Spatial optimization of cotton cultivation in Xinjiang: A climate change perspective

International Journal of Applied Earth Observation and Geoinformation, Год журнала: 2023, Номер 124, С. 103523 - 103523

Опубликована: Окт. 24, 2023

Global climate change is shifting the temperate zone towards higher latitudes, altering crop adaptability and potentially impacting cotton (Gossypium hirsutum L.) cultivation's suitability distribution. However, our understanding of these impacts often based on one-sided assessments, leading to potential biases when optimizing planting spatial distribution adaptability. In this study, we utilized a cultivation optimization framework, combining Geographical Information System (GIS) Remote Sensing (RS) techniques, accurately identify locations with ongoing land-use disputes. We then analyzed extent discrepancy between zones under influence change. The results demonstrate stability suitable areas in southern (19%), northern (4%), eastern (1%) regions, indicating comparative advantage climatic resources for region. climate-suitable were mainly concentrated south side Tianshan Mountains near Tarim River, covering regions Aksu, Hetian, Kashgar, Bazhou. notable increase effective accumulated temperature, precipitation, sunshine hours, minimum proportion very highly unsuitable decreased, while less increased. Additionally, led expansion North Xinjiang. Moreover, center shifted from South Xinjiang during 2000–2020 returned Xinjiang, being nearly balanced by 2021 (49% each). Despite decrease conflict rate 60% 33% 2000–2020, remained relatively high. It reasonable attribute significant target price policy agricultural technological advancement both Overall, study effectively identifies conflicts suggests layout This can leverage resource advantages, reduce production costs, provide valuable references decision makers.

Язык: Английский

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Impacts of climate change and human activity on the potential distribution of Aconitum leucostomum in China

The Science of The Total Environment, Год журнала: 2023, Номер 912, С. 168829 - 168829

Опубликована: Ноя. 28, 2023

Язык: Английский

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Coupling behavioral economics and water management policies for agricultural land-use planning in basin irrigation districts: Agent-based socio-hydrological modeling and application

Agricultural Water Management, Год журнала: 2024, Номер 298, С. 108845 - 108845

Опубликована: Май 7, 2024

Optimizing the cropping structure is of great significance for ensuring efficient water use and ecological sustainability in irrigation districts experiencing shortages. However, how farmers choose crops to plant under intervention factors such as behavioral economics policies has been less considered agricultural land-use planning. This study proposes an agent-based socio-hydrological model embedding a geographic information system (ABSHM-GIS). In ABSHM-GIS, bottom-up research methodology coupled with farmers' government used examine influencing impact decisions on income spatial temporal distributions resources. this study, ABSHM-GIS was applied context planting crop subsidy policy Qira oasis, Xinjiang, China case area. Results showed that effective reducing (18–30 million m3/year) relative farmer intervention, but it also reduced returns (17,850–25,860 yuan/ha). During period irrigation, regulating increase lower residual volume gates 2–4 range 666–869 m3/day 5–9 211–342 could effectively ensure even distribution surface groundwater. structure, by 300 yuan/ha save average 2 m3/year resources safety. The learning factor main changed decision-making behavior farmers. proposed paper help researchers reveal causes provide insights into emergence macro-patterns, changes irrigated agriculture, result microfarmers' economic approach.

Язык: Английский

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Mapping cropland suitability in China using optimized MaxEnt model

Field Crops Research, Год журнала: 2023, Номер 302, С. 109064 - 109064

Опубликована: Июль 29, 2023

Язык: Английский

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Suitability evaluation of the rural settlements in a farming-pastoral ecotone area based on machine learning maximum entropy

Ecological Indicators, Год журнала: 2023, Номер 154, С. 110794 - 110794

Опубликована: Авг. 12, 2023

The suitability evaluation of rural settlements is the core foundation planning and layout optimization. Settlements in a farming-pastoral ecotone are migrative, dynamic, diverse, thus their changes constantly. However, our limited understanding factors that drive this dynamic process affect humane hindered high-quality development human such areas. Here we selected ethnic minority border area Dalham Maomingan United Banner (DMUB) Northern China to evaluate its settlements. A data-driven machine learning maximum entropy (Maxent) method was applied settlement datasets DMUB years 1996, 2010, 2020, as well 13 influencing derived from optical images topographical ancillary data, demonstrating Maxent model can quantitatively measure contribution importance each factor variation over time. Furthermore, results showed distance cultivated land, population density, road had great influence on early-stage distribution land gradually decreased with significantly increased effect grassland later period. fluctuated first increasing then decreasing. also used automatically determine suitable range for according response curve: elevation falling between 1450 1650 m approximately, slope being <7°, aspect about 75°-225°, optimal town hospital within 3000 m, vegetation cover 0.60–0.75. Such multi-period indicated decreased, fragmentation serious. has been dynamically transformed, but mostly toward unsuitable development. This study provides decision-making basis site selection livability assessment villages ecotone.

Язык: Английский

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Develop agricultural planting structure prediction model based on machine learning: The aging of the population has prompted a shift in the planting structure toward food crops

Computers and Electronics in Agriculture, Год журнала: 2024, Номер 221, С. 108941 - 108941

Опубликована: Апрель 16, 2024

Язык: Английский

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Optimizing food crop layout considering precipitation uncertainty: Balancing regional water, carbon, and economic pressures with food security

Journal of Cleaner Production, Год журнала: 2024, Номер 467, С. 142881 - 142881

Опубликована: Июнь 17, 2024

Язык: Английский

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Exploiting the potential of carbon emission reduction in cropping-livestock systems: Managing water-energy-food nexus for sustainable development

Applied Energy, Год журнала: 2024, Номер 377, С. 124443 - 124443

Опубликована: Сен. 21, 2024

Язык: Английский

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Spatial Distribution Pattern of Aromia bungii Within China and Its Potential Distribution Under Climate Change and Human Activity

Ecology and Evolution, Год журнала: 2024, Номер 14(11)

Опубликована: Ноя. 1, 2024

ABSTRACT Aromia bungii is a pest that interferes with the health of forests and hinders development fruit tree industry, its spread influenced by changes in abiotic factors human activities. Therefore, exploring their spatial distribution patterns potential areas under such conditions crucial for maintaining forest ecosystem security. This study analyzed differentiation characteristics geographic pattern A. China using Moran's I Getis‐Ord General G index. Hot spot were identified Gi*. An optimized MaxEnt model was used to predict within four shared economic pathways combining multivariate environmental data: (1) prediction natural variables predicted current climate models; (2) + activities (3) future models (2050s 2070s). Meanwhile, MigClim simulate unoccupied suitable area presence obstacles change. The results showed activities, minimum temperature coldest month, precipitation wettest month had positive effects on . However, period, drastically reduced survival , mainly concentrated eastern central regions China. Under influence change future, habitat will gradually increase. Additionally, indicates has been continuous increasing trend. provides reference prevention control maintenance security, important theoretical guidance researchers, policymakers, governments.

Язык: Английский

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Suitability Evaluation of Tea Cultivation Using Machine Learning Technique at Town and Village Scales

Agronomy, Год журнала: 2022, Номер 12(9), С. 2010 - 2010

Опубликована: Авг. 25, 2022

Suitability evaluation of tea cultivation is very important for improving the yield and quality tea, which can avoid blind expansion achieve sustainable development; however, to date, relevant research at town village scales lacking. This study selected Xinming Township in Huangshan City, Anhui Province, as area, main production area Taiping Houkui Tea—one ten most famous teas China. We proposed a machine learning-based suitability model by comparing logistic regression (LR), extreme gradient boosting (XGBoost), adaptive (AdaBoost), decision tree (GBDT), random forest (RF), Gaussian Naïve Bayes (GNB), multilayer perceptron (MLP) calculate weight accuracy factors. then 12 factors, including climate, soil, terrain, ecological economy using RF with highest factor weights obtained results. The results show that highly suitable moderately generally unsuitable land categories were 14.13%, 27.25%, 32.46%, 26.16%, respectively. Combined field research, areas mainly distributed northwest Town, line distribution township level. provide scientific reference support allocation decisions green agricultural development scales.

Язык: Английский

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