Estimating population size of a nocturnal burrow-nesting seabird using acoustic monitoring and habitat mapping. Nature Conservation 7: 1-13. doi: 10.3897/natureconservation.7.6890 Abstract Population size assessments for nocturnal burrow-nesting seabirds are logistically challenging because these species are active in colonies only during darkness and often nest on remote islands where manual inspections of breeding burrows are not feasible. Many seabird species are highly vocal, and recent technological innovations now make it possible to record and quantify vocal activity in seabird colonies. Here we test the hypothesis that remotely recorded vocal activity in Cory's shearwater (Calonectris borealis) breeding colonies in the North Atlantic increases with nest density, and combined this relationship with cliff habitat mapping to estimate the population size of Cory's shearwaters on the island of Corvo (Azores). We deployed acoustic recording devices in 9 Cory's shearwater colonies of known size to establish a relationship between vocal activity and local nest density (slope = 1.07, R 2 = 0.86, p < 0.001). We used this relationship to predict the nest density in various cliff habitat types and produced a habitat map of breeding cliffs to extrapolate nest density around the island of Corvo. The mean predicted nest density on Corvo ranged from 6.6 (2.1-16.2) to 27.8 (19.5-36.4) nests/ha. Extrapolation of habitat-specific nest densities across the cliff area of Corvo resulted in an estimate of 6326 Cory's shearwater nests (95% confidence interval: 524). This population size estimate is similar to previous assessments, but is too imprecise to detect moderate changes in population size over time. While estimating absolute population size from acoustic recordings may not be sufficiently precise, the strong positive relationship that we found between local nest density and recorded calling rate indicates that passive acoustic monitoring may be useful to document relative changes in seabird populations over time. RESEARCH ARTICLE Launched to accelerate biodiversity conservation A peer-reviewed open-access journalSteffen Oppel et al. / Nature Conservation 7: 1-13 (2014) 2

Although wildlife conservation actions have increased globally in number and complexity, the lack of scalable, cost-effective monitoring methods limits adaptive management and the evaluation of conservation efficacy. Automated sensors and computer-aided analyses provide a scalable and increasingly cost-effective tool for conservation monitoring. A key assumption of automated acoustic monitoring of birds is that measures of acoustic activity at colony sites are correlated with the relative abundance of nesting birds. We tested this assumption for nesting Forster's terns (Sterna forsteri) in San Francisco Bay for 2 breeding seasons. Sensors recorded ambient sound at 7 colonies that had 15-111 nests in 2009 and 2010. Colonies were spaced at least 250 m apart and ranged from 36 to 2,571 m(2) . We used spectrogram cross-correlation to automate the detection of tern calls from recordings. We calculated mean seasonal call rate and compared it with mean active nest count at each colony. Acoustic activity explained 71% of the variation in nest abundance between breeding sites and 88% of the change in colony size between years. These results validate a primary assumption of acoustic indices; that is, for terns, acoustic activity is correlated to relative abundance, a fundamental step toward designing rigorous and scalable acoustic monitoring programs to measure the effectiveness of conservation actions for colonial birds and other acoustically active wildlife.

Marine megafauna are difficult to observe and count because many species travel widely and spend large amounts of time submerged. As such, management programmes seeking to conserve these species are often hampered by limited information about population levels. Unoccupied aircraft systems (UAS, aka drones) provide a potentially useful technique for assessing marine animal populations, but a central challenge lies in analysing the vast amounts of data generated in the images or video acquired during each flight. Neural networks are emerging as a powerful tool for automating object detection across data domains and can be applied to UAS imagery to generate new population‐level insights. To explore the utility of these emerging technologies in a challenging field setting, we used neural networks to enumerate olive ridley turtles Lepidochelys olivacea in drone images acquired during a mass‐nesting event on the coast of Ostional, Costa Rica. Results revealed substantial promise for this approach; specifically, our model detected 8% more turtles than manual counts while effectively reducing the manual validation burden from 2,971,554 to 44,822 image windows. Our detection pipeline was trained on a relatively small set of turtle examples (N = 944), implying that this method can be easily bootstrapped for other applications, and is practical with real‐world UAS datasets. Our findings highlight the feasibility of combining UAS and neural networks to estimate population levels of diverse marine animals and suggest that the automation inherent in these techniques will soon permit monitoring over spatial and temporal scales that would previously have been impractical.

No abstract

Rat eradication has become a common conservation intervention in island ecosystems and its effectiveness in protecting native vertebrates is increasingly well documented. Yet, the impacts of rat eradication on plant communities remain poorly understood. Here we compare native and non-native tree and palm seedling abundance before and after eradication of invasive rats (Rattus rattus) from Palmyra Atoll, Line Islands, Central Pacific Ocean. Overall, seedling recruitment increased for five of the six native trees species examined. While pre-eradication monitoring found no seedlings of Pisonia grandis, a dominant tree species that is important throughout the Pacific region, post-eradication monitoring documented a notable recruitment event immediately following eradication, with up to 688 individual P. grandis seedlings per 100m2 recorded one month post-eradication. Two other locally rare native trees with no observed recruitment in pre-eradication surveys had recruitment post-rat eradication. However, we also found, by five years post-eradication, a 13-fold increase in recruitment of the naturalized and range-expanding coconut palm Cocos nucifera. Our results emphasize the strong effects that a rat eradication can have on tree recruitment with expected long-term effects on canopy composition. Rat eradication released non-native C. nucifera, likely with long-term implications for community composition, potentially necessitating future management interventions. Eradication, nevertheless, greatly benefitted recruitment of native tree species. If this pattern persists over time, we expect long-term benefits for flora and fauna dependent on these native species.