Māui dolphin abundance estimate

2015-16 abundance estimate

In 2015 DOC and Ministry for Primary Industries, in collaboration with Auckland and Oregon State Universities, began a repeat of the abundance estimate of Māui dolphins.

The revised population estimate was carried out over two summer seasons, 2015 and 2016. The 2015 and 2016 field reports are available below.

Key findings

• The abundance of Māui dolphins over 1 year of age was estimated to be 63 with a 95% confidence interval of 57 to 75 (this means that the researchers are 95% confident that there are between 57-75 Māui dolphins over the age of 1 year)
• Over both years a total of 92 biopsy samples were collected from a total of 51 individual dolphins
• 32 of these individuals were females
• 17 individuals were sampled in both years 
• 49 individuals were identified as Māui dolphins
• 2 individuals were identified as Hector’s dolphins, one of which was sampled in the previous surveys (2010/2011), and a male Hector’s was sampled in both 2015 and 2016.

The 2015 and 2016 field seasons were successful in matching the effort of the 2010 and 2011 surveys with a comparable number of surveys, duration of the survey period and coverage of the primary known habitat for Māui dolphins.

The results of this abundance estimate will be used to inform the review of the Hector’s and Māui dolphin Threat Management Plan in 2018.

Reports

Estimating the abundance and effective population size of Māui dolphins using microsatellite genotypes in 2015-16, with retrospective matching to 2001-16:

• Estimating the abundance and effective population size of Māui dolphins (PDF, 4,442K)

Māui dolphin biopsy sampling survey field reports and preliminary results:

• Māui dolphin 2015 biopsy sampling (PDF, 907K)
• Māui dolphin 2016 biopsy sampling (PDF, 7,782K)

2010-2011 abundance estimate

In 2010, DOC began field work in collaboration with the University of Auckland and Oregon State University to obtain a new abundance estimate.

During two austral summers (from February to March) in 2010 and 2011, the research team collected samples from a total of 41 different individuals. Some individuals were sampled more than once and by examining how many of the same dolphins were resampled in the second round of research against the number of new individuals sampled, a revised abundance estimate was calculated.

Key findings

• The abundance of Māui dolphin of over 1 year of age for 2010-11 was estimated to be approximately 55  with a 95% confidence interval of 48 to 69 (this means that the researchers are 95% confident that there are between 48-69 Māui dolphin over the age of 1).
• Utilising genetic samples from Māui dolphin available from 2001-07 and the current 2010-11 sampling period the rate of change for the population from 2001-11 could be estimated. The result suggests a slow decline over the past decade (-3% per year), although this trend could not be confirmed with 95% confidence.
• In 2010, DNA fingerprinting of the samples collected showed that there were two female South Island Hector's dolphins swimming with Māui dolphin. In 2011, one of those Hector's dolphins was sampled again in a similar area. This is the first record of this occurring.
• Although there is no evidence that these female Hector’s dolphins have interbred with Māui dolphin, it is possible that they can. This could enhance the genetic diversity of the Māui dolphin population.
• An individual dolphin moved about 80km in less than three weeks, with others moving in the vicinity of 30km before being sampled again. This indicates that the individuals remaining in the population can still mix amongst themselves and are not restricted to small isolated groups only.
• It seems that there are at least as many females as males in the population. Of the 41 individuals sampled, 25 were female and 16 were male. Having more females in a population usually gives the best chance of the species recovering. 

Report

The data from this report is not directly comparable with earlier aerial surveys (see 2006 estimate) because of the different methods used, but both the reports highlight that the population is very small and are indicative of a recent decline.

Estimating the abundance and effective population size of Maui’s dolphins using microsatellite genotypes in 2010–11, with retrospective matching to 2001–07 (PDF, 3,061K)

2006 estimate

The abundance estimate published in 2006 was made from extensive aerial surveys by Otago University in 2004. The researchers then used a statistical model to come up with the estimate. This suggested that there were around 111 dolphins left (with a 95% confidence interval of 48-252).

Report

A new abundance estimate for Maui’s dolphin: What does it mean for managing this critically endangered species?

Other abundance estimates

• The Scientific Committee of the International Whaling Commission (IWC) endorsed two abundance estimates for the Māui dolphin population (for the population size in 2001 and 2016) at their 2018 meeting.
• The estimates were produced by Cooke et al. using the same data used by Baker et al. for their 2016 estimate
• Cooke et al. used a more sophisticated population model to estimate the trend in abundance and to account for likely mortality over time.
• The number has not gone down from 63 to 57. The lower estimate produced by the Cooke et al. model for 2016 does not represent a decline in the Māui dolphin population from the Baker et al. estimate but is simply a reinterpretation of the existing data.
• The two estimates by Cooke et al. and the estimate by Baker et al. have been endorsed by the IWC Scientific Committee as suitable for management purposes.

Key findings

• There was estimated to be 85 Māui dolphins over 1 year of age in 2001, with a 95% confidence interval of 54 to 133.
• There was estimated to be 57 Māui dolphins over 1 year of age in 2016 with a 95% confidence interval of 44 to 75.
• The model estimated with approximately 95% probability that the population declined over the period 2001-16.
• This model can be used to make projections under different mortality scenarios to estimate the likelihood of recovery under different levels of protection.