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BakhshiGanje M, Mahmoodi S, Ahmadi K, Mirabolfathy M. Potential distribution of Biscogniauxia mediterranea and Obolarina persica causal agents of oak charcoal disease in Iran's Zagros forests. Sci Rep 2024; 14:7784. [PMID: 38565553 PMCID: PMC10987582 DOI: 10.1038/s41598-024-57298-2] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/17/2024] [Accepted: 03/16/2024] [Indexed: 04/04/2024] Open
Abstract
In Iran, native oak species are under threat from episodes of Charcoal Disease, a decline syndrome driven by abiotic stressors (e.g. drought, elevated temperature) and biotic components, Biscogniauxia mediterranea (De Not.) Kuntze and Obolarina persica (M. Mirabolfathy). The outbreak is still ongoing and the country's largest ever recorded. Still, the factors driving its' epidemiology in time and space are poorly known and such knowledge is urgently needed to develop strategies to counteract the adverse effects. In this study, we developed a generic framework based on experimental, machine-learning algorithms and spatial analyses for landscape-level prediction of oak charcoal disease outbreaks. Extensive field surveys were conducted during 2013-2015 in eight provinces (more than 50 unique counties) in the Zagros ecoregion. Pathogenic fungi were isolated and characterized through morphological and molecular approaches, and their pathogenicity was assessed under controlled water stress regimes in the greenhouse. Further, we evaluated a set of 29 bioclimatic, environmental, and host layers in modeling for disease incidence data using four well-known machine learning algorithms including the Generalized Linear Model, Gradient Boosting Model, Random Forest model (RF), and Multivariate Adaptive Regression Splines implemented in MaxEnt software. Model validation statistics [Area Under the Curve (AUC), True Skill Statistics (TSS)], and Kappa index were used to evaluate the accuracy of each model. Models with a TSS above 0.65 were used to prepare an ensemble model. The results showed that among the different climate variables, precipitation and temperature (Bio18, Bio7, Bio8, and bio9) in the case of O. persica and similarly, gsl (growing season length TREELIM, highlighting the warming climate and the endophytic/pathogenic nature of the fungus) and precipitation in case of B. mediterranea are the most important influencing variables in disease modeling, while near-surface wind speed (sfcwind) is the least important variant. The RF algorithm generates the most robust predictions (ROC of 0.95; TSS of 0.77 and 0.79 for MP and OP, respectively). Theoretical analysis shows that the ensemble model (ROC of 0.95 and 0.96; TSS = 0.79 and 0.81 for MP and OP, respectively), can efficiently be used in the prediction of the charcoal disease spatiotemporal distribution. The oak mortality varied ranging from 2 to 14%. Wood-boring beetles association with diseased trees was determined at 20%. Results showed that water deficiency is a crucial component of the oak decline phenomenon in Iran. The Northern Zagros forests (Ilam, Lorestan, and Kermanshah provinces) along with the southern Zagros forests (Fars and Kohgilouyeh va-Boyer Ahmad provinces) among others are the most endangered areas of potential future pandemics of charcoal disease. Our findings will significantly improve our understanding of the current situation of the disease to pave the way against pathogenic agents in Iran.
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Affiliation(s)
- Meysam BakhshiGanje
- Kohgiluyeh va Boyer-Ahmad Agricultural and Natural Resources Research and Education Center, Yasuj, Iran.
| | - Shirin Mahmoodi
- National center of genetic resources, Agricultural Research Education and Extention Organization, Tehran, Iran
| | - Kourosh Ahmadi
- Department of Forestry, Faculty of Natural Resources and Marine Sciences, Tarbiat Modares University, Tehran, Iran.
- Fars Agricultural and Natural Resources Research and Education Center (AREEO), Tehran, Iran.
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Machado IC, Nunes T, Maximino M, Malato J, Tavares L, Almeida V, Sepúlveda N, Gil S. Epidemiologic Factors Supporting Triage of Infected Dog Patients Admitted to a Veterinary Hospital Biological Isolation and Containment Unit. Vet Sci 2023; 10:vetsci10030186. [PMID: 36977225 PMCID: PMC10057909 DOI: 10.3390/vetsci10030186] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/22/2022] [Revised: 02/18/2023] [Accepted: 02/23/2023] [Indexed: 03/06/2023] Open
Abstract
The teaching hospital of the Faculty of Veterinary Medicine at the University of Lisbon hosts a Biological Isolation and Containment Unit (BICU) for the hospitalization of both confirmed and suspected animals of an infectious disease. This study targets the BICU dog population to identify and characterize the most frequent infectious diseases recorded in a 7-year period. Several epidemiologic factors were analyzed for their significance to triage infected cases. During the study period, 534 dogs were admitted, of which 263 (49.3%) had a confirmed infectious disease diagnosis: parvovirosis (49.4%; n = 130); leptospirosis (21.7%; n = 57); multidrug-resistant (MDR) bacterial infection; (10.6%; n = 28), and canine distemper (9.9%; n = 26). Several potential risk factors for these diseases were identified: age under 2 years old (p < 0.001), incomplete vaccination for parvovirosis (p < 0.001), age ≥ 10 years old (p < 0.001), and the presence of concomitant disorders for MDR-infected cases (p = 0.03). Logistic regression models were constructed to classify cases and controls. The sensitivity and specificity estimates were very high (>0.83) for parvovirosis, MDR, and distemper infections. A lower sensitivity (0.77) was obtained for identifying cases with leptospirosis. In conclusion, infectious diseases are frequent, hence, it is essential to decrease their occurrence through effective preventive measures such as vaccination. The constructed logistic models can also help in triaging admitted dogs with a potential infectious disease.
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Affiliation(s)
- Inês Cunha Machado
- Teaching Hospital, Faculty of Veterinary Medicine, University of Lisbon, Av. Universidade Técnica, 1300-477 Lisboa, Portugal
- CIISA—Centre for Interdisciplinary Research in Animal Health, Faculty of Veterinary Medicine, University of Lisbon, Av. Universidade Técnica, 1300-477 Lisboa, Portugal
- Associate Laboratory for Animal and Veterinary Sciences (AL4AnimalS), Av. Universidade Técnica, 1300-477 Lisboa, Portugal
- Faculty of Veterinary Medicine, University of Lisbon, Av. Universidade Técnica, 1300-477 Lisbon, Portugal
| | - Telmo Nunes
- CIISA—Centre for Interdisciplinary Research in Animal Health, Faculty of Veterinary Medicine, University of Lisbon, Av. Universidade Técnica, 1300-477 Lisboa, Portugal
- Associate Laboratory for Animal and Veterinary Sciences (AL4AnimalS), Av. Universidade Técnica, 1300-477 Lisboa, Portugal
- Faculty of Veterinary Medicine, University of Lisbon, Av. Universidade Técnica, 1300-477 Lisbon, Portugal
| | - Miguel Maximino
- Teaching Hospital, Faculty of Veterinary Medicine, University of Lisbon, Av. Universidade Técnica, 1300-477 Lisboa, Portugal
| | - João Malato
- Instituto de Medicina Molecular (IMM), Faculdade de Medicina, Universidade de Lisboa, Av. Prof. Egas Moniz, 1649-028 Lisboa, Portugal
- Centro de Estatística e Aplicações da Universidade de Lisboa, Campo Grande, 1749-016 Lisboa, Portugal
| | - Luís Tavares
- CIISA—Centre for Interdisciplinary Research in Animal Health, Faculty of Veterinary Medicine, University of Lisbon, Av. Universidade Técnica, 1300-477 Lisboa, Portugal
- Associate Laboratory for Animal and Veterinary Sciences (AL4AnimalS), Av. Universidade Técnica, 1300-477 Lisboa, Portugal
- Faculty of Veterinary Medicine, University of Lisbon, Av. Universidade Técnica, 1300-477 Lisbon, Portugal
| | - Virgilio Almeida
- CIISA—Centre for Interdisciplinary Research in Animal Health, Faculty of Veterinary Medicine, University of Lisbon, Av. Universidade Técnica, 1300-477 Lisboa, Portugal
- Associate Laboratory for Animal and Veterinary Sciences (AL4AnimalS), Av. Universidade Técnica, 1300-477 Lisboa, Portugal
- Faculty of Veterinary Medicine, University of Lisbon, Av. Universidade Técnica, 1300-477 Lisbon, Portugal
| | - Nuno Sepúlveda
- Centro de Estatística e Aplicações da Universidade de Lisboa, Campo Grande, 1749-016 Lisboa, Portugal
- Faculty of Mathematics and Information Science, Warsaw University of Technology, Koszykowa 75, 00-662 Warsaw, Poland
| | - Solange Gil
- Teaching Hospital, Faculty of Veterinary Medicine, University of Lisbon, Av. Universidade Técnica, 1300-477 Lisboa, Portugal
- CIISA—Centre for Interdisciplinary Research in Animal Health, Faculty of Veterinary Medicine, University of Lisbon, Av. Universidade Técnica, 1300-477 Lisboa, Portugal
- Associate Laboratory for Animal and Veterinary Sciences (AL4AnimalS), Av. Universidade Técnica, 1300-477 Lisboa, Portugal
- Faculty of Veterinary Medicine, University of Lisbon, Av. Universidade Técnica, 1300-477 Lisbon, Portugal
- Correspondence: ; Tel.: +48-351213652800
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Jiang F, Zhang J, Song P, Qin W, Wang H, Cai Z, Gao H, Liu D, Li B, Zhang T. Identifying priority reserves favors the sustainable development of wild ungulates and the construction of Sanjiangyuan National Park. Ecol Evol 2022; 12:e9464. [PMID: 36349253 PMCID: PMC9631328 DOI: 10.1002/ece3.9464] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/22/2022] [Revised: 10/03/2022] [Accepted: 10/10/2022] [Indexed: 11/06/2022] Open
Abstract
Sanjiangyuan National Park (SNP), the first national park in China, is one of the most important biodiversity conservation areas in the Sanjiangyuan National Nature Reserve (SNNR) and even the world. The threatened ungulates play an irreplaceable role in maintaining the ecosystem diversity and stability in SNNR. Here, based on 1434 occurrence records of six ungulates, the maximum entropy model, with two different strategies, was utilized to determine the priority reserves. The results indicated that the priority reserves in SNNR was mainly located in and around SNP, which were mainly distributed in the middle east, middle west, and southwest of SNNR. Six ungulates shared preference for altitude ranging 4000-5000 m, the average annual temperature below -3.0°C, and average annual precipitation ranging 200-400 mm on meadow, steppe, and unused land. The proportion of high and medium suitable areas for ungulates in SNP was higher than that in SNNR. As the SNP is not contiguously spaced in space, and some core wildlife habitats are not included, it is suggested to optimize the functional areas and adjust the boundary range on the basis of the pilot scope of SNP, so as to enhance the integrity and connectivity of each functional area.
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Affiliation(s)
- Feng Jiang
- Key Laboratory of Adaptation and Evolution of Plateau BiotaNorthwest Institute of Plateau Biology, Chinese Academy of SciencesXiningQinghaiChina
- University of Chinese Academy of SciencesBeijingChina
- Qinghai Provincial Key Laboratory of Animal Ecological GenomicsXiningQinghaiChina
| | - Jingjie Zhang
- Key Laboratory of Adaptation and Evolution of Plateau BiotaNorthwest Institute of Plateau Biology, Chinese Academy of SciencesXiningQinghaiChina
- University of Chinese Academy of SciencesBeijingChina
| | - Pengfei Song
- Key Laboratory of Adaptation and Evolution of Plateau BiotaNorthwest Institute of Plateau Biology, Chinese Academy of SciencesXiningQinghaiChina
- University of Chinese Academy of SciencesBeijingChina
- Qinghai Provincial Key Laboratory of Animal Ecological GenomicsXiningQinghaiChina
| | - Wen Qin
- State Key Laboratory of Plateau Ecology and AgricultureQinghai UniversityXiningQinghaiChina
| | - Haijing Wang
- Key Laboratory of Adaptation and Evolution of Plateau BiotaNorthwest Institute of Plateau Biology, Chinese Academy of SciencesXiningQinghaiChina
- University of Chinese Academy of SciencesBeijingChina
| | - Zhenyuan Cai
- Key Laboratory of Adaptation and Evolution of Plateau BiotaNorthwest Institute of Plateau Biology, Chinese Academy of SciencesXiningQinghaiChina
- University of Chinese Academy of SciencesBeijingChina
| | - Hongmei Gao
- Key Laboratory of Adaptation and Evolution of Plateau BiotaNorthwest Institute of Plateau Biology, Chinese Academy of SciencesXiningQinghaiChina
- University of Chinese Academy of SciencesBeijingChina
| | - Daoxin Liu
- Key Laboratory of Adaptation and Evolution of Plateau BiotaNorthwest Institute of Plateau Biology, Chinese Academy of SciencesXiningQinghaiChina
- University of Chinese Academy of SciencesBeijingChina
| | - Bin Li
- Key Laboratory of Adaptation and Evolution of Plateau BiotaNorthwest Institute of Plateau Biology, Chinese Academy of SciencesXiningQinghaiChina
- University of Chinese Academy of SciencesBeijingChina
- Qinghai Provincial Key Laboratory of Animal Ecological GenomicsXiningQinghaiChina
| | - Tongzuo Zhang
- Key Laboratory of Adaptation and Evolution of Plateau BiotaNorthwest Institute of Plateau Biology, Chinese Academy of SciencesXiningQinghaiChina
- Qinghai Provincial Key Laboratory of Animal Ecological GenomicsXiningQinghaiChina
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Isotopic signature in isolated south-western populations of European brown bear (Ursus arctos). MAMMAL RES 2022. [DOI: 10.1007/s13364-022-00654-2] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/24/2022]
Abstract
AbstractStable isotope analysis of animal tissue samples is increasingly used to study the trophic ecology of target species. The isotopic signatures respond to the type of diet, but also to the environmental conditions of their habitat. In the case of omnivorous, seasonal or opportunistic feeding species, the interpretation of isotopic values is more complex, as it is largely determined by food selection, either due to individual choice or because of availability. We analysed C and N isotopes in brown bear (Ursus arctos) hair from four isolated populations of south-western Europe (Cantabrian, Pyrenees, Central Apennines and Alpine) accounting for the geographical and climatic differences among the four areas. We found inter-population differences in isotopic signatures that cannot be attributed to climatic differences alone, indicating that at least some bears from relatively higher altitude populations experiencing higher precipitation (Pyrenees) show a greater consumption of animal foods than those from lower altitudes (Cantabrian and Apennines). The quantification of isotopic niche space using Layman’s metrics identified significant similarities between the Cantabrian and Central Apennine samples that markedly differ from the Pyrenean and Alpine. Our study provides a baseline to allow further comparisons in isotopic niche spaces in a broad ranged omnivorous mammal, whose European distribution requires further conservation attention especially for southern isolated populations.
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Paulo C, Machado I, Carvalho H, Gomes J, Deodato Mota A, Tavares L, Almeida V, Gil S. A 5-year retrospective study of canine and feline patients referred to an isolation unit for infectious diseases. Vet Rec Open 2021; 8:e5. [PMID: 33981439 PMCID: PMC8110126 DOI: 10.1002/vro2.5] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/17/2020] [Revised: 01/19/2021] [Accepted: 02/03/2021] [Indexed: 11/29/2022] Open
Abstract
BACKGROUND Referral of cases is becoming more and more frequent in companion animal practice. The Infectious Diseases Isolation Unit (IDIU) admits first opinion, second opinion and referred patients with a confirmed infectious disease (ID) or a clinically suspected ID that is awaiting laboratory diagnosis. The primary aims of this study were to describe the annual number and characteristics of patients referred to the IDIU and identify the most frequent IDs in referred dogs and cats. A secondary aim was to investigate possible differences in the length of the hospitalisation and the clinical outcome among referred cases and those admitted to the IDIU after first and second opinion appointments. METHODS A retrospective study was carried out on patients hospitalised at the unit over 5 years from 9th October 2013 to 31st December 2018. RESULTS The study population consisted of 365 dogs and 515 cats to give a total of 880 patients hospitalised at the IDIU from October 2013 to December 2018. Among the 96 referred dogs, parvovirosis (37.7%) and leptospirosis (31.1%) were the most frequent IDs. Feline upper respiratory tract infection (38.2%) and feline leukaemia virus infections (36.4%) were the main causes in the 80 referred cats. Worrying noncompliance rates of dog (51.0%) and cat (52.5%) vaccination schedules were identified. The analysis of the length of hospitalisation in the three groups of patients was not statistically different. In both animal species there were statistically significant higher clinical discharge rates on the first opinion patients' group in comparison to referred patients and the second opinion group. CONCLUSIONS Parvovirosis and leptospirosis in dogs and upper respiratory disease and feline leukaemia virus infection in cats were the most common diagnoses for patients admitted to the IDIU, reinforcing the need for accurate vaccination. Discharge rates results pinpoint the need for timely accurate reference.
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Affiliation(s)
- Catarina Paulo
- Faculty of Veterinary MedicineUniversity of Lisbon, Av. Universidade TécnicaLisbonPortugal
| | - Inês Machado
- CIISA‐ Centre for Interdisciplinary Research in Animal HealthFaculty of Veterinary MedicineAv. Universidade TécnicaUniversity of LisbonLisbonPortugal
- Veterinary Teaching HospitalFaculty of Veterinary MedicineUniversity of LisbonLisbonPortugal
| | - Helena Carvalho
- Centro de Investigação e Estudos de Sociologia, University Institute of Lisbon (ISCTE ‐ IUL)LisboaPortugal
| | - Joana Gomes
- Veterinary Teaching HospitalFaculty of Veterinary MedicineUniversity of LisbonLisbonPortugal
| | - Ana Deodato Mota
- Laranjeiras’ Veterinary HospitalRua São Tomás de Aquino, 8CLisbon1600‐203Portugal
| | - Luís Tavares
- Faculty of Veterinary MedicineUniversity of Lisbon, Av. Universidade TécnicaLisbonPortugal
- CIISA‐ Centre for Interdisciplinary Research in Animal HealthFaculty of Veterinary MedicineAv. Universidade TécnicaUniversity of LisbonLisbonPortugal
| | - Virgílio Almeida
- Faculty of Veterinary MedicineUniversity of Lisbon, Av. Universidade TécnicaLisbonPortugal
- CIISA‐ Centre for Interdisciplinary Research in Animal HealthFaculty of Veterinary MedicineAv. Universidade TécnicaUniversity of LisbonLisbonPortugal
| | - Solange Gil
- Faculty of Veterinary MedicineUniversity of Lisbon, Av. Universidade TécnicaLisbonPortugal
- CIISA‐ Centre for Interdisciplinary Research in Animal HealthFaculty of Veterinary MedicineAv. Universidade TécnicaUniversity of LisbonLisbonPortugal
- Veterinary Teaching HospitalFaculty of Veterinary MedicineUniversity of LisbonLisbonPortugal
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Assessing the impact of climate change on the spatio-temporal distribution of foot-and-mouth disease risk for elephants. Glob Ecol Conserv 2020. [DOI: 10.1016/j.gecco.2020.e01176] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/13/2022] Open
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The Global Potential Distribution of Invasive Plants: Anredera cordifolia under Climate Change and Human Activity Based on Random Forest Models. SUSTAINABILITY 2020. [DOI: 10.3390/su12041491] [Citation(s) in RCA: 11] [Impact Index Per Article: 2.8] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 01/08/2023]
Abstract
The potential distribution of the invasive plant Anredera cordifolia (Tenore) Steenis was predicted by Random Forest models under current and future climate-change pathways (i.e., RCP4.5 and RCP8.5 of 2050s and the 2070s). Pearson correlations were used to select variables; the prediction accuracy of the models was evaluated by using AUC, Kappa, and TSS. The results show that suitable future distribution areas are mainly in Southeast Asia, Eastern Oceania, a few parts of Eastern Africa, Southern North America, and Eastern South America. Temperature is the key climatic factor affecting the distribution of A. cordifolia. Important metrics include mean temperature of the coldest quarter (0.3 °C ≤ Bio11 ≤ 22.9 °C), max temperature of the warmest month (17.1 °C ≤ Bio5 ≤ 35.5 °C), temperature annual range (10.7 °C ≤ Bio7 ≤ 33 °C), annual mean air temperature (6.8 °C ≤ Bio1 ≤ 24.4 °C), and min temperature of coldest month (−2.8 °C ≤ Bio6 ≤ 17.2 °C). Only one precipitation index (Bio19) was important, precipitation of coldest quarter (7 mm ≤ Bio19 ≤ 631 mm). In addition, areas with strong human activities are most prone to invasion. This species is native to Brazil, but has been introduced in Asia, where it is widely planted and has escaped from cultivation. Under the future climate scenarios, suitable habitat areas of A. cordifolia will expand to higher latitudes. This study can provide a reference for the rational management and control of A. cordifolia.
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Setting priority conservation areas of wild Tibetan gazelle (Procapra picticaudata) in China's first national park. Glob Ecol Conserv 2019. [DOI: 10.1016/j.gecco.2019.e00725] [Citation(s) in RCA: 6] [Impact Index Per Article: 1.2] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/23/2022] Open
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Zhang J, Jiang F, Li G, Qin W, Li S, Gao H, Cai Z, Lin G, Zhang T. Maxent modeling for predicting the spatial distribution of three raptors in the Sanjiangyuan National Park, China. Ecol Evol 2019; 9:6643-6654. [PMID: 31236249 PMCID: PMC6580265 DOI: 10.1002/ece3.5243] [Citation(s) in RCA: 53] [Impact Index Per Article: 10.6] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/26/2018] [Revised: 03/30/2019] [Accepted: 04/12/2019] [Indexed: 01/16/2023] Open
Abstract
Upland buzzard (Buteo hemilasius), Saker falcon (Falco cherrug), and Himalayan vulture (Gyps himalayensis) are three common large raptors in the Sanjiangyuan National Park (SNP), China's first national park. Among them, Upland buzzard and Saker falcon play a significant role in controlling plateau rodent populations and reducing the transmission of pathogens carried by rodents. The Himalayan vulture can provide services for the redistribution and recycling of nutrients in the ecosystem, and play an irreplaceable role in the celestial burial culture of Tibetans in China. Exploring their habitat suitability is important for the protection of the three raptors. Our research was based on the current distribution of Upland buzzard, Saker falcon, and Himalayan vulture that we had extensively surveyed in the Sanjiangyuan National Park from 2016 to 2017. Combined with the correlation analysis of environmental variables, we utilized maximum entropy model (MaxEnt) to evaluate and compare the habitat suitability of the three species in the Sanjiangyuan National Park. Elevation, climate, and human disturbance factors, which had direct or indirect effects on species survival and reproduction, were all included in the model. Among them, elevation was the most important environmental variables affecting the suitability of habitats of three species. Temperature-related factor was another important predictor. The high (>60%) suitable habitat areas for Upland buzzard, Saker falcon, and Himalayan vulture were 73,017.63, 40,732.78, and 61,654.33 km2, respectively, accounted for 59.32%, 33.09%, and 50.08% of the Sanjiangyuan National Park and their total suitable area (i.e., the sum area of high and moderate habitats) reached 96.07%, 60.59%, and 93.70%, respectively. Besides, the three species have overlapping areas for the suitable habitats, which means that overlapping areas should be highly valued and protected. Therefore, understanding the distribution of suitable habitats of the three raptors can provide useful information and reasonable reference for us to put forward suggestions for their protection and regional management.
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Affiliation(s)
- Jingjie Zhang
- Key Laboratory of Adaptation and Evolution of Plateau Biota, Northwest Institute of Plateau BiologyChinese Academy of SciencesXiningChina
- University of Chinese Academy of SciencesBeijingChina
- Qinghai Provincial Key Laboratory of Animal Ecological GenomicsXiningChina
| | - Feng Jiang
- Key Laboratory of Adaptation and Evolution of Plateau Biota, Northwest Institute of Plateau BiologyChinese Academy of SciencesXiningChina
- University of Chinese Academy of SciencesBeijingChina
- Qinghai Provincial Key Laboratory of Animal Ecological GenomicsXiningChina
| | - Guangying Li
- Qinghai Provincial Environmental Protection DepartmentXiningChina
| | - Wen Qin
- Key Laboratory of Adaptation and Evolution of Plateau Biota, Northwest Institute of Plateau BiologyChinese Academy of SciencesXiningChina
- University of Chinese Academy of SciencesBeijingChina
| | - Shengqing Li
- Qinghai Academy of Animal Science and Veterinary MedicineQinghai UniversityXiningChina
| | - Hongmei Gao
- Key Laboratory of Adaptation and Evolution of Plateau Biota, Northwest Institute of Plateau BiologyChinese Academy of SciencesXiningChina
- University of Chinese Academy of SciencesBeijingChina
| | - Zhenyuan Cai
- Key Laboratory of Adaptation and Evolution of Plateau Biota, Northwest Institute of Plateau BiologyChinese Academy of SciencesXiningChina
- University of Chinese Academy of SciencesBeijingChina
| | - Gonghua Lin
- Key Laboratory of Adaptation and Evolution of Plateau Biota, Northwest Institute of Plateau BiologyChinese Academy of SciencesXiningChina
| | - Tongzuo Zhang
- Key Laboratory of Adaptation and Evolution of Plateau Biota, Northwest Institute of Plateau BiologyChinese Academy of SciencesXiningChina
- Qinghai Provincial Key Laboratory of Animal Ecological GenomicsXiningChina
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