Species richness and evenness are great components for estimating diversity. But while focusing on dominance, diversity IS part of Simpson's. I recommend you do a lot of reading before trying to do such a diversity study. A simple google search for Simpson' s Diversity Index will give you both some links for good info and some for the statistics. The U of Florida Entomology form is great, and the Kenyon page - "Since evenness and dominance are simply two sides of the same coin, their measures are complimentary." http://biology.kenyon.edu/courses/biol229/diversity.pdf and it includes another index that can compare your sites (Jaccard's). Remember, since the analysis is fairly easy, it is often beneficial to have the calculations for comparison (they are all parts of the big picture of diversity).

Since you can download free software to do the analysis, you should do both and more to see a fuller comparison of diversity from your samples.

The Shannon-Weiner index accounts for both species richness and its evenness so you can go with the Shannon-Weiner Index to estimate diversity. The Simpson index is used only to estimate the dominance of the species and it does not account for the species richness. I think you must prefer Shannon-Weiner according to your research objective. However, to interpret the outcome, you can use both.

Species richness and evenness are great components for estimating diversity. But while focusing on dominance, diversity IS part of Simpson's. I recommend you do a lot of reading before trying to do such a diversity study. A simple google search for Simpson' s Diversity Index will give you both some links for good info and some for the statistics. The U of Florida Entomology form is great, and the Kenyon page - "Since evenness and dominance are simply two sides of the same coin, their measures are complimentary." http://biology.kenyon.edu/courses/biol229/diversity.pdf and it includes another index that can compare your sites (Jaccard's). Remember, since the analysis is fairly easy, it is often beneficial to have the calculations for comparison (they are all parts of the big picture of diversity).

Hi Bekah,

I agree with Robert, it is always advisable to use different indices. As a side note, the mentioned indices can be transformed into Hill numbers (see publication below): Hill numbers can be intuitively interpreted as denoting how many species, all equally abundant, would have to be in the sample to produce the same diversity value as obtained with the actual sample. I find the use of Hill numbers not only intuitive but also simpler to communicate (e.g. to stakeholders). You can find Hill's publication (1973) on Researchgate:

https://www.researchgate.net/publication/201998256

(see also https://www.researchgate.net/publication/263743362)

All best & enjoy the experiment!

Claudio

I would add to what my colleagues have indicated that, once you decide which indexes to occupy, continue with them over time to have comparative estimates. There is nothing wrong with using others, but hopefully keeping the first ones chosen.

Good luck!

A diversity index (also called phylogenetic or Simpson's Diversity Index) is a quantitative measure that reflects how many different types (such as species) there are in a dataset (a community) and that can simultaneously take into account the phylogenetic relations among the individuals distributed among those types, such as richness, divergence or evenness.These indices are statistical representations of biodiversity in different aspects (richness, evenness and dominance).

Simpson and related indices do not helpfully measure biodiversity. They measure plant diversity. A plot with ten indigenous conservative species would typically have a good deal more biodiversity than a plot with 25 common weeds - despite the later having more species diversity. The "Floristic Quality Index" is helpful in measuring plant biodiversity. These indices are compared in a recent paper at https://journals.plos.org/plosone/article?id=10.1371/journal.pone.0241061.

this is always worth a read

http://www.loujost.com/Statistics%20and%20Physics/Diversity%20and%20Similarity/EffectiveNumberOfSpecies.htm

Dear Bekah,

You can use both Shannon and Simpson indexes for alpha diversity-species richness but also try Jaccard and Sorensen indexes (Beta diversity) which could be more appropriate in your case study (See Ricklefs and Relyea, Ecology chap 19).

Best,

Guy

If we calculate species diversity in such a community using the Shannon or Simpson index, it is the most abundant species that will have the most significant impact on the value of both indices, while less numerous and often very rare species will have a small effect on their value. Unfortunately, both of these indices give less weight to less numerous and rare species.

According to me, the most coherent means of measuring species diversity was suggested by Hill. Although Hill’s concept was underappreciated for many years, Jost has demonstrated that ‘Hill numbers of order q’ are the most coherent method combining the most commonly used indices into one simple formula. The only element linking the indices used is the exponent q. According to Jost, the diversity index based on order q is called ‘true diversity’

Article Coprophagous Hydrophilid Beetles (Coleoptera, Hydrophilidae,...

Ozodbek Abduraimov .-. One of the most important indices to many of us is a simple list of species that are present, often designated as S (or R). This is often considered similar to or better than using a phylogenetic index. Just to make sure I understand, I believe you are just giving examples of index types and not saying that this is the same as Simpson's. There are actually dozens of diversity indices and each one has it's useful characteristics (and aspects that may not be useful for a particular study). I agree with many of you to use several indices as each adds to understanding your data. Jaccard is good, and I will now need to look into the Hill numbers. Thanks Guy Lemperiere , Andrzej Górz , and Guy Lemperiere

The Simpson´s coefficient show a fair degree of faunistic similarity between regions.For example the genus Urticina (=Tealia) (Actiniaria) from Barkley Sound Canada):species of Urticina occur in both the Nearctic and Palaearctic Region.All Palaearctic species are found also in the Nearctic Region but the latter has two endemic species:U.columbiana and U.piscivora,so the Simpson´s coefficient give a figure of 71,4%,indicating a fair degree of faunistic similarity between them but the Nearctic Region is the dispersion centre of Urticina´s species because this last has two endemic species.

Try EstimateS, a free download programme... individual-based rarefaction will tell you a lot about the difference in diversity between urban versus wild. You can also calculate species richness estimates (Chao 2, Jackknife 2). PAST.3 (also free download) can calculate these indices too.

Yes, use many indices and compare.

Good suggestion from Zaal....PAST is easy to use

Best

Guy

Try new version of Past 4.2, a free download programme. You can calculate species richness estimates (Chao 2, Jackknife 2), individual-based rarefaction, and Hill numbers.

Yes good suggestion from Zool use many indices and compare, and choose the best one for your data.

Hi everyone,

a (trivial?) note of caution: it’s absolutely fine to use software to compute whatever you’re interested in, but critical thinking is part of (y)our job. It’s pointless to simply present a whole bouquet of properly computed indices in a paper or to stakeholders without an understanding of the underlying assumptions – see first couple of answers to the question. In the end, it’s a thorough understanding that will allow you to draw sensible and defensible conclusions, potentially with far-reaching implications for management.

That said, all best & happy experiment!

Claudio

Claudio Bozzuto .-. Your note is not trivial. It goes to both the potential strength of science and the problem that is plaguing science. Having the numbers (real numbers) to crunch is important, but just having a ton of statistics done to show off these calculations can be the poorest of science. While journals and reviewers want a pile of calculations, the authors and reviewers rarely seem to understand the meaning, the importance, or the value of this data. And this does not just plague young researchers, us older scientists get caught up in it as well. A real question for all of us is - can we really explain what the meaning of our data and calculations is? Not just a quick explanation of what the test does, but a deep explanation of the underlying biology.

In most if not all the studies that I have done using Shannon and Simpson's diversity metrics they are usually highly correlated. However, as I often work on mobile organisms, I prefer Simpson's index as it estimates the probability of two organisms interacting. Also, in my experience of working with environmental assessment, measures of diversity are usually poor indicators of change; my preference is on using changes in community composition (e.g. ordination).

As someone mentioned, Past software is easy to use, calculates many metrics and offers a number of different univariate and multivariate analyses. Finally, also as menitioned previously, formulate clear hypotheses and how you will test these hypotheses in your design phase (exactly the approach that you seem to be taking).

Good luck with your experiment

The index you use will surely depend upon the question being asked and on the method of collecting the data. Unfortunately, most practical work cannot approximate a complete inventory and so you will need to beware of confounding revealed richness, evenness, or diversity with completeness of survey. Beware rarefaction because it corrects the results to a number of individuals, so obscuring real differences in richness between places. Unfortunately standardising on the number of individuals (as you propose) is inappropriate, because it, too, obscures real differences in species richness between the places. I also question the focus on "biodiversity" when you will surely have some species that are seen as alien invaders and others that are seen as threatened natives. Like it or not, you need to grasp the nettle of autoecology.

Couple thoughts I'll add to the discussion:

Anne Magurran's book, Measuring Biological Diversity, is a great resource for understanding the different diversity indices and their upsides/downsides.

Also, as others have noted, it's best to use Hill numbers versus traditional diversity indices. Most quantifying biodiversity are moving in that direction; there's a lot written on the subject. Hill numbers at q=0, q=1, and q=2 are equivalent to richness, Shannon Diversity, and Simpson Diversity respectively. Chao etal. 2014 describes multiple reasons why: https://www.uvm.edu/~ngotelli/manuscriptpdfs/ChaoHill.pdf

Also, Anne Chao has a super easy to use shinyapp, iNEXT, on her website (under the software tab) that calculates Hill numbers and produces graphics that can be downloaded. She also has tons of relevant publications related to the topic of biodiversity estimation, and provides the pdfs. Plenty of material for one to read. http://chao.stat.nthu.edu.tw/wordpress/

who is have tuition fee Past program ?

I agree with Zaal Kikvidze

Presumably you are identifying the plants in the two habitats to species level. As already mentioned, all indices are highly correlated and so it probably does not matter which you decide to use. However, intuitively, Simpson's is easier to understand. Whichever formulation of this index which you use, it either tells you the probability that two plants picked at random will be the same (or different) species.

If you are interested in communicating your comparison of the two habitats to the general public, the probability given by Simpson's index is easier to explain than more complex indices of diversity.

Shannon-Weiener's index is based on randomness of samples in a site. It considers both species richness and species evenness in distribution in a sample. The value of Shannon's index increases as diversity increases.

Simpson's index accounts for proportion of species in a sample. It increases as both richness and evenness of the community increase. The higher the value of Simpson's index, the lower is the diversity.

Munira Nasiruddin -.- I am not sure if you mistyped your comment, or if I am misunderstanding it. As Simpson's Index rises (moves toward 1) it has an increase in diversity. So the earlier sentence that a rise in richness increases the index, so does evennness is correct, and both of these increase the index towards 1.

I am kind of old fashioned in that I still like the simple index of species number (S) as the easiest to 'hang my hat on,' in that it does represent a real situation, represents a real value, and is easy to understand (both by scientists and the general public). But yes, evenness is important as an ecological factor that does impact the functioning of a community. So part of the problem in understanding the responses of each other is that when we say "diversity" increases (or decreases) we often forget to explain how we are defining it. I like to start with species diversity (S) as a simple description of diversity and then discuss the impact of other factors (such as evenness) that impact how a community functions.

https://www.researchgate.net/post/Which_biodiversity_index_is_more_reliable_better_and_how_can_it_be_applied_to_a_mixed_vegetation_How_might_I_differentiate_diversity_indices_and_IVI#:~:text=In%20fact%20Simpson%20index%20is,in%20distribution%20in%20a%20sample. You can look here

I should have mentioned earlier that I addressed this very question in a paper published in 1983. The reference is Field Studies, volume 5, pages 825-832. I can provide copies for anyone who does not have access to the journal 'Field Studies'.

Shannon Weiner is a better approach to scale the biodiversity

A diversity index (also called phylogenetic or Simpson's Diversity Index) is a quantitative measure that reflects how many different types (such as species) there are in a dataset (a community) and that can simultaneously take into account the phylogenetic relations among the individuals distributed among those types, such as richness, divergence or evenness. These indices are statistical representations of biodiversity in different aspects (richness, evenness and dominance). Richness R simply quantifies how many different types the dataset of interest contains. For example, species richness (usually noted S) of a dataset is the number of different species in the corresponding species list. Richness is a simple measure, so it has been a popular diversity index in ecology, where abundance data are often not available for the datasets of interest. Because richness does not take the abundances of the types into account, it is not the same thing as diversity, which does take abundances into account. However, if true diversity is calculated with q = 0[clarification needed], the effective number of types (0D) equals the actual number of types (R).

Who has been working on this in recent years?

Agree with Richard K Johnson Sir. The Simpson index is good for such experiment.

Regards

Dr. Vinaya Tari.

Worth following

Hello,

Below you can find one of my PhD thesis publications, which precisely refer to some diversity indices calculations for Collembola communities investigated in a framework of 20 years.

https://www.sciencedirect.com/science/article/abs/pii/S0031405616301664

Best, Elaheh

A simple suggestion: why not checking rank-frequencies or rank size distributions?

By the way, Elaheh, I am interested in a pdf of your article on Collembola communities.

Best regards to you all,

Guy

Need a link to articles published on the same index? Who do you recommend their work? This is necessary for many.

Dear Elaheh Daghighi Masouleh! Thank you for recommending and attention. Best wishes, Ozodbek.

I would say neither. The biological relevancy of these indices as well as their corresponding "Hill numbers" has never been established theoretically or practically. You might like to look at Article Weighting effective number of species measures by abundance ...