Between a reef and a hard place: capacity to map the next coral reef catastrophe

Increasing sea surface temperature and extreme heat events pose the greatest threat to coral reefs globally, with trends exceeding previous norms. The resultant mass bleaching events, such as those evidenced on the Great Barrier Reef in 2016, 2017, and 2020 have substantial ecological costs in addition to economic and social costs. Advancing remote (nanosatellites, rapid revisit traditional satellites) and in-field (drones) technological capabilities, cloud data processing, and analysis, coupled with existing infrastructure and in-field monitoring programs, have the potential to provide cost-effective and timely information to managers allowing them to better understand changes on reefs and apply effective remediation. Within a risk management framework for monitoring coral bleaching, we present an overview of how remote sensing can be used throughout the whole risk management cycle and highlight the role technological advancement has in earth observations of coral reefs for bleaching events

Streamflow variability and the role of snowmelt in a marginal snow environment

Snowmelt in alpine regions supports hydroelectric power generation, water supply, and agricultural production. These regions are warming, and the impact on streamflow of changes in precipitation and the proportion falling as snow is of interest. We investigate the seasonality and interannual variability of streamflow in the Australian Alps, a key location due to the marginal snowpack with winter air temperatures close to 0°C, and focus on a small subalpine catchment with properties representative of an important part of the broader snow-affected region. Streamflow was highly responsive to precipitation inputs with little autocorrelation observed. Water years were divided into four hydrological seasons based on the mean properties of normalized cumulative inflows. The spring snowmelt season accounted for the greatest proportion of annual inflows (mean = 39 percent). However, correlations between seasonal and annual inflows were only significant in the other three seasons, and winter inflows were the most important contributor to annual variability. The present snowpack is highly variable and sensitive to synoptic-scale influences. Although significant future reductions in snow-covered area have been predicted, we find that water resources are more susceptible to observed declines in total precipitation and likely increases in evapotranspiration than to a shift to proportionally less snowfall

Detecting Frost Stress in Wheat: A Controlled Environment Hyperspectral Study on Wheat Plant Components and Implications for Multispectral Field Sensing

Radiant frost during the reproductive stage of plant growth can result in considerable wheat (Triticum aestivum L.) yield loss. Much effort has been spent to prevent and manage these losses, including post-frost remote sensing of damage. This study was done under controlled conditions to examine the effect of imposed frost stress on the spectral response of wheat plant components (heads and flag leaves). The approach used hyperspectral profiling to determine whether changes in wheat components were evident immediately after a frost (up to 5 days after frosting (DAF)). Significant differences were found between frost treatments, irrespective of DAF, in the Blue/Green (419–512 nanometers (nm)), Red (610–675 nm) and Near Infrared (NIR; 749–889 nm) regions of the electromagnetic spectrum (EMS) in head spectra, and in the Blue (415–494 nm), Red (670–687 nm) and NIR (727–889 nm) regions in the leaf spectra. Significant differences were found for an interaction between time and frost treatment in the Green (544–575 nm) and NIR (756–889 nm) in head spectra, and in the UV (394–396 nm) and Green/Red (564–641 nm) in leaf spectra. These findings were compared with spectral and temporal resolutions of commonly used field agricultural multispectral sensors to examine their potential suitability for frost damage studies at the canopy scale, based on the correspondence of their multispectral bands to the results from this laboratory-based hyperspectral study

Attribution of sources to metal accumulation in an alpine tarn, the Snowy Mountains, Australia

This study analyses 1800 years of heavy metal accumulation in a remote alpine lake experiencing long-range atmospheric contamination and additional inputs of Ag from cloud seeding. In comparison to previous work undertaken on peats, lake sediments show limited post-industrial metal enrichment with enrichment factors of Ag: 1.3, Pb: 1.3, Zn: 1.1, Cu: 1.2 compared to Ag: 2.2, Pb: 3.3, Zn: 2.1, Cu: 4.1 for peat. We show this to be the result of substantial fluvial lithogenic flux of metals (92-97% of total metal flux) to the lake. Total annual metal flux to the lake ranges from: Ag: 4-12 ng/cm2/yr to Zn: 3 383-11 313 ng/cm2/yr. As a result, any contribution of cloud seeding to additional enrichment of Ag in lake sediments is considered negligible. Results show that metal enrichment is not necessarily ubiquitous through a landscape. This has implications for predicting the impacts of atmospheric metal pollution to complex environmental systems

Attribution of sources to metal accumulation in an alpine tarn, the Snowy Mountains, Australia

This study analyses 1800 years of heavy metal accumulation in a remote alpine lake experiencing long-range atmospheric contamination and additional inputs of Ag from cloud seeding. In comparison to previous work undertaken on peats, lake sediments show limited post-industrial metal enrichment with enrichment factors of Ag: 1.3, Pb: 1.3, Zn: 1.1, Cu: 1.2 compared to Ag: 2.2, Pb: 3.3, Zn: 2.1, Cu: 4.1 for peat. We show this to be the result of substantial fluvial lithogenic flux of metals (92-97% of total metal flux) to the lake. Total annual metal flux to the lake ranges from: Ag: 4-12 ng/cm2/yr to Zn: 3 383-11 313 ng/cm2/yr. As a result, any contribution of cloud seeding to additional enrichment of Ag in lake sediments is considered negligible. Results show that metal enrichment is not necessarily ubiquitous through a landscape. This has implications for predicting the impacts of atmospheric metal pollution to complex environmental systems

Spatial controls on the distribution and dynamics of a marginal snowpack in the Australian Alps

Seasonal snowpacks in marginal snow environments are typically warm and nearly isothermal, exhibiting high inter- and intra-annual variability. Measurements of snow depth and snow water equivalent were made across a small subalpine catchment in the Australian Alps over two snow seasons in order to investigate the extent and implications of snowpack spatial variability in this marginal setting. The distribution and dynamics of the snowpack were found to be influenced by upwind terrain, vegetation, solar radiation, and slope. The role of upwind vegetation was quantified using a novel parameter based on gridded vegetation height. The elevation range of the catchment was relatively modest (185\ua0m), and elevation impacted distribution but not dynamics. Two characteristic features of marginal snowpack behaviour are presented. Firstly, the evolution of the snowpack is described in terms of a relatively unstable accumulation state and a highly stable ablation state, as revealed by temporal variations in the mean and standard deviation of snow water equivalent. Secondly, the validity of partitioning the snow season into distinct accumulation and ablation phases is shown to be compromised in such a setting. Snow at the most marginal locations may undergo complete melt several times during a season and, even where snow cover is more persistent, ablation processes begin to have an effect on the distribution of the snowpack early in the season. Our results are consistent with previous research showing that individual point measurements are unable to fully represent the variability in the snowpack across a catchment, and we show that recognising and addressing this variability are particularly important for studies in marginal snow environments

Assessing the Capability and Potential of LiDAR for Weed Detection

Conventional methods of uniformly spraying fields to combat weeds, requires large herbicide inputs at significant cost with impacts on the environment. More focused weed control methods such as site-specific weed management (SSWM) have become popular but require methods to identify weed locations. Advances in technology allows the potential for automated methods such as drone, but also ground-based sensors for detecting and mapping weeds. In this study, the capability of Light Detection and Ranging (LiDAR) sensors were assessed to detect and locate weeds. For this purpose, two trials were performed using artificial targets (representing weeds) at different heights and diameter to understand the detection limits of a LiDAR. The results showed the detectability of the target at different scanning distances from the LiDAR was directly influenced by the size of the target and its orientation toward the LiDAR. A third trial was performed in a wheat plot where the LiDAR was used to scan different weed species at various heights above the crop canopy, to verify the capacity of the stationary LiDAR to detect weeds in a field situation. The results showed that 100% of weeds in the wheat plot were detected by the LiDAR, based on their height differences with the crop canopy

Between a reef and a hard place: capacity to map the next coral reef catastrophe

Increasing sea surface temperature and extreme heat events pose the greatest threat to coral reefs globally, with trends exceeding previous norms. The resultant mass bleaching events, such as those evidenced on the Great Barrier Reef in 2016, 2017, and 2020 have substantial ecological costs in addition to economic and social costs. Advancing remote (nanosatellites, rapid revisit traditional satellites) and in-field (drones) technological capabilities, cloud data processing, and analysis, coupled with existing infrastructure and in-field monitoring programs, have the potential to provide cost-effective and timely information to managers allowing them to better understand changes on reefs and apply effective remediation. Within a risk management framework for monitoring coral bleaching, we present an overview of how remote sensing can be used throughout the whole risk management cycle and highlight the role technological advancement has in earth observations of coral reefs for bleaching events