DOI: 10.5061/dryad.zkh189378
title: Data from: The ghost of disturbance past: long-term effects of pulse disturbances on community biomass and composition

description: Current global change is associated with an increase in disturbance
 frequency and intensity, with the potential to trigger population
 collapses and to cause permanent transitions to new ecosystem states.
 However, our understanding of ecosystem responses to disturbances is still
 incomplete. Specifically, there is a mismatch between the diversity of
 disturbance regimes experienced by ecosystems and the one-dimensional
 description of disturbances used in most studies on ecological stability.
 To fill this gap, we conducted a full factorial experiment on microbial
 communities, where we varied the frequency and intensity of disturbances
 affecting species mortality, resulting in twenty different disturbance
 regimes. We explored the direct and long-term effects of
 these disturbance regimes on community biomass. While most communities
 were able to recover biomass and composition states similar to undisturbed
 controls after a halt of the disturbances, we identified some disturbance
 thresholds that had long-lasting legacies on communities. Using a
 model based on logistic growth, we identified qualitatively the
 sets of disturbance frequency and intensity that had equivalent
 long-term negative impacts on experimental communities.
 Our results show that an increase in disturbance intensity is a bigger
 threat for biodiversity and biomass recovery than the occurrence of more
 frequent but less intense disturbances.
description: <b>Microbial
 community</b> We conducted an experiment on an aquatic community composed of 12 protozoan species, one rotifer species and a set of common freshwater bacteria (<i>Serratia fonticola</i>, <i>Bacillus subtilis</i> and <i>Brevibacillus brevis</i>) as a food resource [39]. Bacteria, in turn were supported on a plant-based nutrient medium. The 12 protozoan species were <i>Blepharisma </i>sp<i>., Chilomonas </i>sp.,<i> Chlorogonium euchlorum, Colpidium </i>sp<i>., Cyclidium </i>sp<i>., Euglena gracilis, Euplotes aediculatus, Loxocephalus </i>sp<i>., Paramecium aurelia, Paramecium caudatum, Spirostomum </i>sp<i>., </i>and<i> Tetrahymena </i>sp<i>., </i>and the rotifer was<i> Cephalodella </i>sp. (subsequently all 13 are referred to as “protists”). All of these species are bacterivores, whereas <i>C. euchlorum</i>, <i>E. gracilis</i> and <i>E. aediculatus</i> can also photosynthesize. Furthermore, <i>Blepharisma </i>sp., <i>Euplotes aediculatus</i>, and <i>Spirostomum </i>sp. may not only feed on bacteria but can also predate on smaller protists (see table S1 for more information on the species). Another angle of this experiment, namely the effect of pulsed disturbances on size-abundance pyramids during the first phase of the experiment, has already been analysed in Jacquet et al. [42]. Here, in addition their direct effect, we investigated the long-term legacy of the disturbance regimes, that is, after a halt of the disturbances, on community composition, species richness and total community biomass.   <b>Disturbance experiment</b> We performed a factorial experiment in which we varied the frequency and intensity of pulse disturbances affecting species density, resulting in a total of twenty different disturbance regimes. A pulse disturbance was achieved by boiling a subsampled fraction of the well-mixed community in a microwave at 800 W that killed all living protists (see also [41–43]). The disturbances were therefore density independent, as all species experienced the same level of density reduction. Afterwards, the medium was cooled down to room temperature and was given back to the microcosm within 45 minutes. By doing so, we kept the composition of the microcosm constant and avoided nutrient addition or loss. This procedure mimics disturbances such as fire and flooding, which initially reduce population density but may also enhance the regeneration of nutrients [25]. We disturbed microcosms at five intensities: <i>I = </i>10, 30, 50, 70 and 90 % and at four frequencies: <i>f </i>= 0.08, 0.11, 0.17 and 0.33, corresponding to a disturbance every 12, 9, 6 and 3 days, respectively. Each factorial treatment combination was replicated 6 times, giving in total 120 replicates. We additionally cultured 8 control microcosms in an undisturbed environment under the same conditions to define a reference community state. The disturbance experiment lasted for 21 days, or 10–50 generations depending on species (table S1). One additional measurement was taken 39 days after the onset of the disturbance experiment in order to estimate the long-term effect of disturbance regimes on community biomass and composition, that is 20 and 26 days after the last disturbance event happened for frequencies <i>f = </i>0.11, 0.17, 0.33, and frequency <i>f </i>= 0.08 respectively. The populations in the microcosms experiencing the lowest frequency (<i>f </i>= 0.08) had therefore 6 more days to recover compared to other microcosms, or 3–14 generations depending on species.    <b>Microcosm description</b> Each replicate consisted of a 250 ml Schott bottle filled with nutrient medium to 100 ml. The microcosms were assembled by first filling each Schott bottle with 30 ml of pre-autoclaved standard protist medium (Carolina Biological Supply, Burlington NC, USA), and 5 ml of a bacteria solution composed of three species (<i>Serratia fonticola</i>, <i>Bacillus subtilis</i> and <i>Brevibacillus brevis</i>). After 24 hours, to allow time for bacteria growth, we added 65 ml of protist solution with each protist species at carrying capacity (5 ml per species). All communities were allowed to grow for 1 week before disturbance treatments started to be implemented. General lab procedures follow the protocols described in Altermatt et al. [39], and build upon previous work on the effect of pulse disturbances on diversity [41,44], size-abundance pyramids [42], and invasion dynamics [45].   <b>Sampling</b> We sampled 0.2 ml of the well-mixed microcosms daily to quantify total community biomass (i.e. total bioarea in mm<sup>2</sup>/ml)) using a standardized video procedure [39,46]. In brief, a constant volume (14.9 μl) of each sample was placed under a dissecting microscope connected to a camera and a computer for the recording of videos (4 s per video, that is 100 video frames). Then, using image processing software (IMAGEJ, National Institute of Health, USA) and the R-package <i>bemovi </i>[47], we extracted the number of moving organisms per video frame and the size of each individual (mean cell area in mm<sup>2</sup>). We estimated community biomass as the sum area of all individuals averaged by video frames, assuming proportionality between area and mass. Other traits, such as organisms’ speed and shape, were used to filter out background movement noise (e.g. particles from the medium). Finally, we assessed manually the presence or absence of each protist species at t = 39 (i.e. visual analysis of the videos) in order to determine the composition and species richness of each microcosm at the end of the experiment.
description: <strong>code_ghost_disturbance_past.R :</strong> main
 file to produce all the figures of the manuscript. Open it with
 statistical software R. To run it entirely, you will need the following
 R-packages: ‘<strong>ggplot2</strong>’,
 ‘<strong>grid</strong>’,
 ‘<strong>RColorBrewer</strong>’,
 ‘<strong>scales</strong>’ ‘<strong>scico</strong>’
 and ‘<strong>sciplot</strong>’. You will also need the R
 functions ’<strong>multiplot.R</strong>',
 ’<strong>param_heatmaps_biomass.R</strong>',
 ’<strong>param_heatmaps_sp.R</strong>" and
 ’<strong>stats_fun.R</strong>' as well as the data files
 ’<strong>community_biomass.Rdata</strong>' and
 ’<strong>table_species_PA.txt</strong>' provided along
 with this code in the same repository to produce the figures. All files
 were created using R version 3.5.1 (2018-07-02).
 <strong>community_biomass.Rdata :</strong> file with
 the time series of community biomass for all the microcosms.
 <strong>table_species_PA.txt :</strong> file with
 species presence/absence (1/0) for all the microcosms at the end of the
 experiment (t = 39).
 <strong>multiplot.R</strong>,
 <strong>param_heatmaps_biomass.R </strong>and <strong>param_heatmaps_sp.R : </strong>R functions used to create the heatmaps in Figure 2-4. <strong>stats_fun.R</strong> : R function to compute the statistics presented in Table S2.