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Including indigenous knowledge in species distribution modeling for increased ecological insights.

Authors :
Skroblin A
Carboon T
Bidu G
Chapman N
Miller M
Taylor K
Taylor W
Game ET
Wintle BA
Source :
Conservation biology : the journal of the Society for Conservation Biology [Conserv Biol] 2021 Apr; Vol. 35 (2), pp. 587-597. Date of Electronic Publication: 2020 Jun 17.
Publication Year :
2021

Abstract

Indigenous knowledge systems hold detailed information on current and past environments that can inform ecological understanding as well as contemporary environmental management. Despite its applicability, there are limited examples of indigenous knowledge being incorporated in species distribution models, which are widely used in the ecological sciences. In a collaborative manner, we designed a structured elicitation process and statistical framework to combine indigenous knowledge with survey data to model the distribution of a threatened and culturally significant species (greater bilby or mankarr [Macrotis lagotis]). We used Martu (Aboriginal people of the Australian western deserts) occurrence knowledge and presence data from track-based surveys to create predictive species distribution models with the Maxent program. Predictions of species distribution based on Martu knowledge were broader than those created with survey data. Together the Martu and survey models showed potential local declines, which were supported by Martu observation. Both data types were influenced by sampling bias that appeared to affect model predictions and performance. Martu provided additional information on habitat associations and locations of decline and descriptions of the ecosystem dynamics and disturbance regimes that influence occupancy. We concluded that intercultural approaches that draw on multiple sources of knowledge and information types may improve species distribution modeling and inform management of threatened or culturally significant species.<br /> (© 2019 Society for Conservation Biology.)

Details

Language :
English
ISSN :
1523-1739
Volume :
35
Issue :
2
Database :
MEDLINE
Journal :
Conservation biology : the journal of the Society for Conservation Biology
Publication Type :
Academic Journal
Accession number :
31216076
Full Text :
https://doi.org/10.1111/cobi.13373