PhD opportunityCalling in the wilderness: the use of Passive Acoustic Monitoring in biodiversity surveys

BTO harnesses the skills and passion of birdwatchers to

advance our understanding of ornithology and produce

impartial science, communicated so that it can be of

benefit to everyone.

OUR GOALSBTO increases knowledge of birds and other wildlife, and

their relationships with the environment and people, by:

Enabling more people to learn about birds and science

and grow through participation in environmental discovery.

Delivering impartial, impactful and relevant science.

Inspiring and empowering people with an understanding

of birds and the importance of knowledge.

OUR PRIORITIESWe will reach our goals by:

Providing more and better opportunities for people to

contribute to our work.

Monitoring the status of species, researching their ecology

and understanding how they respond to change.

Communicating great stories that bring to life the long-

term data, information and knowledge that we hold.

OUR IMPACTOur surveys, monitoring schemes and research

programmes are designed by expert scientists to answer

some of the most pressing questions affecting birds and

their habitats. Because of our independence we are able to

share our data, expertise and knowledge to inform decision-

makers, educate the public and support conservation

action. Our long-term datasets provide a measure of change

and enable us to look for impacts and test solutions. Our

vibrant volunteer network makes us highly effective and

ensures that our work reflects the interests of those for

whom birds and wildlife are important.

OUR FOUNDATIONS AND VALUESThe success of BTO is based on firm foundations that

include: motivated and skilled staff and volunteers; a

strong reputation; a robust business model and effective

governance systems and processes.

We are:

Inclusive and supportive

Impartial

Passionate

Collaborative and open to new ideas

‘A WORLD INSPIRED BY BIRDS AND INFORMED BY SCIENCE’

ABOUT THE BRITISH TRUST FOR ORNITHOLOGY

BRITISH TRUST FOR ORNITHOLOGY

BTO is a Registered Charity Number 216652 (England & Wales), SC039193 (Scotland).

ABOUT THE ROLE

Calling in the wilderness: the use of Passive

Acoustic Monitoring in biodiversity surveys

(NEWSONUBTO20ARIES)

Type of programme: PhD

Start date: October 2020

Mode of study: Full-time or part-time

Studentship length: 3.5 years

Supervisor/s: Dr Stuart Newson (BTO)

Dr Ben Milner (CMP UEA), Dr Adham Ashton-Butt (BTO),

Professor Phil Atkinson (BTO)

Partners: CASE award with Frankfurt Zoological Society

PROJECT DESCRIPTION:

SCIENTIFIC BACKGROUNDBy 2020, the BTO will be in its second year of an exciting

5-year landscape restoration program in Belarus and Ukraine

– ‘Wilderness without borders: creating one of the largest

natural landscapes in Europe’. The project aims to designate

new, and upgrade existing conservation areas, to create a

transboundary protected and interconnected core area of 1.2

million ha, within the wider Prypiat / Polesia area covering

approximately 5.8 million ha.

Underpinning this process, it is crucial for decisions to be

made on robust and representative assessment of the

biodiversity and ecological value of the region. However,

large-scale monitoring of wildlife, and particularly nocturnal

wildlife remains challenging.

RESEARCH METHODOLOGYThis project will examine the potential of passive acoustic

monitoring (PAM) as a tool for providing large-scale

baseline data for nocturnal wildlife. Specifically, the student

will combine the deployment of acoustic recorders in

the Prypiat and Polesia wilderness area with analysis of

acoustic data. As call libraries are essential for building

supervised automatic classifiers, gaps in species coverage

will be identified and prioritised for fieldwork effort

in 2020. The student will evaluate the BTO’s existing

approach for building random forest classifiers, in relation

to new deep learning algorithms (Convolutional Neural

Networks, CNNs), to develop a robust framework and tools

for automated species identification. With four seasons of

data (2019-2022), the student will evaluate the potential of

the approach for providing robust data on the distribution,

relative abundance and habitat requirements of the focal

taxonomic groups.

TRAININGThe successful candidate will receive training in passive

biodiversity monitoring approaches; the construction,

management and analyses of large, long-term monitoring

and acoustic databases; machine-learning including CNN’s

and is expected to achieve a high level of competency in

statistical modelling. Furthermore, the student will obtain

field research and design skills including in large-scale

sample design, small mammal trapping and handling, and

multi-taxa identification.

PHD OPPORTUNITY

ABOUT THE ROLE

REFERENCESNewson SE, Bas Y, Murray A & Gillings S (2017) Potential for coupling

the monitoring of bush-crickets with established large-scale acoustic

monitoring of bats. Methods in Ecology and Evolution 8: 1051-1062.

Barre K, Le Viol, I, Julliard R, Pauwels J, Newson, SE, Jean-Francois

J, Claireau F, Kerbiriou C & Bas Y. (2019) Accounting for automated

identification errors in acoustic surveys. Methods in Ecology and

Evolution.

Newson SE, Evans HE & Gillings S (2015) A novel citizen science

approach for large-scale standardised monitoring of bat activity and

distribution, evaluated in eastern England. Biological Conservation.

Mac Aodha, O, Gibb R, Barlow K, Browning E, Firman M, Freeman R,

Harder B, Kinsey L, Mead G, Newson SE, Pandourski I, Parsons S, Russ

J, Jones K (2018) Bat detective – Deep learning tools for bat acoustic

signal detection. PLOS Computational Biology.

Vickers W, Milner B, Lee R, & Lines J (2019) A comparison of machine

learning methods for detecting right whales from autonomous surface

vessels, European Association for Signal Processing (EUSIPCO) 2019.

SUPPLEMENTARY PROJECT DESCRIPTIONPassive acoustic monitoring (PAM) is particularly useful for

surveying cryptic taxa such as nocturnal fauna, and to monitor

areas that are difficult to access and survey1. Despite rapid

and exciting developments in acoustic monitoring, there have

been substantial challenges in developing this technology

into a cost-effective, scalable tool to assess population

status and trends. Perhaps the biggest and most complex

issue facing acoustic monitoring has been the new field of

objective quantification and statistical taxonomic identification

of bioacoustic signals. This project builds on the BTO and

UEA’s recent successes in automated species identification,

to produce the first multi-taxon acoustic monitoring in Belarus

and Ukraine.

Determining Gaps in Species Coverage. Call libraries are essential

to build supervised automatic classifiers. The BTO already has

an extensive call library of >40,000 recordings of European

bats, bush-crickets, nocturnal birds and small mammals. The

student will evaluate what data is available, and then prioritise

fieldwork effort.

Targeted Fieldwork and Gap-filling. Small mammals will be

live-trapped using Longworth traps. Calls will be recorded from

conspecific pairs held in neighbouring terrariums. For bats,

roosts will be observed over 1-2 nights to determine the routes

that individuals use as they leave their roost; static detectors

will then be positioned along these to obtain reference

recordings. For birds, recordings can be made in the field,

or static detectors left out to collect more extensive data, at

suitable sites identified through local knowledge.

Building and Evaluation of Machine-Learning Classifiers. The

student will develop an optimum machine-learning approach

for the automatic sound identification of nocturnal wildlife. This

will begin by evaluating classifier performance using random

forest and deep learning approaches before researching

and developing novel methods of classification. These will

consider issues such as sparsity of data for some species

Images by Tom Houslay & Daniel Rosengren

and ensuring robustness against environmental noises.

Furthermore, integration with a new and robust framework

recently developed by the BTO for accounting for automated

identification errors in acoustic surveys will be included to

improve classification accuracy and robustness.

Species Distributions, Habitat Requirements and Survey Design.

The student will evaluate and fine-tune our approach to

providing robust data on the distribution, relative abundance

and habitat requirements of our focal taxonomic groups. This

will be used to inform and update decision-makers on the

population status of our focal taxa, the importance of specific

sites and habitats, and to address questions important for

informing future survey and sampling design.

TRAINING & PERSONAL DEVELOPMENT:The student will receive training in biodiversity monitoring

approaches; the management and analyses of large

acoustic databases; recent advances in machine-learning,

advanced spatial analyses in R and will develop a high level

of competency in statistical modelling. The student will also

develop computer programming skills in relevant languages

such as MATLAB and Python. Given the wider interest in and

benefits of wildlife, particularly around their role in health

and well-being, there will also be a strong emphasis on

engagement in dissemination activities. As such, the project

will provide advanced training in several key skills identified in

NERC’s Most Wanted II report.

Frankfurt Zoological Society (FZS) agrees to provide supervisory

and financial aid to the student, with regard the cost of

international travel and living expenses when conducting

field research, to the total of £2,000 a year. Furthermore, FZS

offers to host the student for a period of 3-6 months and will

provide the student with transport costs and accommodation.

FZS also offers the opportunity for the student to carry out an

internship project, related, but different to their PhD research,

if they wish to suspend their PhD candidature for the duration

(and the DTP allows). In this case, FZS will provide a stipend to

fund living costs. The details of this project would be decided

with the successful candidate and their academic supervisory

team, with consideration given to the interest and benefits to

the student, their desired career trajectory, and the feasibility

of the project within the timeframe. During their stay at FZS,

the student will have access to FZS’ considerable knowledge

and expertise in the conservation sector and be involved in

the day to day working life of the organisation, gaining valuable

experience of life in an international NGO.

ELIGIBILITY REQUIREMENTS: First degree in Biology, Ecology, Environmental Sciences, Maths

or Computing

Desirable: Experience of fieldwork, handling large datasets and

familiarity with computer packages such as R, MATLAB and

Python will be an advantage.

FUNDING NOTES AND ELIGIBILITY:This project has been shortlisted for funding by the ARIES

NERC Doctoral Training Partnership, and will involve attendance

at mandatory training events throughout the PhD.

Successful candidates who meet UKRI’s eligibility criteria will

be awarded a NERC studentship. UK and EU nationals who

have been resident in the UK for 3 years are eligible for a full

award.

Excellent applicants from quantitative disciplines with limited

experience in environmental sciences may be considered for

an additional 3-month stipend to take advanced-level courses

in the subject area https://www.aries-dtp.ac.uk/supervisors/

additional-funding/.

FIND OUT MORE:For further information, please visit the Aries Website at

https://www.aries-dtp.ac.uk/studentships/newson/ or if you

would like to talk informally about the studentship please

contact Stuart Newson (stuart.newson@bto.org).

To apply, please visit the following webpage

https://www.uea.ac.uk/study/postgraduate/apply

Closing date: 15th January 2020

Interview date: Applicants will be interviewed by the

supervisory panel on 20th January 2020 at the British Trust

for Ornithology headquarters in Thetford, and the preferred

candidate assessed by the ARIES DTP interview panel on

18/19th February 2020 at the University of East Anglia in

Norwich.

ARIES operates a two-stage application process, in which

first, supervisors select their preferred candidate for their

studentship project; and second, these candidates are

assessed by the ARIES DTP interview panels.