Quantifying collaboration potential and building scenarios
This protocol is extracted from research article:
Navigating the complexities of coordinated conservation along the river Nile
Sci Adv, Apr 3, 2019; DOI: 10.1126/sciadv.aau7668

We compared three collaboration scenarios for the Nile basin. We developed the partial collaboration scenario by quantifying and mapping the strength of potential collaboration among Nile basin countries using a similar framework to Levin et al. (16), in combination with a detailed understanding and discussion of the current politics and historical legacies of the Nile basin.

Many factors affect the likelihood of a country collaborating, including socioeconomic factors such as trade, GDP, and political factors such as governance, corruption, and democracy (16). We worked off the assumption that, when countries have strong connections in the above categories, they are more likely to collaborate in conservation. We did not account for the geographical distance between countries because we assume that this is also reflected in the other variables (e.g., trade statistics) that we analyzed.

To estimate the strength of collaboration potential, we constructed matrices quantifying the relative strength of trade connections for all commodity types between Nile basin countries, for marine commodities only, and for environmental agreements signed. Trade statistics (imports and exports) were obtained from the global Trade Map (www.trademap.org/Index.aspx), which is based on the United Nations Commodity Trade Statistics Database (http://comtrade.un.org). We collated trade statistics for the year 2012 because this was the most recent year with data available for all countries except for South Sudan and Eritrea for which there was no data on imports and exports within the Nile basin (figs. S3 and S4). We used the trade matrices to examine the economic connections between countries by calculating the relative share of each country’s exports and imports to and from each of the other Nile basin countries. We ranked the values in each of the matrices from highest to lowest (e.g., the country importing or exporting the most ranked first) to standardize the matrices and allow comparison between different variables. We then calculated the median rank between each of the 55 possible connections to give a single composite score of trade connections.

The composite trade and environmental agreement matrices were then illustrated spatially as networks; connections were mapped with weighted lines between capital cities to allow for easier visualization (Fig. 3). We used the strength of these connections as a proxy for the likelihood of two countries collaborating in conservation planning (16). These matrices were used to inform and support our decision on the partial collaboration scenario, along with an understanding of the geopolitics.

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