I have read already dozens of book chapters and papers on the notation of Anne Chao et al. on how they define abundance based diversity data and incidence based diversity data. Abundance based means that for an ("plotless"?) area there is a complete (?) count of, let´s say all tree species and their respective number. Incidence based data refers to the case when I have sampling units spread across an area and list the species in these sampling units. Then, the information on the species is reduced to presence/absence and I count in how many plots a species occured in order to have some kind of information on the species frequency.
However, what do I do if I have counted all tree indivduals of trees in let´s say 30 plots? That was done for three different regions (which I want to compare), I counted about 5000 individual trees, in total and now one tells me that I have to reduce the count to 0/1? Or is it allowed to pool the data (see Gotelli and Colwell 2001) and sum up all individuals for one region? Is this then still a "true" abundance data set? Am I corrupting any rules then?
I hope that someone has a good explanation :)
Cheers
Gotelli, N. J., & Colwell, R. K. (2001). Quantifying biodiversity: procedures and pitfalls in the measurement and comparison of species richness. Ecology letters, 4(4), 379-391.
Both Abundance and Incidence are population ecological concepts that are concerned with relative exemplification of a species in a given ecosystem. The two terms relate to species richness and diversity. As observed in Ecology Letters, (2005) 8: 148–159 the number of species recorded in a sample (or a set of samples) is very sensitive to the number of individuals or samples observed or collected, which in turn is influenced by the effective area that is sampled and, in replicated designs, by the spatial arrangement of the replicates. Thus, many measures reported as ‘species richness’ are effectively measures of species density: the number of species collected in a particular total area. For quadrat samples or other methods that sample a fixed area, species density is expressed in units of species per specified area. Even for traps that collect individuals at a single point (such as a pitfall trap), there is probably an effective sampling area that is encompassed by data collection at a single point.
Chao et al., 2005. A new statistical approach for assessing similarity
of species composition with incidence and abundance data. Ecology Letters, (2005) 8: 148–159
Dear Rodrigo,
thank you for your comments. Here a quick explanation what´s going on. I am involved in a study that wants to determine the woody plant diversity of three different coffee systems; natural coffee forests, semi-natural coffee forests and home garden coffee forests. My colleagues in Ethiopia sampled 30 vegetation plots 20x20m each. They did this before I came up with the idea of richness estimation in order to control the bias in the richness estimates. They counted individual trees, hence I thought it would be a great data set to use the abundance-based estimators. However, after reading more and more I got confused if I should not "downgrade" the data to incidence data... That would be a pity because a lot of time was invested.
Hence, I want to know if it is okay to pool the abundances of species per coffee system type, i.e. make 30 plots equal to one sample with abundances added, OR must I downgrade to incidence as the samples are only a partition of the complete area of that particular coffee system.
I looked into many many publications and books, but I never found the answer to this. Closes came Gotelli and Colwell (2001) who acutally cite a much older study, i.e. (Engstrom & James 1981).
Engstrom, R.T. & James, F.C. (1981). Plot size as a factor in winter
bird-population studies. Condor, 83, 34±41.
On page 380 Gotelli and Colwell (2001) give the context:
"Sample- and individual-based data sets are sometimes
treated interchangeably in statistical analyses. For example,
depending upon the scale of interest or the focus of a
hypothesis (in the sense of Scheiner et al. 2000), a group of
individual-based datasets or mass samples can be analysed as
if they were replicate samples from the same statistical
universe (e.g. Grassle & Maciolek 1992). Likewise, a set of
replicated samples can usually be pooled and treated as a
single, individual-based dataset, for some purposes
(Engstrom & James 1981). (This is not possible with
m-species-list curves, since abundances are not recorded.)"
So, I guess it is okay to "pool" species abundances into one single dataset. But this is never mentioned explicitely. Any more (recent) examples of studies that do so, are welcome! :)
Dear Rodrigo,
that is pretty helpful, and an interesting topic, too (biodiversity ~ restoration). Most interesting is the fact that Tropek et al. used relative cover for the vascular plants. This is something I always was afraid of, as the methods clearly (?) depend on abundance "counts". Anyway, this is another problem :) Actually, I already asked Chao and Jost etc. but never got any answer. What a pity. Thanks for your thoughts! I will now pool the dataset and refer to Gotelli & Colwell 2001 and Tropek et al. 2010.
best regards from Hamburg
Dear Jens,
I do not understand yet, why you want to pool all 30 plots per region to one. For a comparison of the diversity of the 3 regions (let´s say the Shannon indices calculated for each plot) you do not need Chao´s statistics. But do you want to calcalute Chao´s indices at all?
The same distinction between abundance based and incidence based data is made for example for the calculation of rarefaction curves. I do not know if this helps to solve your problem, but may be you can have a look in our old paper on rarefaction techniques attached (in German).
Kind regards
Roland
Abundance or Incidence diversity data? - ResearchGate. Available from: https://www.researchgate.net/post/Abundance_or_Incidence_diversity_data2 [accessed Sep 23, 2016].
Article Rarefaction-Methoden und ihre Einsatzmöglichkeiten bei der z...
Dear Roland,
thank you very much for that seeminlgy interesting article. I did not have time to read but will do asap. I am pooling the plots in order to apply the richness estimators of Anne Chao (https://github.com/AnneChao/SpadeR). Her team wrote an R-Package called SpadeR in which all the most recent richness estimators are available. However, these estimators require each community to be represented by one single vector. As I have 30 samples per community (NFC is for example one community), I somehow have to combine them.
Note that my aim is not to compare the average diversity per plot, then I would cleary know how to deal with that. And for sure, there are other solutions than Anne Chao´s bewildering set of estimators. However, they are the most recent ones all developed to circumvent the drawback of the "standard" estimators.
I will check out your rarefaction paper. Yet, rarefaction in my case is actually not necessary, as the sample size is equal.
Still, many thanks for your ideas and the paper!
best
Jens
Dear Jens,
thanks for the information and the interesting link. Now I can understand your problem much better - and I have do admit that I can not be of any further help, sorry. Rarefaction indeed is not necessary in your case...
Best wishes and kind regards
Roland
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