scholarly journals Modelling the response of net primary productivity of the Zambezi teak forests to climate change along a rainfall gradient in Zambia

2019 ◽  
Vol 16 (19) ◽  
pp. 3853-3867
Author(s):  
Justine Ngoma ◽  
Maarten C. Braakhekke ◽  
Bart Kruijt ◽  
Eddy Moors ◽  
Iwan Supit ◽  
...  
Keyword(s):  
Climate Change ◽  
21St Century ◽  
Primary Productivity ◽  
General Circulation ◽  
Net Primary Productivity ◽  
Co2 Concentration ◽  
Annual Rainfall ◽  
Rainfall Gradient ◽  
Local Soil ◽  
Parameter Values

Abstract. Understanding climate change effects on forests is important considering the role forests play in mitigating climate change. We studied the effects of changes in temperature, rainfall, atmospheric carbon dioxide (CO2) concentration, solar radiation, and number of wet days (as a measure of rainfall intensity) on net primary productivity (NPP) of the Zambian Zambezi teak forests along a rainfall gradient. Using 1960–1989 as a baseline, we projected changes in NPP for the end of the 21st century (2070–2099). We adapted the parameters of the dynamic vegetation model, LPJ-GUESS, to simulate the growth of Zambian forests at three sites along a moisture gradient receiving annual rainfall of between 700 and more than 1000 mm. The adjusted plant functional type was tested against measured data. We forced the model with contemporary climate data (1960–2005) and with climatic forecasts of an ensemble of five general circulation models (GCMs) following Representative Concentration Pathways (RCPs) RCP4.5 and RCP8.5. We used local soil parameter values to characterize texture and measured local tree parameter values for maximum crown area, wood density, leaf longevity, and allometry. The results simulated with the LPJ-GUESS model improved when we used these newly generated local parameters, indicating that using local parameter values is essential to obtaining reliable simulations at site level. The adapted model setup provided a baseline for assessing the potential effects of climate change on NPP in the studied Zambezi teak forests. Using this adapted model version, NPP was projected to increase by 1.77 % and 0.69 % at the wetter Kabompo and by 0.44 % and 0.10 % at the intermediate Namwala sites under RCP8.5 and RCP4.5 respectively, especially caused by the increased CO2 concentration by the end of the 21st century. However, at the drier Sesheke site, NPP would respectively decrease by 0.01 % and 0.04 % by the end of the 21st century under RCP8.5 and RCP4.5. The projected decreased NPP under RCP8.5 at the Sesheke site results from the reduced rainfall coupled with increasing temperature. We thus demonstrated that differences in the amount of rainfall received in a site per year influence the way in which climate change will affect forest resources. The projected increase in CO2 concentration would thus have more effects on NPP in high rainfall receiving areas, while in arid regions, NPP would be affected more by the changes in rainfall and temperature. CO2 concentrations would therefore be more important in forests that are generally not temperature- or precipitation-limited; however, precipitation will continue to be the limiting factor in the drier sites.

scholarly journals Response of Net Primary Productivity of Zambezi teak forests to climate change along a rainfall gradient in Zambia

2018 ◽  
Author(s):  
Justine Ngoma ◽  
Maarten C. Braakhekke ◽  
Bart Kruijt ◽  
Eddy Moors ◽  
Iwan Supit ◽  
...  
Keyword(s):  
Climate Change ◽  
21St Century ◽  
Primary Productivity ◽  
Net Primary Productivity ◽  
Co2 Concentration ◽  
Annual Rainfall ◽  
Base Line ◽  
Rainfall Gradient ◽  
Local Soil ◽  
Parameter Values

Abstract. Understanding climate change effects on forests is important considering the role forests play in mitigating climate change. We studied the effects of changes in temperature, rainfall, atmospheric carbon dioxide (CO2) concentration, solar radiation, and number of wet days (as a measure of rainfall intensity) on net primary productivity (NPP) of the Zambian Zambezi teak forests along a rainfall gradient. Using 1960–1989 as base-line, we projected changes in NPP for the end of the 21st century (2070–2099). We adapted the parameters of the dynamic vegetation model, LPJ-GUESS, to simulate the growth of Zambian forests at three sites along a moisture gradient receiving annual rainfall of between 700 mm to more than 1000 mm. The thus adjusted plant functional type was tested against measured data. We forced the model with contemporary climate data (1960–2005) and with climatic forecasts of an ensemble of five General Circulation Models (GCMs) following RCP4.5 and RCP8.5. We used local soil parameter values to characterize texture and measured local tree parameter values for maximum crown area, wood density, leaf longevity, and allometry. While increased CO2 concentration enhances NPP at the wetter Kabompo and the intermediate Namwala sites, NPP decreases at the drier Sesheke site under both scenarios by the end of 21st century. The projected decreased NPP under RCP8.5 at the Sesheke site results from the reduced rainfall. We thus demonstrated that differences in rainfall pattern influence the way in which climate change will affect forests resources. We also showed that using local parameter values is essential to obtaining reasonably reliable simulations.

scholarly journals Roles of Climate Change and Increasing CO2 in Driving Changes of Net Primary Productivity in China Simulated Using a Dynamic Global Vegetation Model

2019 ◽  
Vol 11 (15) ◽  
pp. 4176 ◽  
Author(s):  
Qing Huang ◽  
Weimin Ju ◽  
Fangyi Zhang ◽  
Qian Zhang
Keyword(s):  
Climate Change ◽  
Interannual Variability ◽  
Primary Productivity ◽  
Southwest China ◽  
Net Primary Productivity ◽  
Terrestrial Ecosystem ◽  
Co2 Concentration ◽  
Series Data ◽  
Geographical Regions ◽  
The Future

Net primary productivity (NPP) is the key component of the terrestrial carbon cycle, and terrestrial NPP trends under increasing CO2 and climate change in the past and future are of great significance in the study of the global carbon budget. Here, the LPJ-DGVM was employed to simulate the magnitude and pattern of China’s terrestrial NPP using long-term series data to understand the response of terrestrial NPP to increasing CO2 concentration and climate change. The results showed that total NPP of China’s terrestrial ecosystem increased from 2.8 to 3.6 Pg C yr−1 over the period of 1961–2016, with an annual average of 3.1 Pg C yr−1. The average NPP showed a gradient decrease from the southeast to northwest. Southwest China and Northwest China, comprising mostly arid and semi-arid regions, exhibited the largest increase rate in total NPP among the six geographical regions of China. Additionally, large interannual variability around the NPP trends was presented, and NPP anomalies in China’s terrestrial ecosystem are strongly associated with the El Niño-Southern Oscillation (ENSO). Southwest China made the largest contribution to the interannual variability of national total NPP. The total NPP of China’s terrestrial ecosystem continuously increased with the concurrent increase in the CO2 concentration and climate change under different scenarios in the future. During the period from 2091 to 2100, the average total NPP under the A2 and RCP85 scenarios would reach 4.9 and 5.1 Pg C yr−1 respectively, higher than 4.2 and 3.9 Pg C yr−1 under the B1 and RCP45 scenarios. Forests, especially temperate forests, make the largest contribution to the future increase in NPP. The increase in CO2 concentration would play a dominant role in driving further NPP increase in China’s terrestrial ecosystems, and climate change may slightly attenuate the fertilization effect of CO2 on NPP.

scholarly journals Biogeochemical response of the Mediterranean Sea to the transient SRES-A2 climate change scenario

2019 ◽  
Vol 16 (1) ◽  
pp. 135-165 ◽  
Author(s):  
Camille Richon ◽  
Jean-Claude Dutay ◽  
Laurent Bopp ◽  
Briac Le Vu ◽  
James C. Orr ◽  
...  
Keyword(s):  
Climate Change ◽  
Mediterranean Sea ◽  
21St Century ◽  
Primary Productivity ◽  
Net Primary Productivity ◽  
Nutrient Concentrations ◽  
Change Scenario ◽  
Nutrient Inputs ◽  
Strait Of Gibraltar ◽  
The Mediterranean

Abstract. The Mediterranean region is a climate change hotspot. Increasing greenhouse gas emissions are projected to lead to a substantial warming of the Mediterranean Sea as well as major changes in its circulation, but the subsequent effects of such changes on marine biogeochemistry are poorly understood. Here, our aim is to investigate how climate change will affect nutrient concentrations and biological productivity in the Mediterranean Sea. To do so, we perform transient simulations with the coupled high-resolution model NEMOMED8-PISCES using the high-emission IPCC Special Report on Emissions Scenarios (SRES) A2 socioeconomic scenario and corresponding Atlantic, Black Sea, and riverine nutrient inputs. Our results indicate that nitrate is accumulating in the Mediterranean Sea over the 21st century, while phosphorus shows no tendency. These contrasting changes result from an unbalanced nitrogen-to-phosphorus input from riverine discharge and fluxes via the Strait of Gibraltar, which lead to an expansion of phosphorus-limited regions across the Mediterranean. In addition, phytoplankton net primary productivity is reduced by 10 % in the 2090s in comparison to the present state, with reductions of up to 50 % in some regions such as the Aegean Sea as a result of nutrient limitation and vertical stratification. We also perform sensitivity tests to separately study the effects of climate and biogeochemical input changes on the future state of the Mediterranean Sea. Our results show that changes in nutrient supply from the Strait of Gibraltar and from rivers and circulation changes linked to climate change may have antagonistic or synergistic effects on nutrient concentrations and surface primary productivity. In some regions such as the Adriatic Sea, half of the biogeochemical changes simulated during the 21st century are linked with external changes in nutrient input, while the other half are linked to climate change. This study is the first to simulate future transient climate change effects on Mediterranean Sea biogeochemistry but calls for further work to characterize effects from atmospheric deposition and to assess the various sources of uncertainty.

scholarly journals Reliability Ensemble Averaging of 21st century projections of terrestrial net primary productivity reduces global and regional uncertainties

2017 ◽  
Author(s):  
Jean-François Exbrayat ◽  
A. Anthony Bloom ◽  
Pete Falloon ◽  
Akihiko Ito ◽  
T. Luke Smallman ◽  
...  
Keyword(s):  
Climate Change ◽  
21St Century ◽  
Primary Productivity ◽  
Net Primary Productivity ◽  
Model Development ◽  
Model Averaging ◽  
Mean Value ◽  
System Modelling ◽  
Ensemble Averaging ◽  
Additional Information

Abstract. Multi-model averaging techniques provide opportunities to extract additional information from large ensembles of simulations. In particular, present-day model skill can be used to evaluate their potential performance in future climate simulations. Multi-model averaging methods have been used extensively in climate and hydrological sciences, but they have not been used to constrain projected plant productivity responses to climate change, which is a major uncertainty in earth system modelling. Here, we use three global observation-orientated estimates of current net primary productivity (NPP) to perform a reliability ensemble averaging (REA) using 30 global simulations of the 21st century change in NPP based on the Inter-Sectoral Impact Model Intercomparison Project (ISI-MIP) business as usual emissions scenario. We find that the three REAs support an increase in global NPP by the end of the 21st century (2090s) compared to the 2000s, which is 4–6 % stronger than the ensemble ISIMIP mean value of 23.7 Pg C y−1. Using REA also leads to a 43–67 % reduction in the global uncertainty of 21st century NPP projection, which strengthens confidence in the resilience of the CO2-fertilization effect to climate change. This reduction in uncertainty is especially clear for boreal ecosystems. Conversely, the large uncertainty that remains on the sign of the response of NPP in semi-arid regions points to the need for better observations and model development in these regions.

scholarly journals Reliability ensemble averaging of 21st century projections of terrestrial net primary productivity reduces global and regional uncertainties

2018 ◽  
Vol 9 (1) ◽  
pp. 153-165 ◽  
Author(s):  
Jean-François Exbrayat ◽  
A. Anthony Bloom ◽  
Pete Falloon ◽  
Akihiko Ito ◽  
T. Luke Smallman ◽  
...  
Keyword(s):  
Climate Change ◽  
21St Century ◽  
Primary Productivity ◽  
Net Primary Productivity ◽  
Model Development ◽  
Model Averaging ◽  
Mean Value ◽  
System Modelling ◽  
Ensemble Averaging ◽  
Additional Information

Abstract. Multi-model averaging techniques provide opportunities to extract additional information from large ensembles of simulations. In particular, present-day model skill can be used to evaluate their potential performance in future climate simulations. Multi-model averaging methods have been used extensively in climate and hydrological sciences, but they have not been used to constrain projected plant productivity responses to climate change, which is a major uncertainty in Earth system modelling. Here, we use three global observationally orientated estimates of current net primary productivity (NPP) to perform a reliability ensemble averaging (REA) method using 30 global simulations of the 21st century change in NPP based on the Inter-Sectoral Impact Model Intercomparison Project (ISIMIP) ”business as usual” emissions scenario. We find that the three REA methods support an increase in global NPP by the end of the 21st century (2095–2099) compared to 2001–2005, which is 2–3 % stronger than the ensemble ISIMIP mean value of 24.2 Pg C y−1. Using REA also leads to a 45–68 % reduction in the global uncertainty of 21st century NPP projection, which strengthens confidence in the resilience of the CO2 fertilization effect to climate change. This reduction in uncertainty is especially clear for boreal ecosystems although it may be an artefact due to the lack of representation of nutrient limitations on NPP in most models. Conversely, the large uncertainty that remains on the sign of the response of NPP in semi-arid regions points to the need for better observations and model development in these regions.

scholarly journals Effects of climatic factors on the net primary productivity in the source region of Yangtze River, China

2021 ◽  
Vol 11 (1) ◽  
Author(s):  
Zhe Yuan ◽  
Yongqiang Wang ◽  
Jijun Xu ◽  
Zhiguang Wu
Keyword(s):  
Climate Change ◽  
Primary Productivity ◽  
Yangtze River ◽  
Net Primary Productivity ◽  
Climatic Factors ◽  
Source Region ◽  
Primary Reason ◽  
Vegetation Types ◽  
Temperature And Precipitation ◽  
Increasing Trend

AbstractThe ecosystem of the Source Region of Yangtze River (SRYR) is highly susceptible to climate change. In this study, the spatial–temporal variation of NPP from 2000 to 2014 was analyzed, using outputs of Carnegie–Ames–Stanford Approach model. Then the correlation characteristics of NPP and climatic factors were evaluated. The results indicate that: (1) The average NPP in the SRYR is 100.0 gC/m2 from 2000 to 2014, and it shows an increasing trend from northwest to southeast. The responses of NPP to altitude varied among the regions with the altitude below 3500 m, between 3500 to 4500 m and above 4500 m, which could be attributed to the altitude associated variations of climatic factors and vegetation types; (2) The total NPP of SRYR increased by 0.18 TgC per year in the context of the warmer and wetter climate during 2000–2014. The NPP was significantly and positively correlated with annual temperature and precipitation at interannual time scales. Temperature in February, March, May and September make greater contribution to NPP than that in other months. And precipitation in July played a more crucial role in influencing NPP than that in other months; (3) Climatic factors caused the NPP to increase in most of the SRYR. Impacts of human activities were concentrated mainly in downstream region and is the primary reason for declines in NPP.

scholarly journals Impact of future climate change on water supply and irrigation demand in a small mediterranean catchment. Case study: Nebhana dam system, Tunisia

2019 ◽  
Vol 11 (4) ◽  
pp. 1724-1747 ◽  
Author(s):  
M. Allani ◽  
R. Mezzi ◽  
A. Zouabi ◽  
R. Béji ◽  
F. Joumade-Mansouri ◽  
...  
Keyword(s):  
Climate Change ◽  
Water Supply ◽  
General Circulation ◽  
General Circulation Models ◽  
Future Climate ◽  
Annual Rainfall ◽  
Future Climate Change ◽  
Cycle Duration ◽  
Climate Change Scenarios ◽  
Time Periods

Abstract This study evaluates the impacts of climate change on water supply and demand of the Nebhana dam system. Future climate change scenarios were obtained from five general circulation models (GCMs) of CMIP5 under RCP 4.5 and 8.5 emission scenarios for the time periods, 2021–2040, 2041–2060 and 2061–2080. Statistical downscaling was applied using LARS-WG. The GR2M hydrological model was calibrated, validated and used as input to the WEAP model to assess future water availability. Expected crop growth cycle lengths were estimated using a growing degree days model. By means of the WEAP-MABIA method, projected crop and irrigation water requirements were estimated. Results show an average increase in annual ETo of 6.1% and a decrease in annual rainfall of 11.4%, leading to a 24% decrease in inflow. Also, crops' growing cycles will decrease from 5.4% for wheat to 31% for citrus trees. The same tendency is observed for ETc. Concerning irrigation requirement, variations are more moderated depending on RCPs and time periods, and is explained by rainfall and crop cycle duration variations. As for demand and supply, results currently show that supply does not meet the system demand. Climate change could worsen the situation unless better planning of water surface use is done.

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