Completeness of Digital Accessible Knowledge of Plants of Benin and Priorities for Future Inventory and Data Discovery

Ganglo, Jean Cossi; Kakpo, Sunday Berlioz

doi:10.17161/bi.v11i0.5053

Cited by 11 publications

(14 citation statements)

References 27 publications

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“…Our results are supported by those of Ballesteros-Mejia et al(2013), who reported positive effects of tra c access, road density, and tourism on the inventory completeness of tropical insects in Sub-Saharan Africa. Our results are also supported by a previous study byGanglo and Kakpo (2016) on plant data completeness in Benin, where they found that data completeness was positively impacted by the density of roads and waterways. Our results are also in line with those ofKadmon et al (2004) and Souza-Baena et al (2013) in their respective studies on plant species data of Israel and plant data completeness of Brazil, where they found that road bias affected the distribution of data.…”

supporting

confidence: 91%

“…In line with the present work, data completeness analyses were diversely achieved at national and regional scales across Africa. In Benin, data completeness analysis was achieved on the DAK of the plants to guide future inventory and data discovery efforts in the country (Ganglo and Kakpo, 2016). From the results obtained, many spatial and environmental gaps exist in the completeness of the data, particularly in the northernmost departments of the country.…”

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Will Africa meet the challenge of biodiversity conservation in the digital age?

Ganglo

2023

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Digital accessible knowledge (DAK) is of utmost importance for biodiversity conservation; indeed, its use is indispensable to provide evidence and strategies to support decision-making on natural resource management and sustainable use. The Global Biodiversity Information Facility (GBIF, www.gbif.org) is a mega data infrastructure with more than two billion and two hundred million occurrence records as of 17 January 2023. It is by far the largest initiative assembling and sharing DAK to support scientific research, conservation, and sustainable development. We decided to analyze plant data published at the GBIF site at the scale of Africa. We intend to highlight the contribution of the continent to the GBIF and thereby underline data gaps across taxonomic groups, the basis of records, and geographic space. To achieve our purpose, we downloaded data on 17th January 2023 from the Plantae kingdom from Africa. They are available at https://doi.org/10.15468/dl.p2n6um. We achieved data treatment and analysis using R, several packages and related functions. Although Africa is home to rich biodiversity with many hotspots, the global data contribution of Africa to the GBIF (61,176,994 as of 17th January 2023) is still incredibly low (2.69%). Furthermore, there are huge disparities between African countries, with South Africa contributing alone for 50.64% of the data of the continent. The plant data of Africa (9,116,401 occurrence records) accounted for 14.90% of the data of the continent; this underlines huge gaps between taxonomic groups. Furthermore, Magnoliopsida was the dominant plant class with the highest number of records (71.07%) and the highest number of species (68.36%), followed by Liliopsida, with 22.80% of the records and 19.06% of the species. Two sources of records were dominant: preserved specimens (59.68%) and human observation (30.86%). In geographic space, plant data gaps are also quite large across the continent at either spatial resolution (half degree or one degree spatial grid cells); data completeness is more achieved in West Africa, Southern Africa, East Africa, and Madagascar. The large multidimensional data gaps identified in this study should be in priority addressed in future data collections. Accessibility by roads and large protected areas (> 10,000 Km²) are limiting factors of data completeness across the continent. We deplored important data loss during the process of data cleaning; indeed, the number of data determined up to species level was 7,570,244 and accounted for 83.04% of the initial data; the number of records with adequate coordinates was 6,461,460 and accounted for 70.88% of the initial data; while the data fitness for purpose in completeness analysis (records determined up to species level, with adequate coordinates, and full dates) were only 4,643,586 making approximately 50.94% of the total data records initially downloaded from GBIF site. Efforts for quality check before data publication on GBIF site are still important across African countries.

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Will Africa meet the challenge of biodiversity conservation in the digital age?

Ganglo

2023

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“…Knowledge of the spatial and temporal distribution of a species is key for evaluating extinction risks and forecasting possible future threats from factors such as climate change (Pacifici et al 2015;Urban 2015;Ganglo and Kakpo 2016). Ecological niche models (ENMs) are used to understand ecological requirements of species, predict geographic distributions, select areas for conservation and forecast effects of environmental change (Peterson et al 2011;Ganglo et al 2017;Djotan et al 2018).…”

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confidence: 99%

Spatial distribution and impacts of climate change on Milicia excelsa in Benin, West Africa

et al. 2019

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African teak (Milicia excelsa (Welw.) C.C. Berg) is an endangered multi-use species. Understanding the impact of climate change on the distribution of this species may improve the ability to anticipate or recognize its decline or expansion and to take appropriate conservation measures if necessary. Ecological niche modeling was projected in geographical space to study the current and future distribution of M. excelsa in Bénin. MaxEnt was used to estimate the potential geographic distribution of the species under two Representative Concentration Pathways (RCP). Miroc 5 summaries and two RCP 4.5 and RCP 8.5 scenarios were used as predictor variables for projections of the geographic potential of this species. The performance of the model was assessed by the area under the curve (AUC), true skill statistics (TSS) and partial receiver operating characteristics (Partial ROC). From the results, M. excelsa was more a secondary species in the Guinean climatic zone and part of the Sudanian-Guinean and Sudanian climatic zone. The projections show a significant decrease in suitable habitats for the species from the two RCP scenarios. Only a part of the Guinean climatic zone remained suitable and few protected areas will conserve in situ M. excelsa. For the sustainable conservation of M. excelsa, it is essential to strengthen the protection of sacred forests located in the Guinean climatic zone.

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“…Biodiversity information for the West African region has heretofore been characterized by the existence of major gaps across geography (Koffi et al, 2015;Asase and Peterson, 2016;Ganglo and Kakpo, 2016) and, more broadly, across Africa (Dauby et al, 2016;Sosef et al, 2017). In this sense, the WAP Initiative has made major and significant progress, adding >190,000 new biodiversity records to the information available for the plants of the region.…”

Section: Was the West African Plants Initiative Successful?mentioning

confidence: 99%

A new model for efficient, need‐driven progress in generating primary biodiversity information resources

Asase

Sainge²,

Radji

et al. 2020

Appl Plant Sci

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Biological diversity is distributed unevenly worldwide, with wellknown biogeographic patterns such as the latitudinal diversity gradient (Mannion et al., 2014), in which the tropics hold many more species than higher-latitude regions. Other examples of such uneven distribution of biological diversity include the existence of centers of endemism and so-called "hotspots" of biodiversity (Myers et al., 2000). These imbalances are, for whatever reasons, often correlated (if not causally) with differences in wealth, in which the wealthy, so-called Global North is relatively biodiversity-poor, whereas the so-called Global South is often biodiversity-rich and economically poor (Balmford et al., 2005;Rands et al., 2010). A third dimension of this equation centers on the geographic distribution of biodiversity data worldwide. As with global wealth, this commodity tends to be concentrated in the Global North and to be relatively sparse and rare in tropical countries. The reasons behind this unequal distribution of information have to do with histories of occupation and colonization (Peterson et al., 2016a), as well as with histories of science and its development largely in the Global North, at least until relatively recently (Collen et al., 2008).The field of biodiversity informatics has developed rapidly in recent years, with the appearance of important and exciting new tools for analyzing and interpreting biodiversity data. These tools, when

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Completeness of Digital Accessible Knowledge of Plants of Benin and Priorities for Future Inventory and Data Discovery

Cited by 11 publications

References 27 publications

Will Africa meet the challenge of biodiversity conservation in the digital age?

Will Africa meet the challenge of biodiversity conservation in the digital age?

Spatial distribution and impacts of climate change on Milicia excelsa in Benin, West Africa

A new model for efficient, need‐driven progress in generating primary biodiversity information resources

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