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Jiang X, Mao D, Zhen J, Wang J, Van de Voorde T. Exploring the conservation of historic avian corridors under urbanization threats in China: A case study of egrets in the Greater Bay Area. THE SCIENCE OF THE TOTAL ENVIRONMENT 2024; 948:174921. [PMID: 39038687 DOI: 10.1016/j.scitotenv.2024.174921] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 03/27/2024] [Revised: 06/24/2024] [Accepted: 07/18/2024] [Indexed: 07/24/2024]
Abstract
This study explores the conservation of historic flyway corridors for egret in the Greater Bay Area (GBA), with a focus on habitat connectivity and dynamic corridors. To address the gaps in previous research, we used field observations, bio-climatic data and landcover information spanning three decades. Our approach involves MaxENT modeling and the Linkage Mapper method. The results showed that the MaxENT model effectively simulated the egret habitats at different levels, with coastlines and riverbanks emerging as primary habitat zones. Moreover, bio-climatic factors, particularly Bio 19 and Bio 8, played a dominant role, accounting for 90 % of the habitat suitability in 2020. Other factors contributed rather minimally. Through the utilization of resistance surface and corridor extraction methods, noteworthy alterations in the flyway networks emerged post-2000, followed by a gradual return to normal. Connectivity analyses highlighted a critical 30 km threshold for the egret preservation. Corridor widths should be determined based on cost-effective considerations. We conclude that combining MaxENT with the Linkage Mapper method, even with limited egret observations and integrating multi-source data, such as land cover, might simulate potential suitable habitats and flyway dynamics for waterbirds such as egrets. This study provides valuable insights for the egret conservation and the preservation of their habitats in the GBA, contributing to a global waterbird diversity and habitat quality.
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Affiliation(s)
- Xiapeng Jiang
- Department of Geography, Ghent University, Ghent 9000, Belgium; State Key Laboratory of Black Soils Conservation and Utilization, Northeast Institute of Geography and Agroecology, Chinese Academy of Sciences, Changchun 130102, China.
| | - Dehua Mao
- State Key Laboratory of Black Soils Conservation and Utilization, Northeast Institute of Geography and Agroecology, Chinese Academy of Sciences, Changchun 130102, China
| | - Jianing Zhen
- State Key Laboratory of Black Soils Conservation and Utilization, Northeast Institute of Geography and Agroecology, Chinese Academy of Sciences, Changchun 130102, China.
| | - Junjie Wang
- MNR Key Laboratory for Geo-Environmental Monitoring of Great Bay Area, Guangdong Key Laboratory of Urban Informatics, Shenzhen Key Laboratory of Spatial Smart Sensing and Services, Shenzhen University, Shenzhen 518060, China
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Tang T, Zhu Y, Zhang YY, Chen JJ, Tian JB, Xu Q, Jiang BG, Wang GL, Golding N, Mehlman ML, Lv CL, Hay SI, Fang LQ, Liu W. The global distribution and the risk prediction of relapsing fever group Borrelia: a data review with modelling analysis. THE LANCET. MICROBE 2024; 5:e442-e451. [PMID: 38467129 DOI: 10.1016/s2666-5247(23)00396-8] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 06/01/2023] [Revised: 11/22/2023] [Accepted: 11/22/2023] [Indexed: 03/13/2024]
Abstract
BACKGROUND The recent discovery of emerging relapsing fever group Borrelia (RFGB) species, such as Borrelia miyamotoi, poses a growing threat to public health. However, the global distribution and associated risk burden of these species remain uncertain. We aimed to map the diversity, distribution, and potential infection risk of RFGB. METHODS We searched PubMed, Web of Science, GenBank, CNKI, and eLibrary from Jan 1, 1874, to Dec 31, 2022, for published articles without language restriction to extract distribution data for RFGB detection in vectors, animals, and humans, and clinical information about human patients. Only articles documenting RFGB infection events were included in this study, and data for RFGB detection in vectors, animals, or humans were composed into a dataset. We used three machine learning algorithms (boosted regression trees, random forest, and least absolute shrinkage and selection operator logistic regression) to assess the environmental, ecoclimatic, biological, and socioeconomic factors associated with the occurrence of four major RFGB species: Borrelia miyamotoi, Borrelia lonestari, Borrelia crocidurae, and Borrelia hermsii; and mapped their worldwide risk level. FINDINGS We retrieved 13 959 unique studies, among which 697 met the selection criteria and were used for data extraction. 29 RFGB species have been recorded worldwide, of which 27 have been identified from 63 tick species, 12 from 61 wild animals, and ten from domestic animals. 16 RFGB species caused human infection, with a cumulative count of 26 583 cases reported from Jan 1, 1874, to Dec 31, 2022. Borrelia recurrentis (17 084 cases) and Borrelia persica (2045 cases) accounted for the highest proportion of human infection. B miyamotoi showed the widest distribution among all RFGB, with a predicted environmentally suitable area of 6·92 million km2, followed by B lonestari (1·69 million km2), B crocidurae (1·67 million km2), and B hermsii (1·48 million km2). The habitat suitability index of vector ticks and climatic factors, such as the annual mean temperature, have the most significant effect among all predictive models for the geographical distribution of the four major RFGB species. INTERPRETATION The predicted high-risk regions are considerably larger than in previous reports. Identification, surveillance, and diagnosis of RFGB infections should be prioritised in high-risk areas, especially within low-income regions. FUNDING National Key Research and Development Program of China.
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Affiliation(s)
- Tian Tang
- State Key Laboratory of Pathogen and Biosecurity, Beijing Institute of Microbiology and Epidemiology, Beijing, China
| | - Ying Zhu
- Department of Epidemiology and Biostatistics, School of Public Health, Wuhan University, Wuhan, China
| | - Yuan-Yuan Zhang
- State Key Laboratory of Pathogen and Biosecurity, Beijing Institute of Microbiology and Epidemiology, Beijing, China
| | - Jin-Jin Chen
- State Key Laboratory of Pathogen and Biosecurity, Beijing Institute of Microbiology and Epidemiology, Beijing, China
| | - Jian-Bo Tian
- Department of Epidemiology and Biostatistics, School of Public Health, Wuhan University, Wuhan, China
| | - Qiang Xu
- State Key Laboratory of Pathogen and Biosecurity, Beijing Institute of Microbiology and Epidemiology, Beijing, China
| | - Bao-Gui Jiang
- State Key Laboratory of Pathogen and Biosecurity, Beijing Institute of Microbiology and Epidemiology, Beijing, China
| | - Guo-Lin Wang
- State Key Laboratory of Pathogen and Biosecurity, Beijing Institute of Microbiology and Epidemiology, Beijing, China
| | - Nick Golding
- Telethon Kids Institute, Nedlands, WA, Australia; School of Population Health, Curtin University, Bentley, WA, Australia; Melbourne School of Population and Global Health, University of Melbourne, Parkville, VIC, Australia
| | - Max L Mehlman
- Department of Health Metrics Sciences, School of Medicine, University of Washington, Seattle, WA, USA; Institute for Health Metrics and Evaluation, University of Washington, Seattle, WA, USA
| | - Chen-Long Lv
- State Key Laboratory of Pathogen and Biosecurity, Beijing Institute of Microbiology and Epidemiology, Beijing, China
| | - Simon I Hay
- Department of Health Metrics Sciences, School of Medicine, University of Washington, Seattle, WA, USA; Institute for Health Metrics and Evaluation, University of Washington, Seattle, WA, USA
| | - Li-Qun Fang
- State Key Laboratory of Pathogen and Biosecurity, Beijing Institute of Microbiology and Epidemiology, Beijing, China.
| | - Wei Liu
- State Key Laboratory of Pathogen and Biosecurity, Beijing Institute of Microbiology and Epidemiology, Beijing, China; Department of Epidemiology and Biostatistics, School of Public Health, Wuhan University, Wuhan, China.
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Tarjuelo R, Aragón P. Assessing vulnerability of reptile hotspots through temporal trends of global change factors in the Iberian Peninsula. THE SCIENCE OF THE TOTAL ENVIRONMENT 2023; 871:161917. [PMID: 36736406 DOI: 10.1016/j.scitotenv.2023.161917] [Citation(s) in RCA: 2] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 10/24/2022] [Revised: 01/18/2023] [Accepted: 01/26/2023] [Indexed: 06/18/2023]
Abstract
Habitat degradation and climate change are major threats to the long-term persistence of reptile populations. However, their roles on primary productivity instability remain unclear at certain scales. Besides, the design of protected areas has often overlooked reptiles or assumed that their ecological requirements are represented under the umbrella of more charismatic species. Here, we assess the vulnerability of areas of high diversity of reptiles in the Iberian Peninsula to global change using data from satellite imagery. We focused on primary productivity, climate and land-use change because they are indicators of environmental variability that might impair ecosystem functioning and alter wildlife communities. We used linear regressions to detect monotonic temporal trends in primary productivity (through the enhanced vegetation index, EVI) and climate (mean temperature and accumulated precipitation) at two spatial resolutions (10-km2 UTM squares and CORINE land-cover polygon level) over the period 2000-2020. We also determined how the strength of land-use and climate change affected the intensity of change in primary productivity at both spatial scales with multivariate linear regressions. We identified 339 hotspots (10-km2 UTM squares) and monotonic increments of temperature, EVI or both occurred in 43 %, 16 % and 22 % of them, respectively. Positive trends of the EVI were related to increasing temperatures and changes in shrubland and forest cover. Within the hotspots with monotonic increments in EVI and temperature, EVI increments occurred in 65 % of the CORINE polygons that did not change their land-cover type, with stronger increases in tree crops. Finally, the Natura 2000 network provides only moderate protection to reptile hotspots, being most of the vegetation types relatively underrepresented. The proportion of forest and shrubland protected by the Natura 2000 network was higher in hotspots where EVI changed. Our procedures are relevant to prioritize hotspots requiring ground monitoring that allows economic and time savings.
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Affiliation(s)
- Rocío Tarjuelo
- Instituto Universitario de Investigación en Gestión Forestal Sostenible (iuFOR), Universidad de Valladolid, Spain; Department of Biodiversity, Ecology and Evolution, Faculty of Biological Sciences, Complutense University of Madrid (UCM), Spain.
| | - Pedro Aragón
- Dpt. Biogeografía y Cambio Global, Museo Nacional de Ciencias Naturales (CSIC), Spain; Department of Biodiversity, Ecology and Evolution, Faculty of Biological Sciences, Complutense University of Madrid (UCM), Spain
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Tourinho L, Vale MM. Choosing among correlative, mechanistic, and hybrid models of species' niche and distribution. Integr Zool 2023; 18:93-109. [PMID: 34932894 DOI: 10.1111/1749-4877.12618] [Citation(s) in RCA: 7] [Impact Index Per Article: 7.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/19/2023]
Abstract
Different models are available to estimate species' niche and distribution. Mechanistic and correlative models have different underlying conceptual bases, thus generating different estimates of a species' niche and geographic extent. Hybrid models, which combining correlative and mechanistic approaches, are considered a promising strategy; however, no synthesis in the literature assessed their applicability for terrestrial vertebrates to allow best-choice model considering their strengths and trade-offs. Here, we provide a systematic review of studies that compared or integrated correlative and mechanistic models to estimate species' niche for terrestrial vertebrates under climate change. Our goal was to understand their conceptual, methodological, and performance differences, and the applicability of each approach. The studies we reviewed directly compared mechanistic and correlative predictions in terms of accuracy or estimated suitable area, however, without any quantitative analysis to support comparisons. Contrastingly, many studies suggest that instead of comparing approaches, mechanistic and correlative methods should be integrated (hybrid models). However, we stress that the best approach is highly context-dependent. Indeed, the quality and effectiveness of the prediction depends on the study's objective, methodological design, and which type of species' niche and geographic distribution estimated are more appropriate to answer the study's issue.
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Affiliation(s)
- Luara Tourinho
- Graduate Program in Ecology, Universidade Federal do Rio de Janeiro, Ilha do Fundão, Rio de Janeiro, Brazil
| | - Mariana M Vale
- Ecology Department, Universidade Federal do Rio de Janeiro, Ilha do Fundão, Rio de Janeiro, Brazil
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Sousa‐Guedes D, Sillero N, Bessa F, Marco A. Plastic pollution can affect the emergence patterns of the loggerhead turtle hatchlings. Anim Conserv 2022. [DOI: 10.1111/acv.12837] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/22/2022]
Affiliation(s)
- D. Sousa‐Guedes
- Centro de Investigação em Ciências Geo‐Espaciais (CICGE) Faculdade de Ciências da Universidade do Porto Vila Nova de Gaia Portugal
- Department of Life Sciences University of Coimbra, MARE ‐ Marine and Environmental Sciences Centre/ ARNET – Aquatic Research Network Coimbra Portugal
- Estación Biológica de Doñana, CSIC, C/ Américo Vespucio Sevilla Spain
- BIOS.CV ‐ Conservation of the Environment and Sustainable Development Sal Rei Cabo Verde
| | - N. Sillero
- Centro de Investigação em Ciências Geo‐Espaciais (CICGE) Faculdade de Ciências da Universidade do Porto Vila Nova de Gaia Portugal
| | - F. Bessa
- Department of Life Sciences University of Coimbra, MARE ‐ Marine and Environmental Sciences Centre/ ARNET – Aquatic Research Network Coimbra Portugal
| | - A. Marco
- Estación Biológica de Doñana, CSIC, C/ Américo Vespucio Sevilla Spain
- BIOS.CV ‐ Conservation of the Environment and Sustainable Development Sal Rei Cabo Verde
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Sillero N, Ribeiro‐Silva J, Arenas‐Castro S. Shifts in climatic realised niches of Iberian species. OIKOS 2022. [DOI: 10.1111/oik.08505] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/01/2022]
Affiliation(s)
- Neftalí Sillero
- CICGE, Centro de Investigação em Ciências Geo‐Espaciais, Faculdade de Ciências da Univ. do Porto, Alameda do Monte da Virgem Vila Nova de Gaia Portugal
| | - Joana Ribeiro‐Silva
- CICGE, Centro de Investigação em Ciências Geo‐Espaciais, Faculdade de Ciências da Univ. do Porto, Alameda do Monte da Virgem Vila Nova de Gaia Portugal
| | - Salvador Arenas‐Castro
- CICGE, Centro de Investigação em Ciências Geo‐Espaciais, Faculdade de Ciências da Univ. do Porto, Alameda do Monte da Virgem Vila Nova de Gaia Portugal
- Inst. Politécnico de Viana do Castelo, Escola Superior de Tecnologia e Gestão Viana do Castelo Portugal
- Área de Ecología, Depto de Botánica, Ecología y Fisiología Vegetal, Facultad de Ciencias, Univ. de Córdoba, Campus de Rabanales Córdoba España
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Strategies to Mitigate the Deteriorating Habitat Quality in Dong Trieu District, Vietnam. LAND 2022. [DOI: 10.3390/land11020305] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 11/17/2022]
Abstract
Dong Trieu district is a vital connection for territorial ecological security and human welfare between Hanoi (the capital of Vietnam) and Quang Ninh province. Therefore, habitat quality (HQ) is of extraordinary importance to the area’s sustainable development. The ArcGIS platform, Dyna-CLUE, and InVEST models were utilized in this study to assess the spatial and temporal transformations of land use and the changes of HQ in 2030 under various scenarios, with intentions to find strategies that may mitigate the HQ’s deteriorating trend in the district. Simulated results indicated that, assuming the development is maintained as usual, the average HQ of the District at 2030 could diminish by 0.044 from that of 2019 (a four-times decrease compared to the previous decade). Cases comprised of four basic scenarios, including development as usual, built-up expansion slowdown, forest protection emphasized, and agricultural land conversion, were used to identify potential strategies to mitigate the deteriorating trend. Simulated results revealed that keeping the built-up expansion rate lower than 100 ha y−1, the deforestation rate lower than 20 ha y−1, and preferring orchards over agricultural land conversion is required to limit the drop in HQ to within 0.01 in the next decade. Other than the existing population growth control policy, new guidelines such as (1) changing urban expansion type from outward to upward to control the built-up expansion rate, (2) substituting forest-harming industries to forest-preservation industries to reduce deforestation rate, (3) encouraging orchards preferred over agricultural land conversion to increase incomes while maintaining higher habitat quality, (4) practicing better farming technologies to improve crop production and to alleviate potential food security issues due to considerable reduction in cropland, and (5) promoting Green Infrastructure and the Belt and Road Initiative to increase urban green cover and raise residents’ income should be considered in designing the new mitigation strategies.
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Frans VF, Augé AA, Fyfe J, Zhang Y, McNally N, Edelhoff H, Balkenhol N, Engler JO. Integrated SDM database: Enhancing the relevance and utility of species distribution models in conservation management. Methods Ecol Evol 2021. [DOI: 10.1111/2041-210x.13736] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/26/2022]
Affiliation(s)
- Veronica F. Frans
- Center for Systems Integration and Sustainability Department of Fisheries and Wildlife Michigan State University East Lansing MI USA
- Ecology, Evolution, and Behavior Program Michigan State University East Lansing MI USA
- Wildlife Sciences University of Göttingen Göttingen Germany
| | | | - Jim Fyfe
- Department of Conservation Ōtepoti/Dunedin Office Dunedin New Zealand
| | - Yuqian Zhang
- Center for Systems Integration and Sustainability Department of Fisheries and Wildlife Michigan State University East Lansing MI USA
| | | | - Hendrik Edelhoff
- Wildlife Sciences University of Göttingen Göttingen Germany
- Bavarian State Institute of Forestry Freising Germany
| | - Niko Balkenhol
- Wildlife Sciences University of Göttingen Göttingen Germany
| | - Jan O. Engler
- Terrestrial Ecology Unit Ghent University Ghent Belgium
- Chair of Computational Landscape Ecology Technische Universität Dresden Dresden Germany
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Ma D, Lun X, Li C, Zhou R, Zhao Z, Wang J, Zhang Q, Liu Q. Predicting the Potential Global Distribution of Amblyomma americanum (Acari: Ixodidae) under Near Current and Future Climatic Conditions, Using the Maximum Entropy Model. BIOLOGY 2021; 10:1057. [PMID: 34681156 PMCID: PMC8533137 DOI: 10.3390/biology10101057] [Citation(s) in RCA: 14] [Impact Index Per Article: 4.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 09/01/2021] [Revised: 10/11/2021] [Accepted: 10/13/2021] [Indexed: 11/22/2022]
Abstract
Amblyomma americanum (the lone star tick) is a pathogen vector, mainly from eastern North America, that bites humans. With global integration and climate change, some ticks that are currently confined to a certain place may begin to spread out; some reports have shown that they are undergoing rapid range expansion. The difference in the potential geographic distribution of A. americanum under current and future climatic conditions is dependent on environment variables such as temperature and precipitation, which can affect their survival. In this study, we used a maximum entropy (MaxEnt) model to predict the potential geographic distribution of A. americanum. The MaxEnt model was calibrated at the native range of A. americanum using occurrence data and the current climatic conditions. Seven WorldClim climatic variables were selected by the jackknife method and tested in MaxEnt using different combinations of model feature class functions and regularization multiplier values. The best model was chosen based on the omission rate and the lowest Akaike information criterion. The resulting model was then projected onto the global scale using the current and future climate conditions modeled under four greenhouse gas emission scenarios.
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Affiliation(s)
- Delong Ma
- School of Public Health and Health Management, Shandong First Medical University and Shandong Academy of Medical Sciences, Jinan 250117, China; (D.M.); (C.L.)
- State Key Laboratory of Infectious Diseases Prevention and Control, National Institute for Communicable Disease Control and Prevention, Chinese Center for Disease Control and Prevention, Beijing 102206, China; (X.L.); (R.Z.); (Z.Z.); (J.W.)
| | - Xinchang Lun
- State Key Laboratory of Infectious Diseases Prevention and Control, National Institute for Communicable Disease Control and Prevention, Chinese Center for Disease Control and Prevention, Beijing 102206, China; (X.L.); (R.Z.); (Z.Z.); (J.W.)
| | - Chao Li
- School of Public Health and Health Management, Shandong First Medical University and Shandong Academy of Medical Sciences, Jinan 250117, China; (D.M.); (C.L.)
- State Key Laboratory of Infectious Diseases Prevention and Control, National Institute for Communicable Disease Control and Prevention, Chinese Center for Disease Control and Prevention, Beijing 102206, China; (X.L.); (R.Z.); (Z.Z.); (J.W.)
| | - Ruobing Zhou
- State Key Laboratory of Infectious Diseases Prevention and Control, National Institute for Communicable Disease Control and Prevention, Chinese Center for Disease Control and Prevention, Beijing 102206, China; (X.L.); (R.Z.); (Z.Z.); (J.W.)
| | - Zhe Zhao
- State Key Laboratory of Infectious Diseases Prevention and Control, National Institute for Communicable Disease Control and Prevention, Chinese Center for Disease Control and Prevention, Beijing 102206, China; (X.L.); (R.Z.); (Z.Z.); (J.W.)
- Shandong University Climate Change and Health Center, School of Public Health, Shandong University, Jinan 250012, China
| | - Jun Wang
- State Key Laboratory of Infectious Diseases Prevention and Control, National Institute for Communicable Disease Control and Prevention, Chinese Center for Disease Control and Prevention, Beijing 102206, China; (X.L.); (R.Z.); (Z.Z.); (J.W.)
| | - Qinfeng Zhang
- School of Public Health and Health Management, Shandong First Medical University and Shandong Academy of Medical Sciences, Jinan 250117, China; (D.M.); (C.L.)
| | - Qiyong Liu
- State Key Laboratory of Infectious Diseases Prevention and Control, National Institute for Communicable Disease Control and Prevention, Chinese Center for Disease Control and Prevention, Beijing 102206, China; (X.L.); (R.Z.); (Z.Z.); (J.W.)
- Shandong University Climate Change and Health Center, School of Public Health, Shandong University, Jinan 250012, China
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Sillero N, Arenas-Castro S, Enriquez‐Urzelai U, Vale CG, Sousa-Guedes D, Martínez-Freiría F, Real R, Barbosa A. Want to model a species niche? A step-by-step guideline on correlative ecological niche modelling. Ecol Modell 2021. [DOI: 10.1016/j.ecolmodel.2021.109671] [Citation(s) in RCA: 28] [Impact Index Per Article: 9.3] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/11/2023]
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