Regional diversity of grape varieties is important for climate change

There was a recent paper published in the Proceedings of the National Academy of Sciences of the USA that discussed the possible effects of global climate change on the grape-growing regions of the world. The wine media focussed almost entirely on one aspect of that paper: the expected reduction in suitability of many of the current prime locations (eg. Wine regions wiped out by projected climate change, disaster for some).

However, this was not actually the main point of that paper, as is indicated by its title:

Thus, the paper makes the important point that genetic diversity of grape varieties within each grape-growing region is the key to resisting climate change. This is a basic principle of biology, that genetic variation is a Good Thing, because even if one genotype is affected by a change in conditions, others will probably not be. (For a discussion of genetics and grape varieties, see Grape clones and varieties are not always what they seem.)

The idea can be made clear by thinking about a family. One way of ensuring the long-term continuation of the family is to have lots of children, on the principle that at least some of them will survive. However, this is true only up to a point. If the children all have very similar genes (as they probably will if they all have the same two parents), then they will probably all be affected by the same sorts of problems, such as lack of resistance to a particular disease. This limitation can be addressed by having children who have lots of different genes (ie. different genotypes) — it will then take lots of different problems to affect all of them.

Biologists have long understood this principle of genetic diversity, because it applies throughout the biological world, including agriculture — putting all of your eggs in one basket is not a good long-term idea. Farmers know this perfectly well, and it was the purpose of the PNAS paper to analyze the grape-growing situation in detail, to make some predictions about what might be done in response to climate change. The bit about reduction in the suitability of many current areas was simply scene-setting. These predictions not all bad, of course — New Zealand and Germany were identified as places expected not only to survive but to gain in output, for example.

So, if grape-growers are willing to continue doing what their predecessors did, which was to grow whatever varieties did best in each local area (see Palaeogenomic insights into the origins of French grapevine diversity), then many (if not most) vineyards could continue to exist, even under quite serious effects of climate change. However, some areas will no longer be suitable for any of the currently known varieties, and may require us to develop new late-ripening varieties for the hottest areas. Also, many unplanted areas will become suitable for an increasingly broad range of the currently known varieties (see last week’s post on Climate change and the most northerly vineyards in Europe).

Genetic diversity is an important issue, because observers have sometimes expressed concern about the diversity of wine-grapes narrowing down to a few so-called “international” varieties, often presented as mono-varietal wines. That is, trying to maximize economic returns has resulted in growers specializing in a few varieties that they believe will sell well when turned into wine. So, the recent trend has been to reduce regional genetic diversity, not maintain or increase it, because the economic pressures contradict this idea. Putting all of your eggs in one basket may make short-term economic sense, but not long-term biological sense.

Current varietal diversity

This leads me to wonder which grape-growing areas currently have the most (and least) diversity of grape varieties. Surprisingly, the PNAS paper does not tell me this. So, I thought that I should work it out for myself.

I have used the data from the Database of Regional, National and Global Winegrape Bearing Areas by Variety. This compendium has vineyard area data (in hectares) from 2010, for 1,446 named grape varieties in 642 defined grape-growing regions. Some of these regions are whole countries, if their wine industry is quite small; and countries with very small vineyard areas are excluded entirely. However, most of the data refer to local regions within each country.

You will, of course, never have heard of the vast majority of the varieties! There have probably been at least 10,000 of them recorded at some time in history; and many of them are not very genetically different from each other (see: How many grape clones are there per variety?).

I have put the complete results at the bottom of this post, along with an explanation of the various ways of mathematically measuring diversity. Here, I will simply summarize the main patterns in the data.

We can start with a simple count of the number of varieties (called Richness), which turns out to vary from 1 to 258, which is a lot of grape varieties for any one location — in this case, in Verona, in Italy. Indeed, there 12 regions with > 200 varieties, as shown in the graph, all of them in Italy.

Half of the regions have 15—45 varieties, which may still be more than you were expecting. On the other hand, there are 10 regions with only one recorded grape variety, 5 of them in the USA (Arizona, Arkansas, Georgia, North Carolina, Orange), 4 in China, and 1 in Turkey.

However, for our purposes we need to look at Diversity, which takes into account what is called Evenness. Evenness, and thus diversity, is at its maximum when all of the varieties are equally abundant (measured in hectares, in this case). This means an area dominated by only a few varieties is not very diverse, even if there are lots of rare varieties in the same region. This is actually the case for those regions with the largest numbers of varieties — most of those varieties are very rare, and are thus not making a big contribution to diversity.

So, let's look at the average regional diversity for the top 20 wine-producing countries of 2019 (as listed by the International Organisation of Vine and Wine). This is shown in the table, with two mathematical measures of diversity (as explained at the bottom of the post). Diversity represents the “effective” number of varieties — the amount of diversity that would exist if all of the varieties were equally abundant.

Country Italy France Spain United States Argentina Australia Chile South Africa China Germany Portugal Russia Romania Hungary New Zealand Brazil Austria Greece Georgia Switzerland

Number of regions 110 72 36 89 28 94 9 9 10 13 9 2 8 22 11 1 4 13 1 18

Richness 83.5 30.5 31.5 17 43.5 19 29 18 2 42 102 34.5 21.5 53 9 103 35.5 20 23 36

Shannon Diversity 9.91 6.71 5.19 8.04 12.92 7.00 7.29 10.36 1.30 10.45 13.78 17.25 5.60 14.63 4.26 10.78 13.59 6.88 4.87 5.56

Simpson Diversity 5.63 4.72 3.34 5.89 7.33 4.98 4.54 8.28 1.19 6.26 8.07 11.91 3.69 9.29 3.35 5.49 8.97 4.82 3.07 2.80

So, in Italy’s case there is an average of 83 grape varieties per region (median = 83.5), which seems like a lot, but most of the varieties are very rare, so there is only as much diversity as there would be for an average of 10 varieties per region if they were equally abundant (median Shannon Diversity = 9.91). A similar situation exists for Spain, Portugal, Brazil and Switzerland — the large number of varieties does not represent a lot of diversity.

On the other hand, places like the USA, South Africa and New Zealand have far fewer varieties, but those varieties are more equally abundant, so that diversity is still fairly high.

This means that, ultimately, it is Hungary that does best in terms of grape-vine diversity, at the regional level. No matter how you measure diversity, the top local regions are in Hungary (7 regions), Italy (2 regions), Czechia (1 region), and the USA (Kentucky). Obviously, in the latter case there is not a big area of grape-vines, but there are 25 recorded varieties and these are fairly evenly abundant — this is the essence of biological diversity.

At this stage, of course, we have little idea which, if any, of these grape varieties will be suitable for wine-making in any particular region. The point, though, is that we do currently, have a lot of diversity available, if we have the incentive to do something practical with it. All it takes is a willingness to move the current varieties to new regions, with a suitable climate, and use other varieties in the current regions, when they are happy there. We can also develop new varieties from the ones we have, although it does seem like it would be easier to trial the currently available varieties first.

What the wine industry and the wine-drinking public will think about all of this is another matter. Some of those Hungarian varieties have names that you may have trouble working out how to pronounce!

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Grape variety diversity

There are two components of diversity, called richness and evenness. Richness, in this case, is simply a count of the number of varieties in the region. Evenness, on the other hand, refers to how much difference there is in abundance among the varieties (measured in hectares, in this case). Diversity will be at its maximum when all of the varieties have equal abundance, and it reduces as the varietal abundances become more uneven. Obviously, varieties are never in equal abundance in any given region — indeed, most grape varieties are very rare.

So, attempts to measure true diversity take into account both richness and evenness, Sadly, there are many mathematical ways to do this. They differ in how much mathematical weight they give to the rarer varieties, varying from equal weight down to very little. Three measures of diversity are listed for each region in the table below.

If we treat all varieties as equal (weighting using the harmonic mean) then diversity = richness. If we give a fair bit of weight (weighting using the geometric mean) then we call this the Shannon Diversity. If we apply even more weight (weighting using the arithmetic mean) then we call this the Simpson Diversity.

All three measures contain relevant (but somewhat different) information; and so it is quite usual to list all three of them.

Country Algeria Argentina Armenia Australia Austria Brazil Bulgaria Canada Chile China Croatia Cyprus Czechia Ethiopia France Georgia Germany Greece Hungary Israel Italy Japan Kazakhstan Luxembourg Mexico Moldova Morocco Myanmar New Zealand Peru Portugal Romania Russia Serbia Slovakia Slovenia South Africa Spain Switzerland Taiwan Thailand Tunisia Turkey Ukraine United Kingdom United States Uruguay

Region of planting 25 de Mayo 9 de Julio Albardon Angaco Catamarca Caucete Junin La Rioja Lavalle Lujan de Cuyo Maipu Neuquen Other-Argentina Other-Mendoza Other-San Juan Pocito Rawson Rio Negro Rivadavia Salta San Martin San Martin S San Rafael Santa Rosa Sarmiento Tunuyan Tupungato Ullum Adelaide Hills Adelaide Plains Alpine Valleys Australian Capital Territory Barossa - other Barossa Valley Beechworth Bendigo Big Rivers - other Blackwood Valley Canberra District (ACT) Canberra District (NSW) Central Ranges - other Central Victoria - other Central Western Australia Clare Valley Coonawarra Cowra Currency Creek Eastern Plains, Inland and North of WA Eden Valley Far North - Other Fleurieu - other Geelong Geographe Gippsland Glenrowan Goulburn Valley Grampians Granite Belt Great Southern Greater Perth - other Gundagai Hastings River Heathcote Henty Hilltops Hunter Hunter Valley - other Kangaroo Island King Valley Langhorne Creek Limestone Coast - other Lower Murray - other Macedon Ranges Manjimup Margaret River McLaren Vale Mornington Peninsula Mount Benson Mount Lofty Ranges - other Mudgee Murray Darling - NSW Murray Darling - VIC New England Australia North East Victoria - other North West Victoria - other Northern Rivers - other Northern Slopes - other Orange Padthaway Peel Pemberton Perricoota Perth Hills Port Phillip - other Pyrenees Queensland - other Riverina Riverland Robe Rutherglen Shoalhaven Coast South Burnett South Coast - other South West Australia - other Southern Fleurieu Southern Flinders Ranges Southern Highlands Southern NSW - other Strathbogie Ranges Sunbury Swan District Swan Hill (NSW) Swan Hill (VIC) Tasmania The Peninsulas Tumbarumba Upper Goulburn Western Australian South East Coastal Western Plains - other Western Victoria - other Wrattonbully Yarra Valley Burgenland Niederosterreich Steiermark Wien and other Bundeslander Severen tsentralen Severoiztochen Severozapaden Yugoiztochen Yugozapaden Yuzhen tsentralen British Colombia Ontario Araucania Atacama Coquimbo De Los Lagos Del Bio Bio Del Maule Metropolitana O'Higgins Valparaiso Beijing Gansu Ningxia other region Shandong ShanXi Sichuan Tianjin Xinjiang Yantai Dalmatinska Zagora Hrvatsko Primorje Istra Moslavina Other Regions Plesivica Podunavlje Pokuplje Prigorje - Bilogora Sjeverna Dalmacija Slavonija Srednja Juzna Dalmacija Zagorje-Medimurje Cechy Morava Ain Aisne Allier Alpes-de-Haute-Provence Alpes-Maritimes Ardeche Ariege Aube Aude Aveyron Bas-Rhin Bouches-du-Rhone Cantal Charente Charente-Maritime Cher Correze Corse-du-Sud Cote-d'Or Deux-Sevres Dordogne Doubs Drome Eure-et-Loire Gard Gers Gironde Haute-Corse Haute-Garonne Haute-Loire Haute-Marne Hautes-Alpes Haute-Saone Haute-Savoie Hautes-Pyrenees Haut-Rhin Herault Indre Indre-et-Loire Isere Jura Landes Loire Loire-Atlantique Loiret Loir-et-Cher Lot Lot-et-Garonne Lozere Maine-et-Loire Marne Mayenne Meurthe-et-Moselle Meuse Moselle Nievre Puy-de-Dome Pyrenees-Atlantiques Pyrenees-Orientales Rhone Saone-et-Loire Sarthe Savoie Seine-et-Marne Tarn Tarn-et-Garonne Var Vaucluse Vendee Vienne Vosges Yonne Ahr Baden Franken Hessische Bergstrass Mittelrhein Mosel-Saar-Ruwer Nahe Rheingau Rheinhesse Rhein-Pfalz Saale-Unstrut Sachsen Wurttemberg Anatoliki Makedonia, Thraki Attiki Dytiki Ellada Dytiki Makedonia Ionia Nisia Ipeiros Kentriki Makedonia Kriti Notio Aigaio Peloponissos Sterea Ellada Thessalia Vorreio Aigaio Badacsony Balatonboglar Balatonfelvidek Balatonfured-Csopak Bukk Csongrad Eger Etyek-Budai Hajos-bajai Kunsag Matra Mor Nagy-Somlo Neszmely Pannonhalma Pecs Sopron Szekszard Tokaj Tolna Villany Zala Agrigento Alessandria Ancona Arezzo Ascoli Piceno Asti Avellino Bari Barletta-Andria-Trani Belluno Benevento Bergamo Biella Bologna Bolzano-Bozen Brescia Brindisi Cagliari Caltanissetta Campobasso Carbonia-Iglesias Caserta Catania Catanzaro Chieti Como Cosenza Cremona Crotone Cuneo Enna Fermo Ferrara Firenze Foggia Forlì-Cesena Frosinone Genova Gorizia Grosseto Imperia Isernia La Spezia L'Aquila Latina Lecce Lecco Livorno Lodi Lucca Macerata Mantova Massa-Carrara Matera Medio Campidano Messina Milano Modena Monza e della Brianza Napoli Novara Nuoro Ogliastra Olbia-Tempio Oristano Padova Palermo Parma Pavia Perugia Pesaro e Urbino Pescara Piacenza Pisa Pistoia Pordenone Potenza Prato Ragusa Ravenna Reggio di Calabria Reggio nell'Emilia Rieti Rimini Roma Rovigo Salerno Sassari Savona Siena Siracusa Sondrio Taranto Teramo Terni Torino Trapani Trento Treviso Trieste Udine Valle d'Aosta Varese Venezia Verbano-Cusio-Ossola Vercelli Verona Vibo Valentia Vicenza Viterbo Hokkaido Nagano other region Yamagata Yamanashi Almaty East - Kazakhstan Other-region South - Kazakhstan West - Kazakhstan Zhambyl Aguascalientes Sonora Suma Baja California Suma Coahuila Zacatecas Auckland Canterbury Gisborne Hawkes Bay Marlborough Nelson Otago Other Regions Waikato Waipara Wairarapa Arequipa Lima Moquegua Tacna Alentejo Algarve Alto Tras-os-Montes Beira Interior Beira Litoral Entre Douro e Minho Regiao Autonoma da Madeira (PT) Regiao Autonoma dos Acores Ribatejo e Oeste Bucuresti - Ilfov Centru Nord-Est Nord-Vest Sud - Muntenia Sud-Est Sud-Vest Oltenia Vest Krasnodar Krai Rostov Oblast Juznoslovenska Malokarpatska Nitrianska Stredoslovenska Tokajska Vychodoslovenska Outside wine-growing districts Podravje - Prekmurje Podravje - Stajerska Slovenija Posavje - Bela krajina Posavje - Bizeljsko Sremic Posavje - Dolenjska Primorje - Goriska brda (Brda) Primorje - Kras Primorje - Slovenska Istra Primorje - Vipavska dolina (Vipava) Breedekloof Little Karoo Malmesbury Olifants River Orange River Paarl Robertson Stellenbosch Worcester South Korea Total Alava Albacete Alicante Almeria, Granada, Jaen, Sevilla Avila, Palencia, Salamanca, Segovia, Soria Badajoz Barcelona Burgos Caceres Cadiz Canarias Cantabria Castellon Ciudad Real Comunidad de Madrid Comunidad Foral de Navarra Cordoba Cuenca Galicia Girona, Lleida Guadalajara Guipuzcoa, Vizcaya Huelva Huesca, Teruel Illes Balears La Rioja Leon Malaga Principado de Asturias Region de Murcia Tarragona Toledo Valencia Valladolid Zamora Zaragoza Aargau Basel-Landschaft Bern Fribourg Geneva Graub_nden Jura Lucerne Neuchytel other region Schaffhausen Schwyz St. Gallen Thurgau Ticino Valais Vaud Zurich Akdeniz Ege Guney Dogu Marmara Orta Dogu Orta Guney Orta Kuzey Alameda Amador Arizona Arkansas Benton Co. Butte Calaveras Chautauqua-Erie Colorado Columbia Gorge Columbia River Columbia Valley Colusa Contra Costa Douglas Co. El Dorado Finger Lakes Fresno Georgia Glenn Horse Heaven Hills Humboldt Illinois Indiana Iowa Jackson Co. Josephine Co. Kentucky Kern Kings Lake Lake Chelan Lane Co. Los Angeles Madera Marin Marion Co. Mariposa Mendocino Merced Michigan Minnesota Missouri Monterey Napa Nevada North Carolina Ohio Orange Other New York Other W. Valley Pennsylvania Placer Polk Co. Puget Sound Rattlesnake Hills Red Mountain Riverside Sacramento San Benito San Bernardino San Diego San Joaquin San Luis Obispo San Mateo Santa Barbara Santa Clara Santa Cruz Shasta Siskiyou Snipes Mountain Solano Sonoma Stanislaus Sutter Tehama Texas Trinity Tulare Tuolumne Ventura Virginia Wahluke Slope Walla Walla Valley Washington Co. Yakima Valley Yamhill Co. Yolo Yuba

Richness 8 46 36 30 34 28 43 47 45 46 46 45 31 45 49 44 36 30 48 48 38 50 41 47 47 41 36 37 25 7 32 27 35 6 9 39 18 24 18 16 15 25 19 12 15 38 25 20 19 13 28 3 9 30 26 20 16 34 19 31 25 15 12 13 25 11 22 31 6 15 30 34 19 12 18 12 36 38 26 8 22 30 29 34 15 15 12 14 14 27 24 22 18 18 28 17 22 32 38 42 12 35 19 17 24 11 28 12 20 14 15 18 30 19 32 23 11 13 18 10 19 14 19 30 36 37 33 35 103 13 13 14 13 15 14 67 30 5 17 23 3 29 52 29 35 29 1 7 16 2 1 6 1 1 4 2 22 21 21 22 2 22 22 22 22 22 22 22 22 17 31 34 6 29 5 22 38 37 80 30 8 105 47 22 94 19 42 45 16 23 29 22 38 44 31 75 2 97 71 49 41 67 10 8 33 12 26 37 19 116 31 35 26 20 52 25 42 27 41 57 69 8 36 6 3 16 11 20 16 21 53 59 28 19 26 29 5 58 62 75 110 44 44 11 30 23 23 42 49 25 23 46 50 28 67 60 31 24 45 25 18 20 15 15 13 30 29 19 30 22 28 12 61 51 54 66 36 43 63 62 54 89 69 32 43 51 37 52 50 57 30 52 54 63 12 91 82 133 201 172 79 93 220 216 50 111 58 35 92 67 106 193 62 62 208 45 114 74 66 107 32 142 40 50 82 45 141 60 190 236 87 107 59 49 221 40 140 62 34 91 157 32 117 23 186 152 83 193 70 59 65 37 94 7 73 39 57 45 43 84 217 78 79 61 161 118 42 85 170 115 69 117 60 32 93 88 100 84 80 119 124 161 65 44 201 36 38 207 60 121 103 99 128 236 37 61 54 37 163 18 28 258 50 210 111 8 4 14 3 4 17 17 17 17 16 17 12 3 4 11 5 3 39 10 11 9 18 9 9 9 9 8 8 23 9 9 17 11 19 19 102 58 182 166 195 102 9 11 143 2 18 27 19 24 27 24 17 49 20 6 37 34 36 35 22 33 8 8 11 9 8 6 10 5 8 11 18 18 18 18 16 18 18 18 18 5 23 61 42 37 36 59 35 21 37 13 32 13 28 47 25 23 19 61 50 34 25 14 15 50 21 23 22 14 8 28 38 46 57 31 32 51 38 36 40 32 50 33 11 30 15 36 36 27 37 33 46 51 34 44 4 13 10 10 27 1 14 3 9 4 22 44 29 36 1 1 9 8 33 11 12 10 10 22 11 25 11 38 31 42 1 8 20 14 22 12 30 11 11 44 25 12 34 14 9 15 46 5 9 11 43 25 20 18 13 41 48 19 1 19 1 36 9 44 18 10 5 19 14 39 36 26 14 26 52 52 6 41 34 16 11 10 7 29 52 32 5 13 19 10 31 5 12 24 19 13 10 26 10 32 14 42

Shannon Diversity 6.32 15.26 10.89 5.13 8.01 6.41 13.88 13.97 10.36 15.93 7.84 15.22 6.96 14.04 12.01 11.28 8.50 6.53 15.84 14.82 6.46 13.83 15.26 15.21 16.35 14.13 8.25 9.52 14.18 5.27 10.56 10.10 11.79 5.66 2.42 5.91 8.45 5.32 6.93 6.55 8.25 8.51 5.69 5.36 7.85 6.96 4.10 4.84 5.84 9.60 7.13 2.06 3.44 7.20 8.72 6.79 4.86 10.18 3.93 13.31 8.08 6.57 3.76 9.00 5.69 5.99 5.66 6.92 2.99 5.52 12.75 6.15 6.27 5.11 6.61 7.45 8.90 6.04 5.58 5.03 6.09 7.06 9.42 9.11 5.50 7.12 8.30 5.60 7.15 7.87 7.63 8.28 7.36 6.50 9.55 6.04 6.03 11.79 11.86 9.68 5.79 8.70 12.37 7.79 13.68 7.58 8.07 2.14 10.44 7.42 8.56 8.08 12.18 9.46 12.39 5.43 5.55 4.79 8.25 4.88 6.55 6.93 5.02 7.04 13.60 9.22 13.57 14.56 10.78 8.46 10.99 9.77 10.39 5.99 7.47 18.80 15.34 4.44 12.08 8.80 3.00 10.30 8.91 5.66 7.29 5.61 1.00 3.20 2.34 1.54 1.00 4.55 1.00 1.00 2.72 1.05 11.64 6.13 5.55 10.24 1.90 14.02 5.21 9.14 9.32 14.32 5.75 7.92 11.62 7.00 16.57 20.82 3.19 8.30 2.18 3.72 13.56 11.14 12.60 9.10 1.77 14.23 8.96 7.92 13.26 7.87 1.42 1.73 2.32 4.76 6.80 2.53 10.11 6.95 8.47 5.88 1.82 11.37 10.20 3.76 11.33 11.06 3.11 2.81 10.56 5.38 5.40 8.08 7.49 16.04 9.51 4.13 6.80 5.17 12.14 4.81 3.38 8.87 7.31 4.19 9.66 4.81 6.20 2.97 2.65 6.42 6.63 8.61 2.61 3.33 6.01 10.57 1.35 3.31 5.93 6.28 2.83 12.69 11.91 9.82 7.51 18.19 13.40 2.20 2.20 4.87 4.90 8.72 10.46 6.94 4.14 4.64 13.40 2.27 16.84 15.79 15.80 13.20 10.45 11.17 1.89 5.38 4.15 6.88 4.10 14.75 7.43 9.16 9.90 3.79 7.69 2.64 9.62 20.85 7.34 13.13 17.84 14.54 21.88 22.27 16.95 23.02 24.32 11.61 7.70 17.97 14.72 21.78 6.45 12.32 2.83 20.49 12.83 5.67 10.06 14.89 7.78 8.88 6.18 10.16 6.93 5.36 19.25 14.05 13.53 11.09 9.27 7.79 10.65 17.12 11.94 10.47 11.72 4.48 9.78 3.76 20.04 6.16 12.95 5.32 11.71 16.06 14.81 2.54 6.97 9.89 12.62 7.88 4.23 17.20 4.44 17.08 17.38 13.28 9.39 5.44 11.42 9.62 2.62 13.76 4.81 10.90 10.72 11.67 16.78 17.98 17.61 26.42 17.85 10.76 10.00 12.45 7.22 2.90 9.93 6.73 2.97 1.63 5.81 16.90 12.76 9.86 18.39 8.73 14.94 7.32 3.09 9.09 8.35 5.53 10.83 5.53 7.59 6.66 4.22 14.34 6.86 16.59 4.66 12.54 10.54 14.64 8.87 5.71 4.37 2.63 1.53 10.87 3.54 19.06 9.27 9.27 11.52 7.30 9.88 15.13 15.25 16.81 13.50 6.73 3.88 10.81 9.26 14.00 19.02 4.62 2.79 7.53 2.32 3.46 5.05 8.11 8.55 5.71 5.98 2.21 7.15 2.74 2.25 8.98 4.50 2.40 12.41 6.29 5.65 7.31 5.61 4.15 7.18 2.50 5.23 2.32 2.06 17.17 4.26 4.03 4.93 4.34 4.26 3.58 16.71 10.77 20.77 19.65 13.78 9.00 5.60 3.31 19.57 1.68 8.06 5.18 3.54 5.62 11.50 5.57 12.62 20.37 14.13 4.08 15.94 16.32 17.00 15.29 3.76 14.85 6.39 5.90 9.07 7.65 6.67 4.54 7.91 2.37 4.52 9.60 11.79 9.60 10.36 8.86 4.50 11.41 11.32 10.09 11.76 3.55 4.14 11.84 5.54 16.32 7.10 5.76 8.07 1.36 15.13 1.58 5.39 9.22 10.85 2.99 4.16 4.99 1.91 6.61 11.65 12.71 4.07 3.58 1.32 11.65 12.48 2.75 4.51 2.68 4.14 2.42 11.22 4.05 5.53 3.91 4.53 5.98 5.28 5.83 6.28 5.30 11.00 2.93 6.84 11.79 3.66 7.79 3.65 8.94 4.77 4.44 2.81 9.29 4.19 5.87 2.86 6.47 5.46 9.24 10.33 1.00 6.31 2.22 2.72 2.70 12.76 15.88 8.73 5.54 1.00 1.00 2.26 3.91 13.37 1.79 10.59 7.67 7.87 8.40 4.54 9.48 5.22 15.27 16.28 14.26 1.00 6.34 7.87 8.10 15.92 10.01 17.74 8.33 6.42 21.51 11.27 8.14 7.81 10.39 2.82 7.59 13.43 2.01 3.05 7.28 10.01 10.39 13.39 10.55 10.96 7.33 6.91 9.69 1.00 5.34 1.00 15.49 3.88 11.90 10.10 2.26 3.50 7.97 4.95 15.82 9.74 8.39 2.52 12.87 9.27 10.42 3.46 7.51 10.59 4.55 4.45 9.25 6.66 10.31 8.16 13.33 4.02 3.86 14.12 7.22 15.39 3.34 3.73 16.08 7.66 6.35 3.16 8.90 2.23 8.47 8.10 11.30

Simpson Diversity 5.41 8.57 5.60 2.70 4.21 4.36 7.57 9.83 6.22 11.19 3.72 9.31 4.99 9.26 7.09 5.67 3.91 3.12 10.27 10.66 4.29 9.07 9.35 11.86 11.41 8.77 4.68 6.11 10.71 4.14 7.80 6.31 8.42 5.33 1.66 3.15 6.28 3.01 5.16 5.61 6.81 5.69 4.51 3.15 5.09 4.67 2.64 3.12 4.01 7.57 5.02 1.98 2.91 4.65 6.80 4.67 3.44 6.41 2.31 9.24 6.58 4.21 2.75 6.96 2.79 4.40 3.85 4.88 2.13 3.69 10.14 4.11 4.49 3.86 4.43 6.49 6.81 3.25 3.69 4.76 3.29 4.94 6.70 6.05 3.70 5.41 6.74 3.79 5.56 5.70 5.25 5.51 5.33 4.56 6.63 4.27 3.86 7.18 7.42 5.99 4.75 4.42 9.87 5.63 9.04 6.51 4.84 1.49 8.93 5.65 7.17 5.66 9.29 6.68 7.48 3.85 4.18 3.69 6.81 3.73 4.05 5.38 3.58 5.14 8.62 4.51 10.86 9.31 5.49 7.02 10.11 8.17 9.18 4.12 5.69 12.75 10.50 4.12 8.56 6.42 3.00 7.25 5.34 3.24 4.54 3.99 1.00 2.20 1.63 1.36 1.00 3.86 1.00 1.00 2.16 1.02 6.61 2.82 3.00 7.06 1.82 9.76 2.61 5.86 5.59 10.83 2.67 3.78 7.92 4.13 12.19 17.27 2.55 5.38 1.78 2.80 8.83 8.26 7.89 5.49 1.40 9.28 5.80 6.91 7.12 6.04 1.13 1.23 1.79 3.03 4.87 1.94 6.24 5.14 5.65 3.47 1.69 6.96 6.57 2.65 8.40 5.86 2.10 1.97 6.99 4.81 3.29 4.77 6.34 10.69 7.19 2.75 4.27 4.04 9.26 3.33 1.85 7.98 4.41 2.28 5.68 4.44 3.95 2.93 2.37 4.98 5.44 6.42 1.63 2.26 4.66 7.86 1.13 2.77 3.83 4.26 2.61 10.41 6.07 6.90 3.58 13.60 11.09 1.96 1.55 3.07 2.55 5.22 6.26 3.64 2.17 2.56 8.18 1.51 11.37 9.64 11.84 10.19 7.38 8.41 1.27 3.64 2.75 5.00 3.17 11.05 5.66 7.58 6.42 2.04 4.82 1.81 4.40 16.88 3.35 5.67 11.86 9.15 14.43 16.19 9.95 15.06 18.39 8.67 5.34 13.05 8.71 15.26 2.86 7.49 1.99 15.00 9.43 2.35 8.79 8.18 5.12 5.09 2.36 5.19 3.74 2.98 9.23 6.04 6.54 7.05 5.47 5.34 6.42 13.58 5.78 3.98 7.71 2.11 3.55 2.02 14.05 2.74 6.17 3.10 7.35 7.51 9.83 1.49 5.14 5.55 6.69 3.74 1.89 8.30 2.62 10.84 10.36 9.39 3.35 4.20 6.42 6.01 1.53 8.37 1.93 6.96 5.95 7.79 7.10 10.59 11.54 14.66 10.83 6.26 6.24 8.00 4.48 2.21 6.62 4.06 1.61 1.18 2.84 13.06 5.74 4.47 11.56 6.11 8.64 3.42 1.77 5.59 3.33 2.57 6.04 2.47 3.74 3.53 2.16 7.69 3.85 11.55 2.30 6.95 4.33 8.23 5.67 3.15 1.86 1.52 1.16 3.65 1.98 12.17 6.02 4.56 6.75 3.13 6.89 10.40 9.85 10.88 7.48 4.37 2.10 5.30 4.91 7.10 11.03 3.73 2.32 5.87 2.18 3.25 2.83 5.79 7.24 3.99 3.79 2.01 6.14 2.59 1.77 7.47 4.27 2.21 10.00 4.65 4.21 6.65 4.29 2.93 6.29 1.69 4.09 1.59 1.65 14.00 3.35 2.80 3.23 3.81 3.06 2.49 10.38 6.49 12.07 10.68 8.07 6.64 3.80 2.05 9.77 1.51 6.68 2.87 2.08 3.70 8.38 3.69 11.10 13.02 10.81 3.22 11.15 10.88 11.61 11.74 2.74 9.41 5.37 4.50 7.61 6.96 6.00 3.82 6.73 1.68 3.21 8.57 9.21 6.73 8.28 6.15 2.90 8.99 9.30 8.10 8.86 2.95 2.52 8.27 2.99 11.52 4.90 3.35 5.67 1.12 10.70 1.20 3.80 7.33 7.70 1.91 3.12 3.32 1.30 4.23 9.02 10.13 2.67 2.15 1.10 7.51 9.95 1.87 3.42 1.71 3.39 1.46 7.97 2.37 2.84 2.77 2.68 3.65 2.67 2.71 3.65 3.14 6.66 1.66 6.02 6.62 2.63 4.09 1.97 4.54 2.23 2.47 1.55 5.48 2.43 2.89 2.53 4.14 3.76 8.76 7.43 1.00 4.75 2.07 2.32 2.14 8.95 9.70 5.97 2.54 1.00 1.00 1.67 3.04 9.71 1.32 9.58 6.82 6.77 6.34 3.13 6.42 3.22 10.00 10.29 9.21 1.00 5.82 5.56 6.26 13.17 8.87 12.33 7.33 4.16 14.80 8.73 6.60 4.77 8.73 2.34 4.70 9.59 1.47 2.45 5.90 7.04 7.37 9.88 7.76 9.52 4.57 4.26 7.28 1.00 2.54 1.00 10.35 2.42 5.01 7.32 1.57 3.00 5.63 3.08 9.82 7.19 4.97 1.66 8.62 5.89 6.49 2.87 4.30 6.94 3.17 3.11 8.70 6.36 6.60 6.00 10.20 3.78 2.22 10.96 5.82 11.37 2.60 2.04 12.25 5.55 4.41 2.09 6.48 1.54 4.41 6.65 7.58