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

Abstract

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.

Functional diversity promotes phytoplankton resource use efficiency

“…While traditional BEF research mainly focused on species diversity that includes only information of species richness and relative abundance, increasing number of studies have shown that influences of diversity on ecosystem functions depends largely on the traits and functional roles of species (Cadotte, Carscadden, & Microtchnick, ; Diaz & Cabido, ; Gagic et al, ; Klais, Norros, Lehtinen, Tamminen, & Olli, ; Petchey & Gaston, ). Thus, functional diversity, measuring the functional differences among species based on their traits, has been proposed to improve mechanistic understandings of BEF (Abonyi, Horváth, & Ptacnik, ; Cadotte et al, ; Gagic et al, ; Petchey & Gaston, ). Indeed, several studies have shown that trait‐based functional diversity predicts ecosystem functioning better than species diversity (Abonyi et al, ; Gagic et al, ; Ye, Chang, García‐Comas, Gong, & Hsieh, ).…”

“…Thus, functional diversity, measuring the functional differences among species based on their traits, has been proposed to improve mechanistic understandings of BEF (Abonyi, Horváth, & Ptacnik, ; Cadotte et al, ; Gagic et al, ; Petchey & Gaston, ). Indeed, several studies have shown that trait‐based functional diversity predicts ecosystem functioning better than species diversity (Abonyi et al, ; Gagic et al, ; Ye, Chang, García‐Comas, Gong, & Hsieh, ). Therefore, functional diversity has been suggested as a principal concept for revealing mechanisms linking diversity with ecosystem functioning and processes (Nathan, Osem, Shachak, & Meron, ).…”

Measures and Approaches in Trait-Based Phytoplankton Community Ecology – From Freshwater to Marine Ecosystems

“…All of these indicators are relevant to questions of competitive interaction between phytoplankton, interaction with predators, and thus community assembly. Explicitly-defined traits will also characterize ecosystem functioning, including processes such as primary production, trophic transfer (biomass) and nutrient cycling and this has been addressed mainly in studies relating biodiversity to ecosystem function (BEF studies) (e.g., Zwart et al, 2015;Abonyi et al, 2018).…”

“…It relies heavily on the idea that the morphometry of taxa reflect their autecology (physiology and functioning) (Kruk et al, 2010). Thus, like the response group approach of Reynolds (1988Reynolds ( , 1997, it differs from the explicit trait approach in that it considers trait-mediated effects that arise from species interactions (by empirically assessing group composition) (Abonyi et al, 2018). Summarily, clusters of taxa based entirely on morphological features can be defined statistically and should represent meaningful functional phytoplankton groups.…”

Biodiversity ecosystem functioning research in freshwater phytoplankton: A comprehensive review of trait-based studies

“…In this review, I only included studies that statistically analyzed the link between any trait-based metric of diversity and ecosystem functioning using freshwater phytoplankton. I excluded studies in lotic systems (i.e., rivers and streams) and studies in which phytoplanktonic organisms were classified into functional groups, such as major algal groups or Reynold's classification because they did not include a clear trait-based diversity measure (Schmidtke et al, 2010;Behl et al, 2011;Borics et al, 2012;Fernandez et al, 2014;Abonyi et al, 2017).…”