School of BioSciences - Research Publications

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    Defining and evaluating predictions of joint species distribution models
    Wilkinson, DP ; Golding, N ; Guillera-Arroita, G ; Tingley, R ; McCarthy, MA ; Freckleton, R (WILEY, 2021-03)
    Abstract Joint species distribution models (JSDMs) simultaneously model the distributions of multiple species, while accounting for residual co‐occurrence patterns. Despite increasing adoption of JSDMs in the literature, the question of how to define and evaluate JSDM predictions has only begun to be explored. We define four different JSDM prediction types that correspond to different aspects of species distribution and community assemblage processes. Marginal predictions are environment‐only predictions akin to predictions from single‐species models; joint predictions simultaneously predict entire community assemblages; and conditional marginal and conditional joint predictions are made at the species or assemblage level, conditional on the known occurrence state of one or more species at a site. We define five different classes of metrics that can be used to evaluate these types of predictions: threshold‐dependent, threshold‐independent, community dissimilarity, species richness and likelihood metrics. We illustrate different prediction types and evaluation metrics using a case study in which we fit a JSDM to a frog occurrence dataset collected in Melbourne, Australia. Joint species distribution models present opportunities to investigate the facets of species distribution and community assemblage processes that are not possible to explore with single‐species models. We show that there are a variety of different metrics available to evaluate JSDM predictions, and that choice of prediction type and evaluation metric should closely match the questions being investigated.
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    Data Integration for Large-Scale Models of Species Distributions
    Isaac, NJB ; Jarzyna, MA ; Keil, P ; Dambly, LI ; Boersch-Supan, PH ; Browning, E ; Freeman, SN ; Golding, N ; Guillera-Arroita, G ; Henrys, PA ; Jarvis, S ; Lahoz-Monfort, J ; Pagel, J ; Pescott, OL ; Schmucki, R ; Simmonds, EG ; O'Hara, RB (ELSEVIER SCIENCE LONDON, 2020-01)
    With the expansion in the quantity and types of biodiversity data being collected, there is a need to find ways to combine these different sources to provide cohesive summaries of species' potential and realized distributions in space and time. Recently, model-based data integration has emerged as a means to achieve this by combining datasets in ways that retain the strengths of each. We describe a flexible approach to data integration using point process models, which provide a convenient way to translate across ecological currencies. We highlight recent examples of large-scale ecological models based on data integration and outline the conceptual and technical challenges and opportunities that arise.
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    steps: Software for spatially and temporally explicit population simulations
    Visintin, C ; Briscoe, NJ ; Woolley, SNC ; Lentini, PE ; Tingley, R ; Wintle, BA ; Golding, N ; Graham, L (WILEY, 2020-04)
    Abstract Species population dynamics are driven by spatial and temporal changes in the environment, anthropogenic activities and conservation management actions. Understanding how populations will change in response to these drivers is fundamental to a wide range of ecological applications, but there are few open‐source software options accessible to researchers and managers that allow them to predict these changes in a flexible and transparent way. We introduce an open‐source, multi‐platform r package, steps, that models spatial changes in species populations as a function of drivers of distribution and abundance, such as climate, disturbance, landscape dynamics and species ecological and physiological requirements. To illustrate the functionality of steps, we model the population dynamics of the greater glider Petauroides volans, an arboreal Australian mammal. We demonstrate how steps can be used to simulate population responses of the glider to forest dynamics and management with the types of data commonly used in ecological analyses. steps expands on the features found in existing software packages, can easily incorporate a range of spatial layers (e.g. habitat suitability, vegetation dynamics and disturbances), facilitates integrated and transparent analyses within a single platform and produces interpretable outputs of changes in species' populations through space and time. Further, steps offers both ready‐to‐use, built‐in functionality, as well as the ability for advanced users to define their own modules for custom analyses. Thus, we anticipate that steps will be of significant value to environment and wildlife managers and researchers from a broad range of disciplines.
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    Reconstructing the early global dynamics of under-ascertained COVID-19 cases and infections
    Russell, T ; Russell, T ; Golding, N ; Hellewell, J ; Abbott, S ; Wright, L ; Pearson, C ; Pearson, C ; Zandvoort, KV ; Jarvis, C ; Gibbs, H ; Liu, Y ; Eggo, R ; Edmunds, J ; Kucharski, A ( 2020)

    Background

    Asymptomatic or subclinical SARS-CoV-2 infections are often unreported, which means that confirmed case counts may not accurately reflect underlying epidemic dynamics. Understanding the level of ascertainment (the ratio of confirmed symptomatic cases to the true number of symptomatic individuals) and undetected epidemic progression is crucial to informing COVID-19 response planning, including the introduction and relaxation of control measures. Estimating case ascertainment over time allows for accurate estimates of specific outcomes such as seroprevalence, which is essential for planning control measures.

    Methods

    Using reported data on COVID-19 cases and fatalities globally, we estimated the proportion of symptomatic cases (i.e. any person with any of fever >= 37.5°C, cough, shortness of breath, sudden onset of anosmia, ageusia or dysgeusia illness) that were reported in 210 countries and territories, given those countries had experienced more than ten deaths. We used published estimates of the baseline case fatality ratio (CFR), which was adjusted for delays and under-ascertainment, then calculated the ratio of this baseline CFR to an estimated local delay-adjusted CFR to estimate the level of under-ascertainment in a particular location. We then fit a Bayesian Gaussian process model to estimate the temporal pattern of under-ascertainment.

    Results

    Based on reported cases and deaths, we estimated that, during March 2020, the median percentage of symptomatic cases detected across the 84 countries which experienced more than ten deaths ranged from 2.4% (Bangladesh) to 100% (Chile). Across the ten countries with the highest number of total confirmed cases as of 6th July 2020, we estimated that the peak number of symptomatic cases ranged from 1.4 times (Chile) to 18 times (France) larger than reported. Comparing our model with national and regional seroprevalence data where available, we find that our estimates are consistent with observed values. Finally, we estimated seroprevalence for each country. As of the 7th June, our seroprevalence estimates range from 0% (many countries) to 13% (95% CrI: 5.6% – 24%) (Belgium).

    Conclusions

    We found substantial under-ascertainment of symptomatic cases, particularly at the peak of the first wave of the SARS-CoV-2 pandemic, in many countries. Reported case counts will therefore likely underestimate the rate of outbreak growth initially and underestimate the decline in the later stages of an epidemic. Although there was considerable under-reporting in many locations, our estimates were consistent with emerging serological data, suggesting that the proportion of each country’s population infected with SARS-CoV-2 worldwide is generally low.

    Funding

    Wellcome Trust, Bill & Melinda Gates Foundation, DFID, NIHR, GCRF, ARC.
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    Factors influencing the residency of bettongs using one-way gates to exit a fenced reserve
    Moyses, J ; Hradsky, B ; Tuft, K ; Moseby, K ; Golding, N ; Wintle, B (Wiley, 2020-11)
    Understanding the conditions under which small native Australian mammals can persist in the presence of introduced predators remains a key challenge to conservation ecologists. Bettong‐specific one‐way gates were used at a predator‐free reserve in South Australia to allow the burrowing bettong (Bettongia lesueur) – a small potoroid, listed as ‘vulnerable’ nationally – to disperse out of the reserve. We conducted a field experiment to explore the conditions affecting residence time of bettongs that left the reserve. We monitored bettong and mammalian predator activity outside the fence using track surveys across 18 sites over two seasons. We examined the effect of supplementary feeding as a strategy for increasing residence time, as well as the influence of predator presence and habitat quality, using linear mixed models. Bettong activity was positively associated with supplementary feeding, midstorey vegetation cover and shelter availability. After gates were closed, bettong activity near gates declined to almost zero the following weeks, likely either due to death from predation or due to movement away from the sites. To a small extent, mammalian predators were more likely to be present at sites with high bettong activity. Further research on conditions to support persistence of burrowing bettongs and other small mammals, including understanding minimum necessary predator control effort, is required before successful establishment of populations outside of fences can occur.
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    Assessing biophysical and socio-economic impacts of climate change on regional avian biodiversity
    Kapitza, S ; Van Ha, P ; Kompas, T ; Golding, N ; Cadenhead, NCR ; Bal, P ; Wintle, BA (NATURE PORTFOLIO, 2021-02-08)
    Climate change threatens biodiversity directly by influencing biophysical variables that drive species' geographic distributions and indirectly through socio-economic changes that influence land use patterns, driven by global consumption, production and climate. To date, no detailed analyses have been produced that assess the relative importance of, or interaction between, these direct and indirect climate change impacts on biodiversity at large scales. Here, we apply a new integrated modelling framework to quantify the relative influence of biophysical and socio-economically mediated impacts on avian species in Vietnam and Australia and we find that socio-economically mediated impacts on suitable ranges are largely outweighed by biophysical impacts. However, by translating economic futures and shocks into spatially explicit predictions of biodiversity change, we now have the power to analyse in a consistent way outcomes for nature and people of any change to policy, regulation, trading conditions or consumption trend at any scale from sub-national to global.
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    Reconstructing the early global dynamics of under-ascertained COVID-19 cases and infections
    Russell, TW ; Golding, N ; Hellewell, J ; Abbott, S ; Wright, L ; Pearson, CAB ; van Zandvoort, K ; Jarvis, CI ; Gibbs, H ; Liu, Y ; Eggo, RM ; Edmunds, WJ ; Kucharski, AJ (BMC, 2020-10-22)
    BACKGROUND: Asymptomatic or subclinical SARS-CoV-2 infections are often unreported, which means that confirmed case counts may not accurately reflect underlying epidemic dynamics. Understanding the level of ascertainment (the ratio of confirmed symptomatic cases to the true number of symptomatic individuals) and undetected epidemic progression is crucial to informing COVID-19 response planning, including the introduction and relaxation of control measures. Estimating case ascertainment over time allows for accurate estimates of specific outcomes such as seroprevalence, which is essential for planning control measures. METHODS: Using reported data on COVID-19 cases and fatalities globally, we estimated the proportion of symptomatic cases (i.e. any person with any of fever ≥ 37.5 °C, cough, shortness of breath, sudden onset of anosmia, ageusia or dysgeusia illness) that were reported in 210 countries and territories, given those countries had experienced more than ten deaths. We used published estimates of the baseline case fatality ratio (CFR), which was adjusted for delays and under-ascertainment, then calculated the ratio of this baseline CFR to an estimated local delay-adjusted CFR to estimate the level of under-ascertainment in a particular location. We then fit a Bayesian Gaussian process model to estimate the temporal pattern of under-ascertainment. RESULTS: Based on reported cases and deaths, we estimated that, during March 2020, the median percentage of symptomatic cases detected across the 84 countries which experienced more than ten deaths ranged from 2.4% (Bangladesh) to 100% (Chile). Across the ten countries with the highest number of total confirmed cases as of 6 July 2020, we estimated that the peak number of symptomatic cases ranged from 1.4 times (Chile) to 18 times (France) larger than reported. Comparing our model with national and regional seroprevalence data where available, we find that our estimates are consistent with observed values. Finally, we estimated seroprevalence for each country. As of 7 June, our seroprevalence estimates range from 0% (many countries) to 13% (95% CrI 5.6-24%) (Belgium). CONCLUSIONS: We found substantial under-ascertainment of symptomatic cases, particularly at the peak of the first wave of the SARS-CoV-2 pandemic, in many countries. Reported case counts will therefore likely underestimate the rate of outbreak growth initially and underestimate the decline in the later stages of an epidemic. Although there was considerable under-reporting in many locations, our estimates were consistent with emerging serological data, suggesting that the proportion of each country's population infected with SARS-CoV-2 worldwide is generally low.
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    Modelling geospatial distributions of the triatomine vectors of Trypanosoma cruzi in Latin America
    Bender, A ; Python, A ; Lindsay, SW ; Golding, N ; Moyes, CL ; Werneck, GL (PUBLIC LIBRARY SCIENCE, 2020-08)
    Approximately 150 triatomine species are suspected to be infected with the Chagas parasite, Trypanosoma cruzi, but they differ in the risk they pose to human populations. The largest risk comes from species that have a domestic life cycle and these species have been targeted by indoor residual spraying campaigns, which have been successful in many locations. It is now important to consider residual transmission that may be linked to persistent populations of dominant vectors, or to secondary or minor vectors. The aim of this project was to define the geographical distributions of the community of triatomine species across the Chagas endemic region. Presence-only data with over 12, 000 observations of triatomine vectors were extracted from a public database and target-group background data were generated to account for sampling bias in the presence data. Geostatistical regression was then applied to estimate species distributions and fine-scale distribution maps were generated for thirty triatomine vector species including those found within one or two countries and species that are more widely distributed from northern Argentina to Guatemala, Bolivia to southern Mexico, and Mexico to the southern United States of America. The results for Rhodnius pictipes, Panstrongylus geniculatus, Triatoma dimidiata, Triatoma gerstaeckeri, and Triatoma infestans are presented in detail, including model predictions and uncertainty in these predictions, and the model validation results for each of the 30 species are presented in full. The predictive maps for all species are made publicly available so that they can be used to assess the communities of vectors present within different regions of the endemic zone. The maps are presented alongside key indicators for the capacity of each species to transmit T. cruzi to humans. These indicators include infection prevalence, evidence for human blood meals, and colonisation or invasion of homes. A summary of the published evidence for these indicators shows that the majority of the 30 species mapped by this study have the potential to transmit T. cruzi to humans.