The Utility of the Koala Scat: A Scoping Review

The use of samples or scats to provide important ecological, genetic, disease and physiology details on free-range populations is gaining popularity as an alternative non-invasive methodology. Koala populations in SE Queensland and NSW have recently been listed as endangered and continue to face anthropomorphic and stochastic environmental impacts that could potentially lead to their extinction. This scoping review examines the current and potential utility of the koala scat to contribute data relevant to the assessment of koala conservation status and decision making. Although we demonstrate that there is great potential for this methodology in providing details for both individual wild animal and population biology (distribution, abundance, sex ratio, immigration/emigration, genetic diversity, evolutionary significant unit, disease epidemiology, nutrition, reproductive status and stress physiology), the calibre of this information is likely to be a function of the quality of the scat that is sampled.

Comparison of three methods of estimating the population size of an arboreal mammal in a fragmented rural landscape

Abstract Context Precise and accurate estimates of animal numbers are often essential for population and epidemiological models, as well as for guidance for population management and conservation. This is particularly true for threatened species in landscapes facing multiple threats. Estimates can be derived by different methods, but the question remains as to whether these estimates are comparable. Aims We compared three methods to estimate population numbers, namely, distance sampling, mark–recapture analysis, and home-range overlap analysis, for a population of the iconic threatened species, the koala (Phascolarctos cinereus). This population occupies a heavily fragmented forest and woodland habitat on the Liverpool Plains, north-western New South Wales, Australia, on a mosaic of agricultural and mining lands. Key resultsAll three methods produced similar estimates, with overlapping confidence intervals. Distance sampling required less expertise and time and had less impact on animals, but also had less precision; however, future estimates using the method could be improved by increasing both the number and expertise of the observers. ConclusionsWhen less intrusive methods are preferred, or fewer specialised practitioners are available, we recommend distance sampling to obtain reliable estimates of koala numbers. Although its precision is lower with a low number of sightings, it does produce estimates of numbers similar to those from the other methods. However, combining multiple methods can be useful when other material (genetic, health and demographic) is also needed, or when decisions based on estimates are for high-profile threatened species requiring greater confidence. We recommend that all estimates of population numbers, and their precision or variation, be recorded and reported so that future studies can use them as prior information, increasing the precision of future surveys through Bayesian analyses.

Using virtual reality and thermal imagery to improve statistical modelling of vulnerable and protected species

Biodiversity loss and sparse observational data mean that critical conservation decisions may be based on little to no information. Emerging technologies, such as airborne thermal imaging and virtual reality, may facilitate species monitoring and improve predictions of species distribution. Here we combined these two technologies to predict the distribution of koalas, specialized arboreal foliovores facing population declines in many parts of eastern Australia. For a study area in southeast Australia, we complemented ground-survey records with presence and absence observations from thermal-imagery obtained using Remotely-Piloted Aircraft Systems. These field observations were further complemented with information elicited from koala experts, who were immersed in 360-degree images of the study area. The experts were asked to state the probability of habitat suitability and koala presence at the sites they viewed and to assign each probability a confidence rating. We fit logistic regression models to the ground survey data and the ground plus thermal-imagery survey data and a Beta regression model to the expert elicitation data. We then combined parameter estimates from the expert-elicitation model with those from each of the survey models to predict koala presence and absence in the study area. The model that combined the ground, thermal-imagery and expert-elicitation data substantially reduced the uncertainty around parameter estimates and increased the accuracy of classifications (koala presence vs absence), relative to the model based on ground-survey data alone. Our findings suggest that data elicited from experts using virtual reality technology can be combined with data from other emerging technologies, such as airborne thermal-imagery, using traditional statistical models, to increase the information available for species distribution modelling and the conservation of vulnerable and protected species.

The development of an improved scat survey method for koalas (Phascolarctos cinereus)

Koala scat surveys are important tools for determining koala presence and distribution in large forested areas where it is impractical to conduct direct observation surveys. However, current scat survey methods are problematic due to lack of either accuracy or feasibility, i.e. they are either biased or very time-consuming in the field. This study aimed to establish a new koala scat survey method with improved accuracy compared with existing methods, and practical in the field. We developed a new Balanced Koala Scat Survey method (BKSS), and evaluated it in the field by analysing scat detectability variations and comparing it with a current survey method, the Spot Assessment Technique (SAT), to determine scat searching accuracy. The results revealed that current methods were biased by assigning consistent searching effort for all trees, because effective searching time to detect the first scat was significantly affected by Koala Activity Level (KAL – the proportion of trees found with scats among all 30 trees in a survey site). Compared with BKSS, SAT tended to yield more false negative outcomes; SAT may miss up to 46% of trees with scats when KAL was low. The application of BKSS is expected to greatly enhance the reliability of koala scat surveys in determining koala distribution and thus improve their conservation management.

Fine-scale changes in spatial habitat use by a low-density koala population in an isolated periurban forest remnant

Koala (Phascolarctos cinereus) populations in south-east Queensland are in decline. Although various studies have looked at broad-scale tree preference and habitat quality, there has been little attempt to quantify fine-scale activity shifts from one year to the next or examination of activity at the mesoscale. This study quantified koala activity levels in a 909-ha forest patch at Karawatha Forest Park, in south Brisbane. The Spot Assessment Technique was used to quantify activity and tree selection on 33 long-term monitoring plots in 2009 and 2010. In total, 843 trees were searched and koala pellets were found underneath 34 and 47 trees in 2009 and 2010, respectively. A higher proportion of pellets was found underneath Eucalyptus tindaliae and E. fibrosa and there was weak selection for larger trees. A low occurrence of revisits and a minor shift in activity distribution from 2009 to 2010 indicate that the koala population exists at a low density. Rapid declines in koala populations are occurring in primary habitats. Hence, stable low-density koala populations are important for maintaining genetic diversity and connectivity in fragmented urban landscapes.

Accuracy and efficiency of detection dogs: a powerful new tool for koala conservation and management

Accurate data on presence/absence and spatial distribution for fauna species is key to their conservation. Collecting such data, however, can be time consuming, laborious and costly, in particular for fauna species characterised by low densities, large home ranges, cryptic or elusive behaviour. For such species, including koalas (Phascolarctos cinereus), indicators of species presence can be a useful shortcut: faecal pellets (scats), for instance, are widely used. Scat surveys are not without their difficulties and often contain a high false negative rate. We used experimental and field-based trials to investigate the accuracy and efficiency of the first dog specifically trained for koala scats. The detection dog consistently out-performed human-only teams. Off-leash, the dog detection rate was 100%. The dog was also 19 times more efficient than current scat survey methods and 153% more accurate (the dog found koala scats where the human-only team did not). This clearly demonstrates that the use of detection dogs decreases false negatives and survey time, thus allowing for a significant improvement in the quality and quantity of data collection. Given these unequivocal results, we argue that to improve koala conservation, detection dog surveys for koala scats could in the future replace human-only teams.

Koala habitat use and population density: using field data to test the assumptions of ecological models

In principle, conservation planning relies on long-term data; in reality, conservation decisions are apt to be based upon limited data and short-range goals. For the koala (Phascolarctos cinereus), frequently reliance is made on the assumption that indirect signs can be used to indicate behavioural preferences, such as diet choice. We examined the relationship between the use of trees by koalas and the presence of scats beneath those trees. Tree use was associated with scat presence on 49% of occasions when koalas were radio-tracked in both central Queensland (n = 10 koalas) and south-east Queensland (n = 5 koalas), increasing to 77% of occasions when trees were rechecked the following day. Koala densities were correlated with scat abundance at sites with koala density between ~0.2 and 0.6 koalas per hectare. Our results confirm that scat searches are imprecise indicators of tree use by koalas, but demonstrate that these searches can be used, with caveats, to estimate koala population densities. We discuss how errors in estimating or applying predictive model parameters can bias estimates of occupancy and show how a failure to validate adequately the assumptions used in modelling and mapping can undermine the power of the products to direct rational conservation and management efforts.