Biodiversity Informatics, 11, 2016, pp. 23-39 COMPLETENESS OF DIGITAL ACCESSIBLE KNOWLEDGE OF PLANTS OF BENIN AND PRIORITIES FOR FUTURE INVENTORY AND DATA DISCOVERY JEAN COSSI GANGLO* AND SUNDAY BERLIOZ KAKPO Laboratory of Forest Sciences, Faculty of Agricultural Sciences, University of Abomey- Calavi, 03 BP 393, Cotonou, Benin. *Corresponding author: [email protected]. Abstract.—Discovery of and access to primary biodiversity data are critical components in informed decision-making regarding sustainable use of biological resources and conservation of biodiversity. Primary biodiversity data are increasingly available from Benin, but information about completeness of this information across the country is still lacking for most groups. This study analyzed the Digital Accessible Knowledge regarding the plants of Benin to identify gaps in both geographic and environmental dimensions. Many gaps exist in plant data for Benin, particularly in the northern most departments; central and southern Benin are better known, but some gaps remain even there. The resulting view of Beninese Digital Accessible Knowledge can guide future inventory and data discovery efforts. Key words.—Benin, inventory completeness, data cleaning, digital accessible knowledge, gaps, GBIF. Primary biodiversity data are data that Benin was available previously through other combine three essential attributes: geographic sources3: indeed, institutions in 22 countries location, collection date, and taxonomic including Benin presently contribute data about identification (Johnson, 2007; Soberón and Beninese biodiversity, with 170 occurrence Peterson, 2009; Sousa-Baena et al. 2013). Digital datasets and >190,000 records. DAK on the accessible knowledge (DAK) is the part of the biodiversity of Benin is of great importance to existing primary biodiversity data that is (1) in guiding and shaping priorities of decision-makers digital format, (2) published and accessible and engaging them in sustainable management of worldwide for free, and (3) integrated into the the limited and increasingly stressed natural broader global storehouse of biodiversity resources of the country. information (in essence, a transformation of data into “knowledge”; Sousa-Baena et al. 2013). Biodiversity Assessments versus DAK DAK is essential in enabling decision-making on Availability in Benin natural resource management, especially Many studies have addressed biodiversity, in biodiversity conservation (Peterson et al. 2000; terms of its collections, patterns, and conserva- Peterson et al. 2001; Peterson et al. 2004; tion, at various levels across Benin. Adomou Kremen et al. 2008; Morris et al. 2013; Gaiji et (2005) studied distributional patterns of vegeta- al. 2013). The Global Biodiversity Information tion types of Benin, and divided the country into Facility (GBIF1) is by far the largest initiative 10 phytogeographic districts, and described the assembling and sharing DAK on biodiversity, major vegetation types and conservation with the aim of sustaining scientific research, priorities. Various individual vegetation types conservation, and sustainable development (Gaiji have been studied in terms of plant communities et al. 2013, Peterson et al. 2015). GBIF was and species composition (Ganglo et al. 1999; created in 2001, and—as of May 2016—provides Ganglo and Lejoly 1999; Sokpon et al. 2001; access to >640M records from more than 1.6M Ganglo 2004; Ganglo 2005; Ganglo and De species. Foucault 2006; Tohngodo et al. 2006; Awokou et Although plant collections have accumulated al. 2009; Noumon and Ganglo 2005; Noumon et from Benin since the 1780s (Akoegninou et al., al. 2009; Aoudji et al. 2011; Yêvidé et al.2011), 2006), digitization and publication of primary resulting in classifications of forest sites, and occurrence data within the country began only useful recommendations for sustainable manage- recently (2010), in the framework of the activities ment. The diversity of neglected and under- of the Global Biodiversity Information Facility utilized species was assessed by Dansi et al. (GBIF) through GBIF-Benin2. Some DAK for (2012), who found 41 species of high importance in terms of nutrient content, medicinal value, 1 http://www.gbif.org. 2 http://gbif-benin.org. 3 http://www.gbif.org/country/BJ/about/datasets. 23 Biodiversity Informatics, 11, 2016, pp. 23-39 Figure 1. Loss of DAK records during the data-cleaning process for data regarding occurrences of the plants of Benin. Figure 2. Spatial distribution of georeferenced plant records of Benin. 24 Biodiversity Informatics, 11, 2016, pp. 23-39 contribution to household income, poverty METHODS reduction, extent of consumption, degree of Data cleaning consumption, extent of production, availability Data used in this paper were downloaded during the year, contribution to empowerment of from the GBIF site in January 2015 using the women, market value, and market use. Several filter “Plantae” in the scientific name field on the stands and populations of forest species, Benin page4. To ‘clean’ the data, to make optimal medicinal plants, and multipurpose species have use of information available, we used an iterative been studied in Benin in terms of structural series of cleaning steps, as follows. (1) We characteristics, ecology, and usefulness (Sokpon created lists of unique taxon names in each and Biaou 2002; Sokpon et al. 2006; dataset in Microsoft Excel, and inspected them Gouwakinou et al. 2009; Yêhouénou Tessi et al. for multiple versions of the same taxonomic 2012; Koura et al. 2011; Koura et al. 2013a; concepts: misspellings, name variants, different Koura et al. 2013b).The spatial genetic structure versions of authority information, synonyms, etc. of baobab (Adansonia digitata) populations from Such name variants were flagged, and checked West African agroforestry systems was evaluated with independent sources; a field was created to by Kyndt et al. (2009): 11 populations from hold standardized preferred scientific names that Benin, Ghana, Burkina Faso, and Senegal had correctly corresponded to single taxa. We used comparable levels of genetic diversity, and the the list-matching service of the Catalogue of organization of genetic diversity appeared to Life5 and PROTA6, both of which were accessed result essentially from spatially restricted gene in 2015. (2) We checked for and removed flow, with some influences of human seed incomplete or suspicious geographic coordinates exchange. (e.g., one or both of the coordinates either Although of importance in advancing missing or falling outside of Benin in spite of knowledge of vegetation types and structure, and being referred to that country. (3) Within the their determinants and conservation priorities, country, we checked for consistency between these studies did not address representativeness textual descriptions of departments (administra- of sampling of plant diversity across the country, tive divisions) and the position of geographic which could help identify knowledge gaps, data coordinates. In each case, where problems were resource limitations, and possible biases (Sousa- detected, we created a corrected version of the Baena et al. 2013). The single exception is the data records; where no clear correction was palms (Arecaceae), which were analyzed in detail possible, we discarded records, recording data in terms of completeness across Benin by Idohou losses at each step in the process. Finally, (4) we et al. (2015). Moreover, apart from scientific discarded data records for which full information collections (Ariño, 2010), which covered the on year, month, and day of collection was whole country during the elaboration of the flora lacking; we created a unique ‘stamp’ of time as of Benin (Akoegninou et al. 2006), most of the year_month_day. studies stated above only addressed limited sectors of the country. Worse yet, few, if any, of Inventory completeness the occurrence data from those surveys are Next, we aggregated point-based occurrence openly available to the scientific community. data to 0.5° spatial resolution across the country. A survey of biodiversity data holders and This spatial resolution was the product of users within Benin (GBIF Benin, 2011) showed detailed analyses of balancing the benefits of that the most important collection in terms of aggregating data (i.e., larger sample sizes) versus number of specimens is the national herbarium the loss of spatial resolution that accompanies (50,000 specimens), but <30% of its specimens broader aggregation areas and can make have been digitized and published by Beninese imperceptible important geographic features (i.e., institutions via GBIF-Benin and GBIF. 0.5° resolution is a square ~55 km on a side). Therefore, the representativeness of the DAK Those steps focused on choice of an optimal with regard to the geography and species spatial resolution for analysis are detailed in diversity of the country remains unclear. This another paper (Ariño et al., in preparation). study aims to develop a detailed assessment of We produced the aggregation grid shapefiles DAK for Benin’s plants to assess its fitness for in the Vector Grid module of QGIS, version 2.6, use in detailed analyses. 4 http://www.gbif.org/occurrence/search?country=BJ#. 5 http://www.catalogueoflife.org/listmatching. 6 http://www.prota4u.info/protaindex.asp. 25 Biodiversity Informatics, 11, 2016, pp. 23-39 Table 1. Inventory completeness in the departments of Benin. Departments Percentage of Percentage of Percentage of Total (a) + (b) Percentage of Percentage