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Long-term, reliable datasets of satellite-based vegetation condition are essential for understanding terrestrial ecosystem responses to global environmental change, particularly in Australia, which is characterised by diverse ecosystems and strong interannual climate variability. We comprehensively evaluate several existing global Advanced Very High Resolution Radiometer (AVHRR) normalised-difference vegetation index (NDVI) products for their suitability for long-term vegetation monitoring in Australia. Comparisons with the MODIS NDVI highlight significant deficiencies, particularly over densely vegetated regions. Moreover, all the assessed products failed to adequately reproduce the interannual variability in the pre-MODIS era as indicated by Landsat NDVI anomalies. To address these limitations, we propose a new approach to calibrating and harmonising NOAA's Climate Data Record of AVHRR NDVI to the MODIS MCD43A4 NDVI for Australia using a gradient-boosting decision tree ensemble method. Two versions of the datasets are developed, one incorporating climate data in the predictors (“AusENDVI-clim”: Australian Empirical NDVI-climate) and another that is independent of climate data (“AusENDVI-noclim”). These datasets, spanning 1982–2013 at a spatial resolution of 0.05° and with a monthly time step, exhibit strong correlations (r2=0.89–0.94) and low mean errors compared with MODIS MCD43A4 NDVI (mean absolute error (MAE) = 0.014–0.028, RMSE = 0.021–0.046), accurately reproducing seasonal cycles over densely vegetated regions. Furthermore, they closely replicate the interannual variability in vegetation condition in the pre-MODIS era. A reliable method for gap-filling the AusENDVI record is also developed that leverages climate, atmospheric CO2 concentration, and woody-cover fraction predictors. The resulting synthetic NDVI dataset shows excellent agreement with the MODIS MCD43A4 NDVI and the recalibrated AVHRR NDVI time series (r2=0.82–0.95, MAE = 0.016–0.029, RMSE = 0.039–0.041). Finally, we provide a complete 41-year dataset where the gap-filled AusENDVI-clim from January 1982 to February 2000 is joined with the MODIS MCD43A4 NDVI from March 2000 to December 2022. Analysing 40-year per-pixel trends in Australia's annual maximum NDVI revealed increasing values, and shifts in the timing, of the annual peak NDVI across most of the continent, underscoring the dataset's potential to address crucial questions regarding the changing vegetation phenology and its drivers. The AusENDVI dataset can be used for studying Australia's changing vegetation dynamics and downstream impacts on the terrestrial carbon and water cycles, and it provides a reliable foundation for further research into the drivers of vegetation change. AusENDVI is open access and available at https://doi.org/10.5281/zenodo.10802703 (Burton et al., 2024).

We report on the successful fabrication of orthomode transducer-coupled transition-edge sensor (TES) bolometer arrays for cosmic microwave background (CMB) polarimetry experiments with the superconductor electronics fabrication facility at SEEQC Inc. Commercial microfabrication foundry could provide increase in detector fabrication throughput for a next-generation CMB experiment, CMB-S4, that would deploy approximately one order of magnitude more detectors than current CMB experiments. We also developed TES bolometers with two TESs in series that have two different superconducting temperatures (Tc) using a superconducting proximity effect between niobium (Nb) and aluminum-manganese (AlMn) alloy. We will discuss the motivation, design considerations, fabrication processes, test results, and how industrial detector fabrication could be a path to fabricate hundreds of detector wafers for future CMB polarimetry experiments and other experiments that require TESs and superconducting RF circuits.

I particolari costruttivi presentati durante la XII Triennale di Milano del 1960 e alla Biennale di Architettura di Venezia del 1968, suggeriscono che Franco Albini e Franca Helg abbiano impiegato il mock-up come strumento per valutare soluzioni innovative nella realizzazione della Nuova Rinascente in Piazza Fiume a Roma inaugurata nel 1961. Di fronte a vincoli normativi e fattori contingenti, gli architetti esplorarono le diverse possibilità del progetto. È rilevante notare che il passaggio da un primo progetto (1957), caratterizzato da portali in acciaio e pareti in travertino, al progetto realizzato (1961), con un’ossatura portante in acciaio e chiusura esterna in pannelli di silipol, è da attribuire principalmente a un’imposizione della Soprintendenza che richiese un carattere “romano” per l’edificio. Di conseguenza, il fronte “ostentatamente bidimensionale” del progetto iniziale doveva mutare in una “superficie corrugata” di pannelli, portando gli architetti a concepire una versione prefabbricata della tradizionale facciata in pietra. Il contributo, ricostruendo il processo ideativo del progetto della Nuova Rinascente di Roma, si propone di esplorare l’inclinazione generale dell’architetto-ingegnere a sperimentare, attraverso il mock-up, un approccio “non convenzionale” al progetto, concepito come la potenziale radicalizzazione di nuovi protocolli spaziali, formali e materiali che richiedono la precisione del lavoro come presupposto essenziale per la qualità degli esiti.

Measuring the spatiotemporal dynamics of lake and reservoir water storage is fundamental for assessing the influence of climate variability and anthropogenic activities on water quantity and quality. Previous studies estimated relative water volume changes for lakes where both satellite-derived extent and radar altimetry data are available. This approach is limited to only a few hundred lakes worldwide and cannot estimate absolute (i.e. total volume) water storage. We increased the number of measured lakes by a factor of 300 by using high-resolution Landsat and Sentinel-2 optical remote sensing and ICESat-2 laser altimetry, in addition to radar altimetry from the Topex/Poseidon; Jason-1, Jason-2 and Jason-3; and Sentinel-3 and Sentinel-6 instruments. Historical time series (1984–2020) of water storage could be derived for more than 170 000 lakes globally with a surface area of at least 1 km2, representing 99 % of the total volume of all water stored in lakes and reservoirs globally. Specifically, absolute lake volumes are estimated based on topographic characteristics and lake properties that can be observed by remote sensing. In addition to that, we also generated relative lake volume changes solely based on satellite-derived heights and extents if both were available. Within this dataset, we investigated how many lakes can be measured in near real time (2020–current) in basins worldwide. We developed an automated workflow for near-real-time global lake monitoring of more than 27 000 lakes. The GloLakes historical and near-real-time lake storage dynamics data from 1984 to current are publicly available through https://doi.org/10.25914/K8ZF-6G46 (Hou et al., 2022c) and a web-based data explorer (http://www.globalwater.online, last access: 12 December 2023).

We develop high-resolution (1 km) estimates of gross primary productivity (GPP), ecosystem respiration (ER), and net ecosystem exchange (NEE) over the Australian continent for the period January 2003 to June 2022 by empirical upscaling of flux tower measurements. We compare our estimates with nine other products that cover the three broad categories that define current methods for estimating the terrestrial carbon cycle and assess if consiliences between datasets can point to the correct dynamics of Australia's carbon cycle. Our results indicate that regional empirical upscaling greatly improves upon the existing global empirical upscaling efforts, outperforms process-based models, and agrees much better with the dynamics of CO2 flux over Australia as estimated by two regional atmospheric inversions. Our nearly 20-year estimates of terrestrial carbon fluxes revealed that Australia is a strong net carbon sink of −0.44 PgC yr−1 (interquartile range, IQR = 0.42 PgC yr−1) on average, with an inter-annual variability of 0.18 PgC yr−1 and an average seasonal amplitude of 0.85 PgC yr−1. Annual mean carbon uptake estimated from other methods ranged considerably, while carbon flux anomalies showed much better agreement between methods. NEE anomalies were predominately driven by cumulative rainfall deficits and surpluses, resulting in larger anomalous responses from GPP than ER. In contrast, we show that the long-term average seasonal cycle is dictated more by the variability in ER than GPP, resulting in peak carbon uptake typically occurring during the cooler, drier austral autumn and winter months. This new estimate of Australia's terrestrial carbon cycle provides a benchmark for assessment against land surface model simulations and a means for monitoring of Australia's terrestrial carbon cycle at an unprecedented high resolution. We call this new estimate of Australia's terrestrial carbon cycle “AusEFlux” (Australian Empirical Fluxes).

In this study, a surface plasmon resonance (SPR) sensor based on modified plastic optical fibers (POFs) was combined with a specific molecularly imprinted polymer (MIP), used as a synthetic receptor, for glyphosate (GLY) determination in aqueous solutions. Since GLY is a non-selective herbicide associated with severe environmental and health problems, detecting glyphosate in environmental and biological samples remains challenging. The selective interaction between the MIP layer and GLY is monitored by exploiting the SPR phenomenon at the POF’s gold surface. Experimental results show that in about ten minutes and by dropping microliter volume samples, the presented optical–chemical sensor can quantify up to three orders of magnitude of GLY concentrations, from nanomolar to micromolar, due to a thin MIP layer over the SPR surface. The developed optical–chemical sensor presents a detection limit of about 1 nM and can be used for onsite GLY measurements. Moreover, the experimental analysis demonstrated the high selectivity of the proposed POF-based chemical sensor.

An optical–chemical sensor based on two modified plastic optical fibers (POFs) and a molecularly imprinted polymer (MIP) is realized and tested for the detection of 2-furaldehyde (2-FAL). The 2-FAL measurement is a scientific topic of great interest in different application fields, such as human health and life status monitoring in power transformers. The proposed sensor is realized by using two POFs as segmented waveguides (SW) coupled through a micro-trench milled between the fibers and then filled with a specific MIP for the 2-FAL detection. The experimental results show that the developed intensity-based sensor system is highly selective and sensitive to 2-FAL detection in aqueous solutions, with a limit of detection of about 0.04 mg L−1. The proposed sensing approach is simple and low-cost, and it shows performance comparable to that of plasmonic MIP-based sensors present in the literature for 2-FAL detection.

Calder, Tong et al. discuss how the rapid development of COVID-19 vaccines benefited from HIV/AIDS research. They highlight lessons learned from the COVID-19 vaccine development experience that could accelerate and re-energize the development of a safe and efficacious HIV vaccine.

Many thousands of large dam reservoirs have been constructed worldwide during the last 70 years to increase reliable water supplies and support economic growth. Because reservoir storage measurements are generally not publicly available, so far there has been no global assessment of long-term dynamic changes in reservoir water volumes. We overcame this by using optical (Landsat) and altimetry remote sensing to reconstruct monthly water storage for 6695 reservoirs worldwide between 1984 and 2015. We relate reservoir storage to resilience and vulnerability and investigate interactions between precipitation, streamflow, evaporation, and reservoir water storage. This is based on a comprehensive analysis of streamflow from a multi-model ensemble and as observed at ca. 8000 gauging stations, precipitation from a combination of station, satellite and forecast data, and open water evaporation estimates. We find reservoir storage has diminished substantially for 23 % of reservoirs over the three decades, but increased for 21 %. The greatest declines were for dry basins in southeastern Australia (−29 %), southwestern USA (−10 %), and eastern Brazil (−9 %). The greatest gains occurred in the Nile Basin (+67 %), Mediterranean basins (+31 %) and southern Africa (+22 %). Many of the observed reservoir changes could be explained by changes in precipitation and river inflows, emphasizing the importance of multi-decadal precipitation changes for reservoir water storage. Uncertainty in the analysis can come from, among others, the relatively low Landsat imaging frequency for parts of the Earth and the simple geo-statistical bathymetry model used. Our results also show that there is generally little impact from changes in net evaporation on storage trends. Based on the reservoir water balance, we deduce it is unlikely that water release trends dominate global trends in reservoir storage dynamics. This inference is further supported by different spatial patterns in water withdrawal and storage trends globally. A more definitive conclusion about the impact of changes in water releases at the global or local scale would require data that unfortunately are not publicly available for the vast majority of reservoirs globally.

Context: Rigorous monitoring and reporting helps determine effectiveness of water reforms. We assess implementation of the Murray–Darling Basin Plan, intended to ensure that water resources are used sustainably. Many aspects of Basin Plan implementation are poorly monitored and reported, owing to fragmented and inadequate data collection across jurisdictions. Aims: To address this issue, we synthesised publicly available data for 27 indicators that provide insights into the State of the Basin since implementation of the Plan in 2012–2013. Methods: Indicators, in Indigenous, economic, environmental, social and compliance themes, were chosen to assess effects of policy interventions for water reform within the Water Act 2007 (Cth), the underpinning legislation for the Plan. Key results: Of the targets for the indicators, seven were met (26%), 10 were variable but showed no overall trend (37%) and 10 were not met (37%). Conclusions: Five of seven economic targets, relating to irrigated agriculture and capital value of land, showed improvement, whereas of 20 Indigenous, environmental, social and compliance indicator targets, only two environmental ones were met. Implications: We detail practical improvements, including building a more comprehensive, Basin-wide monitoring and reporting framework that could be implemented to aid assessment of progress on implementation of the Basin Plan. Rigorous monitoring and reporting helps determine the effectiveness of water reforms. The Murray–Darling Basin Plan is a major public policy reform intended to restore water to the environment. We present an independent assessment of the state of the Basin. For 27 indicators, we found that those for the environment were not met and the major benefits were economic, favouring irrigators. [ABSTRACT FROM AUTHOR]

Optical fiber biosensors can be used to develop point-of-care tests (POCTs) for detecting viruses and bacteria in several matrices. In particular, the surface plasmon resonance (SPR) and localized SPR phenomena (LSPR) can be excited by exploiting low-cost and small-size optical fiber chips. Generally, SPR or LSPR sensors are realized using several kinds of modified optical fibers (silica, plastic, or specialty) or by exploiting other optical waveguides (e.g., slab, spoon-shaped waveguides, etc.). More specifically, optical fiber sensors can be classified as intrinsic or extrinsic. In the “optical fiber intrinsic sensors”, the sensing area is realized in the optical fiber directly, such as in the case of plasmonic platforms based on D-shaped plastic optical fibers (POFs), tapered optical fibers, U-bend POFs, or light-diffusing fibers (LDFs). By contrast, when an optical fiber is used as a mere waveguide allowing for the launch of light to the sensing region and its collection, it is defined as an extrinsic optical fiber sensor, like in the case of the plasmonic sensors realized by Cennamo et al. using POFs combined with spoon-shaped waveguides, 3D-printed platforms, bacterial cellulose waveguides, nanogratings, and InkJet-printed chips. To realize optical biosensor chips for the detection of viruses and bacteria, both intrinsic and extrinsic plasmonic POF sensors can be efficiently combined with receptors specific for membrane proteins, either biological (e.g., antibodies, aptamers, enzymes, etc.) or synthetic (e.g., molecularly imprinted polymers), to build groundbreaking POCTs.

A simple and effective two-step data assimilation framework was developed to improve soil moisture representation in an operational large-scale water balance model. The first step is a Kalman-filter-type sequential state updating process that exploits temporal covariance statistics between modelled and satellite-derived soil moisture to produce analysed estimates. The second step is to use analysed surface moisture estimates to impart mass conservation constraints (mass redistribution) on related states and fluxes of the model using tangent linear modelling theory in a post-analysis adjustment after the state updating at each time step. In this study, we assimilate satellite soil moisture retrievals from both Soil Moisture Active Passive (SMAP) and Soil Moisture and Ocean Salinity (SMOS) missions simultaneously into the Australian Water Resources Assessment Landscape model (AWRA-L) using the proposed framework and evaluate its impact on the model's accuracy against in situ observations across water balance components. We show that the correlation between simulated surface soil moisture and in situ observation increases from 0.54 (open loop) to 0.77 (data assimilation). Furthermore, indirect verification of root-zone soil moisture using remotely sensed Enhanced Vegetation Index (EVI) time series across cropland areas results in significant improvements from 0.52 to 0.64 in correlation. The improvements gained from data assimilation can persist for more than 1 week in surface soil moisture estimates and 1 month in root-zone soil moisture estimates, thus demonstrating the efficacy of this data assimilation framework.

Long-term, reliable datasets of satellite-based vegetation condition are essential for understanding terrestrial ecosystem responses to global environmental change, particularly in Australia, which is characterised by diverse ecosystems and strong interannual climate variability. We comprehensively evaluate several existing global Advanced Very High Resolution Radiometer (AVHRR) normalised-difference vegetation index (NDVI) products for their suitability for long-term vegetation monitoring in Australia. Comparisons with the MODIS NDVI highlight significant deficiencies, particularly over densely vegetated regions. Moreover, all the assessed products failed to adequately reproduce the interannual variability in the pre-MODIS era as indicated by Landsat NDVI anomalies. To address these limitations, we propose a new approach to calibrating and harmonising NOAA's Climate Data Record of AVHRR NDVI to the MODIS MCD43A4 NDVI for Australia using a gradient-boosting decision tree ensemble method. Two versions of the datasets are developed, one incorporating climate data in the predictors ("AusENDVI-clim": Australian Empirical NDVI-climate) and another that is independent of climate data ("AusENDVI-noclim"). These datasets, spanning 1982–2013 at a spatial resolution of 0.05° and with a monthly time step, exhibit strong correlations (r2=0.89 –0.94) and low mean errors compared with MODIS MCD43A4 NDVI (mean absolute error (MAE) = 0.014–0.028, RMSE = 0.021–0.046), accurately reproducing seasonal cycles over densely vegetated regions. Furthermore, they closely replicate the interannual variability in vegetation condition in the pre-MODIS era. A reliable method for gap-filling the AusENDVI record is also developed that leverages climate, atmospheric CO 2 concentration, and woody-cover fraction predictors. The resulting synthetic NDVI dataset shows excellent agreement with the MODIS MCD43A4 NDVI and the recalibrated AVHRR NDVI time series (r2=0.82 –0.95, MAE = 0.016–0.029, RMSE = 0.039–0.041). Finally, we provide a complete 41-year dataset where the gap-filled AusENDVI-clim from January 1982 to February 2000 is joined with the MODIS MCD43A4 NDVI from March 2000 to December 2022. Analysing 40-year per-pixel trends in Australia's annual maximum NDVI revealed increasing values, and shifts in the timing, of the annual peak NDVI across most of the continent, underscoring the dataset's potential to address crucial questions regarding the changing vegetation phenology and its drivers. The AusENDVI dataset can be used for studying Australia's changing vegetation dynamics and downstream impacts on the terrestrial carbon and water cycles, and it provides a reliable foundation for further research into the drivers of vegetation change. AusENDVI is open access and available at 10.5281/zenodo.10802703 (Burton et al., 2024). [ABSTRACT FROM AUTHOR]

In this study, a surface plasmon resonance (SPR) sensor based on modified plastic optical fibers (POFs) was combined with a specific molecularly imprinted polymer (MIP), used as a synthetic receptor, for glyphosate (GLY) determination in aqueous solutions. Since GLY is a non-selective herbicide associated with severe environmental and health problems, detecting glyphosate in environmental and biological samples remains challenging. The selective interaction between the MIP layer and GLY is monitored by exploiting the SPR phenomenon at the POF's gold surface. Experimental results show that in about ten minutes and by dropping microliter volume samples, the presented optical–chemical sensor can quantify up to three orders of magnitude of GLY concentrations, from nanomolar to micromolar, due to a thin MIP layer over the SPR surface. The developed optical–chemical sensor presents a detection limit of about 1 nM and can be used for onsite GLY measurements. Moreover, the experimental analysis demonstrated the high selectivity of the proposed POF-based chemical sensor. [ABSTRACT FROM AUTHOR]