Species distribution modelling (SDM) is widely used to predict suitable habitats of living organisms based on niche conservatism on a global scale.

I used a “Maxent” (machine-learning technique called “maximum entropy modelling”) to model comfortable habitat for Homo sapiens, based on the current location of settlements. Maxent software (version 3.4.1) was downloaded from biodiversityinformatics.amnh.org

Maxent software for modelling species niches and distributions by applying a machine-learning technique called maximum entropy modelling. From a set of environmental (e.g., climatic) grids and georeferenced occurrence localities, the model expresses a probability distribution where each grid cell has predicted suitability of conditions for the species. For the map cells predicted using Maxent, cells with values of 1 had the highest degree of habitat suitability, while cells with values of 0 had the lowest. Habitat suitability was determined based on the climatic similarity to sites where the species already occur. The predictive precision of Maxent was based on the area under the curve (AUC) of the receiver operating characteristic (ROC), which regards each value of the prediction result as a possible threshold; the corresponding sensitivity and specificity were obtained through calculations. AUC ranges from 0.5 (lowest predictive ability or not different from a randomly selected predictive distribution) to 1 (highest predictive ability).

I selected towns and cities in the world with 100, 1000, 10000 and 100000 inhabitants and used 19 bioclimatic variables to model the potentially suitable environmental distribution of Homo sapiens. Bioclimatic variables were downloaded from the global database WorldClim (www.worldclim.org) at a spatial resolution of 30 arcseconds.

Settlements with more than 100 inhabitants

The MaxEnt model generated continuous probability values for the presence of Homo sapiens, ranging from 0 to 1. To delineate the presence/absence map of Homo sapiens, those continuous probability values were converted to the binary prediction based on a threshold probability value. This threshold probability was determined according to the ‘maximum training sensitivity plus specificity’ criterion.

The MaxEnt model for Homo sapiens showed a reliable prediction with an AUC of 0.684 (settlements with 100 inhabitants), 0.671 (1000) 0.709 (10,000), 0.778 (settlements with 100,000 inhabitants), higher than the 0.5 of a random model.

The most crucial bioclimatic variable determining the geographical distribution of Homo sapiens is bio 1 (Annual Mean Temperature).

Bioclimatic variables determining the geographical distribution of humans

Variable Percent contribution Permutation importance Annual Mean Temperature (bio 1) 51.5 46.3 Mean Temperature of Warmest Quarter (bio 10) 14.5 7.8 Mean Diurnal Range (bio 2) 12.1 10.5 Annual Precipitation (bio 12) 5.4 2.3 Precipitation of Wettest Month (bio 13) 4.2 5.2 Isothermality (bio 3) 3.2 5.8 Precipitation of Wettest Quarter (bio 16) 1.3 0.6 Precipitation of Coldest Quarter (bio 19) 1.2 1.8 Temperature Seasonality (bio 4) 1.2 2.4 Precipitation Seasonality (bio 15) 1.1 2.9 Mean Temperature of Wettest Quarter (bio 8) 1 2.2 Precipitation of Warmest Quarter (bio 18) 1 0.7 Mean Temperature of Coldest Quarter (bio 11) 0.8 3.7 Temperature Annual Range (bio7=bio5-bio6) 0.4 2.5 Temperature Seasonality (bio 5) 0.4 2.6 Min Temperature of Coldest Month( bio 6) 0.3 1 Mean Temperature of Driest Quarter (bio 9) 0.3 1.4 Precipitation of Driest Quarter (bio 17) 0.2 0.1 Precipitation of Driest Month (bio 14) 0.1 0.1

The most suitable habitats for Homo sapiens

Brazil is the biggest country in the World

The largest countries in the world by area suitable for a comfortable life

Country Area, km2 Density, persons per sq. km. Brazil 7898248 23.65469933 The United States 6991005 42.89030075 China 4843361 271.0880127 Australia 4776039 4.252520084 Russia 4307021 33.42290115 India 2944274 385.2909851 The Democratic Republic of the Congo 2313982 25.38500023 Argentina 2166524 17.8845005 Mexico 1833246 56.87530136 Canada 1814045 17.78930092 Kazakhstan 1705307 8.919569969 Indonesia 1574702 143.5590057 Sudan 1378900 26.76029968 Iran (Islamic Republic of) 1233109 56.29719925 Angola 1230781 13.07719994 South Africa 1127262 42.52659988 Ethiopia 1103404 71.58380127 Saudi Arabia 1044361 22.6093998 Colombia 1004135 4.476069927 United Republic of Tanzania 940153 40.92720032 Bolivia 923239 9.945440292 Peru 904861 30.14189911 Venezuela 858221 31.14069939 Nigeria 857719 164.8049927 Mozambique 783826 26.19540024 Turkey 760249 95.98130035 Namibia 748179 2.69946003 Zambia 718028 15.98589993 Burma 662999 72.34889984 Ukraine 596350 78.67449951 Mali 590550 19.66150093 Madagascar 587809 31.7154007 Kenya 578771 61.50780106 Botswana 576386 3.185260057 Central African Republic 557524 7.517930031 Somalia 547183 14.97929955 France 538044 113.3560028 Chad 520160 19.5048008 Thailand 511147 123.2580032 Spain 502900 86.29450226 Chile 476065 34.22869873 Cameroon 464266 38.32960129 Afghanistan 444905 56.34329987 Pakistan 424016 372.8179932 Papua New Guinea 399083 15.20919991 Paraguay 398814 14.80480003 Zimbabwe 386007 33.98820114 Japan 361710 353.5889893 Germany 356424 231.8930054 Congo 343945 10.49540043 Turkmenistan 343449 14.07269955 Niger 338183 3.922189951 Uzbekistan 335833 79.18560028 Viet Nam 323885 262.5270081 Cote d’Ivoire 320375 58.00920105 Morocco 317475 96.05480194 Poland 311412 122.6529999 Italy 289100 20.28580093 Iraq 286003 97.88700104 Mauritania 285533 10.37749958 Yemen 282036 74.79779816 Philippines 278835 303.2839966 Malaysia 273477 93.80310059 Sweden 272992 33.10739899 Burkina Faso 272333 51.1629982 Algeria 261666 125.5579987 Gabon 260110 4.962100029 Egypt 253863 286.9649963 Uganda 241814 119.7080002 United Kingdom 239574 251.4660034 Ghana 238532 9.447369576 Romania 236747 91.35299683 Lao People’s Democratic Republic 229923 24.63389969 New Zealand 225904 18.1364994 Libyan Arab Jamahiriya 213145 27.76619911 Guyana 210422 3.514230013 Finland 210017 24.97890091 Belarus 207724 47.15530014 Guinea 207170 43.45539856 Senegal 195669 6.015429974 Syrian Arab Republic 182108 103.7509995 Cambodia 181681 76.8132019 Uruguay 177747 18.71050072 Ecuador 172098 75.89279938 Norway 155983 29.73940086 Suriname 144975 3.121010065 Bangladesh 134637 113.8479996 Nicaragua 127660 42.78969955 Greece 127595 86.99189758 Eritrea 119257 37.95769882 Malawi 118522 111.5920029 Nepal 117598 230.3919983 Benin 116066 73.15059662 Honduras 111721 6.117119789 Bulgaria 109725 70.58180237 Guatemala 108718 116.9039993 Cuba 107517 104.7269974 Korea, Democratic People’s Republic of 106665 221.3999939 Oman 98887 25.3526001 Korea, Republic of 95774 499.8210144 Hungary 92989 108.4690018 Portugal 90836 115.9039993 Mongolia 89590 28.8057003 Serbia 87722 112.4349976 Liberia 83933 41.00650024 French Guiana 83435 2.302380085 Kyrgyzstan 82617 62.98400116 Azerbaijan 82016 101.8339996 Tunisia 80647 125.2949982 Czech Republic 78752 129.4160004 Panama 73260 44.11000061 Sierra Leone 71088 78.58429718 Austria 70602 117.4469986 Western Sahara 70504 6.246850014 United Arab Emirates 69092 59.40330124 Ireland 68312 60.65250015 Sri Lanka 65517 291.8439941 Lithuania 64977 52.71210098 Latvia 64420 35.73099899 Tajikistan 62602 104.6330032 Iceland 61426 4.814439774 Togo 57103 109.2509995 Croatia 55451 8.208129883 Jordan 55218 100.4029999 Georgia 53897 82.99919891 Bosnia and Herzegovina 51539 75.96649933 Costa Rica 49838 86.82589722 Slovakia 48648 110.7340012 Dominican Republic 47866 197.8359985 Estonia 44917 29.92880058 Denmark 41588 130.253006 Taiwan 35693 644.3839722 Netherlands 34599 47.19120026 Republic of Moldova 33693 115.0579987 Guinea-Bissau 33121 48.21500015 Switzerland 30782 241.1929932 Belgium 30626 339.5169983 Lesotho 30306 65.36100006 Albania 28054 112.4160004 Burundi 27182 289.1170044 Haiti 26680 348.4370117 Equatorial Guinea 26649 18.16570091 Bhutan 26452 24.08180046 Rwanda 25117 367.631012 The former Yugoslav Republic of Macedonia 24858 81.81089783 Solomon Islands 23992 19.69070053 Armenia 23633 127.6880035 Belize 21672 12.71440029 Djibouti 21225 37.88959885 El Salvador 20510 325.1270142 Slovenia 20309 98.45020294 Israel 20041 333.9169922 New Caledonia 18102 12.93700027 Fiji 17404 47.57789993 Swaziland 17122 65.67739868 Timor-Leste 14503 73.59059906 Montenegro 13459 45.1719017 Vanuatu 11885 18.12080002 Falkland Islands (Malvinas) 10963 0.271367013 Bahamas 10855 29.78300095 Qatar 10732 74.18800354 Jamaica 10707 250.5339966 Gambia 10596 152.6069946 Lebanon 9979 40.19179916 Kuwait 9890 223.802002 Cyprus 9023 92.68769836 Puerto Rico 8830 446.973999 French Southern and Antarctic Lands 6881 0 Palestine 6255 601.4400024 Brunei Darussalam 5606 66.68409729 Trinidad and Tobago 4914 269.3779907 Cape Verde 3368 150.477005 Samoa 2664 69.0109024 Luxembourg 2583 176.776001 Reunion 2518 311.8190002 Greenland 2478 23.19409943 Mauritius 1966 631.3189697 Guadeloupe 1595 274.8609924 Comoros 1580 505.0010071 French Polynesia 1475 173.3099976 Faroe Islands 1284 37.5428009 Martinique 1075 368.2749939 Sao Tome and Principe 982 155.4199982 Hong Kong 859 8215.849609 Dominica 719 94.33519745 Netherlands Antilles 714 261.053009 South Georgia South Sandwich Islands 709 0.042313099 Еland Islands 654 44.66970062 Saint Lucia 627 25.71610069 Micronesia, Federated States of 567 194.1060028 Bahrain 562 1289.660034 Guam 549 30.70490074 Tonga 545 182.3139954 Isle of Man 536 146.1880035 Singapore 531 8149.660156 Barbados 444 657.507019 Antigua and Barbuda 424 195.8470001 Palau 404 49.81930161 Northern Mariana Islands 387 207.3849945 Grenada 376 279.8859863 Saint Vincent and the Grenadines 375 317.6990051 Turks and Caicos Islands 375 65.22399902 Andorra 363 202.4329987 Mayotte 343 0.620990992 Seychelles 325 263.1749878 United States Virgin Islands 316 352.5570068 Saint Helena 303 21.11879921 Malta 296 1360.189941 Niue 244 6.688519955 Saint Kitts and Nevis 243 202.2140045 Cayman Islands 230 198.2220001 Saint Pierre and Miquelon 213 29.79339981 Heard Island and McDonald Islands 193 0 Aruba 184 559.2230225 Cook Islands 179 78.12290192 American Samoa 173 370.2369995 Liechtenstein 170 203.5180054 Kiribati 151 609.2910156 British Virgin Islands 109 201.9819946 Jersey 109 918.1829834 Wallis and Futuna Islands 102 147.8329926

Population density

Alex Egoshin

www.vividmaps.com

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