Quantifying the lagged effects of climate factors on vegetation growth in 32 major cities of China

Vegetation fluctuation is sensitive to climate change, and this response exhibits a time lag. Traditionally, scholars estimated this lag effect by considering the immediate prior lag (e.g., where vegetation in the current month is impacted by the climate in a certain prior month) or the lag accumulation (e.g., where vegetation in the current month is impacted by the last several months). The essence of these two methods is that vegetation growth is impacted by climate conditions in the prior period or several consecutive previous periods, which fails to consider the different impacts coming from each of those prior periods. Therefore, this study proposed a new approach, the weighted time-lag method, in detecting the lag effect of climate conditions coming from different prior periods. Essentially, the new method is a generalized extension of the lag-accumulation method. However, the new method detects how many prior periods need to be considered and, most importantly, the differentiated climate impact on vegetation growth in each of the determined prior periods. We tested the performance of the new method in the Loess Plateau by comparing various lag detection methods by using the linear model between the climate factors and the normalized difference vegetation index (NDVI). The case study confirmed four main findings: (1) the response of vegetation growth exhibits time lag to both precipitation and temperature; (2) there are apparent differences in the time lag effect detected by various methods, but the weighted time-lag method produced the highest determination coefficient (R2) in the linear model and provided the most specific lag pattern over the determined prior periods; (3) the vegetation growth is most sensitive to climate factors in the current month and the last month in the Loess Plateau but reflects a varied of responses to other prior months; and (4) the impact of temperature on vegetation growth is higher than that of precipitation. The new method provides a much more precise detection of the lag effect of climate change on vegetation growth and makes a smart decision about soil conservation and ecological restoration after severe climate events, such as long-lasting drought or flooding.

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Vegetation change in response to climate factors and human activities on the Mongolian Plateau

PeerJ ◽

10.7717/peerj.7735 ◽

2019 ◽

Vol 7 ◽

pp. e7735 ◽

Cited By ~ 4

Author(s):

Meng Meng ◽

Ni Huang ◽

Mingquan Wu ◽

Jie Pei ◽

Jian Wang ◽

...

Keyword(s):

Correlation Analysis ◽

Human Factors ◽

Spatial Scale ◽

Trend Analysis ◽

Human Activities ◽

Growing Season ◽

Temporal Changes ◽

Climate Factors ◽

Mongolian Plateau ◽

Vegetation Growth

Background Vegetation in the Mongolian Plateau is very sensitive to climate change, which has a significant impact on the regulation of terrestrial carbon cycle. Methods We analyzed spatio-temporal changes of both growing season and the seasonal Normalized Difference Vegetation Index (NDVI) using simple linear trend analysis. Besides, correlation analysis was applied to explore the climate factors’ effects on vegetation growth at temporal and spatial scale. Potential effects of human factors on vegetation growth were also explored by residual trend analysis. Results The results indicated that vegetation growth showed a greening trend in the Mongolian Plateau over the past 30 years. At the temporal scale, the growing season NDVI showed an insignificant increasing trend (at a rate of 0.0003 yr−1). At the spatial scale, a large region (53.8% of the whole Mongolian Plateau) with an increasing growing season NDVI, was primarily located in the southern and northern parts of the plateau. The correlation analysis suggested that temperature and precipitation were the main limiting factors that affected vegetation growth in spring and the growing season, respectively. The residual trend analysis showed that human activities primarily stimulated the growth of grasslands and shrublands, while croplands displayed a decreasing trend due to human disturbances, implying that anthropogenic factors may lead to croplands abandonment in favor of grasslands restoration. Our results provided detailed spatial and temporal changes of vegetation growth, and explored how climate and human factors affected vegetation growth, which may offer baseline data and scientific suggestions for local land and resources management, and facilitate the sustainable development of the terrestrial ecosystems.

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Hurricanes Substantially Reduce the Nutrients in Tropical Forested Watersheds in Puerto Rico

Forests ◽

10.3390/f13010071 ◽

2022 ◽

Vol 13 (1) ◽

pp. 71

Author(s):

Jiamei Sun ◽

Xinyuan Wei ◽

Yu Zhou ◽

Catherine Chan ◽

Jiaojiao Diao

Keyword(s):

Puerto Rico ◽

Recovery Period ◽

Heavy Precipitation ◽

Nutrient Budget ◽

Nitrogen And Phosphorus ◽

Vegetation Growth ◽

Quantitative Understanding ◽

Lagged Effects ◽

One Year

Because nutrients including nitrogen and phosphorus are generally limited in tropical forest ecosystems in Puerto Rico, a quantitative understanding of the nutrient budget at a watershed scale is required to assess vegetation growth and predict forest carbon dynamics. Hurricanes are the most frequent disturbance in Puerto Rico and play an important role in regulating lateral nitrogen and phosphorus exports from the forested watershed. In this study, we selected seven watersheds in Puerto Rico to examine the immediate and lagged effects of hurricanes on nitrogen and phosphorous exports. Our results suggest that immediate surges of heavy precipitation associated with hurricanes accelerate nitrogen and phosphorus exports as much as 297 ± 113 and 306 ± 70 times than the long-term average, respectively. In addition, we estimated that it requires approximately one year for post-hurricane riverine nitrogen and phosphorus concentrations to recover to pre-hurricane levels. During the recovery period, the riverine nitrogen and phosphorus concentrations are 30 ± 6% and 28 ± 5% higher than the pre-hurricane concentrations on average.

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Periodic Relations between Terrestrial Vegetation and Climate Factors across the Globe

Remote Sensing ◽

10.3390/rs12111805 ◽

2020 ◽

Vol 12 (11) ◽

pp. 1805

Author(s):

Boyi Liang ◽

Hongyan Liu ◽

Xiaoqiu Chen ◽

Xinrong Zhu ◽

Elizabeth L. Cressey ◽

...

Keyword(s):

Time Lag ◽

Climate Factors ◽

Vegetation Types ◽

Terrestrial Vegetation ◽

Area Index ◽

Vegetation Growth ◽

Annual Cycles ◽

Vegetation Models ◽

Global Vegetation ◽

The Impact

In this paper, cross-spectrum analysis was used to verify the agreement of periodicity between the global LAI (leaf area index) and climate factors. The results demonstrated that the LAI of deciduous forests and permanent wetlands have high agreement with temperature, rainfall and radiation over annual cycles. A low agreement between the LAI and seasonal climate variables was observed for some of the temperate and tropical vegetation types including shrublands and evergreen broadleaf forests, possibly due to the diversity of vegetation and human activities. Across all vegetation types, the LAI demonstrated a large time lag following variation in radiation (>1 month), whereas relatively short lag periods were observed between the LAI and annual temperature (around 2 weeks)/rainfall patterns (less than 10 days), suggesting that the impact of radiation on global vegetation growth is relatively slow, which is in accord with the results of previous studies. This work can provide a benchmark of the phenological drivers in global vegetation, from the perspective of periodicity, as well as helping to parameterize and refine the DGVMs (Dynamic Global Vegetation Models) for different vegetation types.

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Changes in Vegetation Growth Dynamics and Relations with Climate in Inner Mongolia under More Strict Multiple Pre-Processing (2000–2018)

Sustainability ◽

10.3390/su12062534 ◽

2020 ◽

Vol 12 (6) ◽

pp. 2534 ◽

Cited By ~ 2

Author(s):

Dong He ◽

Xianglin Huang ◽

Qingjiu Tian ◽

Zhichao Zhang

Keyword(s):

Air Temperature ◽

Inner Mongolia ◽

Climatic Factors ◽

Vegetation Type ◽

Response Speed ◽

Dominant Factor ◽

Climate Factors ◽

Climate Type ◽

Local Climate ◽

Vegetation Growth

Inner Mongolia Autonomous Region (IMAR) is related to China’s ecological security and the improvement of ecological environment; thus, the vegetation’s response to climate changes in IMAR has become an important part of current global change research. As existing achievements have certain deficiencies in data preprocessing, technical methods and research scales, we correct the incomplete data pre-processing and low verification accuracy; use grey relational analysis (GRA) to study the response of Enhanced Vegetation Index (EVI) in the growing season to climate factors on the pixel scale; explore the factors that affect the response speed and response degree from multiple perspectives, including vegetation type, longitude, latitude, elevation and local climate type; and solve the problems of excessive ignorance of details and severe distortion of response results due to using average values of the wide area or statistical data. The results show the following. 1. The vegetation status of IMAR in 2000-2018 was mainly improved. The change rates were 0.23/10° N and 0.25/10° E, respectively. 2. The response speed and response degree of forests to climatic factors are higher than that of grasslands. 3. The lag time of response for vegetation growth to precipitation, air temperature and relative humidity in IMAR is mainly within 2 months. The speed of vegetation‘s response to climate change in IMAR is mainly affected by four major factors: vegetation type, altitude gradient, local climate type and latitude. 4. Vegetation types and altitude gradients are the two most important factors affecting the degree of vegetation’s response to climate factors. It is worth noting that when the altitude rises to 2500 m, the dominant factor for the vegetation growth changes from precipitation to air temperature in terms of hydrothermal combination in the environment. Vegetation growth in areas with relatively high altitudes is more dependent on air temperature.

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