Demographic distribution models for ecology, conservation & public health

Grant number: DE180100635 | Funding period: 2018 - 2021

Completed

Abstract

This project aims to advance distribution modelling by developing a new demographic species distribution modelling (DSDM) framework that unites correlative and process-based approaches. This project will develop ecologically realistic models of the distributions of species and diseases, leading to better decision-making in conservation and public health. This will provide significant benefits, such as a better understanding of where and how to control mosquitoes to reduce malaria transmission in Africa, how best to conserve the vulnerable greater glider in Eastern Australia, and to forecast where and when outbreaks of Ross River virus are likely occur in Victoria.

Related publications (9)

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A modelling approach to estimate the transmissibility of SARS-CoV-2 during periods of high, low, and zero case incidence.

Nick Golding, David J Price, Gerard Ryan, Jodie McVernon, James M McCaw, Freya M Shearer

2023-01-20

Against a backdrop of widespread global transmission, a number of countries have successfully brought large outbreaks of COVID-19 ..

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A fractional land use change model for ecological applications

Simon Kapitza, Nick Golding, Brendan A Wintle

2021-11-24

By mapping land use under projections of socio-economic change, ecological changes can be predicted to inform conservation decisio..

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Modelling temperature-driven changes in species associations across freshwater communities

Sam Wenaas Perrin, Bert van der Veen, Nick Golding, Anders Gravbrot Finstad

2021-10-20

Due to global climate change-induced shifts in species distributions, estimating changes in community composition through the use ..

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Multi-output Gaussian processes for species distribution modelling

Martin Ingram, Damjan Vukcevic, Nick Golding

2020-12-15

Species distribution modelling is an active area of research in ecology. In recent years, interest has grown in modelling multiple..

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Defining and evaluating predictions of joint species distribution models

David P Wilkinson, Nick Golding, Gurutzeta Guillera-Arroita, Reid Tingley, Michael A McCarthy

2020-11-08

Joint species distribution models (JSDMs) simultaneously model the distributions of multiple species, while accounting for residua..

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Reconstructing the early global dynamics of under-ascertained COVID-19 cases and infections

Timothy W Russell, Nick Golding, Joel Hellewell, Sam Abbott, Lawrence Wright, Carl AB Pearson, Kevin van Zandvoort, Christopher I Jarvis, Hamish Gibbs, Yang Liu, Rosalind M Eggo, W John Edmunds, Adam J Kucharski

2020-10-22

BACKGROUND: Asymptomatic or subclinical SARS-CoV-2 infections are often unreported, which means that confirmed case counts may not..

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steps: Software for spatially and temporally explicit population simulations

Casey Visintin, Natalie J Briscoe, Skipton NC Woolley, Pia E Lentini, Reid Tingley, Brendan A Wintle, Nick Golding

2020-02-25

Species population dynamics are driven by spatial and temporal changes in the environment, anthropogenic activities and conservati..

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Data Integration for Large-Scale Models of Species Distributions

Nick JB Isaac, Marta A Jarzyna, Petr Keil, Lea I Dambly, Philipp H Boersch-Supan, Ella Browning, Stephen N Freeman, Nick Golding, Gurutzeta Guillera-Arroita, Peter A Henrys, Susan Jarvis, Jose Lahoz-Monfort, Joern Pagel, Oliver L Pescott, Reto Schmucki, Emily G Simmonds, Robert B O'Hara

2020-01-01

With the expansion in the quantity and types of biodiversity data being collected, there is a need to find ways to combine these d..

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Utilizing general human movement models to predict the spread of emerging infectious diseases in resource poor settings

MUG Kraemer, N Golding, D Bisanzio, S Bhatt, DM Pigott, SE Ray, OJ Brady, JS Brownstein, NR Faria, DAT Cummings, OG Pybus, DL Smith, AJ Tatem, SI Hay, RC Reiner

2019-03-26

Human mobility is an important driver of geographic spread of infectious pathogens. Detailed information about human movements dur..