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, island or territory||GBIF records||Area in km²||Data density (records/km²)
|Bosnia and Herzegovina||22569||51200||0.44|
|Central African Republic||62035||623000||0.09|
|Congo, The Democratic Republic of the||517527||2267100||0.22|
|Papua New Guinea||1128779||452900||2.49|
|Syrian Arab Republic||67646||183600||0.36|
|United Arab Emirates||429856||83600||5.14|