Four barriers to the global understanding of biodiversity conservation: wealth, language, geographical location and security - PubMed (original) (raw)

Four barriers to the global understanding of biodiversity conservation: wealth, language, geographical location and security

Tatsuya Amano et al. Proc Biol Sci. 2013.

Abstract

Global biodiversity conservation is seriously challenged by gaps and heterogeneity in the geographical coverage of existing information. Nevertheless, the key barriers to the collection and compilation of biodiversity information at a global scale have yet to be identified. We show that wealth, language, geographical location and security each play an important role in explaining spatial variations in data availability in four different types of biodiversity databases. The number of records per square kilometre is high in countries with high per capita gross domestic product (GDP), high proportion of English speakers and high security levels, and those located close to the country hosting the database; but these are not necessarily countries with high biodiversity. These factors are considered to affect data availability by impeding either the activities of scientific research or active international communications. Our results demonstrate that efforts to solve environmental problems at a global scale will gain significantly by focusing scientific education, communication, research and collaboration in low-GDP countries with fewer English speakers and located far from Western countries that host the global databases; countries that have experienced conflict may also benefit. Findings of this study may be broadly applicable to other fields that require the compilation of scientific knowledge at a global level.

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Figures

Figure 1.

Figure 1.

Maps showing the spatial variations in the number of records per square kilometre in four conservation/ecological databases: (a) the GBIF, (b) the GPDD, (c) MoveBank and (d) the EDB. Countries without any records are shown in white.

Figure 2.

Figure 2.

The independent (dark grey) and joint (light grey) contributions (given as _R_2 values) of GDP per capita, the proportion of English speakers (English speakers), the distance from host organizations (distance) and the GPI for the number of records per square kilometre in (a) the GBIF, (b) the GPDD, (c) MoveBank and (d) the EDB, as estimated from hierarchical partitioning.

Figure 3.

Figure 3.

Scatterplots showing the relationships between GDP per capita, the proportion of English speakers (English speakers), the distance from host organizations (distance), the GPI and bird species richness that was controlled for area (species richness), and the number of records per square kilometre in each country (black circles, non-tropics; white circles, tropics) in (a) the GBIF, (b) the GPDD, (c) MoveBank and (d) the EDB. Regression lines were based on the estimated coefficients in the full model using the actual range of values for the explanatory variable of interest, and mean values for the other variables. Note here that high GPI scores indicate low levels of security.

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