Search

Biodiversity monitoring programmes should be designed with sufficient statistical power to detect population change. Here we evaluated the statistical power of monitoring to detect declines in the occupancy of forest birds on Christmas Island, Australia. We fitted zero-inflated binomial models to 3 years of repeat detection data (2011, 2013 and 2015) to estimate single-visit detection probabilities for four species of concern: the Christmas Island imperial pigeon Ducula whartoni , Christmas Island white-eye Zosterops natalis , Christmas Island thrush Turdus poliocephalus erythropleurus and Christmas Island emerald dove Chalcophaps indica natalis. We combined detection probabilities with maps of occupancy to simulate data collected over the next 10 years for alternative monitoring designs and for different declines in occupancy (10–50%). Specifically, we explored how the number of sites (60, 128, 300, 500), the interval between surveys (1–5 years), the number of repeat visits (2–4 visits) and the location of sites influenced power. Power was high (> 80%) for the imperial pigeon, white-eye and thrush for most scenarios, except for when only 60 sites were surveyed or a 10% decline in occupancy was simulated over 10 years. For the emerald dove, which is the rarest of the four species and has a patchy distribution, power was low in almost all scenarios tested. Prioritizing monitoring towards core habitat for this species only slightly improved power to detect declines. Our study demonstrates how data collected during the early stages of monitoring can be analysed in simulation tools to fine-tune future survey design decisions. [ABSTRACT FROM AUTHOR]

Targeted gene flow is a novel conservation strategy that involves translocating individuals with favourable genes to areas where they will have a conservation benefit. One oft-cited risk of the strategy is the potential for outbreeding depression. Here, we used the northern quoll (Dasyurus hallucatus) as a model to test this possibility for the first time in a field setting. Northern quolls are endangered by the spread of the invasive cane toad (Rhinella marina), which they are fatally poisoned by, if they mistakenly attempt to consume them. There are, however, a small number of quolls that are "toad-smart"—they possess a heritable trait that means they innately do not attack toads. It is this trait we hoped to promote through targeted gene flow. We established a hybrid population (54 toad-smart and toad-naïve northern quolls) and introduced this population onto a small offshore, toad-infested island in 2017. Genetic data suggests an increase in the toad-smart proportion of the genome increasing from 29.4% in the release population to 40.2% in the first island generation (F2). Our data demonstrate successful in situ hybridisation between populations, with viable F2 hybrids and backcrosses observed, and some evidence of heterosis (hybrid vigour) in F1 hybrids. The population experienced significant reductions in size over the two years, however, through a combination of toad-mortality, as well as stochastic processes including fire, a cyclone, predation and ineffective breeding, and so small sample sizes hamper our results. Such establishment problems would not occur were we to attempt targeted gene flow into already established quoll populations, and our observation of successful hybridisation suggests targeted gene flow could be a viable strategy in established quoll populations soon to be impacted by toads. [ABSTRACT FROM AUTHOR]

Large-scale disturbance events are forecast to increase in severity and frequency due to climate change. On-ground surveys are crucial for assessing the immediate impact of disturbances on biodiversity and for informing management responses. However, there are few examples where quantitative tools have guided post-disturbance survey design. In this study, we integrated species distribution modelling and spatial prioritisation to identify taxonomic and spatial gaps in surveys for 92 priority vertebrates 6 months after the 2019–20 wildfires in Australia. We predicted the pre-fire distribution of priority species, mapped locations of post-wildfire surveys that were already underway, and integrated this information with remotely-sensed fire severity maps in the tool, Zonation, to prioritise locations for new surveys across three fire severity classes (unburnt, low severity, high severity). Our results suggest that 6 months after the wildfires, surveys by government agencies had targeted 17 of 20 mammals (85%); 11 of 17 birds (65%); 10 of 17 frogs (59%); 10 of 23 reptiles (43%) and 5 of 17 fish (29%). We developed species distribution models for 63 of these species after collating 120,118 occurrence records from 6 data repositories. By predicting their distribution before the wildfires, we most efficiently identified gaps in survey effort while ensuring representation across species and fire severity classes. Our analysis provided an important 'stocktake' of the response effort to the 2019–20 wildfires in Australia and helped inform the allocation of government-funded wildfire recovery programs. Although we focus on wildfire, our approach could assess gaps in survey effort following any large-scale disturbance. • Post-fire survey effort was inconsistent across taxonomic groups. • There was little national coordination of post-fire surveys. • The representation of surveys could be drastically increased with small amounts of additional effort. • Many species and regions are yet to be surveyed after the 2019–20 megafires. [ABSTRACT FROM AUTHOR]

Effective management of alien species requires detecting populations in the early stages of invasion. Environmental DNA (eDNA) sampling can detect aquatic species at relatively low densities, but few studies have directly compared detection probabilities of eDNA sampling with those of traditional sampling methods. We compare the ability of a traditional sampling technique (bottle trapping) and eDNA to detect a recently established invader, the smooth newt Lissotriton vulgaris vulgaris, at seven field sites in Melbourne, Australia. Over a four-month period, per-trap detection probabilities ranged from 0.01 to 0.26 among sites where L. v. vulgaris was detected, whereas per-sample eDNA estimates were much higher (0.29-1.0). Detection probabilities of both methods varied temporally (across days and months), but temporal variation appeared to be uncorrelated between methods. Only estimates of spatial variation were strongly correlated across the two sampling techniques. Environmental variables (water depth, rainfall, ambient temperature) were not clearly correlated with detection probabilities estimated via trapping, whereas eDNA detection probabilities were negatively correlated with water depth, possibly reflecting higher eDNA concentrations at lower water levels. Our findings demonstrate that eDNA sampling can be an order of magnitude more sensitive than traditional methods, and illustrate that traditional- and eDNA-based surveys can provide independent information on species distributions when occupancy surveys are conducted over short timescales.