Phytoplankton Configuration in Six Deep Lakes in the Peri-Alpine Region: Are the Key Drivers Related to Eutrophication and Climate?
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Phytoplankton configuration in six deep lakes in the peri-Alpine region: are the key drivers related to eutrophication and climate? Nicole Gallina, Nico Salmaso, Giuseppe Morabito & Martin Beniston Aquatic Ecology A Multidisciplinary Journal Relating to Processes and Structures at Different Organizational Levels ISSN 1386-2588 Aquat Ecol DOI 10.1007/s10452-013-9433-4 1 23 Your article is protected by copyright and all rights are held exclusively by Springer Science +Business Media Dordrecht. This e-offprint is for personal use only and shall not be self- archived in electronic repositories. If you wish to self-archive your work, please use the accepted author’s version for posting to your own website or your institution’s repository. You may further deposit the accepted author’s version on a funder’s repository at a funder’s request, provided it is not made publicly available until 12 months after publication. 1 23 Author's personal copy Aquat Ecol DOI 10.1007/s10452-013-9433-4 Phytoplankton configuration in six deep lakes in the peri-Alpine region: are the key drivers related to eutrophication and climate? Nicole Gallina • Nico Salmaso • Giuseppe Morabito • Martin Beniston Received: 26 May 2012 / Accepted: 2 March 2013 Ó Springer Science+Business Media Dordrecht 2013 Abstract The aim of this study was to draw a water temperatures, variables that are strongly influ- general picture of the phytoplankton community in enced by climate change and eutrophication. Though peri-Alpine lakes, including for the first time a broad different phytoplankton configurations among lakes data set of six deep peri-Alpine lakes, belonging to the were partly due to their geographical (altitude) same geographical region. The objective was to define position, assemblages were mostly linked to temper- the main key drivers that influence the phytoplankton ature and nutrients. Furthermore, the results confirmed community composition in this particular vulnerable the significant role of the spring fertilization on the region, for which the impacts of climate change have seasonal phytoplankton development. Cyanobacteria been demonstrated to be stronger than on a global were related to the increasing annual average of air average. The phytoplankton was investigated with a and water temperature gradient and therefore might particular focus on cyanobacteria and using a classi- become more important under future warming sce- fication approach based on morpho-functional groups. nario. Air temperatures have a significant impact on We hypothesized that phytoplankton in peri-Alpine water temperature in the uppermost meters of the lakes is mainly driven by nutrient loads as well as by water column, with a stronger influence on warmer lakes. Handling Editor: Piet Spaak. Keywords Cyanobacteria Á Lake effect Á N. Gallina (&) Á M. Beniston Temperature Á Morpho-functional groups Á Climate Change and Climate Impacts, Institute of Phosphorus loads Á Global warming Environmental Science, University of Geneva, Campus Battelle, Building D, 7 Rte de Drize, 1227 Carouge, Switzerland e-mail: [email protected] Introduction N. Salmaso Physical, hydrodynamical, and ecological changes are Sustainable Agro-ecosystems and Bioresources occurring in lake ecosystems; these changes are Department, IASMA Research and Innovation Centre, Istituto Agrario di S. Michele all’Adige, Fondazione E. forecasted to become greater in the future as global Mach, Via E. Mach 1, 38010 S. Michele all’Adige, temperatures are increasing partly as a result of human Trento, Italy activities (IPCC 2007; Williamson et al. 2009; George 2010;). In the course of the twentieth century, the G. Morabito CNR, Istituto Studio Ecossistemi, Largo Tonolli 50, Alpine region has been shown to be particularly 28922 Verbania-Pallanza, VB, Italy vulnerable and sensitive to climate change (Beniston 123 Author's personal copy Aquat Ecol et al. 1997; Beniston 2006), with higher rate of their behavior, which is summarized by the broadly warming, at least double of the observed global accepted Plankton Ecology Group (PEG) model average. (Sommer et al. 1986). The PEG model identifies the The question of particular interest is to assess how main influencing factors of the seasonal behavior, such global warming may affect the phytoplankton com- as climate, weather, grazing, and water chemistry. munity composition, which plays an important role as Several studies debate the duality and the interaction it is the basis of nearly all aquatic ecosystems’ food between nutrients (mainly phosphorus) and tempera- supply (Arrigo 2005). Changes in the phytoplankton ture (reflecting climatological and meteorological community exert an effect on the higher food chain forcing) in affecting phytoplankton communities and can potentially disrupt the ecological equilibrium (Moss et al. 2003; Elliot et al. 2006; Stich and Brinker of lakes. Moreover, particular attention is paid to the 2011). Both these factors have been shown to consid- group of cyanobacteria, the only freshwater phyto- erably influence the seasonal phytoplankton commu- plankton group that not only forms blooms, but is also nity (Gallina et al. 2011; Salmaso et al. 2012). able to produce a variety of toxic compounds (Sivonen As several lakes are implicated, it is noteworthy and Jones 1999). Cyanobacteria thus can potentially that every lake is a mirror of its environment, and harm lake ecosystems through food web disturbance therefore, the phytoplankton community growth can and anoxia due to massive bloom events, affect human be presumed to differ in between lakes, as does the health (water supply, food contamination), the econ- water chemistry and environmental factors (Reynolds omy (fishing industry), and finally, social activities, as, and Walsby 1975; Lung and Paerl 1988; Ryding and for example, the recreational use of lakes. As the Rast 1989; Bleckner 2005). This phenomenon implies world’s oldest known organisms (Schopf 2000), that the hydro-morphometrical features, the surround- cyanobacteria have always been capable of adapting ing landscape, origin, and history of a lake may play an to environmental change (Huisman et al. 2005; Paul important role (Ryding and Rast 1989; Bleckner 2008). They have relatively high temperature optima 2005). Recent studies demonstrate different response for growth (Reynolds 2006) and are able to migrate of lakes to climate change (Bleckner 2005; George vertically in the water column to better compete for 2010). light and nutrients (Ibelings et al. 1991; Walsby et al. The underlying assumption is that phytoplankton 1997; Reynolds 2006). A number of studies have compositions among peri-Alpine lakes mainly repre- predicted that cyanobacteria are likely to become more sent different responses to nutrient concentrations and abundant in the future as climate continues warming temperature. These factors are strongly affected by the (Paerl and Huisman 2008; Paul 2008; Gallina et al. influence of climate change and eutrophication. In 2011; Paerl and Paul 2012). deep lakes, a further element to take into account is the The common phylogenetic classification of phyto- spring replenishment of nutrients from the deeper to plankton is based on taxonomy. However, since a the surface layer. We hypothesize that this pool could traditional taxonomy does only partially reflect the represent an important source of nutrients for phyto- ecological function of phytoplankton (Webb et al. plankton throughout the year. 2002; Litchman and Klausmeier 2008), other classi- After previous research based on a smaller number fications were proposed to aggregate species/genera of northern peri-Alpine lakes (cf. Anneville et al. having similar traits, for example, functional-based 2004, 2005), this study reports a synoptic assessment classifications (Reynolds et al. 2002), the morpho- of phytoplankton assemblages and their main driving functional-based classification (Salmaso and Padisa`k factors across six peri-Alpine lakes situated north and 2007), and the morphological-based classification south of the alpine chain. The main key drivers of (Kruk et al. 2010). These aggregations have the phytoplankton composition changes will be evaluated advantages to better interpret environmental mecha- on yearly and seasonal timescales (summer–autumn). nisms and conditions and are easier to deduce as they A matrix including eight different data sets generated enclose common affinities and considerably reduce from six lakes (two of the lakes were sampled at two the numbers of interpreting components. different locations) was compiled. For reasons of In deep lakes under a continental climate, phyto- comparability, the six lakes are all deep and warm plankton communities exhibit strong seasonality in monomictic lakes, situated in the same geographical 123 Author's personal copy Aquat Ecol region. Additionally, these lakes have the interesting namely Lake Constance, Lake Zu¨rich, Lake Walen, features to cover a large trophic gradient and to be Lake Geneva, Lake Maggiore, and Lake Garda. Data located along an altitudinal gradient. from Lake Geneva and Lake Zu¨rich were collected at two sampling points, named as ‘‘Small Lake Geneva’’ and ‘‘Big Lake Geneva,’’ as well as ‘‘Upper Lake Materials and methods Zu¨rich’’ and ‘‘Lower Lake Zu¨rich,’’ respectively. Consequently, eight data sets were derived from the Lake characteristics and data sources six lakes. The six lakes have a number of features in common: Figure 1 a shows the locations of the lakes. The matrix They are all deep, warm monomictic lakes (Hutch- includes