Dataset Information

Passive acoustic surveys for predicting species' distributions: Optimising detection probability.

ABSTRACT: Surveying terrestrial species across diverse habitats is important for predicting species' distributions and implementing conservation actions. For vocalising species, passive acoustic monitoring (PAM) is increasing in popularity; however, survey design rarely considers the factors influencing the timing and occurrence of vocalisations and in turn, how they may influence detectability of the species. Here, we use the koala (Phascolarctos cinereus) as a case study to show how PAM can be used to first examine the factors influencing vocalisations, and then use occupancy modelling to make recommendations on survey design for the species. We used automated recording units to monitor koala vocalisations at ten sites between August 2016 and January 2017. The timing of male koala vocalisations was linked to time of sunset with vocalisations increasing two hours prior to sunset and peaking at four hours after sunset. Vocalisations had a seasonal trend, increasing from the early to middle stage of the breeding season. Koala population density and stage of the breeding season had more influence on detection probability than daily sampling schedule. Where population density was low, and during the early stage of the breeding season, 7 survey nights (recording for 6 hours from 20:00h to 02:00h; i.e. the period of peak bellowing activity) were required to be 95% confident of a site-specific absence. Our study provides an approach for designing effective passive acoustic surveys for terrestrial species.

SUBMITTER: Hagens SV

PROVIDER: S-EPMC6051584 | biostudies-literature | 2018

REPOSITORIES: biostudies-literature

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Passive acoustic surveys for predicting species' distributions: Optimising detection probability.

Hagens Stiele V SV Rendall Anthony R AR Whisson Desley A DA

PloS one 20180718 7

Surveying terrestrial species across diverse habitats is important for predicting species' distributions and implementing conservation actions. For vocalising species, passive acoustic monitoring (PAM) is increasing in popularity; however, survey design rarely considers the factors influencing the timing and occurrence of vocalisations and in turn, how they may influence detectability of the species. Here, we use the koala (Phascolarctos cinereus) as a case study to show how PAM can be used to f ...[more]

PMID: 30020938

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Project description:Comparative assessment of the relative information content of different independent spatial data types is necessary to evaluate whether they provide congruent biogeographic signals for predicting species ranges. Opportunistic occurrence records and systematically collected survey data are available from the Dominican Republic for Hispaniola's surviving endemic non-volant mammals, the Hispaniolan solenodon (Solenodon paradoxus) and Hispaniolan hutia (Plagiodontia aedium); opportunistic records (archaeological, historical and recent) exist from across the entire country, and systematic survey data have been collected from seven protected areas. Species distribution models were developed in maxent for solenodons and hutias using both data types, with species habitat suitability and potential country-level distribution predicted using seven biotic and abiotic environmental variables. Three different models were produced and compared for each species: (a) opportunistic model, with starting model incorporating abiotic-only predictors; (b) total survey model, with starting model incorporating biotic and abiotic predictors; and (c) reduced survey model, with starting model incorporating abiotic-only predictors to allow further comparison with the opportunistic model. All models predict suitable environmental conditions for both solenodons and hutias across a broadly congruent, relatively large area of the Dominican Republic, providing a spatial baseline of conservation-priority landscapes that might support native mammals. Correlation between total and reduced survey models is high for both species, indicating the substantial explanatory power of abiotic variables for predicting Hispaniolan mammal distributions. However, correlation between survey models and opportunistic models is only moderately positive. Species distribution models derived from different data types can provide different predictions about habitat suitability and conservation-priority landscapes for threatened species, likely reflecting incompleteness and bias in spatial sampling associated with both data types. Models derived using both opportunistic and systematic data must therefore be applied critically and cautiously.

Dataset Information

Passive acoustic surveys for predicting species' distributions: Optimising detection probability.

Publications

Passive acoustic surveys for predicting species' distributions: Optimising detection probability.

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