Examining the vulnerability of Australian eucalypts to future drought-induced tree mortality

Australia is the driest inhabited continent. Annual rainfall is low and is accompanied by marked inter-annual variability, leading to multi-year droughts. Climate change is expected to alter the frequency, magnitude, and intensity of future droughts, with potentially major environmental and socio-economic consequences for Australia. However, Australian vegetation is well adapted to extended dry periods, thus, the likelihood of drought-induced mortality in the future depends both on the severity of future drought events and inherent vegetation resilience. Here, we used the Community Atmosphere Biosphere Land Exchange (CABLE) land surface model, coupled with a stomatal optimisation scheme, to examine the projected impact of future drought for 24 Eucalyptus species. We forced CABLE with future climate from four global climate models (MIROC, ECHAM, CCCMA, and CSIRO) dynamically downscaled by three regional climate models. We separated the impact of climate change (e.g. increasing VPD, precipitation variability) from rising CO2 (increasing water use-efficiency) to provide the first assessment of future drought risk to Australian trees.

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Exploring how groundwater buffers the influence of heatwaves on vegetation function during multi-year droughts

Earth System Dynamics ◽

10.5194/esd-12-919-2021 ◽

2021 ◽

Vol 12 (3) ◽

pp. 919-938

Author(s):

Mengyuan Mu ◽

Martin G. De Kauwe ◽

Anna M. Ukkola ◽

Andy J. Pitman ◽

Weidong Guo ◽

...

Keyword(s):

Land Surface ◽

Forest Canopy ◽

Climate Models ◽

Root Zone ◽

Stomatal Closure ◽

Capillary Rise ◽

Vapour Pressure Deficit ◽

Global Climate Models ◽

Surface Model ◽

The Impact

Abstract. The co-occurrence of droughts and heatwaves can have significant impacts on many socioeconomic and environmental systems. Groundwater has the potential to moderate the impact of droughts and heatwaves by moistening the soil and enabling vegetation to maintain higher evaporation, thereby cooling the canopy. We use the Community Atmosphere Biosphere Land Exchange (CABLE) land surface model, coupled to a groundwater scheme, to examine how groundwater influences ecosystems under conditions of co-occurring droughts and heatwaves. We focus specifically on south-east Australia for the period 2000–2019, when two significant droughts and multiple extreme heatwave events occurred. We found groundwater plays an important role in helping vegetation maintain transpiration, particularly in the first 1–2 years of a multi-year drought. Groundwater impedes gravity-driven drainage and moistens the root zone via capillary rise. These mechanisms reduced forest canopy temperatures by up to 5 ∘C during individual heatwaves, particularly where the water table depth is shallow. The role of groundwater diminishes as the drought lengthens beyond 2 years and soil water reserves are depleted. Further, the lack of deep roots or stomatal closure caused by high vapour pressure deficit or high temperatures can reduce the additional transpiration induced by groundwater. The capacity of groundwater to moderate both water and heat stress on ecosystems during simultaneous droughts and heatwaves is not represented in most global climate models, suggesting that model projections may overestimate the risk of these events in the future.

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A simple approach to mimic the effect of active vegetation in hydrological models to better estimate hydrological variables under climate change

10.5194/egusphere-egu21-12025 ◽

2021 ◽

Author(s):

Thedini Asali Peiris ◽

Petra Döll

Keyword(s):

Climate Change ◽

Land Surface ◽

Climate Models ◽

Potential Evapotranspiration ◽

Global Climate ◽

Global Climate Models ◽

Hydrological Models ◽

Net Radiation ◽

Ensemble Mean ◽

The Impact

Unlike global climate models, hydrological models cannot simulate the feedbacks among atmospheric processes, vegetation, water, and energy exchange at the land surface. This severely limits their ability to quantify the impact of climate change and the concurrent increase of atmospheric CO2 concentrations on evapotranspiration and thus runoff. Hydrological models generally calculate actual evapotranspiration as a fraction of potential evapotranspiration (PET), which is computed as a function of temperature and net radiation and sometimes of humidity and wind speed. Almost no hydrological model takes into account that PET changes because the vegetation responds to changing CO2 and climate. This active vegetation response consists of three components. With higher CO2 concentrations, 1) plant stomata close, reducing transpiration (physiological effect) and 2) plants may grow better, with more leaves, increasing transpiration (structural effect), while 3) climatic changes lead to changes in plants growth and even biome shifts, changing evapotranspiration. Global climate models, which include dynamic vegetation models, simulate all these processes, albeit with a high uncertainty, and take into account the feedbacks to the atmosphere.Milly and Dunne (2016) (MD) found that in the case of RCP8.5 the change of PET (computed using the Penman-Monteith equation) between 1981- 2000 and 2081-2100 is much higher than the change of non-water-stressed evapotranspiration (NWSET) computed by an ensemble of global climate models. This overestimation is partially due to the neglect of active vegetation response and partially due to the neglected feedbacks between the atmosphere and the land surface.The objective of this paper is to present a simple approach for hydrological models that enables them to mimic the effect of active vegetation on potential evapotranspiration under climate change, thus improving computation of freshwater-related climate change hazards by hydrological models. MD proposed an alternative approach to estimate changes in PET for impact studies that is only a function of the changes in energy and not of temperature and achieves a good fit to the ensemble mean change of evapotranspiration computed by the ensemble of global climate models in months and grid cells without water stress. We developed an implementation of the MD idea for hydrological models using the Priestley-Taylor equation (PET-PT) to estimate PET as a function of net radiation and temperature. With PET-PT, an increasing temperature trend leads to strong increases in PET. Our proposed methodology (PET-MD) helps to remove this effect, retaining the impact of temperature on PET but not on long-term PET change.We implemented the PET-MD approach in the global hydrological model WaterGAP2.2d. and computed daily time series of PET between 1981 and 2099 using bias-adjusted climate data of four global climate models for RCP 8.5. We evaluated, computed PET-PT and PET-MD at the grid cell level and globally, comparing also to the results of the Milly-Dunne study. The global analysis suggests that the application of PET-MD reduces the PET change until the end of this century from 3.341 mm/day according to PET-PT to 3.087 mm/day (ensemble mean over the four global climate models).Milly, P.C.D., Dunne K.A. (2016). DOI:10.1038/nclimate3046.

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Predicting the response of the Amazon rainforest to persistent drought conditions under current and future climates: a major challenge for global land surface models

Geoscientific Model Development ◽

10.5194/gmd-7-2933-2014 ◽

2014 ◽

Vol 7 (6) ◽

pp. 2933-2950 ◽

Cited By ~ 29

Author(s):

E. Joetzjer ◽

C. Delire ◽

H. Douville ◽

P. Ciais ◽

B. Decharme ◽

...

Keyword(s):

Land Surface ◽

Tree Mortality ◽

Climate Models ◽

Global Climate ◽

Land Surface Model ◽

Co2 Concentration ◽

Accurate Estimate ◽

Global Climate Models ◽

Surface Model ◽

Vegetation Response

Abstract. While a majority of global climate models project drier and longer dry seasons over the Amazon under higher CO2 levels, large uncertainties surround the response of vegetation to persistent droughts in both present-day and future climates. We propose a detailed evaluation of the ability of the ISBACC (Interaction Soil–Biosphere–Atmosphere Carbon Cycle) land surface model to capture drought effects on both water and carbon budgets, comparing fluxes and stocks at two recent throughfall exclusion (TFE) experiments performed in the Amazon. We also explore the model sensitivity to different water stress functions (WSFs) and to an idealized increase in CO2 concentration and/or temperature. In spite of a reasonable soil moisture simulation, ISBACC struggles to correctly simulate the vegetation response to TFE whose amplitude and timing is highly sensitive to the WSF. Under higher CO2 concentrations, the increased water-use efficiency (WUE) mitigates the sensitivity of ISBACC to drought. While one of the proposed WSF formulations improves the response of most ISBACC fluxes, except respiration, a parameterization of drought-induced tree mortality is missing for an accurate estimate of the vegetation response. Also, a better mechanistic understanding of the forest responses to drought under a warmer climate and higher CO2 concentration is clearly needed.

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Predicting the response of the Amazon rainforest to persistent drought conditions under current and future climates: a major challenge for global land surface models

Geoscientific Model Development Discussions ◽

10.5194/gmdd-7-5295-2014 ◽

2014 ◽

Vol 7 (4) ◽

pp. 5295-5340 ◽

Cited By ~ 3

Author(s):

E. Joetzjer ◽

C. Delire ◽

H. Douville ◽

P. Ciais ◽

B. Decharme ◽

...

Keyword(s):

Land Surface ◽

Tree Mortality ◽

Climate Models ◽

Global Climate ◽

Land Surface Model ◽

Co2 Concentration ◽

Accurate Estimate ◽

Global Climate Models ◽

Surface Model ◽

Vegetation Response

Abstract. While a majority of Global Climate Models project dryer and longer dry seasons over the Amazon under higher CO2 levels, large uncertainties surround the response of vegetation to persistent droughts in both present-day and future climates. We propose a detailed evaluation of the ability of the ISBACC Land Surface Model to capture drought effects on both water and carbon budgets, comparing fluxes and stocks at two recent ThroughFall Exclusion (TFE) experiments performed in the Amazon. We also explore the model sensitivity to different Water Stress Function (WSF) and to an idealized increase in CO2 concentration and/or temperature. In spite of a reasonable soil moisture simulation, ISBACC struggles to correctly simulate the vegetation response to TFE whose amplitude and timing is highly sensitive to the WSF. Under higher CO2 concentration, the increased Water Use Efficiency (WUE) mitigates the ISBACC's sensitivity to drought. While one of the proposed WSF formulation improves the response of most ISBACC fluxes, except respiration, a parameterization of drought-induced tree mortality is missing for an accurate estimate of the vegetation response. Also, a better mechanistic understanding of the forest responses to drought under a warmer climate and higher CO2 concentration is clearly needed.

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Risk and reward of the global truffle sector under predicted climate change

Environmental Research Letters ◽

10.1088/1748-9326/ac47c4 ◽

2022 ◽

Author(s):

Tomas Cejka ◽

Elizabeth Isaac ◽

Daniel Oliach ◽

Fernando Martinez-Pena ◽

Simon Egli ◽

...

Keyword(s):

Climate Change ◽

Land Surface ◽

Climate Models ◽

Climate Model ◽

Heat Waves ◽

Global Climate Models ◽

Future Climate Change ◽

Production Rates ◽

Price Levels ◽

The Impact

Abstract Climate change has been described as the main threat for the cultivation and growth of truffles, but hydroclimate variability and model uncertainty challenge regional projections and adaptation strategies of the emerging sector. Here, we conduct a literature review to define the main Périgord truffle growing regions around the world and use 20 global climate models to assess the impact of future trends and extremes in temperature, precipitation and soil moisture on truffle production rates and price levels in all cultivation regions in the Americas, Europe, South Africa, and Australasia. Climate model simulations project 2.3 million km2 of suitable land for truffle growth will experience 50% faster aridification than the rests of the global land surface, with significantly more heat waves between 2070 and 2099 CE. Overall, truffle production rates will decrease by ~15%, while associated price levels will increase by ~36%. At the same time, a predicted increase in summer precipitation and less intense warming over Australasia will likely alleviate water scarcity and support higher yields of more affordable truffles. Our findings are relevant for truffle farmers and businesses to adapt their irrigation systems and management strategies to future climate change.

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Application of SWAT in Hydrological Simulation of Complex Mountainous River Basin (Part II: Climate Change Impact Assessment)

Water ◽

10.3390/w13111548 ◽

2021 ◽

Vol 13 (11) ◽

pp. 1548

Author(s):

Suresh Marahatta ◽

Deepak Aryal ◽

Laxmi Prasad Devkota ◽

Utsav Bhattarai ◽

Dibesh Shrestha

Keyword(s):

Climate Change ◽

River Basin ◽

Climate Models ◽

Assessment Tool ◽

Swat Model ◽

Global Climate Models ◽

Climate Data ◽

The Future ◽

The Impact ◽

Mountainous River

This study aims at analysing the impact of climate change (CC) on the river hydrology of a complex mountainous river basin—the Budhigandaki River Basin (BRB)—using the Soil and Water Assessment Tool (SWAT) hydrological model that was calibrated and validated in Part I of this research. A relatively new approach of selecting global climate models (GCMs) for each of the two selected RCPs, 4.5 (stabilization scenario) and 8.5 (high emission scenario), representing four extreme cases (warm-wet, cold-wet, warm-dry, and cold-dry conditions), was applied. Future climate data was bias corrected using a quantile mapping method. The bias-corrected GCM data were forced into the SWAT model one at a time to simulate the future flows of BRB for three 30-year time windows: Immediate Future (2021–2050), Mid Future (2046–2075), and Far Future (2070–2099). The projected flows were compared with the corresponding monthly, seasonal, annual, and fractional differences of extreme flows of the simulated baseline period (1983–2012). The results showed that future long-term average annual flows are expected to increase in all climatic conditions for both RCPs compared to the baseline. The range of predicted changes in future monthly, seasonal, and annual flows shows high uncertainty. The comparative frequency analysis of the annual one-day-maximum and -minimum flows shows increased high flows and decreased low flows in the future. These results imply the necessity for design modifications in hydraulic structures as well as the preference of storage over run-of-river water resources development projects in the study basin from the perspective of climate resilience.

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Assessing the impact of global warming on worldwide open field tomato cultivation through CSIRO-Mk3·0 global climate model

The Journal of Agricultural Science ◽

10.1017/s0021859616000654 ◽

2016 ◽

Vol 155 (3) ◽

pp. 407-420 ◽

Cited By ~ 7

Author(s):

R. S. SILVA ◽

L. KUMAR ◽

F. SHABANI ◽

M. C. PICANÇO

Keyword(s):

Climate Change ◽

Global Warming ◽

Open Field ◽

Climate Models ◽

Climate Model ◽

Global Climate ◽

Global Climate Model ◽

Current Model ◽

Global Climate Models ◽

The Impact

SUMMARYTomato (Solanum lycopersicum L.) is one of the most important vegetable crops globally and an important agricultural sector for generating employment. Open field cultivation of tomatoes exposes the crop to climatic conditions, whereas greenhouse production is protected. Hence, global warming will have a greater impact on open field cultivation of tomatoes rather than the controlled greenhouse environment. Although the scale of potential impacts is uncertain, there are techniques that can be implemented to predict these impacts. Global climate models (GCMs) are useful tools for the analysis of possible impacts on a species. The current study aims to determine the impacts of climate change and the major factors of abiotic stress that limit the open field cultivation of tomatoes in both the present and future, based on predicted global climate change using CLIMatic indEX and the A2 emissions scenario, together with the GCM Commonwealth Scientific and Industrial Research Organisation (CSIRO)-Mk3·0 (CS), for the years 2050 and 2100. The results indicate that large areas that currently have an optimum climate will become climatically marginal or unsuitable for open field cultivation of tomatoes due to progressively increasing heat and dry stress in the future. Conversely, large areas now marginal and unsuitable for open field cultivation of tomatoes will become suitable or optimal due to a decrease in cold stress. The current model may be useful for plant geneticists and horticulturalists who could develop new regional stress-resilient tomato cultivars based on needs related to these modelling projections.

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Calculating the turbulent fluxes in the atmospheric surface layer with neural networks

10.5194/gmd-2018-263 ◽

2018 ◽

Author(s):

Lukas Hubert Leufen ◽

Gerd Schädler

Keyword(s):

Land Surface ◽

Field Experiments ◽

Climate Models ◽

Similarity Theory ◽

Turbulent Fluxes ◽

Global Climate Models ◽

Surface Model ◽

Time Step ◽

One Dimensional ◽

Stability Functions

Abstract. The turbulent fluxes of momentum, heat and water vapour link the Earth's surface with the atmosphere. The correct modelling of the flux interactions between these two systems with very different time scales is therefore vital for climate (resp. Earth system) models. Conventionally, these fluxes are modelled using Monin–Obukhov similarity theory (MOST) with stability functions derived from a small number of field experiments; this results in a range of formulations of these functions and thus also in the flux calculations; furthermore, the underlying equations are non-linear and have to be solved iteratively at each time step of the model. For these reasons, we tried here a different approach, namely using an artificial neural network (ANN) to calculate the fluxes resp. the scaling quantities u* and θ*, thus avoiding explicit formulas for the stability functions. The network was trained and validated with multi-year datasets from seven grassland, forest and wetland sites worldwide using the Broyden–Fletcher–Goldfarb–Shanno (BFGS) quasi-Newton backpropagation algorithm and six-fold cross validation. Extensive sensitivity tests showed that an ANN with six input variables and one hidden layer gave results comparable to (and in some cases even slightly better than) the standard method. Similar satisfying results were obtained when the ANN routine was implemented in a one-dimensional stand alone land surface model (LSM), opening the way to implementation in three-dimensional climate models. In case of the one-dimensional LSM, no CPU time was saved when using the ANN version, since the small time step of the standard version required only one iteration in most cases. This could be different in models with longer time steps, e.g. global climate models.

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Uncertainty Impacts of Climate Change and Downscaling Methods on Future Runoff Projections in the Biliu River Basin

Water ◽

10.3390/w11102130 ◽

2019 ◽

Vol 11 (10) ◽

pp. 2130 ◽

Cited By ~ 3

Author(s):

Zhu ◽

Zhang ◽

Wu ◽

Qi ◽

Fu ◽

...

Keyword(s):

Climate Change ◽

River Basin ◽

Water Resource Management ◽

Climate Models ◽

Dynamical Downscaling ◽

Global Climate ◽

Global Climate Models ◽

Liaoning Province ◽

Lower Envelope ◽

The Impact

This paper assesses the uncertainties in the projected future runoff resulting from climate change and downscaling methods in the Biliu River basin (Liaoning province, Northeast China). One widely used hydrological model SWAT, 11 Global Climate Models (GCMs), two statistical downscaling methods, four dynamical downscaling datasets, and two Representative Concentration Pathways (RCP4.5 and RCP8.5) are applied to construct 22 scenarios to project runoff. Hydrology variables in historical and future periods are compared to investigate their variations, and the uncertainties associated with climate change and downscaling methods are also analyzed. The results show that future temperatures will increase under all scenarios and will increase more under RCP8.5 than RCP4.5, while future precipitation will increase under 16 scenarios. Future runoff tends to decrease under 13 out of the 22 scenarios. We also found that the mean runoff changes ranging from −38.38% to 33.98%. Future monthly runoff increases in May, June, September, and October and decreases in all the other months. Different downscaling methods have little impact on the lower envelope of runoff, and they mainly impact the upper envelope of the runoff. The impact of climate change can be regarded as the main source of the runoff uncertainty during the flood period (from May to September), while the impact of downscaling methods can be regarded as the main source during the non-flood season (from October to April). This study separated the uncertainty impact of different factors, and the results could provide very important information for water resource management.

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Timothy yield and nutritive value with a three-harvest system under the projected future climate in Canada

Canadian Journal of Plant Science ◽

10.4141/cjps2013-279 ◽

2014 ◽

Vol 94 (2) ◽

pp. 213-222 ◽

Cited By ~ 15

Author(s):

Qi Jing ◽

Gilles Bélanger ◽

Budong Qian ◽

Vern Baron

Keyword(s):

Climate Change ◽

Nutritive Value ◽

Climate Models ◽

Phleum Pratense ◽

Global Climate Models ◽

Future Climate ◽

Climate Scenarios ◽

Intergovernmental Panel ◽

Stochastic Weather Generator ◽

The Impact

Jing, Q., Bélanger, G., Qian, B. and Baron, V. 2014. Timothy yield and nutritive value with a three-harvest system under the projected future climate in Canada. Can. J. Plant Sci. 94: 213–222. Timothy (Phleum pratense L.) is harvested twice annually in Canada but with projected climate change, an additional harvest may be possible. Our objective was to evaluate the impact on timothy dry matter (DM) yield and key nutritive value attributes of shifting from a two- to a three-harvest system under projected future climate conditions at 10 sites across Canada. Future climate scenarios were generated with a stochastic weather generator (AAFC-WG) using two global climate models under the forcing of two Intergovernmental Panel on Climate Change emission scenarios and, then, used by the CATIMO (Canadian Timothy Model) grass model to simulate DM yield and key nutritive value attributes. Under future climate scenarios (2040–2069), the additional harvest and the resulting three-harvest system are expected to increase annual DM yield (+0.46 to +2.47 Mg DM ha−1) compared with a two-harvest system across Canada but the yield increment will on average be greater in eastern Canada (1.88 Mg DM ha−1) and Agassiz (2.02 Mg DM ha−1) than in the prairie provinces of Canada (0.84 Mg DM ha−1). The DM yield of the first harvest in a three-harvest system is expected to be less than in the two-harvest system, while that of the second harvest would be greater. Decreases in average neutral detergent fibre (NDF) concentration (−19 g kg−1 DM) and digestibility (dNDF, −5 g kg−1 NDF) are also expected with the three-harvest system under future conditions. Our results indicate that timothy will take advantage of projected climate change, through taking a third harvest, thereby increasing annual DM production.

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