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Rötter, Reimund P.; Geijn, S.C. van de

doi:10.1023/a:1005541132734

Cited by 182 publications

(54 citation statements)

References 109 publications

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“…Evaluating the uncertainties in the estimated carbon fluxes computed using a similar LUE-based GPP model, Yi et al (2013) concluded that the uncertainty in LUE (ε) characterization is the main source of simulated GPP uncertainty. GPP simulation errors under dry conditions are increased by an insufficient model vapour pressure deficit (VPD) representation of soil water deficit constraints on canopy stomatal conductance and ε (Leuning et al, 2005;Schaefer et al, 2012). It was also found that the GPP model does not consider the response of ε to diffuse light due to canopy clumping and shaded leaves (Gu et al, 2002).…”

Section: Verification Of Satellite-derived Gppmentioning

confidence: 99%

Environmental controls on the increasing GPP of terrestrial vegetation across northern Eurasia

et al. 2016

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Abstract. Terrestrial ecosystems of northern Eurasia are demonstrating an increasing gross primary productivity (GPP), yet few studies have provided definitive attribution for the changes. While prior studies point to increasing temperatures as the principle environmental control, influences from moisture and other factors are less clear. We assess how changes in temperature, precipitation, cloudiness, and forest fires individually contribute to changes in GPP derived from satellite data across northern Eurasia using a light-useefficiency-based model, for the period 1982-2010. We find that annual satellite-derived GPP is most sensitive to the temperature, precipitation and cloudiness of summer, which is the peak of the growing season and also the period of the year when the GPP trend is maximum. Considering the regional median, the summer temperature explains as much as 37.7 % of the variation in annual GPP, while precipitation and cloudiness explain 20.7 and 19.3 %. Warming over the period analysed, even without a sustained increase in precipitation, led to a significant positive impact on GPP for 61.7 % of the region. However, a significant negative impact on GPP was also found, for 2.4 % of the region, primarily the dryer grasslands in the south-west of the study area. For this region, precipitation positively correlates with GPP, as does cloudiness. This shows that the south-western part of northern Eurasia is relatively more vulnerable to drought than other areas. While our results further advance the notion that air temperature is the dominant environmental control for recent GPP increases across northern Eurasia, the role of precipitation and cloudiness can not be ignored.

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Section: Verification Of Satellite-derived Gppmentioning

confidence: 99%

Environmental controls on the increasing GPP of terrestrial vegetation across northern Eurasia

et al. 2016

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“…For example, field experiments within the past decade or so have shown that when temperatures go above thresholds of about 30-36 °C during flowering, crops including wheat, rice and maize experience a sharp decline in grain set and yield 3,4 . Most process-based models do not account for this, and so tend to overestimate future yields in regions experiencing more frequent hot days during the growing season 3 .…”

Section: A Model Approachmentioning

confidence: 99%

Crop–climate models need an overhaul

et al. 2011

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“…In reality these effects interact both with each other and with CO 2 concentrations (Bernacchi et al, 2006). Interactions between temperature and elevated CO 2 may (Rötter and van de Geijn, 1999;Easterling and Apps, 2005;Long et al, 2004) or may not (Morison and Lawlor, 1999) be important for crop growth and development (see Tubiello and Ewert, 2002;Porter and Semenov, 2005 for further discussion). Interactions between water stress, nutrients and CO 2 concentrations are not considered, and neither is any potential downregulation or acclimation to elevated CO 2 .…”

Section: Crop Yield Simulationsmentioning

confidence: 99%

Crop yield reduction in the tropics under climate change: Processes and uncertainties

Challinor

Wheeler

2008

Agricultural and Forest Meteorology

179

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Abstract.Many modelling studies examine the impacts of climate change on crop yield, but few explore either the underlying bio-physical processes, or the uncertainty inherent in the parameterisation of crop growth and development. We used a perturbed-parameter crop modelling method together with a regional climate model (PRECIS) driven by the 2071-2100 SRES A2 emissions scenario in order to examine processes and uncertainties in yield simulation. Crop simulations used the groundnut (i.e. peanut; Arachis hypogaea L.) version of the General Large-Area Model for annual crops (GLAM). Two sets of GLAM simulations were carried out: control simulations and fixed-duration simulations, where the impact of mean temperature on crop development rate was removed. Model results were compared to sensitivity tests using two other crop models of differing levels of complexity: CROPGRO, and the groundnut model of Hammer et al. (1995).GLAM simulations were particularly sensitive to two processes. First, elevated vapour pressure deficit (VPD) consistently reduced yield. The same result was seen in some simulations using both other crop models. Second, GLAM crop duration was longer, and yield greater, when the optimal temperature for the rate of development was exceeded. Yield increases were also seen in one other crop model. Overall, the models differed in their response to super-optimal temperatures, and that difference increased with mean temperature; percentage changes in yield between current and future climates were as diverse as -50% and over +30% for the same input data. The first process has been observed in many crop experiments, whilst the second has not. Thus, we conclude that there is a need for: (i) more process-based modelling studies of the impact of VPD on assimilation, and (ii) more experimental studies at super-optimal temperatures.Using the GLAM results, central values and uncertainty ranges were projected for mean 2071-2100 crop yields in India. In the fixed-duration simulations, ensemble mean yields mostly rose by 10 to 30%. The full ensemble range was greater than this mean change (20-60% over most of India). In the control simulations, yield stimulation by elevated CO2 was more than offset by other processes -principally accelerated crop development rates at elevated, but sub-optimal, mean temperatures. Hence the quantification of uncertainty can facilitate relatively robust indications of the likely sign of crop yield changes in future climates.

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Untitled

Cited by 182 publications

References 109 publications

Environmental controls on the increasing GPP of terrestrial vegetation across northern Eurasia

Environmental controls on the increasing GPP of terrestrial vegetation across northern Eurasia

Crop–climate models need an overhaul

Crop yield reduction in the tropics under climate change: Processes and uncertainties

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