Gross primary productivity and water use efficiency are increasing in a high rainfall tropical savanna

Hutley, Lindsay B.; Beringer, Jason; Fatichi, Simone; Schymanski, Stanislaus J.; Northwood, Matthew

doi:10.1111/gcb.16012

Cited by 22 publications

(10 citation statements)

References 178 publications

(229 reference statements)

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“…Based on previous studies, the WUE does not significantly correlate with latitude because of the similar changes in GPP and ET with variations in latitude [10]. However, in other studies, the WUE of forest ecosystems increased or decreased with increasing latitude [11][12][13][14]. Such controversy has also been observed regarding the relationships between WUE and the precipitation, temperature, VPD, LAI, and Rg [15][16][17][18].…”

Section: Introductionmentioning

confidence: 90%

Inherent Water-Use Efficiency of Different Forest Ecosystems and Its Relations to Climatic Variables

Liu

et al. 2022

Forests

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Inherent water-use efficiency (IWUE) is a vital parameter connecting the carbon and water cycles. However, the factors influencing the IWUE in different forest ecosystems are still a subject of debate. In this work, FLUXNET platform measurements of 67 forest sites were used to detect trends of the IWUE of four forest ecosystems, namely deciduous broadleaf forests (DBF), evergreen broadleaf forests (EBF), needle-leaf forests (ENF), and mixed forests (MF). The IWUE differed significantly among different forest ecosystems and positively correlated with temperature and solar radiation. The IWUE of EBF was the highest at 32.02 g·C·Kg·H2O−1. The values of DBF and MF were similar and higher than that of ENF. With increasing latitude, the IWUE increased first and then decreased, with a maximum of 35° N. The IWUE of EBF was negatively correlated with precipitation and leaf area index. Temperature and solar radiation were the main factors controlling the IWUE of forest ecosystems, whereas precipitation was the major factor controlling the inter-annual variation in the ΔIWUE of forest ecosystems. Our results provide a scientific basis for the study of forest carbon sinks, forest eco-hydrological processes, and forest ecosystem responses to global climatic changes.

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Section: Introductionmentioning

confidence: 90%

Inherent Water-Use Efficiency of Different Forest Ecosystems and Its Relations to Climatic Variables

Liu

et al. 2022

Forests

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“…The flux tower sites are relatively undisturbed, but suffer occasionally from fires (Beringer et al, 2007;Hutley et al, 2011). At the same time, at Howard Springs it has been noted that trends exist in gross primary productivity and water-use efficiency (Hutley et al, 2022). Also at the catchments and additional locations along the transect, changes and trends may have occurred during this period.…”

Section: Limitationsmentioning

confidence: 99%

Vegetation optimality explains the convergence of catchments on the Budyko curve

Nijzink

Schymanski

2022

Hydrol. Earth Syst. Sci.

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Abstract. The Budyko framework puts the long-term mean annual evapotranspiration (ET) of a catchment in relation to its maximum possible value determined by the conservation of mass (ET cannot exceed mean annual precipitation) and energy (ET can not exceed mean annual net radiation) in the absence of significant storage contributions. Most catchments plot relatively close to this physical limit, which allowed the development of an empirical equation (often referred to as the Budyko curve) for estimating mean annual evaporation and runoff from observed net radiation and precipitation. Parametric forms of the curve often use a shape parameter, n, that is seen as a catchment characteristic. However, a satisfying explanation for the convergence and self-organization of catchments around such an empirical curve is still lacking. In this study, we explore if vegetation optimality can explain the convergence of catchments along a Budyko curve and in how far can n be seen as a catchment characteristic. The Vegetation Optimality Model (VOM) optimizes vegetation properties and behavior (e.g., rooting depths, vegetation cover, stomatal control) to maximize the difference between the total carbon taken up from the atmosphere and the carbon used for maintenance of plant tissues involved in its uptake, i.e., the long-term net carbon profit (NCP). This optimization is entirely independent of observed ET and hence the VOM does not require calibration for predicting ET. In a first step, the VOM was fully optimized for the observed atmospheric forcing at five flux tower sites along the North Australian Tropical Transect, as well as 36 additional locations near the transect and six Australian catchments. In addition, the VOM was run without vegetation for all sites, meaning that all precipitation was partitioned into soil evaporation and runoff. For comparison, three conceptual hydrological models (TUWmodel, GR4J, and FLEX) were calibrated for the Australian catchments using the observed precipitation and runoff. Subsequently, we emulated step changes in climate by multiplying precipitation (P) by factors ranging between 0.2 and 2 before running the VOM and hydrological models without changing the vegetation properties or model parameters, emulating invariant catchment characteristics under a changed climate. In a last step, the VOM was re-optimized for the different P amounts, allowing vegetation to adapt to the new situation. Eventually, Budyko curves were fit by adapting the parameter n to the model results. This was carried out for both multiple sites simultaneously and for each individual study site, thereby assuming that n is a site-specific characteristic. The optimized VOM runs tracked relatively close to a Budyko curve with a realistic n value and close to observations, whereas the runs without vegetation led to significantly lower evaporative fractions and unrealistically low n values compared with literature. When fitting n to individual catchments, changes in P led to changes in n (increasing n for decreasing P) in all model runs (including the three conceptual models) except if the VOM was re-optimized for each change in P, which brought the value of n back close to its value for the unperturbed P in each catchment. For the re-optimized VOM runs, the variation in n between catchments was greater than within each catchment in response to multiplications of P with a factor 0.2 to 2. These findings suggest that optimality may explain the self-organization of catchments in Budyko space, and that the accompanying parameter n does not remain constant for constant catchment and vegetation conditions as hypothesized in the literature, but in fact emerges through the adaptation of vegetation to climatic conditions in a given hydrological setting. Moreover, the results suggest that n might initially increase in response to suddenly reduced P, and only slowly returns to its original, catchment-specific value, as vegetation re-adjusts to the new climate over decades and centuries. This may constitute a new basis for the evaluation and prediction of catchment responses to climatic shifts.

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“…Rising CO 2 was also proven to reduce stomatal conductance to increase water use efficiency (Walker et al., 2021). One point of view is that this effect of rising CO 2 leads to global vegetation carbon uptake increasing at little cost of water consumption (L. Cheng et al., 2017; Hutley et al., 2022; Keenan et al., 2013). Another point of view argues that the improvement of photosynthesis would increase leaf area to accelerate evapotranspiration, which probably offsets the effort from higher water use efficiency to saving water, especially in semiarid and arid areas (Ukkola et al., 2016; Y. Zhang et al., 2022; Zhou et al., 2017).…”

Section: Introductionmentioning

confidence: 99%

Climate Change and Rising CO₂ Amplify the Impact of Land Use/Cover Change on Carbon Budget Differentially Across China

Huang

Sun

et al. 2023

Earth's Future

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Optimizing land use/cover (LUC) decisions has been deemed the most efficient and low-cost way to mitigate climate change and realize carbon neutrality (Drever et al., 2021;Fargione Joseph et al., 2018;Griscom Bronson et al., 2017). Meanwhile, numerous studies have asserted that climate change and rising CO 2 (CCRC) have a considerable effect on vegetation growth and decomposition (Mitchard, 2018;Walker et al., 2021). These global change factors undoubtedly interact with land use/cover change (LUCC) and affect the carbon cycle. However, few studies have measured the amplifying/reducing effect of CCRC on LUCC-induced carbon sink/source changes.

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Gross primary productivity and water use efficiency are increasing in a high rainfall tropical savanna

Abstract: This is an open access article under the terms of the Creat ive Commo ns Attri bution License, which permits use, distribution and reproduction in any medium, provided the original work is properly cited.

Cited by 22 publications

References 178 publications

Inherent Water-Use Efficiency of Different Forest Ecosystems and Its Relations to Climatic Variables

Inherent Water-Use Efficiency of Different Forest Ecosystems and Its Relations to Climatic Variables

Vegetation optimality explains the convergence of catchments on the Budyko curve

Climate Change and Rising CO₂ Amplify the Impact of Land Use/Cover Change on Carbon Budget Differentially Across China

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Gross primary productivity and water use efficiency are increasing in a high rainfall tropical savanna

Abstract: This is an open access article under the terms of the Creat ive Commo ns Attri bution License, which permits use, distribution and reproduction in any medium, provided the original work is properly cited.

Cited by 22 publications

References 178 publications

Inherent Water-Use Efficiency of Different Forest Ecosystems and Its Relations to Climatic Variables

Inherent Water-Use Efficiency of Different Forest Ecosystems and Its Relations to Climatic Variables

Vegetation optimality explains the convergence of catchments on the Budyko curve

Climate Change and Rising CO2 Amplify the Impact of Land Use/Cover Change on Carbon Budget Differentially Across China

Contact Info

Product

Resources

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Climate Change and Rising CO₂ Amplify the Impact of Land Use/Cover Change on Carbon Budget Differentially Across China