Using harvest statistics to monitor temporal variation in kangaroo density and harvest rate

Management of the commercial harvest of kangaroos relies on quotas set annually as a proportion of regular estimates of population size. Surveys to generate these estimates are expensive and, in the larger states, logistically difficult; a cheaper alternative is desirable. Rainfall is a disappointingly poor predictor of kangaroo rate of increase in many areas, but harvest statistics (sex ratio, carcass weight, skin size and animals shot per unit time) potentially offer cost-effective indirect monitoring of population abundance (and therefore trend) and status (i.e. under-or overharvest). Furthermore, because harvest data are collected continuously and throughout the harvested areas, they offer the promise of more intensive and more representative coverage of harvest areas than aerial surveys do. To be useful, harvest statistics would need to have a close and known relationship with either population size or harvest rate. We assessed this using longterm (11-22 years) data for three kangaroo species (Macropus rufus, M. giganteus and M. fuliginosus) and common wallaroos (M. robustus) across South Australia, New South Wales and Queensland. Regional variation in kangaroo body size, population composition, shooter efficiency and selectivity required separate analyses in different regions. Two approaches were taken. First, monthly harvest statistics were modelled as a function of a number of explanatory variables, including kangaroo density, harvest rate and rainfall. Second, density and harvest rate were modelled as a function of harvest statistics. Both approaches incorporated a correlated error structure. Many but not all regions had relationships with sufficient precision to be useful for indirect monitoring. However, there was no single relationship that could be applied across an entire state or across species. Combined with rainfall-driven population models and applied at a regional level, these relationships could be used to reduce the frequency of aerial surveys without compromising decisions about harvest management.

Reassessing spatial and temporal dynamics of kangaroo populations

Long-running datasets from aerial surveys of kangaroos (Macropus giganteus, Macropus [uliginosus, Macropus robustus and Macropus rufus) across Queensland, New South Wales and South Australia have been analysed, seeking better predictors of rates of increase which would allow aerial surveys to be undertaken less frequently than annually. Early models of changes in kangaroo numbers in response to rainfall had shown great promise, but much variability. We used normalised difference vegetation index (NDVI) instead, reasoning that changes in pasture condition would provide a better predictor than rainfall. However, except at a fine scale, NDVI proved no better; although two linked periods of rainfall proved useful predictors of rates of increase, this was only in some areas for some species. The good correlations reported in earlier studies were a consequence of data dominated by large droughtinduced adult mortality, whereas over a longer time frame and where changes between years are less dramatic, juvenile survival has the strongest influence on dynamics. Further, harvesting, density dependence and competition with domestic stock are additional and important influences and it is now clear that kangaroo movement has a greater influence on population dynamics than had been assumed. Accordingly, previous conclusions about kangaroo populations as simple systems driven by rainfall need to be reassessed. Examination of this large dataset has permitted descriptions of shifts in distribution of three species across eastern Australia, changes in dispersion in response to rainfall, and an evaluation of using harvest statistics as an index of density and harvest rate. These results have been combined into a risk assessment and decision theory framework to identify optimal monitoring strategies.

Shedding Light on the Microbial Community of the Macropod Foregut Using 454-Amplicon Pyrosequencing

Twenty macropods from five locations in Queensland, Australia, grazing on a variety of native pastures were surveyed and the bacterial community of the foregut was examined using 454-amplicon pyrosequencing. Specifically, the V3/V4 region of 16S rRNA gene was examined. A total of 5040 OTUs were identified in the data set (post filtering). Thirty-two OTUs were identified as 'shared' OTUS (i.e. present in all samples) belonging to either Firmicutes or Bacteroidetes (Clostridiales/Bacteroidales). These phyla predominated the general microbial community in all macropods. Genera represented within the shared OTUs included: unclassified Ruminococcaceae, unclassified Lachnospiraceae, unclassified Clostridiales, Peptococcus sp. Coprococcus spp., Streptococcus spp., Blautia sp., Ruminoccocus sp., Eubacterium sp., Dorea sp., Oscillospira sp. and Butyrivibrio sp. The composition of the bacterial community of the foregut samples of each the host species (Macropus rufus, Macropus giganteus and Macropus robustus) was significantly different allowing differentiation between the host species based on alpha and beta diversity measures. Specifically, eleven dominant OTUs that separated the three host species were identified and classified as: unclassified Ruminococcaceae, unclassified Bacteroidales, Prevotella spp. and a Syntrophococcus sucromutans. Putative reductive acetogens and fibrolytic bacteria were also identified in samples. Future work will investigate the presence and role of fibrolytics and acetogens in these ecosystems. Ideally, the isolation and characterization of these organisms will be used for enhanced feed efficiency in cattle, methane mitigation and potentially for other industries such as the biofuel industry.