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The koala population in southwest Queensland is a large low-density population of important conservation value which is vulnerable to habitat loss, drought and climate change. The nutrient quality of Eucalyptus food trees favoured by koalas is an important factor influencing the survival of the koala on a low-nutrient-and-high-toxin diet. This study investigated the relationship between the diet of koalas, and food tree characteristics. Vegetation surveys, cuticle analysis and leaf chemical analysis were conducted in 14 study sites in southwest Queensland during the winter of 2010. Koala diet composition was different to eucalypt tree species availability, with Eucalyptus camaldulensis (56.5%) the most important tree species, E. coolabah (15.4%) and E. populnea (12.4%) of secondary preference. Leaf chemicals (moisture, total nitrogen, total phenolics, and a nutrition index = (moisture*nitrogen) / total phenolics) were significantly related to tree species, surface water availability, soil type and proximity to major creeks. Only leaf moisture was significantly correlated with koala food tree species preference. The presence of surface water appears to be a crucial characteristic of suitable koala habitat while riparian habitats dominant by E. camaldulensis are critical for conserving the koala populations in southwest Queensland.

Conservation planning and population assessment for widely-distributed, but vulnerable, arboreal folivore species demands cost-effective mapping of habitat suitability over large areas. This study tested whether multispectral data from WorldView-3 could be used to estimate and map foliar digestible nitrogen (DigN), a nutritional measure superior to total nitrogen for tannin-rich foliage for the koala (Phascolarctos cinereus). We acquired two WorldView-3 images (November 2015) and collected leaf samples from Eucalyptus woodlands in semi-arid eastern Australia. Linear regression indicated the normalized difference index using bands “Coastal” and “NIR1” best estimated DigN concentration (% dry matter, R2 = 0.70, RMSE = 0.19%). Foliar DigN concentration was mapped for multi-species Eucalyptus open woodlands across two landscapes using this index. This mapping method was tested on a WorldView-2 image (October 2012) with associated koala tracking data (August 2010 to November 2011) from a different landscape of the study region. Quantile regression showed significant positive relationship between estimated DigN and occurrence of koalas at 0.999 quantile (R2 = 0.63). This study reports the first attempt to use a multispectral satellite-derived spectral index for mapping foliar DigN at a landscape-scale (100s km2). The mapping method can potentially be incorporated in mapping and monitoring koala habitat suitability for conservation management.

Soil contamination with heavy metals is a worldwide problem especially in China. The interrelation of soil bacterial community structure, antibiotic resistance genes, and heavy metal contamination in soil is still unclear. Here, seven agricultural areas (G1-G7) with heavy metal contamination were sampled with different distances (741 to 2556 m) to the factory. Denaturing gradient gel electrophoresis (DGGE) and Shannon index were used to analyze bacterial community diversity. Real-time fluorescence quantitative PCR was used to detect the relative abundance of ARGs sul1, sul2, tetA, tetM, tetW, one mobile genetic elements (MGE) inti1. Results showed that all samples were polluted by Cadmium (Cd), and some of them were polluted by lead (Pb), mercury (Hg), arsenic (As), copper (Cu), and zinc (Zn). DGGE showed that the most abundant bacterial species were found in G7 with the lightest heavy metal contamination. The results of the principal component analysis and clustering analysis both showed that G7 could not be classified with other samples. The relative abundance of sul1 was correlated with Cu, Zn concentration. Gene sul2 are positively related with total phosphorus, and tetM was associated with organic matter. Total gene abundances and relative abundance of inti1 both correlated with organic matter. Redundancy analysis showed that Zn and sul2 were significantly related with bacterial community structure. Together, our results indicate a complex linkage between soil heavy metal concentration, bacterial community composition, and some global disseminated ARG abundance.

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