Research Article
BibTex RIS Cite

A Comprehensive and Innovative Environmental PSR Model for Biodiversity Priority Conservation Areas

Year 2024, Volume: 8 Issue: 2, 211 - 227, 30.12.2024

Abstract

Biodiversity is essential for ecosystem resilience and human well-being, yet it faces accelerating threats from habitat loss, climate change, and human activities. Conservation models often inadequately address the intertwined ecological and socio-economic drivers of biodiversity loss, leaving a gap between theoretical frameworks and real-world implementation. This study introduces an advanced Pressure-State-Response (PSR) model, developed through extensive fieldwork and leveraging Geographic Information Systems (GIS) and remote sensing technologies. The model integrates ecological indicators with socio-economic factors, including stakeholder engagement, education, and local economic conditions, creating a dynamic, context-specific approach to conservation. By adopting a Multi-Criteria Decision Analysis (MCDA) framework, specifically the Analytic Hierarchy Process (AHP), the enhanced PSR model prioritizes biodiversity hotspots based on ecological urgency and socio-economic resilience. It overcomes limitations of traditional models by incorporating customizable criteria and fostering equitable conservation strategies. The approach optimizes resource allocation, ensuring interventions target areas of highest biodiversity value while balancing local development needs. This study provides a replicable and adaptable methodology for conservation planning, addressing 21st-century challenges of biodiversity loss and socio-ecological complexity. By aligning conservation priorities with sustainable development goals, the model advances a transformative framework that bridges science, policy, and practice, offering global applicability for safeguarding biodiversity and ecosystem services.

References

  • Adams, W. M., Aveling, R., Brockington, D., Dickson, B., Elliott, J., Hutton, J., Roe, D., Vira, B., & Wolmer, W. (2004). Biodiversity conservation and the eradication of poverty. Science, 306 (5699), 1146-1149. https://doi.org/10.1126/science.1097920
  • Areendran, G., Rao, P., Raj, K., Mazumdar, S., & Puri, K. (2019). High conservation value areas: A toolkit for decision-making in biodiversity conservation. Journal of Environmental Management, 241, 382-393. https://doi.org/10.1016/j.jenvman.2019.04.056
  • Beaudrie, C., Corbett, C. J., Lewandowski, T. A., Malloy, T., & Zhou, X. (2021). Evaluating the application of decision analysis methods in simulated alternatives assessment case studies: Potential benefits and challenges of using MCDA. Integrated Environmental Assessment and Management, 17 (1), 27-41
  • Berkes, F. (2007). Community-based conservation in a globalized world. Proceedings of the National Academy of Sciences, 104 (39), 15188-15193. https://doi.org/10.1073/pnas.0702098104
  • Ceballos, G., & Ehrlich, P. R. (2006). Global mammal distributions, biodiversity hotspots, and conservation. Proceedings of the National Academy of Sciences, 103 (51), 19374-19379. https://doi.org/10.1073/pnas.0609334103
  • Ceballos, G., Ehrlich, P. R., Barnosky, A. D., García, A., Pringle, R. M., & Palmer, T. M. (2015). Accelerated modern human–induced species losses: Entering the sixth mass extinction. Science Advances, 1 (5), e1400253. https://doi.org/10.1126/sciadv.1400253
  • Cetas, E. R., & Yasué, M. (2017). A systematic review of motivational values in biodiversity conservation. Conservation Biology, 31 (5), 1202-1214. https://doi.org/10.1111/cobi.12845
  • Chandio, I. A., Matori, A. N. B., WanYusof, K. B., Talpur, M. A. H., Balogun, A. L., & Lawal, D. U. (2013). GIS-based analytic hierarchy process as a multicriteria decision analysis instrument: a review. Arabian Journal of Geosciences, 6, 3059-3066.
  • Chowdary, V. M., Chakraborthy, D., Jeyaram, A., Murthy, Y. K., Sharma, J. R., & Dadhwal, V. K. (2013). Multi-criteria decision making approach for watershed prioritization using analytic hierarchy process technique and GIS. Water Resources Management, 27, 3555-3571.
  • Convention on Biological Diversity. (2003). Handbook of the Convention on Biological Diversity: With the Cartagena Protocol on Biosafety (3rd ed.). Secretariat of the Convention on Biological Diversity, Montreal, Canada.
  • Daily, G. C. (1997). Nature's Services: Societal Dependence on Natural Ecosystems. Washington, DC.: Island Press.
  • DeLong, D. C. (1996). Defining biodiversity. Wildlife Society Bulletin, 24 (4), 738-749.
  • Díaz, S., Settele, J., Brondízio, E. S., Ngo, H. T., Agard, J., Arneth, A., ... & Zayas, C. N. (2019). Pervasive human-driven decline of life on Earth points to the need for transformative change. Science, 366 (6471), eaax3100. https://doi.org/10.1126/science.aax3100
  • Dinh, L. T. (2020). Development and application of a comprehensive PSR model for environmental assessment: The case study of Vietnam. Environmental Monitoring and Assessment, 192 (3), 1-15. https://doi.org/10.1007/s10661-020-8145-2
  • Diniz‐Filho, J. A. F., & De Campos Telles, M. P. (2002). Spatial autocorrelation analysis and the identification of operational units for conservation in continuous populations. Conservation Biology, 16 (4), 924-935.
  • Eldrandaly, K., Eldin, M. N., & Sayed, A. (2012). An integrated AI and GIS approach to location-allocation problem. International Journal of Computer Applications, 59 (8), 33-39. https://doi.org/10.5120/9543-3621
  • Esmail, N., & Geneletti, D. (2017). Environmental assessment and multi-criteria decision analysis: The case of ecosystem services in conservation planning. Environmental Impact Assessment Review, 66, 75-86. https://doi.org/10.1016/j.eiar.2017.05.002
  • Estoque, R. C. (2012). Analytic Hierarchy Process in Geospatial Analysis. In: Progress in Geospatial Analysis. Tokyo: Springer Japan, pp. 157-181.
  • European Environment Agency. (2003). Europe’s Environment: The third assessment. European Environment Agency. Luxembourg: Office for Official Publications of the European Communities.
  • Fisher, B., & Christopher, T. (2007). Poverty and biodiversity: Measuring the overlap of human poverty and the biodiversity hotspots. Ecological Economics, 62 (1), 93-101. https://doi.org/10.1016/j.ecolecon.2006.05.020
  • Folke, C., Carpenter, S., Walker, B., Scheffer, M., Elmqvist, T., Gunderson, L., & Holling, C. S. (2004). Regime shifts, resilience, and biodiversity in ecosystem management. Annual Review of Ecology, Evolution, and Systematics, 35, 557-581. https://doi.org/10.1146/annurev.ecolsys.35.021103.105711
  • Foody, G. M. (2008). GIS: Biodiversity applications. Progress in Physical Geography, 32 (2), 223-235. https://doi.org/10.1177/0309133308091027
  • Forman, E. H., & Gass, S. I. (2001). The analytic hierarchy process — an exposition. Operations Research, 49 (4), 469-486. https://doi.org/10.1287/opre.49.4.469.11231
  • Gaston, K. J. & Spicer, J. I. (2004). Biodiversity: An introduction (2nd ed.). Oxford, UK.: Blackwell Publishing.
  • Geneletti, D. (2010). Integrating ecosystem services in landscape planning: The role of stakeholder engagement. Environmental Impact Assessment Review, 30 (1), 73-81. https://doi.org/10.1016/j.eiar.2009.06.006
  • Geneletti, D., & Ferretti, V. (2015). Multicriteria analysis for sustainability assessment: Concepts, methods, and applications. Sustainability, 7 (3), 3482-3500. https://doi.org/10.3390/su7033482
  • Gould, S. J. (2000). Wonderful Life: The Burgess Shale and The Nature of History. New York & London: W. W. Norton & Company.
  • Greene, D. L., Park, S., & Liu, C. (2011). Analyzing the transition to electric drive vehicles in the US. Futures, 58, 34-52 https://doi.org/10.1016/j.futures.2013.07.003
  • Griffith, D. A. (2021). Interpreting Moran eigenvector maps with the Getis-Ord Gi* statistic. The Professional Geographer, 73 (3), 447-463.
  • Guerrero, A. M., Barnes, M., Bodin, Ö., Chadès, I., Davis, K. J., Iftekhar, M. S., ... & Wilson, K. A. (2020). Key considerations and challenges in the application of social‐network research for environmental decision making. Conservation Biology, 34 (3), 733-742.
  • Gupta, S., Govil, H., Singh, V., & Thakur, S. (2022). Advanced remote sensing technology for biodiversity conservation: Opportunities and challenges. Journal of Environmental Management, 302, 113996. https://doi.org/10.1016/j.jenvman.2021.113996
  • Hajkowicz, S., McDonald, G. T., & Smith, P. N. (2000). An evaluation of multiple objective decision support weighting techniques in natural resource management. Journal of Environmental Planning and Management, 43 (4), 505-518. https://doi.org/10.1080/09640560020001630
  • Harris, G. M., Jenkins, C. N., & Pimm, S. L. (2005). Refining biodiversity conservation priorities. Conservation Biology, 19 (1), 195-199. https://doi.org/10.1111/j.1523-1739.2005.00261.x
  • Hill, S., Motta, R. J., & Ferreira, L. (2005). The impact of machine learning and AI on environmental decision-making processes. Journal of Environmental Engineering, 131 (3), 431-441. https://doi.org/10.1061/(ASCE)0733-9372(2005)131:3(431)
  • Huppes, G., & Ishikawa, M. (2005). Eco-efficiency and its terminology. Journal of Industrial Ecology, 9 (4), 43-46. https://doi.org/10.1162/108819805775248070
  • Ivić, M. (2019). The role of AI in optimizing MCDA for environmental management. Journal of Environmental Informatics, 34 (4), 235-248. https://doi.org/10.3808/jei.201900396
  • Johnson, C. N. (2000). Determinants of loss of mammal species during the Late Quaternary 'megafauna' extinctions: Life history and ecology, but not body size. Proceedings of the Royal Society of London. Series B: Biological Sciences, 267 (1439), 1197-1201. https://doi.org/10.1098/rspb.2000.1126
  • Jones, K. E., Patel, N. G., Levy, M. A., Storeygard, A., Balk, D., Gittleman, J. L., & Daszak, P. (2008). Global trends in emerging infectious diseases. Nature, 451 (7181), 990-993. https://doi.org/10.1038/nature06536
  • Jongman, R. H. G. (1995). Nature conservation planning in Europe: Developing ecological networks. Landscape and Urban Planning, 32 (3), 169-183. https://doi.org/10.1016/0169-2046(94)00194-F
  • Karadeniz, E. (2024). Identification of priority areas (hotspots) for conservation of biodiversity: South of the Anatolian Diagonal. Doctoral thesis, Fırat University, Institute of Social Sciences, Department of Geography, Division of Physical Geography, Elazığ, Türkiye.
  • Laskar, A. (2003). Integrating GIS and Multicriteria Decision Making Techniques For Land Resource Planning. Netherlands: ITC.
  • Lechner, A. M., Brown, G., & Raymond, C. M. (2014). Modeling the impact of socio-economic and environmental changes on ecosystem services. Environmental Modelling & Software, 59, 1-14. https://doi.org/10.1016/j.envsoft.2014.05.004
  • Levrel, H. (2007). Selecting Indicators for The Management of Biodiversity. Institut Français de la Biodiversité, Paris. http://www.gis-ifb.org/documentation/
  • Levrel, H., & Bouamrane, M. (2008). Instrumental learning and sustainability indicators: Outputs from co-construction experiments in West African biosphere reserves. Ecology and Society, 13 (1), 28.
  • Levrel, H., Thompson, J. D., & Raymond, G. (2009). The integration of socio-economic and environmental indicators in sustainable development strategies. Ecological Indicators, 9 (2), 238-246. https://doi.org/10.1016/j.ecolind.2008.03.011
  • Linkov, I., & Moberg, E. (2012). Multi-Criteria Decision Analysis: Environmental Applications and Case Studies. Boca Raton: CRC Press.
  • Liu, J. (2007). Complexity of coupled human and natural systems. Science, 317 (5844), 1513-1516. https://doi.org/10.1126/science.1144004
  • Malczewski, J. (2000). GIS and multicriteria decision analysis. Journal of the Operational Research Society, 51 (2), 247.
  • Malczewski, J. (2004). GIS-based land-use suitability analysis: A critical overview. Progress in Planning, 62, 3-65.
  • Maxim, L., Spangenberg, J. H., & O'Connor, M. (2009). An analysis of risks for biodiversity under the DPSIR framework. Ecological Economics, 69 (1), 12-23.
  • Miłek, M., Stanik, J., Kiedrowicz, M., & Napiórkowski, J. (2023). Multi-criteria comparative analysis of GIS class systems. GIS Odyssey Journal, 3 (1), 97-122.
  • Mohedano Roldán, A., Duit, A., & Schultz, L. (2019). Does stakeholder participation increase the legitimacy of nature reserves in local communities? Evidence from 92 Biosphere Reserves in 36 countries. Journal of Environmental Policy & Planning, 21 (2), 188-203.
  • Moores, J. (2012). Spatial statistical tools for environmental analysis. Environmental Modelling & Software, 38, 155-165. https://doi.org/10.1016/j.envsoft.2012.05.013
  • Moreira, J. R., Abdalla Filho, A. L., & Pires, E. C. (2004). Fuzzy logic applied to environmental data and analysis. Environmental Modelling & Software, 19 (10), 901-912. https://doi.org/10.1016/j.envsoft.2003.11.004
  • Morris, R. J., Gurevitch, J., & Nichols, J. D. (2001). Fuzzy logic and environmental decision making. Trends in Ecology & Evolution, 16 (7), 337-342. https://doi.org/10.1016/S0169-5347(01)02277-7
  • Mukherjee, N., Hugé, J., Sutherland, W. J., McNeill, J., Van Opstal, M., Dahdouh-Guebas, F., & Koedam, N. (2015). The Delphi technique in ecology and biological conservation: Applications and guidelines. Methods in Ecology and Evolution, 6 (9), 1097-1109. https://doi.org/10.1111/2041-210X.12387
  • Myers, N. (1988). Threatened biotas: “Hot spots” in tropical forests. The Environmentalist, 8 (3), 187-208. https://doi.org/10.1007/BF02240252
  • Myers, N., Mittermeier, R. A., Mittermeier, C. G., Da Fonseca, G. A., & Kent, J. (2000). Biodiversity hotspots for conservation priorities. Nature, 403 (6772), 853-858. https://doi.org/10.1038/35002501
  • Negret, P. J., Marco, M. D., Sonter, L. J., Rhodes, J., Possingham, H. P., & Maron, M. (2020). Effects of spatial autocorrelation and sampling design on estimates of protected area effectiveness. Conservation Biology, 34 (6), 1452-1462.
  • Norris, K. (2008). Agriculture and biodiversity conservation: Opportunity knocks. Conservation Letters, 1 (1), 2-11. https://doi.org/10.1111/j.1755-263X.2008.00007.x
  • Odu, G. (2019). A literature review on multi-criteria decision-making models for renewable energy investment decisions. Journal of Renewable and Sustainable Energy, 11 (2), 021201. https://doi.org/10.1063/1.5053177
  • Organisation for Economic Co-operation and Development (OECD). (1994). Environmental Indicators: OECD core set. Paris: OECD Publishing.
  • Papathanasiou, J., & Ploskas, N. (2018). Topsis: Examples and Python Implementations. Springer International Publishing. https://doi.org/10.1007/978-3-319-55538-0_1
  • Parsons, K. (1991). Conceptualizing resilience and vulnerability: The role of stress in the dynamics of ecosystems. Ecology, 72 (1), 153-168. https://doi.org/10.2307/1938914
  • Pelissari, R., Oliveira, M. C., Abackerli, A. J., Ben‐Amor, S., & Assumpção, M. R. P. (2021). Techniques to model uncertain input data of multi‐criteria decision‐making problems: a literature review. International Transactions in Operational Research, 28 (2), 523-559
  • Peng, Y., Ahmad, S. F., Irshad, M., Al-Razgan, M., Ali, Y. A., & Awwad, E. M. (2023). Impact of digitalization on process optimization and decision-making towards sustainability: The moderating role of environmental regulation. Sustainability, 15 (20), 15156.
  • Perihanoğlu, D., & Yeler, G. (2021). Application of spatial autocorrelation methods to detect spatial distribution patterns of environmental variables. Journal of Environmental Management, 291, 112637. https://doi.org/10.1016/j.jenvman.2021.112637
  • Pimm, S. L., Jenkins, C. N., Abell, R., Brooks, T. M., Gittleman, J. L., Joppa, L. N., ... & Sexton, J. O. (2014). The biodiversity of species and their rates of extinction, distribution, and protection. Science, 344 (6187), 1246752. https://doi.org/10.1126/science.1246752
  • Pullin, A. S., Bangpan, M., Dalrymple, S., Dickson, K., Haddaway, N. R., & Petticrew, M. (2016). Human well-being impacts of terrestrial protected areas: A systematic review. Environmental Evidence, 5 (1), 1-25. https://doi.org/10.1186/s13750-016-0053-7
  • Rao, K. S., & Geisler, C. (1990). The social dynamics of biodiversity conservation in developing countries. Population and Development Review, 16, 185-202. https://doi.org/10.2307/1973186
  • Rowley, H. V., Peters, G. M., Lundie, S., & Moore, S. J. (2012). Aggregating sustainability indicators: Beyond the weighted sum. Journal of Environmental Management, 111, 24-33. https://doi.org/10.1016/j.jenvman.2012.05.004
  • Russo, R. P., & Camanho, R. (2015). Criteria and indicators of sustainable forest management. Sustainability, 7 (8), 10043-10059. https://doi.org/10.3390/su70810043
  • Saaty, T. L. (1980). The Analytic Hierarchy Process: Planning, Priority Setting, Resources Allocation. New York: Mcgraw-Hill.
  • Saaty, T. L. (2004). Fundamentals of the Analytic Network Process—Multiple networks with benefits, costs, opportunities, and risks. Journal of Systems Science and Systems Engineering, 13 (3), 348-379. https://doi.org/10.1007/s11518-006-0174-1
  • Saaty, T. L. (2008). Decision making with the Analytic Hierarchy Process. International Journal of Services Sciences, 1 (1), 83-98. https://doi.org/10.1504/IJSSCI.2008.017590
  • Saltelli, A., Chan, K., & Scott, E. M. (2000). Sensitivity analysis. New York: Wiley.
  • Saptarshi, S., & Raghavendra, K. (2009). Integration of remote sensing and GIS for land use/land cover mapping and change detection. Journal of the Indian Society of Remote Sensing, 37 (3), 319-326. https://doi.org/10.1007/s12524-009-0028-7
  • Sen, A. (2014). Development as freedom (2nd ed.). UK.: Oxford University Press.
  • Shih, H. S., Shyur, H.J., & Lee, E. S. (2007). An extension of TOPSIS for group decision making. Mathematical and Computer Modelling, 45 (7-8), 801-813. https://doi.org/10.1016/j.mcm.2006.03.023
  • Steele, K., Carmel, Y., Cross, J., & Wilcox, C. (2009). Uses and misuses of multi-criteria decision analysis (MCDA) in environmental decision-making. Risk Analysis, 29 (1), 26-33. https://doi.org/10.1111/j.1539-6924.2008.01016.x
  • Thakkar, J. J. (2021). Multi-criteria Decision Making. Studies in Systems, In: Decision and Control (336, 1-365). Singapore: Springer.
  • Thibaut, L. M., & Connolly, S. R. (2013). Understanding diversity–stability relationships: towards a unified model of portfolio effects. Ecology Letters, 16 (2), 140-150.
  • Tobler, W. R. (1969). Geographical filters and their inversion. Geographical Analysis, 1 (3), 234-253. https://doi.org/10.1111/j.1538-4632.1969.tb00620.x
  • Uzun, B., Taiwo, M., Syidanova, A., & Uzun Ozsahin, D. (2021). The Technique For Order of Preference By Similarity to Ideal Solution (Topsis). In: G. M. Kontoghiorghes (Ed.), Application of Multi-Criteria Decision Analysis in Environmental And Civil Engineering (pp. 25-30). Springer.
  • Vu, Q. M. (2020). Application of PSR-AHP model for biodiversity conservation prioritization in Vietnam. Journal of Environmental Management, 268, 110617. https://doi.org/10.1016/j.jenvman.2020.110617
  • Wang, Y.M., & Elhag, T.M.S. (2006). Fuzzy TOPSIS method based on alpha level sets with an application to bridge risk assessment. Expert Systems With Applications, 31 (2), 309-319. https://doi.org/10.1016/j.eswa.2005.09.040
  • Wolfslehner, B., & Vacik, H. (2008). Evaluating sustainable forest management strategies with the analytic network process in a Pressure-State-Response framework. Forest Policy and Economics, 10 (5), 364-374. https://doi.org/10.1016/j.forpol.2008.02.007
  • Wurzel, R. K., Zito, A. R., & Jordan, A. J. (2013). Environmental Governance in Europe: A Comparative Analysis of the Use of New Environmental Policy Instruments. Edward Elgar Publishing.
  • Yang, L., Yuan, Y., Xu, B., & Hu, C. (2021). The impact of biodiversity on ecosystem functioning across scales. Nature Communications, 12 (1), 1-13. https://doi.org/10.1038/s41467-021-25155-4
  • Zhang, Y., Li, Q., & Lu, W. (2019). Artificial intelligence for improving decision-making in environmental monitoring and management. Environmental Science & Technology, 53 (21), 12277-12288. https://doi.org/10.1021/acs.est.9b03582
There are 90 citations in total.

Details

Primary Language English
Subjects Conservation and Biodiversity
Journal Section Research articles
Authors

Enes Karadeniz 0000-0003-0757-8553

M. Taner Şengün 0000-0003-4039-6591

Early Pub Date December 8, 2024
Publication Date December 30, 2024
Submission Date December 1, 2024
Acceptance Date December 8, 2024
Published in Issue Year 2024 Volume: 8 Issue: 2

Cite

APA Karadeniz, E., & Şengün, M. T. (2024). A Comprehensive and Innovative Environmental PSR Model for Biodiversity Priority Conservation Areas. International Journal of Nature and Life Sciences, 8(2), 211-227.