scholarly journals Decomposition analysis on soybean productivity increase under elevated CO2 using 3-D canopy model reveals synergestic effects of CO2 and light in photosynthesis

2019 ◽  
Vol 126 (4) ◽  
pp. 601-614 ◽  
Author(s):  
Qingfeng Song ◽  
Venkatraman Srinivasan ◽  
Steve P Long ◽  
Xin-Guang Zhu
Keyword(s):  
Climate Change ◽  
Elevated Co2 ◽  
Developmental Stages ◽  
Decomposition Analysis ◽  
Crop Productivity ◽  
Minor Role ◽  
Co2 Uptake ◽  
Canopy Architecture ◽  
Area Index ◽  
Canopy Model

Abstract Background and Aims Understanding how climate change influences crop productivity helps in identifying new options to increase crop productivity. Soybean is the most important dicotyledonous seed crop in terms of planting area. Although the impacts of elevated atmospheric [CO2] on soybean physiology, growth and biomass accumulation have been studied extensively, the contribution of different factors to changes in season-long whole crop photosynthetic CO2 uptake [gross primary productivity (GPP)] under elevated [CO2] have not been fully quantified. Methods A 3-D canopy model combining canopy 3-D architecture, ray tracing and leaf photosynthesis was built to: (1) study the impacts of elevated [CO2] on soybean GPP across a whole growing season; (2) dissect the contribution of different factors to changes in GPP; and (3) determine the extent, if any, of synergism between [CO2] and light on changes in GPP. The model was parameterized from measurements of leaf physiology and canopy architectural parameters at the soybean Free Air CO2 Enrichment (SoyFACE) facility in Champaign, Illinois. Key Results Using this model, we showed that both a CO2 fertilization effect and changes in canopy architecture contributed to the large increase in GPP while acclimation in photosynthetic physiological parameters to elevated [CO2] and altered leaf temperature played only a minor role in the changes in GPP. Furthermore, at early developmental stages, elevated [CO2] increased leaf area index which led to increased canopy light absorption and canopy photosynthesis. At later developmental stages, on days with high ambient light levels, the proportion of leaves in a canopy limited by Rubisco carboxylation increased from 12.2 % to 35.6 %, which led to a greater enhancement of elevated [CO2] to GPP. Conclusions This study develops a new method to dissect the contribution of different factors to responses of crops under climate change. We showed that there is a synergestic effect of CO2 and light on crop growth under elevated CO2 conditions.

Impact of Elevated Atmospheric CO2 on Biodiversity: Mechanistic Population-Dynamic Perspective

1993 ◽  
Vol 41 (1) ◽  
pp. 11 ◽  
Author(s):  
HP Possingham
Keyword(s):  
Climate Change ◽  
Environmental Change ◽  
Elevated Co2 ◽  
Physical Environment ◽  
Keystone Species ◽  
Direct Interaction ◽  
Terrestrial Ecosystems ◽  
Minor Role ◽  
Elevated Atmospheric Co2 ◽  
The Impact

Biodiversity is characteristically defined on three levels: genetic diversity, species diversity and ecosystem diversity. In this paper I consider the impact of elevated CO2 and associated climate change on the biodiversity of terrestrial systems at the species level. I attempt to understand the impact of a rapidly changing physical environment mechanistically. The direct impact of elevated CO2 is emphasised. A changing physical environment will cause behavioural and physiological responses in organisms that will affect population dynamics and interspecific relationships. In the short term, extinctions will occur via the direct interaction of species with their changing environment. Species exposed to new diseases, and species dependent on mutualists or keystone species that become extinct or change geographical range, may become extinct rapidly through interactions with other species. I hypothesise that the effect of environmental change on competitive interactions will play a minor role in causing declines in biodiversity. Existing literature on the impact of climate change on terrestrial ecosystems emphasises the way in which ecosystems and species should track suitable climates across the landscape. Here I argue that each species will be affected in one, or a combination, of the following ways: range change to track shifting climate zones, tolerating the environmental change, microevolutionary change, and extinction.

scholarly journals Tackling G × E × M interactions to close on-farm yield-gaps: creating novel pathways for crop improvement by predicting contributions of genetics and management to crop productivity

2021 ◽  
Author(s):  
Mark Cooper ◽  
Kai P. Voss-Fels ◽  
Carlos D. Messina ◽  
Tom Tang ◽  
Graeme L. Hammer
Keyword(s):  
Climate Change ◽  
Crop Improvement ◽  
Target Population ◽  
Crop Productivity ◽  
Climate Change Scenarios ◽  
Global Food Security ◽  
Genotype By Environment ◽  
Improvement Strategies ◽  
Yield Gaps ◽  
On Farm

Abstract Key message Climate change and Genotype-by-Environment-by-Management interactions together challenge our strategies for crop improvement. Research to advance prediction methods for breeding and agronomy is opening new opportunities to tackle these challenges and overcome on-farm crop productivity yield-gaps through design of responsive crop improvement strategies. Abstract Genotype-by-Environment-by-Management (G × E × M) interactions underpin many aspects of crop productivity. An important question for crop improvement is “How can breeders and agronomists effectively explore the diverse opportunities within the high dimensionality of the complex G × E × M factorial to achieve sustainable improvements in crop productivity?” Whenever G × E × M interactions make important contributions to attainment of crop productivity, we should consider how to design crop improvement strategies that can explore the potential space of G × E × M possibilities, reveal the interesting Genotype–Management (G–M) technology opportunities for the Target Population of Environments (TPE), and enable the practical exploitation of the associated improved levels of crop productivity under on-farm conditions. Climate change adds additional layers of complexity and uncertainty to this challenge, by introducing directional changes in the environmental dimension of the G × E × M factorial. These directional changes have the potential to create further conditional changes in the contributions of the genetic and management dimensions to future crop productivity. Therefore, in the presence of G × E × M interactions and climate change, the challenge for both breeders and agronomists is to co-design new G–M technologies for a non-stationary TPE. Understanding these conditional changes in crop productivity through the relevant sciences for each dimension, Genotype, Environment, and Management, creates opportunities to predict novel G–M technology combinations suitable to achieve sustainable crop productivity and global food security targets for the likely climate change scenarios. Here we consider critical foundations required for any prediction framework that aims to move us from the current unprepared state of describing G × E × M outcomes to a future responsive state equipped to predict the crop productivity consequences of G–M technology combinations for the range of environmental conditions expected for a complex, non-stationary TPE under the influences of climate change.

scholarly journals Implementing the nitrogen cycle into the dynamic global vegetation, hydrology, and crop growth model LPJmL (version 5.0)

2018 ◽  
Vol 11 (7) ◽  
pp. 2789-2812 ◽  
Author(s):  
Werner von Bloh ◽  
Sibyll Schaphoff ◽  
Christoph Müller ◽  
Susanne Rolinski ◽  
Katharina Waha ◽  
...  
Keyword(s):  
Growth Model ◽  
Nitrogen Cycle ◽  
Crop Productivity ◽  
Crop Growth ◽  
Limiting Factors ◽  
Full Detail ◽  
Crop Growth Model ◽  
Maintenance Respiration ◽  
Area Index ◽  
Global Vegetation

Abstract. The well-established dynamical global vegetation, hydrology, and crop growth model LPJmL is extended with a terrestrial nitrogen cycle to account for nutrient limitations. In particular, processes of soil nitrogen dynamics, plant uptake, nitrogen allocation, response of photosynthesis and maintenance respiration to varying nitrogen concentrations in plant organs, and agricultural nitrogen management are included in the model. All new model features are described in full detail and the results of a global simulation of the historic past (1901–2009) are presented for evaluation of the model performance. We find that the implementation of nitrogen limitation significantly improves the simulation of global patterns of crop productivity. Regional differences in crop productivity, which had to be calibrated via a scaling of the maximum leaf area index, can now largely be reproduced by the model, except for regions where fertilizer inputs and climate conditions are not the yield-limiting factors. Furthermore, it can be shown that land use has a strong influence on nitrogen losses, increasing leaching by 93 %.

Response of microalgae to elevated CO2 and temperature: impact of climate change on freshwater ecosystems

2016 ◽  
Vol 23 (19) ◽  
pp. 19847-19860 ◽  
Author(s):  
Wei Li ◽  
Xiaoguang Xu ◽  
Megumu Fujibayashi ◽  
Qigui Niu ◽  
Nobuyuki Tanaka ◽  
...  
Keyword(s):  
Climate Change ◽  
Elevated Co2 ◽  
Freshwater Ecosystems ◽  
Impact Of Climate Change ◽  
Temperature Impact ◽  
Elevated Co2 And Temperature

Climate Change Impacts on Agriculture in Latin America and the Caribbean: An Application of the Integrated Economic-Environmental Modeling (IEEM) Platform

2021 ◽  
Author(s):  
Onil Banerjee ◽  
Martin Cicowiez ◽  
Ana Rios ◽  
Cicero De Lima
Keyword(s):  
Climate Change ◽  
Labor Productivity ◽  
Latin American ◽  
Climate Change Impacts ◽  
Crop Productivity ◽  
Environmental Modeling ◽  
Sectoral Output ◽  
The Caribbean ◽  
Negative Impacts ◽  
Agricultural Yields

In this paper, we assess the economy-wide impact of Climate Change (CC) on agriculture and food security in 20 Latin American and the Caribbean (LAC) countries. Specifically, we focus on the following three channels through which CC may affect agricultural and non-agricultural production: (i) agricultural yields; (ii) labor productivity in agriculture, and; (iii) economy-wide labor productivity. We implement the analysis using the Integrated Economic-Environmental Model (IEEM) and databases for 20 LAC available through the OPEN IEEM Platform. Our analysis identifies those countries most affected according to key indicators including Gross Domestic Product (GDP), international commerce, sectoral output, poverty, and emissions. Most countries experience negative impacts on GDP, with the exception of the major soybean producing countries, namely, Brazil, Argentina and Uruguay. We find that CC-induced crop productivity and labor productivity changes affect countries differently. The combined impact, however, indicates that Belize, Nicaragua, Guatemala and Paraguay would fare the worst. Early identification of these hardest hit countries can enable policy makers pre-empting these effects and beginning the design of adaptation strategies early on. In terms of greenhouse gas emissions, only Argentina, Chile and Uruguay would experience small increases in emissions.

Subsoil organic carbon turnover is dominantly controlled by soil properties in grasslands across China

2021 ◽  
Author(s):  
Yuehong Shi ◽  
Xiaolu Tang ◽  
Peng Yu ◽  
Li Xu ◽  
Guo Chen ◽  
...  
Keyword(s):  
Climate Change ◽  
Organic Carbon ◽  
Soil Properties ◽  
Soil Carbon ◽  
Carbon Turnover ◽  
Area Index ◽  
Important Indicator ◽  
Environmental Controls ◽  
Biogeochemical Models ◽  
Soc Stock

<p>Soil carbon turnover time (τ, year) is an important indicator of soil carbon stability, and a major factor in determining soil carbon sequestration capacity. Many studies investigated τ in the topsoil or the first meter underground, however, little is known about subsoil τ (0.2 – 1.0 m) and its environmental drivers, while world subsoils below 0.2 m accounts for the majority of total soil organic carbon (SOC) stock and may be as sensitive as that of the topsoil to climate change. We used the observations from the published literatures to estimate subsoil τ (the ratio of SOC stock to net primary productivity) in grasslands across China and employed regression analysis to detect the environmental controls on subsoil τ. Finally, structural equation modelling (SEM) was applied to identify the dominant environmental driver (including climate, vegetation and soil). Results showed that subsoil τ varied greatly from 5.52 to 702.17 years, and the mean (± standard deviation) subsoil τ was 118.5 ± 97.8 years. Subsoil τ varied significantly among different grassland types that it was 164.0 ± 112.0 years for alpine meadow, 107.0 ± 47.9 years for alpine steppe, 177.0 ± 143.0 years for temperate desert steppe, 96.6 ± 88.7 years for temperate meadow steppe, 101.0 ± 75.9 years for temperate typical steppe. Subsoil τ significantly and negatively correlated (p < 0.05) with vegetation index, leaf area index and gross primary production, highlighting the importance of vegetation on τ. Mean annual temperature (MAT) and precipitation (MAP) had a negative impact on subsoil τ, indicating a faster turnover of soil carbon with the increasing of MAT or MAP under ongoing climate change. SEM showed that soil properties, such as soil bulk density, cation exchange capacity and soil silt, were the most important variables driving subsoil τ, challenging our current understanding of climatic drivers (MAT and MAP) controlling on topsoil τ, further providing new evidence that different mechanisms control topsoil and subsoil τ. These conclusions demonstrated that different environmental controls should be considered for reliable prediction of soil carbon dynamics in the top and subsoils in biogeochemical models or earth system models at regional or global scales.</p>

scholarly journals Daily and seasonal patterns of CO2 fluxes and evapotranspiration in maize-grass intercropping

2016 ◽  
Vol 20 (9) ◽  
pp. 777-782 ◽  
Author(s):  
Cássia B. Machado ◽  
José R. de S. Lima ◽  
Antonio C. D. Antonino ◽  
Eduardo S. de Souza ◽  
Rodolfo M. S. Souza ◽  
...  
Keyword(s):  
Soil Water ◽  
Climate Changes ◽  
Carbon Sink ◽  
Soil Water Storage ◽  
Co2 Uptake ◽  
Co2 Fluxes ◽  
Area Index ◽  
Available Energy ◽  
Atmospheric Carbon ◽  
Main Consumer

ABSTRACT Studies that investigate the relationships between CO2 fluxes and evapotranspiration (ET) are important for predicting how agricultural ecosystems will respond to climate changes. However, none was made on the maize-grass intercropping system in Brazil. The aim of this study was to determine the ET and CO2 fluxes in a signal grass pasture intercropped with maize, in São João, Pernambuco, Brazil, in a drought year. Furthermore, the soil water storage (SWS) and leaf area index (LAI) were determined. The latent heat flux was the main consumer of the available energy and the daily and seasonal ET and CO2 variations were mainly controlled by rainfall, through the changes in soil water content and consequently in SWS. The agroecosystem acted as an atmospheric carbon source, during drier periods and lower LAI, and as an atmospheric carbon sink, during wetter periods and higher LAI values. In a dry year, the intercropping sequestered 2.9 t C ha-1, which was equivalent to 8.0 kg C ha-1 d-1. This study showed strong seasonal fluctuations in maize-grass intercropping CO2 fluxes, due to seasonality of rainfall, and that this agroecosystem is vulnerable to low SWS, with significant reduction in CO2 uptake during these periods.

Interactive effects of elevated CO2, N deposition and climate change on plant litter quality in a California annual grassland

Oecologia ◽  
2004 ◽  
Vol 142 (3) ◽  
pp. 465-473 ◽  
Author(s):  
Hugh A. L. Henry ◽  
Elsa E. Cleland ◽  
Christopher B. Field ◽  
Peter M. Vitousek
Keyword(s):  
Climate Change ◽  
Elevated Co2 ◽  
Litter Quality ◽  
N Deposition ◽  
Plant Litter ◽  
Interactive Effects ◽  
Annual Grassland ◽  
California Annual Grassland

scholarly journals Effects of Forest Changes on Summer Surface Temperature in Changbai Mountain, China

Forests ◽  
2021 ◽  
Vol 12 (11) ◽  
pp. 1551
Author(s):  
Jiaqi Zhang ◽  
Xiangjin Shen ◽  
Yanji Wang ◽  
Ming Jiang ◽  
Xianguo Lu
Keyword(s):  
Climate Change ◽  
Surface Temperature ◽  
Land Surface ◽  
Climate Models ◽  
Regional Climate ◽  
Changbai Mountain ◽  
Vegetation Coverage ◽  
Area Index ◽  
Forest Coverage ◽  
Cooling Effects

The area and vegetation coverage of forests in Changbai Mountain of China have changed significantly during the past decades. Understanding the effects of forests and forest coverage change on regional climate is important for predicting climate change in Changbai Mountain. Based on the satellite-derived land surface temperature (LST), albedo, evapotranspiration, leaf area index, and land-use data, this study analyzed the influences of forests and forest coverage changes on summer LST in Changbai Mountain. Results showed that the area and vegetation coverage of forests increased in Changbai Mountain from 2003 to 2017. Compared with open land, forests could decrease the summer daytime LST (LSTD) and nighttime LST (LSTN) by 1.10 °C and 0.07 °C, respectively. The increase in forest coverage could decrease the summer LSTD and LSTN by 0.66 °C and 0.04 °C, respectively. The forests and increasing forest coverage had cooling effects on summer temperature, mainly by decreasing daytime temperature in Changbai Mountain. The daytime cooling effect is mainly related to the increased latent heat flux caused by increasing evapotranspiration. Our results suggest that the effects of forest coverage change on climate should be considered in climate models for accurately simulating regional climate change in Changbai Mountain of China.

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