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Abstract Quantifying the cost‐effectiveness of alternative sampling methods is crucial for efficient biodiversity monitoring and detection of population trends. In this study, we compared the cost‐effectiveness of three novel sampling methods for detecting changes in koala (Phascolarctos cinereus) occupancy: thermal drones, passive acoustic recorders and camera trapping. Specifically, we fitted single‐season occupancy‐detection models to data recorded from 46 sites in eight bioregions of New South Wales, Australia, between 2018 and 2022. We explored the effect of weather variables on daily detection probability for each method and, using these estimates, calculated the statistical power to detect 30%, 50% and 80% declines in koala occupancy. We calculated power for different combinations of sites (1–200) and repeat surveys (2–40) and developed a cost model that found the cheapest survey design that achieved 80% power to detect change. On average, detectability of koalas was highest with one 24‐h period of acoustic surveys (0.32, 95% CI's: 0.26, 0.39) compared to a 25‐ha flight of drone surveys (0.28, 95% 0.15, 0.48) or a 24‐h period of camera trapping consisting of six cameras (0.019, 95% CI's: 0.014, 0.025). We found a negative quadratic relationship between detection probability and air temperature for all three methods. Our power and cost analysis suggested that 148 sites surveyed with acoustic recorders deployed for 14 days would be the cheapest method to sufficiently detect a 30% decline in occupancy with 80% power. We recommend passive acoustic recorders as the most efficient sampling method for monitoring koala occupancy compared to cameras or drones. Further comparative studies are needed to compare the relative effectiveness of these methods and others when the monitoring objective is to detect change in koala abundance over time.

Abstract Offsetting policies have increased worldwide, utilizing a range of biodiversity metrics to compensate for development impacts. We conducted a global analysis of offset legislation by reviewing policies from 108 countries, which have voluntary offsets, or which require offsets by law. We sought to understand how well biodiversity metrics and offset currencies are documented in current policies. Where biodiversity metrics are documented we aimed to understand how metrics were scored, combined, and multiplied to create offset currencies. We found only 22 jurisdictions (from 14 countries) had guidelines documenting how biodiversity should be assessed during offsetting, representing a significant gap in the guidance available for offsets. Of the 22 guidelines, 14 (63%) documented use of aggregated currencies, eight (23%) did not aggregate biodiversity metrics into a single currency, and three (17%) did not specify either approach. Habitat type and condition, as well as area, were widely recommended across policies (>50%). Where species‐level metrics were considered, guidelines generally focused on habitat distributions rather than abundance or population metrics. The lack of consistent and clear guidance about how biodiversity should be measured in offsets reduces our ability to determine the effectiveness of offsets in compensating for development impacts long term.

In the summer of 2019–2020, southern Australia experienced the largest fires on record, detrimentally impacting the habitat of native species, many of which were already threatened by past and current anthropogenic land use. A large-scale restoration effort to improve degraded species habitat would provide fire-affected species with the chance to recover and persist in burnt and unburnt habitat. To facilitate this, decision-makers require information on priority species needs for restoration intervention, the suite of potential restoration interventions, and the priority locations for applying these interventions. We prioritize actions in areas where restoration would most likely provide cost-effective benefits to priority species (defined by each species proportion of habitat burned, threat status, and vulnerability to fires), by integrating current and future species habitat suitability maps with spatially modelled costs of restoration interventions such as replanting, removing invasive species, and implementing ecologically appropriate fire management. We show that restoring the top ∼69% (112 million hectares) of the study region (current and future distributions of priority species) accounts for, on average, 95% of current and future habitat for every priority species and costs ∼AUD$73 billion yr ^−1 (AUD$650 hectare ^−1 yr ^−1 ) annualized over 30 years. This effort would include restoration actions over 6 million hectares of fire-impacted habitat, costing ∼AUD$8.8 billion/year. Large scale restoration efforts are often costly but can have significant societal co-benefits beyond biodiversity conservation. We also show that up to 291 MtCO2 (∼150 Mt DM) of carbon could be sequestered by restoration efforts, resulting in approximately AUD$253 million yr ^−1 in carbon market revenue if all carbon was remunerated. Our approach highlights the scale, costs, and benefits of targeted restoration activities both inside and outside of the immediate bushfire footprint over vast areas of different land tenures.