NDVI indicated inter-seasonal non-uniform time-lag responses of terrestrial vegetation growth to daily maximum and minimum temperature

2019 ◽  
Vol 177 ◽  
pp. 27-38 ◽  
Author(s):  
Youyue Wen ◽  
Xiaoping Liu ◽  
Jian Yang ◽  
Kui Lin ◽  
Guoming Du
Keyword(s):  
Minimum Temperature ◽  
Time Lag ◽  
Daily Maximum ◽  
Terrestrial Vegetation ◽  
Vegetation Growth

scholarly journals Nonuniform Time-Lag Effects of Asymmetric Warming on Net Primary Productivity across Global Terrestrial Biomes

2018 ◽  
Vol 22 (8) ◽  
pp. 1-26 ◽  
Author(s):  
Youyue Wen ◽  
Xiaoping Liu ◽  
Guoming Du
Keyword(s):  
Partial Correlation ◽  
Net Primary Productivity ◽  
Net Primary Production ◽  
Time Lag ◽  
Correlation Coefficients ◽  
Terrestrial Ecosystem ◽  
Terrestrial Vegetation ◽  
Vegetation Growth ◽  
Lag Effects ◽  
Terrestrial Biomes

Abstract Climate warming exhibits asymmetric patterns over a diel time, with the trend of nighttime warming exceeding that of daytime warming, a phenomenon commonly known as asymmetric warming. Recently, increasing studies have documented the significant instantaneous impacts of asymmetric warming on terrestrial vegetation growth, but the indirect effects of asymmetric warming carrying over vegetation growth (referred to here as time-lag effects) remain unknown. Here, we quantitatively studied the time-lag effects (within 1 year) of asymmetric warming on global plant biomes by using terrestrial vegetation net primary production (NPP) derived by the Carnegie–Ames–Stanford Approach (CASA) model and accumulated daytime and nighttime temperature (ATmax and ATmin) from 1982 to 2013. Partial correlation and time-lag analyses were conducted at a monthly scale to obtain the partial correlation coefficients between NPP and ATmax/ATmin and the lagged durations of NPP responses to ATmax/ATmin. The results showed that (i) asymmetric warming has nonuniform time-lag effects on single plant biomes, and distinguishing correlations exist in different vegetation biomes’ associations to asymmetric warming; (ii) terrestrial biomes respond to ATmax (4.63 ± 3.92 months) with a shorter protracted duration than to ATmin (6.06 ± 4.27 months); (iii) forest biomes exhibit longer prolonged duration in responding to asymmetric warming than nonforest biomes do; (iv) mosses and lichens (Mosses), evergreen needleleaf forests (ENF), deciduous needleleaf forests (DNF), and mixed forests (MF) tend to positively correlate with ATmax, whereas the other biomes associate with ATmax with near-equal splits of positive and negative correlation; and (v) ATmin has a predominantly positive influence on terrestrial biomes, except for Mosses and DNF. This study provides a new perspective on terrestrial ecosystem responses to asymmetric warming and highlights the importance of including such nonuniform time-lag effects into currently used terrestrial ecosystem models during future investigations of vegetation–climate interactions.

scholarly journals Periodic Relations between Terrestrial Vegetation and Climate Factors across the Globe

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.

scholarly journals Strong controls of daily minimum temperature on the autumn photosynthetic phenology of subtropical vegetation in China

2021 ◽  
Vol 8 (1) ◽  
Author(s):  
Peixin Ren ◽  
Zelin Liu ◽  
Xiaolu Zhou ◽  
Changhui Peng ◽  
Jingfeng Xiao ◽  
...  
Keyword(s):  
Climate Change ◽  
Minimum Temperature ◽  
Vegetation Index ◽  
Climatic Factors ◽  
Time Lag ◽  
Evergreen Forest ◽  
Maximum Temperature ◽  
Daily Minimum Temperature ◽  
Study Region ◽  
Cumulative Precipitation

Abstract Background Vegetation phenology research has largely focused on temperate deciduous forests, thus limiting our understanding of the response of evergreen vegetation to climate change in tropical and subtropical regions. Results Using satellite solar-induced chlorophyll fluorescence (SIF) and MODIS enhanced vegetation index (EVI) data, we applied two methods to evaluate temporal and spatial patterns of the end of the growing season (EGS) in subtropical vegetation in China, and analyze the dependence of EGS on preseason maximum and minimum temperatures as well as cumulative precipitation. Our results indicated that the averaged EGS derived from the SIF and EVI based on the two methods (dynamic threshold method and derivative method) was later than that derived from gross primary productivity (GPP) based on the eddy covariance technique, and the time-lag for EGSsif and EGSevi was approximately 2 weeks and 4 weeks, respectively. We found that EGS was positively correlated with preseason minimum temperature and cumulative precipitation (accounting for more than 73% and 62% of the study areas, respectively), but negatively correlated with preseason maximum temperature (accounting for more than 59% of the study areas). In addition, EGS was more sensitive to the changes in the preseason minimum temperature than to other climatic factors, and an increase in the preseason minimum temperature significantly delayed the EGS in evergreen forests, shrub and grassland. Conclusions Our results indicated that the SIF outperformed traditional vegetation indices in capturing the autumn photosynthetic phenology of evergreen forest in the subtropical region of China. We found that minimum temperature plays a significant role in determining autumn photosynthetic phenology in the study region. These findings contribute to improving our understanding of the response of the EGS to climate change in subtropical vegetation of China, and provide a new perspective for accurately evaluating the role played by evergreen vegetation in the regional carbon budget.

scholarly journals Effects of Cropland Expansion on Temperature Extremes in Western India from 1982 to 2015

Land ◽  
2021 ◽  
Vol 10 (5) ◽  
pp. 489
Author(s):  
Jinxiu Liu ◽  
Weihao Shen ◽  
Yaqian He
Keyword(s):  
Land Use ◽  
Heat Flux ◽  
Land Cover ◽  
Minimum Temperature ◽  
Negative Impact ◽  
Maximum Temperature ◽  
Daily Minimum Temperature ◽  
Daily Maximum ◽  
Temperature Extremes ◽  
Western India

India has experienced extensive land cover and land use change (LCLUC). However, there is still limited empirical research regarding the impact of LCLUC on climate extremes in India. Here, we applied statistical methods to assess how cropland expansion has influenced temperature extremes in India from 1982 to 2015 using a new land cover and land use dataset and ECMWF Reanalysis V5 (ERA5) climate data. Our results show that during the last 34 years, croplands in western India increased by ~33.7 percentage points. This cropland expansion shows a significantly negative impact on the maxima of daily maximum temperature (TXx), while its impacts on the maxima of daily minimum temperature and the minima of daily maximum and minimum temperature are limited. It is estimated that if cropland expansion had not taken place in western India over the 1982 to 2015 period, TXx would likely have increased by 0.74 (±0.64) °C. The negative impact of croplands on reducing the TXx extreme is likely due to evaporative cooling from intensified evapotranspiration associated with croplands, resulting in increased latent heat flux and decreased sensible heat flux. This study underscores the important influences of cropland expansion on temperature extremes and can be applicable to other geographic regions experiencing LCLUC.

scholarly journals A Weighted-Time-Lag Method to Detect Lag Vegetation Response to Climate Variation: A Case Study in Loess Plateau, China, 1982–2013

2021 ◽  
Vol 13 (5) ◽  
pp. 923
Author(s):  
Qianqian Sun ◽  
Chao Liu ◽  
Tianyang Chen ◽  
Anbing Zhang
Keyword(s):  
Climate Change ◽  
Loess Plateau ◽  
Time Lag ◽  
New Method ◽  
Climate Factors ◽  
The Loess Plateau ◽  
Climate Conditions ◽  
Vegetation Growth ◽  
Lag Effect

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.

scholarly journals The onset in spring and the end in autumn of the thermal and vegetative growing season affect calving time and reproductive success in reindeer

2019 ◽  
Vol 66 (2) ◽  
pp. 123-134 ◽  
Author(s):  
Amélie Paoli ◽  
Robert B Weladji ◽  
Øystein Holand ◽  
Jouko Kumpula
Keyword(s):  
Reproductive Success ◽  
Time Lag ◽  
Growing Season ◽  
Plant Phenology ◽  
Negative Effects ◽  
Main Hypothesis ◽  
Vegetation Growth ◽  
Growing Seasons ◽  
Finnish Lapland ◽  
Reindeer Population

Abstract A developing trophic mismatch between the peak of energy demands by reproducing animals and the peak of forage availability has caused many species’ reproductive success to decrease. The match–mismatch hypothesis (MMH) is an appealing concept that can be used to assess such fitness consequences. However, concerns have been raised on applying the MMH on capital breeders such as reindeer because the reliance on maternal capita rather than dietary income may mitigate negative effects of changing phenologies. Using a long-term dataset of reindeer calving dates recorded since 1970 in a semidomesticated reindeer population in Finnish Lapland and proxies of plant phenology; we tested the main hypothesis that the time lag between calving date and the plant phenology in autumn when females store nutrient reserves to finance reproduction would lead to consequences on reproductive success, as the time lag with spring conditions would. As predicted, the reproductive success of females of the Kutuharju reindeer population was affected by both the onset of spring green-up and vegetative senescence in autumn as calves were born heavier and with a higher first-summer survival when the onset of the vegetation growth was earlier and the end of the thermal growing season the previous year was earlier as well. Our results demonstrated that longer plant growing seasons might be detrimental to reindeer’s reproductive success if a later end is accompanied by a reduced abundance of mushrooms.

Relationships of Rainy Season Precipitation and Temperature to Climate Indices in California: Long-Term Variability and Extreme Events

2018 ◽  
Vol 31 (5) ◽  
pp. 1921-1942 ◽  
Author(s):  
Yi-Chin Liu ◽  
Pingkuan Di ◽  
Shu-Hua Chen ◽  
John DaMassa
Keyword(s):  
Extreme Events ◽  
North Pacific ◽  
Minimum Temperature ◽  
Rainy Season ◽  
Time Lag ◽  
Precipitation Variability ◽  
Climate Indices ◽  
Zero Time ◽  
Enso Indices

To better understand the change in California’s climate over the past century, the long-term variability and extreme events of precipitation as well as minimum, mean, and maximum temperatures during the rainy season (from November to March) are investigated using observations. Their relationships to 28 rainy season average climate indices with and without time lags are also studied. The precipitation variability is found to be highly correlated with the tropical/Northern Hemisphere pattern (TNH) index at zero time lag with the highest correlation in Northern California and the Sierra and the correlation decreasing southward. This is an important finding because there have been no conclusive studies on the dominant climate modes that modulate precipitation variability in Northern California. It is found that the TNH modulates California precipitation variability through the development of a positive (negative) height anomaly and its associated low-level moisture fluxes over the northeast Pacific Ocean during the positive (negative) TNH phase. Temperature fields, especially minimum temperature, are found to be primarily modulated by the east Pacific/North Pacific pattern, Pacific decadal oscillation, North Pacific pattern, and Pacific–North American pattern at zero time lag via changes in the lower-tropospheric temperature advections. Regression analysis suggests a combination of important climate indices would improve predictability for precipitation and minimum temperature statewide and subregionally compared to the use of a single climate index. While California’s precipitation currently is primarily projected by ENSO, this study suggests that using the combination of the TNH and ENSO indices results in better predictability than using ENSO indices only.

scholarly journals Use of Weather Variables to Quantify Sorghum Ergot Potential in South Africa

Plant Disease ◽  
1998 ◽  
Vol 82 (1) ◽  
pp. 26-29 ◽  
Author(s):  
N. W. McLaren ◽  
B. C. Flett
Keyword(s):  
Minimum Temperature ◽  
Pollen Viability ◽  
Breakdown Point ◽  
Field Trials ◽  
Maximum Temperature ◽  
Daily Maximum Temperature ◽  
Daily Maximum ◽  
Weather Variables ◽  
Data Set ◽  
Study Results

Quantification of resistance to ergot requires that the observed ergot severity within a sorghum line be compared with expected ergot severity (ergot potential) to compensate for differences in environmental favorability for the disease among flowering dates and seasons. The ergot potential required to induce the onset of disease is referred to as the ergot breakdown point of that line. In earlier studies, the ergot potential of a specific flowering date was defined as the mean ergot severity in all sorghum heads over all lines in the nursery which commenced flowering on that date in a genetically broad-based sorghum nursery. In this study, results of field trials enabled accurate prediction of ergot potential by using a multiple regression analysis which included three weather variables—namely, pre-flowering minimum temperature (mean of days 23 to 27 pre-flowering), mean daily maximum temperature, and mean daily maximum relative humidity (mean of days 1 to 5 post-flowering; R2 = 0.90; P = 0.91E-5). Evaluation of predicted and observed ergot severity in an independent data set gave an index of agreement of d = 0.94 and R2 = 0.84 (P = 0.106E-4), showing that ergot severity, assuming the presence of viable inoculum, can be accurately predicted. Low pre-flowering minimum temperature was associated with reduced pollen viability, which appeared to be the primary factor predisposing lines to ergot.

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