The intersection between elected representatives and threatened species recovery

This is a Preprint and has not been peer reviewed. This is version 1 of this Preprint.

Add a Comment

You must log in to post a comment.


Comments

There are no comments or no comments have been made public for this article.

Downloads

Download Preprint

Authors

Gareth Sean Kindler, Stephen Kearney, Alex Kusmanoff, Michelle Ward, Richard Fuller, Thomas LLoyd, Sarah Bekessy, Emily Gregg, Romola Stewart, James Watson

Abstract

A core objective of the conservation movement is to motivate government decision-makers into delivering critical policy changes to abate the global species extinction crisis. Using Australia as a case study, we showcase a way of highlighting the intersection between a nation’s elected representatives and extant threatened species. We analyse the relationship between Australia’s 151 Commonwealth Electoral Divisions (CEDs) and the distributions of 1,651 nationally listed threatened species. We show all CEDs contain at least 14 threatened species and nearly half of the species analysed (n=801, 49%) are confined to just one CED (n=44), with 1345 (81%) species intersecting with < five CEDs. These findings demonstrate the importance of enumerating the crisis to better understand the responsibility elected representatives have to their local region and constituents. Linking species distributions to political geography creates data that can be used by the conservation movement to motivate environmental accountability and leadership.

DOI

https://doi.org/10.32942/X2BC75

Subjects

Environmental Sciences, Geography, Political Science

Keywords

conservation, biodiversity, democracy, political representation, science-policy interface, species distribution

Dates

Published: 2022-11-05 18:19

Last Updated: 2022-11-06 01:19

License

CC-By Attribution-NonCommercial-NoDerivatives 4.0 International

Additional Metadata

Conflict of interest statement:
The authors declare no conflict of interest.

Data and Code Availability Statement:
Raw data used in this study is freely available at the locations identified in the Method and References sections. Analysed data is available as supplementary material or by request to the corresponding author. The code used to produce the analysis is available at the corresponding author's GitHub.