3.4 Natural Richness, Biodiversity, Endangerment
We used different indicators for richness, endemism and endangerment of species in
a country.
The natural richness of a country is indicated by the whole number (S) of native
vascular plant species, whole number of mammal plus breeding bird species, number
of endemic (E) vascular plant species, and number of endemic vertebrates (excluding
fish species).
As proxy for the endangerment, we extracted the whole number of critically
endangered species (CR) for each country from the global IUCN Red List (2019)
and additional information. A species that is critically endangered must not be
restricted to a country. In contrary, an endemic species must not be threatened. As
a measure for relative endangerment, we used percentage values of threatened plant
species, i.e. the number of threatened plant species divided by the number of native
plant species in total, and the number of endemic mammals plus birds per country
which are threatened. We calculated these numbers on the basis of raw data in IUCN
Red List (2020, assessed in 3/2020), based on version 12/2019 of Table 6b of the
IUCN (2019), Gleich et al. (2000), Groombridge and Jenkins (2002), and a few
adjustions, cf. Hobohm (2014), and CBD National Reports on the internet.
All these values can also be used as measure for the national mandate/responsibility/accountability in the framework of the Convention on Biological Diversity
(CBD).
For preliminary statistics we used different combinations of all these factors.
However, finally we used the number of native vascular plant species as indicator for
natural richness and all critically endangered species (CR) of a country as indicator
for the endangerment (response variable).
3.5 Statistics
Our statistics enable quantitative analyses on the relationship between (1) geographical/abiotic factors, (2) natural species richness, (3) economic power, (4) economic
inequality, (5) pressure/endangerment of the biota, and (6) biogeographical factors.
We applied correlation analyses (Spearman and Pearson) and multiple linear
regression (MLR) analyses to disentangle the complexity of the data. We also
used Structural Equation Modeling (SEM) to check against less plausible correlations between variables (Browne and Cudeck 1993; Wooldridge 2003; Tabachnick
and Fidell 2006; Bollen and Pearl 2013). Most variables had to be log-transformed
(ln) to make skewed distributions less skewed.
For the interpretation we only used results that were congruent.
206
T. Gaens et al.
We used different indicators for richness, endemism and endangerment of species in
a country.
The natural richness of a country is indicated by the whole number (S) of native
vascular plant species, whole number of mammal plus breeding bird species, number
of endemic (E) vascular plant species, and number of endemic vertebrates (excluding
fish species).
As proxy for the endangerment, we extracted the whole number of critically
endangered species (CR) for each country from the global IUCN Red List (2019)
and additional information. A species that is critically endangered must not be
restricted to a country. In contrary, an endemic species must not be threatened. As
a measure for relative endangerment, we used percentage values of threatened plant
species, i.e. the number of threatened plant species divided by the number of native
plant species in total, and the number of endemic mammals plus birds per country
which are threatened. We calculated these numbers on the basis of raw data in IUCN
Red List (2020, assessed in 3/2020), based on version 12/2019 of Table 6b of the
IUCN (2019), Gleich et al. (2000), Groombridge and Jenkins (2002), and a few
adjustions, cf. Hobohm (2014), and CBD National Reports on the internet.
All these values can also be used as measure for the national mandate/responsibility/accountability in the framework of the Convention on Biological Diversity
(CBD).
For preliminary statistics we used different combinations of all these factors.
However, finally we used the number of native vascular plant species as indicator for
natural richness and all critically endangered species (CR) of a country as indicator
for the endangerment (response variable).
3.5 Statistics
Our statistics enable quantitative analyses on the relationship between (1) geographical/abiotic factors, (2) natural species richness, (3) economic power, (4) economic
inequality, (5) pressure/endangerment of the biota, and (6) biogeographical factors.
We applied correlation analyses (Spearman and Pearson) and multiple linear
regression (MLR) analyses to disentangle the complexity of the data. We also
used Structural Equation Modeling (SEM) to check against less plausible correlations between variables (Browne and Cudeck 1993; Wooldridge 2003; Tabachnick
and Fidell 2006; Bollen and Pearl 2013). Most variables had to be log-transformed
(ln) to make skewed distributions less skewed.
For the interpretation we only used results that were congruent.
206
T. Gaens et al.