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Title: Global and regional variability and change in terrestrial ecosystems net primary production and NDVI: A model-data comparison

Abstract

The net primary productivity (NPP) is commonly used for understanding the dynamics of terrestrial ecosystems and their role in carbon cycle. We used a combination of the most recent NDVI and model–based NPP estimates (from five models of the TRENDY project) for the period 1982-2012, to study the role of terrestrial ecosystems in carbon cycle under the prevailing climate conditions. We found that 80% and 67% of the global land area showed positive NPP and NDVI values, respectively, for this period. The global NPP was estimated to be about 63 Pg C y -1, with an increase of 0.214 Pg C y -1 y -1. Similarly, the global mean NDVI was estimated to be 0.33, with an increasing trend of 0.00041 y-1. The spatial patterns of NPP and NDVI demonstrated substantial variability, especially at the regional level, for most part of the globe. However, on temporal scale, both global NPP and NDVI showed a corresponding pattern of increase (decrease) for the duration of this study except for few years (e.g. 1990 and 1995-98). Generally, the Northern Hemisphere showed stronger NDVI and NPP increasing trends over time compared to the Southern Hemisphere; however, NDVI showed larger trends in Temperate regions whilemore » NPP showed larger trends in Boreal regions. Among the five models, the maximum and minimum NPP were produced by JULES (72.4 Pg C y -1) and LPJ (53.72 Pg C y -1) models, respectively. At latitudinal level, the NDVI and NPP ranges were ~0.035 y -1 to ~-0.016 y -1 and ~0.10 Pg C y -1 y -1 to ~-0.047 Pg C y -1 y -1, respectively. Overall, the results of this study suggest that the modeled NPP generally correspond to the NDVI trends in the temporal dimension. Lastly, the significant variability in spatial patterns of NPP and NDVI trends points to a need for research to understand the causes of these discrepancies between molded and observed ecosystem dynamics, and the carbon cycle.« less

Authors:
ORCiD logo [1];  [2];  [3];  [4];  [1]
  1. Pacific Northwest National Lab., College Park, MD (United States)
  2. Univ. of Maryland, College Park, MD (United States); Potsdam Institute for Climate Impact Research, Potsdam (Germany)
  3. Univ. of Zurich, Zurich (Switzerland)
  4. Univ. of Maryland, College Park, MD (United States)
Publication Date:
Research Org.:
Pacific Northwest National Lab. (PNNL), Richland, WA (United States)
Sponsoring Org.:
USDOE
OSTI Identifier:
1255393
Report Number(s):
PNNL-SA-115751
Journal ID: ISSN 2072-4292
Grant/Contract Number:  
AC05-76RL01830
Resource Type:
Accepted Manuscript
Journal Name:
Remote Sensing
Additional Journal Information:
Journal Volume: 8; Journal Issue: 3; Journal ID: ISSN 2072-4292
Publisher:
MDPI
Country of Publication:
United States
Language:
English
Subject:
54 ENVIRONMENTAL SCIENCES; carbon cycle; ecosystems; NDVI; NPP; TRENDY models; spatial trends; temporal trends

Citation Formats

Rafique, Rashid, Zhao, Fang, de Jong, Rogier, Zeng, Ning, and Asrar, Ghassem. Global and regional variability and change in terrestrial ecosystems net primary production and NDVI: A model-data comparison. United States: N. p., 2016. Web. doi:10.3390/rs8030177.
Rafique, Rashid, Zhao, Fang, de Jong, Rogier, Zeng, Ning, & Asrar, Ghassem. Global and regional variability and change in terrestrial ecosystems net primary production and NDVI: A model-data comparison. United States. doi:10.3390/rs8030177.
Rafique, Rashid, Zhao, Fang, de Jong, Rogier, Zeng, Ning, and Asrar, Ghassem. Thu . "Global and regional variability and change in terrestrial ecosystems net primary production and NDVI: A model-data comparison". United States. doi:10.3390/rs8030177. https://www.osti.gov/servlets/purl/1255393.
@article{osti_1255393,
title = {Global and regional variability and change in terrestrial ecosystems net primary production and NDVI: A model-data comparison},
author = {Rafique, Rashid and Zhao, Fang and de Jong, Rogier and Zeng, Ning and Asrar, Ghassem},
abstractNote = {The net primary productivity (NPP) is commonly used for understanding the dynamics of terrestrial ecosystems and their role in carbon cycle. We used a combination of the most recent NDVI and model–based NPP estimates (from five models of the TRENDY project) for the period 1982-2012, to study the role of terrestrial ecosystems in carbon cycle under the prevailing climate conditions. We found that 80% and 67% of the global land area showed positive NPP and NDVI values, respectively, for this period. The global NPP was estimated to be about 63 Pg C y-1, with an increase of 0.214 Pg C y-1 y-1. Similarly, the global mean NDVI was estimated to be 0.33, with an increasing trend of 0.00041 y-1. The spatial patterns of NPP and NDVI demonstrated substantial variability, especially at the regional level, for most part of the globe. However, on temporal scale, both global NPP and NDVI showed a corresponding pattern of increase (decrease) for the duration of this study except for few years (e.g. 1990 and 1995-98). Generally, the Northern Hemisphere showed stronger NDVI and NPP increasing trends over time compared to the Southern Hemisphere; however, NDVI showed larger trends in Temperate regions while NPP showed larger trends in Boreal regions. Among the five models, the maximum and minimum NPP were produced by JULES (72.4 Pg C y-1) and LPJ (53.72 Pg C y-1) models, respectively. At latitudinal level, the NDVI and NPP ranges were ~0.035 y-1 to ~-0.016 y-1 and ~0.10 Pg C y-1 y-1 to ~-0.047 Pg C y-1 y-1, respectively. Overall, the results of this study suggest that the modeled NPP generally correspond to the NDVI trends in the temporal dimension. Lastly, the significant variability in spatial patterns of NPP and NDVI trends points to a need for research to understand the causes of these discrepancies between molded and observed ecosystem dynamics, and the carbon cycle.},
doi = {10.3390/rs8030177},
journal = {Remote Sensing},
number = 3,
volume = 8,
place = {United States},
year = {2016},
month = {2}
}

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    Dissolved organic carbon in streams within a subarctic catchment analysed using a GIS/remote sensing approach
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