Ecohydrological interactions and landscape response to recent hydroclimatic events in Australia

University of Technology Sydney. Faculty of Science.Amplification of the water cycle as a consequence of climate change is predicted to increase the climate variability as well as the frequency and severity of droughts and wet extremes over continents such as Australia. Australia has recently experienced three large-scale hydroclimatic extremes, including a decadal millennium drought from 2001 to 2009 (termed the 'big dry'), followed by a short wet pulse during 2010 and 2011 (termed the 'big wet'), and another continent-wide dry condition in 2015. These dry and wet events exerted pronounced negative impacts on water resources, natural ecosystems and agriculture over large areas of Australia. Despite these extreme hydroclimatic impacts, the fate of ecohydrological resources such as the loss and recovery of water storage and vegetation remain largely unknown. The overall goal of this thesis is to study the ecohydrological interactions and landscape response to Australia's early 21st century hydroclimatic extremes. To achieve thesis objectives, I (1) firstly investigated the spatial partitioning and temporal evolution of water resources across Australia under extreme hydroclimatic impacts, (2) then assessed the associations between the climate variability and dynamics in water resources and vegetation productivity, (3) furthermore examined the resilience of regional arid ecosystems to the highly variable water regimes and large-scale hydrological fluctuations, and (4) conducted a synthesized assessment of ecohydrological variations and interactions under these dry and wet events at continental, regional and biome scales, respectively. Results show that highly variable continental patterns were observed in water resources and vegetation, involving differences in the direction, magnitude, and duration of total water storage and surface greenness responses to drought and wet periods. These responses clustered into three distinct geographic zones that correlated well with the influences from three large-scale climate modes: the El Niño-Southern Oscillation (ENSO), the Indian Ocean Dipole (IOD) and the Southern Annular Mode (SAM). At regional scale, ecosystems such as arid wetlands exhibit strong ecological resilience to hydroclimatic extremes, and are presumably sensitive to future altered water regimes due to climate change. In addition, Total Water Storage Anomaly (TWSA) data derived from Gravity Recovery And Climate Experiment (GRACE) satellites was found to be a valuable indicator for ecohydrological system performances and effectively linking the extreme climate variability with Australia's ecosystems. This thesis highlights the value of Remote Sensing techniques (e.g. GRACE satellites) as important tools for improved assessments and management of water resources and associated ecosystems in Australia, particularly in the face of future increasing hydroclimatic extremes

Control of astrocyte progenitor specification, migration and maturation by Nkx6.1 homeodomain transcription factor.

Although astrocytes are the most abundant cell type in the central nervous system (CNS), little is known about their molecular specification and differentiation. It has previously been reported that transcription factor Nkx6.1 is expressed in neuroepithelial cells that give rise to astrocyte precursors in the ventral spinal cord. In the present study, we systematically investigated the function of Nkx6.1 in astrocyte development using both conventional and conditional Nkx6.1 mutant mice. At early postnatal stages, Nkx6.1 was expressed in a subpopulation of astrocytes in the ventral spinal cord. In the conventional Nkx6.1KO spinal cord, the initial specification of astrocyte progenitors was affected by the mutation, and subsequent migration and differentiation were disrupted in newborn mice. In addition, the development of VA2 subtype astrocytes was also inhibited in the white matter. Further studies with Nkx6.1 conditional mutants revealed significantly delayed differentiation and disorganized arrangement of fibrous astrocytes in the ventral white matter. Together, our studies indicate that Nkx6.1 plays a vital role in astrocyte specification and differentiation in the ventral spinal cord

Drought rapidly diminishes the large net CO2 uptake in 2011 over semi-arid Australia

Each year, terrestrial ecosystems absorb more than a quarter of the anthropogenic carbon emissions, termed as land carbon sink. An exceptionally large land carbon sink anomaly was recorded in 2011, of which more than half was attributed to Australia. However, the persistence and spatially attribution of this carbon sink remain largely unknown. Here we conducted an observation-based study to characterize the Australian land carbon sink through the novel coupling of satellite retrievals of atmospheric CO2 and photosynthesis and in-situ flux tower measures. We show the 2010–11 carbon sink was primarily ascribed to savannas and grasslands. When all biomes were normalized by rainfall, shrublands however, were most efficient in absorbing carbon. We found the 2010–11 net CO2 uptake was highly transient with rapid dissipation through drought. The size of the 2010–11 carbon sink over Australia (0.97 Pg) was reduced to 0.48 Pg in 2011–12, and was nearly eliminated in 2012–13 (0.08 Pg). We further report evidence of an earlier 2000–01 large net CO2 uptake, demonstrating a repetitive nature of this land carbon sink. Given a significant increasing trend in extreme wet year precipitation over Australia, we suggest that carbon sink episodes will exert greater future impacts on global carbon cycle

A scalable big data approach for remotely tracking rangeland conditions

Rangelands, covering half of the global land area, are critically degraded by unsustainable use and climate change. Despite their extensive presence, global assessments of rangeland condition and sustainability are limited. Here we introduce a novel analytical approach that combines satellite big data and statistical modeling to quantify the likelihood of changes in rangeland conditions. These probabilities are then used to assess the effectiveness of management interventions targeting rangeland sustainability. This approach holds global potential, as demonstrated in Mongolia, where the shift to a capitalist economy has led to increased livestock numbers and grazing intensity. From 1986 to 2020, heavy grazing caused a marked decline in Mongolia’s rangeland condition. Our evaluation of diverse management strategies, corroborated by local ground observations, further substantiates our approach. Leveraging globally available yet locally detailed satellite data, our proposed condition tracking approach provides a rapid, cost-effective tool for sustainable rangeland management

Thank You to Our 2023 Reviewers

The Editors and Staff of Earth and Space Science thank the reviewers whose selfless work has significantly contributed to the publication process of papers highlighting the best research in geophysics, planetary, and space science in 2023. Peer-reviewing is a demanding and thankless job. It is however an essential component of the scientific process, requiring the highest standards of integrity and rigor. Reviewers check data and procedures and test reproducibility of methods and results; they share their expertise to verify that the interpretations and conclusions of a paper are consistent with assumptions and existing knowledge. Without this essential work it would not be possible to trust in the scientific process. Publication of papers in a multidisciplinary journal such as Earth and Space Science, that highlights methods, instruments, data and algorithms, relies directly on the expertise of its reviewers to verify and vouch for the quality of the papers that are published. We are indebted to all our reviewers and are delighted to acknowledge them publicly in this Editorial

Developing an annual global Sub-National scale economic data from 1992 to 2021 using nighttime lights and deep learning

The Gross Domestic Product (GDP) per capita is one of the most widely used socioeconomic indicators, serving as an integral component for climate change impact analysis. However, a national scale assessment may induce considerable bias because it conceals any internal variations within a country. The lack of a long-term sub-national scale GDP data is a substantive hinderance. Leveraging the close relationship between nighttime lights and GDP, we address this gap by developing a novel methodological framework in two steps. First, under the modeling philosophy of spatial statistics, we developed a novel approach based on deep and machine learning techniques to establish a complex mapping between two inconsistent nighttime lights (NTL) datasets: the Defense Meteorological Satellite Program’s Operational Linescan System (DMSP) and the National Polar-Orbiting Partnership’s Visible Infrared Imaging Radiometer Suite (VIIRS). The models achieve accuracies ranging from 0.945 to 0.980 (correlation coefficients). By taking the estimations ensemble of the two techniques, the time series of DMSP data was extended to 2021. Next, a novel modeling strategy based on multi-layer perceptron was developed to derive the non-linear relationship between NTL and GDP per capita at sub-national scale to alleviate scale effects at this granularity, while explicitly capturing regional heterogeneity effect. The trained models achieve average accuracies of 0.967, 0.959, and 0.959 on the training, validation, and test sets, respectively. We evaluate the developed dataset at the global, national, and sub-national scales from various perspective, and the results offer solid evidence on the reliability of the estimated economic data. By linking to historical global climate change data, we quantify global economic losses attributed to extreme heat to demonstrate how the estimated GDP data can be useful in the climate change impact analysis

Method for quickly delineating Merzbacher Lake extent based on Environment and Disaster Monitoring small Satellite images

The Merzbacher Glacial Lake located in the Sary Jaz-Kumarik River Basin has severe impacts on the environment and human well-being in downstream of the AKSU River in China. The Merzbacker Lake has flooded with increased frequency in recent years with the climate warming. It is vital to strengthen observation and monitoring of the Merzbacker Lake, especially by remote sensing data. Large portion by floating ice is the key issues of monitoring the lake. Based on the high temporal and spatial resolution Environment and Disaster Monitoring Satellite images, an improved method focused on threshold and mask technique were presented. Parts of the lake which is clear of ice was extracted mainly by Normalized Difference Water Index method. Parts of the lake covered by floating ice were relarively accurately extracted by using the Band B image of the HSV images. The area change information of Merzbacher Lake then were extracted by the post-processing of the areas in different periods. As an example, the changing areas series of Merbacher Lake in 2009 were analyzed. The results suggests that the date of the Merbacher Lake flood was around 30th July, and the flood lasted for no more than a week. The application indicates that the method can provid quick and relatively accurate monitoring of the lake flood, which is very import to construct forecasting and warning systems of Merzbacher Lake

Plasma Proteomic Analysis Based on 4D-DIA Evaluates the Clinical Response to Imrecoxib in the Early Treatment of Osteoarthritis

Abstract Introduction Nonsteroidal anti-inflammatory drugs (NSAIDs) are the primary treatment for osteoarthritis (OA), but prolonged use has adverse effects and varying efficacy. Among NSAIDs, imrecoxib, a selective cyclooxygenase-2 (COX-2) inhibitor, reduces side effects yet remains ineffective for half of the patient population. This study aims to identify biomarkers for early evaluation of imrecoxib efficacy in OA for personalized therapy optimization. Methods From September 2021 to January 2022, imrecoxib was administered to patients with OA at Nanjing Drum Tower Hospital. Plasma samples from these patients underwent proteomic analysis through the four-dimensional data-independent acquisition (4D-DIA) method, followed by bioinformatics analysis. Potential differentially expressed proteins (DEPs) were validated using enzyme-linked immunosorbent assays (ELISA). Results Sixty-six patients with knee OA were included and divided into responders (n = 35) and non-responders (n = 31). Proteomic analysis was conducted on 15 patients from each group, with ELISA validation for every patient. We found 140 DEPs between the two groups after imrecoxib treatment, characterized by 29 proteins showing upregulation and 111 displaying downregulation (P   ± 1.2). Galectin-1 (LGALS1), galectin-3 (LGALS3), and cluster of differentiation 44 (CD44) were identified as potential markers for evaluating clinical response to imrecoxib in OA following ELISA validation. Conclusion This study successfully identified biomarkers for evaluating imrecoxib’s clinical response in patients with OA using 4D-DIA technology. These biomarkers may play a vital role in future personalized OA treatment strategies, pending further confirmation

Spatial partitioning and temporal evolution of Australia's total water storage under extreme hydroclimatic impacts

Australia experienced one of the worst droughts in history during the early 21st-century (termed the 'big dry'), exerting negative impacts on food production and water supply, with increased forest die-back and bushfires across large areas. Following the 'big dry', one of the largest La Nina events in the past century, in conjunction with an extreme positive excursion of the Southern Annular Mode (SAM), resulted in dramatic increased precipitation from 2010 to 2011 (termed the 'big wet'), causing widespread flooding and a recorded sea level drop. Despite these extreme hydroclimatic impacts, the spatial partitioning and temporal evolution of total water storage across Australia remains unknown. In this study we investigated the spatial-temporal impacts of the recent 'big dry' and 'big wet' events on Australia's water storage dynamics using the total water storage anomaly (TWSA) data derived from the Gravity Recovery and Climate Experiment (GRACE) satellites.Results showed widespread, continental-scale decreases in TWS during the 'big dry', resulting in a net loss of 3.89 +/- 0.47 cm (299 km(3)) total water, while the 'big wet' induced a sharp increase in TWS, equivalent to 11.68 +/- 0.52 cm (898 km(3)) of water, or three times the total water loss during the 'big dry'. We found highly variable continental patterns in water resources, involving differences in the direction, magnitude, and duration of TWS responses to drought and wet periods. These responses clustered into three distinct geographic zones that correlated well with the influences from multiple large-scale climate modes. Specifically, a persistent increasing trend in TWS was recorded over northern and northeastern Australia, where the climate is strongly influenced by El Nifio-Southern Oscillation (ENSO). By contrast, western Australia, a region predominantly controlled by the Indian Ocean Dipole (IOD), exhibited a continuous decline in TWS during the 'big dry' and only a subtle increase during the 'big wet', indicating a weak recovery of water storage. Southeastern Australia, influenced by combined ENSO, IOD and SAM interactions, exhibited a pronounced TWS drying trend during the 'big dry' followed by rapid TWS increases during the 'big wet', with complete water storage recoveries. A spatial intensification of the water cycle was further identified, with a wetting trend over wetter regions (northern and northeastern Australia) and a drying trend over drier regions (western Australia). Our results highlight the value of GRACE derived TWSA as an important indicator of hydrological system performance for improved water impact assessments and management of water resources across space and time. (C) 2016 Elsevier Inc. All rights reserved

Terrestrial total water storage dynamics of Australia's recent dry and wet events

Australia recently experienced a long-term continental drought ('big dry', 2001-2009) followed by an anomalous wet two-year period ('big wet', 2010-2011). Despite the significance of the two extreme events, continental-wide information regarding the effects of the high and low precipitation conditions on the hydrological components, stress and recovery is not available. In this paper, we use terrestrial total water storage changes (ATWS) from the Gravity Recovery and Climate Experiment (GRACE) and precipitation data from the Tropical Rainfall Measuring Mission (TRMM) spanning from 2002 to 2013, where ATWS represents the main source of water available for human consumption, agriculture and natural ecosystems. We rely on a combination of temporal trend analysis and spatial statistics methods in order to evaluate the terrestrial total water storage (TWS) dynamics and the relationship between TWS and rainfall during the 'big dry' and 'big wet' events. Here we report the occurrence of hydrological cycle intensification during the study period in Australia which exhibited strong spatial variations: the wet areas (the northern and northeast regions) got wetter while the dry areas (the west and interior of the continent) became drier. By contrast, in southeastern Australia TWS changes over time showed sudden extreme responses to both events. Our results constitute a step beyond quantifying droughts/anomalous wet years that rely solely on precipitation data. This work demonstrates the ability of TWS observations as a significant indicator of hydrological system performance during hydroclimatic events and also an important tool for understanding continental-wide and regional spatial and temporal patterns of water availability