Response of cyanobacteria and phytoplankton abundance to warming, extreme rainfall events and nutrient enrichment

Cyanobacterial blooms are an increasing threat to water quality and global water security caused by the nutrient enrichment of freshwaters. There is also a broad consensus that blooms are increasing with global warming, but the impacts of other concomitant environmental changes, such as an increase in extreme rainfall events, may affect this response. One of the potential effects of high rainfall events on phytoplankton communities is greater loss of biomass through hydraulic flushing. Here we used a shallow lake mesocosm experiment to test the combined effects of: warming (ambient vs. +4°C increase), high rainfall (flushing) events (no events vs. seasonal events) and nutrient loading (eutrophic vs. hypertrophic) on total phytoplankton chlorophyll‐a and cyanobacterial abundance and composition. Our hypotheses were that: (a) total phytoplankton and cyanobacterial abundance would be higher in heated mesocosms; (b) the stimulatory effects of warming on cyanobacterial abundance would be enhanced in higher nutrient mesocosms, resulting in a synergistic interaction; (c) the recovery of biomass from flushing induced losses would be quicker in heated and nutrient‐enriched treatments, and during the growing season. The results supported the first and, in part, the third hypotheses: total phytoplankton and cyanobacterial abundance increased in heated mesocosms with an increase in common bloom‐forming taxa—Microcystis spp. and Dolichospermum spp. Recovery from flushing was slowest in the winter, but unaffected by warming or higher nutrient loading. Contrary to the second hypothesis, an antagonistic interaction between warming and nutrient enrichment was detected for both cyanobacteria and chlorophyll‐a demonstrating that ecological surprises can occur, dependent on the environmental context. While this study highlights the clear need to mitigate against global warming, oversimplification of global change effects on cyanobacteria should be avoided; stressor gradients and seasonal effects should be considered as important factors shaping the response

Adaptive forecasting of phytoplankton communities

The global proliferation of harmful algal blooms poses an increasing threat to water resources, recreation and ecosystems. Predicting the occurrence of these blooms is therefore needed to assist water managers in making management decisions to mitigate their impact. Evaluation of the potential for forecasting of algal blooms using the phytoplankton community model PROTECH was undertaken in pseudo-real-time. This was achieved within a data assimilation scheme using the Ensemble Kalman Filter to allow uncertainties and model nonlinearities to be propagated to forecast outputs. Tests were made on two mesotrophic lakes in the English Lake District, which differ in depth and nutrient regime. Some forecasting success was shown for chlorophyll a, but not all forecasts were able to perform better than a persistence forecast. There was a general reduction in forecast skill with increasing forecasting period but forecasts for up to four or five days showed noticeably greater promise than those for longer periods. Associated forecasts of phytoplankton community structure were broadly consistent with observations but their translation to cyanobacteria forecasts was challenging owing to the interchangeability of simulated functional species

Integrating freshwater biodiversity data sources: key challenges and opportunities

1. In order to better quantify spatial and temporal patterns in freshwater biodiversity, and potential underlying drivers of change, we must utilise the increasingly broad range of data available on freshwater ecosystems. Statistical advances in the field of integrated modelling provide new opportunities to further our understanding through the combined and simultaneous analysis of these diverse datasets. 2. We briefly introduce integrated modelling in the context of freshwater biodiversity and outline the key steps involved in its implementation, from data collection to analysis. We highlight both opportunities and challenges for the application of integrated approaches. 3. To illustrate the potential for integrated models to improve our understanding of freshwater biodiversity compared to standard approaches, we combine two datasets collected using different methods to model the distribution of Agabus water beetles in England. The integrated model had greater power to detect covariate effects on Agabus distribution, and reduced parameter uncertainty compared with analysis using only a single dataset. 4. We show that integrated methods have the potential to increase our understanding of freshwater systems and enable us to make full use of the diversity of freshwater data available

Effects of brownification and warming on algal blooms, metabolism and higher trophic levels in productive shallow lake mesocosms

An increase of dissolved organic carbon (DOC) in inland waters has been reported across the northern temperate region but the effects of this on whole lake ecosystems, often combined with other anthropogenic stressors like nutrient inputs and warming, are poorly known. The effects of these changes on different component of the ecosystem were assessed in an experiment using twenty-four large (3000L) outdoor mesocosms simulating shallow lakes. Two different temperature regimes (ambient and ambient +4 °C) combined with three levels of organic matter (OM, added as filtered peaty water), simulating the DOC increase that is predicted to take place over the next 4 to 21 years were used. Neither temperature nor OM had significant effects on net ecosystem production, respiration or gross primary production. Phytoplankton chlorophyll a concentration was not significantly affected by warming, however in summer, autumn and winter it was significantly higher in mesocosms receiving intermediate OM levels (July–Feb DOC concentrations 2–6 mg L−1). Summer cyanobacterial blooms were highest in intermediate, and lowest in the highest OM treatments. OM concentration also influenced total macroinvertebrate abundance which was greater in spring and summer in mesocosms with intermediate and high OM. Fish abundance was not significantly affected by OM concentration, but abundance was greater in ambient (55 fish subsample−1) compared to heated mesocosms (17 fish subsample−1) and maximum abundance occurred two weeks later compared to heated mesocosms. The results suggest that changes in OM may have a greater effect on shallow lakes than temperature and that phytoplankton, especially cyanobacteria, benefit from intermediate OM concentrations, therefore, nuisance algal blooms might increase in relatively clear shallow eutrophic lakes where DOC concentrations increase

Constraining uncertainty and process-representation in an algal community lake model using high frequency in-lake observations

Excessive algal blooms, some of which can be toxic, are the most obvious symptoms of nutrient enrichment and can be exacerbated by climate change. They cause numerous ecological problems and also economic costs to water companies. The process-representation of the algal community model PROTECH was tested within the extended Generalised Likelihood Uncertainty Estimation framework which includes pre-defined Limits of Acceptability for simulations. Testing was a precursor to modification of the model for real-time forecasting of algal communities that will place different demands on the model in terms of a) the simulation accuracy required, b) the computational burden associated with the inclusion of forecast uncertainties and c) data assimilation. We found that the systematic differences between the model’s representation of underwater light compared to the real lake systems studied and the uncertainties associated with nutrient fluxes will be the greatest challenges when forecasting algal blooms

Global data set of long-term summertime vertical temperature profiles in 153 lakes

Climate change and other anthropogenic stressors have led to long-term changes in the thermal structure, including surface temperatures, deepwater temperatures, and vertical thermal gradients, in many lakes around the world. Though many studies highlight warming of surface water temperatures in lakes worldwide, less is known about long-term trends in full vertical thermal structure and deepwater temperatures, which have been changing less consistently in both direction and magnitude. Here, we present a globally-expansive data set of summertime in-situ vertical temperature profiles from 153 lakes, with one time series beginning as early as 1894. We also compiled lake geographic, morphometric, and water quality variables that can influence vertical thermal structure through a variety of potential mechanisms in these lakes. These long-term time series of vertical temperature profiles and corresponding lake characteristics serve as valuable data to help understand changes and drivers of lake thermal structure in a time of rapid global and ecological change

The extent and variability of storm-induced temperature changes in lakes measured with long-term and high-frequency data

The intensity and frequency of storms are projected to increase in many regions of the world because of climate change. Storms can alter environmental conditions in many ecosystems. In lakes and reservoirs, storms can reduce epilimnetic temperatures from wind-induced mixing with colder hypolimnetic waters, direct precipitation to the lake's surface, and watershed runoff. We analyzed 18 long-term and high-frequency lake datasets from 11 countries to assess the magnitude of wind- vs. rainstorm-induced changes in epilimnetic temperature. We found small day-to-day epilimnetic temperature decreases in response to strong wind and heavy rain during stratified conditions. Day-to-day epilimnetic temperature decreased, on average, by 0.28 degrees C during the strongest windstorms (storm mean daily wind speed among lakes: 6.7 +/- 2.7 m s(-1), 1 SD) and by 0.15 degrees C after the heaviest rainstorms (storm mean daily rainfall: 21.3 +/- 9.0 mm). The largest decreases in epilimnetic temperature were observed >= 2 d after sustained strong wind or heavy rain (top 5(th) percentile of wind and rain events for each lake) in shallow and medium-depth lakes. The smallest decreases occurred in deep lakes. Epilimnetic temperature change from windstorms, but not rainstorms, was negatively correlated with maximum lake depth. However, even the largest storm-induced mean epilimnetic temperature decreases were typicallyPeer reviewe

Anoxia begets anoxia: a positive feedback to the deoxygenation of temperate lakes

Declining oxygen concentrations in the deep waters of lakes worldwide pose a pressing environmental and societal challenge. Existing theory suggests that low deep-water dissolved oxygen (DO) concentrations could trigger a positive feedback through which anoxia (i.e., very low DO) during a given summer begets increasingly severe occurrences of anoxia in following summers. Specifically, anoxic conditions can promote nutrient release from sediments, thereby stimulating phytoplankton growth, and subsequent phytoplankton decomposition can fuel heterotrophic respiration, resulting in increased spatial extent and duration of anoxia. However, while the individual relationships in this feedback are well established, to our knowledge, there has not been a systematic analysis within or across lakes that simultaneously demonstrates all of the mechanisms necessary to produce a positive feedback that reinforces anoxia. Here, we compiled data from 656 widespread temperate lakes and reservoirs to analyze the proposed anoxia begets anoxia feedback. Lakes in the dataset span a broad range of surface area (1–126,909 ha), maximum depth (6–370 m), and morphometry, with a median time-series duration of 30 years at each lake. Using linear mixed models, we found support for each of the positive feedback relationships between anoxia, phosphorus concentrations, chlorophyll a concentrations, and oxygen demand across the 656-lake dataset. Likewise, we found further support for these relationships by analyzing time-series data from individual lakes. Our results indicate that the strength of these feedback relationships may vary with lake-specific characteristics: For example, we found that surface phosphorus concentrations were more positively associated with chlorophyll a in high-phosphorus lakes, and oxygen demand had a stronger influence on the extent of anoxia in deep lakes. Taken together, these results support the existence of a positive feedback that could magnify the effects of climate change and other anthropogenic pressures driving the development of anoxia in lakes around the world

Causal networks of phytoplankton diversity and biomass are modulated by environmental context

Untangling causal links and feedbacks among biodiversity, ecosystem functioning, and environmental factors is challenging due to their complex and context-dependent interactions (e.g., a nutrient-dependent relationship between diversity and biomass). Consequently, studies that only consider separable, unidirectional effects can produce divergent conclusions and equivocal ecological implications. To address this complexity, we use empirical dynamic modeling to assemble causal networks for 19 natural aquatic ecosystems (N24◦~N58◦) and quantified strengths of feedbacks among phytoplankton diversity, phytoplankton biomass, and environmental factors. Through a cross-system comparison, we identify macroecological patterns; in more diverse, oligotrophic ecosystems, biodiversity effects are more important than environmental effects (nutrients and temperature) as drivers of biomass. Furthermore, feedback strengths vary with productivity. In warm, productive systems, strong nitrate-mediated feedbacks usually prevail, whereas there are strong, phosphate-mediated feedbacks in cold, less productive systems. Our findings, based on recovered feedbacks, highlight the importance of a network view in future ecosystem management

Physical and chemical impacts of a major storm on a temperate lake: a taste of things to come?

Extreme weather can have a substantial influence on lakes and is expected to become more frequent with climate change. We explored the influence of one particular extreme event, Storm Ophelia, on the physical and chemical environment of England's largest lake, Windermere. We found that the substantial influence of Ophelia on meteorological conditions at Windermere, in particular wind speed, resulted in a 25-fold increase (relative to the study-period average) in the wind energy flux at the lake-air interface. Following Ophelia, there was a short-lived mixing event in which the Schmidt stability decreased by over 100 Jm-2 and the thermocline deepened by over 10 m during a 12-hour period. As a result of changes to the strength of stratification, Ophelia also changed the internal seiche regime of Windermere with the dominant seiche period increasing from ~17 h pre-storm to ~21 h post-storm. Following Ophelia, there was an upwelling of cold and low-oxygenated waters at the southern-end of the lake. This had a substantial influence on the main outflow of Windermere, the River Leven, where dissolved oxygen concentrations decreased by ~48 %, from 9.3 mg L-1 to 4.8 mg L-1, while at the mid-lake monitoring station in Windermere, it decreased by only ~3%. This study illustrates that the response of a lake to extreme weather can cause important effects downstream, the influence of which may not be evident at the lake surface. To understand the impact of future extreme events fully, the whole lake and downstream-river system need to be studied together