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Australian fire weather shows spatiotemporal variability on interannual and multi-decadal time scales. We investigate the climate factors that drive this variability using 39 station-based historical time series of the seasonal 90th-percentile of the McArthur Forest Fire Danger Index (FFDI) extending from 1973 through 2017. Using correlation analyses, we examine the relationship of these time series to the El Niño Southern Oscillation (ENSO), the Southern Annular Mode (SAM) and the Indian Ocean Dipole (IOD), considering both concurrent and time-lagged relationships. Additionally, longer term behaviour of the time series using linear trend analysis is discussed in the context of the climate drivers, Interdecadal Pacific Oscillation (IPO) and anthropogenic climate change. The results show that ENSO is the main driver for interannual variability of fire weather, as defined by FFDI in this study, for most of Australia. In general, El Niño-like conditions lead to more extreme fire weather, with this effect stronger in eastern Australia. However, there are significant regional variations to this general rule. In NSW, particularly along the central coast, negative SAM is a primary influence for elevated fire weather in late-winter and spring. In the southeast (VIC and TAS), the El Niño-like impact is exacerbated when positive IOD conditions are simultaneously observed. The spring conditions are key, and strongly influence what is observed during the following summer. On longer time scales (45 years), linear trends are upward at most stations; this trend is strongest in the southeast and during the spring. The positive trends are not driven by the trends in the climate drivers and they are not consistent with hypothesized impacts of the IPO, either before or after its late-1990s shift to the cold phase. We propose that anthropogenic climate change is the primary driver of the trend, through both higher mean temperatures and potentially through associated shifts in large-scale rainfall patterns. Variations from interannual factors are generally larger in magnitude than the trend effects observed to date. [ABSTRACT FROM AUTHOR]

Hormonal assessment tools are important for determining the reproductive success of production animals. This study used non-invasive wool assessment to quantify changes in progesterone and cortisol levels in reproducing female merino sheep. Wool samples were collected from a group of n = 46 maiden merino ewes (22–25 months old), naturally joined under natural light conditions in southern New South Wales (NSW), Australia. Three shearing opportunities were conducted as part of standard on-farm management practices. The wool samples were collected at three different dates during 2017, January (prior to rams being put out with the mob and to provide a baseline level since previous shearing in May 2016), September (during very late stages of gestation–approximately 2 weeks prior to parturition) and December (ewes had given birth and ~2-month-old lambs were at foot). Analysis of cortisol and progesterone was conducted concurrently from the same sample of wool. The hormones in wool samples quantified using commercially available cortisol and progesterone enzyme-immunoassay kits. Wool cortisol concentrations increased significantly (p = 3.04E-14) from pre-joining in January (1.33±0.12 ng/g) to late gestation in September (3.59±0.12 ng/g). Concentration of wool cortisol post-lambing in December (3.27±0.14 ng/g) did not decline significantly (p = 0.124) after gestation however remained significantly higher (p = 3.82E-10) than pre-joining levels. Wool progesterone (PG) concentrations increased significantly (p = 1.83E-33) from pre-joining (0.04±0.005 ng/g) in January to late gestation in September (5.53±0.13 ng/g) with a significant (p = 5.44E-59) decline observed in December (0.05±0.003 ng/g) to post- pregnancy concentrations. No significant difference was shown between pre-joining and post lambing PG concentrations (p = 0.057). Our results showed that non-invasive assessment of hormones in Merino sheep wool reflected significant increase in both cortisol and progesterone guided by pregnancy. [ABSTRACT FROM AUTHOR]