A novel index to aid in prioritizing habitats for site-based conservation

Funding biodiversity conservation strategies are usually minimal, thus
prioritizing habitats at high risk should be conducted.  We
developed and tested a conservation priority index (CPI) that ranks
habitats to aid in prioritizing them for conservation. We tested the index
using 1897 fish species from 273 African inland lakes and 34 countries. In
the index, lake surface area, rarity, and their International Union for
Conservation of Nature (IUCN) Red List status were incorporated. 
We retrieved data from the Global Biodiversity Information Facility
(GBIF), and IUCN data repositories. Lake Nyasa had the highest species
richness (424), Tanganyika (391), Nokoué (246), Victoria (216), and Ahémé
(216). However, lakes Otjikoto and Giunas had the highest CPI of 137.2 and
52.1, respectively. Lakes were grouped into high priority (CPI >
0.5; n=56) and low priority (CPI <0.5; n=217). The median surface
area between priority classes was significantly different (W = 11768,
p<0.05, effect size = 0.65). Prediction accuracy of Random Forest
(RF) and eXtreme Gradient Boosting (XGBoost) for priority classes were
0.912 and 0.954 respectively. Both models exhibited lake surface area as
the variable with the highest importance. CPI generally increased with a
decrease in lake surface area. This was attributed to less ecological
substitutability and higher exposure levels of anthropogenic stressors
such as pollution to a species in smaller lakes. Also, the highest species
richness per unit area was recorded for high-priority lakes. Thus, smaller
habitats or lakes may be prioritized for conservation although larger
water bodies or habitats should not be ignored. The index can be
customized to local, regional, and international scales as well as marine
and terrestrial habitats.