Warming, nitrogen deposition and provenance shift above-belowground insect interactions and host compensatory growth
Data files
Sep 13, 2024 version files 153.85 KB
-
README.md
7.11 KB
-
Zhou_He_Dataset.zip
146.74 KB
Abstract
Above-belowground insect herbivore interactions and plant compensatory growth are crucial for reshaping the fitness of invasive plants, and it is likely that climate warming, nitrogen (N) deposition, and plant provenance influence this interaction and growth in a complex way. We performed an experiment with Solidago canadensis from home and introduced ranges, leaf-chewing Spodoptera litura, and root-feeding Protaetia brevitarsis under climate warming and N deposition, and addressed how these abiotic stressors and plant provenance jointly shaped the reciprocal effects between S. litura and P. brevitarsis and the compensatory growth of S. canadensis after herbivory. Under ambient conditions, S. litura and P. brevitarsis inhibited each other on the basis of growth; warming, N addition or warming plus N addition shifted or even reversed this competition depending on provenance. While the survival-based above-belowground interactions differed from growth-based ones, warming or warming plus N addition also shifted or even reversed the neutralism or amensalism detected under ambient conditions depending on provenance. Solidago canadensis from its home range was more tolerant of herbivory than from its introduced range under ambient conditions; warming, N addition or warming plus N addition decreased the plant compensatory growth of native S. canadensis, but increased that of invasive S. canadensis relative to ambient conditions. These findings suggest that climate warming and N deposition could enhance positive above-belowground insect interactions, increasing insect pressures on S. canadensis, and that plant provenance might be important in mediating climate change effects on insect interactions and host compensatory growth under plant invasions.
https://doi.org/10.5061/dryad.fttdz092r
Description of the data and file structure
Files and variables
File: Zhou___He_Dataset.rar
Description: Note that there were codes in this dataset:
l T0: unwarming
l T1: warming
l N0: no N addition
l N1: N addition
l W: warming
l N: N deposition
l LHO: leaf herbivory only
l RHO: root herbivory only
l LRH: leaf and root herbivory.
Metadata for datasheet_insect relative growth rate
column entry value unit explanation
A provenance categorical populations from North America or China
B warming categorical T0 unwarming,T1 warming
C nitrogen categorical N0 no nitrogen addition, N1 nitrogen addition
D environment categorical four combinations consisting of warming and nitrogen, W warming, N N deposition
E feeding categorical LHO leaf herbivory only, RHO root herbivory only, LRH leaf and root herbivory
F herbivore categorical leaf insect, root insect
G population categorical different populations
H replication numerical replicate
I relative growth rate numerical mg g-1 d-1 biomass gain per initial biomass per unit time
Metadata for datasheet_insect survival rate
column entry value unit explanation
A provenance categorical populations from North America or China
B warming categorical T0 unwarming,T1 warming
C nitrogen categorical N0 no nitrogen addition, N1 nitrogen addition
D environment categorical four combinations consisting of warming and nitrogen, W warming, N N deposition
E population categorical different populations
F treatment categorical LHO leaf herbivory only, RHO root herbivory only, LRH leaf and root herbivory
G herbivore categorical leaf insect, root insect
H replication numerical replicate
I survival rate numerical % final larvae/initial larvae * 100%
Metadata for datasheet_plant biomass
column value unit explanation
A provenance categorical populations from North America or China
B warming categorical T0 unwarming,T1 warming
C nitrogen categorical N0 no nitrogen addition, N1 nitrogen addition
D environment categorical four combinations consisting of warming and nitrogen, W warming, N N deposition
E feeding categorical control, LHO leaf herbivory only, RHO root herbivory only, LRH leaf and root herbivory
F herbivore categorical control, insect
G population categorical different populations
H replication numerical
I shoot biomass numerical g oven-dried mass
J root biomass numerical g oven-dried mass
K total biomass numerical g oven-dried mass
File: R_codes.R
Description: Note that there were codes in this software :
The codes contained in the ‘R_codes.R’ file was utilized for analyzing the experimental data. The analysis results were consistent with the findings presented in the tables of the manuscript. The codes include six main sections of analysis: (1) Relative growth rate of leaf-feeding insects; (2) Relative growth rate of root-feeding insects; (3) Survival rate of leaf-feeding insects; (4) Survival rate of root-feeding insects; (5) Shoot biomass, root biomass, and whole-plant biomass; and (6) Differences in shoot, root, and whole-plant biomass between the control and each feeding treatment for both North America and China.
The package “MuMIn” was used for model selection, the packages “lme4” and “car” were mainly used for linear mixed-effects model analysis, and the package “multcomp” was employed for post-hoc multiple comparisons. In the “R_codes.R”, based on the “Zhou_He_Dataset”, we applied linear mixed-effects models (i.e., four-way analysis of variance (ANOVA)), treating plant populations as a random factor to test the fixed effects of warming, nitrogen addition, provenance, feeding, and their interactions on the relative growth rate of leaf-feeding or root-feeding insects. We used four-way ANOVA to test the fixed effects of warming, N addition, provenance and feeding, and their interaction on the survival rate of leaf insect or root insect. We used linear mixed-effect models with plant populations as a random factor to test the fixed effects of warming, N addition, provenance and feeding, and their interaction effects on the biomass of S. canadensis shoots, roots, and whole plants. For each plant provenance, the differences in shoot, root, and whole-plant biomass among four feeding modes under a given environment were tested using the “TukeyHSD function”.
Fixed factors: (1) provenance: populations from North America or China; (2) warming: unwarming,warming; (3) nitrogen:N0 no nitrogen addition, N1 nitrogen addition; (4)feeding: control, LHO leaf herbivory only, RHO root herbivory only, LRH leaf and root herbivory
Random factor: population categorical different populations
Code/software
All analyses were performed using the package “lme4” (Bates et al., 2015) and the package “multcomp” (Hothorn et al., 2008) in R 4.0.2 (R Core Team, 2020). The analysis codes were available in a file titled ‘R_codes.R’.
1. Relative growth rate of leaf insect:
library(lme4)
library(car)
library(multcomp)
library(MuMIn)
data1<-read.table(“Zhou_He_Ecology2024_insect relative growth rate_leaf insect.csv”,header=TRUE,sep=”,”)
data1
shapiro.test(data1$Relative.growth.rate)
R9<-log(data1$Relative.growth.rate+100)
shapiro.test(R9)
YEWR_result<-lmer(R9~ProvenanceWarmingNitrogen*Feeding+(1 | Population),data=data1) |
YEWR_result
summary(YEWR_result)
Anova(YEWR_result)
r.squaredGLMM(YEWR_result)
2.Relative growth rate of root insect:
data2<-read.table(“Zhou_He_Ecology2024_insect relative growth rate_root insect.csv”,header=TRUE,sep=”,”)
data2
shapiro.test(data2$Relative.growth.rate)
YEWR_result2<-lmer(Relative.growth.rate~ProvenanceWarmingNitrogen*Feeding+(1 | Population),data=data2) |
YEWR_result2
summary(YEWR_result2)
Anova(YEWR_result2)
r.squaredGLMM(YEWR_result2)
3.Survival rate of leaf insect:
data3<-read.table(“Zhou_He_Ecology2024_insect survival rate_leaf insect.csv”,header=TRUE,sep=”,”)
data3
S1_result<-aov(Survival.rate~ProvenanceWarmingNitrogen*Treatment,data=data3)
summary(S1_result)
4.Survival rate of root insect:
data4<-read.table(“Zhou_He_Ecology2024_insect survival rate_root insect.csv”,header=TRUE,sep=”,”)
data4
S2_result<-aov(Survival.rate~ProvenanceWarmingNitrogen*Treatment,data=data4)
summary(S2_result)
5.Shoot biomass, root biomass, whole-plant biomass
data5<-read.table(“Zhou_He_Ecology2024_plant biomass.csv”,header=TRUE,sep=”,”)
data5
SB_result<-lmer(Shoot.biomass~ProvenanceWarmingNitrogen*Feeding+(1 | Population),data=data5) |
SB_result
summary(SB_result)
Anova(SB_result)
r.squaredGLMM(SB_result)
TB_result<-lmer(Total.biomass~ProvenanceWarmingNitrogen*Feeding+(1 | Population),data=data5) |
TB_result
summary(TB_result)
Anova(TB_result)
r.squaredGLMM(TB_result)
A study platform (i.e., a long-term experiment) was established at the Chengdu field site (30.67ºN, 104.06ºE) in June 2012. The purpose of this experiment was to provide identical climate scenarios and seeds for subsequent experiments and to minimize maternal effects. The study site belongs to a subtropical climate, where the mean annual precipitation is 918 mm and the mean annual temperature is 18.6 °C, and the soil is a ferralsol (Peng et al., 2019). The long-term experiment involved warming, N addition, and plant provenances, each with two levels. Experimental warming was achieved by heating with MSR-2420 infrared radiators, and the heater was suspended 1.5–2.0 m above the soil surface, roughly increasing air temperatures by 2 °C (Peng et al., 2019). Nitrogen enhancement was achieved by adding ammonium nitrate (NH4NO3) on the soil surface: adding a pulse of 1 g N m–2 as an aqueous ammonium nitrate solution on four occasions per year. Plant seeds were collected from the native and introduced ranges. A detailed description regarding the long-term experimental design has been given previously (Peng et al., 2019; Zhou and He, 2022).
Study species
Solidago canadensis L. (Asteraceae) is native to North America and an invader worldwide (Weber, 2001). This species has invaded several provinces in southeastern China, and is expanding rapidly (Peng et al., 2019). We selected two provenances of S. canadensis: one from its home range (i.e., Montana, USA) and the other from its introduced range (i.e., Zhejiang, China). We collected seeds from five populations in North America and China in 2011. We also selected Spodoptera litura (Fabricius) (Lepidoptera: Noctuidae) as a leaf-feeding insect (hereafter leaf insect) because it is a generalist herbivore and its larvae feed on plant leaves (Zhang et al., 2021), and Protaetia brevitarsis (Coleoptera) (Scarabaeidae: Cetoniinae) as a root-feeding insect (hereafter root insect) because it is a generalist herbivore and its larvae feed on plant roots (Yang et al., 2020; Wang et al., 2022).
Insect feeding experiment
To test the effects of climate warming, N deposition, and plant provenance on the bi-directional interactions between above- and belowground insect herbivores and host-plant compensatory growth, we conducted an experiment at the Chengdu field site (30.67ºN, 104.06ºE) in May–November 2021. This experiment involved four factors: plant provenance, temperature, N, and feeding modes; the first three factors had two levels and the last one had four levels, thereby yielding 32 combinations (2 provenances × 2 temperatures × 2 N levels × 4 feeding modes).
We first randomly collected seeds from three S. canadensis populations per combination in the long-term experiment (see above) in December 2020. Next, we cultivated S. canadensis seedlings in May 2021 in a greenhouse, in which the air temperature and relative humidity ranged from 15–25 °C and 60–80%. We collected the same local topsoil as the long-term experiment, and then sifted it free from rocks. A mixture of local topsoil and sand (1:1 volume) was filled into plastic trays (42 cm length × 42 cm width × 5 cm depth). The seeds were planted in the trays, which were placed on benches in the greenhouse and watered as required. Three similar-sized seedlings were transplanted into 0.5-L pots filled with a mixture of local topsoil and sand (1:1 volume), and exposed to each of the eight combinations consisting of warming, N addition, and plant provenance in June 2021. It should be noted that all seedlings were subject to the same environments as maternal plants. For example, the seedlings were grown under warming if their maternal plants were previously exposed to warming. In addition, the warming and N treatments were identical between this experiment and the long-term experiment. All seedlings per pot had grown for five months before insect herbivory to provide enough leaf food for insects, and were thinned to only one similar-sized seedling among pots prior to insect feeding.
We used four different herbivory treatments consisting of control (no herbivory), leaf herbivory only (LHO), root herbivory only (RHO), and leaf and root herbivory (LRH). Each herbivory was replicated 10 times, and there were 960 pots (8 maternal combinations × 4 feeding modes × 3 populations per combination × 10 replicates). Larvae of S. litura and P. brevitarsis were obtained from the Henan Jiyuan Keyun Company, and they arrived at the third instar on diet trays. For leaf herbivory only, a S. litura larva was weighed and placed on the leaves grown under eight combinations; for root herbivory only, a P. brevitarsis larva was weighed and placed on the roots grown under eight combinations; for leaf and root herbivory, a S. litura larva and a P. brevitarsis larva were weighed and simultaneously placed on the leaves and roots grown under eight combinations. Each pot was covered with an insect net to prevent insects from escaping and external interference. The insect feeding duration lasted for 14 days, in which S. litura survival was observed every day and P. brevitarsis survival was observed at the end of this experiment.
Here, we focused on the relative growth rate and survival rate of insects. At the end of this experiment, we recorded the number of surviving leaf and/or root insects, and weighed them. The relative growth rate was calculated as larval mass gain per initial mass per unit time (mg g–1 d–1), and the survival rate was calculated as follows: the final larvae / the initial larvae feeding on a given host-plant population × 100%. Ten days after ending the insect herbivory, we harvested all plants, separated them into shoots and roots, oven-dried them at 65 °C for 48 h, and measured their biomass. The whole-plant biomass (g) was defined as the sum of shoot dry biomass and root dry biomass. The biomass of shoots, roots, and whole plants at the end of the experiment were selected to gauge their compensatory potential after insect herbivory damage.
Data analysis
Performance of above- and belowground insect herbivores
Here, insect performance parameters included relative growth and survival rates. Before data analysis, we first tested whether our data met the assumptions of normality and homoscedasticity. Based on the residuals from the models, the Gaussian family was appropriate for our data. The data of relative growth were log-transformed to meet the assumptions of normality. We then performed linear mixed-effect models (i.e., four-way analysis of variance (ANOVA)) with plant populations as a random factor to test the fixed effects of warming, N addition, provenance and feeding, and their interaction effects on the relative growth rate of S. litura or P. brevitarsis. We used four-way ANOVA to test the fixed effects of warming, N addition, provenance and feeding, and their interaction on the survival rate of S. litura or P. brevitarsis. Please note that there were only two levels for feeding in these analyses: leaf herbivory only and leaf and root herbivory for S. litura, and root herbivory only and leaf and root herbivory for P. brevitarsis. Importantly, these analyses revealed unidirectional effects between above- and belowground insects.
To unravel the bi-directional effects between above- and belowground insects, we calculated the difference between the treatment and control groups as the response variable, and treated leaf and root herbivory as the treatment group and leaf herbivory only or root herbivory only as the control group when quantifying the reciprocal effects of above- and belowground insects. Accordingly, we could analyze the type and outcome of interactions between above- and belowground insects. Here, we defined the effect of the direction from the initial insect herbivore to the subsequent insect herbivore as a plus (+) when the presence of the initial herbivore allows the subsequent herbivore to perform better compared to the absence of the effector herbivore, the effect as a minus (–) when the presence of the initial herbivore allows the subsequent herbivore to perform worse compared to the absence of the effector herbivore, and the effect as a neutral (0) when the presence of the initial herbivore has no effect on the subsequent herbivore. For a specific environment (ambient, warming, N addition, and warming plus N addition), the differences in relative growth and survival rates among feeding modes were tested using the “TukeyHSD function”. All analyses were performed using the package “lme4” (Bates et al., 2015) and the package “multcomp” (Hothorn et al., 2008) in R 4.0.2 (R Core Team, 2020).
Compensatory growth of the host plant S. canadensis after insect herbivore damage
To address compensatory growth, we selected the ultimate biomass as a response variable when analyzing data. We used linear mixed-effect models (i.e., four-way ANOVA) with plant populations as a random factor to test the fixed effects of warming, N addition, provenance and feeding, and their interaction effects on the biomass of S. canadensis shoots, roots, and whole plants. For each plant provenance, the differences in shoot, root, and whole-plant biomass among four feeding modes under a given environment were tested using the “TukeyHSD function”. We also considered leaf herbivory only, root herbivory only, and leaf and root herbivory as a whole. In this case, we used linear mixed-effect models, where plant populations and three feeding modes nested in feeding were treated as random factors, to test the fixed effects of warming, N addition, provenance and feeding, and their interaction effects on the shoot, root, and whole-plant biomass of S. canadensis. For a specific environment, the differences in shoot, root, and whole-plant biomass between the control and each feeding were tested using the “TukeyHSD function”. All analyses were performed using the package “lme4” (Bates et al., 2015) and the package “multcomp” (Hothorn et al., 2008) in R 4.0.2 (R Core Team, 2020).