Retrieving vegetation growth patterns from soil moisture, precipitation and temperature using maximum entropy

2015 ◽  
Vol 309-310 ◽  
pp. 10-21 ◽  
Author(s):  
Dagbegnon C. Sohoulande Djebou ◽  
Vijay P. Singh
2021 ◽  
Vol 13 (2) ◽  
pp. 187
Author(s):  
Rui Sun ◽  
Shaohui Chen ◽  
Hongbo Su

As an important part of a terrestrial ecosystem, vegetation plays an important role in the global carbon-water cycle and energy flow. Based on the Global Inventory Monitoring and Modeling System (GIMMS) third generation of Normalized Difference Vegetation Index (NDVI3g), meteorological station data, climate reanalysis data, and land cover data, this study analyzed the climate dynamics of the spatiotemporal variations of vegetation NDVI in northern China from 1982 to 2015. The results showed that growth season NDVI (NDVIgs) increased significantly at 0.006/10a (p < 0.01) in 1982–2015 on the regional scale. The period from 1982 to 2015 was divided into three periods: the NDVIgs increased by 0.026/10a (p < 0.01) in 1982–1990, decreased by −0.002/10a (p > 0.1) in 1990–2006, and then increased by 0.021/10a (p < 0.01) during 2006–2015. On the pixel scale, the increases in NDVIgs during 1982–2015, 1982–1990, 1990–2006, and 2006–2015 accounted for 74.64%, 85.34%, 48.14%, and 68.78% of the total area, respectively. In general, the dominant climate drivers of vegetation growth had gradually switched from solar radiation, temperature, and precipitation (1982–1990) to precipitation and temperature (1990–2015). For woodland, high coverage grassland, medium coverage grassland, low coverage grassland, the dominant climate drivers had changed from temperature and solar radiation, solar radiation and precipitation, precipitation and solar radiation, solar radiation to precipitation and solar radiation, precipitation, precipitation and temperature, temperature and precipitation. The areas controlled by precipitation increased significantly, mainly distributed in arid, sub-arid, and sub-humid areas. The dominant climate drivers for vegetation growth in the plateau climate zone or high-altitude area changed from solar radiation to temperature and precipitation, and then to temperature, while in cold temperate zone, changed from temperature to solar radiation. These results are helpful to understand the climate dynamics of vegetation growth, and have important guiding significance for vegetation protection and restoration in the context of global climate change.


2014 ◽  
Vol 36 (2) ◽  
pp. 185 ◽  
Author(s):  
Fang Chen ◽  
Keith T. Weber

Changes in vegetation are affected by many climatic factors and have been successfully monitored through satellite remote sensing over the past 20 years. In this study, the Normalised Difference Vegetation Index (NDVI), derived from the Moderate Resolution Imaging Spectroradiometer (MODIS) onboard the Terra satellite, was selected as an indicator of change in vegetation. Monthly MODIS composite NDVI at a 1-km resolution was acquired throughout the 2004–09 growing seasons (i.e. April–September). Data describing daily precipitation and temperature, primary factors affecting vegetation growth in the semiarid rangelands of Idaho, were derived from the Surface Observation Gridding System and local weather station datasets. Inter-annual and seasonal fluctuations of precipitation and temperature were analysed and temporal relationships between monthly NDVI, precipitation and temperature were examined. Results indicated NDVI values observed in June and July were strongly correlated with accumulated precipitation (R2 >0.75), while NDVI values observed early in the growing season (May) as well as late in the growing season (August and September) were only moderately related with accumulated precipitation (R2 ≥0.45). The role of ambient temperature was also apparent, especially early in the growing season. Specifically, early growing-season temperatures appeared to significantly affect plant phenology and, consequently, correlations between NDVI and accumulated precipitation. It is concluded that precipitation during the growing season is a better predictor of NDVI than temperature but is interrelated with influences of temperature in parts of the growing season.


1996 ◽  
Vol 26 (4) ◽  
pp. 670-681 ◽  
Author(s):  
S.B. McLaughlin ◽  
D.J. Downing

Seasonal growth patterns of mature loblolly pine (Pinustaeda L.) trees over the interval 1988–1993 have been analyzed to evaluate the effects of ambient ozone on growth of large forest trees. Patterns of stem expansion and contraction of 34 trees were examined using serial measurements with sensitive dendrometer band systems. Study sites, located in eastern Tennessee, varied significantly in soil moisture, soil fertility, and stand density. Levels of ozone, rainfall, and temperature varied widely over the 6-year study interval. Regression analysis identified statistically significant influences of ozone on stem growth patterns, with responses differing widely among trees and across years. Ozone interacted with both soil moisture stress and high temperatures, explaining 63% of the high frequency, climatic variance in stem expansion identified by stepwise regression of the 5-year data set. Observed responses to ozone were rapid, typically occurring within 1–3 days of exposure to ozone at ≥40 ppb and were significantly amplified by low soil moisture and high air temperatures. Both short-term responses, apparently tied to ozone-induced increases in whole-tree water stress, and longer term cumulative responses were identified. These data indicate that relatively low levels of ambient ozone can significantly reduce growth of mature forest trees and that interactions between ambient ozone and climate are likely to be important modifiers of future forest growth and function. Additional studies of mechanisms of short-term response and interspecies comparisons are clearly needed.


2019 ◽  
Vol 40 (2) ◽  
pp. 272-283
Author(s):  
Yiyang Ding ◽  
Pauliina Schiestl-Aalto ◽  
Heljä-Sisko Helmisaari ◽  
Naoki Makita ◽  
Kira Ryhti ◽  
...  

Abstract Scots pine (Pinus sylvestris L.) is one of the most important conifers in Northern Europe. In boreal forests, over one-third of net primary production is allocated to roots. Pioneer roots expand the horizontal and vertical root systems and transport nutrients and water from belowground to aboveground. Fibrous roots, often colonized by mycorrhiza, emerge from the pioneer roots and absorb water and nutrients from the soil. In this study, we installed three flatbed scanners to detect the daily growth of both pioneer and fibrous roots of Scots pine during the growing season of 2018, a year with an unexpected summer drought in Southern Finland. The growth rate of both types of roots had a positive relationship with temperature. However, the relations between root elongation rate and soil moisture differed significantly between scanners and between root types indicating spatial heterogeneity in soil moisture. The pioneer roots were more tolerant to severe environmental conditions than the fibrous roots. The pioneer roots initiated elongation earlier and ceased it later than the fibrous roots. Elongation ended when the temperature dropped below the threshold temperature of 4 °C for pioneer roots and 6 °C for fibrous roots. During the summer drought, the fibrous roots halted root surface area growth at the beginning of the drought, but there was no drought effect on the pioneer roots over the same period. To compare the timing of root production and the aboveground organs’ production, we used the CASSIA model, which estimates the aboveground tree carbon dynamics. In this study, root growth started and ceased later than growth of aboveground organs. Pioneer roots accounted for 87% of total root productivity. We suggest that future carbon allocation models should separate the roots by root types (pioneer and fibrous), as their growth patterns are different and they have different reactions to changes in the soil environment.


2020 ◽  
Vol 11 (1) ◽  
Author(s):  
Laibao Liu ◽  
Lukas Gudmundsson ◽  
Mathias Hauser ◽  
Dahe Qin ◽  
Shuangcheng Li ◽  
...  

Abstract Dryness stress can limit vegetation growth and is often characterized by low soil moisture (SM) and high atmospheric water demand (vapor pressure deficit, VPD). However, the relative role of SM and VPD in limiting ecosystem production remains debated and is difficult to disentangle, as SM and VPD are coupled through land-atmosphere interactions, hindering the ability to predict ecosystem responses to dryness. Here, we combine satellite observations of solar-induced fluorescence with estimates of SM and VPD and show that SM is the dominant driver of dryness stress on ecosystem production across more than 70% of vegetated land areas with valid data. Moreover, after accounting for SM-VPD coupling, VPD effects on ecosystem production are much smaller across large areas. We also find that SM stress is strongest in semi-arid ecosystems. Our results clarify a longstanding question and open new avenues for improving models to allow a better management of drought risk.


2016 ◽  
Vol 17 (6) ◽  
pp. 1781-1800 ◽  
Author(s):  
Reepal D. Shah ◽  
Vimal Mishra

Abstract Medium-range (~7 days) forecasts of agricultural and hydrologic droughts can help in decision-making in agriculture and water resources management. India has witnessed severe losses due to extreme weather events during recent years and medium-range forecasts of precipitation, air temperatures (maximum and minimum), and hydrologic variables (root-zone soil moisture and runoff) can be valuable. Here, the skill of the Global Ensemble Forecast System (GEFS) reforecast of precipitation and air temperatures is evaluated using retrospective data for the period of 1985–2010. It is found that the GEFS forecast shows better skill in the nonmonsoon season than in the monsoon season in India. Moreover, skill in temperature forecast is higher than that of precipitation in both the monsoon and nonmonsoon seasons. The lower skill in forecasting precipitation during the monsoon season can be attributed to representation of intraseasonal variability in precipitation from the GEFS. Among the selected regions, the northern, northeastern, and core monsoon region showed relatively lower skill in the GEFS forecast. Temperature and precipitation forecasts were corrected from the GEFS using quantile–quantile (Q–Q) mapping and linear scaling, respectively. Bias-corrected forecasts for precipitation and air temperatures were improved over the raw forecasts. The influence of corrected and raw forcings on medium-range soil moisture, drought, and runoff forecasts was evaluated. The results showed that because of high persistence, medium-range soil moisture forecasts are largely determined by the initial hydrologic conditions. Bias correction of precipitation and temperature forecasts does not lead to significant improvement in the medium-range hydrologic forecasting of soil moisture and drought. However, bias correcting raw GEFS forecasts can provide better predictions of the forecasts of precipitation and temperature anomalies over India.


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