TY - JOUR
T1 - How global dryland vegetation dynamics relate to changing climatic conditions and anthropogenic dynamics
AU - Abel, Christin
AU - Horion, Stéphanie
AU - Tagesson, Torbern
AU - De Keersmaecker, Wanda
AU - Seddon, Alistair W. R.
AU - Abdi, Abdulhakim M.
AU - Fensholt, Rasmus
PY - 2020/5/1
Y1 - 2020/5/1
N2 - Monitoring ecosystem dynamics is fundamental to understanding and
eventually forecasting ecosystem states. To achieve this, it is crucial
to identify and understand potential negative/ positive effects from a
changing world on the system. As one key aspect of every ecosystem are
the living organisms it involves, our research focuses on vegetation,
since it has major implications for both the climate, because plants
absorb carbon dioxide, and human well-being, because people depend on
the products of plants. Specifically addressing global drylands, where
vegetation productivity is tightly linked to the availability of water
(mainly through rainfall), we quantify changes in vegetation functioning
by analyzing the slopes of a sequential linear regression (SeRGS) over a
time series of remote sensing data (NDVI and rainfall), as introduced in
Abel et al., 2019. Further, we apply a data-driven, empirical approach
to estimate the relative importance of potential drivers of identified
changes, as in Abel et al., 2020 (in revision). We show that there are
substantial regional and continental differences in vegetation
functioning and that these trends can be linked to global trends of
population expansion, large-scale agriculture intensification/ expansion
and changing climatic conditions. Results from these studies, follow-up
research and perspectives will be presented and discussed at
EGU.References:Abel, C., Horion, S., Tagesson, T., Brandt, M., Fensholt,
R. (2019). Towards improved remote sensing based monitoring of dryland
ecosystem functioning using sequential linear regression slopes (SeRGS).
Remote Sens. Environ. 224, 317-332.Abel, C., Horion, S., Tagesson, T.,
De Keersmaecker, W., Seddon, A. W. R., Abdi A. M., Fensholt, R. (2020).
How the human-environment nexus changes global dryland vegetation
functioning, in revision.
AB - Monitoring ecosystem dynamics is fundamental to understanding and
eventually forecasting ecosystem states. To achieve this, it is crucial
to identify and understand potential negative/ positive effects from a
changing world on the system. As one key aspect of every ecosystem are
the living organisms it involves, our research focuses on vegetation,
since it has major implications for both the climate, because plants
absorb carbon dioxide, and human well-being, because people depend on
the products of plants. Specifically addressing global drylands, where
vegetation productivity is tightly linked to the availability of water
(mainly through rainfall), we quantify changes in vegetation functioning
by analyzing the slopes of a sequential linear regression (SeRGS) over a
time series of remote sensing data (NDVI and rainfall), as introduced in
Abel et al., 2019. Further, we apply a data-driven, empirical approach
to estimate the relative importance of potential drivers of identified
changes, as in Abel et al., 2020 (in revision). We show that there are
substantial regional and continental differences in vegetation
functioning and that these trends can be linked to global trends of
population expansion, large-scale agriculture intensification/ expansion
and changing climatic conditions. Results from these studies, follow-up
research and perspectives will be presented and discussed at
EGU.References:Abel, C., Horion, S., Tagesson, T., Brandt, M., Fensholt,
R. (2019). Towards improved remote sensing based monitoring of dryland
ecosystem functioning using sequential linear regression slopes (SeRGS).
Remote Sens. Environ. 224, 317-332.Abel, C., Horion, S., Tagesson, T.,
De Keersmaecker, W., Seddon, A. W. R., Abdi A. M., Fensholt, R. (2020).
How the human-environment nexus changes global dryland vegetation
functioning, in revision.
U2 - 10.5194/egusphere-egu2020-7723
DO - 10.5194/egusphere-egu2020-7723
M3 - Journal article
VL - 22
JO - 22nd EGU General Assembly, held online 4-8 May, 2020
JF - 22nd EGU General Assembly, held online 4-8 May, 2020
M1 - 7723
ER -