Phytoplankton functional response to spatial and temporal differences in a cold and oligotrophic lake

Cellamare, María; Lançon, Anne Marie; Leitão, Maria; Cerasino, Leonardo; Obertegger, Ulrike; Flaim, Giovanna

doi:10.1007/s10750-015-2313-2

Cited by 25 publications

(33 citation statements)

References 53 publications

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“…The FT and RG compositions were repeatedly found to correlate well with local environmental predictors in individual lakes (Cellamare et al, 2013(Cellamare et al, , 2016. Kruk et al (2011) showed that the morphological trait composition of phytoplankton could be best predicted from local environmental parameters over the RG and taxonomic compositions.…”

Section: Introductionmentioning

confidence: 87%

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Functional richness outperforms taxonomic richness in predicting ecosystem functioning in natural phytoplankton communities

2017

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Recent studies clearly support a positive biodiversity–ecosystem functioning (BEF) relationship in phytoplankton. As taxon richness does not quantify functional diversity, functional approaches have been developed to link community functioning to diversity. Compared to terrestrial plant communities, only a few studies have validated phytoplankton functional approaches in BEF relationships. Furthermore, the ability of functional and taxonomic richness measures in predicting ecosystem functioning of natural phytoplankton communities has not been compared yet. Here, we analysed the BEF relationship using taxonomic and functional (trait categories and response groups sensu Reynolds) approaches in a broad‐scale phytoplankton dataset from Fennoscandia. First, we analysed how taxonomic and functional compositions were related to local environmental predictors. We then compared how taxonomic and functional richness performed in predicting resource‐use efficiency (the yield in phytoplankton biomass standardised by total phosphorus) as an ecosystem functioning measure. Finally, we tested whether the relationship between ecosystem functioning and taxonomic richness is further enhanced once each of the functional richness measure is also considered. Among the approaches, phytoplankton functional trait categories as community matrix showed the best correspondence with the local environment. The richness of phytoplankton response groups predicted ecosystem functioning significantly better than the taxonomic and the functional trait category richness—both in the full dataset and in almost all Fennoscandian countries. On top of taxonomic richness, only the residual variation in response group richness predicted ecosystem functioning positively in the entire dataset and in all individual countries. Applying functional approaches, reduced complexity of data should come along with reduced ecological information. We showed, however, that both functional approaches represented some functional redundancy among taxa in a meaningful way, and enhanced our ability in predicting community composition from environmental predictors. Moreover, phytoplankton response group richness sensu Reynolds summarises information on ecosystem functioning contained in the taxonomic data in a way that represents functional diversity better than the richness of functional trait categories. Interestingly, the response group approach, which is exclusively derived from field observations rather than from quantified phytoplankton traits, outperforms taxonomic richness and trait category richness in predicting ecosystem functioning in our dataset. This may highlight that our ability to quantify phytoplankton traits is still limited. Existing phytoplankton functional approaches, however, can translate the taxonomic information into a reduced but reliable functional matrix already and predict ecosystem functioning better than taxonomic data.

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Section: Introductionmentioning

confidence: 87%

“…The FT and RG compositions were repeatedly found to correlate well with local environmental predictors in individual lakes (Cellamare et al., , ). Kruk et al.…”

Section: Introductionmentioning

confidence: 94%

Functional richness outperforms taxonomic richness in predicting ecosystem functioning in natural phytoplankton communities

2017

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“…According to this study it is dominant in oligotrophic karst system, but also present in oligo-to mesotrophic conditions of all other investigated lakes. P. costei concurs with C. comensis in ecological preference toward oligotrophy, since C. comensis was inserted into codon A Cellamare et al, 2016). Lindavia radiosa has been described from Lake Mondsee (Austria) as Cyclotella radiosa (Lemmermann, 1900), but latest taxonomic and phylogenetic analyses resulted with its transfer into genus Lindavia based on the position of rimoportula, striae structure, and presence of a complex alveolar structure in the central area (Nakov et al, 2015;Á cs et al, 2016).…”

Section: Assemblage Analysesmentioning

confidence: 96%

Defining centric diatoms of most relevant phytoplankton functional groups in deep karst lakes

et al. 2016

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Phytoplankton in karst lakes is characterized by co-occurrence of chrysophytes (Chrysophyceae), dinoflagellates (Dinophyceae), and diatoms (Bacillariophyta) as the most diverse and abundant group. Using Reynolds functional approach in ecological phytoplankton investigations makes karstic lakes comparable and facilitates interpretation of their responses to changing environmental conditions. Accurate taxonomic identification to species level, based on precise resolution of specific characteristics by electron microscopy, is essential in order to correctly associate species into coda. This paper defines the most abundant centric diatoms and coexisting species in the phytoplankton of karst lakes in Croatia as a contribution to better description of phytoplankton functional groups dominated by centric diatoms. Several representatives for diatom-based Reynolds functional groups of four lakes in Croatia were described in this paper: Pantocsekiella costei and Stephanocostis chantaica for group A, Pantocsekiella ocellata and Cyclotella distinguenda for group B, and Stephanodiscus neoastraea for group C, together with their ecological preferences which clearly correspond to pertaining functional classification. Selected and coexisting functional groups define natural, oligo-to mesotrophic karst deep lake systems.

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“…This study compares the temporal patterns of prokaryotes and protists in three different habitats for 4 years in Lake Tovel. This cold‐water montane lake shows steep temperature gradients in its basins (Cellamare et al, ), making it particularly vulnerable to changes in its thermal structure. Flaim et al () show how altered precipitation patterns led to a substantial temperature increase in Lake Tovel.…”

Section: Introductionmentioning

confidence: 99%

“…Generally, the concept of time is linked to a fixed calendar year of 365 days. However, the hydrological year starts after the snowmelt event that usually flushed the lake and thus emphasizes the ecological effect of water renewal in a highly dynamic system where communities are determined by hydrology (prokaryotes: Obertegger et al, ; phytoplankton and zooplankton: Flaim et al, ; phytoplankton: Cellamare et al, ; zooplankton: Obertegger et al, ).…”

Section: Introductionmentioning

confidence: 99%

Multifaceted aspects of synchrony between freshwater prokaryotes and protists

2019

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Community composition of freshwater prokaryotes and protists varies through time. Few studies contemporarily investigate temporal variation of these freshwater communities for more than 1 year. We compared the temporal patterns of prokaryotes and protists in three distinct habitats for 4 years (2014–2017) in Lake Tovel, a cold‐water lake. This lake showed a marked temperature increase in 2017 linked to altered precipitation patterns. We investigated whether microbial communities reflected this change across habitats and whether changes occurred at the same time and to the same extent. Furthermore, we tested the concept of hydrological year emphasizing the ecological effect of water renewal on communities for its explanatory power of community changes. Microbe diversity was assessed by Illumina sequencing of the V3–V4 hypervariable region of the 16S rRNA gene and 18S rRNA gene, and we applied co‐inertia analysis and asymmetric eigenvector maps modelling to infer synchrony and temporal patterns of prokaryotes and protists. When considering community composition, microbes were invariable in synchrony across habitats and indicated a temporal gradient linked to decreasing precipitation; however, when looking at temporal patterns, the extent of synchrony was reduced. Small‐scale patterns were similar across habitats and microbes and linked to seasonally varying environmental variables, while large‐scale patterns were different and partially linked to an ecosystem change as indicated by increasing water transparency and temperature and decreasing dissolved oxygen. Our advanced statistical approach outlined the multifaceted aspect of synchrony when linked to community composition and temporal patterns.

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Phytoplankton functional response to spatial and temporal differences in a cold and oligotrophic lake

Cited by 25 publications

References 53 publications

Functional richness outperforms taxonomic richness in predicting ecosystem functioning in natural phytoplankton communities

Functional richness outperforms taxonomic richness in predicting ecosystem functioning in natural phytoplankton communities

Defining centric diatoms of most relevant phytoplankton functional groups in deep karst lakes

Multifaceted aspects of synchrony between freshwater prokaryotes and protists

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