Storylines: an alternative approach to representing uncertainty in physical aspects of climate change

Investigating the relationships between climate extremes and crop yield can help us understand how unfavourable climatic conditions affect crop production. In this study, two statistical models, multiple linear regression and random forest, were used to identify rainfall extremes indices affecting wheat yield in three different regions of the New South Wales wheat belt. The results show that the random forest model explained 41–67% of the year-to-year yield variation, whereas the multiple linear regression model explained 34–58%. In the two models, 3-month timescale standardized precipitation index of Jun.–Aug. (SPI_JJA), Sep.–Nov. (SPI_SON), and consecutive dry days (CDDs) were identified as the three most important indices which can explain yield variability for most of the wheat belt. Our results indicated that the inter-annual variability of rainfall in winter and spring was largely responsible for wheat yield variation, and pre-growing season rainfall played a secondary role. Frequent shortages of rainfall posed a greater threat to crop growth than excessive rainfall in eastern Australia. We concluded that the comparison between multiple linear regression and machine learning algorithm proposed in the present study would be useful to provide robust prediction of yields and new insights of the effects of various rainfall extremes, when suitable climate and yield datasets are available.     

Abiotic ammonium formation in the presence of Ni-Fe metals and alloys and its implications for the Hadean nitrogen cycle

Experiments with dinitrogen-, nitrite-, nitrate-containing solutions were conducted without headspace in Ti reactors (200°C), borosilicate septum bottles (70°C) and HDPE tubes (22°C) in the presence of Fe and Ni metal, awaruite (Ni₈₀Fe₂₀) and tetrataenite (Ni₅₀Fe₅₀). In general, metals used in this investigation were more reactive than alloys toward all investigated nitrogen species. Nitrite and nitrate were converted to ammonium more rapidly than dinitrogen, and the reduction process had a strong temperature dependence. We concluded from our experimental observations that Hadean submarine hydrothermal systems could have supplied significant quantities of ammonium for reactions that are generally associated with prebiotic synthesis, especially in localized environments. Several natural meteorites (octahedrites) were found to contain up to 22 ppm N_tot. While the oxidation state of N in the octahedrites was not determined, XPS analysis of metals and alloys used in the study shows that N is likely present as nitride (N^3-). This observation may have implications toward the Hadean environment, since, terrestrial (e.g., oceanic) ammonium production may have been supplemented by reduced nitrogen delivered by metal-rich meteorites. This notion is based on the fact that nitrogen dissolves into metallic melts.     

In situ arsenic removal in an alkaline clastic aquifer

In situ removal of As from ground water used for water supply has been accomplished elsewhere in circum-neutral ground water containing high dissolved Fe(II) concentrations. The objective of this study was to evaluate in situ As ground-water treatment approaches in alkaline ground-water (pH > 8) that contains low dissolved Fe (<a few tens of μg/L). The low dissolved Fe content limits development of significant Fe-oxide and the high-pH limits As adsorption onto Fe-oxide. The chemistries of ground water in the two aquifers studied are similar except for the inorganic As species. Although total inorganic As concentrations were similar, one aquifer has dominantly aqueous As(III) and the other has mostly As(V). Dissolved O₂, Fe(II), and HCl were added to water and injected into the two aquifers to form Fe-oxide and lower the pH to remove As. Cycles of injection and withdrawal involved varying Fe(II) concentrations in the injectate. The As concentrations in water withdrawn from the two aquifers were as low as 1 and 6 μg/L, with greater As removal from the aquifer containing As(V). However, Fe and Mn concentrations increased to levels greater than US drinking water standards during some of the withdrawal periods. A balance between As removal and maintenance of low Fe and Mn concentrations may be a design consideration if this approach is used for public-supply systems. The ability to lower As concentrations in situ in high-pH ground water should have broad applicability because similar high-As ground water is present in many parts of the world.     

Detecting shadows in multi-temporal aerial imagery to support near-real-time change detection

Multi-temporal aerial imagery captured via an approach called repeat station imaging (RSI) facilitates post-hazard assessment of damage to infrastructure. Spectral-radiometric (SR) variations caused by differences in shadowing may inhibit successful change detection based on image differencing. This study evaluates a novel approach to shadow classification based on bi-temporal imagery, which exploits SR change signatures associated with transient shadows. Changes in intensity (brightness from red–green–blue images) and intensity-normalized blue waveband values provide a basis for classifying transient shadows across a range of material types with unique reflectance properties, using thresholds that proved versatile for very different scenes. We derive classification thresholds for persistent shadows based on hue to intensity ratio (H/I) images, by exploiting statistics obtained from transient shadow areas. We assess shadow classification accuracy based on this procedure, and compare it to the more conventional approach of thresholding individual H/I images based on frequency distributions. Our efficient and semi-automated shadow classification procedure shows improved mean accuracy (93.3%) and versatility with different image sets over the conventional approach (84.7%). For proof-of-concept, we demonstrate that overlaying bi-temporal imagery also facilitates normalization of intensity values in transient shadow areas, as part of an integrated procedure to support near-real-time change detection.     

The development of a non-linear autoregressive model with exogenous input (NARX) to model climate-water clarity relationships: reconstructing a historical water clarity index for the coastal waters of the southeastern USA

Theoretical and Applied Climatology - The coastal waters of the southeastern USA contain important protected habitats and natural resources that are vulnerable to climate variability and singular...     

Postmaterialism and Support for the Environment in the United States

Postmaterialist theory suggests that under conditions of continuously expanding economic and personal security, younger generations will be less oriented to acquiring material goods and more committed than their older peers to attaining postmaterial social goals such as increased free self-expression and a healthy natural environment. Using the latest World Values Survey sample for the United States, ordinary least squares (OLS) and logit regressions are employed to test whether youth is a predictor of postmaterialism as theory suggests, and whether postmaterialism positively predicts environmental concern and individual actions in support of the environment. Age is found to be a negative and statistically significant factor in explaining variation in the postmaterialism index, and this index is in turn found to be a statistically significant positive factor in explaining individual environmental concern and activism. A combination of increased economic security and entrance of younger generations into adulthood could well matter for our environmental future.     

A comparison of mercury in estuarine fish between Florida Bay and the Indian River Lagoon, Florida, USA

Concentrations of mercury (Hg) in fish were compared between two Florida estuaries, the Indian River Lagoon and Florida Bay. The objective was to determine if differences in Hg concentration exist and to attempt to relate those differences to sources of Hg. Five hundred and thirteen estuarine fish were collected and analyzed for Hg concentration. Fish species collected were black drum, bluefish, bonnethead shark, common snook, crevalle jack, gafftopsail catfish, gray snapper, Mayan cichlid, pompano, red drum, sheepshead, southern flounder, spadefish, and spotted seatrout. Analysis of variance of species-specific Hg data among the three defined regions of eastern and western Florida Bay and the Indian River Lagoon substantiated regional differences. Proximity to known anthropogenic sources of Hg appeared to be a significant factor in the distribution of Hg concentration among the fish collected. Sufficient numbers of crevalle jack, gray snapper, and spotted seatrout were collected to permit statistical analysis among regions. Hg concentrations in all three of these species from eastern Florida Bay were higher than those collected in the other two areas. A major fraction of the estuarine fish collected in eastern Florida Bay exceeded one or more State of Florida or U.S. Food and Drug Administration fish consumption health advisory criteria. In general, fish from western Florida Bay contained less Hg than those from the Indian River Lagoon, and fish from the Indian River contained less Hg than those from eastern Florida Bay. Crevalle jack from all areas and spotted seatrout from Florida Bay were placed on a consumption advisory in Florida. Detailed study of Florida Bay food web dynamics and Hg biogeochemical cycling is recommended to better understand the processes underlying the elevated Hg levels in fish from eastern Florida Bay. This information may be vital in the formulation of appropriate strategies in the ongoing South Florida restoration process.