Introduction

How we can better support acoustic monitoring programmes across the country, based on survey results.

Context

Recent technological developments have enabled automatic recording devices (ARDs) to be used for a variety of monitoring purposes, including wildlife (eg birds, bats, insects and marine mammals), industrial noise (eg from construction or aircraft) and other anthropogenic noise (Blumstein et al. 2011; Merchant et al. 2015; Sousa-Lima et al. 2013).

The potential applications of ARDs are enormous, and in recent years their use has increased dramatically (Frick 2013; Steer 2010), however for many uses the hardware and software are still in the early stages of development. Despite this, ARDs are proving to be a useful addition to more traditional monitoring methods and have a number of advantages including data collection over prolonged time periods and generation of a permanent reviewable record (Acevedo and Villanueva-Rivera 2006; Haselmayer and Quinn 2000).

In March 2017, DOC’s Planning, Monitoring and Reporting Team conducted a survey to gain a better understanding of the current state of acoustic monitoring and use of ARDs in New Zealand. This was to inform direction regarding what tools, if any, should be researched and developed to support acoustic monitoring programmes across the country. The survey asked detailed questions in the following areas: objectives and monitoring plans; technical information concerning ARDs; data analysis and reporting; training and support; and challenges and limitations.

Key findings

  • ARDs were being used by a wide range of organisations (including government agencies, community groups, universities and consultancies), mainly for monitoring of wildlife.
  • The most frequent challenges regarding ARD use were related to processing of recordings (ie turning them into usable data). Many survey respondents reported issues with processing due to lack of time, funding or skills.
  • Many respondents expressed the need for standard protocols, software development/support and training in ARD use.

Survey response

From 300 individuals contacted, 76 completed surveys were returned from a range of organisations including government agencies, universities, consultancies, community groups and charitable trusts (Figure 1).

Most respondents were currently using ARDs in some way, although there were a few that were not. Factors preventing ARD use included cost of equipment, time required to process recordings and lack of appropriate skills.

Bar chart.
Figure 1: Proportion of survey responses from each type of organisation

Objectives

Most respondents (93%) identified wildlife as their primary purpose for undertaking acoustic monitoring (Figure 2).

53% had an ARD monitoring plan in place, 43% did not, whilst the remainder were unsure.

Of those that had no monitoring plan, half reportedly faced challenges that prevent them from designing or implementing such a plan. Lack of resources (e.g. time, funding, knowledge/skills) was the most common issue. 25% of respondents commented on the lack of existing protocols to support development of monitoring plans and guide the use of ARDs.

The most common challenge for ARD users in addressing their monitoring objectives was processing of recordings. Issues included lack of staff or volunteer time, funding or a shortage of the necessary skills. Other common issues included limitations of the data (ie inability of ARDs to measure abundance) and the difficulties/cost of establishing and retrieving ARDs in remote locations.

Bar chart.
Figure 2: Proportion of survey responses for each type of monitoring purpose for which ARDs are used

Hardware

The most common device in use was the ARD designed and built by DOC. Others included those produced by SongMeter and Cornell University.

Challenges specifically related to ARD hardware included storage and management of large volumes of recordings, battery life, weather damage, theft and vandalism.

Data Analysis & reporting

Many respondents used a combination of techniques (audio/visual, manual/automated) in processing their recordings to convert them into usable data (Figure 3).

40% of respondents were using automated processing of some kind, and half of these reported challenges and/or limitations with analysis and reporting, especially processing time, data storage/management and reliability of the software.

Bar chart.
Figure 3: Proportion of survey responses for each type of processing method. Note that several respondents used multiple processing methods

Training and support

38% of respondents reported that training was available to them, of which 79% was delivered in-house, whilst 32% provided externally.

One-on-one training was most common, followed by workshops/seminars and on-line training.

61% of respondents expressed a desire for external training and support, covering various aspects of using ARDs (Figure 4).

There was a high demand for software design and support, including reliable automated detection software.

Bar chart.
Figure 4: Proportion of survey responses for each type of support required. Note that several respondents required support in multiple aspects of ARD use

Future challenges

Different, potentially incompatible technologies, protocols or analysis techniques, could result in problems comparing or sharing data. A need for standard protocols was highlighted by many respondents (especially those from community groups). Many felt that current issues with automated detection, data storage and data management were likely to improve as technologies continue to evolve.

Methodology

The survey was conducted via an online SurveyMonkey questionnaire, accessed through this website.

The survey contained detailed questions on the use of ARDs. There were 53 questions in total, some with a list of response options, some yes/no, and others open-ended.

300 people were invited to participate, from a wide range of organisation types. 76 responses were received and analysed to produce this summary report.

Glossary of terms

  • Automatic Recording Device: any device that records audio/visual information and does not require presence of an operator.
  • Processing: the conversion of recorded information (audio/visual) into data that can be analysed (e.g. a spreadsheet containing bird species identified).

References

Acevedo MA, Villanueva-Rivera LJ 2006. Using automated digital recording systems as effective tools for the monitoring of birds and amphibians. Wildlife Society Bulletin 34: 211-214.

Blumstein DT, Mennill DJ, Clemins P, Girod L, Yao K, Patricelli G, Deppe JL, Krakauer AH, Clark C, Cortopassi KA, Hanser SF, McCowan B, Ali AM, Kirschel ANG 2011. Acoustic monitoring in terrestrial environments using microphone arrays: Applications, technological considerations and prospectus. Journal of Applied Ecology 48: 758-767.

Frick WF 2013. Acoustic monitoring of bats, considerations of options for long-term monitoring. Therya 4: 69-78.

Haselmayer J, Quinn JS 2000. A comparison of point counts and sound recording as bird survey methods in Amazonian southeast Peru. The Condor 102: 887-893.

Merchant ND, Fristrup KM, Johnson MP, Tyack PL, Witt MJ, Blondel P, Parks SE 2015. Measuring acoustic habitats. Methods in Ecology and Evolution 6: 257-265.

Sousa-Lima RS, Norris TF, Oswald JN, Fernandes DP 2013. A review and inventory of fixed autonomous recorders for passive acoustic monitoring of marine mammals. Aquatic Mammals 39: 23-53.

Steer J 2010. Bioacoustic monitoring of New Zealand birds. Notornis 57: 75–80.

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