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Assessing uncertainty in sighting records: an example of the Barbary lion.

Lee TE, Black SA, Fellous A, Yamaguchi N, Angelici FM, Al Hikmani H, Reed JM, Elphick CS, Roberts DL - PeerJ (2015)

Bottom Line: We find that asking experts to provide scores for these three aspects resulted in each sighting being considered more individually, meaning that this new questioning method provides very different estimated probabilities that a sighting is valid, which greatly affects the outcome from an extinction model.We consider linear opinion pooling and logarithm opinion pooling to combine the three scores, and also to combine opinions on each sighting.We find the two methods produce similar outcomes, allowing the user to focus on chosen features of each method, such as satisfying the marginalisation property or being externally Bayesian.

View Article: PubMed Central - HTML - PubMed

Affiliation: Mathematical Institute, University of Oxford , UK.

ABSTRACT
As species become rare and approach extinction, purported sightings can be controversial, especially when scarce management resources are at stake. We consider the probability that each individual sighting of a series is valid. Obtaining these probabilities requires a strict framework to ensure that they are as accurately representative as possible. We used a process, which has proven to provide accurate estimates from a group of experts, to obtain probabilities for the validation of 32 sightings of the Barbary lion. We consider the scenario where experts are simply asked whether a sighting was valid, as well as asking them to score the sighting based on distinguishablity, observer competence, and verifiability. We find that asking experts to provide scores for these three aspects resulted in each sighting being considered more individually, meaning that this new questioning method provides very different estimated probabilities that a sighting is valid, which greatly affects the outcome from an extinction model. We consider linear opinion pooling and logarithm opinion pooling to combine the three scores, and also to combine opinions on each sighting. We find the two methods produce similar outcomes, allowing the user to focus on chosen features of each method, such as satisfying the marginalisation property or being externally Bayesian.

No MeSH data available.


The distribution of ‘best’ estimates pooled over the expert opinions.The middle line marks the median over the sightings, the box represents the interquartile range, and the whiskers provide the range, excluding outliers (which are indicated by crosses).
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fig-6: The distribution of ‘best’ estimates pooled over the expert opinions.The middle line marks the median over the sightings, the box represents the interquartile range, and the whiskers provide the range, excluding outliers (which are indicated by crosses).

Mentions: Overall, linear and logarithm pooling provide similar outcomes (Fig. 6), with both providing a median valid probability of approximately 0.65 for all sightings. This is lower than the median valid probability under Q1, with an average pooling, which is over 0.75 for both Algeria and Morocco. Weighting experts according to perceived expertise shifts the median up in all cases, implying those that were perceived more qualified had stronger confidence in the sightings overall. This effect is more noticeable in Q1 than in Q2–Q4, implying that liner and logarithm pooling are more robust to variance in expertise.


Assessing uncertainty in sighting records: an example of the Barbary lion.

Lee TE, Black SA, Fellous A, Yamaguchi N, Angelici FM, Al Hikmani H, Reed JM, Elphick CS, Roberts DL - PeerJ (2015)

The distribution of ‘best’ estimates pooled over the expert opinions.The middle line marks the median over the sightings, the box represents the interquartile range, and the whiskers provide the range, excluding outliers (which are indicated by crosses).
© Copyright Policy - open-access
Related In: Results  -  Collection

License
Show All Figures
getmorefigures.php?uid=PMC4562256&req=5

fig-6: The distribution of ‘best’ estimates pooled over the expert opinions.The middle line marks the median over the sightings, the box represents the interquartile range, and the whiskers provide the range, excluding outliers (which are indicated by crosses).
Mentions: Overall, linear and logarithm pooling provide similar outcomes (Fig. 6), with both providing a median valid probability of approximately 0.65 for all sightings. This is lower than the median valid probability under Q1, with an average pooling, which is over 0.75 for both Algeria and Morocco. Weighting experts according to perceived expertise shifts the median up in all cases, implying those that were perceived more qualified had stronger confidence in the sightings overall. This effect is more noticeable in Q1 than in Q2–Q4, implying that liner and logarithm pooling are more robust to variance in expertise.

Bottom Line: We find that asking experts to provide scores for these three aspects resulted in each sighting being considered more individually, meaning that this new questioning method provides very different estimated probabilities that a sighting is valid, which greatly affects the outcome from an extinction model.We consider linear opinion pooling and logarithm opinion pooling to combine the three scores, and also to combine opinions on each sighting.We find the two methods produce similar outcomes, allowing the user to focus on chosen features of each method, such as satisfying the marginalisation property or being externally Bayesian.

View Article: PubMed Central - HTML - PubMed

Affiliation: Mathematical Institute, University of Oxford , UK.

ABSTRACT
As species become rare and approach extinction, purported sightings can be controversial, especially when scarce management resources are at stake. We consider the probability that each individual sighting of a series is valid. Obtaining these probabilities requires a strict framework to ensure that they are as accurately representative as possible. We used a process, which has proven to provide accurate estimates from a group of experts, to obtain probabilities for the validation of 32 sightings of the Barbary lion. We consider the scenario where experts are simply asked whether a sighting was valid, as well as asking them to score the sighting based on distinguishablity, observer competence, and verifiability. We find that asking experts to provide scores for these three aspects resulted in each sighting being considered more individually, meaning that this new questioning method provides very different estimated probabilities that a sighting is valid, which greatly affects the outcome from an extinction model. We consider linear opinion pooling and logarithm opinion pooling to combine the three scores, and also to combine opinions on each sighting. We find the two methods produce similar outcomes, allowing the user to focus on chosen features of each method, such as satisfying the marginalisation property or being externally Bayesian.

No MeSH data available.