influences of precipitation and land use on stream properties in a rapidly urbanizing watershed

Limnological data derived from high frequency monitoring buoys are asynchronous in a large lake

Autonomous data collection is rapidly becoming an integral part of water quality monitoring, particularly for agencies looking to manage and protect aquatic ecosystems. While beneficial, it is unclear how the collection of these data can be applied in spatially complex large lakes (e.g., Laurentian Great Lakes) given the spatial heterogeneity of the ecosystem. To address this potential shortcoming in large lakes, we assessed the synchrony of sensor variables between 10 pairs of static buoys in the western basin of Lake Erie (western basin surface area =  3,282 km2). Within western Lake Erie, water temperature was highly synchronous whereas dissolved oxygen, turbidity, chlorophyll and phycocyanin were asynchronous. The extent of this asynchrony was higher with increasing spatial distance between buoys. We found that between pairs of static buoys, temperature, dissolved oxygen, and turbidity all experienced decreasing correlations with increasing distance. Our results show that if researchers intend to leverage these data to answer important questions and provide real-time applications related to environmental issues like harmful algal/cyanobacterial blooms, monitoring networks need to be designed carefully with spatial complexity in mind. While autonomous data collection has many benefits, the reliance on a single or limited network of anchored monitoring buoys in large lake ecosystems has a high probability of missing important spatial features of these systems.

Investigating extreme hydrological risk impact on water quality; evidence from Buffalo catchment headwater, Eastern Cape, South Africa

Evidence from increasing mineralization, micropollutant concentrations, waterborne epidemics, an algal boom, and dissolved organic matter has provided substantial evidence that climate change impacts water quality. While the impact of the extreme hydrological event (EHE) on water quality (WQ) has aroused considerable research interest, research uncertainty has been premised on WQ data scarcity, a short time frame, data non-linearity, data structure, and environmental biases on WQ. This study conceptualized a categorical and periodic correlation using confusion matrices and wavelet coherence for varying standard hydrological drought index (SHDI; 1971-2010) and daily WQ series (1977-2011) of four spatially distinct basins. By condensing the WQ variables using chemometric analyses, confusion matrices were assessed by cascading the SHDI series into 2-, 3-, and 5-phase scenarios. 2-phase revealed an overall accuracy (0.43-0.73), sensitivity analysis (0.52-1.00), and Kappa coefficient (- 0.13 to 0.14), which declines substantially with the phase increase, suggesting the disruptive impact of EHE on WQ. Wavelet coherence depicted the substantial ([Formula: see text]) mid- and long-term (8-32 days; 6-128 days) co-movement of streamflow over WQ, confirming the varying sensitivity of WQ variables. Land use/land cover mapping and the Gibbs diagram corroborate the eventful WQ evolution by EHE and their spatial variability concerning landscape transformation. Overall, the study deduced that hydrologic extreme triggers substantial WQ disruption with dissimilar WQ sensitivity. Consequently, suitable chemometric indicators of EHE impacts such as WQ index, nitrate-nitrogen, and Larson index at designated landscapes were identified for extreme chemodynamics impact assessment. This study proffers a recommendation for monitoring and managing the impact of climate change, floods, and drought on water quality.

Synchronous Biodegradability and Production of Dissolved Organic Matter in Two Streams of Varying Land Use

In aquatic ecosystems, dissolved organic matter (DOM) composition is driven by land use, microbial activity, and seasonal variation in hydrology and water temperature, and, in turn, its microbial bioavailability is expected to vary due to differences in its composition. It is commonly assumed that DOM of terrestrial origin is resistant to microbial activity because it is composed of more complex aromatic compounds. However, the effect of DOM sources on the microbial reworking and degradation of the DOM pool remains debated. We performed laboratory incubation experiments to examine how temporal changes in DOM composition influence its microbial biodegradability in two contrasting streams (agricultural and forested) in southern Ontario, Canada. Despite a more allochthonous-like DOM signature in the forest stream and a more autochthonous-like DOM signature in the agriculture stream, we found that biodegradation and production of DOC were the same in both streams and synchronous throughout the sampling period. However, the initial DOM composition impacted how the DOM pool changed upon degradation. During the incubations, both autochthonous-like and allochthonous-like fractions of the DOM pool increased. We also found that a greater change in DOM composition during the incubations induced higher degradation of carbon. Finally, temporal variation in DOC biodegradation and production over time or across streams was not related to DOM composition, although there was a significant relationship between BDOC and nutrient concentrations in the agriculture stream. This observation potentially challenges the notion that DOM origin predicts its bioavailability and suggests that broad environmental factors shape DOC consumption and production in aquatic ecosystems. More research is needed to better understand the drivers of microbial biodegradability in streams, as this ultimately determines the fate of DOM in aquatic ecosystems.

Effects of connectivity and watercourse distance on temporal coherence patterns in a tropical reservoir

Temporal coherence exists when environmental variables measured at different spatial locations vary synchronously over time. This is an important property to be analyzed because levels of coherence may indicate the role of regional and local processes in determining population and ecosystem dynamics. Also, studies on temporal coherence may guide the optimal allocation of sampling effort. We analyzed a dataset from a monitoring program undertaken at a tropical reservoir (Peixe Angical Reservoir, State of Tocantins, Brazil) to test three predictions. First, coherence should be a common pattern in the reservoir considering that sampling sites were distributed in a single water body and over a small spatial extent. Second, coherence was expected to decline with increasing watercourse distance and to increase with hydrological connectivity. Third, abiotic variables should exhibit higher coherence than biological variables. Twenty limnological variables were monitored at 14 sites and for 31 months. We found significant levels of coherence for all variables, supporting our first prediction. Watercourse distances, hydrological connectivity, or both were significant predictors of coherence for 17 environmental variables. In all these cases, the signs of the coefficients were in the direction predicted. Interestingly, for some environmental variables (color, turbidity, alkalinity, and total phosphorus), hydrological connectivity was even more important in predicting coherence than watercourse distance. The view that abiotic variables should exhibit higher coherence than biological variables was supported. Our analyses revealed that precipitation was an important factor inducing coherence of a key set of environmental variables, highlighting the role of regional processes in ecosystem dynamics.