Estimating koala density from incidental koala sightings in South-East Queensland, Australia (1997–2013), using a self-exciting spatio-temporal point process model

Dissanayake, Ravi Bandara and Giorgi, Emanuele and Stevenson, Mark and Allavena, Rachel and Henning, Joerg (2021) Estimating koala density from incidental koala sightings in South-East Queensland, Australia (1997–2013), using a self-exciting spatio-temporal point process model. Ecology and Evolution, 11 (20). pp. 13805-13814. ISSN 2045-7758

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Abstract

The koala, Phascolarctos cinereus, is an iconic Australian wildlife species facing a rapid decline in South-East Queensland (SEQLD). For conservation planning, the ability to estimate the size of koala populations is crucial. Systematic surveys are the most common approach to estimate koala populations but because of their cost they are often restricted to small geographic areas and are conducted infrequently. Public interest and participation in the collection of koala sighting data is increasing in popularity, but such data are generally not used for population estimation. We modeled monthly sightings of koalas reported by members of the public from 1997 to 2013 in SEQLD by developing a self-exciting spatio-temporal point process model. This allowed us to account for characteristics that are associated with koala presence (which vary over both space and time) while accounting for detection bias in the koala sighting process and addressing spatial clustering of observations. The density of koalas varied spatially due to the heterogeneous nature of koala habitat in SEQLD, with a mean density of 0.0019 koalas per km2 over the study period. The percentage of land areas with very low densities (0–0.0005 koalas per km2) remained similar throughout the study period representing, on average, 66% of the total study area. The approach described in this paper provides a useful starting point to allow greater use to be made of incidental koala sighting data. We propose that the model presented here could be used to combine systematic koala survey data (which is spatially restricted, but more precise) with koala sighting data (which is incidental and often biased by nature, but often collected over large geographical areas). Our approach could also be adopted for modeling the density of other wildlife species where data is collected in the same manner.

Item Type:
Journal Article
Journal or Publication Title:
Ecology and Evolution
Uncontrolled Keywords:
/dk/atira/pure/subjectarea/asjc/1100/1105
Subjects:
?? citizen sciencekoalamodelingpopulationqueenslandecology, evolution, behavior and systematicsecologynature and landscape conservation ??
ID Code:
159872
Deposited By:
Deposited On:
20 Sep 2021 09:20
Refereed?:
Yes
Published?:
Published
Last Modified:
15 Jul 2024 21:57