GBIF Content Mobilization Priorities 2017

Three main priorities for content mobilization within the GBIF network in 2017

Oecophylla smaragdina
An army of Oecophylla smaragdina ants bridging a gap. Photo by Francois Wolfaardt licensed under CC BY-NC 4.0.

GBIF is working to develop priorities to guide investment and effort in digitizing and mobilizing biodiversity data. Such priorities are important for allowing GBIF nodes and other institutions, researchers, citizen science groups, funding bodies (among others) to plan projects and work programmes that add the most valuable information possible to what we know of biodiversity patterns and trends.

The 2016 GBIF Ebbe Nielsen Challenge highlighted a range of approaches for identifying gaps or areas of ignorance within GBIF data, including gaps in taxonomic, spatial and temporal coverage. GBIF has been focused on redevelopment of GBIF.org thus far in 2017, but in the coming months, we expect to integrate some of these approaches into our data management processes, enabling us both to identify priority gaps and to measure progress toward addressing them.

That said, we can immediately highlight three general content mobilization priorities for biodiversity data. We strongly encourage all GBIF stakeholders to consider opportunities to mobilize data that will address these priorities, and we encourage funding agencies to fund activities that will contribute new data in these areas.

Priority 1 – Addressing major geospatial gaps

The current geographic coverage of data within GBIF.org is very uneven. Rich data exists for some regions on all continents, but the volume of available data remains low across massive areas. One basic measure for investigating these differences is to compare, at the country level, the average number of mobilized GBIF records per square kilometer. Mapping GBIF-mediated data in this way reveals an average of between five and several hundred records per square kilometer for most countries across western Europe, North America, Central America, northern South America, parts of east Asia, South Africa, Australia and New Zealand. Coverage across areas outside these regions is much lower, with many countries showing an average of less than one record per square kilometer.

Despite the rudimentary quality of this metric, it is clear that GBIF cannot yet represent biodiversity data patterns or fully support evaluation of species ranges in these countries.

We therefore call for the urgent mobilization of additional GBIF-compatible biodiversity data from all countries that currently have an average of less than one record per square kilometer. For reference, the table below shows the current record density for all GBIF participant countries or territories and for all other countries with land area greater than 10,000 km².

Map of species occurrences along the border between Botswana and South Africa

Priority 2 – Mobilizing sampling-event data

Historically, GBIF has served as a platform for publishing presence records for any species but has not enabled usable data on species abundance or absence. With the adoption and promotion of the sampling-event extension of the Darwin Core standard, GBIF can now support the mobilization of richer structured data from field-based research activities, which typically use a repeatable protocol to record a suite of species at a particular time and place. Such data offer opportunities for greatly improved statistical analysis and will serve as a key building block for Essential Biodiversity Variables (EBVs) for species distribution and population abundance. Encouraging sharing of these data and managing them well is critical if we are to support land-use and conservation activities and to understand changes in species abundance.

Many datasets already published through GBIF derive from survey and monitoring activities and included all the measurements necessary to deliver sampling-event data. We encourage data publishers to consider upgrading their datasets to take advantage of the expanded standard.

More generally, GBIF can now serve as the global platform for aggregating sampling-event data.

We call for agencies and organizations that carry out field surveys or manage such data to publish them for wider use through GBIF.

Vegetation transects by the Bureau of Land Management, Alaska licensed under CC BY 2.0.

Priority 3 – Digitizing natural history collections

Data from natural history specimens has always been at the core of GBIF’s work. Several countries have invested or are currently investing significantly in digitization of their historical collections. Such efforts assist taxonomists in the study of their organisms, and also contribute essential information on the distribution of countless species that in many cases are otherwise rarely recorded. Data from specimens is also often our best or only basis for understanding historical species distributions.

We call for additional investments to liberate data from all the world’s natural history collections. Such efforts will complement other content mobilization initiatives by maximizing the total taxonomic coverage of data within the network.

Herbarium sheet from the N. I. Vavilov Institute, St. Petersburg by Petr Kosina licensed under CC BY-NC 2.0.

Table: GBIF record density by country or territory

The following table includes all countries and territories that have a land area greater than 10,000 km² and all GBIF participants (marked in bold).

The data are likely best considered as a first draft toward an assessment of the density of available data for different countries. Note that the record counts include those from associated marine areas, although the areas given are limited to terrestrial portions. This is the main reason for excluding the smallest countries and territories here, since the calculation does not reflect the large maritime areas associated with many island states.

In the coming months, we plan to introduce figures on the terrestrial and marine record density for each country or territory on each country page in GBIF.org.

Country GBIF records Area in km² Data density (records/km²)
Aug 2017
Afghanistan 520354 652900 0.79
Albania 17615 27400 0.64
Algeria 128871 2381700 0.05
Andorra 127565 500 255.13
Angola 185338 1246700 0.14
Argentina 2646466 2736700 0.96
Armenia 68383 28500 2.39
Australia 38630943 7682300 5.02
Austria 3289815 82500 39.87
Azerbaijan 42864 82700 0.51
Bangladesh 76488 130200 0.58
Belarus 21470 202900 0.1
Belgium 11919631 30300 393.38
Belize 727481 22800 31.9
Benin 344065 112800 3.05
Bhutan 62914 38100 1.65
Bolivia 994823 1083300 0.91
Bosnia and Herzegovina 22569 51200 0.44
Botswana 303408 566700 0.53
Brazil 9758456 8358100 1.16
Bulgaria 196949 108600 1.81
Burkina Faso 181484 273600 0.66
Burundi 50323 25700 1.95
Cambodia 111867 176500 0.63
Cameroon 395189 472700 0.83
Canada 32422886 9093500 3.56
Central African Republic 62035 623000 0.09
Chad 15941 1259200 0.01
Chile 1323975 743500 1.78
China 2493207 9388200 0.26
Chinese Taipei 1921906 35980 53.41
Colombia 4716497 1109500 4.25
Congo, The Democratic Republic of the 517527 2267100 0.22
Costa Rica 7421733 51100 145.23
Cote d’Ivoire 228229 318000 0.71
Croatia 105425 56000 1.88
Cuba 593001 104000 5.7
Czech Republic 189121 77200 2.44
Denmark 11311455 42300 267.41
Djibouti 6901 23200 0.29
Dominican Republic 333041 48300 6.89
Ecuador 2584887 248400 10.4
Egypt 190910 995500 0.19
El Salvador 240136 20700 11.6
Equatorial Guinea 62874 28100 2.23
Eritrea 12226 101000 0.12
Estonia 1980762 42400 46.71
Ethiopia 322671 1000000 0.32
Fiji 182890 18300 9.99
Finland 3339200 303900 10.98
France 34902830 547600 63.73
Gabon 239484 257700 0.92
Gambia 58699 10100 5.81
Georgia 54581 69500 0.78
Germany 23956555 348900 68.66
Ghana 277661 227500 1.22
Greece 629461 128900 4.88
Greenland 254161 410500 0.61
Guatemala 710727 107200 6.62
Guinea 90320 245700 0.36
Guinea-Bissau 30091 28100 1.07
Guyana 403520 196900 2.04
Haiti 165875 27600 6
Honduras 752627 111900 6.72
Hungary 195275 90500 2.15
Iceland 994793 100300 9.91
India 3449923 2973200 1.16
Indonesia 1670855 1811600 0.92
Iran 289433 1628800 0.17
Iraq 36563 434300 0.08
Ireland 1174840 68900 17.05
Israel 984654 21600 45.58
Italy 949648 294100 3.22
Jamaica 411364 10800 38.08
Japan 3967409 364600 10.88
Jordan 38691 88800 0.43
Kazakhstan 114695 2699700 0.04
Kenya 712053 569100 1.25
Kuwait 115638 17800 6.49
Kyrgyz Republic 51947 191800 0.27
Lao PDR 104950 230800 0.45
Latvia 44735 62200 0.71
Lebanon 35438 10200 3.47
Lesotho 97667 30400 3.21
Liberia 103575 96300 1.07
Libya 31564 1759500 0.01
Lithuania 24582 62700 0.39
Luxembourg 978358 2600 376.29
Macedonia 38053 25200 1.51
Madagascar 1179979 581800 2.02
Malawi 181751 94300 1.92
Malaysia 816069 328600 2.48
Mali 47512 1220200 0.03
Mauritania 41493 1030700 0.04
Mexico 14354653 1944000 7.38
Moldova 17466 32900 0.53
Mongolia 172833 1553600 0.11
Montenegro 16082 13500 1.19
Morocco 520848 446300 1.16
Mozambique 196171 786400 0.24
Myanmar 123970 653100 0.18
Namibia 743897 823300 0.9
Nepal 189159 143400 1.31
Netherlands 19351155 33700 574.21
New Caledonia 411067 18300 22.46
New Zealand 5127683 263300 19.47
Nicaragua 603478 120300 5.01
Niger 28835 1266700 0.02
Nigeria 200928 910800 0.22
North Korea 13627 120400 0.11
Norway 24539876 365200 67.19
Oman 133332 309500 0.43
Pakistan 215107 770900 0.27
Panama 1685983 74300 22.69
Papua New Guinea 1128779 452900 2.49
Paraguay 566276 397300 1.42
Peru 2737747 1280000 2.13
Philippines 1034610 298200 3.46
Poland 1692371 306200 5.52
Portugal 2527546 91600 27.59
Qatar 22564 11600 1.94
Rep. Congo 70249 341500 0.2
Romania 246259 230100 1.07
Russian Federation 1701308 16376900 0.1
Rwanda 65172 24700 2.63
Saudi Arabia 115999 2149700 0.05
Senegal 147567 192500 0.76
Serbia 124870 87500 1.42
Sierra Leone 68624 72200 0.95
Slovak Republic 187711 48100 3.9
Slovenia 297435 20100 14.79
Solomon Islands 137194 28000 4.89
Somalia 52006 627300 0.08
South Africa 23791283 1213100 19.61
South Korea 1637683 97500 16.79
South Sudan 3526 619745 0.01
Spain 23917747 500200 47.81
Sri Lanka 219933 62700 3.5
Sudan 76199 1886068 0.04
Suriname 277061 156000 1.77
Swaziland 250657 17200 14.57
Sweden 84530756 407300 207.53
Switzerland 1639073 39500 41.49
Syrian Arab Republic 67646 183600 0.36
Tajikistan 30494 138800 0.21
Tanzania 701269 885800 0.79
Thailand 973171 510900 1.9
Timor-Leste 15333 14900 1.02
Togo 43836 54400 0.8
Tunisia 198188 155400 1.27
Turkey 1001615 769600 1.3
Turkmenistan 23418 469900 0.04
Uganda 352753 200500 1.75
Ukraine 194429 579300 0.33
United Arab Emirates 429856 83600 5.14
United Kingdom 18410857 241900 76.1
United States 256869948 9147400 28.08
Uruguay 132565 175000 0.75
Uzbekistan 35761 425400 0.08
Vanuatu 92455 12200 7.57
Venezuela 1254368 882100 1.42
Vietnam 300706 310100 0.96
Yemen 96428 528000 0.18
Zambia 207091 743400 0.27
Zimbabwe 373722 386900 0.96