Negligible Impact of Drought-Resistant Genetically Modified Maize on Arthropod Community Structure Observed in a 2-Year Field Investigation
Abstract
:1. Introduction
2. Results
2.1. Arthropods in Transgenic and Non-Transgenic Maize Plots
2.2. Impacts of Maize Type, Year, and Sampling Time on Abundance and Diversity of Arthropods
2.3. Effects of Maize Type, Year, and Sampling Time on the Community Composition of Arthropods
2.3.1. Time-Dependent Effects of GM1 on Arthropod Community
2.3.2. Similarity of Arthropod Communities in Transgenic and Non-Transgenic Maize Fields
3. Discussion
4. Materials and Methods
4.1. Experimental Materials
4.2. Experimental Field
4.3. Experimental Design
4.4. Sample Collection Methods
4.4.1. Whole Plant Inspection Method
4.4.2. Pitfall Trap Method
4.4.3. Suction Sampler Method
4.5. Statistical Analysis
5. Conclusions
Author Contributions
Funding
Institutional Review Board Statement
Informed Consent Statement
Data Availability Statement
Conflicts of Interest
References
- Li, B.; Wang, Z.C.; Sun, Z.G.; Chen, Y.; Yang, F. Resources and sustainable resource exploitation of salinized land in China. Agric. Res. Arid. Areas 2005, 23, 154–158. [Google Scholar]
- Ji, J.H.; Li, Y.Y.; Liu, S.Q.; Tong, Y.X. Effect of Plastic Film Mulch and Drip Irrigation under Plastic Film Mulch on Growth and Development of Maize and Water use Efficiency. Water Sav. Irrig. 2015, 3, 22-24+27. [Google Scholar]
- Yu, G.R.; Zhang, W.; Du, W.P.; Song, J.; Chen, Q.; Xu, L.Y. Transgenic Drought-resistant Gene IrrE Maize Material Obtaining and Resistance Identification. Southwest China J. Agric. Sci. 2016, 29, 1782–1786. [Google Scholar] [CrossRef]
- Liu, B.; Zeng, Q.; Yan, F.M.; Xu, H.G.; Xu, C.R. Effects of transgenic plants on soil microorganisms. Plant Soil 2005, 271, 1–13. [Google Scholar] [CrossRef]
- Truter, J.; Hamburg, H.V.; Berg, J.V.D. Comparative diversity of arthropods on Bt maize and non-Bt maize in two different cropping systems in South Africa. Environ. Entomol. 2014, 43, 197–208. [Google Scholar] [CrossRef] [PubMed]
- Yu, H.L.; Li, Y.H.; Li, X.J.; Wu, K.M. Arthropod Abundance and Diversity in Transgenic Bt Soybean. Environ. Entomol. 2014, 43, 1124–1134. [Google Scholar] [CrossRef]
- Bal, H.K.; Dhawan, A.K. Impact of intercropping on arthropod diversity in Bt and non-Bt cotton. J. Insect Sci. 2010, 23, 136–140. [Google Scholar]
- Bal, H.K.; Dhawan, A.K. Impact of transgenic cotton on diversity of non-target arthropod communities in cotton agro-ecosystem. J. Insect Sci. 2009, 22, 130–138. [Google Scholar]
- Romeis, J.; Hellmich, R.L.; Candolfi, M.P.; Carstens, K.; Schrijver, A.D.; Gatehouse, A.M.R.; Herman, R.A.; Huesing, J.E.; Mclean, M.A.; Raybould, A. Recommendations for the design of laboratory studies on non-target arthropods for risk assessment of genetically engineered plants. Transgenic Res. 2011, 20, 1–22. [Google Scholar] [CrossRef] [Green Version]
- Romeis, J.; Raybould, A.; Bigler, F.; Candolfi, M.P.; Hellmich, R.L.; Huesing, J.E.; Shelton, A.M. Deriving criteria to select arthropod species for laboratory tests to assess the ecological risks from cultivating arthropod-resistant genetically engineered crops. Chemosphere 2013, 90, 901–909. [Google Scholar] [CrossRef] [Green Version]
- Romeis, J.; Meissle, M.; Alvarez-Alfageme, F.; Bigler, F.; Bohan, D.A.; Devos, Y.; Malone, L.A.; Pons, X.; Rauschen, S. Potential use of an arthropod database to support the non-target risk assessment and monitoring of transgenic plants. Transgenic Res. 2014, 23, 995–1013. [Google Scholar] [CrossRef] [PubMed]
- Szénási, A.; Pálinkás, Z.; Zalai, M.; Schmitz, O.J.; Adalbert, B. Short-term effects of different genetically modified maize varieties on arthropod food web properties: An experimental field assessment. Sci. Rep. 2014, 4, 5315. [Google Scholar] [CrossRef] [PubMed] [Green Version]
- Hu, H.H.; Xiong, L.Z. Genetic Engineering and Breeding of Drought-Resistant Crops. Annu. Rev. Plant Biol. 2014, 65, 715–741. [Google Scholar] [CrossRef] [PubMed]
- Kang, Q.; Vahl, C.I. Statistical Analysis in the Safety Evaluation of Genetically-Modified Crops: Equivalence Tests. Crop Sci. 2014, 54, 2183–2200. [Google Scholar] [CrossRef]
- Zhang, M.D.; Sun, L.; Xiong, Q.F. The Safety Evaluation of the Genetically Modified Crops. Hubei Agric. Sci. 2015, 6, 98–104. [Google Scholar] [CrossRef]
- Ren, Z.T.; Shen, W.J.; Liu, B.; Xue, K. Effects of Transgenic Maize on Biodiversity of Arthropod Communities in the Fields. Sci. Agric. Sin. 2017, 50, 2315–2325. [Google Scholar] [CrossRef]
- Guo, J.F.; He, K.L.; Bai, S.X.; Zhang, T.T.; Liu, Y.J.; Wang, F.X.; Wang, Z.Y. Effects of transgenic cry1Ie maize on non-lepidopteran pest abundance, diversity and community composition. Transgenic Res. 2016, 25, 761–772. [Google Scholar] [CrossRef]
- Guo, J.F.; He, K.L.; Hellmich, R.L.; Bai, S.X.; Zhang, T.T.; Liu, Y.J.; Ahmed, T.; Wang, Z.Y. Field trials to evaluate the effects of transgenic cry1Ie maize on the community characteristics of arthropod natural enemies. Sci. Rep. 2016, 6, 22102. [Google Scholar] [CrossRef]
- Guo, Y.Y.; Feng, Y.J.; Ge, Y.; Tetreau, G.; Chen, X.W.; Dong, X.H.; Shi, W.P. The Cultivation of Bt Corn Producing Cry1Ac Toxins Does Not Adversely Affect Non-Target Arthropods. PLoS ONE 2014, 9, e114228. [Google Scholar] [CrossRef]
- Habustova, O.; Dolezal, P.; Spitzer, L.; Svobodova, Z.; Hussein, H.; Sehnal, F. Impact of Cry1Ab toxin expression on the non-target insects dwelling on maize plants. J. Appl. Entomol. 2014, 138, 164–172. [Google Scholar] [CrossRef]
- Rauschen, S.; Schultheis, E.; Hunfeld, H.; Schaarschmidt, F.; Schuphan, I.; Eber, S. Diabrotica-resistant, Bt-maize, DKc5143 event MON88017 has no impact on the field densities of the leafhopper, Zyginidia scutellaris. Environ. Biosaf. Res. 2010, 9, 87–99. [Google Scholar] [CrossRef] [PubMed] [Green Version]
- Xu, Z.S.; Chen, M.; Li, L.C.; Ma, Y.Z. Functions of the ERF transcription factor family in plants. Botany 2008, 86, 969–977. [Google Scholar] [CrossRef]
- Xu, Z.S.; Chen, M.; Li, L.C.; Ma, Y.Z. Functions and application of the AP2/ERF transcription factor family in crop improvement. J. Integr. Plant Biol. 2011, 53, 570–585. [Google Scholar] [CrossRef] [PubMed]
- Xu, Z.S.; Ni, Z.Y.; Liu, L.; Nie, L.N.; Li, L.C.; Chen, M.; Ma, Y.Z. Characterization of the TaAIDFa gene encoding a CRT/DRE-binding factor responsive to drought, high-salt, and cold stress in wheat. Mol. Genet. Genom. 2008, 280, 497–508. [Google Scholar] [CrossRef]
- Jiang, Q.Y.; Li, X.H.; Hu, Z.; Ma, Y.Z.; Zhang, H.; Xu, Z.S. Safety Assessment of Weediness of Transgenic Drought-Tolerant Wheat (Triticum aestivum L.). Sci. Agric. Sin. 2015, 48, 2096–2107. [Google Scholar]
- Yu, M.Z.; Dai, R.Y.; Wu, J.R.; Xu, J.H.; Du, J.; Chen, S.L.; Shi, J.R. Analysis of available nutrient, enzyme activities and microorganism community diversity in rhizospheric soil of TaDREB4 transgenic wheat with drought resistance. Jiangsu J. Agric. Sci. 2013, 29, 938–945. [Google Scholar]
- Wang, J.Y.; Ding, W.; Muhammad, S.K.; Cheng, Z.; Dai, H.Y. Survival competition between transgenic drought-resistant soybean and weeds with different carbon metabolism pathways under drought stress. Jiangsu Agric. Sci. 2018, 46, 73–76. [Google Scholar] [CrossRef]
- Cao, Y.; Ding, W.; Li, X.H.; Ma, Y.Z.; Wang, Z.H.; Li, W.B. Effect of transgenic drought resistant soybean on soil microbial community and beneficial microorganism. J. Northeast Agric. Univ. 2011, 42, 17–20. [Google Scholar] [CrossRef]
- Xing, S.; Yao, Y.; Lei, X.; Hu, X.; Yang, L. Advances of Drought-resistant Genes and Drought-resistant Transgenic of Main Crops of Gramineae Plants. Chin. Agric. Sci. Bull. 2014, 42, 251–258. [Google Scholar]
- Shirai, Y. Influence of transgenic insecticidal crops on non-target arthropods: A review. Jpn. J. Ecol. 2004, 54, 47–65. [Google Scholar] [CrossRef]
- Cui, K.; Shoemaker, S.P. Public perception of genetically modified (GM) food: A Nationwide Chinese consumer study. Sci. Food 2018, 2, 10. [Google Scholar] [CrossRef] [PubMed]
- Li, Y.H.; Zhang, X.J.; Chen, X.P.; Romeis, J.; Yin, X.M.; Peng, Y.F. Consumption of Bt rice pollen containing Cry1C or Cry2A does not pose a risk to Propylea japonica (Thunberg) (Coleoptera: Coccinellidae). Sci. Rep. 2015, 5, 7679. [Google Scholar] [CrossRef] [PubMed] [Green Version]
- Wang, Y.Y.; Li, Y.H.; Romeis, J.; Chen, X.P.; Zhang, J.; Chen, H.Y.; Peng, Y.F. Consumption of Bt rice pollen expressing Cry2Aa does not cause adverse effects on adult Chrysoperla sinica Tjeder (Neuroptera: Chrysopidae). Biol. Control 2012, 61, 246–251. [Google Scholar] [CrossRef]
- Yang, Y.; Liu, Y.; Cao, F.Q.; Chen, X.P.; Chen, L.S.; Romeis, J.; Li, Y.H.; Peng, Y.F. Consumption of Bt Rice Pollen Containing Cry1C or Cry2A Protein Poses a Low to Negligible Risk to the Silkworm Bombyx mori (Lepidoptera: Bombyxidae). PLoS ONE 2014, 9, e102302. [Google Scholar] [CrossRef]
- Ahmad, A.; Wilde, G.E.; Zhu, K.Y. Detectability of Coleopteran-specific Cry3Bb1 Protein in Soil and Its Effect on Nontarget Surface and Below-Ground Arthropods. Environ. Entomol. 2005, 34, 385–394. [Google Scholar] [CrossRef]
- Li, X.G.; Liu, B.; Desneux, N. A 2-Year Field Study Shows Little Evidence That the Long-Term Planting of Transgenic Insect-Resistant Cotton Affects the Community Structure of Soil Nematodes. PLoS ONE 2013, 8, e61670. [Google Scholar] [CrossRef] [Green Version]
- Romeis, J.; Bartsch, D.; Bigler, F.; Candolfi, M.P.; Gielkens, M.M.C.; Hartley, S.E.; Hellmich, R.L.; Huesing, J.E.; Jepson, P.C.; Layton, R.; et al. Assessment of risk of insect-resistant transgenic crops to nontarget arthropods. Nat. Biotechnol. 2008, 26, 203–208. [Google Scholar] [CrossRef] [Green Version]
- Li, Y.H.; Romeis, J.; Wu, K.M.; Peng, Y.F. Tier-1 assays for assessing the toxicity of insecticidal proteins produced by genetically engineered plants to non-target arthropods. Insect Sci. 2014, 21, 125–134. [Google Scholar] [CrossRef] [Green Version]
- Wang, B.F.; Wu, F.C.; Yin, J.Q.; Jiang, Z.L.; Song, X.Y.; Reddy, G.V.P. Use of taxonomic and trait-based approaches to evaluate the effect of bt maize expressing cry1ie protein on non-target collembola: A case study in northeast china. Insects 2021, 12, 88. [Google Scholar] [CrossRef]
- Fan, C.M.; Wu, F.C.; Dong, J.Y.; Wang, B.F.; Yin, J.Q.; Song, X.Y. No impact of transgenic cry1Ie maize on the diversity, abundance and composition of soil fauna in a 2-year field trial. Sci. Rep. 2019, 9, 10333. [Google Scholar] [CrossRef] [Green Version]
- Song, X.Y.; Chang, L.; Reddy, G.V.P.; Zhang, L.; Fan, C.M.; Wang, B.F. Use of taxonomic and trait-based approaches to evaluate the effects of transgenic cry1ac corn on the community characteristics of soil collembola. Environ. Entomol. 2018, 48, 263–269. [Google Scholar] [CrossRef] [PubMed]
- Carpenter, J.E. Impact of GM crops on biodiversity. Communities of ground-dwelling arthropods in conventional and transgenic maize: Background data for the post-market environmental monitoring. J. Appl. Entomol. 2015, 139, 31–45. [Google Scholar]
- Bogya, S.; Markó, V. Effect of pest management systems on ground-dwelling spider assemblages in an apple orchard in Hungary. Agric. Ecosyst. Environ. 1999, 73, 7–18. [Google Scholar] [CrossRef]
- Liu, J.; Chen, J. Effects of transgenetic Bt cotton on ground-dwelling spider assemblages by pitfall traps. J. Plant Prot. 2015, 42, 59–65. [Google Scholar] [CrossRef]
- Wang, Y.; Chen, J.; Xiao, D.H.; Ma, F.G.; Hua, H.X. Assessing the efficacy of different sampling methods for arthropods in rice field. J. Environ. Entomol. 2016, 38, 1090–1098. [Google Scholar] [CrossRef]
- Mu, J.; Qiu, M.J.; Gu, Y.; Ren, J.Q.; Liu, Y. Applicability of five drought indices for agricultural drought evaluation in Jilin Province, China. Chin. J. Appl. Ecol. 2018, 29, 2624–2632. [Google Scholar] [CrossRef]
- Liang, J.G.; Meng, F.; Sun, S.; Wu, C.X.; Wu, H.Y.; Zhang, M.R.; Zhang, H.F.; Zheng, X.B.; Song, X.Y.; Zhang, Z.G. Community structure of arbuscular mycorrhizal fungi in rhizospheric soil of a transgenic high-methionine soybean and a near isogenic variety. PLoS ONE 2015, 10, e0145001. [Google Scholar] [CrossRef]
- Ministry of Agriculture of the PRC. NY/T 720.3-2003 Environmental impact testing of genetically modified maize-Part 3:testing the effects on biodiversity. Standards Press of China: Beijing, China, 2003. [Google Scholar]
- Braak, C.J.F.T.; Smilauer, P. CANOCO reference manual andCanoDraw for Windows user’s guide: Software for canonical communityordination (version 4.5). Microcomputer Power: Ithaca, NY, USA, 2002. [Google Scholar]
- Jackson, M.M.; Turner, M.G.; Pearson, S.M.; Ives, A.R. Seeing the forest and the trees: Multilevel models reveal both species and community patterns. Ecosphere 2012, 3, 1–16. [Google Scholar] [CrossRef]
- Clarke, K.R. Non-parametric multivariate analyses of changes in community structure. Aust. J. Ecol. 2010, 18, 117–143. [Google Scholar] [CrossRef]
Investigation Method | Factor | Shannon–Weiner’s Index (H’) | Simpson’s Diversity Index (D) | Pielou’s Evenness Index (J) | Number of Species (S) | Total Abundance (N) | Abundance of Critical Groups | |||||||||
---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
Rhopalosiphum maidis | Formicidae | |||||||||||||||
F | p | F | p | F | p | F | p | F | p | F | p | F | p | |||
Whole plant inspection method | Year | 18.823 | 0.002 ** | 61.658 | 0.000 *** | 80.475 | 0.000 *** | 3.964 | 0.082 | 0.212 | 0.657 | 0 | 1 | 2.462 | 0.155 | |
Maize type | 0.064 | 0.807 | 0.038 | 0.85 | 0.823 | 0.391 | 0.367 | 0.561 | 1.156 | 0.314 | 2.709 | 0.138 | 0.427 | 0.532 | ||
Sampling time | 19.56 | 0.000 *** | 38.71 | 0.000 *** | 84.41 | 0.000 *** | 21.41 | 0.000 *** | 244.91 | 0.000 *** | 306.456 | 0.000 *** | 10.178 | 0.000 *** | ||
Maize type with Year | 0.202 | 0.665 | 0.035 | 0.857 | 0.274 | 0.615 | 0.187 | 0.677 | 0.001 | 0.979 | 0.142 | 0.717 | 1.094 | 0.326 | ||
Year with Sampling time | 15.32 | 0.000 *** | 38.31 | 0.000 *** | 54.47 | 0.000 *** | 2.93 | 0.041 * | 20.33 | 0.000 *** | 53.152 | 0.000 *** | 3.427 | 0.032 * | ||
Maize type with Sampling time | 0.30 | 0.863 | 0.10 | 0.964 | 0.32 | 0.868 | 0.70 | 0.588 | 1.09 | 0.38 | 1.881 | 0.179 | 0.98 | 0.42 | ||
Maize type with Year and Sampling time | 0.21 | 0.921 | 0.20 | 0.905 | 0.38 | 0.824 | 0.35 | 0.828 | 2.32 | 0.07 | 2.158 | 0.141 | 0.344 | 0.8 | ||
Mean ± SD (GM1) | 2.312 ± 0.171 | 0.733 ± 0.028 | 0.756 ± 0.019 | 8.866 ± 1.063 | 37.484 ± 3.085 | 12.967 ± 1.026 | 1.467 ± 0.503 | |||||||||
Mean ± SD (CK) | 2.288 ± 0.170 | 0.730 ± 0.033 | 0.765 ± 0.022 | 8.517 ± 0.917 | 35.499 ± 2.451 | 11.800 ± 1.293 | 1.300 ± 0.626 | |||||||||
Pitfall trap method | Year | 23.087 | 0.001 *** | 14.533 | 0.005 ** | 12.843 | 0.007 ** | 5.911 | 0.041 * | 3.275 | 0.108 | 0.181 | 0.682 | 1.852 | 0.211 | |
Maize type | 2.756 | 0.135 | 2.831 | 0.131 | 0.024 | 0.882 | 4.034 | 0.079 | 0.078 | 0.787 | 0.647 | 0.445 | 4.605 | 0.064 | ||
Sampling time | 60.849 | 0.000 *** | 85.218 | 0.000 *** | 163.107 | 0.000 *** | 23.25 | 0.000 *** | 213.789 | 0.000 *** | 46.295 | 0.000 *** | 31.194 | 0.000 *** | ||
Maize type with Year | 1.695 | 0.229 | 1.798 | 0.217 | 0.114 | 0.745 | 3.229 | 0.11 | 1.719 | 0.226 | 4.942 | 0.057 | 4.274 | 0.073 | ||
Year with Sampling time | 0.6 | 0.7 | 0.884 | 0.436 | 1.05 | 0.373 | 0.352 | 0.878 | 7.037 | 0.000 *** | 8.438 | 0.006 ** | 1.332 | 0.292 | ||
Maize type with Sampling time | 1.376 | 0.254 | 3.29 | 0.061 | 1.51 | 0.251 | 1.02 | 0.420 | 1.738 | 0.148 | 0.659 | 0.506 | 1.52 | 0.25 | ||
Maize type with Year and Sampling time | 1.339 | 0.268 | 2.37 | 0.123 | 1.69 | 0.216 | 1.48 | 0.219 | 0.902 | 0.489 | 1.971 | 0.181 | 0.743 | 0.483 | ||
Mean ± SD (GM1) | 2.831 ± 0.148 | 0.799 ± 0.027 | 0.769 ± 0.023 | 13.389 ± 0.977 | 99.584 ± 8.970 | 4.000 ± 0.920 | 23.028 ± 5.218 | |||||||||
Mean ± SD (CK) | 2.733 ± 0.101 | 0.780 ± 0.020 | 0.767 ± 0.021 | 12.333 ± 0.802 | 101.390 ± 8.549 | 3.528 ± 0.721 | 18.472 ± 2.981 | |||||||||
Suction sampler method | Year | 0.578 | 0.469 | 5.416 | 0.048 * | 12.626 | 0.007 ** | 1.84 | 0.212 | 5.788 | 0.043 * | 1.903 | 0.205 | 8.696 | 0.018 * | |
Maize type | 0.05 | 0.829 | 2.476 | 0.154 | 2.288 | 0.169 | 0.115 | 0.743 | 0.027 | 0.874 | 0.004 | 0.954 | 4.261 | 0.073 | ||
Sampling time | 9.825 | 0.000 *** | 22.19 | 0.000 *** | 41.108 | 0.000 *** | 14.973 | 0.000 *** | 104.592 | 0.000 *** | 49.17 | 0.000 *** | 17.171 | 0.000 *** | ||
Maize type with Year | 0.078 | 0.787 | 0.319 | 0.587 | 2.917 | 0.126 | 0.013 | 0.913 | 0.197 | 0.669 | 0.291 | 0.604 | 4.261 | 0.073 | ||
Year with Sampling time | 1.122 | 0.364 | 0.451 | 0.653 | 2.568 | 0.057 | 0.50 | 0.739 | 3.107 | 0.029 * | 5.148 | 0.003 ** | 7.805 | 0.000 *** | ||
Maize type with Sampling time | 0.816 | 0.524 | 0.73 | 0.501 | 1.31 | 0.286 | 0.42 | 0.794 | 1.536 | 0.215 | 1.36 | 0.27 | 2.341 | 0.076 | ||
Maize type with Year and Sampling time | 0.412 | 0.799 | 0.62 | 0.555 | 1.71 | 0.173 | 0.68 | 0.614 | 0.483 | 0.748 | 0.556 | 0.696 | 0.39 | 0.814 | ||
Mean ± SD (GM1) | 2.277 ± 0.227 | 0.860 ± 0.020 | 0.903 ± 0.017 | 6.300 ± 0.937 | 14.333 ± 2.014 | 3.567 ± 0.699 | 0.900 ± 0.307 | |||||||||
Mean ± SD (CK) | 2.244 ± 0.212 | 0.831 ± 0.040 | 0.888 ± 0.024 | 6.100 ± 0.806 | 14.567 ± 1.665 | 3.533 ± 0.911 | 1.367 ± 0.482 |
Variable Factor | Proportion of Variance Explained (%) | p | F |
---|---|---|---|
Sampling time | 34 | 0.0020 ** | 60.90 |
Year | 2 | 0.0120 * | 3.01 |
Maize type | 0 | 0.9440 | 0.44 |
Total | 36 |
Variable Factor | Proportion of Variance Explained (%) | p | F |
---|---|---|---|
Sampling time | 35 | 0.0020 ** | 38.50 |
Year | 1 | 0.1180 | 1.49 |
Maize type | 1 | 0.7660 | 0.62 |
Total | 37 |
Variable Factor | Proportion of Variance Explained (%) | p | F |
---|---|---|---|
Sampling time | 29 | 0.0020 ** | 23.71 |
Year | 3 | 0.0480 * | 2.10 |
Maize type | 1 | 0.8880 | 0.50 |
Total | 33 |
Correlation with nMDS Structure | Whole Plant Inspection Method | Pitfall Trap Method | Suction Sampler Method | |||
---|---|---|---|---|---|---|
R2 | p | R2 | p | R2 | p | |
Sampling time | 0.80 | 0.001 *** | 0.67 | 0.001 *** | 0.49 | 0.001 *** |
Year | 0.00 | 0.07 | 0.00 | 0.26 | 0.00 | 0.112 |
Maize type | 0.00 | 0.994 | 0.00 | 0.897 | 0.00 | 0.986 |
Publisher’s Note: MDPI stays neutral with regard to jurisdictional claims in published maps and institutional affiliations. |
© 2022 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https://creativecommons.org/licenses/by/4.0/).
Share and Cite
Yin, J.-Q.; Wang, D.-M.; Liang, J.-G.; Song, X.-Y. Negligible Impact of Drought-Resistant Genetically Modified Maize on Arthropod Community Structure Observed in a 2-Year Field Investigation. Plants 2022, 11, 1092. https://doi.org/10.3390/plants11081092
Yin J-Q, Wang D-M, Liang J-G, Song X-Y. Negligible Impact of Drought-Resistant Genetically Modified Maize on Arthropod Community Structure Observed in a 2-Year Field Investigation. Plants. 2022; 11(8):1092. https://doi.org/10.3390/plants11081092
Chicago/Turabian StyleYin, Jun-Qi, Da-Ming Wang, Jin-Gang Liang, and Xin-Yuan Song. 2022. "Negligible Impact of Drought-Resistant Genetically Modified Maize on Arthropod Community Structure Observed in a 2-Year Field Investigation" Plants 11, no. 8: 1092. https://doi.org/10.3390/plants11081092
APA StyleYin, J. -Q., Wang, D. -M., Liang, J. -G., & Song, X. -Y. (2022). Negligible Impact of Drought-Resistant Genetically Modified Maize on Arthropod Community Structure Observed in a 2-Year Field Investigation. Plants, 11(8), 1092. https://doi.org/10.3390/plants11081092