# The role of vocal individuality in conservation

> Every bittern’s boom is a little different. This review explains how researchers can recognise individual animals by their calls, without ever catching them, and how doing so revealed that a corncrake population had been undercounted by up to 30% and that roaming bitterns had been counted twice. It also sets out the pitfalls, from voices that change over the years to quiet females.

Summary by Kersey Lawrence, Original Wisdom. Updated 9 November 2026. Page: https://www.originalwisdom.com/tracking-literature/2005-terry-peake-role-vocal-individuality-conservation/

## Citation and access

- **Authors:** Andrew M. R. Terry, Tom M. Peake and Peter K. McGregor
- **Year published:** 2005
- **Journal or source:** Frontiers in Zoology
- **Full citation:** Terry, A. M. R., Peake, T. M. and McGregor, P. K. 2005. The role of vocal individuality in conservation. Frontiers in Zoology 2: 10.
- **DOI:** 10.1186/1742-9994-2-10
- **Access status:** Open access (CC BY 2.0)
- **PDF:** https://www.originalwisdom.com/wp-content/uploads/2026/11/2005_Terry_and_Peake_etal_the-role-of-vocal-individuality-in-conservation.pdf

## Tags

- **Species:** Birds > African wood owl; Birds > Barred owl; Birds > Christmas Island hawk-owl; Birds > Corncrake; Birds > Eastern screech owl; Birds > Eurasian bittern; Birds > Eurasian eagle-owl; Birds > Eurasian pygmy owl; Birds > European scops owl; Birds > Great horned owl; Birds > Northern saw-whet owl; Birds > Seychelles scops owl; Birds > Tawny owl
- **Behaviour and ecology:** Behaviour; Communication; Movement; Site fidelity
- **Methods and technology:** Capture-mark-recapture; Literature review; Machine learning; Observer reliability; Population estimation; Radio telemetry
- **Data type:** Review
- **Observer qualification:** Not needed
- **Discipline:** Behaviour and ecology
- **Year published:** 2005

## Detailed keywords

- **Species:** Case studies: European bittern (Botaurus stellaris), corncrake (Crex crex), and owls including European scops owl (Otus scops), African wood owl (Strix woodfordii), barred owl (Strix varia), northern saw-whet owl (Aegolius acadicus, spelled “arcadicus” in the paper), eagle owl (Bubo bubo), screech owl (Otus asio), Christmas Island hawk owl (Ninox natalis), tawny owl (Strix aluco), pygmy owl (Glaucidium passerinum), Seychelles scops owl (Otus insularis) and great horned owl (Bubo virginianus). Other examples discussed: common buzzard (Buteo buteo), Yuma clapper rail (Rallus longirostris yumanensis), black rail (Laterallus jamaicensis), Adélie penguin (Pygoscelis adeliae), brown-headed cowbird (Molothrus ater), red-fronted parrot (Poicephalus gulielmi), twite (Acanthis flavirostris, written “Acanthus” in the paper), wild turkey (Meleagris gallopavo mexicana), petrels, geese; cheetah (Acinonyx jubatus, written “Acynonyx” in the paper), lion (Panthera leo), spotted hyena (Crocuta crocuta), African wild dog (Lycaon pictus), swift fox (Vulpes velox), fallow deer (Dama dama), Gunnison’s prairie dog (Cynomys gunnisoni), Steller sea lion (Eumetopias jubatus, written “Stellar” in the paper), chacma baboon (Papio ursinus), cotton-top tamarin (Saguinus oedipus), chimpanzees, marmosets, gibbons, bottlenose dolphin (Tursiops truncatus), sperm whale (Physeter macrocephalus), killer whale (Orcinus orca); túngara frog (Physalaemus pustulosus).
- **Location and habitat:** A review with no study area of its own. Bittern examples from the United Kingdom (dense reed beds) and Italy; corncrakes in United Kingdom hay meadows and silage fields; Serengeti wild dogs.
- **Topics:** vocal individuality (individually distinctive calls) as a non-invasive marking technique; discrimination versus identification of individuals; census error and sampling bias; floaters (non-territorial, mobile individuals) inflating counts; playback bias; welfare effects of capture, handling and marking; population viability analysis (PVA); life-history data (survival, turnover, habitat use); vocal stability over time; monitoring females; recording equipment (shotgun and parabolic microphones, recorders, filters, sampling rate); waveforms, power spectra and spectrograms; identifying individuals by ear and by eye; mammal and cetacean vocal individuality.
- **Statistics or models:** Reviewed, not run: discriminant function analysis (DFA), stepwise discriminant analysis, adaptive kernel-based DFA, principal components analysis, similarity techniques (acoustic space with Euclidean distance; spectrogram cross-correlation using Pearson correlation), artificial neural networks (including Kohonen networks), dynamic time warping, hidden Markov models, linear predictive coding, inter-observer reliability and repeatability, population viability analysis.
- **Data type:** Review of the literature, including the authors’ own earlier studies. Note: the figure 1 caption labels panel B as the spectrogram and panel C as the power spectrum, while the text cites them the other way round (Fig. 1B power spectrum, Fig. 1C spectrogram).

## Synopsis

### 1. What they did

Many animals can be told apart by their calls, because each individual’s voice varies little from call to call but differs from other individuals. The authors reviewed how this “vocal individuality” can be used in conservation, as a way of recognising individuals without catching or marking them.

They:

- Set out why identifying individuals matters for conservation: better population models, spotting individuals that matter more for breeding, catching errors in counts, and avoiding the harm that capture and marking can cause.

- Distinguished discrimination (telling individuals apart at one point in time) from identification (recognising the same individual again later).

- Gave practical advice on recording and measuring calls, and compared the main ways of analysing them, by ear and eye and with statistics.

- Described three bird case studies (European bittern, corncrake and owls), discussed the main limitations, and considered the potential in mammals.

### 2. What they found

Why individuals matter

- Population viability analysis (PVA) models usually treat all individuals as equal, which can make predicted extinction risk overly pessimistic. Knowing individuals improves the estimates of survival and breeding.

- A few individuals often produce most of the young: 17% of a common buzzard population produced 50% of the next year’s fledglings, and 8% of cheetah matrilineages produced over 50% of the population over 20 years.

- Counts can be biased. Playback drew responses from only 10 to 40% of Yuma clapper rail males present. Mobile floating male bitterns were counted repeatedly, so a population of 15 (nine residents and six floaters) was counted as 25.

- Capture and marking can harm animals and also only mark part of a population. Radio-tags often last a year or less, while stable calls could allow longer monitoring.

Methods

- Microphone choice depends on the call: low-pitched bittern booms (100 to 200 Hz) need a shotgun microphone rather than a parabola. Compressed recording formats (such as MiniDisc) can distort important parts of a call.

- Spectrograms are useful for looking at sounds but should not be used for direct measurements; the authors suggest waveforms for timing and power spectra for frequency.

- Experienced field researchers can often identify individuals by ear, but this has rarely been tested as a census method; one bittern study found it depended on experience and worked only for small numbers. Comparing spectrograms by eye is common and sometimes beats statistics (for example with bottlenose dolphin signature whistles), but it is subjective, so observer repeatability and inter-observer reliability need checking.

- Standard discriminant function analysis (DFA) can only assign calls to individuals already known, so it cannot detect newcomers. Similarity techniques and some neural networks can recognise new individuals. Classification scores without validation on new data are “almost meaningless”.

Case studies

- European bittern: the only species the authors knew of that is routinely counted and monitored by voice, in the United Kingdom for over 10 years. A semi-automatic method separated more than 40 bitterns, but the main feature, the boom’s dominant frequency, changed between years in four radio-tagged males, sometimes by more than the differences between birds.

- Corncrake: census rules assumed about 75% of males call each night. Voice identification showed only 41% did, so the population was underestimated by up to 30%. Males in poorer habitat moved further.

- Owls: calls are individually distinctive in many species and seem stable. European scops owl territories had 55 to 78% turnover between years; African wood owls, where both sexes call, showed 19.3% turnover in males and 13.7% in females over a 12-year study. These owl studies assumed vocal stability without independently marked birds.

Limitations

Four main problems: proving individuality and its stability needs intensive study, ideally with independently marked animals; it needs sound analysis skills and equipment; it only covers the animals that call (often territorial males); and identifications always carry some uncertainty. Females of many bird species are quiet, although contact calls (as in Steller sea lion mothers and pups) may help.

### 3. What they concluded

- Vocal individuality is surprisingly under-used. Most studies show that individuality exists, not that it works as a conservation tool.

- To test it as a tool: choose an easily recorded call (usually long-range advertising calls); test with as many individuals as will be monitored (studies often use only 10 to 20); choose measures that survive poor recordings; prefer similarity techniques; record locations, times and other calling birds; test with blind, simulated census trials; and give clear guidelines to the people who will collect and analyse recordings.

- Mammals have potential but are harder: their calls are more complex and can change with social context (chimpanzees, marmosets, dolphins). The swift fox is a notable exception where it has been applied.

- It is not a cure for every monitoring problem, but where a species is sensitive to disturbance or hard to monitor, its voice can be an effective conservation tool.

### 6. Other technologies, skills or innovations

- Shotgun and parabolic microphones, analogue, digital and compressed recorders, calibration tones, high-pass and low-pass filters.

- Waveform, power spectrum and spectrogram measurements.

- Automated identification with neural networks, which the authors had used to count and identify corncrakes in simulated census and monitoring tasks with a set of 30 individuals.

### 7. Implications for conservation (from the paper)

- In the authors’ view, non-invasive techniques such as vocal individuality should be the default, with invasive marking used only when its benefits outweigh possible harm.

- Recognising individuals by voice can correct census errors (floaters, birds that call less than expected) and give survival, turnover and habitat-use data for secretive, nocturnal or low-density species.

- Vocal stability over time and how to monitor females are the most important current limits.

### 8. Implications for tracking (Original Wisdom's observations)

_These are Original Wisdom's observations, not the authors'._

- Vocal individuality is a sound-based version of what trackers do with footprints: recognising individuals from natural variation, without capture. The same questions apply to both: is the feature consistent within an individual over time, different enough between individuals, and how reliable are different observers?

- The paper notes that experienced field researchers can often identify individuals by ear, but that this skill has rarely been tested. As with tracker skill, it can be evaluated through observer reliability and blind trials.

## Cite this summary

Lawrence, K. 2026. Summary of: The role of vocal individuality in conservation (Terry and Peake et al., 2005). Original Wisdom, Tracking Literature. https://www.originalwisdom.com/tracking-literature/2005-terry-peake-role-vocal-individuality-conservation/