Contributions of Climate Change, Vegetation Growth, and Elevated Atmospheric CO2 Concentration to Variation in Water Use Efficiency in Subtropical China

Xiao, Jianru; Xie, Binggeng; Zhou, Kaichun; Li, Junhan; Xie, Jing; Liang, Chao

doi:10.3390/rs14174296

Cited by 15 publications

(3 citation statements)

References 63 publications

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“…From the measurement results, the 10 plots have different canopy structures. Xiao et al (2022) explained that the condition of crown cover can be beneficial for the growth of certain species in the vegetation community (tolerant species) and detrimental to other species (intolerant species). Canopy closure also affects the microclimate changes in plants.…”

Section: Environmental Parametersmentioning

confidence: 99%

Vegetation Structure and Composition in the Nusa Gede Panjalu Nature Reserve Area, Ciamis, Indonesia

Adnan

Supriatna

Kurniawati

2023

Quagga

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The Nusa Gede Panjalu Nature Reserve in Ciamis Regency is a conservation area that holds a variety of biodiversity and within it is a natural tourism area. It is feared that the existence of natural tourism areas will result in damage caused by human activities. This study aims to analyze the structure and composition of vegetation as well as environmental factors that affect vegetation growth in the Nusa Gede Panjalu Nature Reserve area. The method used in this study is the line transect method with sampling using quadrat. The data obtained were analyzed using the Importance Value Index (IVI), the index of Shannon-Wiener, and the index of Evenness. The results showed that the structure and composition of the vegetation in the Nusa Gede Panjalu Nature Reserve consisted of 416 individuals divided into 29 species. The plant species with the highest Importance Value Index (IVI) in the seedling category were Dysoxylum densiflorum (28.73%), the pole category Litsea noronhae (23.72%) and for the tree category Dysoxylum densiflorum (49.12%). The diversity index obtained is included in the moderate level of diversity. Environmental factors affecting the growth of vegetation in the Nusa Gede Nature Reserve are the temperature, humidity, light intensity, and pH with an average temperature of 28.4°C, humidity of 85.1% light intensity of 1070.1 lux, and pH of 6.3.

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Section: Environmental Parametersmentioning

confidence: 99%

Vegetation Structure and Composition in the Nusa Gede Panjalu Nature Reserve Area, Ciamis, Indonesia

Adnan

Supriatna

Kurniawati

2023

Quagga

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“…Jasechko et al made water resource predictions indicating that improvements in the simulation of biological flux should be prioritized in the development of climate models [26]. Li et al showed that LAI was the major factor driving changes in WUE [17]; other important factors affecting changes in WUE included the atmospheric CO 2 concentration and VPD [27]. Wei et al found that soil moisture was a key factor affecting changes in EPE [23].…”

Section: Introductionmentioning

confidence: 99%

Spatial and Temporal Variation in Water Use Efficiency and Ecosystem Photosynthetic Efficiency in Central Asia

Yahefujiang,

Zou,

Ding

et al. 2023

Remote Sensing

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Ecosystem water use efficiency (WUE) and ecosystem photosynthetic efficiency (EPE) are key indicators in studies of the carbon–water cycle in terrestrial ecosystems. Analyses of WUE and EPE can enhance our understanding of the relationship between ecosystem light use efficiency and WUE. Although several studies of individual indexes (i.e., either WUE or EPE) have been conducted, analyses of variation in both WUE and EPE, as well as their relationships, have rarely been conducted. Here, we analyzed spatial and temporal variation in WUE and EPE in Central Asia. Specifically, time trend analysis was conducted to characterize temporal and spatial changes in WUE and EPE in Central Asia from 2001 to 2020 at different altitudes and latitudes. Pearson correlation analysis was used to characterize the effects of precipitation and temperature on WUE and EPE. WUE decreased and EPE increased in Central Asia over the 20-year study period; this might have been due to interannual variations in precipitation and temperature. WUE was highest in August, and EPE was highest in June and July. Substantial spatial heterogeneity in WUE and EPE was observed; WUE was highly variable in Central Asia as well as in western and southern Central Asia. Major changes in EPE were observed in northern, eastern, and southern Central Asia. We also found that both WUE and EPE decreased with the increase in altitude. WUE was positively correlated with temperature and negatively correlated with precipitation, whereas EPE was positively correlated with both temperature and precipitation. The increase in photosynthetic efficiency might be one of the main factors contributing to increases in ecosystem productivity in arid environments. The temporal and spatial variation in WUE and EPE observed in our study will aid ecosystem research, providing a reliable theoretical basis for ecosystem research in areas with scarce large-scale data, integrated water resources management, and ecosystem restoration efforts. Our findings also enhance our understanding of the terrestrial carbon–water cycle and have implications for predicting ecosystem responses to climate change. The results of this study provide insights that will aid studies of the terrestrial carbon–water cycle under the background of climate change. It is of great significance to further study the carbon water cycle in the future.

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“…The Leaf Area Index (LAI) is a crucial biophysical parameter of vegetation [2]. It is an essential input parameter for vegetation dynamics, phenology monitoring, crop yield estimation, and climate model [3][4][5][6], and LAI can also detect changes in climate and land use/cover [6,7].…”

Section: Introductionmentioning

confidence: 99%

Spatio-Temporal Variability Analysis of Vegetation Dynamics in China from 2000 to 2022 Based on Leaf Area Index: A Multi-Temporal Image Classification Perspective

Yan

et al. 2023

Remote Sensing

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Leaf Area Index (LAI) is one of the most important biophysical parameters of vegetation, and its dynamic changes can be used as a reflective indicator and differentiation basis of vegetation function. In this study, a VCA–MLC (Vertex Component Analysis–Maximum Likelihood Classification) algorithm is proposed from the perspective of multi-temporal satellite LAI image classification to monitor and quantify the spatial and temporal variability of vegetation dynamics in China since 2000. The algorithm extracts the vegetation endmembers from 46 multi-temporal images of MODIS LAI in 2011 without the aid of other a priori knowledge and uses the maximum likelihood classification method to select the categories that satisfy the requirements of the number of missing periods, absolute distance, and relative distance for the rest pixels to be classified, ultimately dividing the vegetation area of China into 10 vegetation zones called China Vegetation Functional Zones (CVFZ). CVFZ outperforms MCD12Q1 and CLCD land cover datasets in the overall differentiation of vegetation functions and can be used synergistically with other land cover datasets. In this study, CVFZ is used to cut the constant vegetation-type pixels of MCD12Q1 during 2001–2022. The results of the LAI mean time series decomposition of each subregion using the STL (Seasonal-Trend Decomposition based on Loess) method show that the rate of vegetation greening ranges from 9.02 × 10−4 m2m−2yr−1 in shrubland subregions to 2.34 × 10−2 m2m−2yr−1 in savanna subregions. In relative terms, the average greening speed of forests is moderate, and savannas tend to have the fastest average greening speed. The greening speed of grasslands and croplands in different zones varies widely. In contrast, the average greening speed of shrublands is the slowest. In addition, CVFZ detected grasslands with one or two phenological cycles, broadleaf croplands with one or two phenological cycles, and shrublands with no apparent or one phenological cycle.

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Contributions of Climate Change, Vegetation Growth, and Elevated Atmospheric CO2 Concentration to Variation in Water Use Efficiency in Subtropical China

Cited by 15 publications

References 63 publications

Vegetation Structure and Composition in the Nusa Gede Panjalu Nature Reserve Area, Ciamis, Indonesia

Vegetation Structure and Composition in the Nusa Gede Panjalu Nature Reserve Area, Ciamis, Indonesia

Spatial and Temporal Variation in Water Use Efficiency and Ecosystem Photosynthetic Efficiency in Central Asia

Spatio-Temporal Variability Analysis of Vegetation Dynamics in China from 2000 to 2022 Based on Leaf Area Index: A Multi-Temporal Image Classification Perspective

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