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Article

Spatial Conservation Prioritization of Persian Squirrel Based on Habitat Suitability and Climate-Induced Forest Mortality Risk

by
Omid Ghadirian Baharanchi
1,
Mahmoud-Reza Hemami
2 and
Rasoul Yousefpour
1,*
1
Institute of Forestry and Conservation, Daniels Faculty of Architecture, Landscape, and Design, University of Toronto, Toronto, ON M5S 1A1, Canada
2
Department of Natural Resources, Isfahan University of Technology, Isfahan 84156-83111, Iran
*
Author to whom correspondence should be addressed.
Forests 2024, 15(2), 290; https://doi.org/10.3390/f15020290
Submission received: 6 January 2024 / Revised: 29 January 2024 / Accepted: 30 January 2024 / Published: 3 February 2024
(This article belongs to the Special Issue Conservation and Management of Forest Wildlife)
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Abstract

:
The Zagros forests in Iran are currently experiencing an exacerbation of climate-induced mortality, placing the Persian squirrel, a keystone species reliant on these ecosystems, in jeopardy. Addressing this imminent threat, our research employed a spatial prioritization methodology, integrating assessments of habitat suitability and mortality risk. Utilizing a weighted ensemble approach, incorporating the strengths of diverse models and expert rules, we discerned that approximately 62% of surveyed forests are at risk, with 7% classified as high risk and 17% as very high risk. Notably, 83% of the forests exhibited varying degrees of habitat suitability, with 11% and 12% demonstrating high and very high suitability, respectively. Employing a conservation prioritization framework, we systematically categorized habitats into priority classes, with 8%, 17%, 29%, and 46% assigned to very high, high, moderate, and low conservation priority classes, respectively. Significantly, areas classified as very high priority demand immediate restoration efforts due to ongoing mortality, while other priority classes underscore the importance of protection and prevention in unaffected habitats. Acknowledging the irreversible nature of current climatic conditions in the Zagros forests, our strategic emphasis aligns with conservation triage principles, prioritizing the preservation of intact habitats yet to succumb to irreversible mortality.

1. Introduction

Continued habitat degradation attributable to climate change, human population expansion, and unregulated development represent the pre-eminent threats to biodiversity [1,2]. Consequently, effective habitat management and conservation stand as pivotal considerations in species preservation [3]. Forest ecosystems, acknowledged as critical habitats for a myriad of species, encompass over 80% of terrestrial biodiversity and span approximately one third of the Earth’s land area [4,5]. However, both the quantity and quality of forest habitats are undergoing persistent diminishment in numerous regions [4]. The accelerating transformation and exploitation of these ecosystems on a global scale have outpaced their capacity for sustainable regeneration, as indicated by the 3% reduction in global forest coverage between 1990 and 2015, reported in a comprehensive study conducted by the Food and Agriculture Organization [6].
Concurrently, a discernible escalation in climate-induced forest mortality events has been extensively documented in diverse regions worldwide, including Africa [7], Europe [8,9,10,11,12], America [13,14,15,16,17,18,19], and Asia [20,21,22,23,24,25]. Given the noticeable response of forests to contemporary climatic shifts, climate-induced forest mortality is poised to emerge as a significant global phenomenon in the foreseeable future [26,27,28,29]. Consequently, species reliant on forest ecosystems, particularly those exhibiting a pronounced dependency on these habitats, confront an array of threats arising from habitat loss. This is especially important for rare tree species (squirrels and dormice), which are sensitive to changes in the taxonomic and ecological composition of forest stands [30,31]. This predicament is anticipated to be particularly acute in arid regions, where forest ecosystems are already operating at the threshold of water availability.
The Persian or Caucasian squirrel (Sciurus anomalus) exemplifies a species profoundly reliant on forest habitats [32,33]. Despite being categorized as “Least Concern (LC)” with a decreasing population trend in the IUCN Red List [32,33,34] and being listed under Annex IV of the European Habitats Directive [35], the species confronts formidable challenges. These include illegal hunting, habitat fragmentation, and habitat loss attributed to agricultural expansion, fire, timber harvesting, and drought [33,34,36]. The Persian squirrel’s distribution spans Southeast Europe to Southwest Asia, encompassing three recognized subspecies: Sciurus anomalus anomalus, Sciurus anomalus pallescens, and Sciurus anomalus syriacus [32,33,37]. S. a. pallescens holds special ecological importance as the subspecies exclusive to the Zagros range in Iran and Iraq. It stands as the sole tree squirrel within the Sciuridae family in this region and is recognized as a keystone species [38,39]. This designation is attributed to its substantial influence on ecosystem patterns and processes [32,39]. The Persian squirrel’s pivotal role in the regeneration of the Iranian Zagros forest is particularly evident through its winter activities, including the collection and subterranean storage of oak fruits. This underscores the ecological significance of the species [32].
Iran’s forests are estimated to cover approximately 14 million hectares; a total of 41% of this expanse (approximately 6,000,000 hectares) comprises the Zagros Mountain Chain, spanning 11 provinces from Northwest to Southeast Iran (Figure 1). Dominated by coppiced oak species constituting nearly 70% of the flora, these ecologically and genetically rich Zagros forests provide a habitat for diverse wildlife, including the Persian squirrel. Since the turn of the millennium, a notable incidence of forest mortality has been observed throughout the entire Iranian Zagros mountains. A recent assessment conducted by the Iranian Forests, Range, and Watershed Management Organization (IFRWMO) indicates that approximately 25% of all Zagros plant life-forms, including trees, shrubs, and grasses, have experienced varying degrees of forest mortality.
Given the escalating trend of forest mortality in the Zagros Mountains and the pronounced reliance of the Persian squirrel as a keystone species on these habitats, the imperative of formulating a comprehensive conservation plan is evident. Due to resource constraints, spatial prioritization emerges as the initial step in this endeavor. Thus, the objectives of this study encompass (1) identifying suitable habitats for the Persian squirrel, (2) delineating habitat regions susceptible to forest mortality, and (3) prioritizing the conservation of suitable habitats based on insights gained from the first two objectives. Finally, we define and map the optimal spatial allocation of forest conservation area for the Persian squirrel in the Zagros Mountains.

2. Materials and Methods

2.1. Study Area

This investigation took place in the Zagros forests located in Lorestan Province; a region significantly affected by forest mortality. The province covers an extensive landmass, approximately 75% (21,000 km2) of which is characterized by diverse natural vegetation types. Among these, Zagros forests make up a substantial portion, accounting for 44% of the total area (12,300 km2; see Figure 1). These forests are predominantly composed of coppiced oak species, constituting nearly 70% of the flora. Lorestan Province exhibits a topographical composition predominantly defined by parallel sub-ranges of the Zagros Mountains, covering approximately 85% of its expanse in a northwest-to-southeast orientation. The region experiences distinct climatic variations, with cold highland conditions prevalent in the Zagros Mountains, moderate conditions in the central area, and warm conditions in the southern reaches. The annual mean precipitation is 550 mm, primarily concentrated between December and March. Notably, the Zagros forests in Lorestan, acknowledged as pivotal habitats for the target subspecies under investigation, have been undergoing a pronounced and alarming increase in forest mortality in recent years. A comprehensive assessment conducted by IFRWMO reveals that approximately 20% of the Zagros forests in Lorestan Province have encountered varying degrees of forest mortality. This discernible trend underscores the severity of the ecological challenge facing this particular region, emphasizing the urgent need for scientific inquiry and conservation interventions to mitigate the escalating threat to the biodiversity and ecological integrity of these forests.

2.2. Forest Mortality Data

Forest mortality incidents (Figure 2), delineated as desiccated forest patches in polygonal form, were sourced from IFRWMO. To minimize spatial autocorrelation effects on model fit, we adopted a centroid-based approach, considering the central point of each polygon as a discrete occurrence of forest mortality. This methodology yielded a dataset comprising 1056 occurrences and an equivalent number of absences, each represented by distinct geographical coordinates, which facilitated a robust modeling framework.
The selection of environmental variables for the modeling process involved an exhaustive literature review, expert insights, constraints related to data availability and quality, and the exclusion of factors exhibiting correlations exceeding 80%. Consequently, 13 pivotal environmental factors deemed to exert significant influences on forest mortality were identified, mapped, and incorporated into the modeling framework. It is pertinent to note that the severity of forest mortality is acknowledged to be contingent upon the tree species in question [40,41,42]. However, due to the unavailability of raster or vector data pertaining to forest structure and species composition within the study area, this species-specific factor was regrettably omitted from the modeling process.
To compensate for this limitation and gauge an approximation of tree density, the normalized difference vegetation index (NDVI), derived from Landsat satellite imagery scenes, was integrated into the modeling process. The spatial distribution of environmental factors 1 to 5 (see Table 1) was delineated using inverse distance weighted (IDW) interpolation and data sourced from 21 strategically positioned weather stations across the study area (see Figure 1). This interpolation technique facilitated the creation of spatially continuous maps depicting the distribution patterns of pertinent environmental variables, thereby enhancing the granularity of our modeling efforts (see Figure 1).

2.3. Habitat Suitability Data

A dataset comprising three hundred spatially non-autocorrelated points denoting the occurrences and absences of Sciurus anomalus pallescens, specifically associated with the prelude to forest mortality events (prior to the year 2000), was procured from the National Department of Environment. This dataset served as the foundational information for our modeling endeavors. Concurrently, an integrative approach informed by an extensive literature review, expert consultations, considerations regarding data availability and quality, and the exclusion of factors demonstrating correlations exceeding 80%, facilitated the identification of nine pertinent environmental factors. These factors were mapped to reflect conditions in the year 2000, and subsequently incorporated into the modeling framework (Table 1).

2.4. Modelling Procedure

Species distribution models (SDMs) represent numerical tools designed to simulate species distribution patterns by correlating field observations with environmental variables [45,46]. In the context of simulating forest mortality risk, a parallel framework is employed to establish the connection between forest mortality occurrence locations and the associated environmental drivers, akin to methodologies utilized in species distribution modeling. In addition to modeling the habitat suitability for the Persian squirrel, we harnessed the predictive capabilities inherent in SDMs to assess the forest mortality risk. Among various SDMs, maximum entropy (MaxEnt) stands out as the most widely employed and recognized model due to its flexibility and ease of implementation [47,48,49,50]. Nonetheless, given the diversity in model performance [51], our approach initially involved applying 15 distinct models (Table 2) using the sdm and dismo packages in the R statistical software version 4.3.1 [52,53].
Subsequently, models exhibiting an area under the ROC curve (AUC) surpassing the threshold of 0.8 were selectively retained and integrated within a weighted ensemble forecasting framework. This ensemble approach aimed to generate habitat suitability and forest mortality risk maps, thereby leveraging the strengths of multiple models. To ensure model robustness and accuracy, 75% of occurrence and absence points were employed for model calibration, with the remaining 25% reserved for model evaluation through the implementation of 10,000 replicative runs. This rigorous evaluation protocol facilitated a comprehensive assessment of the models’ performance and their capacity to reliably predict both habitat suitability for the Persian squirrel and the associated risk of forest mortality.

2.5. Spatial Conservation Prioritization

To generate a conservation priority map, a systematic approach was undertaken, encompassing the following steps. Initially, the conclusive ensemble maps depicting forest mortality risk and habitat suitability were discretized into five distinct classes, as delineated in Table 3. Subsequently, guided by expert insights, a set of five rules was formulated, as detailed in Table 4. These rules served as the foundational criteria for the amalgamation of the classified maps, wherein elevated conservation priority was assigned to habitats characterized by both high and very high suitability, coupled with heightened forest mortality risk.

3. Results

3.1. Habitat Suitability and Forest Mortality Risk

With the exception of the Bioclim model, exhibiting area under the receiver operating characteristic curve (AUC) values of 0.74 for forest mortality risk and 0.72 for habitat suitability modeling, all other models demonstrated AUC values exceeding 0.8 (Figure 3). Consequently, these high-performing models were integrated into the weighted ensemble forecasting framework. Notably, mixture discriminant analysis (MDA) emerged as the most accurate model for forest mortality risk, boasting an AUC of 0.93, while boosted regression tree (BRT) achieved a commendable AUC of 0.94, rendering it the most accurate model for habitat suitability modeling.
The culmination of these models is illustrated in the final categorized ensemble maps portraying forest mortality risk and habitat suitability, as presented in Figure 4. Discernible in this representation is an escalating trend of mortality risk emanating from the central regions of the forests towards the southwestern extents. Approximately 62% of Lorestanian forests are identified as being at risk of forest mortality, with 23% categorized as having low risk, 15% as moderate risk, 7% as high risk, and 17% as very high risk. The distribution of habitat suitability for the Persian squirrel is spatially diverse, with the central and southern portions, along with select northwestern areas, exhibiting very high and high suitability. In terms of habitat quality, about 83% of the forests fall within varying levels of suitability for the species. This breakdown reveals that 35% have low habitat suitability, 25% have moderate habitat suitability, 11% have high habitat suitability, and 12% have very high habitat suitability. These findings offer a nuanced understanding of the intricate interplay between forest mortality risk and habitat suitability, which is crucial for informed conservation and management strategies.

3.2. Spatial Conservation Prioritization

Roughly 57% of the habitat deemed suitable for the Persian squirrel is susceptible to forest mortality risk, with a nuanced breakdown revealing that 22% faces low risk, 14% experiences moderate risk, 6% contends with high risk, and 15% confronts a very high risk scenario (Figure 5). The subsequent allocation of these habitats to conservation priority classes, as depicted in Figure 6, underscores the imperative for strategic conservation measures. Specifically, 8%, 17%, 29%, and 46% of habitats categorized as high and very high suitability for the species are apportioned to very high, high, moderate, and low conservation priority classes, respectively. This hierarchical distribution aligns with a judicious conservation strategy, prioritizing interventions based on the varying degrees of habitat suitability and the concomitant risk of forest mortality.

4. Discussion

We employed 15 distinct species distribution models (SDMs) to forecast both habitat suitability and forest mortality risk, ensuring a comprehensive analysis of predictive accuracy. All models exhibited an AUC exceeding 0.5, indicative of predictive performance surpassing random chance. Notably, 14 of the models demonstrated either an excellent or very excellent prediction, with AUC values falling within the ranges of 0.8 to 0.9 and 0.9 to 1. However, the Bioclim model, while exhibiting AUC values exceeding 0.5, did not reach the benchmark of excellence. Given the nuanced variations in model accuracies and the absence of identical behavior among them, a weighted ensemble approach was judiciously employed to amalgamate the diverse predictions of individual models [67]. The robust accuracy observed across the models not only underscores their reliability but also affirms the trustworthiness of SDMs in predicting forest mortality risk, thereby validating their utility as a predictive tool. This corroborates previous recognitions of SDMs’ efficacy in risk prediction [68,69].
Within the context of this study, the Persian squirrel is posited as a surrogate for the broader Zagros forest biodiversity, emphasizing its status as a keystone species in the Iranian Zagros forest with significant impacts on ecosystem patterns and processes [32,39,70]. The pivotal role of the Persian squirrel in the regeneration of Iranian Zagros forest, particularly through the collection and subterranean storage of oak fruits during winter, further underscores its ecological significance [32,70]. The potential diminution in habitat suitability and population of this keystone species could reverberate negatively, impacting other species and fundamental ecosystem processes [70]. Consequently, the conservation of Persian squirrel habitats and populations assumes a crucial role in fostering ecosystem health and biodiversity within the study forests. Monitoring fluctuations in Persian squirrel populations could serve as a valuable indicator of ecosystem dynamics in the ensuing years.
Moreover, a feedback loop linking climate change and forest mortality exists, wherein climate-induced forest mortality may accelerate climate change and global warming. Given that 55% of terrestrial carbon is stored in forests, climate-induced forest mortality could influence wildfire frequency, duration, extent, and intensity, further contributing to fire-induced tree mortality [27,71,72,73,74,75]. Without effective conservation measures, climate-induced forest mortality poses a formidable threat to future forest habitat integrity [26,27,28,29].
In response to these challenges, conservation endeavors should adopt a dual focus, addressing the protection of intact forest habitats and the restoration of degraded ones [76,77]. Our findings reveal that a substantial proportion of habitats classified under the very high conservation priority class (approximately 27%) has already been impacted by forest mortality, necessitating restoration interventions. Conversely, other conservation priority classes remain unaffected by forest mortality and therefore require proactive protection and preventative measures rather than restoration initiatives. This nuanced conservation approach is essential for mitigating the impacts of climate-induced forest mortality and fostering the long-term sustainability of the ecosystem.
Ecological restoration constitutes a multifaceted process aimed at facilitating the recovery of ecosystems that have undergone degradation, damage, or destruction [78]. Globally, diverse restoration initiatives have been increasingly implemented, targeting the restoration of both ecosystem services and biodiversity [4,77,78]. These initiatives span a spectrum of restoration actions, from passive measures that involve the removal and prevention of disturbances to allow for natural recovery—termed “passive restoration”—to more interventionist approaches that actively accelerate and manage the recovery process, referred to as “active restoration” [76,77,78].
Given the apparent irreversibility of forest mortality in the Zagros forests under prevailing climatic conditions and considering the triage concept for judicious resource allocation in conservation and management, the primary focus should be on preserving and safeguarding intact habitats. Acknowledging that Zagros forest mortality, similar to phenomena observed globally [26,27], is predominantly climate-induced, implementing measures to enhance adaptation to climate change [79] emerges as a viable consideration. Climate change adaptation involves making adjustments in ecological, social, and economic systems in response to the impacts of climate change. Strategies for climate change adaptation can be integral components of comprehensive sustainable forest management plans, which serve as risk management mechanisms.
In tandem with climate change adaptation efforts, preventing deforestation, curbing the expansion of cultivated lands, and regulating the harvest of oak fruits by local communities within conservation priority classes are essential measures to protect both the Persian squirrel and the integrity of the forests. The approach employed for spatial conservation prioritization in this study is deemed transferable and applicable to other forested regions grappling with forest mortality, thereby offering a systematic framework for effective conservation strategies in the face of ecological challenges.
The comprehensive analysis presented in this study highlights the critical interplay between climate-induced forest mortality, habitat suitability for the Persian squirrel, and the associated conservation priorities within the Zagros forests of Iran. Our spatial prioritization approach, integrating habitat suitability and mortality risk assessments, provides a nuanced perspective essential for informed conservation and management strategies.

5. Conclusions

In conclusion, our study sheds light on the alarming climate-induced mortality trends within the Zagros forests of Iran and their profound implications for the Persian squirrel, a species intricately tied to these ecosystems. The urgency of our findings cannot be overstated, as approximately 62% of surveyed forests face mortality risks, with a significant portion categorized as high and very high risk. By allocating conservation priority classes to habitats based on their suitability and risk levels, we offer a strategic framework for directing limited resources towards the most critical areas. The allocation of priority classes underscores the need for a nuanced approach, where restoration actions are targeted where feasible, and protective measures are employed to safeguard habitats not yet subjected to irreversible decline.
In line with the principles of conservation triage, our approach acknowledges the practical constraints and directs attention to areas where intervention can yield the most significant benefits. As we navigate the complexities of climate-induced threats to biodiversity, our study underscores the importance of adaptive conservation strategies that evolve with the dynamic nature of ecosystems. By focusing on the preservation of intact habitats, we contribute to the resilience of the Persian squirrel and the broader ecological balance of the Zagros forests. It is our hope that these findings will inform and guide conservation practitioners, policymakers, and stakeholders in developing effective strategies to mitigate the impact of climate-induced mortality and secure a sustainable future for these vital ecosystems and their inhabitants.

Author Contributions

Conceptualization, O.G.B. and M.-R.H.; methodology, O.G.B.; software, O.G.B.; validation, O.G.B., M.-R.H. and R.Y.; formal analysis, O.G.B.; investigation, O.G.B.; resources, M.-R.H.; data curation, O.G.B.; writing—original draft preparation, O.G.B.; writing—review and editing, R.Y.; visualization, O.G.B.; supervision, M.-R.H. and R.Y.; project administration, O.G.B.; funding acquisition, M.-R.H. and R.Y. All authors have read and agreed to the published version of the manuscript.

Funding

We acknowledge receiving funding from NSERC Discovery Grant (Canada) and supports provided by EU RISE project “DecisionES” (Grant agreement No: 101007950).

Data Availability Statement

The data presented in this study are available on request from the corresponding author.

Acknowledgments

We are grateful to the Iranian Forest, Range and Watershed Management Organization and Department of Environment for providing data and their valuable cooperation in this study.

Conflicts of Interest

The authors declare no conflicts of interest. The funders had no role in the design of the study; in the collection, analyses, or interpretation of data; in the writing of the manuscript; or in the decision to publish the results.

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Forests 15 00290 g001
Figure 1. The geographical location of Iranian Zagros forests, study area, and the synoptic weather stations used in this study.
Figure 1. The geographical location of Iranian Zagros forests, study area, and the synoptic weather stations used in this study.
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Figure 2. Forest mortality in Zagros forests.
Figure 2. Forest mortality in Zagros forests.
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Figure 3. The area under the curve (AUC) index of the 15 models used in this study (for model numbers, see Table 2).
Figure 3. The area under the curve (AUC) index of the 15 models used in this study (for model numbers, see Table 2).
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Figure 4. Final categorized ensemble forest mortality risk (above) and habitat suitability (below) maps.
Figure 4. Final categorized ensemble forest mortality risk (above) and habitat suitability (below) maps.
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Figure 5. Ratio (%) of effect of forest mortality risk classes on different habitat suitability classes.
Figure 5. Ratio (%) of effect of forest mortality risk classes on different habitat suitability classes.
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Figure 6. Conservation priority map.
Figure 6. Conservation priority map.
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Table 1. The environmental variables used in this study.
Table 1. The environmental variables used in this study.
NumberForest MortalityHabitat Suitability
1Mean Annual TemperatureMean Annual Temperature
2Mean Annual PrecipitationMean Annual Precipitation
3Reference Evapotranspiration [43]Distance to residential areas
4Standardized Precipitation Index (SPI)Distance to Surface Water
5Dust Storm Index (DSI) [44]Distance to Roads
6Geographic AspectGeographic Aspect
7Percentage of SlopePercentage of Slope
8NDVINDVI
9Distance to Agricultural LandsDistance to Agricultural Lands
10Distance to Surface Water
11Soil Moisture
12Soil PH
13Soil Organic Matter
Table 2. The species distribution models used in this study.
Table 2. The species distribution models used in this study.
Model NumberModel NameReference
1Mahalanobis Distance[54]
2Artificial Neural Network (ANN)[55]
3Random Forest (RF)[56]
4Support Vector Machine (SVM)[57]
5Generalized Additive Model (GAM)[58]
6Generalized Linear Model (GLM)[59]
7Boosted Regression Tree (BRT)[60]
8Maximum Entropy (MaxEnt)[49]
9Flexible Discriminant Analysis (FDA)[61]
10Mixture Discriminant Analysis (MDA)[61]
11Bioclim[62]
12Domain[63]
13Multivariate Adaptive Regression Spline (MARS)[64]
14Environmental Niche Factor Analysis (ENFA)[65]
15Classification And Regression Tree (CART)[66]
Table 3. Forest mortality risk and habitat suitability classes.
Table 3. Forest mortality risk and habitat suitability classes.
Class NumberForest Mortality RiskHabitat SuitabilityRange of Values
1No RiskNo Suitability0.1 > Values
2Low RiskLow Suitability0.1 ≤ Values ≤ 0.25
3Moderate RiskModerate Suitability0.25 < Values ≤ 0.5
4High RiskHigh Suitability0.5 < Values ≤ 0.75
5Very High RiskVery High Suitability0.75 < Values ≤ 1
Table 4. Conservation priority classes and rules.
Table 4. Conservation priority classes and rules.
Priority Class Rules
Very HighF-M-R 1 Class Number5or4
AndAnd
H-S 1 Class Number5 or 45
HighF-M-R Class Number3 or 2or4 or 3
AndAnd
H-S Class Number54
ModerateF-M-R Class Number2
And
H-S Class Number4
LowF-M-R Class Number1
And
H-S Class Number4 or 5
No priorityF-M-R Class Number5 or 4 or 3 or 2 or 1
And
H-S Class Number1 or 2 or 3
1 F-M-R = Forest Mortality Risk; H-S = Habitat Suitability.
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Ghadirian Baharanchi, O.; Hemami, M.-R.; Yousefpour, R. Spatial Conservation Prioritization of Persian Squirrel Based on Habitat Suitability and Climate-Induced Forest Mortality Risk. Forests 2024, 15, 290. https://doi.org/10.3390/f15020290

AMA Style

Ghadirian Baharanchi O, Hemami M-R, Yousefpour R. Spatial Conservation Prioritization of Persian Squirrel Based on Habitat Suitability and Climate-Induced Forest Mortality Risk. Forests. 2024; 15(2):290. https://doi.org/10.3390/f15020290

Chicago/Turabian Style

Ghadirian Baharanchi, Omid, Mahmoud-Reza Hemami, and Rasoul Yousefpour. 2024. "Spatial Conservation Prioritization of Persian Squirrel Based on Habitat Suitability and Climate-Induced Forest Mortality Risk" Forests 15, no. 2: 290. https://doi.org/10.3390/f15020290

APA Style

Ghadirian Baharanchi, O., Hemami, M. -R., & Yousefpour, R. (2024). Spatial Conservation Prioritization of Persian Squirrel Based on Habitat Suitability and Climate-Induced Forest Mortality Risk. Forests, 15(2), 290. https://doi.org/10.3390/f15020290

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