Effects of different artificial planting schemes on invasive weeds

Weed invasion is the main reason affecting grassland productivity, which also serves as a key difficulty encountered during technical grassland restoration. Modern agriculture relies heavily on chemical herbicides to control weeds; however, this is not applicable to the restoration of degraded grass...

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Main Authors: Zi Wei Tao, HaiYan Bu, JinJuan Li, Peng Jia, Wei Qi, Kun Liu, Guo Zhen Du
Format: Article
Language:English
Published: Elsevier 2021-08-01
Series:Global Ecology and Conservation
Subjects:
Online Access:http://www.sciencedirect.com/science/article/pii/S2351989421002018
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spelling doaj-581425b21cb644e7bc11f861d6202f912021-08-12T04:34:33ZengElsevierGlobal Ecology and Conservation2351-98942021-08-0128e01651Effects of different artificial planting schemes on invasive weedsZi Wei Tao0HaiYan Bu1JinJuan Li2Peng Jia3Wei Qi4Kun Liu5Guo Zhen Du6Lanzhou University, School of Life Sciences, State Key Laboratory of Grassland & Agroecosystem, Lanzhou, Gansu, PR China; Corresponding authors.Lanzhou University, School of Life Sciences, State Key Laboratory of Grassland & Agroecosystem, Lanzhou, Gansu, PR ChinaGansu Academy of Agricultural Sciences, Lanzhou, Gansu, PR ChinaLanzhou University, School of Life Sciences, State Key Laboratory of Grassland & Agroecosystem, Lanzhou, Gansu, PR ChinaLanzhou University, School of Life Sciences, State Key Laboratory of Grassland & Agroecosystem, Lanzhou, Gansu, PR ChinaLanzhou University, School of Life Sciences, State Key Laboratory of Grassland & Agroecosystem, Lanzhou, Gansu, PR ChinaLanzhou University, School of Life Sciences, State Key Laboratory of Grassland & Agroecosystem, Lanzhou, Gansu, PR China; Corresponding authors.Weed invasion is the main reason affecting grassland productivity, which also serves as a key difficulty encountered during technical grassland restoration. Modern agriculture relies heavily on chemical herbicides to control weeds; however, this is not applicable to the restoration of degraded grasslands. In this study, artificial establishment methods employing interspecific competition were used to suppress weed invasion while greatly increasing grassland productivity.The establishment of different combinations and densities were then evaluated. Compared to the blank control block, the high-density planting of four pastures was found to reduce the types of invasive weeds by 69.4% and the number of invasive weeds by 79.4%. In addition, the individual biomass of weeds fell by 96.3%. Moreover, 7.56 t hm−2 dry weight of forage was provided in the first year, and 6.52 t hm−2 dry weight of forage was continuously provided in the second year, which had the best input-output ratio in this experiment. This study also demonstrated that the low-density mixed sowing scheme of the three forages can effectively inhibit the invasion of weeds, reducing the types of invasive weeds by 58.3%, the number of invasive weeds by 73.9%, and the individual biomass of weeds by 89.1%, which was the least economical investment among weed control programs. At the same time, unsupervised learning, which was included in the machine learning framework Scikit-learn, was used to verify the relationship between the establishment density of pasture and the number of weed invasive species. The results indicated that the contribution rate of Avena sativa and Elymus nutans to the number of invasive weed species was 89.79%. The present study demonstrated that artificial planting methods can effectively control weeds and increase pasture yields. Accordingly, they have great potential and research value in terms of ecological and economic recovery of degraded grasslands.http://www.sciencedirect.com/science/article/pii/S2351989421002018Ecological restorationArtificial plantingWeed managementEconomic recoveryMachine learningUnsupervised learning
collection DOAJ
language English
format Article
sources DOAJ
author Zi Wei Tao
HaiYan Bu
JinJuan Li
Peng Jia
Wei Qi
Kun Liu
Guo Zhen Du
spellingShingle Zi Wei Tao
HaiYan Bu
JinJuan Li
Peng Jia
Wei Qi
Kun Liu
Guo Zhen Du
Effects of different artificial planting schemes on invasive weeds
Global Ecology and Conservation
Ecological restoration
Artificial planting
Weed management
Economic recovery
Machine learning
Unsupervised learning
author_facet Zi Wei Tao
HaiYan Bu
JinJuan Li
Peng Jia
Wei Qi
Kun Liu
Guo Zhen Du
author_sort Zi Wei Tao
title Effects of different artificial planting schemes on invasive weeds
title_short Effects of different artificial planting schemes on invasive weeds
title_full Effects of different artificial planting schemes on invasive weeds
title_fullStr Effects of different artificial planting schemes on invasive weeds
title_full_unstemmed Effects of different artificial planting schemes on invasive weeds
title_sort effects of different artificial planting schemes on invasive weeds
publisher Elsevier
series Global Ecology and Conservation
issn 2351-9894
publishDate 2021-08-01
description Weed invasion is the main reason affecting grassland productivity, which also serves as a key difficulty encountered during technical grassland restoration. Modern agriculture relies heavily on chemical herbicides to control weeds; however, this is not applicable to the restoration of degraded grasslands. In this study, artificial establishment methods employing interspecific competition were used to suppress weed invasion while greatly increasing grassland productivity.The establishment of different combinations and densities were then evaluated. Compared to the blank control block, the high-density planting of four pastures was found to reduce the types of invasive weeds by 69.4% and the number of invasive weeds by 79.4%. In addition, the individual biomass of weeds fell by 96.3%. Moreover, 7.56 t hm−2 dry weight of forage was provided in the first year, and 6.52 t hm−2 dry weight of forage was continuously provided in the second year, which had the best input-output ratio in this experiment. This study also demonstrated that the low-density mixed sowing scheme of the three forages can effectively inhibit the invasion of weeds, reducing the types of invasive weeds by 58.3%, the number of invasive weeds by 73.9%, and the individual biomass of weeds by 89.1%, which was the least economical investment among weed control programs. At the same time, unsupervised learning, which was included in the machine learning framework Scikit-learn, was used to verify the relationship between the establishment density of pasture and the number of weed invasive species. The results indicated that the contribution rate of Avena sativa and Elymus nutans to the number of invasive weed species was 89.79%. The present study demonstrated that artificial planting methods can effectively control weeds and increase pasture yields. Accordingly, they have great potential and research value in terms of ecological and economic recovery of degraded grasslands.
topic Ecological restoration
Artificial planting
Weed management
Economic recovery
Machine learning
Unsupervised learning
url http://www.sciencedirect.com/science/article/pii/S2351989421002018
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