DOI: 10.5061/dryad.31zcrjdwd
title: Density-driven facilitations increase ecological resilience under eutrophic stress

description: Eutrophication has been observed to decrease the ecological resilience of
 macrophyte-dominated freshwater ecosystems, thereby resulting in more
 vulnerability to external perturbations and easily tipping into an
 algae-dominated state. The stress gradient hypothesis (SGH) posits that
 plants exhibit positive plant-plant interaction (facilitation) in response
 to stress, potentially buffering the detrimental impacts of
 eutrophication. However, few studies attempted to link plant density with
 species-species interactions and ecological resilience in the context of
 eutrophic stress. Here, we investigated how the density of neighbour plant
 species (Potamogeton lucens) affects the change rate of nutrients or Chl a
 (chlorophyll-a) and target plant species (Potamogeton maackianus) along a
 gradient of nutrient levels (oligotrophic, mesotrophic, eutrophic) via a
 42-day mesocosm experiment. Our objective was to corroborate: (1) species
 interactions may shift from competition to facilitation with the increased
 eutrophic stress. (2) High plant density is indispensable to generate
 facilitation and thereby augment ecological resilience under high
 eutrophic stress. Results showed that eutrophic scenarios significantly
 augmented chlorophyll-a concentration and inhibited plant height, number
 of branches and leaves, showing that submerged macrophytes in eutrophic
 states are exposed to stressful conditions. However, the increasing
 density of neighbouring vegetation reduced nutrient and Chl a
 concentrations and enhanced the performance of Potamogeton
 maackianus in eutrophic conditions, but not in mesotrophic and
 oligotrophic conditions. Our results indicated that density-dependent
 facilitation is more prevalent in eutrophic circumstances, and species
 interactions are likely transformed from competition to facilitation with
 increasing nutrient concentrations. Our research demonstrated that plant
 density could alter the relationship between facilitation and competition;
 high plant density is indispensable for the operation of the stress
 gradient hypothesis. Density-dependent facilitation under severe
 conditions could mitigate the adverse influence of eutrophication. With
 freshwater ecosystems progressively subjected to eutrophication,
 harnessing the density-dependent facilitation of submerged macrophytes in
 resilience-driven management is crucial to inhibiting the transition to an
 algae-dominated turbid state, which further broadens our understanding of
 the theory of alternative stable states in shallow lakes.
description: <strong>Experimental design</strong>
 <em>Potamogeton maackianus</em> and
 <em>Potamogeton</em><em> lucens </em>are widely
 distributed around the world and in China (Cao et al., 2017).
 <em>Potamogeton maackianus</em>, erstwhile the predominant
 species in Yangtze shallow lakes (Chambers & Kalff, 1987; Qiu et
 al., 2001), has been significantly suppressed by eutrophication and
 manifests difficulty restoring its population, despite its capacity to
 withstand a broad range of fluctuations in environmental nutrient
 concentrations (Ni, 2001; Fu et al., 2013). Moreover,
 <em>P</em><em>.
 </em><em>lucens</em> is also sensitive to
 eutrophication, showing inhibited growth and expansion (Litav &
 Lehrer, 1978; Uehara et al, 2006). Thus, we opted for <em>P.
 maackianus</em> and
 <em>P.</em><em> </em><em>lucens</em> in our experiment given their sensitivity to eutrophic stress. Our experiment was conducted at the Donghu Ecosystem Experimental Station, Institute of Hydrobiology, Chinese Academy of Sciences (114.36 E, 30.55 N) for 42 days. <em>Potamogeton maackianus</em> and <em>P.</em> <em>lucens</em> were collected from Erhai (100.1902 E, 25.7582 N) in Yunnan Province, China.  Submerged plants with a shorter main axis (such as <em>Potamogeton maackianus</em>) can form a dense mat at the bottom of lakes, and have an advantage in inhibiting sediment re-suspension (Barko & James, 1998; Li et al., 2008). Compared with <em>P. maackianus</em>, <em>P. lucens</em> could tolerate low light to compete with phytoplankton because of its greater height. Thus, the system in which species of different plant heights co-occur may be more likely to exhibit stronger positive interactions. We emulated the methodology of prior research (Le Bagousse-Pinguet et al., 2012) where <em>P. maackianus</em> was<em> </em>selected as the central species and <em>P. lucens </em>was chosen as the neighbour species (n), with the planting layout depicted in Figure 2. Three nutrient levels (oligotrophic, mesotrophic and eutrophic) were established and 3 <em>P. maackianus</em> and 0, 3, 6, 9, 12, or 16 <em>P. lucens</em> were planted in each nutrient level (50 cm × 50cm × 80cm). We set up one control group (n = 0) and five treatment groups (n = 3, 6, 9, 12, 16 respectively) in each nutrient level. For each species, plants with similar height (length of main axis, cm) and number of leaves were chosen, and surplus branches were pruned. Subsequently, plants were transplanted into plastic containers (7 cm in diameter and 10 cm in height) bearing sediment harvested from East Lake of Wuhan using a Peterson sediment harvester. There were three replicates per treatment or control, yielding an aggregate of 18 tanks per nutrient level, with a total of 54 tanks. The entire experiment was draped with cloth to prevent excessive solar radiation from damaging the plants. All plants were thoroughly acclimatized to the aquatic environment for two weeks. After that, based on the evaluation of the possible nutrient thresholds of lakes (Yang et al., 2008; Cheng & Li, 2006; Richardson et al., 2007), the concentrations of total nitrogen and total phosphorus were adjusted by adding NaNO<sub>3</sub> and K<sub>2</sub>HPO<sub>4</sub> (Oligotrophic: + 1 mg L<sup>-1</sup> N, + 0.1 mg L<sup>-1</sup> P; Mesotrophic: + 0.5 mg L<sup>-1</sup> N, + 0.05 mg L<sup>-1</sup> P; Eutrophic: + 0.1 mg L<sup>-1</sup> N, + 0.01 mg L<sup>-1</sup> P). Then, TN and TP (total nitrogen and phosphorus of surface water, mg L<sup>-1</sup>, including the content in particulate matter) in the tank were measured immediately after the addition of nitrogen and phosphorus, while Chl a was measured on two days later, at which juncture the concentrations of TN, TP and Chl a were denoted as the results of the first week. One week later, TN, TP, and Chl a in the water were measured again, at which juncture the concentrations of TN, TP and Chl a were denoted as the results of the second week. Subsequently, all <em>P. maackianus</em> were gently removed from tanks along with their respective cups to measure plant height (cm), number of branches and leaves as the result for the second week of morphological traits. Then, <em>P. maackianus</em> plants were placed back into the tanks. After the sediment settled, the above steps were repeated, and the measured results were recorded as TN, TP, Chl a in the third and fourth weeks, and as morphological traits at the fourth week. During the experiment, nutrients were added twice to achieve a significant nutrient gradient (Figure 3 a, b and Figure S5 a, b). TN, TP and Chl a were measured four times, and morphological traits were measured twice and each replicate was sampled on a different day. Each time, 80 ml of surface raw water was taken to measure TN and TP concentrations in water, and 1L of surface water was filtered through a GFC membrane, and then used to measure Chl a. At the end of the experiment, the central species and the neighbour species were taken out to measure dry weight (g). <strong>Laboratory analysis</strong> Total nitrogen (TN, mg L<sup>-1</sup>) and total phosphorus (TP, mg L<sup>-1</sup>) in the water column were measured by standard methods (Huang et al., 1999). In particular, the water TN and TP were digested with potassium persulfate (Sigma Aldrich, Sigma Aldrich Trading Co., LTD, Shanghai, China) in a sterilized pot (GR85DA, Zealway instrument Inc, Xiamen, China) at 120 ℃ for 30 minutes in advance. In addition, the water (filter 1L per measurement) is first filtered through the Whatman GF/C fiber glass filter (GF/C, Whatman, GE Healthcare UK Limited, Buckinghamshire, UK) and subsequently extracted from the residue on the fiber glass filter with 90% ethanol (GoldWallReagent Co. LTD, Shanghai, China) at 4 ℃ for 24 h, and finally Chl a (µg L<sup>-1</sup>) was determined by spectrophotometer (UV-2550, Shimadzu Instrument Co., LTD, Jiangsu, China). The neighbour species and the central species were dried to a constant mass in an oven (101-1AB, Tianjin Test Instrument Co., LTD, Tianjin, China) at 60 ℃ and the dry weight was weighed (g). <strong>Data analysis</strong> The log-response-ratio (LRR) (Hedges et al., 1999) of nutrient decrease could be used to quantify the rate of change of the treatment (neighbour = 3, 6, 9, 12 and 16) relative to the control group (neighbour = 0) and indirectly reflect the interactions among plants (Le Bagousse-Pinguet et al., 2012), as specified in Eq (1): LRR = log[(T<sub>2</sub>-T<sub>1</sub>)/(C<sub>2</sub>-C<sub>1</sub>)]                                      (1) Where, T<sub>1</sub> and T<sub>2 </sub>are TN, TP and Chl a of the water in the first (third) and second (fourth) measurement results in treatment groups of each nutrient level. C<sub>1</sub> and C<sub>2 </sub>are TN, TP and Chl a of the water in the first (third) and second (fourth) measurement results in control groups respectively. The LRR calculated using TN, TP, and Chl a of the first (third) and second (fourth) weeks is recorded as the LRR of second (fourth) week. Positive interactions triggered by neighbour plants under eutrophic stress increased with the TN, TP, and Chl a rate of change (Le Bagousse-Pinguet et al., 2012). Conversely, if nutrient change in the treatment group was lower than that in the control group, there may be negative plant-plant interactions (competition) in the system. To further explore the interactions between central and neighbour species, especially for morphological traits, we quantified the effects of neighbours on central species using a neighbour-effect intensity index with additive symmetry (NInt<sub>A</sub>, Eq.2), because NInt<sub>A</sub> exhibits additive symmetry, avoiding underestimation of facilitation (Díaz-Sierra et al., 2017; Danet et al., 2024). NInt<sub>A</sub> &lt; 0 indicates competing interactions, and &gt; 0 indicates facilitating interactions. NIntA = 2×[ΔP/(P<sub>-N</sub>+|ΔP|)]                              (2) Where, ΔP is the total neighbour effect (P<sub>+N</sub> - P<sub>-N</sub>). P<sub>-N </sub>is the performance (number of branches, height and number of leaves) of central species without neighbours. P<sub>+N</sub> is the performance of central species with neighbours. Measurements of morphological traits in second and fourth week were used to quantify the effects of neighbouring species on morphological traits of central species (NInt<sub>A</sub>) in the second and the fourth week, respectively.
description: # Density-driven facilitations increase ecological resilience under
 eutrophic stress # Description of the data and file structure The dataset
 contains nutrient level (Eutrophic, mesotrophic and oligotrophic),
 sampling time, environmental variables (TN, TP and Chl a, in
 Data-FWB-P-Jan-24-0013-Nutrient) , morphological traits (height, number of
 branches and leaves, in Data-FWB-P-Jan-24-0013-Trait) of central species
 (Potamogeton maackianus), biomass, density of neighbour species, nutrient
 change rate (LRR) and interactions among plants (NintA). LRR of TN, TP and
 Chla and NIntA of number of branches, height and number of leaves in
 Data-FWB-P-Jan-24-0013-LRR_and_NIntA. NULL in
 Data-FWB-P-Jan-24-0013-LRR_and_NIntA indicates no calculation result. ##
 Column names null in the table indicates that no calculation result is
 obtained. ### In Data-FWB-P-Jan-24-0013-Nutrient: Nutrient: nutrient level
 including eutrophic (Eu), mesotrophic (Me), oligotrophic (Ol). den:
 Density of neighbour species TN: Total nitrogen (mg/L) TP: Total
 phosphorus (mg/L) Chla: Chyllorophy a (μg/L) Time: Sampling time (no unit)
 ### In Data-FWB-P-Jan-24-0013-Trait Nutrient: nutrient level including
 eutrophic (Eu), mesotrophic (Me), oligotrophic (Ol). den: Density of
 neighbour species (individual/tank) Time: Sampling time (no unit) Branch:
 Number of branches (no unit) Height: Length of main axis of plant (cm)
 Leaf: Number of leaves ### In Data-FWB-P-Jan-24-0013-LRR\_and\_NIntA
 Nutrient: nutrient level including eutrophic (Eu), mesotrophic (Me),
 oligotrophic (Ol). den: Density of neighbour species (individual/tank)
 Time: Sampling time (no unit) LRRTN, LRRTP and LRRChla: Log-response-ratio
 of TN, TP and Chla  (no unit) NIntAbranch, NIntAheight and NIntAleaf:
 additive symmetry of number of branch, plant height and number of leaves 
 (no unit)