Based on the surveys and the statistic data during 1980-2003, the variation character of grain yield per unit area in Northeast China and its main factors have been discussed by the methods of statistics and grey corr...Based on the surveys and the statistic data during 1980-2003, the variation character of grain yield per unit area in Northeast China and its main factors have been discussed by the methods of statistics and grey correlation analysis. The results show that: 1) the grain yield per unit area has been taking on an increasing trend in the recent 20 years. It increased from 2519.80kg/ha in 1980 to 4216.11kg/ha in 2003, with an increasing rate of 67.32%; 2) the variation of grain yield per unit area is considerably prominent and its range is also very great, with the maximal increase rate of 42.59% and maximal decrease rate of 21.13%, respectively, which are far above the whole Chinese average level; 3) the variation of main crops' yield per unit area is remarkable, which takes on the character that the yield of corn is much higher than that of soybean and rice; and 4) the grey correlation analysis shows that the most important factors impacting the variation of grain yield per unit area are the total power of agricultural machinery, the consumption of chemical fertilizer and effective irrigated area. However, the influence of natural disaster and income level should not be ignored. Effective ways to improve grain yield per unit area are to construct farmland improvement groundwork, reclaim the middle- and low-yield farmland, etc.展开更多
Aims Monitoring and assessing diversity change at a large scale is important for any meaningful biodiversity conservation and management.Spatial analysis techniques can provide information about different aspects of d...Aims Monitoring and assessing diversity change at a large scale is important for any meaningful biodiversity conservation and management.Spatial analysis techniques can provide information about different aspects of diversity distribution including change.We applied some common spatial analysis methods and additive partitioning of species diversity in the Northeast China Transect as a case study to show how to characterize the distribution and change of tree diversity in this area from different perspectives.Methods The field data were collected from the permanent plots conducted every 4 km.The additive partitioning of species diversity was used to characterize the diversity of tree species at different scales.Moran’s I was used for identifying the spatial scale of autocorrelation,lacunarity was studied for diversity patch contagion and dispersion and spectral entropy was used for assessing the overall spatial distribution.Important findings Datacollectedfrom 1986 to 1994 indicate that the change of adiversity was not significant in the study area,but the change of b diversity was significant.The percentage of a diversity in total diversity(c)increased from 14.2 to 17.2%,and the percentage of b diversity decreased from 85.8 to 82.8%.For both a and b diversities,the scale of spatial autocorrelation decreased at the scale of 25–40 km and increased around 15–20 and 200 km.The lacunarity of a diversity decreased significantly and there wasasuddenchangeat the scale of 56–68km,butthelacunarity of b diversity increased across scales.The spectral entropy decreased slightlyina diversityandremainedsimilarforb diversity.Byusingspatial analysis,we can monitor the diversity change over a large area and also assess the effectiveness of the current conservation strategies.展开更多
基金Under the auspices of the National Natural Science Foundation of China (No. 40601027)
文摘Based on the surveys and the statistic data during 1980-2003, the variation character of grain yield per unit area in Northeast China and its main factors have been discussed by the methods of statistics and grey correlation analysis. The results show that: 1) the grain yield per unit area has been taking on an increasing trend in the recent 20 years. It increased from 2519.80kg/ha in 1980 to 4216.11kg/ha in 2003, with an increasing rate of 67.32%; 2) the variation of grain yield per unit area is considerably prominent and its range is also very great, with the maximal increase rate of 42.59% and maximal decrease rate of 21.13%, respectively, which are far above the whole Chinese average level; 3) the variation of main crops' yield per unit area is remarkable, which takes on the character that the yield of corn is much higher than that of soybean and rice; and 4) the grey correlation analysis shows that the most important factors impacting the variation of grain yield per unit area are the total power of agricultural machinery, the consumption of chemical fertilizer and effective irrigated area. However, the influence of natural disaster and income level should not be ignored. Effective ways to improve grain yield per unit area are to construct farmland improvement groundwork, reclaim the middle- and low-yield farmland, etc.
基金supported by the University of California Agricultural Experimental Station and School of Agricultural and Environmental Sciences in Alabama A&M University.
文摘Aims Monitoring and assessing diversity change at a large scale is important for any meaningful biodiversity conservation and management.Spatial analysis techniques can provide information about different aspects of diversity distribution including change.We applied some common spatial analysis methods and additive partitioning of species diversity in the Northeast China Transect as a case study to show how to characterize the distribution and change of tree diversity in this area from different perspectives.Methods The field data were collected from the permanent plots conducted every 4 km.The additive partitioning of species diversity was used to characterize the diversity of tree species at different scales.Moran’s I was used for identifying the spatial scale of autocorrelation,lacunarity was studied for diversity patch contagion and dispersion and spectral entropy was used for assessing the overall spatial distribution.Important findings Datacollectedfrom 1986 to 1994 indicate that the change of adiversity was not significant in the study area,but the change of b diversity was significant.The percentage of a diversity in total diversity(c)increased from 14.2 to 17.2%,and the percentage of b diversity decreased from 85.8 to 82.8%.For both a and b diversities,the scale of spatial autocorrelation decreased at the scale of 25–40 km and increased around 15–20 and 200 km.The lacunarity of a diversity decreased significantly and there wasasuddenchangeat the scale of 56–68km,butthelacunarity of b diversity increased across scales.The spectral entropy decreased slightlyina diversityandremainedsimilarforb diversity.Byusingspatial analysis,we can monitor the diversity change over a large area and also assess the effectiveness of the current conservation strategies.
