Open AccessThe role of criteria in selecting important areas for conservation in biodiversity‐rich territories
Author(s) -
Sánchez de Dios Rut,
Cabal Ruano Ciro,
Domínguez Lozano Felipe,
Sainz Ollero Helios,
Moreno Saiz Juan Carlos
Publication year - 2017
Publication title -
diversity and distributions
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.918
H-Index - 118
eISSN - 1472-4642
pISSN - 1366-9516
DOI - 10.1111/ddi.12535
Subject(s) - species richness , endemism , geography , biodiversity , biodiversity hotspot , plant species , ecology , distribution (mathematics) , global biodiversity , range (aeronautics) , selection (genetic algorithm) , biology , computer science , mathematics , composite material , mathematical analysis , materials science , artificial intelligence
Aim To improve our knowledge of the process of selection of important plant areas ( IPA s), a recent requirement of the Global Strategy for Plant Conservation. The study was conducted at a hotspot of plant conservation in the European continent, using a comprehensive database of plant species distribution in the area. Location Spain. Methods We used range distribution data for 3218 vascular plants found in Spain, in the form of 10 km UTM squares, totalling 169,124 species occurrences across 5508 UTM cells. We identified IPA s by scoring threat status, endemism, rarity, phylogeny and species richness. We then performed two different analyses, with and without incorporating the species richness score of every square. Finally, a null model was used to obtain a general pattern of species occurrences, we computed an index of occurrence richness ( SI ), and then we selected a number of specific territories of different sizes to reveal differences in sampling effort within the study area. Results We identified IPA s in Spain according to the proposed scoring method. We detected a positive relationship among richness and total score calculated with the rest of the criteria. However, endemism and threat status produced certain specific effects for species‐poor squares. Regarding sample bias, we detected over‐ and under‐recorded areas. This bias seems to be due to the accumulation of field prospecting in species‐rich areas in detriment to poor areas. Main conclusions We envisage two different approaches to address IPA selection in hotspots. First, we advocate a complementary scoring‐mapping method for areas where a relatively large amount of range distribution data and plant knowledge is available. Secondly, as richness per se encompasses a great amount of biogeographical information, we suggest using species richness or any other environmental surrogate to delineate preliminary IPA s in poorly known but species‐rich territories.