کد مقاله کد نشریه سال انتشار مقاله انگلیسی نسخه تمام متن
5741907 1617193 2017 10 صفحه PDF دانلود رایگان
عنوان انگلیسی مقاله ISI
A methodology for analyzing biological choruses from long-term passive acoustic monitoring in natural areas
ترجمه فارسی عنوان
یک روش برای تجزیه و تحلیل خواص بیولوژیک از نظارت بلند مدت آکوستیک منفعل در مناطق طبیعی
کلمات کلیدی
موضوعات مرتبط
علوم زیستی و بیوفناوری علوم کشاورزی و بیولوژیک بوم شناسی، تکامل، رفتار و سامانه شناسی
چکیده انگلیسی


- A first analysis of underwater soundscape of the Alcatrazes Wildlife Refuge, southern Brazil.
- Biophonic activities strongly correlated with sunrise and sunset dominated the studied habitat.
- Fish choruses dominated the frequency band below 2 kHz and snapping shrimps frequency band above 2 kHz.
- An approach for long-term acoustic data visualization and a method for automatic detection of chorus trends are presented.

Long-term passive acoustic monitoring can provide important insights on the study of biological choruses, which represent a key component of natural environments. Nowadays, the development of methods for analysis and visualization of large acoustic datasets is an active area of research. In this context, the present paper addresses how the traditional computation of spectrograms and Sound Pressure Levels (SPL) could be used for analyzing large sound datasets. Additionally, a visualization tool named here as SPL-Gram and a method for automatic detection of trends in dawn and dusk choruses are presented. The dataset used as a case study represents 3 months of underwater sound collected in a marine wildlife refuge in southern Brazilian coast. Results reveal events with strong daily periodicity, originated by fish choruses in the frequency band from 0.01-2 kHz, and, in the higher frequencies, reflecting acoustic activity of crustaceans. The reported periodicities show a marked relation with sunrise and sunset through the studied period, thus revealing circadian cycles present in the monitored environment. The proposed methodology is not only easy for implementation, but also proves to be valuable in the description of daily and seasonal patterns of biological choruses in large acoustic datasets.

ناشر
Database: Elsevier - ScienceDirect (ساینس دایرکت)
Journal: Ecological Informatics - Volume 41, September 2017, Pages 1-10
نویسندگان
, ,