The first question addressed is which countries are currently providing DSI to the global dataset available through the INSDC (Figure 1). The largest providers of DSI are currently not LMICs but are the United States, China, Canada, and Japan, providing roughly half of the global dataset, although large middle-income countries such as India and Brazil are in the next wave of providers (Fig. 1a). In the two years since Rohden et al. [12] described this trend for a CBD-commissioned study the pattern has not significantly changed. Although, it is important to note that only 14.6% of all sequences in INSDC had country information available. This is down slightly from the 16% observed in the April 2019 global sequence dataset analyzed by Rohden et al. However, this does not necessarily represent a statistical trend. There are multiple factors that could cause this seeming decrease. For example, large deposits of sequences that are not appropriate for country labelling, e.g., human data could grow the dataset but decrease the amount of country-labelled DSI. This was not further investigated.

Once these DSI are made available by provider countries, the natural question is to ask “who” is using the DSI, i.e., scientists sitting in which countries are publishing (which we call “using”) and citing DSI in a publication (Fig. 1b). In order to begin to understand the provider-user relationship, it is also important to understand where the DSI they are citing comes from, i.e., which countries provided acces to the GR (Fig.1c). To summarize, most DSI is being provided and used by HICs. Although there is DSI use and provision in many different directions. These data do not support the idea of a uni-directional provider-user dichotomy.

To further understand the real-world provider-user relationship, another angle to examine is the relationship between a country’s use of its own “national DSI” (where it was the provider country of the GR) versus its use of DSI from other countries: We call this the “self:world” ratio where self-use of DSI is divided by use of DSI from all other countries (Figure 2).

Although there are significant differences in the number of scientists and the volume of use and re-use between LMICs and HICs, the relationship between a country’s use of its own DSI and use of the global DSI dataset (all non-national DSI) is relatively homogenous. A few countries have more “foreign use”, i.e. their national scientists use less relative to non-national scientists, such as Chad and Guyana. However, the vast swaths of green suggest that the ratio between national and foreign use of DSI is relatively even.

At international meetings, including the CBD Conference of the Parties, countries can form negotiating blocs that enable coordination between similar perspectives and sharing of preparation work when developing negotiating positions. These blocs often represent underlying economic similarities between countries. To understand broad trends through a similar lens used in these political discussions, we grouped countries into three overarching groups: low-income countries in a group called G-77, middle-income countries known as BRICS (Brazil, Russia, India, China, South Africa), and high-income countries under OECD (Organization of Economic Cooperation and Development). These broad groupings, although imperfect, allow for visual representations that could proxy common trends within UN political discussions.

Three significant trends can be observed in figure 3. First, the largest color block of users (counted by a publication not an individual) in each bar corresponds with the economic bloc of the country of origin of the DSI. For example, the biggest group of users using G77 DSI is G77 users. This suggests that users tend to use DSI from their own country/bloc rather than from outside. They research and publish more with “locally-sourced” DSI. This data again rejects the unidirectional provider-use hypothesis. If that hypothesis were true, then OECD users (from HICs) should be the biggest bloc in all three bars.

Second, OECD DSI is used nearly 3 times more in comparison to both BRICS-sourced DSI and G77-sourced DSI. This is shown by the difference in the height of the bars. This is likely due mostly to the fact that there is simply a lot more OECD-sourced DSI in the databases than DSI from the other blocs. Many negotiators feel strongly that DSI sourced from mega-biodiverse countries is inherently more usable and valuable than DSI from other sources. The data shown here do not support this, otherwise G77 or BRICS DSI would be used more than OECD DSI. Finally, the graph also shows that there are important gaps between the different blocs. There are fewer total DSI-related publications coming from authors in G77 and BRICS than from OECD-based authors (roughly 30-40% fewer). The use of DSI and, likely biological research in general, has lower total output as compared to OECD countries. However, the scale of the data also shows that G77 and BRICS-based authors are still quite scientifically productive. We suspect, but cannot presently confirm, that a fuller view of the author landscape would further emphasize the contribution of G77 and BRICS-based authors.

The fourth question we were able to investigate with this dataset is the geographical interconnectedness between DSI researchers. To this end, two network diagrams were built. The “providing” network displays which countries are using a given country’s DSI (i.e., the countries to which country X is providing”). And the “using” network displays the countries whose DSI are being used by country X’s scientists. These data are also helpful to show that both neighboring and distant countries use DSI from many countries.

In Figure 4, DSI provisioning and use for Malaysia, which is both a G77 member and a mega-biodiverse country, is shown as an example. In Figure 4a, many LMICs (and not just HICs) use DSI from Malaysia, for example, Zambia, India, Peru, and Mexico to name a few. Conversely, in Figure 4b, scientists in Malaysia use DSI from 68 countries. Again, here there is no evidence of a provider-use relationship in DSI usage. Rather, Malaysian scientists use (cite in publications) DSI from a wide variety of countries and economic settins including Germany, Norway, Costa Rica, and Ghana to name a few. This data complements the data presented in Figure 3a which suggests that, although scientists use their own national DSI more frequently, when they use foreign DSI they do not appear to be primarily using DSI from biodiversity-rich countries but rather DSI from across the world without any clear geographical or economic clustering patterns.

A final question that can be addressed is what the overall providing-use relationship is for every country and whether there is a global trend to this relationship. Indeed, given the linear trend displayed in figure 5, it seems that many countries provide and use DSI from a roughly equal number of countries. In other words, if scientists from a given country are providing DSI, they are often using DSI at a similar level. However, for small countries, especially LMICS, with accordingly smaller datasets and scientific communities, tend to cluster in the bottom left of the graph meaning they have little provisioning of DSI and even less scientific use of DSI.