Spatiotemporal Response of Rangeland NPP to Drought in Central Iran based on SPDI Index

Yaghmaei, Leila; Koupaei, S Soltani; Jafari, Reza

doi:10.1134/s1995425520060141

Cited by 3 publications

(1 citation statement)

References 46 publications

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“…With soil dryness, the amount of leaf area index, photosynthetic reflection of plants and its relationship with plant indices (NDVI) and simulated models such as CASA also decrease while it has been proven in various observations (Coughenour 1999;Hunt Jr et al 2003). In addition, the comparison of plant types in a similar climate showed that the production of plant types with medium rangeland condition has a higher correlation with CASA model than poor rangeland condition which has been stated by Hadian et al (2019) due to reduced fertility, leaf area and greenness.Temperature, precipitation and solar energy factors play major role in plant production (Yaghmaei et al 2020). At the beginning of the season, there is a temperature limit on plant growth, so compared to the middle of the growing season, the vegetation production rate was lower (Table 1).…”

Section: Discussionmentioning

confidence: 99%

Investigating net primary production in climate regions of Khuzestan Province, Iran using CASA model

Afzali,

Hadian,

Sabri

et al. 2024

Int J Biometeorol

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This study aimed to investigate the vegetation production changes in Khuzestan province, Iran using MODIS data production, meteorological data, vegetation maps as well as topographic and field monitoring data in CASA model. The study area was divided into different climatic classes based on multivariate statistical method, so the vegetation of each climatic region was examined separately for changes in NPP values. Production changes due to degradation were calculated using the Miami model and subsequently, the rain use efficiency (RUE) and the light use efficiency (LUE) and correlation indices between the CASA model and ground data were determined. The results of this study (R2) showed that the accuracy of this model varies depending on the type of climatic regions (R2 = 80 to R2 = 15). In different climatic regions, the rate of NPP changes (very humid 68 gC/m2 to ultra-dry 15 gC/m2) varies in rangeland types. The highest rate of vegetation production is observed seasonally in May. Degradation conditions also reduced RUE and LUE.However, in hyper-arid regions, adaptations of plants in some different species (Hammada sp.) increase their efficiency compared to other vegetation types. The results showed the importance of vegetation and climate classification in vegetation production studies.

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Section: Discussionmentioning

confidence: 99%

Investigating net primary production in climate regions of Khuzestan Province, Iran using CASA model

Afzali,

Hadian,

Sabri

et al. 2024

Int J Biometeorol

View full text Add to dashboard Cite

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Investigating Net Primary Production in Climate Regions of Khuzestan Province, Iran using CASA model

Afzali

Hadian²,

Sabri³

et al. 2023

Preprint

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This study aimed to investigate the vegetation production changes in Khuzestan province, Iran using MODIS data production, meteorological data, vegetation maps as well as topographic and field monitoring data in CASA model. The study area was divided into different climatic classes based on multivariate statistical method, so the vegetation of each climatic region was examined separately for changes in NPP values. Production changes due to degradation were calculated using the Miami model and subsequently, the rain use efficiency (RUE) and the light use efficiency (LUE) and correlation indices between the CASA model and ground data were determined. The results of this study (R2) showed that the accuracy of this model varies depending on the type of climatic regions (R2 = 80 to R2 = 15). In different climatic regions, the rate of NPP changes (very humid 68 gC/m2 to ultra-dry 15 gC/m2) varies in rangeland types. The highest rate of vegetation production is observed seasonally in May. Degradation conditions also reduced RUE and LUE. However, in hyper-arid regions, adaptations of plants in some different species (Hammada sp.) increase their efficiency compared to other vegetation types. The results showed the importance of vegetation and climate classification in vegetation production studies.

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Ecological Restoration Projects Adapt Response of Net Primary Productivity of Alpine Grasslands to Climate Change across the Tibetan Plateau

Liang,

Zhao,

Yuan

et al. 2024

Remote Sensing

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Alpine grassland is sensitive to climate change, and many studies have explored the trends in alpine vegetation. Most research focuses on the effects of climate warming and increased humidity on vegetation greening. However, less attention has been given to the positive impacts of human activities, particularly ecological restoration projects (ERPs). Our study utilized the CASA (Carnegie Ames Stanford Approach) model to simulate the net primary productivity (NPP) of alpine grasslands on the Tibetan Plateau (TP) from 2000 to 2020. Additionally, a moving window approach was employed to comparatively analyze the changes in the response characteristics of NPP to climate change before and after the implementation of ERPs. Our results indicated: (1) The NPP exhibited a fluctuating upward trend. The NPP growth rates of alpine meadow, alpine grassland, and desert grassland were found to be 2.38, 1.5, and 0.8 g C·m−2·a−1, respectively. (2) The annual average NPP and annual growth rate of alpine grasslands after the implementation of ERPs were both higher than before, indicating that ERPs have intensified the growth trend of NPP in alpine grasslands. (3) ERPs have reduced the responsiveness of alpine grassland NPP to temperature variations and enhanced its responsiveness to changes in precipitation. In detail, ERPs enhanced the responsiveness of NPP in alpine meadow to both temperature and precipitation, reduced the responsiveness of NPP in alpine steppe to temperature while enhancing its responsiveness to precipitation, and mitigated the changes in the response of NPP in desert steppe to temperature and significantly enhanced its responsiveness to precipitation.

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Spatiotemporal Response of Rangeland NPP to Drought in Central Iran based on SPDI Index

Cited by 3 publications

References 46 publications

Investigating net primary production in climate regions of Khuzestan Province, Iran using CASA model

Investigating net primary production in climate regions of Khuzestan Province, Iran using CASA model

Investigating Net Primary Production in Climate Regions of Khuzestan Province, Iran using CASA model

Ecological Restoration Projects Adapt Response of Net Primary Productivity of Alpine Grasslands to Climate Change across the Tibetan Plateau

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