Elsevier

Harmful Algae

Volume 97, July 2020, 101859
Harmful Algae

Comparing key drivers of cyanobacteria biomass in temperate and tropical systems

https://doi.org/10.1016/j.hal.2020.101859Get rights and content

Highlights

  • Predictive cyanobacteria models have an essential role in lake management (75).

  • Temperate and tropical regions data analyzed for similarities and differences (79).

  • Trophic state, climate and hydrodynamic were significant for cyanobacteria increase (85).

  • Data syntheses help to predict broad-scale patterns of cyanobacteria biomass (86).

Abstract

There is growing evidence that cyanobacterial blooms are becoming more common in different parts of the world; within this context, predictive cyanobacteria models have an essential role in lake management. Several models have been successfully used in temperate systems to describe the main drivers of cyanobacterial blooms, but relatively less work has been conducted in the Tropics. We analyzed data from six Brazilian reservoirs and from five Canadian lakes using a combination of regression tree analyses and variation partitioning to evaluate the similarities and differences between regions. Our results, together with a synthesis of the literature from different latitudes, showed that trophic state (i.e. nutrients), climatic variables (e.g., temperature and/or precipitation) and hydrodynamic regimes (i.e. water residence time) are significant drivers of cyanobacteria biomass over several scales. Nutrients came out as the primary predictor in both regions, followed by climate, but when all systems were pooled together, water residence time came out as most important. The consistency in variables identified between regions suggests that these drivers are widely important and cyanobacteria responded quite similarly in different geographical settings and waterbody types (i.e. lakes or reservoirs). However, more work is needed to identify key thresholds across latitudinal gradients. Taken together, these results suggest that multi-region syntheses can help identify drivers that predict broad-scale patterns of cyanobacteria biomass.

Introduction

Cyanobacteria are major component of phytoplankton and a group of special concern because several common species produce toxic peptides and alkaloids, like hepatotoxins, neurotoxins, cytotoxins, dermatotoxins, and genotoxins (Carmichael 1994; Buratti et al. 2017). Under favorable environmental conditions, cyanobacteria populations can grow into high-density blooms (Brookes & Carey, 2011; Paerl & Paul 2012; O'Neil et al., 2012). As a result of their potential to produce powerful toxins, cyanobacteria blooms can present a risk to humans and animals through direct contact or the consumption of contaminated water. However, cyanobacterial dominance and bloom occurrence remains highly variable among lakes of the world, and it is still difficult to predict their onset and duration (Carvalho et al., 2011; Cha et al., 2014; Chapra et al., 2017). Predictive modelling efforts also tend to be biased towards temperate ecosystems. Thus, while there has been substantial effort to study cyanobacteria to date, there has been only a limited effort to compare field studies from tropical and temperate ecosystems (see Fig. 1, Table S1).

Analyses of long-term and paleolimnological records (from mostly north temperate and subarctic lakes) have shown that cyanobacteria have become a more dominant portion of the plankton community in many sites around the world in recent decades (Taranu et al. 2015). High-resolution satellite images also showed that peak intensity of summertime algal blooms (many dominated by cyanobacteria) increased in more than two-thirds of freshwater bodies studied from around the world (Ho et al., 2019). The observed rise in cyanobacterial blooms in many waterbodies has been linked to rising nutrients concentrations (Carvalho, et al. 2011; Elliott, 2012), warmer water temperatures (Carey et al 2012; O'Neil et al., 2012), changes in thermal stratification and water-column stability (Wagner & Adrian 2009; Paerl & Paul, 2012), as well as the amount and timing of precipitation and its effect on hydrological patterns and runoff events (Brookes & Carey 2011; Romo et al 2013), which can modify nutrient loading to lakes, water residence time and water level fluctuations. Together, these changes are creating opportune conditions for cyanobacterial growth and dominance (Huisman et al., 2018) thanks to several characteristics of their metabolism and physiology. As an example, many cyanobacterial species have the ability to regulate their buoyancy through the formation and control of gas vesicles, which enable them to move within stratified water columns and outcompete other phytoplankton (Walsby 1994; Pfeifer, 2012).

Changes in each of these key drivers will not be isolated, but instead, are expected to interact with unforeseen outcomes. Furthermore, the effect of temperature and nutrients on the phytoplankton community can be additive or even synergistic (Vinebrooke et al 2004; Jackson et al 2016; Taherzadeh et al. 2019). Temperature is known to control metabolic rates and the growth of organisms, which in turn is also dependent on the availability of limiting nutrients. Nutrients are needed for maintenance and reproduction, but temperature will regulate their uptake, storage and use, thus again the interaction of these two factors is evident. Cross et al. (2015) suggested the concepts of metabolic theory in ecology (Brown et al., 2004) and ecological stoichiometry (Sterner & Elser, 2002) as a framework to explore links between temperature and nutrients. This framework can allow us to better understand how organisms and ecosystem function, given that they are based on the thermodynamics and mass balance principles, respectively. Overall, in order to accurately predict community responses to multiple global-change drivers, it is important to consider their interactions and combined effects.

Empirical statistical models have been developed for several aquatic environments to predict cyanobacterial bloom occurrence and to identify the multiple factors that promote their dominance (Downing et al. 2001; Giani et al. 2005; Taranu et al. 2012; Beaulieu et al. 2013, 2014; Pitois et al. 2014). Some studies have also included aquatic systems from different latitudinal regions, with the intent of generalizing patterns over broader geographical areas (Kosten et al. 2012; Mowe et al. 2015; Rigosi et al. 2015; Taranu et al. 2015). However, most of these studies still focus on temperate waterbodies (as summarized in Table S1). Only 19% of studies that adopted empirical models to predict cyanobacterial abundances in the last 20 year were developed in tropical or sub-tropical regions, whereas 65% were based in temperate environments and 15% included both regions (Fig. 1).

To evaluate how comparable temperate lake models are to tropical ones, we conducted a study using data from two groups of freshwater environments: six reservoirs in southeastern Brazil (Minas Gerais state, a tropical region), and four lakes in western Canada (province of Alberta, a temperate region). Because the two regions experience different climatic regimes, we wanted to contrast patterns of cyanobacteria biomass and their potential environmental drivers to recognize differences and similarities in parameter fit. By developing models over a broad geographical range, our objectives were thus to test whether the main drivers of cyanobacterial dominance were similar in temperate and tropical systems. We also evaluated if certain drivers were especially important in only one region. Lastly, given that our study sites covered a broad range of nutrient inputs and hydrodynamic regimes, we aimed to predict cyanobacteria risk in the context of both climate and eutrophication changes.

Section snippets

Study sites

We studied six reservoirs located in the state of Minas Gerais (Brazil): São Simão, Emborcação, Furnas, Marimbondo, Volta Grande and Pampulha (Fig. 2). To the exception of Pampulha, which is an urban artificial lake, all reservoirs were built for hydroelectric power generation. Pampulha reservoir was built in 1938 as a water supply for the city of Belo Horizonte, but its use was interrupted in the late 1980s with the first occurrence of cyanobacterial blooms. The six reservoirs cover a gradient

Results

Temperature clearly distinguished the two sets of waterbodies, as the Brazilian reservoirs were consistently warmer than the Canadian lakes over the growing season (Fig. 4). Regional precipitation was generally more variable in Brazil than in Canada. Measures of water residence time (WRT), defined as the average time spent by the water from time of inflow to that of outflow, were lowest in the Brazilian reservoirs, though within each ecosystem, broad WRT ranges were observed (Fig. 4). The

Discussion

Several models and simulations have been developed to explain and predict the widespread increase of toxic cyanobacteria blooms across different lake types and regions, although few studies have compared regions with a balanced design, giving tropical sites equal weight in model development (see references in Table S1). Our results showed that high nutrient concentration (as TP) was the major driver of elevated cyanobacteria biomass in each region (Figs. 5, 7A and 7B), which is consistent with

Acknowledgments

Sampling and samples processing in Brazil were supported by grants from Furnas Centrais Hidroelétrica S.A., Centrais Elétricas de Minas Gerais (CEMIG), Fundação do Amparo a Pesquisa de Minas Gerais (FAPEMIG), and Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq) to AG. A sabbatical visit of AG to the McGill University was supported by a CAPES Senior Fellowship. In Canada, funding was provided from a Natural Science and Engineering Research Council (NSERC) Strategic grant

Declaration of Competing Interest

The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper.

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