The power of monitoring: optimizing survey designs to detect occupancy changes in a rare amphibian population

www.nature.com/scientificreports OPEN Received: 2 August 2017 Accepted: 10 November 2017 Published: xx xx xxxx The power of monitoring: optimizing survey designs to detect occupancy changes in a rare amphibian population Izabela M. Barata1, Richard A. Griffiths1 & Martin S. Ridout2 Biodiversity conservation requires reliable species assessments and rigorously designed surveys. However, determining the survey effort required to reliably detect population change can be challenging for rare, cryptic and elusive species. We used a tropical bromeliad-dwelling frog as a model system to explore a cost-effective sampling design that optimizes the chances of detecting a population decline. Relatively few sampling visits were needed to estimate occupancy and detectability with good precision, and to detect a 30% change in occupancy with 80% power. Detectability was influenced by observer expertise, which therefore also had an effect on the sampling design – less experienced observers require more sampling visits to detect the species. Even when the sampling design provides precise parameter estimates, only moderate to large changes in occupancy will be detected with reliable power. Detecting a population change of 15% or less requires a large number of sites to be surveyed, which might be unachievable for range-restricted species occurring at relatively few sites. Unless there is high initial occupancy, rare and cryptic species will be particularly challenging when it comes to detecting small population changes. This may be a particular issue for long-term monitoring of amphibians which often display low detectability and wide natural fluctuations. The global biodiversity crisis has driven the development of increasingly sophisticated databases, such as the Living Planet Index1 and the IUCN Red List for Threatened Species2, which require reliable baseline information on species, habitats and population trends. Although monitoring data are of increasing value to conservation managers, population and status assessments are currently limited by the lack of data3, resulting in poor evidence for conservation practitioners. Monitoring programmes must inform decision-making through the application of reliable survey design and statistical analysis – otherwise they will be an ineffective use of resources. Conservationists must therefore develop projects with clear objectives4 and provide appropriate sampling designs5,6 with sufficient statistical power to reliably describe population trends7–9. Nonetheless, issues of sampling design are widely ignored and remain a challenge for species monitoring and modelling10. Occupancy modelling is increasingly being applied in monitoring programmes to assess the determinants of population changes for different taxonomic groups11,12. Occupancy models estimate site occupancy and detection probabilities in an unbiased way13,14 and occupancy may also be used as a proxy for abundance6. Although sampling designs for occupancy models have been explored theoretically15–18, few studies have used empirical data to investigate the survey effort required for the reliable inference of absence19–21 or to explore the precision and accuracy of occupancy estimates22–24. In the context of occupancy monitoring, studies have also considered statistical power using empirical data8,24–29. Statistical power considers the number of samples, variability in the data and the expected rate of change30 to evaluate the probability of detecting a change in the estimated parameter when that change actually occurs (e.g., increase or decrease in occupancy). Power analysis has long been recognized as a useful tool for study design, especially for the early stages of monitoring planning4,7,18,31. Evaluating changes in populations at risk is particularly important in the case of amphibians, which are currently more threatened than birds or mammals and show accelerating rates of extinction32. However, amphibians 1 Durrell Institute of Conservation and Ecology, School of Anthropology and Conservation, University of Kent, Canterbury, Kent, CT2 7NR, UK. 2National Centre for Statistical Ecology, School of Mathematics, Statistics and Actuarial Science, University of Kent, Canterbury, Kent, CT2 7NF, UK. Correspondence and requests for materials should be addressed to I.M.B. (email: ) SCIEntIfIC REPOrTS | 7: 16491 | DOI:10.1038/s41598-017-16534-8 1 www.nature.com/scientificreports/ are often rare, cryptic or elusive and can display considerable natural population fluctuations33, which can make long-term monitoring difficult. Significant advances in amphibian monitoring have been developed, such as the improvement of novel research methods (e.g., environmental DNA34), application of advanced data analysis (e.g., occupancy models12) and evaluation of national monitoring schemes (e.g., UK National Amphibian and Reptile Scheme20). Nonetheless, these developments are often limited by the availability of funding, which contributes further to difficulties in assessing population changes. In this study we used patchily distributed bromeliads that are inhabited by a rare and threatened amphibian species, as a model system to assess sampling design and the statistical power associated with detecting population changes. The endemic frog Crossodactylodes itambe35,36 is only found at the Itambe summit, southeastern Brazil, living exclusively inside bromeliads on a high elevation rocky outcrop and with an extent of occurrence of less than ca. 0.5 km2. Crossodactylodes itambe is included in the Brazilian Conservation Action Plan for amphibians at the Espinhaço Mountain Range37, which recommends the implementation of long-term monitoring studies for threatened species that are rare and elusive. Our aim was to design a monitoring protocol that improves the chance of detecting a population change, which could also allow better allocation of survey effort and financial resources. We therefore addressed three questions fundamental to any monitoring programme: (1) Is the currently used sampling design providing precise estimates of occupancy and detectability? (2) Is this sampling design providing sufficient power to detect changes in occupancy over time? (3) How can we improve statistical power to detect small changes in populations? The bromeliad-frog system therefore provides an opportunity to explore issues of sampling and statistical power that would prove unwieldy on a larger landscape scale and we present a rigorous assessment that could benefit future monitoring programmes in their earlier stages. Methods Study system and sampling design. The Itambe summit is the highest point of the Espinhaço Mountain Range at 2062 m above sea level (a.s.l.) and is located in South-eastern Brazil, in Minas Gerais state. The area is characterized by open field habitats with vegetation growing in humid rocky outcrops. Crossodactylodes itambe is restricted to 1800 m a.s.l. and occupies a single species of bromelia (...truncated)