Greening and browning of the coastal areas in mainland China: Spatial heterogeneity, seasonal variation and its influential factors

Meng, Zhibin; Liu, Min; Gao, Chanchan; Zhang, Yang; She, Qiannan; Long, Lingbo; Tu, Yue; Yang, Yixuan

doi:10.1016/j.ecolind.2019.105888

Cited by 27 publications

(18 citation statements)

References 74 publications

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“…For areas far from the center, there was enough land for ecological use even with heavy human impacts. For different countries, the "green" and "brown" trend difference can be attributed to multiple factors, such as economic structure, population changes, policy making, and climatic changes [10,11,[67][68][69]. For example, THA had the highest green trend due to dependence on the agricultural economy, especially in urban and peri-urban areas [70].…”

Section: Influential Factors Of Spatial Differencementioning

confidence: 99%

“…A smaller time lag effect and larger duration for a MODIS/NDVI increase might indicate a better ecological and environmental adjusting ability to the human activities. Apart from the above-mentioned factors, different protection schemes or policies of vegetation and concepts of urban planning can also result in this difference [68,69]. For example, in SGP, the rooftop garden is popular and can make urban areas greener [71], and BRN and SGP always have the high-level rate of urban forest cover with little construction in recent years.…”

Section: Influential Factors Of Spatial Differencementioning

confidence: 99%

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Mapping Impacts of Human Activities from Nighttime Light on Vegetation Cover Changes in Southeast Asia

Xia

Cheng

2021

Land

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It is commonly believed that the impacts of human activities have decreased the natural vegetation cover, while some promotion of the vegetation growth has also been found. In this study, negative or positive correlations between human impacts and vegetation cover were tested in the Southeast Asia (SEA) region during 2012–2018. The Visible Infrared Imaging Radiometer Suite—Day/Night Band (VIIRS/DNB) nocturnal data were used as a measure of human activities and the moderate resolution imaging spectroradiometer (MODIS)/normalized difference vegetation index (NDVI) diurnal data were used as a measure of vegetation cover. The temporal segmentation method was introduced to calculate features of two sets of time series with spatial resolution of about 500 m, including the overall trend, maximum trend, start date, and change duration. The regions with large variation in human activities (V-change region) were first extracted by the Gaussian fitted method, and 8.64% of the entire SEA (VIIRS overall trend <-0.2 or >0.4) was set as the target analysis area. According to statistics, the average overall VIIRS trend for the V-change region in SEA was about 2.12, with a slight NDVI increment. The time lag effect was also found between vegetation cover and human impacts change, with an average of 10.26 months. Our results indicated a slight green overall trend in the SEA region over the most recent 7 years. The spatial pattern of our trend analysis results can be useful for vegetation management and regional planning.

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Section: Influential Factors Of Spatial Differencementioning

confidence: 99%

Section: Influential Factors Of Spatial Differencementioning

confidence: 99%

Mapping Impacts of Human Activities from Nighttime Light on Vegetation Cover Changes in Southeast Asia

Xia

Cheng

2021

Land

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“…Therefore, exploring the spatiotemporal pattern of vegetation greenness and discussing the driving role of climate factors has become one of the main topics of current global change research [1,7,8]. Many previous studies have shown that vegetation greening varies with climate change globally [1,9] and regionally [10,11]. However, the underlying mechanisms of longitudinal and latitudinal changes in vegetation greenness related to climate change are not yet well understood in arid and semi-arid areas.…”

Section: Introductionmentioning

confidence: 99%

“…However, this trend in vegetation greening is spatially and temporally heterogeneous [14]. Moreover, the greenness of vegetation in Central Asia [10], East Asia [15], and China [11,16] has also increased. In contrast, browning occurred in northern Eurasia [7], southwestern United States [17], and Central Asia [18].…”

Section: Introductionmentioning

confidence: 99%

Vegetation Greenness Variations and Response to Climate Change in the Arid and Semi-Arid Transition Zone of the Mongo-Lian Plateau during 1982–2015

et al. 2021

Remote Sensing

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Vegetation greenness dynamics in arid and semi-arid regions are sensitive to climate change, which is an important phenomenon in global climate change research. However, the driving mechanism, particularly for the longitudinal and latitudinal changes in vegetation greenness related to climate change, has been less studied and remains poorly understood in arid and semi-arid areas. In this study, we investigated changes in vegetation greenness and the vegetation greenness line (the mean growing season normalized difference vegetation index (NDVI) = 0.1 contour line) and its response to climate change based on AVHRR-GIMMS NDVI3g and the fifth and latest global climate reanalysis dataset from 1982 to 2015 in the arid and semi-arid transition zone of the Mongolian Plateau (ASTZMP). The results showed that the mean growing season NDVI increased from the central west to east, northeast, and southeast in ASTZMP. The vegetation greenness line migrated to the desert during 1982–1994, to the grassland during 1994–2005, and then to the desert during 2005–2015. Vegetation greenness was positively correlated with precipitation and negatively correlated with temperature. The latitudinal variation of the vegetation greenness line was mainly affected by the combination of precipitation and temperature, while the longitudinal variation was mainly affected by precipitation. In summary, precipitation was a key climatic factor driving rapid changes in vegetation greenness during the growing season of the transition zone. These results can provide meaningful information for research on vegetation coverage changes in arid and semi-arid regions.

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“…The terrestrial ecosystem plays a vital role in sequestering carbon. As an important part of the terrestrial ecosystem, forests cover about 31% of the earth's surface area (4.06 billion ha) [1], and they have irreplaceable values for their ability to manage biodiversity, store carbon, and provide other ecosystem services [2]. Forest ecosystems are enormous carbon pools and hold almost 662 (GT C) in 2020 [1], therefore playing a great role in mitigating climate change [3].…”

Section: Introductionmentioning

confidence: 99%

Disentangling Climatic Factors and Human Activities in Governing the Old and New Forest Productivity

Chen

Wen

et al. 2021

Remote Sensing

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Forest ecosystem plays a vital role in the global carbon cycle and maintaining climate stability. However, how net primary productivity (NPP) dynamics of different stand ages of forest respond to climatic change and residual (being other climate factors or human activities) still remain unclear. In this study, firstly, forests are divided into two categories based on their stand age: forests appeared before appeared before the research period (Fold), and forests appeared during the research period (Fnew). Secondly, we improved a quantitative method of basic partial derivatives to disentangle the relative contributions of climatic factors, other climate factors, and human activities to the NPP of Fold and Fnew. Then, different scenarios were simulated to identify the dominant drivers for forest restoration and degradation. In this study, we hypothesized the residual of Fold was other climate factors rather than human activities. Our results revealed that from 2000 to 2019, Fold and Fnew of NPP in Yangtze River Basin showed a significant increment trend and precipitation was the major positive contributor among all of the climatic factors. We found that, in Fold, climate change and other climate factors contributed 9.77% and 28.33%, respectively, in explaining NPP. This finding unsupported our initial hypothesis and implied that residuals should be human activities for Fold. Furthermore, we found that human activities dominate either restoration or degradation of Fnew. This result may be due to the attenuated human disturbances and strengthened forest management, such as ecological policies, forest tending, closing the land for reforestation, etc. Therefore, based on disentangling the two types of factors, we concluded that human activities govern the forest change, and imply that the environment-friendly forest managements may favorite to improving the forest NPP against the impacts of climate change. Thus, effective measures and policies are suggested implement in controlling forest degradation in facing climate change.

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Greening and browning of the coastal areas in mainland China: Spatial heterogeneity, seasonal variation and its influential factors

Cited by 27 publications

References 74 publications

Mapping Impacts of Human Activities from Nighttime Light on Vegetation Cover Changes in Southeast Asia

Mapping Impacts of Human Activities from Nighttime Light on Vegetation Cover Changes in Southeast Asia

Vegetation Greenness Variations and Response to Climate Change in the Arid and Semi-Arid Transition Zone of the Mongo-Lian Plateau during 1982–2015

Disentangling Climatic Factors and Human Activities in Governing the Old and New Forest Productivity

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