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1.
Artigo em Inglês | MEDLINE | ID: mdl-33499091

RESUMO

Crop potential yields in cropland are the essential reflection of the utilization of cropland resources. The changes of the quantity, quality, and spatial distribution of cropland will directly affect the crop potential yields, so it is very crucial to simulate future cropland distribution and predict crop potential yields to ensure the future food security. In the present study, the Cellular Automata (CA)-Markov model was employed to simulate land-use changes in Northeast China during 2015-2050. Then, the Global Agro-ecological Zones (GAEZ) model was used to predict maize potential yields in Northeast China in 2050, and the spatio-temporal changes of maize potential yields during 2015-2050 were explored. The results were the following. (1) The woodland and grassland decreased by 5.13 million ha and 1.74 million ha respectively in Northeast China from 2015 to 2050, which were mainly converted into unused land. Most of the dryland was converted to paddy field and built-up land. (2) In 2050, the total maize potential production and average potential yield in Northeast China were 218.09 million tonnes and 6880.59 kg/ha. Thirteen prefecture-level cities had maize potential production of more than 7 million tonnes, and 11 cities had maize potential yields of more than 8000 kg/ha. (3) During 2015-2050, the total maize potential production and average yield decreased by around 23 million tonnes and 700 kg/ha in Northeast China, respectively. (4) The maize potential production increased in 15 cities located in the plain areas over the 35 years. The potential yields increased in only nine cities, which were mainly located in the Sanjiang Plain and the southeastern regions. The results highlight the importance of coping with the future land-use changes actively, maintaining the balance of farmland occupation and compensation, improving the cropland quality, and ensuring food security in Northeast China.


Assuntos
Florestas , Zea mays , Agricultura , China , Cidades , Fazendas
2.
Artigo em Inglês | MEDLINE | ID: mdl-30987325

RESUMO

Maize yield has undergone obvious spatial and temporal changes in recent decades in Northeast China. Understanding how maize potential yield has changed over the past few decades and how large the gaps between potential and actual maize yields are is essential for increasing maize yield to meet increased food demand in Northeast China. In this study, the spatial and temporal dynamics of maize potential yield in Northeast China from 1990 to 2015 were simulated using the Global Agro-ecological Zones (GAEZ) model at the pixel level firstly. Then, the yield gaps between actual and potential yields were analyzed at city scale. The results were the following. (1) The maize potential yield decreased by about 500 kg/ha and the potential production remained at around 260 million tonnes during 1990-2000. From 2000 to 2015, the maize potential yield and production increased by approximately 1000 kg/ha and 80 million tonnes, respectively. (2) The maize potential yield decreased in most regions of Northeast China in the first decade, such as the center area (CA), south area (SA), southwest area (SWA), and small regions in northeast area (NEA), due to lower temperature and insufficient rainfall. The maize potential yield increased elsewhere. (3) The maize potential yield increased by more than 1000 kg/ha in the center area (CA) in the latter 15 years, which may be because of the climate warming and sufficient precipitation. The maize potential yield decreased elsewhere and Harbin in the center area (CA). (4) In 40 cities of Northeast China, the rates of actual yield to potential yield in 17 cities were higher than 80%. The actual yields only attained 50-80% of the potential yields in 20 cities. The gaps between actual and potential yields in Hegang and Dandong were very large, which need to be shrunk urgently. The results highlight the importance of coping with climate change actively, arranging crop structure reasonably, improving farmland use efficiency and ensuring food security in Northeast China.


Assuntos
Produtos Agrícolas/crescimento & desenvolvimento , Abastecimento de Alimentos/estatística & dados numéricos , Análise Espaço-Temporal , China , Grão Comestível/crescimento & desenvolvimento , Humanos , Modelos Teóricos , Zea mays
3.
Artigo em Inglês | MEDLINE | ID: mdl-30022018

RESUMO

During the last 40 years, the quantity and spatial patterns of farmland in Western Jilin have changed dramatically, which has had a great impact on soybean production potential. This study used one of the most advanced crop production potential models, the Global Agro-Ecological Zones model, to calculate the soybean production potential in Western Jilin based on meteorological, topography, soil and land use data, and analyzed the impact of farmland change on soybean production potential during 1975⁻2013. The main conclusions were the following: first, the total soybean production potential in Western Jilin in 2013 was 8.92 million tonnes, and the average soybean production potential was 1612 kg/ha. The production potential of eastern area was higher than the other areas of Western Jilin. Second, farmland change led to a growth of 3.30 million tonnes in soybean production potential between 1975 and 2000, and a decrease of 1.03 million tonnes between 2000 and 2013. Third, taking account of two situations of farmland change, the conversion between dryland and other categories, and the change of irrigation percentage led to the total soybean production potential in Western Jilin increased by 2.31 and only 0.28 million tonnes respectively between 1975 and 2000, and increased by 0.12 and 0.29 million tonnes respectively between 2000 and 2013. In general, the increase of soybean potential production was mainly due to grassland and woodland reclamation. The results of this study would be a good guideline for protecting safe baseline of farmland, managing land resources, and ensuring continuity and stability of soybean supply and food security.


Assuntos
Produção Agrícola/história , Produção Agrícola/tendências , Fazendas/história , Fazendas/tendências , Glycine max , China , Produção Agrícola/estatística & dados numéricos , Fazendas/estatística & dados numéricos , Previsões , História do Século XX , História do Século XXI
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