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Rain use efficiency (RUE) quantifies the ecosystem's capacity to use precipitation water to assimilate atmospheric CO 2 . The spatial distribution of RUE and its drivers across the Australian continent is largely unknown. This knowledge gap limits our understanding of the possible contribution of Australian ecosystems to global carbon assimilation. This study investigates the spatial distribution of RUE across diverse terrestrial ecosystems in Australia. The results show that RUE ranges from 0.43 (1st percentile) to 3.10 (99th percentile) g C m -2  mm -1 with a continental mean of 1.19 g C m -2  mm -1 . About 68 % of the spatiotemporal variability of RUE can be explained by a multiple linear regression model primarily contributed by climatic predictors. Benchmarked by the model estimation, drainage-diverging/converging landscapes tend to have reduced/increased RUE. The model also revealed the impact of increasing atmospheric CO 2 concentration on RUE. The continental mean RUE would increase by between 29.3 and 64.8 % by the end of this century under the SSP5-8.5 scenario in which the CO 2 concentration is projected to double from the present level. This increase in projected RUE is attributed to the assumed greening effect of increasing CO 2 concentration, which does not consider the saturation of CO 2 fertilisation effect and the warming effect on increasing wildfire occurrence. Under the SSP1-2.6 scenario, RUE would decrease by about 7 %. This study provides baseline RUEs of various ecosystems in Australia for investigating the impacts of human interferences and climate change on the capacity of Australian vegetation to assimilate atmospheric CO 2 under given precipitation., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2024 The Authors. Published by Elsevier B.V. All rights reserved.)

[Display omitted] • Mild impact of climate extremes on vegetation was found for Hu Line transect in China. • Latitudinal and altitudinal patterns of vegetation responses to climate were analyzed. • Non-woody plants in the mid-to-high latitudes were more sensitive to climate extremes. • Productivity above 45°N increased with drought severity due to favorable environment. • Policy making suggestions were proposed with emphasis on the identified hotspots. Climate projections infer increasing frequency of extreme events in the future which would alter terrestrial hydrologic functioning and ecosystem services. Understanding the responses of vegetation to extreme events can provide prerequisite knowledge to mitigate climate change impacts. The relationships between climate extremes and vegetation phenology and productivity were examined for a transect along the Hu Line across China during 1988–2014. Results show that high frequency and severity of droughts existed in the mid-latitude regions where happened to be mostly occupied by grassland and cropland with relatively low productivity compared to trees. Prolonged growing seasons (4.3 days/decade) resulted mostly from advanced green-up were observed over the transect. No strong impact of extreme droughts on vegetation was observed for any plant functional types, due to the timing of drought occurrences primarily in pre- and post-growing seasons while water supply was likely not so limited during growth indicated by a drought index. Non-woody plants in the mid-to-high latitudes (37-54°N) were identified more sensitive to climate extremes than woody plants in the low latitudes. Meanwhile, grassland in the relatively low-elevation areas (<1000 m.a.s.l) was more responsive than that in the high-elevation areas. Productivity above 45°N increased with drought severity attributable to an intensified favorable environment during frequent and mild droughts with warmer temperature and increased solar radiation. The results may suggest the generally relative stability of the ecosystems along the Hu Line, however, with further deteriorating climate, the stable relationships between climate and ecosystems may be shifted, likely starting from low-elevation grassland. [ABSTRACT FROM AUTHOR]

Abstract Large-scale drought and wet phases, via ecosystem responses, can significantly influence the global atmospheric carbon budget. Australian landscapes, dominated by arid and semi-arid rangelands, play an important role in this regard. In this study, temporal variation of monthly Normalised Difference Vegetation Index (NDVI) of two rangelands with different grazing intensity were analysed against monthly precipitation and Gravity Recovery and Climate Experiment (GRACE) total water storage (TWS). The results show that regardless grazing regime, over 55% temporal variation of monthly NDVI anomaly can be explained by structured cumulative antecedent precipitation. It appears that the antecedent precipitation forms better predictor variables than GRACE TWS for this study area. The results also show that both grazing and drought reduce vegetation cover, and its response to precipitation. Drought exacerbates the grazing impact on NDVI-precipitation response. These results imply that grazing in arid and semi-arid rangelands can reduce the capacity of ecosystems to assimilate atmospheric CO 2 during wet years and episodic wet events. It is important to incorporate temporal structures of intra- and inter-annual antecedent precipitation in investigating vegetation dynamic responses to precipitation. By doing so, it is possible to predict monthly vegetation dynamics to support grazing management. Highlights • Both grazing and drought reduce vegetation response to precipitation. • Over 55% temporal variation of monthly NDVI can be explained with antecedent precipitation. • Antecedent precipitation appears to form better predictor variables than GRACE TWS for vegetation dynamics. • Different lags in vegetation-precipitation relationship for winter and summer are likely related to different frequency of heavy storms. [ABSTRACT FROM AUTHOR]

[Display omitted] • Climate effects on stomatal conductance simulation evaluated in land surface models. • Stomatal conductance simulation cause uncertainty in land surface models. • Mixed Generalized Additive Model defines the interaction between environmental factors. • Global sensitivity analysis describes uncertainty to parameterization. Ongoing changes in climate and carbon dioxide (C s) in the atmosphere have profound effects on plant transpiration and, consequently, on the water balance. Land surface models (LSMs) reflect plant response to these changes by simulation of stomatal conductance (g s). However, the plant response is not well understood and varies with climate. In this study, the simulation of g s within different LSMs is reviewed and a new approach, a Mixed Generalized Additive Model (MGAM) for g s simulation, is developed. The alternative g s estimation is proposed as a solution for the high parameterisation uncertainty in semi-empirical g s simulation models, and high dependency on mathematical functions for environmental stress factors in empirical g s simulation models. MGAM has high Pearson and Spearman correlations (87% and 85%, respectively) and efficiency coefficients (71%), with low error values (0.07 mol/m2s) in g s simulation. The global sensitivity analysis of the MGAM approach shows the necessity of considering the interaction between C s and other key climate variables in g s simulation. The high accuracy and low uncertainty to the first-order key climate factors in g s simulation highlight the MGAM model's importance in future studies. [ABSTRACT FROM AUTHOR]

Vegetation phenology is a sensitive indicator of the dynamic response of terrestrial ecosystems to climate change. In this study, the spatiotemporal pattern of vegetation dormancy onset date ( DOD) and its climate controls over temperate China were examined by analysing the satellite-derived normalized difference vegetation index and concurrent climate data from 1982 to 2010. Results show that preseason (May through October) air temperature is the primary climatic control of the DOD spatial pattern across temperate China, whereas preseason cumulative precipitation is dominantly associated with the DOD spatial pattern in relatively cold regions. Temporally, the average DOD over China's temperate ecosystems has delayed by 0.13 days per year during the past three decades. However, the delay trends are not continuous throughout the 29-year period. The DOD experienced the largest delay during the 1980s, but the delay trend slowed down or even reversed during the 1990s and 2000s. Our results also show that interannual variations in DOD are most significantly related with preseason mean temperature in most ecosystems, except for the desert ecosystem for which the variations in DOD are mainly regulated by preseason cumulative precipitation. Moreover, temperature also determines the spatial pattern of temperature sensitivity of DOD, which became significantly lower as temperature increased. On the other hand, the temperature sensitivity of DOD increases with increasing precipitation, especially in relatively dry areas (e.g. temperate grassland). This finding stresses the importance of hydrological control on the response of autumn phenology to changes in temperature, which must be accounted in current temperature-driven phenological models. [ABSTRACT FROM AUTHOR]