- Terrestrial Ecosystems: Vegetation Dynamics

2016 ◽  
pp. 438-475
Keyword(s):  
Vegetation Dynamics ◽  
Terrestrial Ecosystems

scholarly journals Interactive impacts of fire and vegetation dynamics on global carbon and water budget using Community Land Model version 4.5

2019 ◽  
Vol 12 (1) ◽  
pp. 457-472 ◽  
Author(s):  
Hocheol Seo ◽  
Yeonjoo Kim
Keyword(s):  
Vegetation Dynamics ◽  
Vegetation Type ◽  
Soil Layer ◽  
Terrestrial Ecosystems ◽  
Water Fluxes ◽  
Moisture Profile ◽  
Community Land Model ◽  
Model Version ◽  
Global Increase ◽  
Induced Changes

Abstract. Fire plays an important role in terrestrial ecosystems. The burning of biomass affects carbon and water fluxes and vegetation distribution. To understand the effect of interactive processes of fire and ecological succession on surface carbon and water fluxes, this study employed the Community Land Model version 4.5 to conduct a series of experiments that included and excluded fire and dynamic vegetation processes. Results of the experiments that excluded the vegetation dynamics showed a global increase in net ecosystem production (NEP) in post-fire regions, whereas the inclusion of vegetation dynamics revealed a fire-induced decrease in NEP in some regions, which was depicted when the dominant vegetation type was changed from trees to grass. Carbon emissions from fires are enhanced by reduction in NEP when vegetation dynamics are considered; however, this effect is somewhat mitigated by the increase in NEP when vegetation dynamics are not considered. Fire-induced changes in vegetation modify the soil moisture profile because grasslands are more dominant in post-fire regions. This results in less moisture within the top soil layer than that in unburned regions, even though transpiration is reduced overall. These findings are different from those of previous fire model evaluations that ignored vegetation dynamics and thus highlight the importance of interactive processes between fires and vegetation dynamics in evaluating recent model developments.

scholarly journals Global Evaluation of the Ecosystem Demography Model (ED v3.0)

2021 ◽  
Author(s):  
Lei Ma ◽  
George Hurtt ◽  
Lesley Ott ◽  
Ritvik Sahajpal ◽  
Justin Fisk ◽  
...  
Keyword(s):  
Vegetation Dynamics ◽  
Gross Primary Production ◽  
Critical Role ◽  
Terrestrial Ecosystems ◽  
Global Evaluation ◽  
Ecological Processes ◽  
Modelling Framework ◽  
Global Calibration ◽  
Global Patterns ◽  
Uncertain Future

Abstract. Terrestrial ecosystems play a critical role in the global carbon cycle but have highly uncertain future dynamics. Ecosystem modelling that includes the scaling-up of underlying mechanistic ecological processes has the potential  to improve the accuracy of future projections, while retaining key process-level detail. Over the past two decades,  multiple modelling advances have been made to meet this challenge, including the Ecosystem Demography (ED)  model and its derivatives including ED2 and FATES. Here, we present the global evaluation of the Ecosystem  Demography model (ED v3.0), which likes its predecessors features the formal scaling of physiological processes of  individual-based vegetation dynamics to ecosystem scales, together with integrated submodules of soil  biogeochemistry and soil hydrology, while retaining explicit tracking of vegetation 3-D structure. This new version  builds on previous versions and provides the first global calibration and evaluation, global tracking of the effects of  climate and land-use change on vegetation 3-D structure, new spin-up process and input datasets, as well as  numerous other advances. Model evaluation was performed with respect to a set of important benchmarking  datasets, and model estimates were within observational constraints for multiple key variables including: (i) global  patterns of dominant plant functional types (broadleaf vs evergreen); (ii) spatial distribution, seasonal cycle, and  interannual trends of global Gross Primary Production (GPP); (iii) global interannual variability of Net Biome  Production (NBP); and (iv) global patterns of vertical structure including leaf area and canopy height. With this  global model version, it is now possible to simulate vegetation dynamics from local to global scales and from seconds to centuries, with a consistent mechanistic modelling framework amendable to data from multiple  traditional and new remote sensing sources, including lidar.

Augmenting the multiscale hydrologic modeling system with adequate vegetation dynamics for improved representation of coupled water and carbon cycles

2020 ◽  
Author(s):  
Bahar Bahrami ◽  
Rohini Kumar ◽  
Stephan Thober ◽  
Corinna Rebmann ◽  
Rico Fischer ◽  
...  
Keyword(s):  
Soil Moisture ◽  
Vegetation Dynamics ◽  
Net Primary Productivity ◽  
Water Cycle ◽  
Terrestrial Ecosystems ◽  
Carbon Fluxes ◽  
Low Complexity ◽  
Hydrologic Model ◽  
Model Concept ◽  
Projected Changes

<p>As climate is changing, future functionality and resilience of terrestrial ecosystems are expected to change in numerous ways. However, these projected changes remain uncertain. One of the major sources of uncertainty is the representation of vegetation dynamics which directly respond to increased temperature and ambient CO2 concentrations and thereby alter transpiration. Many of the existing hydrologic models representing components of the water cycle have a very simplified representation of vegetation dynamics that are not able to represent this link.  In this study we aim to augment the existing mesoscale Hydrologic Model (mHM) with a low complexity dynamic vegetation model (DVM). This will provide the model with improved capabilities to represent the coupled water and carbon fluxes. Our analyses focus on representing the vegetation (i.e. biomass growth) including fluxes such as gross and net primary productivity and their inter-linkages to water storage and fluxes (e.g., soil moisture and evapotranspiration) across biomes (e.g., grasslands). These inter-linkages, which are spatially and temporally variable and scale-related, are crucial for adequately representing the coupled water and carbon cycle. For example, the adequate representation of soil moisture is essential to capture the mechanistic response of plant productivity to changes in soil moisture; and vice versa especially under extreme environmental conditions. In this presentation, we will discuss the simplified structure of the DVM based on a Light Use Efficiency (LUE) model concept and couple the model components to the mHM. Furthermore, the coupled simulation results of different water and carbon fluxes will be presented for a test region in Central Germany.   </p>

Effects of multi-time scales drought on vegetation dynamics in Qaidam River Basin, Qinghai-Tibet Plateau from 1998 to 2015

2020 ◽  
Author(s):  
Yongxiu Sun ◽  
Shiliang Liu ◽  
Yuhong Dong ◽  
Shikui Dong ◽  
Fangning Shi
Keyword(s):  
River Basin ◽  
Time Scales ◽  
Vegetation Dynamics ◽  
Vegetation Index ◽  
Normalized Difference Vegetation Index ◽  
Terrestrial Ecosystems ◽  
Tibet Plateau ◽  
Desert Grassland ◽  
Qinghai Tibet Plateau ◽  
Different Time Scales

<p>Quantifying drought variations at multi-time scales is important to assess the potential impacts of climate change on terrestrial ecosystems, especially vulnerable desert grassland. Based on the Normalized Difference Vegetation Index (NDVI) and Standardized Precipitation Evapotranspiration Index (SPEI), we assessed the influences of different time-scales drought (SPEI-3, SPEI-6, SPEI-12, SPEI-24, and SPEI-48 with 3, 6, 12, 24 and 48 months, respectively) on vegetation dynamics in the Qaidam River Basin, Qinghai-Tibet Plateau. Results showed that: (1) Temporally, annual and summer NDVI increased, while spring and autumn NDVI decreased from 1998 to 2015. Annual, spring and summer SPEI increased and autumn SPEI decreased. (2) Spatially, annual, spring, summer, and autumn NDVI increased in the periphery of the Basin, with 45.98%, 22.68%, 43.90%  and 30.80% of the study area, respectively. SPEI showed a reverse variation pattern with NDVI, with an obvious decreasing trend from southeast to northwest. (3) Annual vegetation growth in most areas (69.53%, 77.33%, 86.36%, 90.19% and 85.44%) was correlated with drought at all time-scales during 1998-2015. However, high spatial and seasonal differences occurred among different time-scales, with the maximum influence in summer under SPEI24. (4) From month to annual scales, NDVI of all land cover types showed higher correlation to long-term drought of SPEI24 or SPEI48. Vegetation condition index (VCI) and SPEI were positively correlated at all time-scales and had a more obvious response in summer. The highest correlation was VCI of grassland (June-July) or forest (April-May, August-October) and SPEI48. This study contributes to exploring the effect of drought on vegetation dynamics at different time scales, further providing credible guidance for regional water resources management.</p>

Vegetation Dynamics

2016 ◽  
Author(s):  
Derek Eamus ◽  
Alfredo Huete ◽  
Qiang Yu
Keyword(s):  
Vegetation Dynamics

NetCO2andH2Ofluxes of terrestrial ecosystems

1999 ◽  
Vol 13 (3) ◽  
pp. 751-760 ◽  
Author(s):  
Nina Buchmann
Keyword(s):  
Terrestrial Ecosystems
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