Biology subjects

Boersch-Supan, P. H.

Publications and source records attributed to Boersch-Supan, P. H..

4 recordsLinked to original sources

bioRxiv2021

Integrating structured and unstructured citizen science data to improve wildlife population monitoring

Accurate and robust population trend assessments are key to successful biodiversity conservation. Citizen science surveys have provided good evidence of biodiversity declines whilst engaging people with them. Citizen scientists are also collecting opportunistic biodiversity records at unprecedented scales, vastly outnumbering records gathered through structured surveys. Opportunistic records exhibit spatio-temporal biases and heterogeneity in observer effort and skill, but their quantity offers a rich source of information. Data integration, the combination of multiple information sources in a common analytical framework, can potentially improve inferences about populations compared to analysing either in isolation. We combine count data from a structured citizen science survey and detection-nondetection data from an opportunistic citizen science programme. Population trends were modelled using dynamic N-mixture models to integrate both data sources. We applied this approach to two different inferential challenges arising from sparse data: (i) the estimation of population trends for an area smaller than a structured survey stratum, and (ii) the estimation of national population trends for a rare but widespread species. In both cases, data integration yielded population trajectories similar to those estimated from structured survey data alone but had higher precision when the density of opportunistic records was high. In some cases this allowed inferences about population trends where indices derived from single data sources were too uncertain to assess change. However, there were differences in the trend magnitude between the integrated and the standard survey model. We show that data integration of large-scale structured and unstructured data is feasible and offers potential to improve national and regional wildlife trend estimates, although a need to independently validate trends remains. Smaller gains are achieved in areas where uptake of opportunistic recording is low. The integration of opportunistic records from volunteer-selected locations alone may therefore not adequately address monitoring gaps for management and policy applications. To achieve the latter, scheme organisers should consider providing incentives for achieving representative coverage of target areas in both structured and unstructured recording schemes.

ecology↗

bioRxiv2018

Environmental drivers of ranavirus in free living amphibians in constructed ponds.

Amphibian ranaviruses occur globally, but we are only beginning to understand mechanisms for emergence. Ranaviruses are aquatic pathogens which can cause > 90% mortality in larvae of many aquatic-breeding amphibians, making them important focal host taxa. Host susceptibilities and virulence of ranaviruses have been studied extensively in controlled laboratory settings, but research is needed to identify drivers of infection in natural environments. Constructed ponds, essential components of wetland restoration, have been associated with higher ranavirus prevalence than natural ponds, posing a conundrum for conservation efforts, and emphasizing the need to understand potential drivers. In this study, we analyzed four years of Frog virus 3 prevalence and associated environmental parameters in populations of wood frogs (Lithobates sylvaticus) and green frogs (Lithobates clamitans) in a constructed pond system. High prevalence was best predicted by low temperature, high host density, low zooplankton concentrations, and Gosner stages approaching metamorphosis. This study identified important variables to measure in assessments of ranaviral infection risk in newly constructed ponds, including effects of zooplankton, which have not been previously quantified in natural settings. Examining factors mediating diseases in natural environments, particularly in managed conservation settings, is important to both validate laboratory findings in situ, and to inform future conservation planning, particularly in the context of adaptive management.

ecology↗

bioRxiv2018

A tutorial on Bayesian parameter inference for dynamic energy budget models

Mechanistic representations of individual life-history trajectories are powerful tools for the prediction of organismal growth, reproduction and survival under novel environmental conditions. Dynamic energy budget (DEB) theory provides compact models to describe the acquisition and allocation of energy by organisms over their full life cycle. However, estimating DEB model parameters, and their associated uncertainties and covariances, is not trivial. Bayesian inference provides a coherent way to estimate parameter uncertainty, and propagate it through the model, while also making use of prior information to constrain the parameter space. We outline a Bayesian inference approach for energy budget models and provide two case studies - based on a simplified DEBkiss model, and the standard DEB model - detailing the implementation of such inference procedures using the open-source software package deBInfer. We demonstrate how DEB and DEBkiss parameters can be estimated in a Bayesian framework, but our results also highlight the difficulty of identifying DEB model parameters which serves as a reminder that fitting these models requires statistical caution.

physiology↗

bioRxiv2017

Quantifying Seasonal and Diel Variation in Anopheline and Culex Human Biting Rates in Southern Ecuador

BackgroundQuantifying mosquito biting rates for specific locations enables estimation of mosquito-borne disease risk, and can inform intervention efforts. Measuring biting itself is fraught with ethical concerns, so the landing rate of mosquitoes on humans is often used as a proxy measure. Southern coastal Ecuador was historically endemic for malaria (P. falciparum and P. vivax), although successful control efforts in the 2000s eliminated autochthonous transmission (since 2011). This study presents an analysis of data collected during the elimination period.\n\nMethodsWe examined human landing catch (HLC) data for three mosquito taxa: 2 malaria vectors, Anopheles albimanus and Anopheles punctimacula, and grouped Culex spp. These data were collected by the National Vector Control Service of the Ministry of Health over a 5-year time span (2007 - 2012) in five cities in southern coastal Ecuador, at multiple households, in all months of the year, during dusk-dawn (18:00-6:00) hours, often at both indoor and outdoor locations. Hurdle models were used to determine if biting activity was fundamentally different for the three taxa, and to identify spatial and temporal factors influencing bite rate. Due to the many different approaches to studying and quantifying bite rates in the literature, we also created a glossary of terms, to facilitate comparative studies in the future.\n\nResultsBiting trends varied significantly with species and time. All taxa exhibited exophagic feeding behavior, and outdoor locations increased both the odds and incidence of bites across taxa. An. albimanus was most frequently observed biting, with an average of 4.7 bites per hour. The highest and lowest respective months for significant biting activity were March and July for An. albimanus, July and August for An. punctimacula, and February and July for Culex spp.\n\nConclusionsFine-scale spatial and temporal differences exist in biting patterns among mosquito taxa in southern coastal Ecuador. This analysis provides detailed information for targeting vector control and household level behavioral interventions. These data were collected as part of routine vector surveillance conducted by the Ministry of Health, but such data have not been collected since. Reinstating such surveillance measures would provide important information to aid in preventing malaria re-emergence.

epidemiology↗