Large Differences in Terrestrial Vegetation Production Derived from Satellite-Based Light Use Efficiency Models

نویسندگان

  • Wenwen Cai
  • Wenping Yuan
  • Shunlin Liang
  • Shuguang Liu
  • Wenjie Dong
  • Yang Chen
  • Dan Liu
  • Haicheng Zhang
چکیده

Terrestrial gross primary production (GPP) is the largest global CO2 flux and determines other ecosystem carbon cycle variables. Light use efficiency (LUE) models may have the most potential to adequately address the spatial and temporal dynamics of GPP, but recent studies have shown large model differences in GPP simulations. In this study, we investigated the GPP differences in the spatial and temporal patterns derived from seven widely used LUE models at the global scale. The result shows that the global annual GPP estimates over the period 2000–2010 varied from 95.10 to 139.71 Pg C·yr among models. The spatial and temporal variation of global GPP differs substantially between models, due to different model structures and dominant environmental drivers. In almost all models, water availability dominates the interannual variability of GPP over large vegetated areas. Solar radiation and air temperature are not the primary controlling factors for interannual variability of global GPP estimates for most models. The disagreement among the current LUE models highlights the need for further model improvement to quantify the global carbon cycle. OPEN ACCESS Remote Sens. 2014, 6 8946

برای دانلود رایگان متن کامل این مقاله و بیش از 32 میلیون مقاله دیگر ابتدا ثبت نام کنید

ثبت نام

اگر عضو سایت هستید لطفا وارد حساب کاربری خود شوید

منابع مشابه

Comparison between remote sensing and a dynamic vegetation model for estimating terrestrial primary production of Africa

BACKGROUND Africa is an important part of the global carbon cycle. It is also a continent facing potential problems due to increasing resource demand in combination with climate change-induced changes in resource supply. Quantifying the pools and fluxes constituting the terrestrial African carbon cycle is a challenge, because of uncertainties in meteorological driver data, lack of validation da...

متن کامل

Impact of land cover uncertainties on estimates of biospheric carbon fluxes

[1] Large-scale bottom-up estimates of terrestrial carbon fluxes, whether based on models or inventory, are highly dependent on the assumed land cover. Most current land cover and land cover change maps are based on satellite data and are likely to be so for the foreseeable future. However, these maps show large differences, both at the class level and when transformed into Plant Functional Typ...

متن کامل

Uncertainty in simulating gross primary production of cropland ecosystem from satellite-based models

Accurate estimates of gross primary production (GPP) for croplands are needed to assess carbon cycle and crop yield. Satellite-based models have been developed to monitor spatial and temporal GPP patterns. However, there are still large uncertainties in estimating cropland GPP. This study compares three light use efficiency (LUE) models (MODISGPP, EC-LUE, and VPM) with eddy-covariance measureme...

متن کامل

A new approach for estimating northern peatland gross primary productivity using a satellite‐sensor‐derived chlorophyll index

[1] Carbon flux models that are largely driven by remotely sensed data can be used to estimate gross primary productivity (GPP) over large areas, but despite the importance of peatland ecosystems in the global carbon cycle, relatively little attention has been given to determining their success in these ecosystems. This paper is the first to explore the potential of chlorophyll‐based vegetation...

متن کامل

Prediction of Net Primary Production Changes in Different Phytogeographical Regions of Iran from 2000 to 2016, Using Time Series Models

Vegetation cover is an important component of terrestrial ecosystems that changes seasonally. Accurate parameterization of vegetation cover dynamics through developing indicators of periodic patterns can assist our understanding of vegetation-climate interactions. The current study was conducted to investigate and model vegetation changes in some phytogeographical regions of Iran including, Kha...

متن کامل

ذخیره در منابع من


  با ذخیره ی این منبع در منابع من، دسترسی به آن را برای استفاده های بعدی آسان تر کنید

عنوان ژورنال:
  • Remote Sensing

دوره 6  شماره 

صفحات  -

تاریخ انتشار 2014