Sunday, 18 August 2013

False positives are the worst kind of error

If in doubt leave it out

Misidentifications and unnoticed species are quite common in botanical surveys. Both lead to errors and misinformation. Failing to observe a species, when it is in-fact present, is a false negative. False negatives are fairly easy to counteract by repeat surveying and using multiple observers. False negatives can even be used to quantify the abundance of a species, since the single largest determinant of observability is abundance (Royle & Nichols, 2003;  Kéry, Royle & Schmid, 2005;  Chen, 2009, Groom, 2012).
On the other hand, false positives are a menace as they are much more difficult to resolve. They pollute our datasets and are impossible to refute with certainty. +MichaelShermer suggests that the number of false positives are greater when there is a cost associated with a false negative. For example, if the risk of a false negative were to be eaten by a tiger it would be more advantageous to make a few false positive identifications.
In the case of botanical surveying the costs are probably fairly well balanced between false negatives and false positives. However, under certain conditions one can imagine that the cost swings in either direction. For example, if a keen amateur wants to prove their botanical prowess, there is a cost to one’s ego associated with a false negative. On the other hand, a poorly paid professional ecologist may want to complete as many plots as possible in a short period, in which case the cost of a false negative reduces in comparison to a false positive.

False positives arise from several different behaviors.
  • An over-reliance on jizz, leads to dismissive identification without due consideration.
  • Inexperience of recorders, unaware of all the possible taxa that might occur.
  • Inadequate reference material, not including all the possible taxa.
  • Poor navigation, so that surveyors are outside of the survey area.

So what can be done to reduce the number of false positives?
  • Insist on a specimen for previously unobserved taxa. This can be done at a national and county level.
  • Training, not just in the identification of taxa, but also in navigation and in the consequences of misidentification.
  • When analyzing, grade observations by their sources and level of evidence (Molinari-Jobin et al., 2012).
  • Survey in a group: groups create fewer false positives (Wolf et al., 2013).
  • Don’t foster a culture where a long list is a good list. Foster a supportive, open, nonjudgmental culture where peer review is welcomed.
  • Using computer software that alerts the user if that taxon is new to the area. Never store records on paper or in spreadsheets.
  • Use a survey protocol whereby each new taxon has to be checked against at least one key character.

False positives litter our databases. They are made by everyone and in-fact experienced botanists, particularly the most confident, can be the worst offenders. Once these errors are made they contaminate the data misleading researchers and leading to many waste hours of confusion, if in doubt leave it out.

Chen, G., Kéry, M., Zhang, J., & Ma, K. (2009). Factors affecting detection probability in plant distribution studies. Journal of Ecology, 97(6), 1383–1389. doi:10.1111/j.1365-2745.2009.01560.x

Groom, Q. J. (2013). Estimation of vascular plant occupancy and its change using kriging. New Journal of Botany, 3(1), 33–46. doi:10.1179/2042349712Y.0000000014

Kéry, M., Royle, J. A., & Schmid, H. (2005). Modeling Avian Abundance From Replicated Counts Using Binomial Mixture Models. Ecological Applications, 15(4), 1450–1461. doi:10.1890/04-1120

Molinari-Jobin, A., Kéry, M., Marboutin, E., Molinari, P., Koren, I., Fuxjäger, C., … Breitenmoser, U. (2012). Monitoring in the presence of species misidentification: the case of the Eurasian lynx in the Alps. Animal Conservation, 15(3), 266–273. doi:10.1111/j.1469-1795.2011.00511.x

Royle, J. A., & Nichols, J. D. (2003). Estimating Abundance From Repeated Presence–Absence Data or Point Counts. Ecology, 84(3), 777–790. doi:10.1890/0012-9658(2003)084[0777:EAFRPA]2.0.CO;2

Wolf, M., Kurvers, R. H. J. M., Ward, A. J. W., Krause, S., & Krause, J. (2013). Accurate decisions in an uncertain world: collective cognition increases true positives while decreasing false positives. Proceedings. Biological sciences / The Royal Society, 280(1756), 20122777. doi:10.1098/rspb.2012.2777

A presentation given to the Botanical Society of the British Isles on this subject is available here. 

No comments:

Post a Comment