Assessing the Current and Future Potential Distribution of Solanum rostratum Dunal in China Using Multisource Remote Sensing Data and Principal Component Analysis

Remote Sensing, Journal Year: 2024, Volume and Issue: 16(2), P. 271 - 271

Published: Jan. 10, 2024

Accurate information concerning the spatial distribution of invasive alien species’ habitats is essential for species prevention and management, ecological sustainability. Currently, nationwide identification suitable highly destructive potentially weed, Solanum rostratum Dunal (S. rostratum), poses a series challenges. Simultaneously, research on potential future invasion areas likely directions spread has not received adequate attention. This study, based occurrence data multi-dimensional environmental variables constructed from multi-source remote sensing data, utilized Principal Component Analysis (PCA) in combination with Maxent model to effectively current habitat S. China, while quantitatively assessing various factors influencing its distribution. Research findings indicate that area covers 1.3952 million km2, all which located northern China. As trend climate warming persists, suitability range projected shift southward expand future; still predominantly it will have varying degrees expansion at different time frames. Notably, during period 2040 2061, under SSP1-2.6 scenario, exhibits most significant increase, surpassing scenario by 19.23%. Furthermore, attribution analysis PCA inverse transformation reveals soil, climate, spatial, humanistic, topographic collectively influence habitats, soil factors, particular, playing dominant role contributing up 75.85%. study identifies target management control rostratum, providing valuable insights into factor selection variable screening methods modeling (SDM).

Language: Английский

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Identifying the potential soil pollution areas derived from the metal mining industry in China using MaxEnt with mine reserve scales (MaxEnt_MRS)

Environmental Pollution, Journal Year: 2023, Volume and Issue: 329, P. 121687 - 121687

Published: April 25, 2023

Language: Английский

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Predicting the Impact of Climate Change on the Geographical Distribution of Leafhopper, Cicadella viridis in China through the MaxEnt Model

Insects, Journal Year: 2023, Volume and Issue: 14(7), P. 586 - 586

Published: June 28, 2023

Cicadella viridis (Hemiptera: Cicadellidae) is an omnivorous leafhopper that feeds on plant sap. It significantly reduces the yield of agricultural and forestry crops while feeding or ovipositing host plant. In recent years, rapid expansion C. has posed a serious threat to crops. To study impact climate change geographical distribution leafhopper, maximum entropy (MaxEnt) model ArcGIS software, combined with 253 geographic records pest 24 environmental variables, were used, for first time, predict potential in China under conditions climatic change. The results showed currently suitable areas are 29.06-43° N, 65.25-85.15° E, 93.45-128.85° estimated area 11,231,423.79 km2, i.e., 11.66% China. Loess Plateau, North Plain, Shandong Peninsula main areas. high medium suitability decreased each scenario (except RCP8.5 2090s). Several key variables have most significant effect identified, including mean annual temperature (Bio1), standard deviation seasonality (Bio4), minimum coldest month (Bio6), precipitation quarter (Bio19). Our research provides important guidance developing effective monitoring control methods viridis, given predicted challenges altered dynamics related future

Language: Английский

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Report on the first detection of Asian citrus psyllid Diaphorina citri Kuwayama (Hemiptera: Liviidae) in the Republic of Benin, West Africa

Scientific Reports, Journal Year: 2023, Volume and Issue: 13(1)

Published: Jan. 16, 2023

The Asian citrus psyllid (ACP), Diaphorina citri, was detected for the first time in Republic of Benin, West Africa. ACP is a known vector Candidatus Liberibacter asiaticus (CLas), putative causal agent devastating Huanglongbing (HLB; greening disease). During visual surveys, only observed on residential trees southern but not areas or commercial groves central and northern parts country. Its identity confirmed morphologically molecularly via DNA barcoding with published primers. Analysis obtained sequences showed that recorded Benin clustered ones previously reported from Nigeria, suggesting common origin both populations. samples also carried Ca. Carsonella ruddii Profftella armatura, two commonly found endosymbionts. However, all sampled individuals tested negative africanus, americanus, CLas by quantitative polymerase chain reaction. This second report Africa after eastern bordering country Benin. has an expanding industry, especially part Although HLB associated bacteria, detection requires swift actions including area-wide surveys to determine extent spread this pest implementation eradication control efforts prevent its establishment

Language: Английский

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Forecasting the Expansion of Bactrocera tsuneonis (Miyake) (Diptera: Tephritidae) in China Using the MaxEnt Model

Insects, Journal Year: 2024, Volume and Issue: 15(6), P. 417 - 417

Published: June 4, 2024

The invasive pest, Bactrocera tsuneonis (Miyake), has become a significant threat to China’s citrus industry. Predicting the area of potentially suitable habitats for B. is essential optimizing pest control strategies that mitigate its impact on Here, existing distribution data tsuneonis, as well current climate and projections four future periods (2021–2040, 2041–2060, 2061–2080, 2081–2100) from Coupled Model Intercomparison Project Phase 6 (CMIP6) were obtained. under different change scenarios in China was predicted using optimized MaxEnt model, ArcGIS, ENMeval package. accuracy assessed ROC curves, primary environmental factors influencing identified based percent contribution. When regularization multiplier (RM) set 1.5 feature combination (FC) LQH, model with lower complexity Under these parameter settings, mean training AUC 0.9916, testing 0.9854, indicating high predictive performance. most influential variables limiting Precipitation Warmest Quarter (Bio18) Temperature Seasonality (standard deviation ×100) (Bio4). climatic conditions, habitat covered an 215.9 × 104 km2, accounting 22.49% country’s land area. Potentially primarily concentrated Central China, South East China. However, projections, exhibited varying degrees expansion. Furthermore, centroid total this gradually shifted westward northward. These findings suggest will spread northern western regions changes. results our study indicate have major effect invasion implications development

Language: Английский

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Leveraging machine learning for advancing insect pest control: A bibliometric analysis

Journal of Applied Entomology, Journal Year: 2024, Volume and Issue: unknown

Published: Jan. 20, 2024

Abstract Insects have flourished in various ecosystems owing to their evolutionary prowess. However, certain behaviours led specific species be classified as pests human‐dominated settings. Ensuring accurate pest identification and assessing risks are vital for both agricultural productivity effective control. While traditional methods, based on manual checks expert opinions, tend time‐consuming error‐prone, machine learning (ML)—a branch of artificial intelligence—has brought groundbreaking shifts computer vision predictive analytics, paving the way advanced methods. This study delves into a bibliometric analysis confluence between ML control from 1999 2022. Drawing data 2348 publications Web Science (WoS) databases, we identified marked uptick interest after 2017—a decade by 40‐fold growth publication numbers. An examination 706 WoS core articles offered insights temporal geographic trends, co‐citation patterns, key publications, recurring keywords. Also, spotlight major techniques employed management hint at promising directions subsequent research. Overall, this paper serves an exhaustive resource individuals intrigued intersection science agriculture.

Language: Английский

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A novel hybrid model for species distribution prediction using neural networks and Grey Wolf Optimizer algorithm

Scientific Reports, Journal Year: 2024, Volume and Issue: 14(1)

Published: May 20, 2024

Abstract Neural networks are frequently employed to model species distribution through backpropagation methods, known as neural (BPNN). However, the complex structure of BPNN introduces parameter settings challenges, such determination connection weights, which can affect accuracy simulation. In this paper, we integrated Grey Wolf Optimizer (GWO) algorithm, renowned for its excellent global search capacity and rapid convergence, enhance performance BPNN. Then obtained a novel hybrid algorithm optimized (GNNA), designed predicting species’ potential distribution. We also compared GNNA with four prevalent models (SDMs), namely generalized boosting (GBM), linear (GLM), maximum entropy (MaxEnt), random forest (RF). These were evaluated using three evaluation metrics: area under receiver operating characteristic curve, Cohen’s kappa, true skill statistic, across 23 varied species. Additionally, examined predictive concerning spatial The results showed that was significantly improved BPNN, better than GLM GBM, even comparable MaxEnt RF in distributions small sample sizes. Furthermore, demonstrates exceptional powers forecasting non-native invasive plant

Language: Английский

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Predicting the potential distribution of three invasive insect pests (Tuta absoluta, Aleurodicus rugioperculatus and Phenacoccus manihoti) under future climate scenarios in India based on CMIP6 projections

Theoretical and Applied Climatology, Journal Year: 2025, Volume and Issue: 156(2)

Published: Jan. 10, 2025

Language: Английский

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Algorithms for Plant Monitoring Applications: A Comprehensive Review

Algorithms, Journal Year: 2025, Volume and Issue: 18(2), P. 84 - 84

Published: Feb. 5, 2025

Many sciences exploit algorithms in a large variety of applications. In agronomy, amounts agricultural data are handled by adopting procedures for optimization, clustering, or automatic learning. this particular field, the number scientific papers has significantly increased recent years, triggered scientists using artificial intelligence, comprising deep learning and machine methods bots, to process crop, plant, leaf images. Moreover, many other examples can be found, with different applied plant diseases phenology. This paper reviews publications which have appeared past three analyzing used classifying agronomic aims crops applied. Starting from broad selection 6060 papers, we subsequently refined search, reducing 358 research articles 30 comprehensive reviews. By summarizing advantages applying analyses, propose guide farming practitioners, agronomists, researchers, policymakers regarding best practices, challenges, visions counteract effects climate change, promoting transition towards more sustainable, productive, cost-effective encouraging introduction smart technologies.

Language: Английский

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Candidatus Liberibacter africanus Candidatus Liberibacter americanus Candidatus Liberibacter asiaticus Pest Report to support the ranking of EU candidate priority pests

EFSA Supporting Publications, Journal Year: 2025, Volume and Issue: 22(3)

Published: March 1, 2025

Abstract In 2022, EFSA was mandated by the European Commission's Directorate‐General for Health and Food Safety (M‐2022‐00070) to provide technical assistance on list of Union quarantine pests qualifying as priority pests, specified in Article 6(2) Regulation (EU) 2016/2031 protective measures against plant pests. As part Task C, conducted comprehensive expert knowledge elicitations candidate lag period, rate expansion impact production (yield quality losses) environment. This report provides rationale dataset three Candidatus Liberibacter species associated with citrus greening disease, delivered Joint Research Centre, feed into Impact Indicator Priority Pest (I2P2) model complete pest prioritisation ranking exercise.

Language: Английский

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