DOI: 10.5061/dryad.qfttdz0rz
title: Data from: Intercropping generates trait plasticity, which corresponds with year-to-year stability in productivity

description: Environmentally friendly approaches to increasing food production include
 using the positive effects of plant biodiversity, such as in
 intercropping. Functional traits are key drivers of these positive
 effects, in part because variation in functional traits can increase niche
 partitioning. However, we know little about how variation in functional
 traits affects the long-term stability of yield in
 agroecosystems. We conducted a five-year field experiment with
 five different cropping systems; maize/peanut, maize/soybean, and maize,
 peanut and soybean monocultures. We compared the productivity of
 monocultures to intercrops and then compared plasticity in functional
 traits at different rates of nitrogen supply between the cropping
 systems. Intercropping generated plasticity, measured here as the
 inverse of the coefficient of variation, in three functional traits of
 maize (height, stem diameter, ear height), which probably increases
 aboveground spatial niche differentiation, and decreases the intraspecific
 competition of maize. Intercropping also increased the stability
 of grain yield and aboveground biomass. Plasticity in functional traits of
 maize correlated positively with year-to-year temporal stability (CV-1) of
 grain yield and biomass of maize and with the total productivity of the
 agroecosystem. Synthesis and applications. Our study provides evidence of
 the greater productivity and temporal stability of species-diverse
 intercropping systems. Interspecific interaction-induced plasticity
 suggests a unique mechanism for biodiversity effects on ecosystem
 function, which adds to our understanding of fixed, or inherent, variation
 in traits among genotypes or species. Theoretically, our findings provide
 novel insights into how interspecific interactions contribute to ecosystem
 service, especially in yield temporal stability, by increased trait
 plasticity of the dominant crop, maize. The results also had implications
 for applying intercropping in the sustainable management of
 food-production systems with the use of more crop species. Greater
 stability in production has the potential to provide a stable income for
 farmers.
description: This field experiment was arranged as a split-plot design with
 two factors and ran from 2017 to 2021. The factors were four nitrogen (N)
 applications (N0, N1, N2, and N3) and five cropping systems – maize in
 monoculture (<em>Zea mays</em> L. cv. Xian-yu No. 335),
 soybean in monoculture (<em>Glycine max</em> (L.) Merr. cv.
 Ji-yu No. 47), peanut in monoculture (<em>Arachis
 hypogaea</em> L. cv. Bai-sha No. 1016), intercropped maize/soybean,
 and intercropped maize/peanut. N application was the main treatment, and
 cropping system was the sub-plot treatment. Peanut and
 soybean monocultures received N-fertilizer treatments at 0, 40, 80, and
 120 kg N ha<sup>-1</sup> (N0 through N3) each year. Maize
 monocultures received either 0, 180, 240, and 300 kg N
 ha<sup>-1</sup> (N0 through N3) each year. N applications for
 the maize/peanut intercrop were 0, 110, 160, and 210 kg N ha<sup>-1
 </sup>(N0 through N3) each year, the same as in the maize/soybean
 intercrop. One-third of the N was applied as basal fertilizer, and
 two-thirds was divided into two portions applied at the maize stem
 elongation stage and the pre-tasseling stage. N supplied to maize vs.
 legumes differed due to standard crop requirements, but maize in
 monoculture and intercrops received same N additions and legumes in
 monoculture and intercrops received the same N additions. The N level in
 the N2 treatment was based on the recommendation of local farmers, and N1,
 and N3 were chosen to test reasonable increases and decreases in N supply
 relative to N2. The N application rate for maize/peanut and maize/soybean
 was the average of the monocultures. The topdressing fertilizer was only
 for maize, and the amount was 1/2 that of the monoculture because the
 proportions of maize was in intercropping was 0.5 of that in the
 monocultures.. All plots received 52 kg ha<sup>-1</sup> P
 fertilizer as calcium superphosphate and 83 kg ha<sup>-1</sup>
 K fertilizer as potassium sulfate before sowing. Throughout the five-year
 duration of the experiment, no large-scale disease outbreaks were
 observed, and no pesticides were applied. Maize borers were effectively
 managed by releasing <em>Trichogramma</em> wasps, and all
 plots were manually weeded.
description: # Data from: Intercropping generates trait plasticity, which corresponds
 with year-to-year stability in productivity
 [https://doi.org/10.5061/dryad.qfttdz0rz](https://doi.org/10.5061/dryad.qfttdz0rz) ## Description of the data and file structure This field experiment was arranged as a split-plot design with two factors and ran from 2017 to 2021. At maturity, two continuous rows of maize, soybean, and peanut were harvested in 5 m in each row to measure grain yield and biomass. Plant trait data were collected from 2018-2021. ### Files and variables #### File: revision\_data.xlsx **Description:** The data include traits of different crops, their ITV-1 values, the productivity of different crops, and the stability of productivity. ##### Variables N: nitrogen application CS: cropping system H: height (cm) D: basal stem diameter (mm) EH: ear height (cm) EL: ear length (cm) ED: ear diameter (mm) BL: bald length (cm) 1st PH: 1st pod height (cm) PN: pods number SN: seeds number BL: branches number SB：stability of grain yield SBB: stability of biomass Y: grain yield (t ha-1) B: biomass (t ha-1) MONO: monoculture INTER: maize/legume intercropping M/S: maize/soybean intercropping M/P: maize/peanut intercropping M: sole maize S: sole soybean P: sole peanut M/S-M: maize in maize/soybean intercropping M/P-M: maize in maize/peanut intercropping M/S-S: soybean in maize/soybean intercropping M/P-P: peanut in maize/peanut intercropping TM: trait of maize TS: trait of soybean TP: trait of peanut STM: stability of maize STS: stability of soybean STP: stability of peanut ITVM: ITV-1 of maize trait ITVS: ITV-1 of soybean trait ITVP: ITV-1 of peanut trait MS: productivity of maize/soybean intercropping MP: productivity of maize/peanut intercropping Linear-mixed effect models (using the ‘name’ package in R v.4.0.5) were used to test the effects of N application (N) and cropping systems (CS) on functional traits (2018-2021), ITV-1 of functional traits among different individuals (2018-2021), productivity (2017-2021), and the temporal stability of different crops. N and CS were fixed factors, and in the analysis of multi-year data, year was included as a random factor in the model. Once a main effect or interaction between the two factors was found to be significant, a Tukey’s post hoc test was used for pairwise comparisons among treatments. We used a generalized linear model to determine variation in yield and biomass over five years. The regression relationships between stability and nitrogen application, stability of intercropping, and stability of crops were determined in the same way. We took the common logarithms of stability of intercropping and the CV-1 of functional traits and determined the regression relationships between them with a general linear model. We used structural equation models (SEMs) to compare how nitrogen supply vs. intercropping, induced plasticity in functional traits and their effects on stability in grain yield and total productivity. We could not construct a stable SEM that integrated both cropping system and N, and so we constructed separate SEMs for each of these factors. This allowed us to focus explicitly on the effects of intercropping on trait plasticity (evaluated by ITV-1 in our research) and grain yield stability, and to compare the effects of cropping system to N, which is used globally to promote consistent crop production. SEMs were conducted with the ‘piecewiseSEM’ package in R v.4.0.5. Because legumes did not contribute substantially to stability in regressions, we also conducted a principal component analysis (PCA) in a effort to detect any relationships among functional traits and yield stability of legumes under N0 treatment. We used the ‘vegan’ package in R v.4.0.5.