DOI: 10.5061/dryad.73n5tb3bw
title: Assemblage organization over time prevents invasion success in phytoplankton

description: Invasion plays a central role in long-term species coexistence, sometimes
 rejuvenating and, at other times, collapsing diversity. Community
 resistance to invasions depends partly on the community’s species richness
 and structure, both of which change with community organization over time.
 Here, we study the resistance of phytoplankton assemblages to invasions
 based on varied initial species richness and structure, as well as
 assemblage organization over time. We hypothesize that invasion success
 will be greater in less organized assemblages and lower in more organized
 assemblages. To test this, we first experimentally constructed
 phytoplankton assemblages by mixing natural assemblages from regional
 lakes and manipulated richness along with a dilutional gradient as part of
 a large-scale mesocosm experiment. Phytoplankton assemblages from these
 mesocosms of varying dilution rate were selected and mixed to create
 unorganized assemblages of  high and low richness. We considered
 these constructed phytoplankton assemblages unorganized because their
 structures were not the result of ecological interactions. For an invader,
 we used the green alga Golenkinia radiata, a taxon historically observed
 in the region but absent from the natural assemblages at the time of
 sampling. We conducted four sequential invasion experiments, each lasting
 seven days, initiated with the increasingly organized assemblages of the
 mesocosms. We found that assemblages, while still unorganized early in
 succession, were vulnerable to invasions. However, as the assemblages
 organized with time, they became resistant to invasions. Assemblage
 richness, which ranged from 23 to 29 in the high-richness mesocosms and
 from 15 to 24 in the low-richness mesocosms, had only a marginal effect on
 invasion success. Instead, declining resources, notably phosphorus,
 reduced diversity, and the emerging dominance of strong competitors near
 the niche of the G. radiata invader explained the decreased success of
 invasions as the assemblages organized with time. In the more organized
 assemblages, G. radiata encountered formidable competitors in established
 populations of the diatom Nitzschia acicularis and the chrysophyte Synura
 sp., both of which had higher affinities for phosphorus than G. radiata.
 Our study highlights that assemblage organization with time plays a
 fundamental role in phytoplankton species coexistence, including a
 stronger resistance to invasion as assemblages mature.
description: Invasion experiments were initiated at different times using
 water samples collected from an ongoing mesocosm experiment. That mesocosm
 experiment had manipulated initial species pool richness from natural
 phytoplankton assemblages. Those constructed assemblages then organized
 over time, allowing for these invasion experiments (Figure 1). In the
 sections below, this is described in detail.
 <em>Collection of phytoplankton
 assemblages</em> Integrated water column samples
 were gathered from the euphotic zones of three sub-Alpine lakes in Lower
 Austria during August 2022. The euphotic zones were estimated using 2.5
 times the Secchi depth (Nõges et al. 2010). The lakes included Lake Lunz
 (N 47°85’37”, E 15°05’23”, dimictic, maximum depth 32 meters), Lake
 Erlaufsee (N 47°79’30”, E 15°27’08”, dimictic, maximum depth 30 meters),
 and Lake Purgstall (N 48°09’61”, E 15°13’62”, polymictic, maximum depth
 3.5 meters). Samples were sieved through a 100 µm mesh in the field to
 remove large zooplankton and were then transported to a mesocosm facility
 at the Biological Station of WasserCluster Lunz, Lunz am See. Lake
 assemblages were mixed and further sieved through a 55 µm mesh to
 eliminate microzooplankton. Consequently, an unorganized and species-rich
 assemblage was formed, which was then distributed into several mesocosm
 containers. <em>Making of unorganized
 assemblages, high and low richness, in mesocosms</em>
 The mesocosms were situated outdoors, with a volume of 320
 liters, and constructed from food-safe polyethylene (ARICON Kunststoffwerk
 GmbH, Solingen, Germany). They rested on a gravel bed in an unshaded
 meadow (N 47°85’45”, E 15°06’76”). The water in each mesocosm was
 continuously, but gently, circulated using an airlift. The mesocosms were
 insulated with mineral wool to mitigate daily temperature fluctuations and
 covered with a 250 µm-mesh net to minimize the introduction of particles
 and other species. To create unorganized assemblages of
 varying species richness, mesocosms were first maintained for a three-week
 period hosting the initial regional species pool inoculum at five
 different dilution rates in duplicate. The dilutions spanned a gradient of
 0.066 d<sup>-1</sup> to 0.505 d<sup>-1</sup>. The
 approach excluded slower-growing and rare taxa from the initial species
 rich pool in response to  dilution rates (Hammerstein et al., 2017), and
 successfully created a richness gradient. From assemblages of varied
 richness at the end of the three-week period, mixtures of varied
 proportions were used to further enhance the species richness gradient. By
 creating mixtures, any assemblage organization that had occurred during
 the previous three weeks was undone. These remixed assemblages were
 monitored for four weeks (see Smeti et al. <em>In
 Preparation</em>). It is during this four-week period that the
 invasion experiments were conducted. Two remixed assemblages —one with the
 highest and another with the lowest species richness— were utilized for
 our invasion experiment. <em>Design of the
 invasion experiments</em> Invasion experiments
 were conducted in 2.5-liter transparent plastic spouted bags (PET/NY/LDPE
 material, DaklaPack®), that were started on days 0, 7, 14, and 21 of the
 four-week mesocosm experiment described in Smeti et al. (<em>In
 Preparation</em>), with each lasting seven days. These experiments
 were initiated using assemblages collected from the high- and low-richness
 mesocosms, resulting in each invasion experiment being conducted with a
 progressively organized assemblage. The invader species used was
 <em>Golenkina radiata</em> Chodat, a species common to the
 region but absent from the mixed assemblages in the mesocosms. Two
 invasion propagules were explored, comprising 1% and 10% of the resident
 assemblage’s biomass, determined fluorometrically. Treatments and
 controls, with no added <em>G. radiata</em>, were performed in
 triplicate. Phytoplankton enumeration, which included determining
 population densities and cellular volumes for all taxa, was performed at
 the start of each invasion experiment, along with measurements for
 chlorophyll <em>a</em> (Chl-<em>a</em>), total
 phosphorus (TP), soluble reactive phosphorus (SRP), nitrate
 (NO<sub>3</sub>), nitrite (NO<sub>2</sub>), and
 ammonium (NH<sub>4</sub>). Cell counts of the <em>G.
 radiata</em> culture were also performed at these times.
 <em>Parameter measurements</em> To
 determine the volume of culture needed to produce our target invader
 propagules in the invader experiments, phytoplankton biomass estimates
 were made from the mesocosms and in the <em>G. radiata</em>
 culture. We used chlorophyll <em>a</em> as a proxy for
 biomass. We measured chlorophyll <em>a</em> <em>in
 vivo</em> using autofluorescence. A hand-held AquaPen-C AP-C 100 PSI
 (Drásov, Czech Republic) fluorometer, along with a 20-minute dark
 adaptation period, was employed for measurements of
 autofluorescence. An analytical method for measuring
 Chl-<em>a</em> samples was also employed, conducted twice per
 week in the mesocosms, with one of the weekly measurements coinciding with
 the start times of the invasion experiments. In these instances, water was
 passed through GF/F filters (Whatman, pore size: 0.7 μm), extracted in
 acetone, stored at -20 °C until analyses, and then analyzed using a
 fluorescence method without phaeophytin correction (Arar and Collins,
 1997). For nutrients, TP was measured using an ascorbic
 acid colorimetric method (Hansen and Koroleff, 1999) after persulfate
 digestion (Clesceri et al., 1999). The detection limit of this method was
 0.2 µg liter<sup>-1</sup>. A FLOWSYS Continuous Flow Analyzer
 (CFA, SYSTEA, Italy) was used for the measurements of
 NO<sub>3</sub>, NO<sub>2</sub>,
 NH<sub>4</sub>, and SRP with detection limits of 100 µg-N
 liter<sup>-1</sup>, 1 µg-N liter<sup>-1</sup>, 2
 µg-N liter<sup>-1</sup>, and 0.04 µg-P
 liter<sup>-1</sup>, respectively. Nutrients were measured at
 least twice per week in the mesocosms, with one of the weekly measurements
 coinciding with the start times of the invasion experiments.
 Samples for phytoplankton enumeration were collected twice weekly
 from the mesocosms and preserved in Lugol’s iodine solution, with sampling
 coinciding with the start times of the invasion experiments. Phytoplankton
 samples were analyzed according to Utermöhl method (1958) and Lund et al.
 (1958), using an Axio Observer 7 (Zeiss, International) inverted
 microscope at 400x magnification. Counts included 400 sedimentation units.
 Taxon-specific median biovolume for each species per sample was calculated
 using approximate geometrical forms (Hillebrand et al., 1999), based on at
 least 20 measurements for dominant taxa. Biovolume was converted to
 biomass by assuming a density of 1 g
 ml<sup>-1</sup>. <em>Calculations and
 Analyses</em> In this study, species richness
 refers to the number of taxa identified in our microscopic enumeration.
 Using the number of taxa and the biomass densities, diversity and evenness
 were determined with the Shannon Index (Shannon 1948) and Pielou's
 Index (Pielou 1966), respectively. Resource use efficiency (RUE) was
 calculated as ln(Chl-<em>a</em>/TP) following Ptacnik et al.
 (2008). The productivity of the phytoplankton assemblage was calculated as
 the total biomass change in the mesocosm divided by the initial total
 biomass for seven-day periods coinciding with the invasion experiments.
 The invasion success was assessed by the change in <em>G.
 radiata</em> biomass density in a bag divided by the biomass density
 of the added <em>G. radiata</em>. Large proportional changes
 were considered high invasion success (here in the 200-300% range), lower
 proportional changes were considered lower invasion success (here in the
 ~100% range), and decreases in the proportional changes were considered as
 unsuccessful invasion outcomes (here in the -50% to -100%
 range). Invasion success into increasingly organized
 assemblages was assessed using one-way ANOVAs with Tukey’s post hoc tests
 and smooth spline models. Four data arrangements were explored with these
 tests based on the t0, t7, t14, and t21 invasion experiments that began
 with high- and low-species richness, and at 1% and 10% invader propagules.
 These statistics were performed using the Statistics Toolbox in the MATLAB
 programming language. Relationships between invasion
 success, measures of assemblage structure (richness, evenness, diversity),
 performance (biomass, RUE, production), and nutrient availability (SRP,
 TP, NO<sub>3</sub>, NO<sub>2</sub>,
 NH<sub>4</sub>) at the 1% and 10% invader propagule levels
 were explored using multiple linear regression models. To achieve this, we
 created regression models representing all combinations of the measured
 parameters, omitting models that had diversity included with either
 richness or evenness, as diversity is calculated from those. So, the
 regression model that included all considered parameters (omitting
 diversity) took the form: <em>Invasion</em>
 =       a0 + a1<em>Richness + a2</em>Evenness + a3*Biomass
                               (1) + a4<em>RUE +
 a5</em>Production + a6<em>SRP + a7</em>TP
 + a8<em>NO<sub>3</sub> +
 a9</em>NO<sub>2</sub> +
 a10*NH<sub>4</sub> and the regression model
 that included all considered parameters (omitting richness and evenness)
 took the form: <em>Invasion</em> =       a0
 + a1<em>Diversity + a2</em>Biomass + a3<em>RUE +
 a4</em>Production          (2) + a5<em>SRP
 + a6</em>TP + a7<em>NO<sub>3</sub> +
 a8</em>NO<sub>2</sub> +
 a9*NH<sub>4</sub> where a0 through a10 were
 coefficients of the regression models. The root mean square errors (RMSEs)
 of all models were then used to determine the best models, with the lowest
 RMSE indicating the optimal model. We explored these regression models
 using both raw data and z-scored data. These regression models were
 performed using the Statistics Toolbox in the MATLAB programming
 language. The relationships between invasion success
 and species composition of assemblages at 1% and 10% invader propagule
 levels were investigated using Principal Component Analysis. There are
 many taxa observed in these experiments. The multivariate analysis, here
 PCA, shows which taxa negatively associate with invasion success,
 suggesting which taxa are likely bringing about poor invader outcomes. To
 achieve this, a covariance matrix was created from the z-scored species
 biomasses and invasion success data from the invasion experiments using a
 1% propagule, and another covariance matrix was generated from the
 invasion experiments using a 10% propagule. PCAs were conducted using the
 Statistics Toolbox in the MATLAB programming language.
 The distribution of P-affinities was used to explore if lumpy
 coexistence was occurring in these assemblages, as this is a factor
 important to invasion success. The P-affinities can also be used to
 identify like competitors. Distribution of the taxa in each assemblage
 along the P-affinity gradient was estimated using log10(cell volume),
 based on the assumption that body size distributions represent niche
 differentiations (Scheffer and van Nes 2006, Segura et al. 2011, 2013,
 Muhl et al. 2018, Graco‐Roza et al. 2021). Nutrient affinities for each
 taxon were estimated using the bioinformatics-driven online tool
 Phyto-PhlyoPars (Bruggeman et al. 2009, Bruggeman 2011). Our focus was on
 phosphorus affinity (P-affinity), since nitrogen was less influential in
 these experiments (to be shown).
description: # Assemblage organization over time prevents invasion success in
 phytoplankton Dataset DOI:
 [10.5061/dryad.73n5tb3bw](https://doi.org/10.5061/dryad.73n5tb3bw)
 **Description of the data and file structure** The data are from mesocosm
 experiments in which artificially assembled phytoplankton communities were
 allowed to organize over time. Two communities were used, one that started
 with low diversity and another that started with high diversity. During
 this period of organization, invasion experiments were conducted using
 aliquots from these mesocosms. The data is in a workbook. The first
 worksheet shows the cell count data of the invader from the start and end
 of the invasion experiment. Four invasion experiments were performed one
 after the other. The second worksheet shows the species composition of the
 phytoplankton communities as they organized over time. **File:
 BEFree_Invasion_Exp_raw_data_plus_comm_data_2_(post_to_Dryad).xlsx** In
 the first worksheet called 'counts of invader', the population
 densities of the invader species are shown. In column A, called
 'Experiment' the treatments are identified. An 'H'
 means that the initial phytoplankton diversity was high. An 'M'
 means that the initial phytoplankton diversity was low. 'zero',
 '1', and '10' refer to the propagule size of the
 invasion. There are four groupings designated, each showing the results
 from the four back-to-back invasion experiments. These are: 1\. H - zero
 invader – First invasion experiment, high diversity mesocosm, no invader
 added. 1\. H - '1' invader – First invasion experiment, high
 diversity mesocosm, 1% invader propagule. 1\. H - '10' invader –
 First invasion experiment, high diversity mesocosm, 10% invader propagule.
 1\. M - zero invader – First invasion experiment, low diversity mesocosm,
 no invader added. 1\. M - '1' invader – First invasion
 experiment, low diversity mesocosm, 1% invader propagule. 1\. M -
 '10' invader – First invasion experiment, low diversity
 mesocosm, 10% invader propagule. 2\. H - zero invader – Second invasion
 experiment, high diversity mesocosm, no invader added. 2\. H -
 '1' invader – Second invasion experiment, high diversity
 mesocosm, 1% invader propagule. 2\. H - '10' invader – Second
 invasion experiment, high diversity mesocosm, 10% invader propagule. 2\. M
 - zero invader – Second invasion experiment, low diversity mesocosm, no
 invader added. 2\. M - '1' invader – Second invasion experiment,
 low diversity mesocosm, 1% invader propagule. 2\. M - '10'
 invader – Second invasion experiment, low diversity mesocosm, 10% invader
 propagule. 3\. H - zero invader – Third invasion experiment, high
 diversity mesocosm, no invader added. 3\. H - '1' invader –
 Third invasion experiment, high diversity mesocosm, 1% invader propagule.
 3\. H - '10' invader – Third invasion experiment, high diversity
 mesocosm, 10% invader propagule. 3\. M - zero invader – Third invasion
 experiment, low diversity mesocosm, no invader added. 3\. M -
 '1' invader – Third invasion experiment, low diversity mesocosm,
 1% invader propagule. 3\. M - '10' invader – Third invasion
 experiment, low diversity mesocosm, 10% invader propagule. 4\. H - zero
 invader – Fourth invasion experiment, high diversity mesocosm, no invader
 added. 4\. H - '1' invader – Fourth invasion experiment, high
 diversity mesocosm, 1% invader propagule. 4\. H - '10' invader –
 Fourth invasion experiment, high diversity mesocosm, 10% invader
 propagule. 4\. M - zero invader – Fourth invasion experiment, low
 diversity mesocosm, no invader added. 4\. M - '1' invader –
 Fourth invasion experiment, low diversity mesocosm, 1% invader propagule.
 4\. M - '10' invader – Fourth invasion experiment, low diversity
 mesocosm, 10% invader propagule. Still in the first worksheet called
 'counts of invader', in columns 'C', 'D',
 and 'E' are shown the initial cell density of the invader in
 units of cells per liter, the final cell density of the invader in units
 of cells per liter, and the proportional change in the invader's cell
 density of the course of each invasion experiment. Column ‘F’ is the
 mesocosm identifier, where ‘14’ signifies the mesocosm of high diversity,
 and ‘15’ signifies the mesocosm of low diversity. In the second worksheet
 called 'community data', the population densities of all
 phytoplankton species are shown. These were the community compositions of
 the two mesocosms from which waters were used to initiate the invasion
 experiments. The units of these population densities are µg-carbon per
 liter. Rows 2 though 6 show the phytoplankton community composition from
 the high diversity mesocosm, and rows 7 though 11 show the phytoplankton
 community composition from the low diversity mesocosm. The taxa are:
 Achnanthidium minutissimum Acutodesmus acutiformis Chlamydomonas incerta
 Chlamydomonas sp. Chlorella like sphere Chlorella vulgaris Chlorella-like
 sphere colony Chlorococcum infusionum Chromulina sp. Chrysochromulina
 parva Chrysophyceae small sphere Cryptomonas obovate Cryptomonas Phaseolus
 Desmodesmus communis Desmodesmus subspicatus Diadesmis like chain
 Flagellated green sphere Fragilaria capucina Fragilaria tenera
 Granulocystis verrucosa Gymnodinium sp. Hariotina reticulata Katablepharis
 sp. Kirchneriella irregularis Koliella longiseta Lanceola spatulifera
 Lemmermannia tetrapedia Lemmermannia triangularis Mychonastes jurisii
 Nephrochlamys subsolitaria Nitzschia acicularis Nitzschia gracilis
 Nitzschia sp. Ochromonas sp. Oocystis borgei Oocystis marssonii
 Plagioselmis lacustris Plagioselmis nannoplanctica Pseudopediastrum
 boryanum Pseudopedinella sp. Pseudopedinella sp. (small) Rhopalodia gibba
 Scenedesmus sp. Synura sp. - single cell Ulnaria acus Ulnaria ulna Still
 in this second worksheet called 'community data', Columns ‘A’
 through ‘F’ indentify the experiment and time. In column ‘A’: T014 –
 mesocosm waters at the start of the first invasion experiment from the
 high-diversity mesocosm. T114 – mesocosm waters at the start of the second
 invasion experiment from the high-diversity mesocosm. T214 – mesocosm
 waters at the start of the third invasion experiment from the
 high-diversity mesocosm. T314 – mesocosm waters at the start of the fourth
 invasion experiment from the high-diversity mesocosm. T414 – mesocosm
 waters at the end of the fourth invasion experiment from the
 high-diversity mesocosm. T015 – mesocosm waters at the start of the first
 invasion experiment from the low-diversity mesocosm. T115 – mesocosm
 waters at the start of the second invasion experiment from the
 low-diversity mesocosm. T215 – mesocosm waters at the start of the third
 invasion experiment from the low-diversity mesocosm. T315 – mesocosm
 waters at the start of the fourth invasion experiment from the
 low-diversity mesocosm. T415 – mesocosm waters at the end of the fourth
 invasion experiment from the low-diversity mesocosm. In column ‘B’: ‘14’ –
 mesocosm identifier for the high-diversity mesocosm. ‘15’ – mesocosm
 identifier for the low-diversity mesocosm. In column ‘C’: ‘H’ – mesocosm
 identifier for the planned high-diversity mesocosm. ‘M’ – mesocosm
 identifier for a planned middle-diversity mesocosm (which did not result
 from our pre-treatment). In column ‘D’: ‘MH’ – mesocosm identifier for the
 realized high-diversity mesocosm. ‘L’ – mesocosm identifier for the
 realized low-diversity mesocosm. In column ‘E’: “T0” – sampling from the
 mesocosm at the start of the first invader experiment. “T1” – sampling
 from the mesocosm at the start of the second invader experiment. “T2” –
 sampling from the mesocosm at the start of the third invader experiment.
 “T3” – sampling from the mesocosm at the start of the fourth invader
 experiment. “T4” – sampling from the mesocosm at the end of the fourth
 invader experiment. In column ‘F’: “0” – sampling from the mesocosm at the
 start of the first invader experiment. “7” – sampling from the mesocosm at
 the start of the second invader experiment. “14” – sampling from the
 mesocosm at the start of the third invader experiment. “21” – sampling
 from the mesocosm at the start of the fourth invader experiment. “28” –
 sampling from the mesocosm at the end of the fourth invader experiment.  
 **Sharing/Access information** Other publicly accessible locations of the
 data: * none Data was derived from the following sources: * Cells counts
 performed in the research labs of the authors