Assessing the conservation status of species with limited available data and disjunct distribution

Highlights

• We compare ecological niche modeling and the α-hull technique.

• We demonstrate the accuracy of ecological niche models to estimate range size.

• Ecological niche modeling is a better tool than the α-hull to estimate range size.

• Ecological niche modeling is a promising tool for evaluating conservation status.

Abstract

Current techniques for estimating the extent of occurrence (EOO) of species, especially those with a naturally disjunct distribution and limited available data, lead to overestimations of their geographic distributions. Accurate EOO estimates are of great importance because they are used to assess conservation status. Topological methods, such as those proposed by the International Union for Conservation of Nature (IUCN), are not able to estimate the geographical distribution of these species accurately because they do not consider the abiotic characteristics suitable to maintain viable populations. In this study, we propose the use of ecological niche models (ENMs) to estimate the EOO. We use the Maximum Entropy (MaxEnt) algorithm and the topological method suggested by IUCN (α-hull method) to estimate the EOO for a species with disjunct distribution and limited available data. The estimate obtained using the ENM was considered the most accurate because only areas with suitable abiotic conditions were taken into account. Thus, analyses related to the conservation status of species become more accurate, especially when evaluating the effects of potential threats in the potential areas occupied by the taxon. The estimate obtained from ENM can also assist the design of conservation strategies for the species, by indicating areas for specific surveys and assessing changes in the EOO over time.

Introduction

An important criterion in evaluating the conservation status of a given species is the estimation of the range size, which is most frequently expressed as the ‘extent of occurrence’ (EOO) (Herzog et al., 2012). The EOO is a parameter that measures the spatial spread of areas currently occupied by a taxon and is used to assess how disturbances (habitat quality decreases, fragmentation, continuing decline, or extreme fluctuations in extent of occurrence) can affect the populations within its geographical range (IUCN, 2011). The International Union for Conservation of Nature (IUCN) states that the EOO of a species can be defined as an area encompassed by the shortest continuous imaginary boundary that holds all known sites of inferred or projected species occurrences, excluding cases of vagrancy. Discontinuities and disjunctions may be excluded within the overall distributions of species (IUCN, 2011).

The EOO is usually measured by a minimum convex polygon, which is also called the convex hull. Following the IUCN (2011) guidelines, researchers can construct a convex hull to estimate the distribution of species; however, if geographical discontinuities or disjunctions of the species are excluded from that hull, the IUCN does not recommend an assessment of the conservation status based on an analysis of its geographical distribution. The selection and exclusion of disjunctions can lead to large changes in the polygon boundary, which results in a reduced estimate of the EOO, and therefore overestimate the degree of threat that certain disturbances may have on the populations of a species. However, when a species has a very disjunct distribution, the boundary determined by the convex hull will have low resolution and will include large areas that are actually not environmentally suitable, leading to an overestimation of the EOO (Herzog et al., 2012, Ostro et al., 1999). Changes in the species distribution (as points outside the boundary of the original polygon) can lead to major changes in the EOO and can result in erroneous inferences about reductions or increases in the geographic range size, leading to changes in the conservation status (Paglia and Fonseca, 2009). Thus, the construction of a convex hull is not considered a good method to compare temporal estimates (IUCN, 2011).

To reduce this bias, the IUCN (2011) recommends the use of the α-hull method, which is a generalization of the convex hull. The α-hull provides more precise information about the distribution of a species and transforms the convex hull into several packages. Some of these packages, which can contain areas with inadequate environmental conditions for the species, could be excluded from the final estimate using the α-hull technique, leading to a more precise EOO for species with a disjunct distribution (for more information about the construction of the α-hull, see Section 2.4 in Materials and Methods).

The precise extent of a species’ geographic range is seldom known because most species (and especially threatened ones) are known by only a few occurrence records (Peterson, 2006) making both techniques, the convex hull and α-hull, subject to gross errors. Existing maps, for example, show only vague extents of the occurrence of the distributions of even well-studied groups, such as birds (Alves et al., 2008). Examples of recent species distribution maps (Franklin, 2010) show that the survey data were often collected by dividing the landscape into relatively coarse-grain or low resolution grid cells of equal area. Topological methods, such as the convex hull and the α-hull methods, do not consider information about the environmental requirements necessary for the survival of the species in estimating their geographical distribution.

Studies have shown that these current techniques for determining the EOO lead to overestimations of the geographic distribution of bird species (Jetz et al., 2008), especially those with a disjunct distribution (Hurlbert and White, 2005). Ecological specialists (e.g., those with narrower diets) and those with a smaller range size are more susceptible to overestimation, which can lead to incorrect decisions related to the management and conservation of these species. Thus, the EOOs of rare, vulnerable or endangered species are proportionately more susceptible to overestimation (Jetz et al., 2008). Studies that evaluated the accuracy of these strategies to estimate the EOO of these species indicate the need to use tools that use spatially explicit environmental data related to the distribution of the species (Herzog et al., 2012, Jetz et al., 2008).

A tool that can be considered as an alternative to the topological methods to estimate the extent of occurrence of species, particularly those with a disjunct distribution, is the construction of ecological niche models (ENMs). ENMs usually involves the determination of associations between environmental conditions and information on the occurrence of species to identify areas critical to the maintenance of species populations (Peterson et al., 1999, Warren et al., 2010), and this technique can be used to analyze the limiting factors or regulators that determine the spatial distribution of plants and animals (Guisan and Zimmermann, 2000). ENMs has received attention in the field of conservation planning as an important tool to define areas or reserve networks that can efficiently protect biodiversity (Alves et al., 2008, Araújo et al., 2002, Barros et al., 2012, Giovanelli et al., 2008, Kremen et al., 2008, Marcer et al., 2013, Thorn et al., 2009, Young, 2007). Recently, it was demonstrated that ENMs can be a better tool for estimating the EOO of endangered species (Herzog et al., 2012). However, comparisons with topological methods were based only on the convex hull.

As indicated in the IUCN Guidelines (2011), the EOO is not intended to be an estimate of the amount of occupied or potential habitat; therefore, using a tool that considers only areas with suitable abiotic conditions for the survival of the species will lead to a more accurate estimate of the impact of possible threats. If researchers provide rigorous control of their data quality, ENM provide an accurate predictive map and offers the advantage of low costs (compared to strategies such as genetic studies or behavioral and demographic data) and useful information for biodiversity conservation strategies, especially those involving a large number of species but with only limited available resources (Araújo et al., 2002, Cayuela et al., 2009).

The aim of this study is to show the applicability of ENM as a tool to estimate the EOO for species with a naturally disjunct distribution and limited available data. We compare the estimate of the EOO based on the predictive model with that obtained from the construction of the α-hull. Thus, we used the neotropical ovenbird, Asthenes luizae Vielliard, 1990, as an example because it displays several interesting features. This species has a very restricted and patchy geographic distribution because it is found only on rocky outcrops above 1000 m on mountain tops in the southern portion of the Espinhaço Range, Brazil (Vasconcelos and Rodrigues, 2010, Vasconcelos, 2008). Recently, the classification of this species was changed from Vulnerable to Near Threatened because new records led the species to be known by more than 10 occurrence points and the quality of its habitat appears to be stable (BirdLife International, 2012). However, its highly disjunct distribution and specificity to its habitat remain threats to the species, in addition to frequent fires and the brood parasitism of the shiny cowbird, Molotrhus bonariensis (Gmelin, 1789).

In this study, we show that the ENM method can lead to a more accurate estimate of geographic distributions. We also offer specific observations regarding A. luizae as related to its current classification as Near Threatened and the need to more accurately assess the potential threats within its EOO.