Dataset Information

Temporal and spatial variation of extreme temperatures in an agro-pastoral ecotone of northern China from 1960 to 2016.

ABSTRACT: The agro-pastoral ecotone of northern China is one of the areas most sensitive to global temperature change. To analyze the temporal and spatial trends of extreme temperature events in this area, we calculated the values of 16 extreme-temperature indices from 1960 to 2016 based on data from 45 national meteorological stations. We found that the coldest-temperature indices decreased significantly and the warmest-temperature indices increased significantly. The warming of night temperatures contributed more than warming of day temperatures to the overall warming trend. In addition, the warm-temperature indices appeared to be increasing since the late 1980s and early 1990s. Overall, though the four extremal indices showed an increasing trend, the rate of change in the minimum temperature was greater than that of the maximum temperature; thus, the minimum temperature contributed most strongly to the overall temperature increases. The growing season is being prolonged in higher-elevation areas, but vegetation maturation in lower-elevation areas has been accelerated by the high temperatures, potentially leading to a shorter growing season at low altitudes. However, the impacts of land-use changes caused by human activities on the temperature increases will require additional study.

SUBMITTER: Wang X

PROVIDER: S-EPMC5993746 | biostudies-literature | 2018 Jun

REPOSITORIES: biostudies-literature

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Temporal and spatial variation of extreme temperatures in an agro-pastoral ecotone of northern China from 1960 to 2016.

Wang Xuyang X Li Yuqiang Y Chen Yinping Y Lian Jie J Luo Yongqing Y Niu Yayi Y Gong Xiangwen X Yu Peidong P

Scientific reports 20180608 1

The agro-pastoral ecotone of northern China is one of the areas most sensitive to global temperature change. To analyze the temporal and spatial trends of extreme temperature events in this area, we calculated the values of 16 extreme-temperature indices from 1960 to 2016 based on data from 45 national meteorological stations. We found that the coldest-temperature indices decreased significantly and the warmest-temperature indices increased significantly. The warming of night temperatures contri ...[more]

PMID: 29884865

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Project description:Being subject to climate change and human intervention, the land-use pattern in the agro-pastoral ecotone of Northern China has undergone complex changes over the past few decades, which may jeopardize the provision of ecosystem services. Thus, for sustainable land management, ecosystem services should be evaluated and monitored. In this study, based on Landsat TM/ETM data, we quantitatively evaluated the losses of ecosystem service values (ESV) in three sections of the agro-pastoral ecotone from 1980-2015. The results were as follows: (1) the main characteristic of the land conversions was that a large area of grassland was converted into cultivated land in the agro-pastoral ecotone; (2) on the spatial scale, the ESV losses of the agro-pastoral ecotone can be called an "inclined surface" in the direction of the northeast to southwest, and the northeastern section of the agro-pastoral ecotone lost more ESV than the middle and northwest sections (p < 0.05), on the temporal scale, the order of losses was 1990-2000 > 1980-1990 > 2000-2015; (3) the agro-pastoral ecotone lost more ESV, which was mainly due to four kinds of land conversion, which were grassland that was transformed into cultivated land, grassland transformed into unused land, grassland transformed into built-up areas, and cultivated land transformed into built-up areas; (4) although these land conversions were curbed after the implementation of protection policies at the end of the 1990s, due to reduced precipitation and increasing temperatures, the agro-pastoral ecotone will face a more severe situation in the future; and, (5) during the period of 1990-2015, the overall dynamic processes of increasing population gradually expanded to the sparsely populated pastoral area. Therefore, we believe that human interventions are the main cause of ecological deterioration in the agro-pastoral ecotone. This study provides references for fully understanding the regional differences in the ecological and environmental effects of land use change and it helps to objectively evaluate ecological civilization construction in the agro-pastoral ecotone of Northern China.

Project description:Land use land cover (LULC) changes frequently in ecotones due to the large climate and soil gradients, and complex landscape composition and configuration. Accurate mapping of LULC changes in ecotones is of great importance for assessment of ecosystem functions/services and policy-decision support. Decadal or sub-decadal mapping of LULC provides scenarios for modeling biogeochemical processes and their feedbacks to climate, and evaluating effectiveness of land-use policies, e.g. forest conversion. However, it remains a great challenge to produce reliable LULC maps in moderate resolution and to evaluate their uncertainties over large areas with complex landscapes. In this study we developed a robust LULC classification system using multiple classifiers based on MODIS (Moderate Resolution Imaging Spectroradiometer) data and posterior data fusion. Not only does the system create LULC maps with high statistical accuracy, but also it provides pixel-level uncertainties that are essential for subsequent analyses and applications. We applied the classification system to the Agro-pasture transition band in northern China (APTBNC) to detect the decadal changes in LULC during 2003-2013 and evaluated the effectiveness of the implementation of major Key Forestry Programs (KFPs). In our study, the random forest (RF), support vector machine (SVM), and weighted k-nearest neighbors (WKNN) classifiers outperformed the artificial neural networks (ANN) and naive Bayes (NB) in terms of high classification accuracy and low sensitivity to training sample size. The Bayesian-average data fusion based on the results of RF, SVM, and WKNN achieved the 87.5% Kappa statistics, higher than any individual classifiers and the majority-vote integration. The pixel-level uncertainty map agreed with the traditional accuracy assessment. However, it conveys spatial variation of uncertainty. Specifically, it pinpoints the southwestern area of APTBNC has higher uncertainty than other part of the region, and the open shrubland is likely to be misclassified to the bare ground in some locations. Forests, closed shrublands, and grasslands in APTBNC expanded by 23%, 50%, and 9%, respectively, during 2003-2013. The expansion of these land cover types is compensated with the shrinkages in croplands (20%), bare ground (15%), and open shrublands (30%). The significant decline in agricultural lands is primarily attributed to the KFPs implemented in the end of last century and the nationwide urbanization in recent decade. The increased coverage of grass and woody plants would largely reduce soil erosion, improve mitigation of climate change, and enhance carbon sequestration in this region.

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Dataset Information

Temporal and spatial variation of extreme temperatures in an agro-pastoral ecotone of northern China from 1960 to 2016.

Publications

Temporal and spatial variation of extreme temperatures in an agro-pastoral ecotone of northern China from 1960 to 2016.

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