Using endemism to assess representation of protected areas – the family Myrtaceae in the Greater Blue Mountains World Heritage Area

Abstract

Aim We assess how much of species' ranges are present within protected areas and how different land units within protected areas contribute to overall protection, both within their region and at continental scales. We do this using the plant family Myrtaceae in relation to the globally important Greater Blue Mountains World Heritage Area (GBMWHA) in New South Wales, Australia. Location South‐eastern Australia. Methods Compiling data throughout the region and nationally, we considered two spatially based quantitative measures of endemism (relative range restriction): weighted endemism (WE) and corrected weighted endemism (CWE). In both measures, species are weighted by the proportion of their ranges found within the analysis window, with the ranges calculated as the total number of cells in which they occur (10 km × 10 km in this research). We also derived a novel expectation for the contribution of each species to the endemism scores at each taxonomic level based on the additive properties of the metrics and their relationship to species richness. We used this expectation to assess the proportional contribution of each genus to the endemism scores. Results The degree to which Myrtaceae species within the GBMWHA are endemic to the GBMWHA area is 16%, meaning that an average of 16% of the ranges of species found in the GBMWHA are restricted to that area. The figure for those species with ranges less than or equal to the median (80 cells) is 33%. The genus Eucalyptus contributes the most to the endemism scores obtained, but no more than would be expected given its number of species. The genus Leptospermum is 3.7% less restricted to the GBMWHA than would be expected, while the genus Melaleuca is 5% more restricted than expected. Main conclusions Centres of high endemism within the GBMWHA and surrounds were identified. This research presents a template for quantifying endemism for regions at local to global scales. Spatially‐based quantitative measures of endemism, such as outlined here, are an important means to quantify and visualize these aspects of conservation significance for the management of protected areas.

Updated distribution and biogeography of amphibians and reptiles of Europe

“…The sum of the weighted values for a given cell (weighted endemism) is then divided by the number of species occurring in the cell. This correction for the cell species richness ensures that CWE values highlight areas with a high proportion of endemic species but not necessarily high in richness (Crisp et al, 2001;Laffan and Crisp, 2003;Laffan, Ramp and Roger, 2012). We calculated CWE using the "endemicity tools" extension for ArcView 3.2 (Danho, 2003), and performed computations at the cell level (radius = 1), excluding empty grid cells from analysis.…”

Key environmental determinants of global and regional richness and endemism patterns for a wild bee subfamily

“…Although alternative measures of weighted endemism designed for regions comprising many cells and polygonal regions (Laffan and Crisp 2003;Laffan et al 2013) exist, the analysis based on individual grid cells used in our study is justified by a relatively coarse grid cell size and limited knowledge about species ranges due to incomplete sampling.…”

El endemismo: diferenciación del término, métodos y aplicaciones

“…Algunos índices del endemismo se encuentran disponibles en el programa Biodiverse (Laffan et al 2010), incluyendo los WE y CWE normalizados con el número de celdas que componen el área de estudio (Apéndice I). Otras aplicaciones incluyen la identificación de endemismo con el uso de ventanas para diferentes niveles taxonómicos (orden, familia, género) en el llamado Endemismo Completo con Partición Jerárquica (Laffan et al 2013) (Apéndice I), bajo el supuesto que cada nivel taxonómico contribuye al endemismo de un taxón.…”

“…En los índices que consideran ventanas o radios para estimar la densidad durante la ponderación, se ha mencionado que el movimiento y tamaño de las ventanas incrementan los valores de endemismo (Laffan et al 2013). Esto se relaciona con el uso de la riqueza para corregir el índice de endemismo, donde la riqueza alrededor de la celda objetivo puede ser variable.…”