Application of Invest Habitat Quality Module in Spatially Vulnerability Assessment of Natural Habitats (Case Study: Chaharmahal and Bakhtiari Province, Iran)

Environ Monit Assess (2020) 192:487 https://doi.org/10.1007/s10661-020-08460-6

Application of InVEST habitat quality module in spatially vulnerability assessment of natural habitats (case study: Chaharmahal and Bakhtiari province, Iran)

Shekoufeh Nematollahi & Sima Fakheran & Felix Kienast & Ali Jafari

Received: 25 October 2019 /Accepted: 25 June 2020 # Springer Nature Switzerland AG 2020

Abstract There has been a growing pressure of human and Bakhtiari province in the southwestern part of Iran, activities, especially road network, on natural habitats of which is among the most important habitats for wild sheep the world, which has led to habitat degradation and loss of (Ovis orientalis) classified as vulnerable on the IUCN Red ecosystem services. To mitigate the impacts of human List. In this study, we used the habitat quality module of activities, appropriate studies quantifying ecosystem ser- the InVEST software (Integrated Valuation of Environ- vices and assessing ecological impacts of road network mental Services and Tradeoffs), which was driven from are essential. The main goal of this study was modeling land use/cover data, information on anthropogenic threats, habitat quality and habitat degradation of Chaharmahal and expert knowledge. We tested the reliability of the habitat quality values by comparing them with the distribution map of wild sheep obtained from the Department of the Environment. Then, to have a more comprehensive Electronic supplementary material The online version of this article (https://doi.org/10.1007/s10661-020-08460-6)contains assessment of the roads’ effects on the natural habitats of supplementary material, which is available to authorized users. this province, considering ecosystem services model, the : Spatial Road Disturbance Index (SPROADI) was applied S. Nematollahi S. Fakheran (*) as a landscape index. The results of this study revealed Department of Natural Resources, Isfahan University of Technology, Isfahan 84156-83111, Iran that the east and north eastern parts of the study area which e-mail: [email protected] were among the most suitable habitats for wild sheep were e-mail: [email protected] highly affected by road network. Overall, findings of our study provided useful information on the spatially explicit S. Nematollahi distribution of habitat quality and degradation which were e-mail: [email protected] a valuable input for conservation planning and enhancing e-mail: [email protected]? ecosystem services.

S. Nematollahi : F. Kienast Swiss Federal Institute for Forest, Snow and Landscape Research Keywords Ecosystem services . InVEST . Habitat (WSL), Zürcherstrasse 111, 8903 Birmensdorf, Switzerland quality . Ecological impacts . SPROADI . Road network F. Kienast e-mail: [email protected] Introduction A. Jafari Department of Natural Resources and Earth Sciences, Shahrekord University, Shahrekord 88186-34141, Iran There has been a growing pressure of human activities e-mail: [email protected] on ecosystems and natural habitats, which has caused

Content courtesy of Springer Nature, terms of use apply. Rights reserved. 487 Page 2 of 17 Environ Monit Assess (2020) 192:487 high rates of habitat degradation and loss of the benefits expert knowledge to attain reliable indicators about the such as air quality, climate regulation, and habitat ser- current biodiversity’s response to the threats, and unlike vices (“ecosystem services”) that ecosystems provide other approaches in the field of biodiversity conserva- (Butchart et al. 2010; Terrado et al. 2016). These chang- tion, it does not require prior information on the occur- es have been so widespread that about 32.8% of the rences data of a species (Leh et al. 2013; Baral et al. global protected area networks are heavily influenced by 2014; Terrado et al. 2016). human activities (Jones et al. 2018). As stated by recent The main drivers of the decrease in the quality of the assessments, up to 60% of the world’s ecosystem ser- habitats are climate change and land use change (Pecl vices have been degraded (Maes et al. 2015;Lanzas et al. 2017), which are intensified by other anthropogen- et al. 2019). To mitigate the impacts of human activities, ic threats including the contribution of infrastructure it has been necessary to quantify the current status of and, more particularly, road network development ecosystem services. The four main categories of ecosys- (Freudenberger et al. 2013; Nematollahi et al. 2017). tem services are provisioning, supporting, regulating, The effects of road network on wildlife population and and cultural (Millennium Ecosystem Assessment ecosystem services are cumulative and often irreversible 2005; Lanzas et al. 2019). The major problem is that (Selva et al. 2011; Nematollahi et al. 2017). Roads have the benefits and values of nature are still largely invis- caused death due to crash with vehicles (Bruschi et al. ible to people and decision makers in business and 2015;Ogletreeetal.2019), habitat degradation governments (Albert et al. 2016). These services should (Sánchez-de-Jesús et al. 2016), and decrease in habitat be considered and also valued in ensuring the sustain- quality for wildlife population, and have made barrier able management of multi-functional landscapes which between the left habitat patches (Bruschi et al. 2015; support human well-being (Kienast et al. 2009). ES Esperandio et al. 2019) and also changes in ecosystem mapping could make the nature’s benefits spatially ex- services (Mitchell et al. 2015;Lanzasetal.2019). To plicit and visible to people and decision makers (Grêt- better understand the ecological impacts of roads on Regamey et al. 2015; Hou et al. 2018). wildlife, habitats and ecosystem services at the scale of Conservation efforts have used distribution model of landscape, different indices including DIVISION, species to understand the relationship between the envi- SPLIT, MESH (Mehdipour et al. 2019), Landscape ronment and biodiversity (Elith and Leathwick 2009; Ecological Risk Index (ERI) (Mo et al. 2017), and Kuemmerlen et al. 2014). Such models take into ac- Infrastructure Fragmentation Index (IFI) (Madadi et al. count the occurrences data of a species and relate them 2017) have been developed to quantify and assess the with environmental characteristics including climate, impacts of roads. topography, distance to water resources, distance to To have an exhaustive assessment of road’simpacts, human settlements, and land use/cover and then predict other parameters related to disturbances of road network the areas where those suitable environmental character- should also be considered. The SPROADI, a recently istics are available. In all cases, it is critically important developed index, uses three sub-indices, including traf- to select and use those environmental characteristics fic intensity (T), which measured the traffic load (per which are relevant to the ecology of the species. In space and time), vicinity impact (V), which quantified recent years, focus has shifted towards determining the roads’ effects on neighboring habitats, and fragmen- and including the threat distribution in these models tation grade (F), which calculated the landscape frag- (Allan et al. 2013; Tulloch et al. 2015). GLOBIO mentation degree caused by roads, in calculating the (Alkemade et al. 2009), which is based on the mean cumulative effects of roads on natural habitats species abundance (MSA) and (Tallis et al. 2014)onthe (Freudenberger et al. 2013; Nematollahi et al. 2017). estimation of habitat quality, is considered the example The main goal of this study was modeling and of such models. In contrast to GLOBIO, in which the assessing the habitat quality of wild sheep (Ovis index of biodiversity is related to the baseline corre- orientalis), in Chaharmahal and Bakhtiari province, sponding to the similarity of the natural situation, In- which is among the most important habitats for this VEST requires an evaluation to indicate which habitat species in Iran. For this purpose, at first based on litera- type has the best natural conditions. The habitat quality ture reviews and expert knowledge, the environmental module of InVEST, as a new model, proceeds with data variables which reflected the suitable habitats for wild on anthropogenic threats, land use/land cover, and sheep were identified. Then, the habitat quality module of

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InVEST was used as a new method. After that, since road amphibian species, and 22 fish species (Jafari and network in the study area is taken as one of the most Azizi 2015; Department of Environmental Protection important risk factors for wild sheep and high density of Agency of Chaharmahal and Bakhtiari Province that (0.29 km/km2) has caused habitat fragmentation and 2007). This province consisted 1 national natural mon- habitat loss, the ecological impacts of road network on ument (Fritillaria imperialis), 1 wildlife refuge wild sheep’s habitats were assessed using the SPROADI. (Shirestan), and 5 protected areas (Tang-e-Sayyad, To this end, the restoration/protection plans were identi- Sabzkouh, Helen, Sheyda, and Gheisari) which cover fied and prioritized for reducing the impacts of road 12.5% of this province area (Department of network for those affected areas. Environmental Protection Agency of Chaharmahal and Bakhtiari Province 2007). Figure 1 shows the location of the protected areas in the Ch & B province. However, Materials and methods because of the high rates of land use change and the high density of road network, these natural habitats are highly Study area vulnerable.

Our study area was the Chaharmahal and Bakhtiari (Ch Input data & B) province which is located in the southwestern part of Iran and the central part of the Zagros Mountain The main input data used in the InVEST habitat quality Chains, with an approximate area of 16,332 km2 and module and SPROAD index are given in Table 1. average altitude of 2153 m. The average annual temper- ature is between 8.5° and 20° and the average annual Method rainfall is 560 mm. The Ch & B province has various climatic conditions ranging from hot and dry to cold and The general research methodology of this study is de- wet. Based on the Forests, Ranges and Watershed scribed in Fig. 2 as a flowchart. Organization (2004) and the management and planning organization (2019), about 55.6% (908 thousand hect- Description of the habitat quality module of InVEST ares), 20.57% (336 thousands hectares), and 9.6% (156,617 ha) areas of this province are rangelands, In this part of the study, the habitat quality module of forests, and agricultural lands, respectively, and about InVEST was used to assess and map the habitat quality 14.23% of this province is human settlements, outcrops, and habitat degradation of the study area (Tallis et al. rivers, and wetlands (Soltani et al. 2010; Zare et al. 2014; Sallustio et al. 2017). This module used HQ as a 2011)(theSupplementary data). Ten percent of Iran’s representative for biodiversity associated with different freshwater, as rivers and wetlands, flows in this prov- land use and land cover (LULC) classes (Tallis et al. ince, though it covers only 1% of Iran’s land area. Forty- 2014). As reported by Terrado et al. (2016), “this model nine percent and 27% of this province include hills and was based on the hypothesis that areas with higher mountains, respectively, and the other 24% encom- habitat quality supported higher richness of native spe- passes alluvial plains and plateaus (Jafari and Azizi cies, and that decrease of habitat extent and quality led 2015;Jafarietal.2019). The high topographic diversity to a decline in species persistence.” This model calcu- including Alpine (Niveal: < 3000 m and Subniveal: lates the quality of habitat for each LULC pixel. The 2400–3000 m) and Timberline (1900 m) and the InVEST habitat quality module is estimated as a func- resulting climatic diversity have led to the emergence tion of (a) the suitability of each land use/land cover type of significant ecological slopes in the region and caused for providing suitable habitat for biodiversity, (b) differ- a high diversity of ecosystems which have provided ent kinds of anthropogenic threats have negative effects suitable habitats for a high variety of plant and animal on the quality of the habitats, and (c) the sensitivity of species (Jafari 2014; Department of Environmental each LU/LC type to each threat (Terrado et al. 2016). Protection Agency of Chaharmahal and Bakhtiari An input LU/LC map of the Ch & B was gathered Province 2007)(theSupplementary data). This province from the Regional Land Cover map (2012) and updated has been supporting 923 plant species, 62 mammal using Landsat ETM+ and field visiting, and the land use species, 170 bird species, 35 reptile species, 5 map was classified in 15 different main categories

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Fig. 1 Location of the study area and protected areas corresponding to the habitat types (Fig. 3). Five of these A relative value of habitat suitability (Hj) is between LULC classes were considered main sources of degra- 0 and 1, where1 is assigned to each habitat type which dation which were categorized based on their features to has maximum suitability for the target species. One of have a better understanding of its effects on the habitat the most important characteristics of this model is its quality and biodiversity (i.e., roads, mine, agricultural capacity to consider the sensitivity of each habitat type lands, dry farming lands, and settlements). to various threats including industrial sources,

Table 1 Input data used for the InVEST habitat quality module and SPROAD Index

Model Required input Data used

InVEST Land use/ land cover map Regional vector land cover map produced by the department of natural resources and updated using satellite images (ETM+ and OLI), rasterized. Threat to habitats A list of identified threats to biodiversity. To each threat, a weight and distance decay was assigned based on the outcomes of a survey involving 10 selected experts in the field of biodiversity and environmental assessments. Impact sources A raster map showing the spatial distribution of each of the 9 above-mentioned threats Habitat types and sensitivity of each A matrix listing land cover types in the first column; for each land cover, a (0–1) score of habitat to each threat its suitability to be regarded as habitat (second column), and a (0–1) score of its sensitivity to each of the 9 above-mentioned threats (3rd to 11th column) is given; sensitivity levels were assigned through an expert-based approach. Half-saturation constant Default value (i.e., 0.5). SPROAD Road network map Topographic map with the scale of 1/50000 and Google Earth Index Traffic data Institution of roads transportation of Chaharmahal and Bakhtiari province

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Land use/ Anthropogenic Traffic Vicinity Fragmentation cover map threats maps Intensity Impact Grade

Using InVEST Habitat Using SPROADI Index Quality module

Habitat Degradation Habitat Quality Road Disturbances Map map (HD) map (HQ) (SPROADI)

Overlay

Ecological Impacts Assessments of Road Network

Degree of habitat quality and roads disturbances in each protected area

Identification & Prioritization of Protection/ restoration plans

Fig. 2 General research methodology flowchart transportation infrastructures, and settlements. For this habitat type to a threat (Sjr). It means that the more purpose, each threat source is mapped as raster in which sensitive a habitat type is to a threat, the more degraded the grid cell value (normalized between 0, as the lowest it is by the threat. In our study, Hj and the threat threat, and 1, as the highest threat) reveals the threat parameters were initially determined from literature re- intensity within each cell. The threats’ impacts on the view and expert knowledge (Terrado et al. 2016; habitats in each grid cell are mediated by the following Sallustio et al. 2017). Ten experts with different ecolog- factors: (1) the distance between the sources of the threat ical backgrounds, ranging from experimental ecology and the grid cell (Max.D is defined as the maximum and ecological modeling to ecological impact assess- distance over which the threat affects the habitat suit- ment, were asked to propose values for the parameters ability; (2) the threat’srelativeweight(thethreat’sim- of the model. In advance of expert scoring, the function- portance compared with the others is defined as Wr); ing of the InVEST habitat quality model, the parame- and (3) the habitat types’ relative sensitivity to the ters, and the structure and meaning of the tables they threats (Sjr) (Terrado et al. 2016). should fill in were described in details (the In general, the threats’ impacts on the habitats are Supplementary Data). reduced as distance from the degradation source grows, so that the grid cells closer to the threat sources would Spatial Road Disturbance Index development experience greater impacts. Wr, which is ranged between 0 and 1, indicates the relative destructiveness of To have an exhaustive assessment of roads’ impacts on a degradation source to all kinds of habitats. In addition, natural habitats of the study area, the recently developed this model considers the relative sensitivity of each SPROAD Index was used. To calculate this landscape

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Fig. 3 Land use map of the study area

index including traffic intensity (T), vicinity impact (V), northeastern parts of the study area, and then decreased and fragmentation grade (F), the layer of the traffic data to the south and western parts (Fig. 4, up). The results with the resolution of 1 km2 (UNEP 2001;Eigenbrod showed that 15% of this province consisted of the most et al. 2009; Makki et al. 2013; Nematollahi et al. 2017) suitable habitats for Wild Sheep. In this regard, this was used as the basic layer in producing these indices. In species is a resident of foothills where important envi- this part, the formula developed by Freudenberger et al. ronmental characteristics, including vegetation cover (2013) was used (Table 2) (Nematollahi et al. 2017). (Scariola orientalis and Astragalus spp.), slope (5– 20%), distance to settlements (8–13 km), availability of water (spring and river), distance to roads (> 3 km), Results and discussion and the possibility of escaping from predators like the Persian leopard and gray wolves which positively influ- Habitat quality and habitat degradation enced the wild sheep presence, are found; the high values of HQ were concentrated around these areas. The spatial patterns of habitat quality and habitat degra- These results were in accordance with the ecology of dation maps were different across the study area (Fig. 4). this species as cited in the relevant literature (Shackleton HQ (habitat quality) values, which ranged between 0 and and the IUCN/SSC Caprinae Specialist Group and 1, were generally higher along the east and 1997; Firouz 2005;Ziaei2009; Maleki Najafabadi

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Table 2 Formula which used for calculating each sub-indices and the SPROAD Index (Freudenberger et al. 2013; Nematollahi et al. 2017)

Sub-indices Formula Explanation

Traffic intensity (T ) T = Traffic intensity in grid k k nk k R = road length T k ¼ ∑Rk;iTVk;i k,I i¼1 TVk,i = number of vehicles per hour (which provided by institution of roads transportation) Vicinity impact (V ) V = vicinity impact on grid k k nk k 1 T = traffic intensity in an adjacent (v) grid cell V k ¼ : ∑T k;v k,v nk v¼1 v = {1, 2, 3, …,nk{ nk = number of surrounding cells of grid cell k

Fragmentation grade (F) Fk = fragmentation grade of a grid cell k ¼ Ak Fk n compl ∑ k ; : j={1,2,3,,nk}, number of polygons j¼1A j k A j;k nk = number of polygons without roads belonging to a grid cell k Ak =areasizeofagridcellk (m2) Aj,k = area size of the fraction of a polygon j lying within a grid cell k (m2)

compl 2 A j:k j = area size of the complete polygon j that Aj,k is part of (m )

n SPROADIk ¼ ∑ wi:Ik:norm 1

SPROADIk Spatial Road Disturbance Index of a grid cell k n number of sub-indices (in this case: 3) wi ={wT, wV, wF}wherew stands for the assigned weight for each of the sub-indices. In this study, we assigned equal weights to each, i.e., wi =0.33 et al. 2010; Makki et al. 2013;Keyaetal.2016;Jafari suitability and quality for wild sheep, but closer to et al. 2019). threats. Therefore, those high suitable areas, for instance In addition, the HQ values were decreased around the the Tang-e-Sayyad National Park and the protected area, major urban areas of Farokhshar, Lordegan, Shahrekord, which is surrounded by roads as a human threat, were and Borujen. These areas had the highest human popu- more sensitive to human disturbance; accordingly, it had lation densities because historically, they were mainly a moderate value in the HD map. dedicated to the industrial and agricultural developments. Indeed, these low values were due to the existence of Testing InVEST assessment with species distribution LULC classes with low HQ values, including industrial, data urban areas, intensive agricultural lands, and high density of road network. We tested the reliability of the habitat In this part of the study, we tested the reliability of the quality values by comparing them with presence data of habitat quality values by comparing its map with pres- wild sheep obtained from the DOE. ence data of wild sheep obtained from the DOE (Fig. 5). HD (habitat degradation) values, which combined Based on the distribution map and the existing presence the overall human threats in the study area, ranged from data, the east and northeastern parts of the Ch & B 0, with the lowest human disturbances, to 1.129, with province, consisting the Sheyda Protected Area and the highest cumulative effects of human disturbances Tang-e-Sayyad National Park and Protected Area, were (Fig. 4, down). The high values of HD were concentrat- among “the most suitable habitats” for wild sheep, be- ed around the major urban areas in the northeast and cause important environmental characteristics including central parts with high density of road network, and vegetation cover (Scariola orientalis and Astragalus industrial and residential areas. The InVEST habitat spp.), slope (5–20%), distance to settlements (8– quality module also considered the sensitivity of the 13 km), availability of water (river and spring), and suitable habitats to threats and spatially explicit them distance to roads (> 3 km), which provided both nutri- on the map. The moderate values of HD on the map tional and security needs and critically influenced the were concentrated around the areas which had high wild sheep presence, were found in these areas,

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Fig. 4 Distribution of (a) habitat quality (up) and (b) habitat degradation (down) maps of wild sheep at Chaharmahal and Bakhtiari

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Fig. 5 Overlaying habitat quality map and presence points of wild sheep in the Ch & B province especially the Tang-e-Sayyad National Park and mountainous and steppe were among the “low to Protected Area, and Sheyda Protected Area moderate suitable habitats”, for wild sheep in the (Shackleton and and the IUCN/SSC Caprinae Specialist Ch & B province. Group 1997;Firouz2005;Ziaei2009;Maleki Najafabadi et al. 2010; Makki et al. 2013;Keyaetal. Results of the SPROAD Index 2016;Jafarietal.2019; Malakoutikhah et al. 2020). The study conducted by Jafari et al. (2019), confirmed that The total amount of road length and road density across the the Tang-e-Sayyad National Park and Protected Area Ch & B province was about 4800 km and 0.29 km/km2, was among the most suitable habitat for wild sheep due respectively, which meant that the road density was higher to its large hillside (approximately, 65% of the area), in this province, compared with other adjacent provinces availability of water (rivers and 42 springs), distance to including Lorestan (0.2), Isfahan (0.1), and Khuzestan settlement (8–13 km), and high number of guard camps. (0.06), and to the whole country (0.13) (Ministry of Additionally, 85% of this area is covered by Scariola Roads and Urban Development of Islamic Republic of orientalis and Astragalus spp., which are among the Iran 2018). In regard to the high quality of this province most suitable vegetation types for wild sheep. Besides, for a variety of animal and plant species including wild based on the annual consensus of the DOE, approxi- sheep, this amount of road density was inconsequent. The mately 4000 to 5000 wild sheep are found in the Tang- mean numbers of vehicles per time (hr) for some main e-Sayyad National Park and Protected Area which roads of the study area are shown in Table 3 (Department confirmed the high qualityandsuitabilityofthis of Manitanance and Transportation of Ch & B 2019). area for this species (Department of Environmental Figure 6 shows all raster maps of traffic intensity, protection of Caharmahal and Bakhtiari 2018). But vicinity impact, fragmentation grade, and the SPROAD the Helen and Sabzkouh Protected Areas which are Index. The amounts of traffic intensity and vicinity

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Table 3 The average number of vehicles per hours in the main networks’ impacts on the study area (Fig. 6 (4)), there roads was a significant positive spatial correlation between The name of road section Number of vehicles per hour these two maps showing that there was a high value of disturbances in the northeast and central parts of the Shahrekurd-Chelgerd 501 study area. In other words, the road’s density was higher Naghan-Dehdez 320 in the northeast and central parts of the Ch & B prov- Jankan 294 ince, which has been resulted in higher rates of urbani- Ganduman-Borujen 294 zation and industrial developments and consequently Soreshjan-Farsan 244 caused a high ratio of human disturbances. Accordingly, Borujen-Buldaji 123 compared with other threats, road network was the main Chelehgah-Lordegan 121 risk element in the study area, which negatively affected the wild sheep habitats at a landscape scale. In this part of the study, to assess the ecological impact were high in the northeast, southwest, and cen- impacts of road network on suitable habitats for wild tral parts, where the Shahrekord-Dimeh and Naghan- sheep, the habitat quality map of wild sheep across the Dehdez main roads with high traffic load are located study area, obtained from the InVEST habitat quality (Fig. 6 (1) and (2)). The east and northeastern parts module, and the map of the SPROAD Index were over- suffered high level of habitat fragmentation caused by laid (Fig. 7). Dolgener et al. (2014) showed that, con- the high road’s density (Fig. 6 (3)). sidering the ecological impacts of road network, the use Figure 6 (4) shows that the SPROADI value, which of the SPROAD Index was an important factor for focused only on the negative impacts of the road net- modeling and assessing the quality of fire-bellied toad work, ranged from 0 to 54.48, and revealed that about Bombina bombina’s habitats in Germany. Figure 7 in- 28% of the Ch & B province was affected by road dicated that though 15% of the study area was consid- network. The high degree of road disturbances was ered as the most suitable habitats for wild sheep, about found at the vicinity of the Shalamzar-Naghan, 28% of the study area, including suitable habitats for Burujen-Buldaji, and Gandoman-Gosheki main roads wild sheep in some parts, was negatively affected by in the northeast and central parts, where suitable habitats road network. After overlaying this map with the for wild sheep were also recorded. This amount of road protected areas’ network map, Table 4, which shows disturbances in these areas was because of high traffic the percentage of habitat quality and road disturbances load and high degree of habitat fragmentation. The high for each protected area, was obtained. The results of this level of road’s density (0.29 km/km2)resultedinhabitat part, revealed that the Tang-e-Sayyad National Park and fragmentation, barrier effects, and more accessibility to Protected Area, and the Sheyda Protected Area which key conservation and suitable habitats including the were among the most important and suitable habitats for Tang-e-Sayyad National Park and Protected Area, wild sheep and located in the east and northern parts, Sheyda Protected Area, and Helen and Sabzkouh respectively, were highly affected by roads Protected Areas which increased their vulnerability. Be- (Shahrekord-Borujen) surrounding these protected sides, approximately 20 animal-vehicle accidents per areas. Besides, the Helen and Sabzkouh Protected Areas year are reported in these roads, which confirmed the which are located in the central parts experienced the negative impacts of road network in this province highest degree of roads disturbances (Fig. 7and (Department of Environmental protection of Table 4). This level of disturbances was caused by the Caharmahal and Bakhtiari 2018). Naghan-Dehdez and Lordegan-Sarkhun main roads that surrounded and crossed these protected areas. Road Combining the linear and area-covering indices network could negatively affect this species and its to realize a combined habitat assessment habitats by increasing the rate of animal-vehicle collision and the edge effects (Forman et al. 2003; Grilo et al. Based on the results of the HD map obtained from the 2010; Bruschi et al. 2015; De Montis et al. 2018; InVEST habitat quality module, which modeled the Ogletree et al. 2019), reducing the amount and quality overall threats in the study area (Fig. 4, up), and the of habitats (Forman et al. 2003; Grilo et al. 2010; SPROAD Index, which combined three aspects of road Sánchez-de-Jesús et al. 2016), and also increasing noise,

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Fig. 6 (1) Traffic intensity (T), (2) vicinity impact (V), (3) frag- high road disturbance, low values in dark purple represent low mentation grade (F), and (4) the combination of the three sub- road disturbance along the different sub-indices or the overall indices into the SPROADI; high values in light yellow represent SPROADI outcome

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Fig. 7 Overlaying the maps of HQ and the SPROAD Index

air, and light pollution (Dean et al. 2019). Besides, roads Esperandio et al. 2019). In addition, road network has have caused habitat fragmentation which itself is result- facilitated human access to important habitats of wildlife ed in a decrease in the landscape connectivity and in- and increased the human-caused mortality and land use crease of wildlife population isolation; consequently, a change (Proctor et al. 2020). loss of genetic diversity will be brought about Based on the overlaying maps of the SPROAD Index (Ascensão et al. 2016; De Montis et al. 2018; and HQ (Fig. 7), and the percentage of habitat quality and road disturbances for each protected area (Table 4), Table 5, which was obtained from expert knowledge Table 4 The percentage of habitat quality and SPROADI for each and literature reviews (Clarke et al. 2010;Brands2016; protected area Palmer et al. 2016), shows the consequences for some Protected area SPROADI % Habitat quality (HQ) % possible protection/restoration plans and their priority (low, moderate, and high) for each protected area and Low High Low Medium High highlighted how the two methods were complemented. Tang-e-Sayyad 12.24 10.21 5 7 85.83 Protection and restoration plans included all possible Sheyda 12.85 12 37.3 15 17 actions, in terms of restoration, construction, and con- Sabzkouh 9.21 7.69 23.68 23.95 servation taken to minimize negative impacts of road ’ Helen 16.5 14.5 4 15.62 network, either by controlling the impacts sources or the exposure to ecological receptors. The aim of these

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Table 5 The consequences for protection/restoration planning

Plans Protected areas

Tang-e-Sayyad Sheyda Helen Sabzkouh National Park and Protected Protected Protected Protected Area Area Area Area

LMHLMHLMHLMH

Restoration of Springs and watering places ■■■■ Historic migratory corridors ■■ ■ ■ Lands changed to dry farming and orchards ■■ ■■ Rangeland and forests removed by the road construction ■■ ■■ Viaduct bridge ■■ Wire fencing (height > 1 m) ■■ ■ ■ Wildlife overpass ■■ Guard’s camp and stations ■■■■ Conservation of Overgrazing and illegal poaching ■■■■ Cutting trees and shrubs and convert to charcoal ■■ ■■ The speed of service vehicles along project roads ■■ ■■ Motorized access management ■■ ■■ Include wildlife awareness information in regular safety ■■■■ and environmental inductions. Existing infrastructure for access and minimize ■■ ■■ construction of new roads The passage of gas, oil, electricity, water pipelines ■■ ■■ and roads from the area Traditional rangeland management techniques ■■■■

Low (L), medium (M), and high (H) priority for restoration/conservation actions plans was identifying options which safeguard biodiver- high number of this species in these areas while their sity and ecosystem services (Rajvanshi et al. 2007;Van home range is restricted by road network that der Grift et al. 2013; Magintan 2013). heightens concerns on conservation of these species. Some of these plans were described as follows: The reason is that the carrying capacity, which is affected by socioeconomic development and vegeta- – Restoration of springs and watering places, replace- tion succession, limits the viability of this species’ ment of rangeland and forests removed by road con- population (Van der Grift et al. 2013). So, to avoid struction, and restoration of historic migratory corri- this problem, it is necessary to restore and make their dors that improve the migration and gene flow be- historical migratory corridors safe to guide target tween isolated populations were some of the possible species across these corridors and try to increase gene plans which could restore the protected areas. Based flow and expand their home range. on this table, the Tang-e-Sayyad National Park and – Designation and construction of crossing structures Protected Area, and Sheyda Protected Area needed including wire fencing (Clevenger and Huijser 2011; high-priority and moderate-priority restoration plans, Van der Grift et al. 2013;Magintan2013;Jarvisetal. respectively, in terms of historic migratory corridors. 2019) and wildlife overpass (Iuell et al. 2003; The reason was that, on one hand, these two areas Forman et al. 2003; Clevenger and Walto 2005; were considered as the most suitable habitats for wild VanderGriftetal.2013; Gülci and Akay 2015; sheep; on the other hand, both of them were highly Magintan 2013) were among the most effective tech- affected by the roads that surrounded these two areas niques which minimized the barrier effects of roads which limited the migration of this species. There is a and facilitated species mobility through the

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fragmented landscape. Fences are designed to pre- species on the IUCN Red List, as an indicator of eco- vent the access of animals to roads with the purpose system services. Then, the ecological impacts of anthro- of reducing the number of species-vehicle accidents pogenic threats especially road network on their habitats on the roads. These fences should be placed where in the Ch & B province, which has been among the most there is a high risk of wildlife accidents. The con- suitable habitats for wild sheep, were assessed. For this struction of overpasses has two main objectives: (a) purpose, the habitat quality of wild sheep in the study connecting isolated habitats and wildlife populations, area was modeled using the habitat quality module of and (b) ensuring the safety of species mobility and the InVEST. Then, considering the habitat services reducing accidents on roads. Only native plant spe- model, the SPROADI, was applied for assessing the cies to the local area should be used on the overpass ecological impacts of road network. There has been a because they should reflect the habitats situated on lack of studies on the importance of ecosystem service either side of the infrastructure. A standard width of modeling in assessing the ecological impacts of road 40 to 59 m was recommended by Iuell et al. (2003). network. Therefore, this study exemplifies the advan- Although the Helen and Sabzkouh Protected Areas tages of using the InVEST habitat quality module to- were among the “low to moderate suitable habitats” gether with the SPROAD Index for assessing ecological for wild sheep, these two areas have been supporting impacts of transportation infrastructures on natural hab- a variety of animal and plant species. These two itats. Our results revealed that in addition to habitat protected areas were highly affected by road net- fragmentation, the road network could have negative work. Therefore, to mitigate the impacts of roads impacts on natural habitats by reducing the original area on these areas, conservation implication is necessary. of the habitat and decreasing the quality of the remain- One of the useful tools for reducing the barrier effects ing habitats. Overall, findings of our study provided of roads on natural habitats of wildlife, in this case, valuable information on the spatially explicit distribu- was “Overpass Wildlife,” which connected the hab- tion of habitat quality, habitat degradation, and spatial itats and wildlife populations in terms of reducing the road disturbance, which complemented each other by fragmentation effects of roads which crossed these providing useful maps and data. These maps and data protected areas. The combination of wildlife over- showed the degree of habitat quality on one hand, and passes and fences was more recommended to im- the degree of habitat degradation caused by road net- prove connectivity for animals and reduce the num- work, on the other hand. These inputs and data were ber of animal-vehicle accidents (Huijser et al. 2008). useful for conservation planning, restoration planning, – In terms of conservation, some effective actions, and enhancing ecosystem services. Moreover, further including conserving the protected areas from detailed studies are needed to be carried out on the overgrazing, illegal poaching, cutting trees, shrubs, Tang-e-Sayyad National Park and Protected Area, and and also, controlling the motorized access, were Sheyda Protected Area which were among the most recommended in the table. These actions would be suitable habitats for wild sheep but experienced signif- useful in areas where roads occurred in the most icant impacts of road network development. suitable habitats, within and near the identified link- age areas between the isolated habitats and popula- Acknowledgments We are grateful to the Department of the tions (Proctor et al. 2020). In addition, placing the Environment of Iran (DOE). We thank guards of the Helen and Sabzkouh Protected Areas and Tang-e-Sayyad National Park and warning signs of wild sheep near the area where Protected Area, local people, Mr. Tooraj Reisei and Mr. Ghadir species often cross the roadways and also in zones Valipour, for their valuable inputs and cooperation to this study. where the collisions often occur is effective (Iuell et al. 2003; Magintan 2013).

Conclusion References

The present study focused on the habitat quality model- Albert, C., Galler, C., Hermes, J., Neuendorf, F., Von Haaren, C., ing of wild sheep, which is classified as vulnerable & Lovett, A. (2016). Applying ecosystem services indicators

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in landscape planning and management: the ES-in-Planning park and protected area, Helen and Sabzkouh protected areas. framework. Ecological Indicators, 61,100–113. Unpublished reports. Alkemade, R., van Oorschot, M., Miles, L., Nellemann, C., Department of Manitanance and Transportation of Chaharmahal Bakkenes, M., & ten Brink, B. (2009). GLOBIO3: a frame- & Bakhtiari. (2019). Online document of reports, statistics work to investigate options for reducing global terrestrial and traffic information of roads. http://charmahal.rmto.ir/. biodiversity loss. Ecosystems, 12,374–390. Dolgener, N., Freudenberger, L., Schneeweiss, N., Ibisch, P. L., & Allan, J. D., McIntyre, P. B., Smith, S. D., Halpern, B. S., Boyer, Tiedemann, R. (2014). Projecting current and potential future G. L., Buchsbaum, A., Burton, G. A., Campbell, L. M., distribution of the fire-bellied toad Bombina bombina under Chadderton,W.L.,Ciborowski,J.J.,&Doran,P.J. climate change in north-eastern Germany. Regional (2013). Joint analysis of stressors and ecosystem services to Environmental Change, 14(3), 1063–1072. enhance restoration effectiveness. Proceedings of the Eigenbrod, F., Hecnar, S. J., & Fahrig, L. (2009). Quantifying the National Academy of Sciences, 110(1), 372–377. road effect zone: threshold effects of a motorway on anuran Ascensão, F., Mata, C., Malo, J. E., Ruiz-Capillas, P., Silva, C., populations in Ontario. Ecology and Society, 14(1), 24. Silva, A. P., Santos-Reis, M., & Fernandes, C. (2016). Elith, J., & Leathwick, J. R. (2009). Species distribution models: Disentangle the causes of the road barrier effect in small ecological explanation and prediction across space and time. mammals through genetic patterns. PLoS One, 11(3), Annual Review of Ecology, Evolution, and Systematics, 40, e0151500. 677–697. Baral, H., Keenan, R. J., Sharma, S. K., Stork, N. E., & Kasel, S. Esperandio, I. B., Ascensão, F., Kindel, A., Tchaicka, L., & de (2014). Spatial assessment and mapping of biodiversity and Freitas, T. R. O. (2019). Do roads act as a barrier to gene flow conservation priorities in a heavily modified and fragmented of subterranean small mammals? A case study with – production landscape in north-central Victoria, Australia. Ctenomys minutus. Conservation Genetics, 20(2), 385 393. Ecological Indicators, 36,552–562. Firouz, E. (2005). The complete Fauna of Iran. I.B. Tauris Brands, L. (2016). Using stepping stones and translocations to Publication, London. p. 322. ISBN: 185043946X, facilitate dispersal for the endangered Ord’s kangaroo rat, 9781850439462. Dipodomys ordii, PhD Thesis, University of Calgary. 169 pp. Forman, R. T. T., Sperling, D., Bissonette, J. A.,Clevenger, A. P., Cutshall,C. D., Dale, V. H., Fahrig, L., France, R. L., Bruschi, D., Garcia, D. A., Gugliermetti, F., & Cumo, F. (2015). Goldman, Ch. R., Heanue, K., Jones, J., Swanson, F., Characterizing the fragmentation level of Italian’s National Turrentine, Th., & Winter, Th. C. (2003). Road ecology: Parks due to transportation infrastructures. Transportation science and solutions. Washington, DC: Island Press, 504 p. Research Part D: Transport and Environment, 36,18–28. Freudenberger, L. R., Hobson, P., Rupic, S., Pe’er, G., Schluck, Butchart,S.H.,Walpole,M.,Collen,B.,VanStrien,A., M., Sauermann, J., Kreft, S., Selva, N., Ibisch, L., & P. Scharlemann, J. P., Almond, R. E., Baillie, J. E., Bomhard, (2013). Spatial road disturbance index (SPROADI) for con- B., Brown, C., Bruno, J., & Carpenter, K. E. (2010). Global servation planning: a novel landscape index, demonstrated biodiversity: indicators of recent declines. Science, fortheStateofBrandenburg,Germany.Landscape Ecology, 328(5982), 1164–1168. 28(7), 1353–1369. Clarke, I., Stokes, Z., & Wallace, R. (2010). Habitat restoration Grêt-Regamey, A., Weibel, B., Kienast, F., Rabe, S. E., & Zulian, planning guide for natural resource managers. Government G. (2015). A tiered approach for mapping ecosystem ser- of South Australia, through Department of Environment and vices. Ecosystem Services, 13,16–27. Natural Resources, Adelaide. Retrieved January, 12, p. Grilo, C., Bissonette, J. A., & Cramer, P. C. (2010). Mitigation Clevenger, A. P., & Huijser, M.P. (2011). Wildlife crossing struc- measures to reduce impacts on biodiversity. In S. R. Jones ture handbook: design and evaluation in North America. (Ed.), Highways: construction, management, and mainte- Report to the Federal Highway Administration. Western nance (pp. 73–114). Nova science publisher. Transportation Institute, Bozeman, Montana. Gülci, S., & Akay, A. E. (2015). Assessment of ecological pas- Clevenger, A. P., & Walto, N. (2005). Performance indices to sages along road networks within the Mediterranean forest identify attributes of highway crossing structures facilitating using GIS-based multi criteria evaluation approach. movement of large mammals. Biological Conservation, 121, Environmental Monitoring and Assessment, 187,779. – 453 464. Hou, Y., Li, B., Müller, F., Fu, Q., & Chen, W. (2018). A De Montis, A., Ledda, A., Ortega, E., Martín, B., & Serra, V. conservation decision-making framework based on ecosys- (2018). Landscape planning and defragmentation measures: tem service hotspot and interaction analyses on multiple an assessment of costs and critical issues. Land Use Policy, scales. Science of the Total Environment, 643,277–291. 72,313–324. Huijser, M.P., McGowen, P., Clevenger, A. P., & Ament, R. Dean, W. R. J., Seymour, C. L., Joseph, G. S., & Foord, S. H. (2008). Best practices manual, wildlife-vehicle collision re- (2019). A review of the impacts of roads on wildlife in semi- duction study, report to U.S. Congress. McLean: Federal arid regions. Diversity, 11(5), 81. Highway Administration. Available from http://www.fhwa. Department of Environmental Protection Agency of Chaharmahal dot.gov/environment/hconnect/wvc/index.htm. & Bakhtiari Province (2007). Environmental scene of Iuell, B., Bekker, G. J., Cuperus, R., Dufek, J., Fry, G., Hicks, C., Chaharmahal & Bakhtiari Province. Office of the Hlavác, V., Keller, V., Rosell, C., Sangwine, T., Tørsløv, N., Directorate of Department of Environmental Protection & le Maire Wandall, B. (2003). COST 341.Habitat fragmen- Agency. (In Farsi). tation due to transportation infrastructure. Wildlife and traf- Department of Environmental protection of Caharmahal & fic: a European handbook for identifying conflicts and de- Bakhtiari (2018). Wildlife census of Tang-e-Sayyad national signing solutions. Utrecht: KNNV Publishers.

Content courtesy of Springer Nature, terms of use apply. Rights reserved. 487 Page 16 of 17 Environ Monit Assess (2020) 192:487

Jafari, A. (2014). Identify the focal areas of the biodiversity of the infrastructure on spatial dynamics of two vulnerable ungulate central Zagros Conservation Area. National Biodiversity species in Ghamishloo Wildlife Refuge, Iran. Ecological Conservation Plan in the Central Zagros Conservation Indicators, 31,6–14. Area. Shahrekord University. 178 p. Malakoutikhah, S., Fakheran, S., Hemami, M. R., Tarkesh, M. & Jafari, A., & Azizi, Z. (2015). Estimation of the extent of land Senn, J. (2020). Assessing future distribution, suitability of affected by ecological network of roads in the Chaharmahal corridors and efficiency of protected areas to conserve vul- & Bakhtiari province. The first National Conference on nerable ungulates under climate change. Diversity and Sustainable Development in Construction with an Distributions,1–14. Environmental Conservation Approach. Shiraz University, Maleki Najafabadi, S., Hemami, M. R., & Salman Mahini, A. Shiraz. (2010). Determining habitat suitability of Ovis orientalis Jafari, A., Zamani-Ahmadmahmoodi, R., & Mirzaei, R. (2019). isfahanica in Mothe wildlife refuge using ENFA. Natural Persian leopard and wild sheep distribution modeling using Environment, 63,279–290. the Maxent model in the Tang-e-Sayad protected area, Iran. Mehdipour, N., Fakheran, S., Soffianian, A., & Pourmanafi, S. Mammalia, 83(1), 84–96. (2019). Road-induced fragmentation and the environmental Jarvis, L. E., Hartup, M., & Petrovan, S. O. (2019). Road mitiga- value of roadless areas in a partly protected landscape in tion using tunnels and fences promotes site connectivity and Central Iran. Environmental Monitoring and Assessment, population expansion for a protected amphibian. European 191(7), 461. Journal of Wildlife Research, 65(2), 27. Millennium Ecosystem Assessment (2005). Ecosystems and hu- Jones, K. R., Venter, O., Fuller, R. A., Allan, J. R., Maxwell, S. L., man well-being: scenarios: findings of the Scenarios Negret, P. J., & Watson, J. E. (2018). One-third of global Working Group Vol. 2. Island Press. protected land is under intense human pressure. Science, Ministry of Roads & Urban Development of Islamic Republic of – 360(6390), 788 791. Iran (2018). Online document of reports, statistics and length Keya, Z. Y., Faryadi, S., Yavari, A., Kamali, Y., & Shabani, A. A. of intercity and rural roads in the country. https://www.mrud. (2016). Habitat suitability & connectivity of Alborz wild ir/. sheep in the east of Tehran, Iran. Open Journal of Ecology, Mitchell, M. G., Suarez-Castro, A. F., Martinez-Harms, M., 6(6), 325–342. Maron, M., McAlpine, C., Gaston, K. J., Johansen, K., & Kienast, F., Bolliger, J., Potschin, M., De Groot, R. S., Verburg, P. Rhodes, J. R. (2015). Reframing landscape fragmentation’s H., Heller, I., Wascher, D., & Haines-Young, R. (2009). effects on ecosystem services. Trends in Ecology & Assessing landscape functions with broad-scale environmen- Evolution, 30(4), 190–198. tal data: insights gained from a prototype development for Mo, W., Wang, Y., Zhang, Y., & Zhuang, D. (2017). Impacts of Europe. Environmental Management, 44(6), 1099–1120. road network expansion on landscape ecological risk in a Kuemmerlen, M., Schmalz, B., Guse, B., Cai, Q., Fohrer, N., & megacity, China: a case study of Beijing. Science of the Total Jähnig, S. C. (2014). Integrating catchment properties in Environment, 574,1000–1011. small scale species distribution models of stream macroin- vertebrates. Ecological Modelling, 277,77–86. Nematollahi, S., Fakheran, S., & Soffianian, A. R. (2017). Lanzas, M., Hermoso, V., de-Miguel, S., Bota, G., & Brotons, L. Ecological impact assessment of road networks at landscape (2019). Designing a network of green infrastructure to en- scale using Spatial Road Disturbance Index (SPROADI). hance the conservation value of protected areas and maintain Journal of Environmental Engineering and Landscape – ecosystem services. Science of the Total Environment, 651, Management, 25(3), 297 304. 541–550. Ogletree, K. A., Mead, A. J., & Boitet, E. R. (2019). Identifying Leh, M. D. K., Matlock, M. D., Cummings, E. C., & Nalley, L. L. roadkill hotspots using a running average. Georgia Journal (2013). Quantifying and mapping multiple of Science, 77(2), 3. ecosystemservices change inWest Africa. Agriculture, Palmer, M. A., Zedler, J. B., & Falk, D. A. (2016). Ecological Ecosystems & Environment, 165,6–18. theory and restoration ecology. In foundations of restoration Madadi, H., Moradi, H., Salmanmahiny, A., Senn, J., & Geneletti, ecology (pp. 3–26). Washington, DC: Island Press. D. (2017). Degradation of natural habitats by roads: compar- Pecl, G. T., Araújo, M. B., Bell, J. D., Blanchard, J., Bonebrake, T. ing land-take and noise effect zone. Environmental Impact C., Chen, I. C., Clark, T. D., Colwell, R. K., Danielsen, F., Assessment Review, 65, 147155. Evengård, B., & Falconi, L. (2017). Biodiversity redistribu- Maes, J., Fabrega, N., Zulian, G., Barbosa, A., Vizcaino, P., Ivits, tion under climate change: Impacts on ecosystems and hu- E., Polce, C, Vandecasteele, I., Marí Rivero, I., Guerra, C., man well-being. Science, 355(6332), eaai9214. Perpiña Castillo, C., Vallecillo, S., Baranzelli, C., Barranco, Proctor, M. F., McLellan, B. N., Stenhouse, G. B., Mowat, G., R., Batista e Silva, F., Jacobs-Crisoni, C., Trombetti, M., & Lamb, C. T., & Boyce, M. S. (2020). Effects of roads and Lavalle, C. (2015). Mapping and assessment of ecosystems motorized human access on grizzly bear populations in and their services, MAES: trends in ecosystems and ecosys- British Columbia and Alberta, Canada. Ursus, 30e2,16–39. tem services in the European Union between 2000 and 2010. Rajvanshi, A., Mathur, V. B., & Iftikhar, U. A. (2007). Best JRC Science and policy report. Publications Office of practice guidance for biodiversity-inclusive impact assess- European Union, Luxembourg. ment: a manual for practitioners and reviewers in South Magintan, D. (2013). Mitigation of roads related impacts on India. CBBIA-IAIA CBBIA-IAIA guidance Series, Capacity wildlife. PhD Thesis. wildlife institute of India. 27 pp. Building in Biodiversity and Impact Assessment (CBBIA) Makki, T., Fakheran, S., Moradi, H., Iravani, M., & Senn, J. PROJECT, International Association for Impact (2013). Landscape–scale impacts of transportation Assessment (IAIA), North Dakota, USApp. 199.

Content courtesy of Springer Nature, terms of use apply. Rights reserved. Environ Monit Assess (2020) 192:487 Page 17 of 17 487

Sallustio, L., De Toni, A., Strollo, A., Di Febbraro, M., Gissi, E., engineering office, remote sensing group and Geographic Casella, L., Geneletti, D., Munafò, M., Vizzarri, M., & information system. pp: 1–138. Marchetti, M. (2017). Assessing habitat quality in relation The management and planning organization of Chaharmahal & to the spatial distribution of protected areas in Italy. Journal Bakhtiari province (2019). Land use planning studies of of Environmental Management, 201,129–137. Chaharmahal & Bakhtiari province pp: 1–275. (In Farsi). Sánchez-de-Jesús, H. A., Arroyo-Rodríguez, V., Andresen, E., & Tulloch, V. J., Tulloch, A. I., Visconti, P., Halpern, B. S., Watson, Escobar, F. (2016). Forest loss and matrix composition are J. E., Evans, M. C., Auerbach, N. A., Barnes, M., Beger, M., the major drivers shaping dung beetle assemblages in a Chadès, I., & Giakoumi, S. (2015). Why do we map threats? fragmented rainforest. Landscape Ecology, 31(4), 843–854. Linking threat mapping with actions to make better conser- Selva, N., Kreft, S., Kati, V., Schluck, M., Jonsson, B., Mihok, B., vation decisions. Frontiers in Ecology and the Environment, Okarma, H., & Ibisch, P. L. (2011). Road less and low–traffic 13(2), 91–99. areas as conservation targets in Europe. Environmental UNEP (2001). Globio: Global methodology for mapping human – Management, 48(5), 865 877. impacts on the biosphere. UNEP/DEWA/TR.01–3. Shackleton, D. M. (ed.) and the IUCN/SSC Caprinae Specialist Environment Information and Assessment Technical Group. (1997). Wild sheep and goats and their relatives. Report. UNEP. Nairobi, UNEP: 55. Status Survey and Conservation Action Plan for Caprinae. Van der Grift, E. A., Van der Ree, R., Fahrig, L., Findlay, S., 390 + vii pp. IUCN, Gland, Switzerland and Cambridge, UK. Houlahan, J., Jaeger, J. A., Klar, N., Madrinan, L. F., & Soltani, S., Yaghmaei, L., Khodagholi, M., & Sabouhi, R. (2010). Olson, L. (2013). Evaluating the effectiveness of road miti- Bioclimatic zoning of Chaharmahal and Bakhtiari province gation measures. Biodiversity and Conservation, 22(2), 425– using multivariate statistical methods. Journal of 448. Agricultural Sciences and Technology and Natural Zare, S., Nemati, H., Ashuri, P. & Shirmohammadi, H. A. (2011). Resources, Water and Soil Sciences, 54(6), 53–68. Recognition plan of the country’s ecological areas: plant Tallis, H. T., Ricketts, T., Guerry, A. D., Wood, S. A., Sharp, R., types of Chaharmahal & Bakhtiari province. Forest and Nelson, E., Ennaanay, D., Wolny, S., Olwero, N., Vigerstol, rangeland research institute 186 pp. Chaharmahal & K., & Pennington, D. (2014). Integrated valuation of envi- bakhtiari, Iran. ronmental services and tradeoffs (InVEST) 3.1. 0 user’s guide. Natural Capital Project. Ziaei, H (2009). A field guid to the mammals of Iran. Third Terrado, M., Sabater, S., Chaplin-Kramer, B., Mandle, L., Ziv, G., edition, 432 pp. Iran Wild Life Center Publication. ISBN: & Acuña, V. (2016). Model development for the assessment 978-964-04-19-69-0. of terrestrial and aquatic habitat quality in conservation planning. Science of the Total Environment, 540,63–70. Publisher’snoteSpringer Nature remains neutral with regard to The Forests, Ranges and Watershed Organization (2004). Report jurisdictional claims in published maps and institutional of preparing the national country's vegetation map. The affiliations.

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