Environmental stoichiometry mediates phytoplankton diversity effects on communities' resource use efficiency and biomass

Resource availability sets an upper limit to potential primary production, whereas autotroph diversity constrains how much of this is realized (Cardinale et al., 2009; Hillebrand 2014; Lewandowska 2016). On one side, phytoplankton biomass constrained by nutrient concentrations and the ratios in which limiting nutrients are available (balanced or imbalanced; Elser 2007; Harpole 2011). At balanced ratios, organisms co-limited (supplied match organismal needs) transfer into maximized (Figure 1, Cardinale 2009). Traditionally, Redfield ratio for nitrogen (N) phosphorous (P) (N:P = 16, Redfield, 1958) has been treated as optimum. However, empirical theoretical work shown that optimal N:P might vary substantially between taxa, growth rates temperature (Elser 2000; Gerhard 2019; 2013; Klausmeier 2004; Thrane 2017). Contrarily, imbalanced decrease production efficiency do not needs build-up Sterner & Elser, 2002). Phytoplankton on other side expected increase ecosystem functioning (e.g. production). This based idea diverse communities show a higher functional (i.e. trait diversity; Cadotte 2011; Weithoff Beisner, 2019) allow complementarity effects niche partitioning facilitation generate increased function; Loreau Hector, 2001). Such effect results resource use (RUE, efficiently resources turned production) therefore 1; Ptacnik 2008; Schabhüttl Striebel Using metacommunity model, Hodapp al. (2016) showed enables strong positive when heterogeneity supply high. declines extending range involves inclusion highly ratios. if differ sites (homogeneous conditions) RUE determined best adapted species given conditions (Hodapp These predictions support biodiversity equals play out under high environmental variability, but uniform environments (Ptacnik 2010). variability provides wide spectrum can be used occupancy enhancing maintaining (Chen Norberg 2001; Smith Instead, homogeneous select certain traits favouring dominance few well-adapted independently community (identity effect; 2016; In addition direct affect coexistence (resource theory; Tilman, 1982). aspect was directly addressed our since study designed test competitive exclusion 1). Thus, conceptual modelling 2016) studies predict biodiversity–ecosystem (BEF) relationships strength variable availability, these have poorly tested experimentally. Few experimental investigations evaluated RUE, stoichiometry responses (Striebel 2009), (Frank 2020; Weis 2008) separately, combining factors concentrations, diversity). Additionally, BEF experiments random losses, while nature extinction driven species-specific features sensitivity, rarity). artificial assemblages indirectly combine with different history cultured laboratory, biasing understanding natural (Gamfeldt 2015; Srivastava Vellend, 2005). Because rare considered sensitive due their small population size (Pimm 1988), we gradient generated loss testing scenarios. previous mesocosm study, does result significant decay standing long common abundant maintained, considering two levels (Gerhard 2020). Here, investigated combined analyse affects using microcosm experiment. Results were compared they conducted simultaneously same conditions. initial scenarios, hypothesized following: (H1) Balanced (nutrient co-limitation) promote increasing utilization, especially present strategies trade-offs; (H2) The reflect supplied also influences content nutrient; (H3) becomes more important exposed (microcosm experiment) than similar (mesocosm experiment), thus representing environments, respectively. We expect mirrored carbon:nutrient transferring biomass. experiment coupled additional (Appendix S1: Figure S1) evaluate community, stoichiometry. Both collected from lake (Grafschaftsee, Germany, 53°33? 05?N; 7°58? 49?E) at end summer (2017). After sampling, grazers excluded filtering water through 53 ?m mesh. (six levels, lowest D1 highest D6) dilution (dilution ranged 1:1 × 105 1:1) removal (Engel 2017; Hammerstein Each level incubated flasks 26 days prior start (for methodological details, see created maintained during incubation until inoculation experiment, manipulation pool 2). richness inverse Simpson indices better represents species, effective number species) information about evenness. Despite changes over time, general remained duration S2). no data Nutrient treatments performed manipulating N P elements excess according WC medium (Guillard Lorenzen, 1972). 20°C (same summer) day–night cycle 12:12 hr light intensity 300 ?mol photon m?2 s?1 mesocosms 80 µmol photons flask incubations. Although absolute surface lower flasks, limitation as, Lambert–Beer law, low depth had little self-shading. Changes monitored photometrically daily optical density measurements (wavelength 440–450 nm) custom-tailored device six inoculated (low high) 600 L indoor comprising 12 units S1; Gall inoculum (corresponding levels) added volumes (between 150 ml) assuring amount all treatments. 8 52 (from D6; For treatments, 0.65 ?mol/L 14.2 added, mimicking (concentrations measured before experiments). To simulate enrichment, 1.9 42.6 total deviations initially narrow S3). sampled every 4 day 7 27 samplings. continued reached stationary phase. sampling event, 10% (60 L) replaced containing design concentrations. From volume water, 20 filtered mesh control presence large zooplankton (small controlled processing samples). Experimental details generation described (2020). carried factorial where each 25 leading units. that, cell culture flaks (250 ml polystyrene, Sarstedt Ltd.) filled 200 taken treatment) (see Appendix S1). 11 31 combinations 0.1, 0.7, 1.3, 2.6 P/L 3, 19, 35, 48 62 N/L treatment. including intermediate ‘balanced’ extreme ‘imbalanced’ treatment (not classified imbalanced) flexibility among communities. slightly base final variations cases established prevent sinking losses differences manually shaken randomly rearranged day. Samples phase reached. corresponding (D2–D6) after 24 days, (D1) 38 days. Water samples particulate organic carbon (POC), (PON) phosphorus (POP) onto acid-washed pre-combusted glass-fibre filters (Whatman GF/C). Filters POC PON elemental analyser (Flash EA 1112, Thermo Scientific). dissolved fractions ( ) following method Schnetger Lehners (2014) NO2), modified version Benesch Mangelsdorf (1972) ammonium (). POP () molybdate reaction fraction digestion potassium peroxydisulphate (K2S2O8) solution (Wetzel Likens, 2013). preserved Lugol counted identified inverted microscope Utermöhl's (Utermöhl, 1958). Sedimentation adjusted consistent counted. morphospecies clear assignment name possible. both experiments, analysed biomass, (carbon:nutrient ratios). POC, calculated unit per system (RUEP POC/total RUEN N; 2008), represent sum P, previously 2020), only report main paper (but Table S1 S4 RUEP). molar phytoplankton. produced nutrient, assimilation uptake. datasets, included numeric explanatory models numbers 1 6 assigned sequence, D1–D6). argument instead determination include uncertainty, complex identification counting. violates model assumption independent variables without error. comparison those obtained S2 incubations (n 150) interactive continuous linear model. response ln-transformed statistical analysis obtain relationships. visualization figures, non-linear curves fitted local polynomial regression (loess) RUEP across gradient. Alternative predictors (instead ratios) Supplementary Information S4). mixed models. gradient, (high low), time fixed 72). component defined comparing intercept (mesocosms), slopes together. accounted non-independence autocorrelation (autocorrelation function residual analyses) AR-1 structure Model selection done Akaike criterion protocol recommended Zuur (2009). lme (nmle package). marginal R2 conditional (Nakagawa Schielzeth, 2013) estimated (r.squaredGLMM MuMIn (2020), here order answer scientific questions. All analyses figures R 3.6.1 (R Development Core Team, ? 0.05 significance analyses. F-tests p values identify validation RUEN, (POC) interaction (Table Species (highest lowest) levels: consistently D6 D1, led did 3). difference (interactive linearly declined reflecting 3a). saturating rather 3b). saturation (~30), most linear. According (D1 D6), became evident 4a). D2 4a), indicating N-rich Only peaked decreased able (showed RUEP); reduction maintain (Figures 3 reflected decreasing 4b; S5). negative showing relative less relationship close up around 30, above rapidly 4b). patterns S5 S6). any its 2; 5). significantly low, high, level, both, lack responded differently level: tended (D6); nutrients, Interestingly, (D6) indicated explained proportion variance. Deviations consequently Methods) likely driving detected affected C:N C:P towards Overall, (according H3). Hence, highlight importance scenarios considered, contrasting found biological like terrestrial plants (Smith Knapp, 2003; Yoshihara bacteria (Roger 2016), functioning. diversity, promotes suggested (Hillebrand Matthiessen, 2010) studies. strongest resulted peak (rejecting H1). allowed incorporate (supporting H2). multiple limitation, (co-limitation) because uptake efficient, become 2016, 2019). necessarily (contrary depends stoichiometric context- characteristics Furthermore, highest. suggests communities' performance Generally, limited overall S5) buffering decay, (D1). losing reduced grew P-limiting strongly influenced While microcosms, slight tendency could observed. A smaller within variation. (2013) richness, suggesting processes. despite uptake, (Klausmeier 2008). suggest physiological limits (P-limitation) (Hall pattern 2019), curve limitation) weaker mirroring capacity cope (except dealing limitation). Ecosystem (neutral) (positive) sustaining context role caused generally compensated commonly plant supported decline extirpated (in D1). systems 2014). case, greater enhance dominant productive (species identity Vaughn, partially changed second (D2) represented almost Monoraphidium contortum monoculture S7) concordance M. monocultures (Bogen dominating (Ferragut de Campos Bicudo, 2012) limitation. concentration (this Contrasting scenario, (including played mixtures (of 5 find (close presented variety efficient trends taxonomic S8). Cell related therefore, (Acevedo-Trejos 2018; Litchman 2010; Marañón, 2015). Size positively experiments. translated it experiment). favours note composition conditioned pool, competition). rarity aspects composition, evenness; Bonachela Dickman 2006; even history), non-random develop consequence biotic interactions influence example, dominated generating high-biomass contribution pressure S7). manipulated minimize limitations assemblages: co-occur histories. manipulate distribution arbitrary simulated losses. need considered. increases complexity sample handling count identification), what us mechanistic patterns. Microscopy approaches lead underestimation subsample higher. such bias change addition, closed combination (N concentration) unit. recolonization possible, experienced unique scenario pulse fluctuations). step further meta-community approaches, set-ups deal dispersal). Finally, prioritized replication, risk detecting stochastic effects. Beyond limitations, consider worth novel enabling (closer simple well variable. processes effect, complementarity) resulting contrary expected, Most coped distribution) buffer general, modulates highlights addressing ecosystems crucial investigate variation interacts change. thank Dorothee advice Silvia Heim, Alexander Wacker, Andrea Gall, Lena Engelmann, Corinna Mori technical support. M.G. Uruguayan Agency Investigation Innovation (ANII: POS_EXT_2015_1_122989) German Academic Exchange Service (DAAD: 91645020). M.S. H.H. acknowledge funding Research Foundation (DFG: STR 1383/6-1) priority program DynaTrait (SPP 1704). Open access enabled organized Projekt DEAL. declare conflict interest. M.G., conceived ideas methodology; A.S. data; writing manuscript. authors contributed critically drafts gave approval publication. peer review article https://publons.com/publon/10.1111/1365-2745.13811. Data Dryad Digital Repository https://doi.org/10.5061/dryad.s1rn8pk8w 2021). 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