Abstract
Knowledge gaps regarding species distribution and abundance are great in remote regions with political instability, and they might be even larger concerning elusive and rare species. We predict the potential distribution for Hierophis andreanus, a poorly known endemic snake in the Iranian Plateau, and assess its conservation status in relation to existing protected areas. We used a maximum entropy modeling tool and Mahalanobis distance to produce an ensemble species distribution model. The most suitable habitats where located mainly in mountain ranges and adjacent areas of Iran and Afghanistan. Mean temperature and slope were the most important predictors for our models. Furthermore, just five localities for H. andreanus were inside the Iranian protected areas. A 10 km expansion from existing boundaries of protected areas in all directions would double protected localities to 10, and a 20 km buffer would result in 13 protected localities. Our findings are particularly valuable to select locations to conduct new surveys and produce a more reliable estimate of current population size to improve conservation and management for this reptile in the Irano-Anatolian region.
Most species remain undescribed and our knowledge of species distributions is incomplete (Linnean and Wallacean shortfalls; Lomolino, 2004). These shortfalls in our knowledge of biodiversity have important consequences for conservation prioritization, and may be more strongly marked for some regions and taxa. Although Iran and the Irano-Anatolian region are considered biodiversity hotspots for western Palearctic reptiles, the lack of accessibility and monitoring are known to underestimate reptile richness and endemism (Sindaco and Jeremčenko, 2008; Gholamifard, 2011; Ficetola et al., 2013; Hosseinzadeh et al., 2014). Besides, conservation management of endemics of the Irano-Anatolian region is hampered by our scant knowledge about their distribution and ecology, and by the low coverage of protected sites. Among the 66 endemic reptiles described in Iran, there are ten colubrids (Safaei-Mahroo et al., 2015; Rajabizadeh et al., 2015; Fathinia et al., 2017; Torki, 2017a, 2017b); one of them is the Andreas’ Racer, Hierophis andreanus (Werner, 1917), a poorly known endemic species from the southern Zagros Mountains, southwestern Iran (Schätti, 2001; Schätti and Monsch, 2004). Very little is known about the distribution, abundance and ecology of this Iranian endemic, and its current population trend is completely unknown (Anderson et al., 2009).
Ecological niche models (ENMs) are useful to provide more information on the potential distributional range and habitat suitability for such a poorly known and elusive Iranian snake. Because reptiles and amphibians are ectotherms and need environmental warmth to increase their body temperature, they have limited climatic tolerance and are highly dependent on climatic conditions (Buckley and Jetz, 2010; Hosseinzadeh et al., 2014); thus, bioclimatic models can be extremely useful in predicting reptile and amphibian distributions (see e.g. Guisan and Hofer, 2003; Pineda and Lobo, 2009). Additionally, ENMs may facilitate survey design, the assessment of the effectiveness of protected areas (e.g. Araújo et al., 2011; Mazaris et al., 2013; Chefaoui et al., 2017), and the selection of habitat of high conservation value (e.g. Almpanidou et al., 2014, 2016) towards directing management initiatives and policy recommendations.
In Iran, established protected areas include high biodiversity ecosystems (Makhdoum, 2008). At the present time, there are 272 Iranian conservation areas designated by national legislation, which include: national parks (28), national natural monuments (35), wildlife refuges (43) and protected areas (166) (Kolahi et al., 2012; DoE, 2016). Nevertheless, protected areas are facing increasing threats related to overexploitation and anthropogenic habitat change, which are causing the disruption of habitats and loss of endemics (Croitoru and Sarraf, 2010; Kolahi et al., 2012). According to World Bank (1995), 80% of all Iranian wildlife vanished during Iran-Iraq war and 50% of the protected areas were seriously affected. Unfortunately, mismanagement and insufficient resources make it extremely difficult to secure effective conservation inside the Iranian protected areas (Makhdoum, 2008; Kolahi et al., 2012).
The objectives of this study are: i) to model the environmental niche of H. andreanus and predict its potential distribution in the Irano-Anatolian region, and ii) assess the gaps of the current Iranian protected areas network in covering the species distribution. Here, we enhance our knowledge of the potential distribution of H. andreanus as well as of the possible factors related to its occurrence, with the purpose of targeting suitable areas for surveying and increasing its monitoring and protection.
To compile a spatial database on presences of H. andreanus, we reviewed literature (Rajabizadeh and Rastegar-Pouyani, 2006; Torki, 2010; Sindaco et al., 2013) and conducted field surveys. From May 2009 to September 2012, we randomly sampled the occurrence of the snake during six expeditions across its known range of distribution in the Zagros Mountains (Ilam, Markazi, Fars, Lorestan and Bushehr provinces). Despite our sampling effort, we could detect just three new point localities of this elusive snake. A total of 18 occurrences of H. andreanus were compiled from our own field work and the literature (supplementary table S1).
Due to the lack of knowledge on the specific variables affecting the species, twenty climatic variables mostly related to the temperature and precipitation were obtained from the Worldclim 30-arc-seconds resolution data set (http://www.worldclim.org/; Hijmans et al., 2005). In addition, a slope layer was derived from altitude using the “raster” package (Hijmans, 2016) in R. Pearson correlation analysis was performed to discard variables with
Contribution of the variables to the Environmental Niche Factor Analysis (ENFA) and MaxEnt model of Hierophis andreanus. Those variables with the highest contribution to the ENFA marginality factor (in bold) were used to perform MaxEnt and Mahalanobis distance models. The eigenvalues of the specialization axes indicate that the first one explains most of the specialization, and only the contributions of variables to this first specialization axis are included in the table. Variables contributing most to specialization were temperature annual range and precipitation of the driest quarter, suggesting that the distribution of H. andreanus detections is much narrower for annual temperature range and precipitation of the driest quarter than for the study area as a whole.
Citation: Amphibia-Reptilia 39, 3 (2018) ; 10.1163/15685381-17000185
Due to our small sample size, we followed a similar methodology to that applied by Pearson et al. (2007) to use maximum entropy modeling (MaxEnt; Phillips et al., 2006). MaxEnt is an ENM technique to make predictions or inferences from incomplete information, since instead of real absence data it uses background data (Phillips et al., 2006). ENMs were calibrated across the Middle East. All MaxEnt runs were carried out using default settings with a convergence threshold of 0.00001, with 500 iterations and the regularization value set to 0.1. We used 10,000 background points and the logistic output format, displaying probability values from 0 (low probability) to 1 (optimal). To evaluate the MaxEnt model, we used a jackknife procedure, and calculated the significance of jackknife estimates using the “pValueCompute” software (Pearson et al., 2007). In jackknife, every observed occurrence record was excluded once from the data set and a model was fitted using the residual
As MaxEnt uses background data, its predictions are closer to the realized niche (Elith et al., 2006). In order to obtain two contrasting niche hypotheses, we also performed Mahalanobis distance (MD), a presence-only method, to map the potential distribution of H. andreanus. MD algorithm computes the elliptic envelope for the species, creating a potential suitability map (Clark et al., 1993). To do that, variables were first scaled to even their variance. By using both techniques (MaxEnt and MD) we produced two predictions in the range between realized and potential niche (Jiménez-Valverde et al., 2008). Comparison between these different hypotheses may be advantageous in the case of lack of reliable absence data. The consensus prediction (ensemble) was also computed as the mean between the two models, a more reliable and parsimonious approach to obtain predictions for survey design according to Gil and Lobo (2012). In addition, we described the niche and the importance of the selected variables by means of an ENFA analysis. ENFA and MD were run using the “adehabitat” package (Calenge, 2006) in R.
We finally performed a GAP analysis to assess the effectiveness of Iranian Protected Areas in representing H. andreanus. We compared the location of the present wildlife refuges, protected areas and national parks with an expanded network to find priority regions for expanding (Rodrigues et al., 2004). Spatial datasets of Iranian Protected Areas were obtained from DoE (2016). We used buffers of 10 km and 20 km to evaluate the achievement of protection of the proposed expansion.
After preliminary ENFA for selection of variables, three out of ten uncorrelated variables remained as the most relevant in explaining the marginality: slope, the mean temperature of the wettest quarter (bio8), and the mean diurnal range of temperature (bio2; mean of monthly (max temperature-min temperature)) (see table 1). These variables were used for the rest of the analyses. According to ENFA, H. andreanus is found in terrains with higher slope and mean diurnal range in relation to the study area (see table 1 and supplementary figure S1). In addition, the species occurs in locations with lower temperature of the wettest quarter than the mean conditions.
MaxEnt model accurately predicted the confirmed locations of H. andreanus (AUC = 0.911; TSS = 0.629; Kappa = 0.280). The Jackknife test showed a high success rate (94.44%) at LPT and 0.10 thresholds, and was statistically significant in both cases (
Mahalanobis distance prediction showed a wider potential habitat for H. andreanus, covering different countries of the study area: Iran, western Afghanistan, northern Pakistan, western Iraq, southern Syria, eastern Jordan and a small area in Saudi Arabia. This model found suitable not only mountain ranges, but also areas with lower altitudes. The ensemble between MaxEnt and Mahalanobis distance models produced a consensus distribution (fig. 1A).
(A) Ensemble prediction for Hierophis andreanus calculated as the mean between MaxEnt and Mahalanobis distance models calibrated across the Middle East. Probability of occurrence ranges from 0 to 1 (highest probability). (B) Localities of Hierophis andreanus (red circles) in relation to the different protected areas of Iran. The Iranian region examined corresponds to the boundary box displayed in fig. 1A. Ecoregions are shown for informative purposes.
Citation: Amphibia-Reptilia 39, 3 (2018) ; 10.1163/15685381-17000185
From the 18 occurrence points detected for H. andreanus in Iran, just five localities (27.7%) are covered by protected areas (fig. 1B). These five locations pertain to four provinces: Fars, Ilam, Kerman and Lorestan. From these, just one occurrence (locality n° 1 according to table S1) is inside a national park (“Bamoo National Park”). Four are in several protected areas: localities 4 and 7 in “Sefid kuh Protected Area”, locality 11 inside “Koh-e shir Protected Area”, and locality 13 in “Kabir koh Protected Area” (table S1; fig. 1B). An expansion of 10 km would include 55.5% of occurrences (10 localities), and one of 20 km would cover 72.2% (13 localities).
The ensemble model showed the most suitable habitats for H. andreanus were located in mountain ranges: the Zagros Mountains in Iran and the Hindu Kush Mountains in Afghanistan. As expected, we found differences between the algorithms used as Mahalanobis distance, the profile method, showed a wider potential distribution for the species than MaxEnt. According to MD, suitable habitats for the snake could also be located outside mountain areas, such as the Plateau of Iran, where it has not been found up to now. Thus, if the actual occurrence of H. andreanus is restricted to the Zagros Mountains as observed, it would probably not be due to an environmental barrier (provided all relevant variables affecting its distribution were considered in the analysis), but because the species could have found shelter from human activity in that region of low accessibility. In fact, its presence has already been detected once at a very low altitude in the coastline of the Persian Gulf (20 m; table S1) and more field work would be needed to estimate the actual population size in this area. Due to the low number of occurrences and the lack of reliable absence data, our consensus prediction between the two models (ensemble) seems a more reliable approach to plan additional surveys for this relatively unknown reptile (see Gil and Lobo, 2012). This study is subject to the usual uncertainties related to ENMs, such as the incomplete observed distribution data, and the election of the algorithms and threshold used for binary classification (see e.g. Beale and Lennon, 2012; Chefaoui and Serrão, 2017).
ENFA found that temperature related variables (the mean diurnal range and the mean temperature of wettest quarter) and slope were the most important factors explaining the difference between the mean conditions at H. andreanus localities and the available environment. Moreover, the distribution of H. andreanus detections is much narrower for annual temperature range and precipitation of the driest quarter than for the study area as a whole (table 1). Temperature is a known factor limiting the distribution of reptiles due to their ectothermy. Species richness of lizards was found to decrease with decreasing temperatures across the Southwestern United States (Buckley and Jetz, 2010), the complete Western Palaearctic region (Ficetola et al., 2013), and was also found as the most relevant variable affecting reptile richness in Iran (Hosseinzadeh et al., 2014). The higher slope where the species occurs could be related to the protection provided by steep and rough terrains to human disturbance and habitat change.
The Irano-Anatolian region is considered one of the world’s 34 biodiversity hotspots (Mittermeier et al., 2004), and particularly, southwestern Iran has been identified as one of the hotspots for western Palearctic reptile richness (Sindaco and Jeremčenko, 2008; Ficetola et al., 2013; Hosseinzadeh et al., 2014). Our ensemble prediction is coincident with the Irano-Anatolian biodiversity hotspot with the exception of Afghanistan, which is the habitat of another species of the genus (Hierophis spinalis). The hotspot mountains have served as both a refuge and a corridor between the eastern Mediterranean and western Asia, resulting in many centers of local endemism that include some endemic species of snakes (Arsenault et al., 2005). Recently, a new record of Hierophis andreanus, based on one specimen, has been reported from the Qara Dagh Mountains, South Kurdistan, Iraq (Auer et al., 2016). Consequently, our results showed that the region is habitat suitable for the species and distribution probably extends to the western slope of the Zagros Mountains in Iraq. Hierophis andreanus mostly occur on the western slope of the Zagros Mountains with other snake species: Xerotyphlops luristanicus, Xerotyphlops wilsoni, Eirenis nigrofasciatus, Eirenis (Pseudocyclophis) persicus, Eirenis (Pediophis) punctatolineatus condoni, Eirenis (Pediophis) rechingeri, Lytorhynchus levitoni, Platyceps najadum schmidtleri, Rhynchocalamus ilamensis, Spalerosophis microlepis, Telescopus tesellatus, Montivipera kuhrangica and Pseudocerastes urarachnoides.
Despite the acknowledged biodiversity of the Irano-Anatolian region, remoteness, inaccessibility and political instability have been cited as important causes producing underestimation of the actual richness (Ficetola et al., 2013). Numerous armed conflicts occurred within countries comprising this biodiversity hotspot since 1950 (Hanson et al., 2009). War is known to alter ecosystem structure and function by contributing to biodiversity losses and population declines (Lawrence et al., 2015). Since Iranian wildlife was seriously damaged during the Iran-Iraq war (World Bank, 1995), the populations of the endemic H. andreanus in former war regions could have been affected. In addition, the location of military facilities within biodiversity hotspots can restrict research access and create knowledge gaps (Lawrence et al., 2015). As a result, sound conservation policies have been difficult to develop and implement and there are still large gaps in knowledge of reptiles’ distributions. Our findings help assess the conservation status of H. andreanus, which is poorly known (Anderson et al., 2009). We have found that this endemic species seems to be insufficiently protected: from the 18 known localities for the Andreas’ Racer, just five are located inside the Iranian protected areas (fig. 1B). Disastrous reductions and changes in Iran’s ecosystems have produced landscape fragmentation and homogenization, threatening biodiversity and affecting ecosystem services (Kolahi et al., 2012). Thus, despite the connection among the known localities for the species and potential suitable habitats, we find that H. andreanus is currently underprotected by the existing conservation network. Protected localities would double to 10 if a 10 km buffer was applied to all Iranian protected areas, or simply by expanding 20 km the boundaries of “Bamoo National Park” and the protected areas of Ilam and Lorestan provinces.
In this study, we provide new localities and a potential distributional range for H. andreanus. Though its potential distribution seems wide, increasing threats related to overexploitation and anthropogenic habitat change affecting these areas, even in protected sites, might already be diminishing extant populations. There is a need to improve our knowledge of the actual distribution, effective population size and general ecology of this poorly known species in order to develop and implement possible conservation measures.
Acknowledgements
We are grateful to B. Schätti, H. Ghaffari and R.A. Pyron for providing occurrence data of H. andreanus and guiding us. We also thank J.C. Brito, B.J. Halstead, S.C. Anderson, M. Blair and an anonymous referee for their helpful comments and suggestions on the manuscript. RC was supported by the postdoctoral fellowship SFRH/BPD/85040/2012 from the Fundação para a Ciência e a Tecnologia (FCT, Portugal). We also thank FCT funding by “UID/Multi/04326/2013” for CCMAR.
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Footnotes
Associate Editor: José C. Brito.
