DOI: 10.5061/dryad.w3r228118
title: Population asynchrony within and between trophic levels have contrasting effects on consumer community stability in a subtropical lake

description: 1.  Clarifying the effects of biodiversity on ecosystem stability
 in the context of global environmental change is crucial for maintaining
 ecosystem functions and services. Asynchronous changes between trophic
 levels over time (i.e., trophic community asynchrony) are expected to
 increase trophic mismatch and alter trophic interactions, which may
 consequently alter ecosystem stability. However, previous studies have
 often highlighted the stabilising mechanism of population asynchrony
 within a single trophic level, while rarely examining the mechanism of
 trophic community asynchrony between consumers and their food resources.
 2.  In this study, we analysed the effects of population
 asynchrony within and between trophic levels on community stability under
 the disturbances of climate warming, fishery decline, and
 de-eutrophication, based on an 18-year monthly monitoring dataset of 137
 phytoplankton and 91 zooplankton in a subtropical lake. 3.  Our
 results showed that species diversity promoted community stability mainly
 by increasing population asynchrony both for phytoplankton and
 zooplankton. Trophic community asynchrony had a significant negative
 effect on zooplankton community stability rather than that of
 phytoplankton, which supports the match-mismatch hypothesis that trophic
 mismatch has negative effects on consumers. Furthermore, the results of
 the structural equation models showed that warming and top-down effects
 may simultaneously alter community stability through population dynamics
 processes within and between trophic levels, whereas nutrients act on
 community stability mainly through the processes within trophic levels.
 Moreover, we found that rising water temperature decreased trophic
 community asynchrony, which may challenge the prevailing idea that climate
 warming increases the trophic mismatch between primary producers and
 consumers. 4.  Overall, our study provides the first evidence
 that population and trophic community asynchrony have contrasting effects
 on consumer community stability, which offers a valuable insight for
 addressing global environmental change.
description: <strong>Study sites</strong> Lake
 Donghu (30°31′–30°36′ N, 114°21′–114°28′ E) is a subtropical shallow lake
 in the Yangtze River basin in Wuhan, Hubei province, China. Lake Donghu
 contains more than 10 connected sub-lakes, with a total surface area of
 approximately 33 km<sup>2</sup> and a catchment area of
 approximately 187 km<sup>2</sup>. The mean depth of Lake
 Donghu is 2.21 m. <strong>Data
 obtained</strong> An 18-year monthly dataset for
 Lake Donghu from 2003 to 2020 was gathered from the Donghu Experimental
 Station, which belongs to the framework of the Chinese Ecosystem Research
 Network (CERN). Lake Guozhenghu (11.37 km<sup>2</sup>) and
 Lake Tanglinhu (5.78 km<sup>2</sup>) are the first and second
 largest sub-lakes of Lake Donghu. Stations I and II are located in the
 coastal and pelagic zones of Lake Guozhenghu, respectively, and Station
 III is located in the pelagic zone of Lake Tanglinhu. Monthly surveys (in
 the order of Station III, Station II, and Station I) were conducted on
 sunny days on approximately the 15<sup>th</sup> to reduce the
 potential impacts of the weather and departed from the Donghu Experimental
 Station at 8:30 every morning. In this study, the
 abiotic indicators monitored were water temperature (℃), the concentration
 of total nitrogen (TN, mg/L), and total phosphorus (TP, mg/L), while the
 biotic indicators were the biomass of phytoplankton (mg/L, covering
 Bacillariophyta, Chlorophyta, Chrysophyta, Cryptophyta, Cyanophyta,
 Euglenophyta, Pyrrophyta, and Xanthophyta), zooplankton (mg/L, covering
 Cladoceran, Copepod, and Rotifer), and fish yield (kg/ha). Mixed water
 samples were collected 0.5 m below the lake surface and 0.5 m above the
 lake bottom by using a 5 L Schindler sampler for subsequent hydrochemical
 parameter analysis and plankton identification. A 10 L mixed water sample
 was filtered through a 64 μm plankton net into a small square bottle, and
 4% formalin reagent was immediately added to fix the crustacean
 zooplankton (i.e., Cladoceran and Copepod), while a 1 L mixed water
 samples were preserved with 1% Lugol’s iodine solution and concentrated to
 50 mL after standing for 48 hours to analyse phytoplankton and rotifers.
 Although zooplankton are considered lower organisms and receive less
 attention from the animal ethics committees, we strive to minimize
 disturbance to their habitats during the sampling process, in addition to
 using standard methods. The water temperature was
 recorded immediately. The TN and TP concentrations were determined
 according to standard methods [1]. The identification and biomass
 measurements of phytoplankton and zooplankton mainly referred to relevant
 professional books [1-6]. Both phytoplankton and zooplankton were
 identified as the smallest taxon (species or genera). For crustacean
 zooplankton samples, all individuals were counted at 40× magnification.
 The phytoplankton and rotifer samples were measured and counted under 400×
 magnifications with 0.1 mL and 100× magnifications with 1 mL after mixing,
 respectively. Given the changes in plankton nomenclature, we unified the
 species and genera of the plankton dataset based on information from
 relevant professional books [1-6] and consultations with other
 professionals.<strong> </strong>Between 2003 and 2020, 137
 phytoplankton and 91 zooplankton species were identified at all three
 stations. The fish yield, mainly consisting of planktivorous fish
 (<em>Hypophthalmichthys molitrix</em> and
 <em>Aristichthys nobilis</em>), was obtained from the Fishery
 Management Committee of Lake Donghu. 
 <strong>Estimation of diversity, stability, and
 asynchrony</strong> Based on the 18-year monthly
 monitoring biomass dataset, diversity, stability, and asynchrony indices
 were calculated with a one-year (12 continuous monitoring months) moving
 window, sliding every six months [7,8]. Here, we concurrently focused on
 four diversity indices: Simpson diversity
 (Simpson,1-∑<em>p<sub>i<sup>2</sup></sub></em>), <em>p<sub>i</sub></em>  is the proportional abundance of species <em>i</em> in the community), species richness (Richness, <em>S</em>, the number of species observed per month at each station), Shannon diversity (Shannon, -∑<em>p<sub>i </sub></em>ln(<em>p<sub>i</sub>)</em>), and Pielou’s evenness index (Evenness,-∑<em>p<sub>i </sub></em>ln(<em>p<sub>i</sub></em>)/ln(<em>S</em>)). The average of each diversity index within each window at every station was used to determine species diversity. Temporal stability and asynchrony at the population and community levels were used to quantify and explore the seasonal dynamic characteristics of plankton biomass. Temporal stability, encompassing population stability and community stability, characterises the capacity of ecosystems to maintain functioning in a fluctuating environment. Temporal asynchrony includes population asynchrony and trophic community asynchrony, the former characterises the inconsistency of variations among populations within a trophic level, and the latter describes the strength of the temporal coupling relationship between adjacent trophic levels. In this study, population stability was defined as the weighted average of species stability within a community, and was calculated as follows: Population stability = ∑<em><sup>N</sup></em><sub><em>i </em>= 1 </sub><em>m<sub>i</sub></em>/<em>m<sub>c</sub></em> * <em>μ<sub>i</sub></em>/<em>σ<sub>i</sub></em>,  Where <em>m<sub>i</sub></em> represents the total biomass of species <em>i</em> and <em>m<sub>c</sub></em>  represents the total community biomass, while  <em>μ<sub>i</sub></em> and <em>σ<sub>i</sub></em>  denote the mean and standard deviation of the biomass of species <em>i</em> in each plankton community, respectively, and <em>N</em> is the number of species in each plankton community throughout the year [9-10]. Community stability was weighed as follows: Community stability = <em>μ<sub>T</sub></em>/<em>σ<sub>T </sub></em>,  where  <em>μ<sub>T</sub></em> and <em>σ<sub>T</sub></em>  represent the mean and standard deviation of the biomass of each plankton community, respectively [9]. Population asynchrony was measured using: Population asynchrony = 1 - <em>σ<sub>T</sub></em><sup>2</sup>/(∑<em><sup>N</sup></em><sub><em>i </em>= 1 </sub><em>σ<sub>i</sub></em>)<sup>2 </sup>,                                 ,  where <em>σ<sub>T<sup>2</sup></sub></em>  is the temporal variance of the biomass of each plankton community and  <em>σ<sub>i</sub></em> is the standard deviation of the biomass of species <em>i</em> in each plankton community with <em>N</em> species [11]. Combined the calculation method of population asynchrony [11], trophic community asynchrony was quantified as: Trophic community asynchrony = 1 -  <em>σ<sub>t</sub></em><sup>2</sup>/(<em>σ<sub>p</sub></em> + <em>σ<sub>z</sub></em>)<sup>2</sup>, where <em>σ<sub>t</sub></em> is the temporal variance of the total biomass of phytoplankton and zooplankton communities, and <em>σ<sub>p</sub></em>  and <em>σ<sub>z</sub></em>  are the standard deviation of phytoplankton community and zooplankton community biomass, respectively. References [1]     Huang, X., Chen, W., &　Cai, Q. (1999). Survey, observation, and analysis of lake ecology. Standard methods for observation and analysis in Chinese Ecosystem Research Network, Series V. [2]     Hu, H., & Wei, Y. (2006). The freshwater algae of China: systematics, taxonomy and ecology. [3]     Wang, Y. (2020). A Pictorial Guide to Common Aquatic Organisms in Chinese River Basins. [4]     Chiang, S.C., & Du, N.S. (1979). Fauna sinica, crustacea, freshwater cladocera. [5]     Shen, J., Tai, A., Zhang, C., Li, Z., Song, D., & Chen, G. (1979). Fauna sinica, crustacea, freshwater copepoda. [6]     Wang, J. (1961). Freshwater rotifer fauna in China. [7]     Pomati, F., Matthews, B., Jokela, J., Schildknecht, A., & Ibelings, B. W. (2012). Effects of re-oligotrophication and climate warming on plankton richness and community stability in a deep mesotrophic lake. <em>Oikos</em>, <em>121(8)</em>, 1317-1327. https://doi.org/10.1111/j.1600-0706.2011.20055.x [8]     Zhao, Q., Van den Brink, P. J., Xu, C., Wang, S., Clark, A. T., Karakoc, C., Sugihara, G., Widdicombe, C. E., Atkinson, A., Matsuzaki, S. S., Shinohara, R., He, S., Wang, Y. X. G., & De Laender, F. (2023). Relationships of temperature and biodiversity with stability of natural aquatic food webs. <em>Nature Communications</em>, <em>14(1)</em>, 3507. https://doi.org/10.1038/s41467-023-38977-6 [9]     Lehman, C. L., & Tilman, D. (2000). Biodiversity, stability, and productivity in competitive communities. <em>The American Naturalist</em>, <em>156(5)</em>, 534-552. https://doi.org/10.1086/303402 [10]   Thibaut L. M., & Connolly S. R. (2013). Understanding diversity-stability relationships: towards a unified model of portfolio effects. <em>Ecology Letters</em>, <em>16(2)</em>, 140-150. https://doi.org/10.1111/ele.12019 [11]   Loreau, M., & de Mazancourt, C. (2008). Species synchrony and its drivers: neutral and nonneutral community dynamics in fluctuating environments. <em>The American Naturalist</em>, <em>172(2)</em>, E48-E66. https://doi.org/10.1086/589746
description: # Population asynchrony within and between trophic levels have contrasting
 effects on consumer community stability in a subtropical lake
 [https://doi.org/10.5061/dryad.w3r228118](https://doi.org/10.5061/dryad.w3r228118) ## Description of the data and file structure We have submitted our raw data (**the_data_used_in_the_manuscript.xlsx**). **the_data_used_in_the_manuscript** Station: Name of stations in the Lake Donghu during investigation, including Station I, Station II, and Station III. Start_year&month: the start year&month of the one-year the moving window. End_year&month: the end year&month of the one-year the moving window. Water_temperature: the average water temperature (℃) in the moving window. Fish_yield: the average fish yield (kg/ha) in the moving window. Total_nitrogen: the average concentration of total nitrogen (TN, mg/L) in the moving window. Total_phosphorus: the average concentration of total phosphorus (TP, mg/L) in the moving window. Phytoplankton_population_stability: Phytoplankton population stability in the moving window. Phytoplankton_population_asynchrony: Phytoplankton population asynchrony  in the moving window. Phytoplankton_community_stability: Phytoplankton community stability in the moving window. Zooplankton_population_stability:Zooplankton population stability in the moving window. Zooplankton_population_asynchrony: Zooplankton population asynchrony  in the moving window. Zooplankton_community_stability: Zooplankton community stability in the moving window. Trophic_community_asynchrony: Trophic community asynchrony  in the moving window. Phytoplankton_Simpson: Phytoplankton Simpson diversity (monthly average phytoplankton Simpson diversity index at each station in the moving window, range from 0.54 to 0.84). Phytoplankton_Evenness: Phytoplankton Pielou’s evenness (monthly average phytoplankton Pielou’s evenness index at each station in the moving window, range from 0.46 to 0.73). Phytoplankton_Shannon: Phytoplankton Shannon diversity (monthly average phytoplankton Shannon diversity index at each station in the moving window, range from 1.29 to 2.29). Phytoplankton_Richness: Phytoplankton richness (monthly average number of phytoplankton species observed at each station in the moving window, range from 12.91 to 34.17). Zooplankton_Simpson:Zooplankton Simpson diversity (monthly average zooplankton Simpson diversity index at each station in the moving window, range from 0.37 to 0.77). Zooplankton_Evenness: Zooplankton Pielou’s evenness (monthly average zooplankton Pielou’s evenness index at each station in the moving window, range from 0.42 to 0.77). Zooplankton_Shannon: Zooplankton Shannon diversity (monthly average phytoplankton Shannon diversity index at each station in the moving window, range from 0.79 to 1.77). Zooplankton_Richness: Zooplankton richness (monthly average number of zooplankton species observed at each station in the moving window, range 5.83~12.92). For more detailed information on  the measurements and definitions of species diversity (i.e., Simpson, Evenness, Shannon, and Richness), stability (i.e., population stability and community stability), and asynchrony (i.e., population asynchrony and trophic community asynchrony) mentioned above, please refer to the **Methods** section (i.e., **Estimation of diversity, stability, and asynchrony**). ### Files and variables #### File: the\_data\_used\_in\_the\_manuscript.xlsx