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Volume 40, Issue 3 (2025)
GeoRes 2025, 40(3): 267-277 |
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Received: 2025/07/31 | Accepted: 2025/09/19 | Published: 2025/10/2
Received: 2025/07/31 | Accepted: 2025/09/19 | Published: 2025/10/2
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Gravand F, Hasani Shah Shahidani E, Fallah Mojaver M, Hejazi S, Kafaei S. Dynamic Role of Vegetation 3D Structure and the Cumulative Effects of Human Threats on the Habitat Suitability of the Caspian Roe Deer. GeoRes 2025; 40 (3) :267-277
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1- Department of Environment Guilan Province, Rasht, Iran
2- Cohort Center, Guilan University of Medical Sciences, Rasht, Iran
3- Department of Environment Kerman Province, Kerman, Iran
2- Cohort Center, Guilan University of Medical Sciences, Rasht, Iran
3- Department of Environment Kerman Province, Kerman, Iran
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Background
Habitat degradation and fragmentation in the Hyrcanian forests, especially under human and climatic pressures, have led to a severe decline in the Caspian red deer population. Although species distribution models such as MaxEnt and ENFA are applied, these methods alone are insufficient for a comprehensive analysis of habitat quality, highlighting the need for an integrated approach for more accurate assessment.
Previous Studies
Previous studies have extensively reported the consequences of habitat degradation and fragmentation on biodiversity at structural, functional, and genetic levels. Newbold et al. (2015) and Di Marco et al. (2019) have demonstrated that human activities such as agricultural expansion, logging, and road construction reduce vegetation integrity and lower habitat quality for sensitive forest species. Global studies have also confirmed a significant decline in forest mammal populations due to human pressures; in particular, Dirzo et al. (2014) have estimated that the Caspian red deer population declined by over 80% over a 40-year period.
In the field of ecological niche modeling, research has shown the high accuracy of the MaxEnt model in predicting species distributions and analyzing influential environmental factors (Elith et al., 2011; Phillips et al., 2017). Additionally, Hirzel et al. (2002) have introduced the ENFA model, which allows the analysis of species marginality and specialization without absence data. However, a review of previous studies indicates that most relied on a single model and have paid limited attention to the multidimensional relationships between habitat structure and human pressures (Elith & Leathwick, 2009).
Aim(s)
The present study aimed to provide a comprehensive analytical framework for assessing the habitat suitability of Caspian red deer in the Hyrcanian forests of northern Iran.
Research Type
The present study was descriptive in nature.
Research Society, Place and Time
This study was descriptive and conducted in 2024. The study population comprised three main habitats of the Caspian red deer including Kordmir, Rokouh-Sara, and Gousalekah located in the Fararud area of Rudbar County, Gilan Province. These sites lie on the slopes of the Hyrcanian forests within the Deylaman–Dorfak protected area, recognized as one of the key biodiversity hotspots in northern Iran.
Sampling Method and Number
In this study, data were collected from three main sources. First, a set of specialized questionnaires was distributed among environmental experts and local residents to identify the habitat requirements of the Caspian red deer and the stressors affecting its habitats. Next, field surveys were conducted to measure habitat parameters, including canopy cover density, understory vegetation, food resources, and evidence of species presence. Subsequently, remote sensing data, including Sentinel-2 satellite imagery and topographic parameters, were extracted to provide the environmental layers required for modeling. In total, 43 presence points of the Caspian red deer were processed, with duplicates removed, and used as input for ecological models.
Used Devices & Materials
In this study, a combination of tools and environmental data was used to assess habitat suitability. Sentinel-2 satellite imagery was employed to extract vegetation indices such as NDVI, and topographic data, including elevation, slope, and aspect, were obtained from the USGS Earth Explorer and ESA Copernicus databases. Field measurements were conducted using vegetation assessment tools to record canopy cover density and observe evidence of species presence. Additionally, ArcGIS 10.8 and QGIS 3.26 were used for spatial processing, Biomapper 4.0 for running the ENFA model, MaxEnt 3.4.4 for predicting species distribution, and SPSS 26 for statistical analyses. Furthermore, data obtained from specialized questionnaires were incorporated as key inputs in the analyses.
Findings
In this study, the evaluation of six habitat parameters and six stress factors across the three habitats including Gousalekah , Kordmir, and Rokouh-Sara revealed significant differences in habitat quality and human pressure. Gousalekah performed best in most vegetation indices, food resources, and forest structure, Kordmir was intermediate, and Rokouh-Sara had the lowest quality (Tables 1 and 2). Analysis of human factors showed that Gousalekah experienced minimal exploitation, livestock density, and waste, while being farthest from human settlements; in contrast, Kordmir and Rokouh-Sara were under higher human pressure (Table 1). Structural vegetation features indicated that Gousalekah had dense canopy and understory, a four-layered structure, and high diversity of edible species, making it the most suitable habitat (Table 2).
Table 1) Ranking of stressor factors
The Habitat Evaluation Procedure (HEP) matrices showed Gousalekah with the highest habitat suitability score (26/30) and lowest human stress (28), followed by Kordmir and Rokouh-Sara (Tables 3 and 4). Combining these matrices in HEP ranked Gousalekah as high suitability (54), Kordmir as medium (43), and Rokouh-Sara as low (34; Figure 1). The Habitat Suitability Index (HSI) values confirmed this pattern: 0.86 for Gusaleh-Gah, 0.73 for Kordmir, and 0.36 for Rokuh-Sara (Figure 2). Spatial HSI mapping indicated that 25% of the area was high suitability, 55% medium, and 20% low, consistent with the three habitat conditions (Figure 3). Sensitivity analysis identified canopy cover (SIV5) and understory (SIV2) as the most influential parameters, contributing 40–42% and 33–36% to HSI variance (Figure 4).
Table 3) Habitat requirements matrix
Table 4) Stressor factors matrix
Figure 1) Total Scores of Habitat Requirements and Stressor Factors
Figure 2) Habitat Suitability Index (HSI) profiles in three habitats
Figure 3) Habitat suitability zoning map
Figure 4) Sensitivity analysis of parameters
Figure 5) MaxEnt Map, evaluation of Caspian Red Deer habitat suitability
Modeling results from MaxEnt demonstrated high accuracy (AUC = 0.91), with NDVI (34%), canopy cover (25%), and distance from villages (18%) being key predictors (Table5; Figure 5). ENFA results (Tables 6 and 7, ENFA map) reported Marginality=0.72, Specialization=1.90, and Boyce index=0.74, highlighting NDVI and village distance as critical factors. Table 8 shows strong agreement between MaxEnt and ENFA in identifying high-suitability areas in Gousalekah and Kordmir and overlapping medium and low zones.
Table 5) Relative Importance of Environmental Parameters in the MaxEnt Model for Caspian Red Deer
Table 6) Ecological indices derived from the ENFA model for Caspian red deer
Table 7) Relative contribution of parameters to marginality and specialization in the ENFA Model
Table 8) Spatial classification of habitats based on MaxEnt and ENFA outputs
Main Comparisons to Similar Studies
Compared to similar studies, the findings of this research emphasize that Chamois habitat suitability is not determined solely by environmental parameters but is primarily shaped by the complex interaction between three-dimensional vegetation structure and human pressures [Bobrowski et al., 2020; Stritih et al., 2024; Schwegmann et al., 2023]. Consistent with other research, human pressures such as livestock density, forest exploitation, and proximity to settlements cumulatively reduce the species’ habitat capacity [Araújo et al., 2019; Brooks et al., 2019; Nogueira et al., 2021]. Multi-model analyses (MaxEnt and ENFA) have demonstrated that Chamois are sensitive to optimal habitat conditions, and the presence of food resources and shelter maintains its habitat value only under reduced human disturbance [Pourmosa et al., 2024; Champagne et al., 2021]. Structural parameters, particularly canopy and understory cover, had the greatest influence on HSI, aligning with previous studies on managing specialized habitats and structural restoration [Mahmoodi et al., 2020; Evcin et al., 2019; Valavi et al., 2022]. This research, particularly through integrating multi-modeling approaches and human pressure analyses, provides a more comprehensive framework for managing sensitive habitats and is consistent with prior studies on the sensitivity of specialist species and the importance of synergy between habitat structure and human pressures [Iverson et al., 2023; Kass et al., 2021; Margules & Pressey, 2000].
Suggestions
In future studies, integrating remote-sensing data, genetic sampling, and population monitoring could enhance the explanatory power of models and enable the assessment of both seasonal and interannual heterogeneity. The success of Chamois conservation depends on the synergy between structural restoration measures and the reduction of human pressures. This synergy should be implemented through a regional program that prioritizes actions based on habitat value and restoration potential, and allocates conservation resources strategically. Accordingly, a combination of interventions at local levels (livestock grazing control, protection of seedling areas), regional levels (designing conservation networks and ecological corridors), and policy levels (regulating resource use and engaging local communities) can increase the likelihood of successful conservation outcomes.
Conclusion
The Chamois selects its habitat not based on simple habitat criteria, but according to the "three-dimensional structural complexity of the forest."
Acknowledgments: None reported by the authors.
Ethical Approval: This study is an analytical investigation and did not require ethical approval from relevant authorities.
Conflict of Interest: The authors declare that there are no financial or personal conflicts of interest related to the content of this article.
Authors’ Contributions: Gravand F (first author), Introduction Writer/Methodology/Statistical Analyst/Discussion Writer (38%); Hasani Shah Shahidani E (second author), Introduction Writer/Discussion Writer (15%); Fallah Majavor M (third author), Introduction Writer/Discussion Writer (15%); Hejazi SA (fourth author), Introduction Writer/Statistical Analyst/Discussion Writer(10%); Kafaei S (fifth author), Introduction Writer/Statistical Analyst/Discussion Writer (22%)
Funding: This research did not receive any specific financial support, and all costs were covered by the authors.
Habitat degradation and fragmentation in the Hyrcanian forests, especially under human and climatic pressures, have led to a severe decline in the Caspian red deer population. Although species distribution models such as MaxEnt and ENFA are applied, these methods alone are insufficient for a comprehensive analysis of habitat quality, highlighting the need for an integrated approach for more accurate assessment.
Previous Studies
Previous studies have extensively reported the consequences of habitat degradation and fragmentation on biodiversity at structural, functional, and genetic levels. Newbold et al. (2015) and Di Marco et al. (2019) have demonstrated that human activities such as agricultural expansion, logging, and road construction reduce vegetation integrity and lower habitat quality for sensitive forest species. Global studies have also confirmed a significant decline in forest mammal populations due to human pressures; in particular, Dirzo et al. (2014) have estimated that the Caspian red deer population declined by over 80% over a 40-year period.
In the field of ecological niche modeling, research has shown the high accuracy of the MaxEnt model in predicting species distributions and analyzing influential environmental factors (Elith et al., 2011; Phillips et al., 2017). Additionally, Hirzel et al. (2002) have introduced the ENFA model, which allows the analysis of species marginality and specialization without absence data. However, a review of previous studies indicates that most relied on a single model and have paid limited attention to the multidimensional relationships between habitat structure and human pressures (Elith & Leathwick, 2009).
Aim(s)
The present study aimed to provide a comprehensive analytical framework for assessing the habitat suitability of Caspian red deer in the Hyrcanian forests of northern Iran.
Research Type
The present study was descriptive in nature.
Research Society, Place and Time
This study was descriptive and conducted in 2024. The study population comprised three main habitats of the Caspian red deer including Kordmir, Rokouh-Sara, and Gousalekah located in the Fararud area of Rudbar County, Gilan Province. These sites lie on the slopes of the Hyrcanian forests within the Deylaman–Dorfak protected area, recognized as one of the key biodiversity hotspots in northern Iran.
Sampling Method and Number
In this study, data were collected from three main sources. First, a set of specialized questionnaires was distributed among environmental experts and local residents to identify the habitat requirements of the Caspian red deer and the stressors affecting its habitats. Next, field surveys were conducted to measure habitat parameters, including canopy cover density, understory vegetation, food resources, and evidence of species presence. Subsequently, remote sensing data, including Sentinel-2 satellite imagery and topographic parameters, were extracted to provide the environmental layers required for modeling. In total, 43 presence points of the Caspian red deer were processed, with duplicates removed, and used as input for ecological models.
Used Devices & Materials
In this study, a combination of tools and environmental data was used to assess habitat suitability. Sentinel-2 satellite imagery was employed to extract vegetation indices such as NDVI, and topographic data, including elevation, slope, and aspect, were obtained from the USGS Earth Explorer and ESA Copernicus databases. Field measurements were conducted using vegetation assessment tools to record canopy cover density and observe evidence of species presence. Additionally, ArcGIS 10.8 and QGIS 3.26 were used for spatial processing, Biomapper 4.0 for running the ENFA model, MaxEnt 3.4.4 for predicting species distribution, and SPSS 26 for statistical analyses. Furthermore, data obtained from specialized questionnaires were incorporated as key inputs in the analyses.
Findings
In this study, the evaluation of six habitat parameters and six stress factors across the three habitats including Gousalekah , Kordmir, and Rokouh-Sara revealed significant differences in habitat quality and human pressure. Gousalekah performed best in most vegetation indices, food resources, and forest structure, Kordmir was intermediate, and Rokouh-Sara had the lowest quality (Tables 1 and 2). Analysis of human factors showed that Gousalekah experienced minimal exploitation, livestock density, and waste, while being farthest from human settlements; in contrast, Kordmir and Rokouh-Sara were under higher human pressure (Table 1). Structural vegetation features indicated that Gousalekah had dense canopy and understory, a four-layered structure, and high diversity of edible species, making it the most suitable habitat (Table 2).
Table 1) Ranking of stressor factors
The Habitat Evaluation Procedure (HEP) matrices showed Gousalekah with the highest habitat suitability score (26/30) and lowest human stress (28), followed by Kordmir and Rokouh-Sara (Tables 3 and 4). Combining these matrices in HEP ranked Gousalekah as high suitability (54), Kordmir as medium (43), and Rokouh-Sara as low (34; Figure 1). The Habitat Suitability Index (HSI) values confirmed this pattern: 0.86 for Gusaleh-Gah, 0.73 for Kordmir, and 0.36 for Rokuh-Sara (Figure 2). Spatial HSI mapping indicated that 25% of the area was high suitability, 55% medium, and 20% low, consistent with the three habitat conditions (Figure 3). Sensitivity analysis identified canopy cover (SIV5) and understory (SIV2) as the most influential parameters, contributing 40–42% and 33–36% to HSI variance (Figure 4).
Table 3) Habitat requirements matrix
Table 4) Stressor factors matrix
Figure 1) Total Scores of Habitat Requirements and Stressor Factors
Figure 2) Habitat Suitability Index (HSI) profiles in three habitats
Figure 3) Habitat suitability zoning map
Figure 4) Sensitivity analysis of parameters
Figure 5) MaxEnt Map, evaluation of Caspian Red Deer habitat suitability
Modeling results from MaxEnt demonstrated high accuracy (AUC = 0.91), with NDVI (34%), canopy cover (25%), and distance from villages (18%) being key predictors (Table5; Figure 5). ENFA results (Tables 6 and 7, ENFA map) reported Marginality=0.72, Specialization=1.90, and Boyce index=0.74, highlighting NDVI and village distance as critical factors. Table 8 shows strong agreement between MaxEnt and ENFA in identifying high-suitability areas in Gousalekah and Kordmir and overlapping medium and low zones.
Table 5) Relative Importance of Environmental Parameters in the MaxEnt Model for Caspian Red Deer
Table 6) Ecological indices derived from the ENFA model for Caspian red deer
Table 7) Relative contribution of parameters to marginality and specialization in the ENFA Model
Table 8) Spatial classification of habitats based on MaxEnt and ENFA outputs
Main Comparisons to Similar Studies
Compared to similar studies, the findings of this research emphasize that Chamois habitat suitability is not determined solely by environmental parameters but is primarily shaped by the complex interaction between three-dimensional vegetation structure and human pressures [Bobrowski et al., 2020; Stritih et al., 2024; Schwegmann et al., 2023]. Consistent with other research, human pressures such as livestock density, forest exploitation, and proximity to settlements cumulatively reduce the species’ habitat capacity [Araújo et al., 2019; Brooks et al., 2019; Nogueira et al., 2021]. Multi-model analyses (MaxEnt and ENFA) have demonstrated that Chamois are sensitive to optimal habitat conditions, and the presence of food resources and shelter maintains its habitat value only under reduced human disturbance [Pourmosa et al., 2024; Champagne et al., 2021]. Structural parameters, particularly canopy and understory cover, had the greatest influence on HSI, aligning with previous studies on managing specialized habitats and structural restoration [Mahmoodi et al., 2020; Evcin et al., 2019; Valavi et al., 2022]. This research, particularly through integrating multi-modeling approaches and human pressure analyses, provides a more comprehensive framework for managing sensitive habitats and is consistent with prior studies on the sensitivity of specialist species and the importance of synergy between habitat structure and human pressures [Iverson et al., 2023; Kass et al., 2021; Margules & Pressey, 2000].
Suggestions
In future studies, integrating remote-sensing data, genetic sampling, and population monitoring could enhance the explanatory power of models and enable the assessment of both seasonal and interannual heterogeneity. The success of Chamois conservation depends on the synergy between structural restoration measures and the reduction of human pressures. This synergy should be implemented through a regional program that prioritizes actions based on habitat value and restoration potential, and allocates conservation resources strategically. Accordingly, a combination of interventions at local levels (livestock grazing control, protection of seedling areas), regional levels (designing conservation networks and ecological corridors), and policy levels (regulating resource use and engaging local communities) can increase the likelihood of successful conservation outcomes.
Conclusion
The Chamois selects its habitat not based on simple habitat criteria, but according to the "three-dimensional structural complexity of the forest."
Acknowledgments: None reported by the authors.
Ethical Approval: This study is an analytical investigation and did not require ethical approval from relevant authorities.
Conflict of Interest: The authors declare that there are no financial or personal conflicts of interest related to the content of this article.
Authors’ Contributions: Gravand F (first author), Introduction Writer/Methodology/Statistical Analyst/Discussion Writer (38%); Hasani Shah Shahidani E (second author), Introduction Writer/Discussion Writer (15%); Fallah Majavor M (third author), Introduction Writer/Discussion Writer (15%); Hejazi SA (fourth author), Introduction Writer/Statistical Analyst/Discussion Writer(10%); Kafaei S (fifth author), Introduction Writer/Statistical Analyst/Discussion Writer (22%)
Funding: This research did not receive any specific financial support, and all costs were covered by the authors.
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