Exploring the impact of political regimes on biodiversity

Abstract

18National governments are the main actors responsible for mapping and protecting their 19 biodiversity, but countries differ in their capacity, willingness, and effectiveness to do so. We 20 quantify the global biodiversity managed by different regime types and developed a tool to 21 explore the links between level of democracy and other key socio-economic variables with the 22 number of natural history specimens registered within country boundaries. Using this tool, 23 distinct and previously unknown patterns emerge around the world, that urge for increased 24 collaboration between the natural and social sciences to further explore these patterns and 25 their underlying processes. 26 28 85 the exploration of how regime change, as well as armed conflict, affect the availability of 86 primary biodiversity data. Taking Cambodia as an example, we find a decrease of new 87 biodiversity data records by two orders of magnitude in the 1970s, coinciding with the 88 beginning of a period of conflicts and autocratization (Fig. 2c). The end of this period 89 and the corresponding increase in the level of democracy led to a sudden increase in data 90 availability. Similarly, in India political turmoil and a related decrease in the level of 91 democracy in 1975 and 1976 led to an abrupt decrease in the availability of biodiversity data 92 from national institutions (Fig. 2d). Despite historical turmoil and a minor recent decline 93 in the level of democracy, Cambodia and India mirror most other countries in exhibiting a 94 general increase in biodiversity data, probably attributable to the widespread use of citizen 95 science applications for mobile phones such as iNaturalist. 96 The relationships between political differences, socio-economic variables and biodiversity 97 knowledge are multi-faceted. 1 These links are also likely to be multi-directional. Increasing 98 societal concerns for environmental protection are likely to affect political processes and the 99 gathering of biodiversity data. In general, a causal interpretation of the observed patterns 100 is difficult, due to indirect or unclear mechanisms, and the large number of potentially 101 confounding factors. 1 The Bio-Dem app and its underlying data sources provide a useful 102 platform for research at a global and regional scale and over time. We hope it will foster 103 increased collaborations between biologists, conservationists and political and other social 104 scientists. 15 105 Material and Methods 106 Commented scripts for all analyses are available in the electronic supplement of this article 107 and the source code of the Bio-Dem app is available at https://github.com/Antonelli 108 Lab/Bio-Dem under a MIT license.109We used two datasets of species geographic distributions to estimate the fraction of 110 species covered by regime type. For amphibians, non-marine birds and mammals, we used 111 112 of Nature (www.iucn.org) together with country borders as provided by Naturalearth 113 (www.naturalearth.org) to estimate the range-weighted species endemi...

Automated conservation assessment of the orchid family using deep learning

“…5). Although AA are certainly not free from error, due to the biased availability of the underlying occurrence records and RL data (Meyer et al 2016, Supplementary Figure S5; Daru et al 2018), the reduced bias compared to IUCN RL is likely related to the fact that the factors biasing the collection of species geographic occurrence records, such as physical accessibility or socio-economic factors (Meyer et al 2016;Daru et al 2018;Zizka et al 2020d), affect the collection of detailed data necessary for IUCN RL assessments (e.g., population trends) even more strongly.…”

sampbias, a method for quantifying geographic sampling biases in species distribution data

“…Many aspects can lead to sampling biases, including socio‐economic factors (e.g. national research spending, history of scientific research; Meyer et al 2015, Daru et al 2018, Zizka et al 2020), political factors (e.g. armed conflict, democratic rights; Rydén et al 2020), and physical accessibility (e.g.…”