Real-time drone derived thermal imagery outperforms traditional survey methods for an arboreal forest mammal

Health Assessments of Koalas after Wildfire: A Temporal Comparison of Rehabilitated and Non-Rescued Resident Individuals

Many koalas (Phascolarctos cinereus) required rehabilitation after the 2019/20 Australian megafires. Little is known about how the post-release health of rehabilitated koalas compares to non-rescued resident koalas. We evaluated health parameters in rehabilitated koalas and resident koalas in burnt and unburnt habitat in southern New South Wales, Australia. Health checks were undertaken within six weeks of fire (rehabilitated group), 5-9 months post-fire and 12-16 months post-fire. Body condition improved significantly over time in rehabilitated koalas, with similar condition between all groups at 12-16 months. Rehabilitated koalas therefore gained body condition at similar rates to koalas who remained and survived in the wild. The prevalence of Chlamydia pecorum was also similar between groups and timepoints, suggesting wildfire and rehabilitation did not exacerbate disease in this population. While there was some variation in measured serum biochemistry and haematology parameters between groups and timepoints, most were within normal reference ranges. Our findings show that koalas were generally healthy at the time of release and when recaptured nine months later. Landscapes in the Monaro region exhibiting a mosaic of burn severity can support koalas, and rehabilitated koala health is not compromised by returning them to burnt habitats 4-6 months post-fire.

Warm beach, warmer turtles: Using drone-mounted thermal infrared sensors to monitor sea turtle nesting activity

For decades sea turtle projects around the world have monitored nesting females using labor-intensive human patrolling techniques. Here we describe the first empirical testing of a drone-mounted thermal infrared sensor for nocturnal sea turtle monitoring; on the Osa peninsula in Costa Rica. Preliminary flights verified that the drone could detect similar sea turtle activities as identified by on-the-ground human patrollers – such as turtles, nests and tracks. Drone observers could even differentiate tracks of different sea turtle species, detect sea turtle hatchlings, other wildlife, and potential poachers. We carried out pilot flights to determine optimal parameters for detection by testing different thermal visualization modes, drone heights, and gimbal angles. Then, over seven nights, we set up a trial to compare the thermal drone and operators’ detections with those observed by traditional patrollers. Our trials showed that thermal drones can record more information than traditional sea turtle monitoring methods. The drone and observer detected 20% more sea turtles or tracks than traditional ground-based patrolling (flights and patrols carried out across the same nights at the same time and beach). In addition, the drone operator detected 39 other animals/predators and three potential poachers that patrollers failed to detect. Although the technology holds great promise in being able to enhance detection rates of nesting turtles and other beach activity, and in helping to keep observers safer, we detail challenges and limiting factors; in drone imagery, current cost barriers, and technological advances that need to be assessed and developed before standardized methodologies can be adopted. We suggest potential ways to overcome these challenges and recommend how further studies can help to optimize thermal drones to enhance sea turtle monitoring efforts worldwide.

Multiyear monitoring of threatened iconic arboreal mammals in a mid‐elevation conservation reserve in eastern Australia

Multiyear investigations of population dynamics are fundamental to threatened species conservation. We used multiseason occupancy based on spotlight surveys to investigate dynamic occupancy of the koala and the greater glider over an 8‐year period that encompassed a severe drought in year 6. We combined our occupancy estimates with literature estimates of density to estimate the population sizes of these species within the focal conservation reserve. Both species showed substantial yearly variation in the probability of detection (koala: 0.13–0.24; greater glider: 0.12–0.36). Detection of the koala did not follow any obvious pattern. Low detection of the greater glider coincided with the drought and two subsequent years. We suggest the low detection reflected a decline in abundance. The probability of occupancy of the koala was estimated to be 0.88 (95% CI: 0.75–1.0) in year 8. Autonomous recording units were also used in year 8, enabling an independent occupancy estimate of 0.80 (0.64–0.90). We found no evidence of a drought‐induced decline in the koala. Habitat variables had a weak influence on koala occupancy probabilities. The probability of occupancy of the greater glider changed little over time, from 0.52 (95% CI: 0.24–0.81) to 0.63 (0.42–0.85) in year 8. Modeling suggested that the probability of colonization was positively influenced by the percentage cover of rainforest. Increased cover of these nonbrowse trees may reflect thermal buffering, site productivity, or soil moisture. We estimate that our study reserve is likely to contain >900 adult koalas and >2400 adult greater gliders. These are among some of the first reserve‐wide estimates for these species. Our study reserve can play an important role in the conservation of both species.

Regulated timber harvesting does not reduce koala density in north-east forests of New South Wales

The compatibility of forestry and koala conservation is a controversial issue. We used a BACIPS design to assess change in koala density after selective harvesting with regulations to protect environmental values. We also assessed additional sites heavily harvested 5-10 years previously, now dominated by young regeneration. We used replicate arrays of acoustic sensors and spatial count modelling of male bellowing to estimate male koala density over 3600 ha. Paired sites in nearby National Parks served as controls. Naïve occupancy was close to 100% before and after harvesting, indicating koalas were widespread across all arrays. Average density was higher than expected for forests in NSW, varying between arrays from 0.03-0.08 males ha^-1. There was no significant effect of selective harvesting on density and little change evident between years. Density 5-10 years after previous heavy harvesting was equivalent to controls, with one harvested array supporting the second highest density in the study. Within arrays, density was similar between areas mapped as selectively harvested or excluded from harvest. Density was also high in young regeneration 5-10 years after heavy harvesting. We conclude that native forestry regulations provided sufficient habitat for koalas to maintain their density, both immediately after selective harvesting and 5-10 years after heavy harvesting.

Drone thermal imaging technology provides a cost-effective tool for landscape-scale monitoring of a cryptic forest-dwelling species across all population densities

Abstract Context Drones, or remotely piloted aircraft systems, equipped with thermal imaging technology (RPAS thermal imaging) have recently emerged as a powerful monitoring tool for koala populations. Before wide uptake of novel technologies by government, conservation practitioners and researchers, evidence of greater efficiency and cost-effectiveness than with other available methods is required. Aims We aimed to provide the first comprehensive analysis of the cost-effectiveness of RPAS thermal imaging for koala detection against two field-based methods, systematic spotlighting (Spotlight) and the refined diurnal radial search component of the spot-assessment technique (SAT). Methods We conducted various economic comparisons, particularly comparative cost-effectiveness of RPAS thermal imaging, Spotlight and SAT for repeat surveys of a low-density koala population. We compared methods on cost-effectiveness as well as long-term costs by using accumulating cost models. We also compared detection costs across population density using a predictive cost model. Key results Despite substantial hardware, training and licensing costs at the outset (>A$49 900), RPAS thermal imaging surveys were cost-effective, detecting the highest number of koalas per dollar spent. Modelling also suggested that RPAS thermal imaging requires the lowest survey effort to detect koalas within the range of publicly available koala population densities (~0.006–18 koalas ha−1) and would provide long-term cost reductions across longitudinal monitoring programs. RPAS thermal imaging would also require the lowest average survey effort costs at a landscape scale (A$3.84 ha−1), providing a cost-effective tool across large spatial areas. Conclusions Our analyses demonstrated drone thermal imaging technology as a cost-effective tool for conservation practitioners monitoring koala populations. Our analyses may also form the basis of decision-making tools to estimate survey effort or total program costs across any koala population density. Implications Our novel approach offers a means to perform various economic comparisons of available survey techniques and guide investment decisions towards developing standardised koala monitoring approaches. Our results may assist stakeholders and policymakers to confidently invest in RPAS thermal imaging technology and achieve optimal conservation outcomes for koala populations, with standardised data collection delivered through evidence-based and cost-effective monitoring programs.