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Ansari A, Ghorbanpour M, Kazemi A, Kariman K. Ecological assessment of Iran's terrestrial biomes for wildlife conservation. Sci Rep 2023; 13:17761. [PMID: 37853178 PMCID: PMC10584875 DOI: 10.1038/s41598-023-45120-4] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/30/2023] [Accepted: 10/16/2023] [Indexed: 10/20/2023] Open
Abstract
Man-made activities pose the greatest threats to wildlife in Iran's terrestrial biomes, causing significant habitat damage and fragmentation in recent years. To fully understand these threats, the present study was conducted to identify and map the Iran's terrestrial biomes using the IDRISI TerrSet 18.31 Software, the Terrestrial Biomes Ecosystem Service Modeler on the InVEST toolkit (TBESMI), and comprehensive data sources including maps of roads, protected areas, terrestrial biomes, and country-wide land cover maps of 2017. The results showed that the largest terrestrial biome in Iran is deserts and xeric shrublands (DXS), while flooded grasslands and savannas (FGS) is the smallest biome. Roads, along with urban and agricultural developments are among the biggest threats and most destructive stressors in Iran's terrestrial biomes. The results also revealed that there was a growth in destruction of habitats located in the temperate broadleaf and mixed forest (TBMF), temperate coniferous forest (TCF), and FGS, alongside a decrease in the DXS biome. Furthermore, we detected an increase in habitat landscape quality in the DXS, FGS and montane grasslands and shrub lands (MGS), and a decrease in the temperate grasslands, savannas and shrublands (TGSS) and TBMF biomes. Finally, the cumulative risk of habitat degradation increased in the FGS, TCF, TGSS, and TBMF biomes, whereas it decreased in the DXS biome. The FGS biome with the highest consequence cumulative score, and the MGS biome with the highest cumulative risk exposure score were found to be at the highest risk from man-made activities. Stressors associated with agriculture and urbanization had the highest cumulative exposure scores in the MGS, while roads had the highest exposure scores in the TBMF and DXS biomes. Our study underscores the critical importance of conserving Iran's terrestrial biomes and wildlife, especially in high-risk biomes like FGS and MGS, given the substantial threats posed by human activities.
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Affiliation(s)
- Amir Ansari
- Department of Environmental Sciences and Engineering, Faculty of Agriculture and Environment, Arak University, Arak, 38156-8-8349, Iran.
| | - Mansour Ghorbanpour
- Department of Medicinal Plants, Faculty of Agriculture and Natural Resources, Arak University, Arak, 38156-8-8349, Iran.
| | - Ali Kazemi
- Department of Environmental Sciences and Engineering, Faculty of Agriculture and Environment, Arak University, Arak, 38156-8-8349, Iran
| | - Khalil Kariman
- UWA School of Agriculture and Environment, The University of Western Australia, Perth, WA, 6009, Australia
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Kantharajan G, Govindakrishnan PM, Chandran R, Singh RK, Kumar K, Anand A, Krishnan P, Mohindra V, Shukla SP, Lal KK. Anthropogenic risk assessment of riverine habitat using geospatial modelling tools for conservation and restoration planning: a case study from a tropical river Pranhita, India. ENVIRONMENTAL SCIENCE AND POLLUTION RESEARCH INTERNATIONAL 2023; 30:37579-37597. [PMID: 36572775 DOI: 10.1007/s11356-022-24825-5] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 05/06/2022] [Accepted: 12/14/2022] [Indexed: 06/18/2023]
Abstract
The riverine ecosystem provides multiple benefits to human community and contributes to the sustainable development of the ecoregion. The growing dependency on these ecosystems has largely contributed to aggravating the ecological risks, habitat degradation, and loss of ecosystem services. The present study evaluates the ecological risk emanating from nine anthropogenic stressors including river use, hydro-morphology, catchment pollution, and biological stressor on river Pranhita in Godavari Basin of Peninsular India using InVEST (Integrated Valuation of Ecosystem Services and Tradeoffs) Habitat Risk Assessment model. The primary field survey, remote sensing, and secondary data-assisted spatial modelling results revealed low ecological risk (R = 0.65 of 3) in river Pranhita due to anthropogenic activities. Sediment loading, the inflow of nitrogen, and habitat fragmentation were the major stressors with relatively higher risk score (> 1); influence on a sizeable portion of riverine habitat (29-75% of the total area under high-risk zone) indicates the mounting threat from catchment activities. The low-risk value observed in protected river reaches as compared to unprotected areas is likely to be influenced by the abundant presence of intact riparian vegetation which mitigate the catchment stressors and minimal anthropogenic activity within protected areas. This study demonstrates the application of InVEST HRA model for ecological risk assessment of riverine ecosystems and fish assemblages along with their input data generation framework. This has the potential for prioritization of sensitive habitats based on computed ecological risk and stressor identification based on their exposure and consequences for developing appropriate mitigation measures. This model is spatially explicit and accommodates user-defined criteria for ecosystem-level assessment at a regional and national scale to facilitate the resource managers and policymakers for conservation and restoration planning and implementation of targeted management measures for sustainable development.
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Affiliation(s)
- Ganesan Kantharajan
- ICAR - National Bureau of Fish Genetic Resources, Lucknow, 226002, Uttar Pradesh, India
- ICAR - Central Institute of Fisheries Education, Mumbai, 400061, Maharashtra, India
| | | | - Rejani Chandran
- ICAR - National Bureau of Fish Genetic Resources, Lucknow, 226002, Uttar Pradesh, India
| | - Rajeev Kumar Singh
- ICAR - National Bureau of Fish Genetic Resources, Lucknow, 226002, Uttar Pradesh, India.
| | - Kundan Kumar
- ICAR - Central Institute of Fisheries Education, Mumbai, 400061, Maharashtra, India
| | - Arur Anand
- Regional Remote Sensing Centre, NRSC, ISRO-Department of Space, Nagpur, 440033, Maharashtra, India
| | - Pandian Krishnan
- Bay of Bengal Programme, Inter-Governmental Organisation (BOBP-IGO), Chennai, 600018, Tamil Nadu, India
| | - Vindhya Mohindra
- ICAR - National Bureau of Fish Genetic Resources, Lucknow, 226002, Uttar Pradesh, India
| | - Satya Prakash Shukla
- ICAR - Central Institute of Fisheries Education, Mumbai, 400061, Maharashtra, India
| | - Kuldeep Kumar Lal
- ICAR - National Bureau of Fish Genetic Resources, Lucknow, 226002, Uttar Pradesh, India
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Regional Ecological Security Pattern Construction Based on Ecological Barriers: A Case Study of the Bohai Bay Terrestrial Ecosystem. SUSTAINABILITY 2022. [DOI: 10.3390/su14095384] [Citation(s) in RCA: 4] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 02/06/2023]
Abstract
The construction of ecological barriers and ecological security patterns is an important way of maintaining regional ecological security in landscape ecology. However, there is still no consensus on the concept and connotation of ecological barriers, and the zoning and adaptive management of ecological sources are rarely considered in the construction of ecological security patterns. This study uses the terrestrial ecosystem of Bohai Bay, China as a study area, and the identification and zoning of ecological sources in the ecological security pattern are achieved by combining an ecosystem service assessment with an ecological risk assessment, and on this basis, ecological barriers are identified to optimize the structure and function of ecological sources. The minimum cumulative resistance model is used to identify ecological corridors and ecological strategic nodes and to construct an ecological security pattern based on the modified ecological sources. The results demonstrate that firstly, 2873.25 km2 was identified as the ecological source, accounting for 14.28% of the total. Secondly, there are three large ecological barrier zones and nine ecological barrier cells with a total area of 1173.06 km2, accounting for 40.83% of the ecological sources. Thirdly, a total of 35 ecological corridors were extracted, and 32 ecological strategic nodes were marked, mainly distributed at the intersection and branches of important ecological corridors. An ecological security pattern construction system was formed with the collection of ecological source selection, ecological barrier identification, ecological resistance surface construction, and ecological corridor extraction. Fourthly, the concept and connotation of ecological barriers was analyzed, and the complementary relationship between ecological barriers and ecological security patterns in terms of structure and function is discussed. This study enriches the definition and connotation of ecological barriers, provides a new framework for identifying the ecological security patterns, and provides scientific guidance for ecological protection and management in coastal areas.
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Zhai T, Huang L. Linking MSPA and Circuit Theory to Identify the Spatial Range of Ecological Networks and Its Priority Areas for Conservation and Restoration in Urban Agglomeration. Front Ecol Evol 2022. [DOI: 10.3389/fevo.2022.828979] [Citation(s) in RCA: 8] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/13/2022] Open
Abstract
Rapid urbanization has led to the continuous degradation of natural ecological space within large urban agglomerations, triggering landscape fragmentation and habitat loss, which poses a great threat to regional ecological sustainability. Ecological networks (ENs) are a comprehensive control scheme to protect regional ecological sustainability. However, in the current research about ENs, most studies can only determine the orientation of ecological corridors but not their specific spatial range. This leads to the fact that ENs can only be abstract concepts composed of points and lines, and cannot be implemented into concrete spatial planning. In this study, taking the Shandong Peninsula urban agglomeration as an example, ecological sources were identified by morphological spatial pattern analysis (MSPA) and habitat quality assessment, ecological resistance surfaces were constructed based on habitat risk assessment (HRA). And circuit theory was used to simulate the ecosystem processes in heterogeneous landscapes via by calculating the cumulative current value and cumulative current recovery value, to identify the spatial range and key areas of ecological corridors. The results showed that the ENs includes 6,263.73 km2 of ecological sources, 12,136.61 km2 of ecological corridors, 283.61 km2 of pinch points and 347.51 km2 of barriers. Specifically, ecological sources were distributed in a spatial pattern of five groups, and ecological corridors were short and dense within groups, long in distance and narrow in width between groups. The pinch points and barriers mainly exist in the ecological corridors connecting the inner and outer parts of the central city and in the inter-group corridors. In order to ensure the connectivity and effectiveness of ENs, it is necessary to focus on the pinch points and barriers and include them in the priority areas for protection and restoration. Based on MSPA and circuit theory, this study provides a new method for determining the spatial range of ENs and the specific locations of priority areas, and provides a feasible solution for the concrete implementation of ENs to achieve effective ecological protection and restoration.
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Identification and Prediction of Wetland Ecological Risk in Key Cities of the Yangtze River Economic Belt: From the Perspective of Land Development. SUSTAINABILITY 2021. [DOI: 10.3390/su13010411] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 11/16/2022]
Abstract
Rapid urbanization aggravates the degradation of wetland function. However, few studies have quantitatively analyzed and predicted the comprehensive impacts of different scenarios and types of human activities on wetland ecosystems from the perspective of land development. Combined with the Habitat Risk Assessment (HRA) model and the Cellular Automata (Ca)-Markov model, this study quantitatively measured the impact intensity and spatial distribution of different types of human activities on the wetland ecosystem in 2015, simulated and predicted the ecological pressure on the wetland in 2030, and identified the ecological risk hotspots of the Yangtze River waterfront along the upper, middle, and lower reaches of the Yangtze River Economic Belt. The results showed that the ecological risk of wetlands in the study area was low in the urban core and high in the suburbs. Construction activities posed a greater risk to wetlands. The intensity of human activities in the ecological protection scenario will be significantly lower than that in the natural development scenario in 2030. The waterfront in the middle and lower reaches of the Yangtze River will face more ecological risks. The results of the study can provide theoretical and technical support for wetland conservation policy formulation and waterfront development in the Yangtze River Economic Belt.
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Verutes GM, Johnson AF, Caillat M, Ponnampalam LS, Peter C, Vu L, Junchompoo C, Lewison RL, Hines EM. Using GIS and stakeholder involvement to innovate marine mammal bycatch risk assessment in data-limited fisheries. PLoS One 2020; 15:e0237835. [PMID: 32817725 PMCID: PMC7446845 DOI: 10.1371/journal.pone.0237835] [Citation(s) in RCA: 6] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/05/2019] [Accepted: 08/04/2020] [Indexed: 11/25/2022] Open
Abstract
Fisheries bycatch has been identified as the greatest threat to marine mammals worldwide. Characterizing the impacts of bycatch on marine mammals is challenging because it is difficult to both observe and quantify, particularly in small-scale fisheries where data on fishing effort and marine mammal abundance and distribution are often limited. The lack of risk frameworks that can integrate and visualize existing data have hindered the ability to describe and quantify bycatch risk. Here, we describe the design of a new geographic information systems tool built specifically for the analysis of bycatch in small-scale fisheries, called Bycatch Risk Assessment (ByRA). Using marine mammals in Malaysia and Vietnam as a test case, we applied ByRA to assess the risks posed to Irrawaddy dolphins (Orcaella brevirostris) and dugongs (Dugong dugon) by five small-scale fishing gear types (hook and line, nets, longlines, pots and traps, and trawls). ByRA leverages existing data on animal distributions, fisheries effort, and estimates of interaction rates by combining expert knowledge and spatial analyses of existing data to visualize and characterize bycatch risk. By identifying areas of bycatch concern while accounting for uncertainty using graphics, maps and summary tables, we demonstrate the importance of integrating available geospatial data in an accessible format that taps into local knowledge and can be corroborated by and communicated to stakeholders of data-limited fisheries. Our methodological approach aims to meet a critical need of fisheries managers: to identify emergent interaction patterns between fishing gears and marine mammals and support the development of management actions that can lead to sustainable fisheries and mitigate bycatch risk for species of conservation concern.
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Affiliation(s)
- Gregory M. Verutes
- Faculty of Political and Social Sciences, Universidade de Santiago de Compostela, Santiago de Compostela, Spain
- Campus Do*Mar, International Campus of Excellence, Vigo, Spain
- * E-mail:
| | - Andrew F. Johnson
- MarFishEco Fisheries Consultants, Edinburgh, United Kingdom
- The Lyell Centre, Institute of Life and Earth Sciences, School of Energy, Geoscience, Infrastructure and Society, Heriot-Watt University, Edinburgh, United Kingdom
| | | | | | - Cindy Peter
- Institute of Biodiversity and Environmental Conservation, University Malaysia Sarawak, Sarawak, Malaysia
| | - Long Vu
- Vietnam Marine Megafauna Network, Center for Biodiversity Conservation and Endangered Species, Ho Chi Minh, Vietnam
| | | | - Rebecca L. Lewison
- Department of Biology, San Diego State University, San Diego, CA, United States of America
| | - Ellen M. Hines
- Estuary & Ocean Science Center, San Francisco State University, Tiburon, CA, United States of America
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Kheirkhah Ghehi N, MalekMohammadi B, Jafari H. Integrating habitat risk assessment and connectivity analysis in ranking habitat patches for conservation in protected areas. J Nat Conserv 2020. [DOI: 10.1016/j.jnc.2020.125867] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/23/2022]
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Zhai T, Wang J, Fang Y, Qin Y, Huang L, Chen Y. Assessing ecological risks caused by human activities in rapid urbanization coastal areas: Towards an integrated approach to determining key areas of terrestrial-oceanic ecosystems preservation and restoration. THE SCIENCE OF THE TOTAL ENVIRONMENT 2020; 708:135153. [PMID: 31810665 DOI: 10.1016/j.scitotenv.2019.135153] [Citation(s) in RCA: 38] [Impact Index Per Article: 9.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 07/09/2019] [Revised: 09/25/2019] [Accepted: 10/22/2019] [Indexed: 06/10/2023]
Abstract
Rapid urbanization and industrialization in the coastal zone have caused increasingly serious impacts on coastal ecosystems. It is necessary to assess the ecological risk caused by human activities to determine key areas of terrestrial-oceanic ecosystems preservation and restoration to ensure sustainable ecological management in the coastal zone. Key areas of ecosystem preservation and restoration were studied through the assessment of the impacts of ecological pressure sources related to human activities from the perspective of terrestrial-oceanic ecosystems, using the habitat risk assessment (HRA) and habitat quality (HQ) models in the Chinese coastal zone. The results showed that the impact of human activities on the terrestrial ecosystems in the South of China was significantly lower than that in the North. An improvement rate of habitat quality was noticed only in the south and central coastal areas when further away from industrial land. Agricultural production, urban expansion, and industrial pollution had major negative impacts on the habitat quality of terrestrial ecosystems in the Chinese coastal zone, and also threatened the health of marine ecosystems. The ecological risks caused by human activities in the offshore areas of northern Shandong and eastern Jiangsu were relatively low. Mineral development in the north, excessive nitrogen and phosphorus emissions from agricultural production in the south, and port operations were important drivers of increased ecological risks in offshore areas. There were regional spatial differences in the key ecosystem preservation and restoration areas. The provinces of Shandong, Jiangsu, Hebei, Liaoning, and Guangdong are key areas for strengthening the preservation and restoration of terrestrial-oceanic ecosystems. This study provides a reference for large-scale territorial spatial planning and ecosystems conservation.
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Affiliation(s)
- Tianlin Zhai
- School of Resource and Environmental Sciences, Wuhan University, Wuhan 430079, China
| | - Jing Wang
- School of Resource and Environmental Sciences, Wuhan University, Wuhan 430079, China.
| | - Ying Fang
- School of Resource and Environmental Sciences, Wuhan University, Wuhan 430079, China
| | - Yun Qin
- School of Environmental Studies, China University of Geosciences, Wuhan 430074, China
| | - Longyang Huang
- School of Resource and Environmental Sciences, Wuhan University, Wuhan 430079, China
| | - Ye Chen
- School of Resource and Environmental Sciences, Wuhan University, Wuhan 430079, China
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