Analyzing the spatiotemporal pattern and driving factors of wetland vegetation changes using 2000‐2019 time-series Landsat data

Zhang, Meng; Lin, Hui; Long, Xiangren; Cai, Yaotong

doi:10.1016/j.scitotenv.2021.146615

Cited by 62 publications

(30 citation statements)

References 60 publications

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“…In these above zones, the rapid urbanization process, population growth rate and economic development had led to the intensification of the contradiction between man and land (Han et al,2021). Although certain protection measures had been taken, the speed of social and economic development far exceeded the pace of ecological and environmental protection, so the change of vegetation cover was not obvious (Zhang et al,2021). After 2000, the vegetation NDVI in most sub-regions showed an increasing trend, which was consistent with previous studies.…”

Section: Migration Trajectory Of Gravity Centerssupporting

confidence: 89%

Quantitatively determine the dominant driving factors of the spatial-temporal changes of vegetation-impacts of global change and human activity

wang

Ping

Wang

et al. 2022

Preprint

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The differences of spatial-temporal distribution patterns and dominant driving factors of vegetation evolution in different regions and different historical periods were not clearly. Therefore, this study introduced the gravity center model and geodetector to analyze the spatial-temporal change characteristics and dominant driving factors of vegetation NDVI in China during 1981-2019 from the perspective of geographic divisions. Results showed that: (1) During 1981-2019, the average vegetation coverage in China, as a whole, showed an increasing trend and zones with obviously increasing vegetation NDVI were mainly distributed in the middle reaches of the Yellow River basin and the upper reaches of the Yangtze River. (2) During 1981-2019, the gravity centers of vegetation NDVI, nationally, were mainly concentrated in Yan'an City and Tongchuan City, showing a southward migration trend as a whole, which indicates that the increment and growth rates of the southern were greater than those of the northern part. (3) The growth of vegetation in southern China was primarily affected by temperature, while that of northern China was largely influenced by precipitation. (4) Specific factors, including land use, precipitation and soil types exerted significant influences on the vegetation NDVI, and their interaction could enhance the influence of single factor.

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Section: Migration Trajectory Of Gravity Centerssupporting

confidence: 89%

Quantitatively determine the dominant driving factors of the spatial-temporal changes of vegetation-impacts of global change and human activity

wang

Ping

Wang

et al. 2022

Preprint

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“…For example, plants in high-elevation areas are strongly affected by temperature, light intensity, CO 2 concentration, and microclimatic conditions (Bresson et al 2011 ; Sun et al 2016a , b ). Epiphytes are significantly affected by water availability and light conditions (Sun et al 2014 ), whereas wetland plants are generally largely affected by temperature, CO 2 concentration, water, sediment environment, among others (Zhang et al 2021 ). In our study, the photosynthetic and transpiration rates of S. tabernaemontani decreased significantly under increasing temperatures (Fig.…”

Section: Discussionmentioning

confidence: 99%

Responses of leaf hydraulic traits of Schoenoplectus tabernaemontani to increasing temperature and CO2 concentrations

et al. 2022

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Background Against the background of a changing climate, the responses of functional traits of plateau wetland plants to increasing temperatures and CO2 concentrations need to be understood. Hydraulic traits are the key for plants to maintain their ecological functions and affect their growth and survival. However, few studies have comprehensively considered the response strategies of wetland plants' hydraulic traits to environmental changes in the context of water and matter transport, loss, and retention. According to the latest IPCC prediction results, we performed experiments under increased temperature (2 °C) and CO2 levels (850 μmol/mol) in an artificial Sealed-top Chamber (STC) to investigate the responses of the hydraulic characteristics of Schoenoplectus tabernaemontani, the dominant species in plateau wetlands in China. Results Compared with the CK group, net photosynthetic rate, transpiration rate, stomatal length, cuticle thickness, vascular bundle length, vascular bundle width, and vascular bundle area of S. tabernaemontani in the ET group were significantly reduced, whereas stomatal density and vein density increased significantly. Compared with the CK group, the hydraulic traits of S. tabernaemontani in the EC group were reduced considerably in stomatal length and cuticle thickness but increased dramatically in stomatal density, and there were no significant differences between other parameter values and the control group. Net photosynthetic rate was significantly positively correlated with stomatal length, cuticle thickness, and vascular bundle length, and stomatal conductance was significantly positively correlated with cuticle thickness. The transpiration rate was significantly positively correlated with cuticle thickness, epidermal cell area, vascular bundle length, vascular bundle width, and vascular bundle area. Regarding the hydraulic traits, there was a significant negative correlation between stomatal density and stomatal length, or cuticle thickness, and a significant positive correlation between the latter two. The epidermal cell area was significantly positively correlated with epidermal thickness, vascular bundle length, vascular bundle width, and vascular bundle area. Conclusions Increased temperature and CO2 levels are not conducive to the photosynthetic activity of S. tabernaemontani. Photosynthetic rate, stomatal density and size, vein density, epidermal structure size, and vascular bundle size play an essential role in the adaptation of this species to changes in temperature and CO2 concentration. In the process of adaptation, hydraulic traits are not isolated from each other, and there is a functional association among traits. This study provide a scientific basis for the management and protection of plateau wetlands.

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“…Among those methods, BFAST overcomes the weaknesses of DBEST by improving the estimation of seasonal changes. Utilizing an ordinary least squares moving sum (OLS-MOSUM) to define the position of the breakpoint in the time series, and the Bayesian information criterion to determine the optimal number of breakpoints, the BFAST algorithm stands out due to its capacity to effectively interpret seasonal data; it has been successfully applied in many fields [36][37][38][39][40]. In terms of vegetation-related studies, de Jong et al (2011) [41] applied BFAST to detect vegetation changes in shrubland and grassland areas, while Verbesselt et al (2012) [42] and Saatchi et al (2012) [43] studied vegetation drought in Somalia and the Amazon rainforest, respectively.…”

Section: Introductionmentioning

confidence: 99%

Vertical Differences in the Long-Term Trends and Breakpoints of NDVI and Climate Factors in Taiwan

2021

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This study explored the long-term trends and breakpoints of vegetation, rainfall, and temperature in Taiwan from overall and regional perspectives in terms of vertical differences from 1982 to 2012. With time-series Advanced Very-High-Resolution Radiometer (AVHRR) normalized difference vegetation index (NDVI) data and Taiwan Climate Change Estimate and Information Platform (TCCIP) gridded monthly climatic data, their vertical dynamics were investigated by employing the Breaks for Additive Seasonal and Trend (BFAST) algorithm, Pearson’s correlation analysis, and the Durbin–Watson test. The vertical differences in NDVI values presented three breakpoints and a consistent trend from positive (1982 to 1989) to negative at varied rates, and then gradually increased after 2000. In addition, a positive rainfall trend was discovered. Average and maximum temperature had similar increasing trends, while minimum temperature showed variations, especially at higher altitudes. In terms of regional variations, the vegetation growth was stable in the north but worse in the central region. Higher elevations revealed larger variations in the NDVI and temperature datasets. NDVI, along with average and minimum temperature, showed their largest changes earlier in higher altitude areas. Specifically, the increasing minimum temperature direction was more prominent in the mid-to-high-altitude areas in the eastern and central regions. Seasonal variations were observed for each region. The difference between the dry and wet seasons is becoming larger, with the smallest difference in the northern region and the largest difference in the southern region. Taiwan’s NDVI and climatic factors have a significant negative correlation (p < 0.05), but the maximum and minimum temperatures have significant positive effects at low altitudes below 500 m. The northern and central regions reveal similar responses, while the south and east display different feedbacks. The results illuminate climate change evidence from assessment of the long-term dynamics of vegetation and climatic factors, providing valuable references for establishing correspondent climate-adaptive strategies in Taiwan.

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Analyzing the spatiotemporal pattern and driving factors of wetland vegetation changes using 2000‐2019 time-series Landsat data

Cited by 62 publications

References 60 publications

Quantitatively determine the dominant driving factors of the spatial-temporal changes of vegetation-impacts of global change and human activity

Quantitatively determine the dominant driving factors of the spatial-temporal changes of vegetation-impacts of global change and human activity

Responses of leaf hydraulic traits of Schoenoplectus tabernaemontani to increasing temperature and CO2 concentrations

Vertical Differences in the Long-Term Trends and Breakpoints of NDVI and Climate Factors in Taiwan

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