ORCID Profile
0000-0002-9982-9518
Current Organisation
Zhejiang University
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In Research Link Australia (RLA), "Research Topics" refer to ANZSRC FOR and SEO codes. These topics are either sourced from ANZSRC FOR and SEO codes listed in researchers' related grants or generated by a large language model (LLM) based on their publications.
Terrestrial Ecology | Ecological Impacts of Climate Change | Ecological Applications | Ecological Physiology
Effects of Climate Change and Variability on Australia (excl. Social Impacts) | Climate Change Models | Native Forests |
Publisher: Frontiers Media SA
Date: 31-05-2019
Publisher: American Geophysical Union (AGU)
Date: 11-2018
DOI: 10.1029/2017JG004378
Publisher: Oxford University Press (OUP)
Date: 14-10-2019
Abstract: Vapour pressure deficit (D) is projected to increase in the future as temperatures rise. In response to increased D, stomatal conductance (gs) and photosynthesis (A) are reduced, which may result in significant reductions in terrestrial carbon, water, and energy fluxes. It is thus important for gas exchange models to capture the observed responses of gs and A with increasing D. We tested a series of coupled A-gs models against leaf gas exchange measurements from the Cumberland Plain Woodland (Australia), where D regularly exceeds 2 kPa and can reach 8 kPa in summer. Two commonly used A-gs models (Leuning 1995 and Medlyn et al. 2011) were not able to capture the observed decrease in A and gs with increasing D at the leaf scale. To explain this decrease in A and gs, two alternative hypotheses were tested: hydraulic limitation (i.e., plants reduce gs and/or A due to insufficient water supply) and non-stomatal limitation (i.e., downregulation of photosynthetic capacity). We found that the model that incorporated a non-stomatal limitation captured the observations with high fidelity and required the fewest number of parameters. While the model incorporating hydraulic limitation captured the observed A and gs, it did so via a physical mechanism that is incorrect. We then incorporated a non-stomatal limitation into the stand model, MAESPA, to examine its impact on canopy transpiration and gross primary production. Accounting for a non-stomatal limitation reduced the predicted transpiration by ~19%, improving the correspondence with sap flow measurements, and gross primary production by ~14%. Given the projected global increases in D associated with future warming, these findings suggest that models may need to incorporate non-stomatal limitation to accurately simulate A and gs in the future with high D. Further data on non-stomatal limitation at high D should be a priority, in order to determine the generality of our results and develop a widely applicable model.
Publisher: Wiley
Date: 28-05-2022
DOI: 10.1111/GEB.13548
Abstract: To estimate loss of above‐ground carbon (AGC) and conversion of live carbon to dead carbon following understorey and canopy fire. South‐eastern Australia. 2019–2020. Four widespread resprouting eucalypt forests. Above‐ground carbon was measured in 15 plots in each of four forest types one‐year post‐fire. We also assessed topkill, that is, trees subject to canopy loss that failed to resprout epicormically. While canopy fire was associated with greater declines in AGC than understorey fire, this was only statistically significant for only one forest type, where AGC declined from 154 to 85 Mg C ha −1 following canopy fire. Significant post‐fire increases in dead AGC were observed in one forest type, where dead carbon increased from 22 to 60% after canopy fire. Topkill of trees following canopy fire (48–78% of stems) was higher than topkill after understorey fire (36–53% of stems) and in unburnt forest (12–55%). Topkill occurred primarily in small‐diameter stems. Consequently, there was no effect of fire on the proportion of dead AGC in trees, with the exception of the forest with lowest productivity (i.e., lowest biomass) and lowest annual rainfall, where dead tree carbon increased from 8% in unburnt forest to 13 and 53% after understorey and canopy fire, respectively. AGC in understorey vegetation and coarse woody debris was similar or lower in burnt compared with unburnt forest. Litter carbon was significantly lower and pyrogenic carbon significantly higher in burnt forest, with no difference between understorey and canopy fire. While increased fire severity was associated with increased changes to carbon stocks, there were differences among forest types. Specifically, the driest forest type had the highest rates of topkill following canopy fire. These results highlight the importance of spatial variability in fire severity and forest type in determining the effects of fire on carbon stocks.
Publisher: Wiley
Date: 24-09-2017
DOI: 10.1111/GEB.12635
Publisher: Wiley
Date: 02-02-2018
DOI: 10.1111/GCB.14037
Abstract: Heatwaves are likely to increase in frequency and intensity with climate change, which may impair tree function and forest C uptake. However, we have little information regarding the impact of extreme heatwaves on the physiological performance of large trees in the field. Here, we grew Eucalyptus parramattensis trees for 1 year with experimental warming (+3°C) in a field setting, until they were greater than 6 m tall. We withheld irrigation for 1 month to dry the surface soils and then implemented an extreme heatwave treatment of 4 consecutive days with air temperatures exceeding 43°C, while monitoring whole-canopy exchange of CO
Publisher: Wiley
Date: 11-05-2022
DOI: 10.1111/JBI.14375
Abstract: Climate shapes the composition and function of plant communities globally, but it remains unclear how this influence extends to floral traits. Flowering phenology, or the time period in which a species flowers, has well‐studied relationships with climatic signals at the species level but has rarely been explored at a cross‐community and continental scale. Here, we characterise the distribution of flowering periods (months of flowering) across continental plant communities encompassing six biomes, and determine the influence of climate on community flowering period lengths. Australia. Flowering plants. We combined plant composition and abundance data from 629 standardised floristic surveys (AusPlots) with data on flowering period from the AusTraits database and additional primary literature for 2983 species. We assessed abundance‐weighted community mean flowering periods across biomes and tested their relationship with climatic annual means and the predictability of climate conditions using regression models. Combined, temperature and precipitation (annual mean and predictability) explain 29% of variation in continental community flowering period. Plant communities with higher mean temperatures and lower mean precipitation have longer mean flowering periods. Moreover, plant communities in climates with predictable temperatures and, to a lesser extent, predictable precipitation have shorter mean flowering periods. Flowering period varies by biome, being longest in deserts and shortest in alpine and montane communities. For instance, desert communities experience low and unpredictable precipitation and high, unpredictable temperatures and have longer mean flowering periods, with desert species typically flowering at any time of year in response to rain. Current climate conditions shape flowering periods across biomes, with implications for phenology under climate change. Shifts in flowering periods across climatic gradients reflect changes in plant strategies, affecting patterns of plant growth and reproduction as well as the availability of floral resources for pollinators across the landscape.
Publisher: Copernicus GmbH
Date: 20-01-2020
Abstract: Abstract. The response of mature forest ecosystems to a rising atmospheric carbon dioxide concentration (Ca) is a major uncertainty in projecting the future trajectory of the Earth's climate. Although leaf-level net photosynthesis is typically stimulated by exposure to elevated Ca (eCa), it is unclear how this stimulation translates into carbon cycle responses at the ecosystem scale. Here we estimate a key component of the carbon cycle, the gross primary productivity (GPP), of a mature native eucalypt forest exposed to free-air CO2 enrichment (the EucFACE experiment). In this experiment, light-saturated leaf photosynthesis increased by 19 % in response to a 38 % increase in Ca. We used the process-based forest canopy model, MAESPA, to upscale these leaf-level measurements of photosynthesis with canopy structure to estimate the GPP and its response to eCa. We assessed the direct impact of eCa, as well as the indirect effect of photosynthetic acclimation to eCa and variability among treatment plots using different model scenarios. At the canopy scale, MAESPA estimated a GPP of 1574 g C m−2 yr−1 under ambient conditions across 4 years and a direct increase in the GPP of +11 % in response to eCa. The smaller canopy-scale response simulated by the model, as compared with the leaf-level response, could be attributed to the prevalence of RuBP regeneration limitation of leaf photosynthesis within the canopy. Photosynthetic acclimation reduced this estimated response to 10 %. After taking the baseline variability in the leaf area index across plots in account, we estimated a field GPP response to eCa of 6 % with a 95 % confidence interval (−2 %, 14 %). These findings highlight that the GPP response of mature forests to eCa is likely to be considerably lower than the response of light-saturated leaf photosynthesis. Our results provide an important context for interpreting the eCa responses of other components of the ecosystem carbon cycle.
Publisher: Cold Spring Harbor Laboratory
Date: 12-10-2021
DOI: 10.1101/2021.10.10.463841
Abstract: Climate shapes the composition and function of plant communities globally, but it remains unclear how this influence extends to floral traits. Flowering phenology, or the time period in which a species flowers, has well-studied relationships with climatic signals at the species level but has rarely been explored at a cross-community and continental scale. Here, we characterise the distribution of flowering periods (months of flowering) across continental plant communities encompassing six biomes, and determine the influence of climate on community flowering period lengths. Australia Flowering plants We combined plant composition and abundance data from 629 standardised floristic surveys (AusPlots) with data on flowering period from the AusTraits database and additional primary literature for 2,983 species. We assessed abundance-weighted community mean flowering periods across biomes and tested their relationship with climatic annual means and the predictability of climate conditions using regression models. Combined, temperature and precipitation (annual mean and predictability) explain 29% of variation in continental community flowering period. Plant communities with higher mean temperatures and lower mean precipitation have longer mean flowering periods. Moreover, plant communities in climates with predictable temperatures and, to a lesser extent, predictable precipitation have shorter mean flowering periods. Flowering period varies by biome, being longest in deserts and shortest in alpine and montane communities. For instance, desert communities experience low and unpredictable precipitation and high, unpredictable temperatures and have longer mean flowering periods, with desert species typically flowering at any time of year in response to rain. Our findings demonstrate the role of current climate conditions in shaping flowering periods across biomes, with implications under climate change. Shifts in flowering periods across climatic gradients reflect changes in plant strategies, affecting patterns of plant growth and reproduction as well as the availability of floral resources across the landscape.
Publisher: Wiley
Date: 03-2015
Publisher: Wiley
Date: 12-06-2013
Publisher: Wiley
Date: 15-12-2022
DOI: 10.1111/NPH.18618
Abstract: Optimal stomatal theory predicts that stomata operate to maximise photosynthesis ( A net ) and minimise transpirational water loss to achieve optimal intrinsic water‐use efficiency (iWUE). We tested whether this theory can predict stomatal responses to elevated atmospheric CO 2 (eCO 2 ), and whether it can capture differences in responsiveness among woody plant functional types (PFTs). We conducted a meta‐analysis of tree studies of the effect of eCO 2 on iWUE and its components A net and stomatal conductance ( g s ). We compared three PFTs, using the unified stomatal optimisation (USO) model to account for confounding effects of leaf–air vapour pressure difference ( D ). We expected smaller g s , but greater A net , responses to eCO 2 in gymnosperms compared with angiosperm PFTs. We found that iWUE increased in proportion to increasing eCO 2 in all PFTs, and that increases in A net had stronger effects than reductions in g s . The USO model correctly captured stomatal behaviour with eCO 2 across most datasets. The chief difference among PFTs was a lower stomatal slope parameter ( g 1 ) for the gymnosperm, compared with angiosperm, species. Land surface models can use the USO model to describe stomatal behaviour under changing atmospheric CO 2 conditions.
Publisher: Springer Science and Business Media LLC
Date: 08-04-2020
Publisher: Springer Science and Business Media LLC
Date: 18-07-2016
DOI: 10.1038/SREP29962
Abstract: Characterizing precipitation seasonality and variability in the face of future uncertainty is important for a well-informed climate change adaptation strategy. Using the Colwell index of predictability and monthly normalized precipitation data from the Coupled Model Intercomparison Project Phase 5 (CMIP5) multi-model ensembles, this study identifies spatial hotspots of changes in precipitation predictability in the United States under various climate scenarios. Over the historic period (1950–2005), the recurrent pattern of precipitation is highly predictable in the East and along the coastal Northwest, and is less so in the arid Southwest. Comparing the future (2040–2095) to the historic period, larger changes in precipitation predictability are observed under Representative Concentration Pathways (RCP) 8.5 than those under RCP 4.5. Finally, there are region-specific hotspots of future changes in precipitation predictability, and these hotspots often coincide with regions of little projected change in total precipitation, with exceptions along the wetter East and parts of the drier central West. Therefore, decision-makers are advised to not rely on future total precipitation as an indicator of water resources. Changes in precipitation predictability and the subsequent changes on seasonality and variability are equally, if not more, important factors to be included in future regional environmental assessment.
Publisher: Wiley
Date: 19-02-2021
DOI: 10.1111/NPH.15688
Abstract: Contents Summary 1223 I. Introduction 1223 II. Photosynthesis and respiration 1224 III. Biomass growth 1224 IV. Carbon allocation 1225 V. Plant internal P redistribution 1226 VI. Plant P uptake 1227 VII. Conclusion 1227 Acknowledgements 1228 References 1228 SUMMARY: Our ability to understand the effect of nutrient limitation on ecosystem productivity is key to the prediction of future terrestrial carbon storage. Significant progress has been made to include phosphorus (P) cycle processes in land surface models (LSMs), but these efforts are focused on the soil component of the P cycle. Incorporating the soil component is important to estimate plant-available P, but does not necessarily address the vegetation response to P limitation or plant-soil interactions. A more detailed representation of plant P processes is needed to link nutrient availability and ecosystem productivity. We review physiological and biochemical evidence for vegetation responses to P availability, and recommend ways to move towards a more physiological representation of vegetation P processes in LSMs.
Publisher: Copernicus GmbH
Date: 28-05-2019
Abstract: Abstract. Elevated carbon dioxide (CO2) can increase plant growth, but the magnitude of this CO2 fertilization effect is modified by soil nutrient availability. Predicting how nutrient availability affects plant responses to elevated CO2 is a key consideration for ecosystem models, and many modeling groups have moved to, or are moving towards, incorporating nutrient limitation in their models. The choice of assumptions to represent nutrient cycling processes has a major impact on model predictions, but it can be difficult to attribute outcomes to specific assumptions in complex ecosystem simulation models. Here we revisit the quasi-equilibrium analytical framework introduced by Comins and McMurtrie (1993) and explore the consequences of specific model assumptions for ecosystem net primary productivity (NPP). We review the literature applying this framework to plant–soil models and then analyze the effect of several new assumptions on predicted plant responses to elevated CO2. Examination of alternative assumptions for plant nitrogen uptake showed that a linear function of the mineral nitrogen pool or a linear function of the mineral nitrogen pool with an additional saturating function of root biomass yield similar CO2 responses at longer timescales ( years), suggesting that the added complexity may not be needed when these are the timescales of interest. In contrast, a saturating function of the mineral nitrogen pool with linear dependency on root biomass yields no soil nutrient feedback on the very-long-term ( years), near-equilibrium timescale, meaning that one should expect the model to predict a full CO2 fertilization effect on production. Secondly, we show that incorporating a priming effect on slow soil organic matter decomposition attenuates the nutrient feedback effect on production, leading to a strong medium-term (5–50 years) CO2 response. Models incorporating this priming effect should thus predict a strong and persistent CO2 fertilization effect over time. Thirdly, we demonstrate that using a “potential NPP” approach to represent nutrient limitation of growth yields a relatively small CO2 fertilization effect across all timescales. Overall, our results highlight the fact that the quasi-equilibrium analytical framework is effective for evaluating both the consequences and mechanisms through which different model assumptions affect predictions. To help constrain predictions of the future terrestrial carbon sink, we recommend the use of this framework to analyze likely outcomes of new model assumptions before introducing them to complex model structures.
Publisher: Wiley
Date: 31-07-2020
DOI: 10.1111/GCB.15277
Publisher: Wiley
Date: 22-03-2022
DOI: 10.1111/GCB.16141
Abstract: In 2020, the Australian and New Zealand flux research and monitoring network, OzFlux, celebrated its 20 th anniversary by reflecting on the lessons learned through two decades of ecosystem studies on global change biology. OzFlux is a network not only for ecosystem researchers, but also for those ‘next users’ of the knowledge, information and data that such networks provide. Here, we focus on eight lessons across topics of climate change and variability, disturbance and resilience, drought and heat stress and synergies with remote sensing and modelling. In distilling the key lessons learned, we also identify where further research is needed to fill knowledge gaps and improve the utility and relevance of the outputs from OzFlux. Extreme climate variability across Australia and New Zealand (droughts and flooding rains) provides a natural laboratory for a global understanding of ecosystems in this time of accelerating climate change. As evidence of worsening global fire risk emerges, the natural ability of these ecosystems to recover from disturbances, such as fire and cyclones, provides lessons on adaptation and resilience to disturbance. Drought and heatwaves are common occurrences across large parts of the region and can tip an ecosystem's carbon budget from a net CO 2 sink to a net CO 2 source. Despite such responses to stress, ecosystems at OzFlux sites show their resilience to climate variability by rapidly pivoting back to a strong carbon sink upon the return of favourable conditions. Located in under‐represented areas, OzFlux data have the potential for reducing uncertainties in global remote sensing products, and these data provide several opportunities to develop new theories and improve our ecosystem models. The accumulated impacts of these lessons over the last 20 years highlights the value of long‐term flux observations for natural and managed systems. A future vision for OzFlux includes ongoing and newly developed synergies with ecophysiologists, ecologists, geologists, remote sensors and modellers.
Publisher: American Meteorological Society
Date: 29-03-2016
Abstract: The proper understanding of precipitation variability, seasonality, and predictability are important for effective environmental management. Precipitation and its associated extremes vary in magnitude and duration both spatially and temporally, making it one of the most challenging climate parameters to predict on the basis of global and regional climate models. Using information theory, an improved understanding of precipitation predictability in the conterminous United States over the period of 1949–2010 is sought based on a gridded monthly precipitation dataset. Predictability is defined as the recurrent likelihood of patterns described by the metrics of magnitude variability and seasonality. It is shown that monthly mean precipitation and duration-based dry and wet extremes are generally highly variable in the east compared to those in the west, while the reversed spatial pattern is observed for intensity-based wetness indices except along the Pacific Northwest coast. It is thus inferred that, over much of the U.S. landscape, variations of monthly mean precipitation are driven by the variations in precipitation occurrences rather than the intensity of infrequent heavy rainfall. It is further demonstrated that precipitation seasonality for means and extremes is homogeneously invariant within the United States, with the exceptions of the West Coast, Florida, and parts of the Midwest, where stronger seasonality is identified. A proportionally higher role of variability in regulating precipitation predictability is demonstrated. Seasonality surpasses variability only in parts of the West Coast. The quantified patterns of predictability for precipitation means and extremes have direct applications to those phenomena influenced by climate periodicity, such as bio ersity and ecosystem management.
Publisher: Wiley
Date: 08-09-2022
DOI: 10.1111/PCE.14427
Publisher: Wiley
Date: 08-10-2018
Publisher: Springer Science and Business Media LLC
Date: 16-09-2016
DOI: 10.1038/SREP33618
Abstract: Scientific Reports 6: Article number: 29962 published online: 18 July 2016 updated: 16 September 2016. This Article contains typographical errors in Reference 21. “Ehasani, N., B. M. Fekete, C. J. Vorosmarty & Z. D. Tessler A neural network based general reservoir operation scheme. Stochastic Environmental Research and Risk Assessment 1:16, doi: 10.
Publisher: Springer Science and Business Media LLC
Date: 05-08-2019
Publisher: Elsevier BV
Date: 02-2023
Publisher: American Meteorological Society
Date: 2020
Abstract: Our broad research goal is to understand how human societies adapt to natural hazards, such as droughts and floods, and how their social and cultural structures are shaped by these events. Here we develop meteorological data of extreme dry, wet, cold, and warm indices relative to 96 largely nonindustrial societies in the worldwide Standard Cross-Cultural S le to explore how well the meteorological data can be used to hindcast ethnographically reported drought and flood events and the global patterns of extremes. We find that the drought indices that are best at hindcasting ethnographically reported droughts [precipitation minus evaporation ( P − E ) measures] also tend to overpredict the number of droughts, and therefore we propose a combination of these two indices plus the PDSI as an optimal approach. Some wet precipitation indices (R10S and R20S) are more effective at hindcasting ethnographically reported floods than others. We also calculate the predictability of those extreme indices and use factor analysis to reduce the number of variables so as to discern global patterns. This work highlights the ability to use extreme meteorological indices to fill in gaps in ethnographic records in the future, this may help us to determine relationships between extreme events and societal response over longer time scales than are otherwise available.
Publisher: American Meteorological Society
Date: 04-2021
Abstract: All societies have religious beliefs, but societies vary widely in the number and type of gods in which they believe as well as their ideas about what the gods do. In many societies, a god is thought to be responsible for weather events. In some of those societies, a god is thought to cause harm with weather and/or can choose to help, such as by bringing needed rain. In other societies, gods are not thought to be involved with weather. Using a worldwide, largely nonindustrial s le of 46 societies with high gods, this research explores whether certain climate patterns predict the belief that high gods are involved with weather. Our major expectation, largely supported, was that such beliefs would most likely be found in drier climates. Cold extremes and hot extremes have little or no relationship to the beliefs that gods are associated with weather. Since previous research by Skoggard et al. showed that greater resource stress predicted the association of high gods with weather, we also tested mediation path models to help us evaluate whether resource stress might be the mediator explaining the significant associations between drier climates and high god beliefs. The climate variables, particularly those pertaining to dryness, continue to have robust relationships to god beliefs when controlling on resource stress at best, resource stress has only a partial mediating effect. We speculate that drought causes humans more anxiety than floods, which may result in the greater need to believe supernatural beings are not only responsible for weather but can help humans in times of need.
Publisher: Wiley
Date: 21-10-2020
DOI: 10.1111/NPH.16866
Abstract: Atmospheric carbon dioxide concentration ([CO 2 ]) is increasing, which increases leaf‐scale photosynthesis and intrinsic water‐use efficiency. These direct responses have the potential to increase plant growth, vegetation biomass, and soil organic matter transferring carbon from the atmosphere into terrestrial ecosystems (a carbon sink). A substantial global terrestrial carbon sink would slow the rate of [CO 2 ] increase and thus climate change. However, ecosystem CO 2 responses are complex or confounded by concurrent changes in multiple agents of global change and evidence for a [CO 2 ]‐driven terrestrial carbon sink can appear contradictory. Here we synthesize theory and broad, multidisciplinary evidence for the effects of increasing [CO 2 ] (iCO 2 ) on the global terrestrial carbon sink. Evidence suggests a substantial increase in global photosynthesis since pre‐industrial times. Established theory, supported by experiments, indicates that iCO 2 is likely responsible for about half of the increase. Global carbon budgeting, atmospheric data, and forest inventories indicate a historical carbon sink, and these apparent iCO 2 responses are high in comparison to experiments and predictions from theory. Plant mortality and soil carbon iCO 2 responses are highly uncertain. In conclusion, a range of evidence supports a positive terrestrial carbon sink in response to iCO 2 , albeit with uncertain magnitude and strong suggestion of a role for additional agents of global change.
Publisher: Wiley
Date: 16-02-2021
DOI: 10.1111/NPH.17233
Abstract: Elevated atmospheric CO 2 (eC a ) may benefit plants during drought by reducing stomatal conductance ( g s ) but any ‘water savings effect’ could be neutralized by concurrent stimulation of leaf area. We investigated whether eC a enhanced water savings, thereby ameliorating the impact of drought on carbon and water relations in trees. We report leaf‐level gas exchange and whole‐plant and soil water relations during a short‐term dry‐down in two Eucalyptus species with contrasting drought tolerance. Plants had previously been established for 9 to 11 months in steady‐state conditions of ambient atmospheric CO 2 (aC a ) and eC a , with half of each treatment group exposed to sustained drought for 5 to 7 months. The lower stomatal conductance under eC a did not lead to soil moisture savings during the dry‐down due to the counteractive effect of increased whole‐plant leaf area. Nonetheless, eC a ‐grown plants maintained higher photosynthetic rates and leaf water potentials, making them less stressed during the dry‐down, despite being larger. These effects were more pronounced in the xeric species than the mesic species, and in previously water‐stressed plants. Our findings indicate that eC a may enhance plant performance during drought despite a lack of soil water savings, especially in species with more conservative growth and water‐use strategies.
Start Date: 2021
End Date: 01-2022
Amount: $335,528.00
Funder: Australian Research Council
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