DOI: 10.5061/dryad.kh18932gw
title: Tree species richness suppresses red imported fire ant invasion in a subtropical plantation forest

description: The ecological resistance to the invasion of alien species has been
 extensively researched at the within-trophic level; however, the effect of
 cross-trophic interactions remains largely unknown. The red imported fire
 ant (RIFA, Solenopsis invicta) is a globally invasive species, and a
 cross-trophic interaction study between RIFAs and plants may provide a
 more comprehensive understanding and management of its invasion. We
 hypothesized that the diversity of trees, which are the primary producers
 supporting terrestrial ecosystems, could suppress the invasion of
 omnivorous RIFAs by regulating food resources (e.g., plants and
 arthropods) and the microenvironment (e.g., soil microclimate) as well as
 enhancing competition with other carnivorous ants. To test this
 hypothesis, we investigated RIFA abundance and mound numbers across tree
 species richness gradients in a subtropical plantation forest. Using
 structural equation models, we discovered that tree species richness had
 contrasting effects on RIFA abundance and mound numbers. RIFA abundance
 directly decreased with higher tree species richness because of the
 dilution effect (i.e., lower abundance of preferred tree species). In
 contrast, RIFA mound numbers indirectly increased with tree species
 richness via an increase in arthropod abundance (excluding ants) (i.e.,
 more ample food resources for RIFA). Moreover, warmer soil temperatures
 decreased RIFA abundance, whereas other carnivorous ant species richness
 and abundance negatively affected RIFA abundance and mound
 numbers.  Synthesis and applications: Our findings demonstrate
 that the ecological resistance to RIFA invasion is influenced by tree
 species richness in a complex manner; specifically, the relative strengths
 of the effects of tree species characteristics, native competitors, and
 environmental conditions are likely to impact the power of ecological
 resistance. This highlights the importance of cross-trophic interactions
 underlying the resistance of complex ecosystems to alien species invasion;
 therefore, maintaining diverse tree communities in controlled systems
 (e.g., suburban and urban green spaces) should be viewed as a potential
 strategy for controlling RIFA invasion.
description: Dataset Collection For both two datasets, they
 contains the results of filed survey for
 <strong>tree</strong>, <strong>ants</strong> and
 <strong>micro-environment</strong>.
 <strong>1 Study site and RIFA invasion
 status</strong> The biodiversity-ecosystem
 subtropical experimental plantation forest (Guangdong Province, China;
 23°30′ N, 111°49′ E) was established in 2018 (no need for permission for
 fieldwork). The experimental plantation forest was constructed on flat
 ground in an abandoned field (rice paddy prior to 2013), which was
 dominated by herbaceous plant species. The regional climate is
 characterized as a subtropical moist monsoon climate, with an average
 annual temperature of 19.6 °C and monthly average temperatures ranging
 from 10.6 °C (January) to 28.4 °C (July). The average annual precipitation
 is 1,744 mm, approximately 79% of which occurs between April and
 September. The natural regional vegetation is dominated by subtropical
 evergreen broad-leaved forests. The entire experimental
 plantation forest consisted of four tree species richness levels in eight
 blocks (32 x 20 m), serving as replications. A total of 20,480 trees were
 initially planted, and 40 plots were established for each block. Each plot
 was a 4 x 4 m square area, and 64 native tree seedlings were planted, with
 each seedling spaced 0.5 m apart. In each plot, different numbers of tree
 species (1, 2, 4, 8) were planted in equal individual proportions at
 different richness levels. Each block consisted of four tree richness
 levels, each with a varying number of plots. This included mono-species (8
 plots per block), two-species (18 plots per block), four-species (12 plots
 per block), and eight-species (2 plots per block) blocks. The positioning
 of trees within each plot and the number of plots per block followed
 randomized designs. Each tree was tagged with a unique identification
 number. Because the reclamation of this field was
 conducted to establish the experimental plantation forest, all visible
 RIFA mounds were destroyed by deeply churning the soil using farming
 machinery and employing broad irrigation in the study region (RIFA had
 already invaded this region prior to the establishment of our experimental
 plantation forest). Therefore, the progress of RIFA invasion was reset in
 our study region at that time. The perimeter of each study block was
 delineated by a square soil ridge of approximately 1 m in width and about
 1.5 m in height. The entire study experimental plantation forest was
 surrounded by a buffer region. The buffer was a square band with a width
 of approximately 3 m. The northern and western sides consisted of concrete
 pavements, whereas the eastern and southern sides comprised wild weeds and
 shrubs. All these measures mitigated the adverse impacts of surrounding
 farmland on the study experimental plantation forest.
 <strong>2 Tree survey data</strong>
 Annual tree surveys were conducted from 2018 to 2022, and the
 tree height (TH), diameter at breast height (DBH), and status (alive or
 dead) were recorded. Given that some trees died during the survey, we
 utilized the species richness of the remaining living trees from 2022 for
 further analyses. Therefore, the realized tree species richness consisted
 of the following: 1 (69 plots), 2 (137 plots), 3 (11 plots), 4 (85 plots),
 7 (8 plots), and 8 (8 plots). <strong>3 Ant
 survey and specimen collection</strong> The ant
 survey (no requirement for ethical approval) was conducted between July
 2022 and August 2022. First, we checked each plot to record the total
 number of visible RIFA mounds along with their length, width, and height
 to estimate their size from the beginning of July to the middle of
 August:  C<sub>size</sub>=2abcπ/3         
                                        (eqn 1) where
 <em>C<sub>size </sub></em>is the estimated mound
 size while <em>a</em>, <em>b</em>, and
 <em>c</em> are the mound length, width, and height,
 respectively. The observed number of mounds represented the sum of old and
 newly constructed mounds. Each RIFA mound condition was verified by
 puncturing the mound from the top using elongated metal tweezers. If there
 was a substantial amount of workers, estimated to be more than 100,
 dashing out within 10 s, we recorded such a mound as a “RIFA-present
 mound.” If there were no workers or only one or two workers appearing
 slowly, we recorded such a mound as a “RIFA-absent mound.” The majority of
 recorded mounds were “RIFA-absent mounds” (they did not contain RIFA but
 still had complete structure); therefore, the number of mounds in our
 study was considered an independent index of RIFA invasion in relation to
 RIFA abundance. The absence of RIFA from almost all mounds can be
 attributed to a flood that occurred during the first part of the year
 (2022). During this event, flood water surged into the study region and
 inundated the soil of the entire area. Following the
 mound survey, ant specimen collection was initiated. Because the size of
 each plot was small, a baited pitfall trap was placed in the center of
 each plot to collect ants and other arthropods. However, plots located at
 the block margin were excluded to eliminate any boundary effects. The trap
 was set up once in the middle of August and left for 3 days, ensuring that
 there was no rainfall following the mound survey. The pitfall trap
 consisted of a piece of hot dog as bait and a 75% ethanol solution as the
 fixation fluid. To test our hypothesis regarding food resources and to
 facilitate the collection of other arthropods, we modified our pitfall
 trap by adding three larger holes (10-mm diameter) on the front and back
 sides. It is noted that because a hot dog was used as bait, we probably
 collected more carnivorous ants. The aim of the ant investigation was to
 estimate the competitor effect; therefore, the hot dog bait was suitable
 for our study. The term “other arthropods” hereafter mainly refers to
 carnivorous arthropods. All collected specimens were
 preserved in a 75% ethanol solution, and we counted the total number of
 individuals per species per trap. Although other arthropods were
 identified into morpho-species, we identified ants at the species level in
 two steps: 1) We conducted a preliminary identification of each specimen
 by comparing it directly with descriptions and illustrations from AntWeb
 (www.antweb.org) and Ants-China Web (www.ants-china.com); 2) We used the
 TIANamp Genomic DNA Kit (TIANGEN BIOTECH (BEIJING) CO., LTD) to extract
 fragmented COI (primers: LCO1490 and HCO2198) from at least three
 specimens per species. We then conducted a search using the Basic Local
 Alignment Search Tool (BLAST) in the National Center of Biotechnology
 Information (NCBI) to select and compare results with the highest maximum
 score obtained from morphological identification. When a mismatch between
 morphological and molecular identification was observed, we reviewed the
 data and opted for the morphological identification results.
 Phylogenetic diversity (PD) was calculated for ants, which showed
 a high correlation with species richness. Consequently, PD was excluded
 from subsequent analyses (Supporting Information, Section 2).
 <strong>4 Soil microclimate survey</strong>
 RIFAs are ectothermic soil fauna that are highly sensitive to
 moisture changes; therefore, soil microclimate indexes can serve as
 reliable proxies for predicting their activities. We randomly selected
 five points in each plot and used a portable soil sensor (Generation I,
 PURUISEN company, China) to measure soil temperature and moisture at a
 5-cm depth on days without rain during the RIFA mound survey (completed on
 the day before the pitfall sampling). Average values per plot were used
 for further analyses. It typically took 1 day (half of measurements in the
 morning and half in the afternoon) to measure the soil microclimate for
 each block. Therefore, a total of 8 days were spent to complete the
 measurements for all eight blocks. However, the slight change in soil
 conditions between these days likely rendered the measurements on
 different days incomparable. In addition, slight differences in soil
 conditions probably existed between the morning and afternoon. To address
 the incomparability, we standardized the soil microclimate within each
 block by calculating the Z-scores of temperature and moisture. The
 Z-scores were calculated by dividing the mean values measured during the
 same period (e.g., in the morning or afternoon) by their corresponding
 standard deviations.
description: # Tree species richness suppresses red imported fire ant invasion in a
 subtropical plantation forest —— Ant community and microenvironment: Open
 source data
 [https://doi.org/10.5061/dryad.kh18932gw](https://doi.org/10.5061/dryad.kh18932gw) We have submitted our raw data of ant community (**AntCommunity.csv**) which includes the numbers of different ant species in each plot. The the name of each column was the species name. We also submitted our data for structural equation model building (**Datasets for SEMs.csv**) which includes the values of all variables mentioned in the article. ## Description of the data and file structure ### Files and variables #### File: AntCommunity.csv **Description:**  This dataset includes the numbers of different ant species in each plot. The the name of each column was the species name. ##### Variables * PlotNum: The identifier number of each plot * Solenopsis invicta: Ant species name * Tetramorium bicarinatum : Ant species name * Nylanderia bourbonica: Ant species name * Nylanderia ogasawarensis : Ant species name * Monomorium triviale: Ant species name * Tapinoma melanocephalum: Ant species name * Diacamma rugosum : Ant species name * Pheidole nodus: Ant species name * Pheidole cf. sauteri: Ant species name * Camponotus humilior : Ant species name * Brachyponera chinensis: Ant species name * Pheidole sp.: Ant species name, sp. means uncertain name * Cardiocondyla minutior : Ant species name * Ectomomyrmex javanus: Ant species name * Strumigenys emmae : Ant species name * Polyrhachis dives: Ant species name * TSR: Tree species richness, i.e. the total number of tree species #### File: Datasets\_for\_SEMs.csv **Description:** This dataset includes the values of all variables mentioned in the article, especially for structural equation model building. Soil temperature, moisture and electrical conductivity were Z-transformed to eliminate weather impact. Some variables may not be used in the final analyses of our article. ##### Variables * Num: Plot identifier number in whole dataset * Plot: Plot identifier number in each block * Comb: Tree planting combination type, the number of character represents the number of species. * PSR: Tree species richness, i.e. the total number of tree species * CNASR: Other carnivorous ant species richness * CNAab: Other carnivorous ant abundance * RIFAab: Red important fire ant abundance * RIFAabsent: Individual of red important fire ant present (1) and non-present (0) * MoundN: Red important fire ant mound number * MoundAbsent: Mound of red important fire ant present (1) and non-present (0) * SoilMoisture: Z-transformed soil moisture, the primary unit is percentage (%) * SoilTemperature: Z-transformed soil temperature, the primary unit is Celsius (℃) * EC: Z-transformed soil electrical conductivity, the primary unit is us/cm * MoundAveSize: Red important fire ant mound average size, the unit is cubic centimeter * PlantDensity: The tree density in each plot, i.e. the total number of tree individuals * TreeMortality: The tree mortality rate in each plot, the unit is percentage (%) * OtherInsectsAb: Abundance of other carnivorous arthropods * OtherInsectsSR: Species richness of other carnivorous arthropods * GM: Individual number of *Erythrophleum fordii* * MWS:  Individual number of *Pinus massoniana* * LS: Individual number of *Castanopsis fissa* * MZ: Individual number of *Castanopsis carlesii* * SDY: Individual number of *Elaeocarpus sylvestris* * MH: Individual number of *Schima superba* * TDQ: Individual number of *Ilex rotunda* * XZ:  Individual number of *Cinnamomum camphora* * Pd: The Faith’s phylogenetic diversity of ants in each plot