ORCID Profile
0000-0002-2515-3316
Current Organisation
University of Tasmania
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Publisher: Wiley
Date: 09-2019
DOI: 10.1002/ECS2.2859
Abstract: Expanding the reserve system is a key strategy to enhance bio ersity protection. Yet, conservation outcomes can be undermined by underrepresentation of some habitats and opportunistic placement of protected areas. Irreplaceability and vulnerability, the key principles of conservation, should thus be combined within a bioregionalization framework to implement protection in the habitats that most need it. We proposed a simple and flexible method to prioritize bioregions for conservation based on these principles and used it to rank the 85 bioregions of the Australian continent. To do so, we quantified bio ersity values and threats in each bioregion by gathering open‐access data on species, landscapes, and land use. Bioregions were then ranked using a set of customizable scenarios, including ecologically meaningful combinations of measures of irreplaceability and vulnerability. To identify bio erse areas under threat but potentially overlooked, we compared our results with the location of already established bio ersity hotspots (i.e., areas identified as important for bio ersity and under threat). We found that bioregions with the highest bio ersity values are predominantly located in the southwest, east, and north of the continent. Similarly, threats, particularly land clearance, are concentrated along the east coast and in the southwest. When ranking bioregions using scenarios including both threats and bio ersity values, the majority (75%) of the highest‐ranking bioregions were already included in bio ersity hotspots. For five of these bioregions, the proportion of protected land to date still falls below the 17% recommended by the Convention on Biological Diversity and thus they likely require prompt prioritization and intervention. The method proposed can support ongoing monitoring and prioritization of land units for conservation. Its simplicity and flexibility mean it can be easily adopted for different areas and adjusted to local priorities.
Publisher: Springer Science and Business Media LLC
Date: 14-10-2016
Publisher: Springer Science and Business Media LLC
Date: 20-06-2018
Publisher: Wiley
Date: 28-01-2021
DOI: 10.1111/ANS.16601
Publisher: Elsevier BV
Date: 04-2019
Publisher: Wiley
Date: 19-06-2017
DOI: 10.1111/JBI.13039
Publisher: Springer Science and Business Media LLC
Date: 29-11-2020
Publisher: Cold Spring Harbor Laboratory
Date: 09-2021
DOI: 10.1101/2021.08.31.458457
Abstract: Despite the increasing interest in developing new bioregionalizations and assessing the most widely accepted biogeographic frameworks, no study to date has sought to systematically define a system of small bioregions nested within larger ones that better reflect the distribution and patterns of bio ersity. Here, we examine how an algorithmic, data-driven model of ersity patterns can lead to an ecologically interpretable hierarchy of bioregions. Australia. Present. Terrestrial vertebrates and vascular plants. We compiled information on the biophysical characteristics and species occupancy of Australia’s geographic conservation units (bioregions). Then, using cluster analysis to identify groupings of bioregions representing optimal discrete-species areas, we evaluated what a hierarchical bioregionalization system would look like when based empirically on the within-and between-site ersity patterns across taxa. Within an information-analytical framework, we then assessed the degree to which the World Wildlife Fund’s (WWF) biomes and ecoregions and our suite of discrete-species areas are spatially associated and compared those results among bioregionalization scenarios. Information on bio ersity patterns captured was moderate for WWF’s biomes (50– 58% for birds’ beta, and plants’ alpha and beta ersity, of optimal discrete areas, respectively) and ecoregions (additional 4–25%). Our plants and vertebrate optimal areas retained more information on alpha and beta ersity across taxa, with the two algorithmically derived biogeographic scenarios sharing 86.5% of their within- and between-site ersity information. Notably, discrete-species areas for beta ersity were parsimonious with respect to those for alpha ersity. Nested systems of bioregions must systematically account for the variation of species ersity across taxa if bio ersity research and conservation action are to be most effective across multiple spatial or temporal planning scales. By demonstrating an algorithmic rather than subjective method for defining bioregionalizations using species- ersity concordances, which reliably reflects the distributional patterns of multiple taxa, this work offers a valuable new tool for systematic conservation planning.
Publisher: Wiley
Date: 09-02-2017
DOI: 10.1002/ECE3.2734
Publisher: CSIRO Publishing
Date: 2021
DOI: 10.1071/WR20010
Publisher: Pensoft Publishers
Date: 29-06-2017
Publisher: MDPI AG
Date: 17-04-2017
DOI: 10.3390/F8040123
Publisher: Elsevier BV
Date: 08-2020
Publisher: Springer Science and Business Media LLC
Date: 28-11-2023
Publisher: Elsevier BV
Date: 03-2020
Publisher: MDPI AG
Date: 05-10-2017
DOI: 10.3390/LAND6040068
Publisher: Springer Science and Business Media LLC
Date: 04-12-2018
Location: Australia
Start Date: 2019
End Date: 2022
Funder: University of Tasmania
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