Hydrogen utilising bacteria from the forestomach of eastern grey (Macropus giganteus) and red (Macropus rufus) kangaroos

Reductive acetogenesis is an alternative to methanogenesis for removing hydrogen produced during enteric fermentation. In Australia, kangaroos have evolved an enlarged forestomach analogous to the rumen of sheep and cattle. However, unlike sheep and cattle, kangaroos produce very little methane from enteric fermentation. From samples of gut contents from five eastern grey and three red kangaroos, we were not able to detect methanogens using a PCR protocol, but did detect the formyltetrahydrofolate synthetase (FTHFS) gene (likely to be used for reductive acetogenesis) in all animals. Isolations to recover acetogens resulted in two different classes of hydrogen consuming bacteria being isolated. The first class consisted of acetogens that possessed the FTHFS gene, which except for Clostridium glycolicum, were not closely related to any previously cultured bacteria. The second class were not acetogens but consisted of enterobacteria (Escherichia coli and Shigella) that did not possess FTHFS genes but did utilise hydrogen and produce acetate. Enumeration of the acetogens containing the FTHFS gene by real-time PCR indicated that bacteria of the taxa designated YE257 were common to all the kangaroos whereas YE266/YE273 were only detected in eastern grey kangaroos. When present, both species occurred at densities above *106 cell equivalents per mL. C. glycolicum was not detected in the kangaroos and, unlike YE257 and YE266/273, is unlikely to play a major role in reductive acetogenesis in the foregut of kangaroos.

Stochastic demography and population dynamics in the red kangaroo Macropus rufus

1. Many organisms inhabit strongly fluctuating environments but their demography and population dynamics are often analysed using deterministic models and elasticity analysis, where elasticity is defined as the proportional change in population growth rate caused by a proportional change in a vital rate. Deterministic analyses may not necessarily be informative because large variation in a vital rate with a small deterministic elasticity may affect the population growth rate more than a small change in a less variable vital rate having high deterministic elasticity. 2. We analyse a stochastic environment model of the red kangaroo (Macropus rufus), a species inhabiting an environment characterized by unpredictable and highly variable rainfall, and calculate the elasticity of the stochastic growth rate with respect to the mean and variability in vital rates. 3. Juvenile survival is the most variable vital rate but a proportional change in the mean adult survival rate has a much stronger effect on the stochastic growth rate. 4. Even if changes in average rainfall have a larger impact on population growth rate, increased variability in rainfall may still be important also in long-lived species. The elasticity with respect to the standard deviation of rainfall is comparable to the mean elasticities of all vital rates but the survival in age class 3 because increased variation in rainfall affects both the mean and variability of vital rates. 5. Red kangaroos are harvested and, under the current rainfall pattern, an annual harvest fraction of c. 20% would yield a stochastic growth rate about unity. However, if average rainfall drops by more than c. 10%, any level of harvesting may be unsustainable, emphasizing the need for integrating climate change predictions in population management and increase our understanding of how environmental stochasticity translates into population growth rate.

Fencing artificial waterpoints failed to influence density and distribution of red kangaroos (Macropus rufus)

Provision of artificial waterpoints in Australian rangelands has resulted in an increase in the range and density of kangaroos. At high densities, kangaroos can inhibit vegetation regeneration, particularly in some protected areas where harvesting is prohibited. Fencing off waterpoints has been proposed to limit these impacts. Our aim was to determine whether fencing off waterpoints during a drought (when kangaroos would be especially water-limited) would influence the density and distribution of red kangaroos (Macropus rufus). Two waterpoints were fenced within the first 6 months of the 27-month study and a further two waterpoints were kept unfenced as controls in Idalia National Park, western Queensland. We estimated kangaroo densities around waterpoints from walked line-transect counts, and their grazing distribution from dung-pellet counts. Fencing off waterpoints failed to influence either the density or distribution up to 4 km from the waterpoints. Our results indicate that food availability, rather than the location of waterpoints, determines kangaroo distribution. Few areas in the rangelands are beyond kangaroos' convenient reach from permanent waterpoints. Therefore, fencing off waterpoints without explicitly considering the spatial context in relation to other available water sources will fail to achieve vegetation regeneration.

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.