A Typology of Australian Terrestrial Bird Communities

ABSTRACT Aim Holistic measurement of the response of fauna communities to interventions requires suitable community condition metrics. However, the development of such metrics is hindered by the absence of broad‐scale typologies at suitable spatial and ecological resolutions. We aimed to derive a preliminary typology of terrestrial bird communities for Australia, based on bird co‐occurrence data, and describe and map the likely distribution of each community type across the continent. Location Mainland Australia, continental islands. Time Period 1973–2022. Major Taxa Studied Aves. Methods We used fine‐scale co‐occurrence data from standard 2‐ha surveys in BirdLife Australia's citizen‐science database. After filtering to reduce bias, we used hierarchical clustering followed by iterative consultation with experts to identify reliably distinct and recognisable terrestrial bird communities across Australia. We used Maxent to model the likely distributions of each community and developed community descriptions based on each community's composition and distribution. Results The resultant typology included 29 reliably distinct and recognisable bird communities with major clusters corresponding with seven broad geographical regions. The distributions of bird communities did not correspond tightly to the boundaries of major vegetation groups, with most communities occurring across multiple vegetation types. Main Conclusions Our preliminary typology of bird communities provides a standard classification at a continental scale. It newly defines distinct bird communities as entities for which condition benchmarks can be established to allow assessment of their conservation status and monitoring of change over time. Refinement will enable cryptic communities in areas with sparse data to be identified. The method could be translated to other regions where adequate coverage of data in the form of standardised surveys of fauna is available. Vast biodiversity datasets delivered through citizen science programs provide the opportunity to develop such typologies for fauna communities, as a precursor to developing targeted and informative community condition metrics.

Authors

Institutions

Publication Details

Journal
Diversity and Distributions
Published
2026-02-01
DOI
https://doi.org/10.1111/ddi.70143
Primary Topic
Ecology and Vegetation Dynamics Studies
Type
article
Field-Weighted Citation Impact
0.00

Funders

Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

A Typology of Australian Terrestrial Bird Communities

Jeremy S. Simmonds, Courtney B. Melton, Richard Loyn, April E. Reside et al.
Diversity and Distributions
Ecology and Vegetation Dynamics Studies
article

A Typology of Australian Terrestrial Bird Communities

Jeremy S. Simmonds, Courtney B. Melton, Richard Loyn, April E. Reside, Matthew Gibson, Katherine E. Selwood, Bryony Palmer, Helen J. Mayfield, Martine Maron, Teresa J. Eyre, Hugh P. Possingham, Simon J. Verdon, Golo Maurer, Rohan H. Clarke, Richard Noske, Jacinta E. Humphrey, Paul G. McDonald, Birgita D. Hansen, Rebecca Spindler, Eric Vanderduys, James Watson, Amanda N. D. Freeman, Michael F. Clarke, Hannah Fraser, Allan H. Burbidge, Fred William Rainsford, John Reid, Alex C. Maisey, Alex Kutt, Karlina Indraswari, Robert Davis, Helenna Mihailou, Andrew Bennett, David Watson, Ayesha Tulloch, James Radford, Daniella Teixeira, Nigel Jackett, Jonathan Mills‐Anderson, Doug Robinson, Jacinta Humphrey
article en

Abstract

ABSTRACT Aim Holistic measurement of the response of fauna communities to interventions requires suitable community condition metrics. However, the development of such metrics is hindered by the absence of broad‐scale typologies at suitable spatial and ecological resolutions. We aimed to derive a preliminary typology of terrestrial bird communities for Australia, based on bird co‐occurrence data, and describe and map the likely distribution of each community type across the continent. Location Mainland Australia, continental islands. Time Period 1973–2022. Major Taxa Studied Aves. Methods We used fine‐scale co‐occurrence data from standard 2‐ha surveys in BirdLife Australia's citizen‐science database. After filtering to reduce bias, we used hierarchical clustering followed by iterative consultation with experts to identify reliably distinct and recognisable terrestrial bird communities across Australia. We used Maxent to model the likely distributions of each community and developed community descriptions based on each community's composition and distribution. Results The resultant typology included 29 reliably distinct and recognisable bird communities with major clusters corresponding with seven broad geographical regions. The distributions of bird communities did not correspond tightly to the boundaries of major vegetation groups, with most communities occurring across multiple vegetation types. Main Conclusions Our preliminary typology of bird communities provides a standard classification at a continental scale. It newly defines distinct bird communities as entities for which condition benchmarks can be established to allow assessment of their conservation status and monitoring of change over time. Refinement will enable cryptic communities in areas with sparse data to be identified. The method could be translated to other regions where adequate coverage of data in the form of standardised surveys of fauna is available. Vast biodiversity datasets delivered through citizen science programs provide the opportunity to develop such typologies for fauna communities, as a precursor to developing targeted and informative community condition metrics.

Diversity and DistributionsVol. 32(2)
Griffith University (AU), Australian National University (AU), Edith Cowan University (AU), University of Tasmania (AU), Australian Wildlife Conservancy (AU), Bush Heritage Australia (AU), Federation University (AU), Charles Sturt University (AU), Queensland University of Technology (AU), The University of Queensland (AU), The University of Melbourne (AU), La Trobe University (AU), BirdLife Australia (AU), Australian Institute of Tropical Health and Medicine (AU), Charles Darwin University (AU), MIT University (MK), Clinical Insights (US), Health Sciences and Nutrition (AU), Zoos Victoria (AU), Queensland Department of Environment and Science (AU), Department of Biodiversity, Conservation and Attractions (AU), Monash University (AU), RMIT University (AU), James Cook University (AU), University of New England (AU), National Trust for Nature Conservation (NP)
University of Queensland
Life in Land
Openalex Percentile: Top 79%
Ecology and Vegetation Dynamics Studies
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.