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Bartın İli (Türkiye’nin Kuzeyi) Karasal Alanlarının Doğallık Düzeyi

Year 2025, Volume: 10 Issue: 3, 292 - 300, 30.05.2025

Celalettin Duran

https://doi.org/10.35229/jaes.1659880

Abstract

Karasal ekosistemlerin doğallık düzeyini, insan etkisine maruz kalma derecesi belirler. Yüksek doğallık düzeyi, düşük insan etkisini ve yüksek biyolojik çeşitliliği yansıtır. Karasal ekosistemlerin doğallık düzeyinin belirlenmesi, uzun vadeli arazi planlaması ve korunması, sürdürülebilirlik ve kaynak yönetimi açısından son derece önemlidir. Bu çalışmada, Bartın ili idari sınırları içindeki doğal/antropojen alanların doğallık düzeyi incelenmiştir. Altı mekânsal faktör kullanılmıştır. Bunlar, yerleşim yeri yoğunluğu, nüfus yoğunluğu, yol yoğunluğu, arazi örtüsü/kullanımı, Normalize Edilmiş Fark Bitki Örtüsü İndeksi (NDVI) ve Topoğrafik Pürüzlülük İndeksidir (TRI). Bu altı temel faktör, Coğrafi Bilgi Sistemleri (CBS) kullanılarak mekânsal bulanık üyeliklere dönüştürülmüştür. Sonuç haritası, bulanık üyelerin fuzzy overlay modelinde (FOM) üst üste çakıştırılmasıyla elde edilmiştir. Ortaya çıkan bu haritaya göre, kent merkezi ve çevresi yüksek antropojenik etkiye ve düşük doğallık düzeyine sahiptir. İlin doğusundaki Kure Dağları Milli Parkı (KMNP) ve güneyindeki engebeli dağ sıraları, antropojenik etkiden uzak olmaları nedeniyle yüksek bir doğallığa sahiptir. Antropojenik arazi bozulması, yol yapımı, madencilik ve ormancılık faaliyetleri nedeniyle genişlemiştir. Kontrolsüz ekonomik faaliyetler, insan kaynaklı bozulmanın potansiyel alanlarını oluşturur.

Keywords

Bartın Bozulma Bulanık Çakıştırma Haritalama Doğallık Düzeyi.

References

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  • Angermeier, P.L. (2000). The natural imperative for biological conservation. Conservation Biology, 14, 373-381.
  • Atalay, İ. (2022). A look at the impact of the natural environment on archaeology and the settlements and cultures of ancient societies, Avrasya Beşeri Bilim Araştırmaları Dergisi, 2(1), 1-32.
  • Baidya, P., Chutia, D., Sudhakar, S., Goswami, C., Goswami, J., Saikhom, V., ... & Sarma, K.K. (2014). Effectiveness of Fuzzy Overlay Function for Multi-Criteria Spatial Modeling-A Case Study on Preparation of Land Resources Map for Mawsynram Block of East Khasi Hills District of Meghalaya, India. Journal of Geographic Information System, 6, 605-612.
  • Carver, S., Tricker, J., & Landres, P., (2013). Keeping it wild: Mapping wilderness character in the United States. J. Environ. Manage. 131, 239-255.
  • Çakıt, E., & Karwowski, W. (2018). A fuzzy overlay model for mapping adverse event risk in an active war theatre, Journal of Experimental & Theoretical Artificial. 30, 691-701, DOI: /10.1080/0952813X.2018.1467494
  • De Jong, L., De Bruin, S., Knoop, J., & Van Vliet, J. (2021). Understanding land-use change conflict: a systematic review of case studies. Journal of Land Use Science, 16(3), 223-239. DOI: 10.1080/1747423X.2021.1933226
  • De Keersmaecker, W., Miralles, D.G., Peñuelas, J., & Veroustraete, F. (2023). Long-term NDVI trends and their drivers in drylands: A meta-analysis. Remote Sensing of Environment, 296, 113732. DOI: 10.1016/j.rse.2023.113732
  • Duran, C., & Günek, H., (2007). Hazar gölü havzası arazi kullanımındaki değişikliklerin belirlenmesi (1956- 2004), Fırat Üniversitesi Sosyal Bilimler Dergisi, 17(2), 31-52.
  • Duran, C. (2024). Spatial Distribution of Natural and Anthropogenic Areas in Kastamonu Province (Northern Turkiye), 7th International Anatolian Agriculture, Food, Environment and Biology Congress, Kastamonu/Türkiye
  • Ellis, E.C. (2015). Ecology in an anthropogenic biosphere. Ecological Monographs, 85, 287-331. DOI: 10.1890/14-2274.1
  • Ellis, E.C. (2021). Land Use and Ecological Change: A 12,000-Year History. Annual Review of Environment and Resources, 46, 1-33. DOI: 10.1146/annurev-environ-012220-010822
  • Ekim, B., Dong, Z., Rashkovetsky, D., & Schmitt, M. (2021). The naturalness index for the identification of natural areas on a regional scale, International Journal of Applied Earth Observation and Geoinformation, 105, 102622, ISSN 1569-8432, DOI: 10.1016/j.jag.2021.102622
  • Fahrig, L., & Rytwinski, T. (2009). Effects of roads on animal abundance: An empirical review and synthesis. Ecology and Society, 14(1), 21. http://www.ecologyandsociety.org/vol14/iss1/art 21/
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  • Foley, J.A., DeFries, R., Asner, G.P., Barford, C., Bonan, G., Carpenter, S.R., Chapin, F.S., III, Coe, M.T., Daily, G.C., Gibbs, H.K., Helkowski, J.H., Holloway, T., Howard, E.A., Kucharik, C.J., Monfreda, C., Patz, J.A., Prentice, I.C., Ramankutty, N., & Snyder, P.K. (2005). Global consequences of land use. Science, 309(5734), 570-574. DOI: 10.1126/science.1111772
  • Goward, S.N., Markham, B., Dye, D.G., Dulaney, W., & Yang, J. (1994). Normalized difference vegetation index (NDVI) of the terrestrial biosphere. BioScience, 44(10), 692-703.
  • Grilo, C., Bissonette, J.A., & Santos-Reis, M. (2021). Effects of road traffic noise on wildlife: A meta- analysis. Environmental Pollution, 289, 117913. DOI: 10.1016/j.envpol.2021.117913
  • Lambin, E.F., & Ehrlich, D. (1997). Land-cover change and its drivers in the tropics. Annals of the New York Academy of Sciences, 823(1), 179-196.
  • Lambin, E. F. et al (2001). The causes of land-use and land-cover change: moving beyond the myths. Global Environmental Change, 11(4), 261-269. ISSN 0959-3780, DOI: 10.1016/S0959- 3780(01)00007-3
  • Kainz, W. (2007). Fuzzy Logic in Geography. In Fotheringham, A. S., & Rogerson, P. A. (Eds.), The SAGE Handbook of Quantitative Geography (pp. 227-246). SAGE Publications Ltd.
  • Karra, Kontgis, et al. (2021). “Global land use/land cover with Sentinel-2 and deep learning.” IGARSS 2021-2021 IEEE International Geoscience and Remote Sensing Symposium. IEEE,
  • McKinney, M.L. (2002). Urbanization, biodiversity, and conservation. BioScience, 52(10), 883-890.
  • Morelli, T.L., Barrows, C.W., Ramirez, A.R., Cartwright, J.M., Ackerly, D. D., … & Thorne, J. H.(2020). Climate‐change refugia: biodiversity in the slow lane. Frontiers in Ecology and the Environment, 18(5), 225-308. DOI: 10.1002/fee.2189
  • Newbold, T., Hudson, L.N., Hill, S.L., Contu, S., Lysenko, I., Senior, R.A., ... & Purvis, A. (2015). Global effects of land use on local terrestrial biodiversity. Nature, 520(7545), 45-50.
  • Potapov, P., Hansen, M.C., Laestadius, L., Turubanova, S., Yaroshenko, A., Thies, C., Smith, W., Zhuravleva, I., Komarova, A., Minnemeyer, S., & Esipova, E. (2017). The last frontiers of wilderness: Tracking the loss of intact forest landscapes from 2000 to 2013. Sci. Adv., 3(1), e1600821.
  • Povilitis, T. (2002). What is a natural area? Natural Areas Journal 21, 70-74.
  • Reba, M., Reitsma, F., & Seto, K.C. (2016). Spatializing 6,000 years of global urbanization from 3700 BC to AD 2000. Sci. Data, 3, 160034
  • Rosa, I.M.D. et al. (2023). Future scenarios of global biodiversity and their implications for conservation. Nature Communications, 14(1), 1- 12.
  • Sala, O.E., Chapin, F.S., III, Armesto, J.J., Berlow, E., Bloomfield, J., Dirzo, R., Huber-Sanwald, E., Huenneke, L.F., Jackson, R.B., Jaksic, F. M., Leemans, R., Loreau, M., Mooney, H.A., Oesterheld, M., Poff, N.L., Sykes, M.T., Walker, B.H., Walker, M., & Wall, D.H. (2000). Global biodiversity scenarios for the year 2100. Science, 287(5453), 1770-1774. DOI: 10.1126/science.287.5459.1770
  • Seto, K. C., Güneralp, B., & Hutyra, L. R. (2012). Global forecasts of urban expansion to 2030 and direct impacts on biodiversity and carbon pools. Proceedings of the National Academy of Sciences, 109(40), 16037-16042. DOI: 10.1073/pnas.1211658109
  • Stambaugh, M.C., & Guyette, R.P. (2008). Predicting spatio-temporal variability in fire return intervals using a topographic roughness index. Forest Ecology and Management, 254(3), 463-473, ISSN 0378-1127, DOI: 10.1016/j.foreco.2007.08.029
  • Şen, G., & Erkan Buğday, S. (2015). Kastamonu İlinde Çeşitli Statülerde Koruma ve Kullanma Amaçlı Belirlenmiş Alanlar. Kastamonu University Journal of Forestry Faculty, 15(2), 214-230. DOI: 10.17475/kuofd.62142
  • Tennakoon, S., Apan, A., Maraseni, T., & Altarez, R. D.D. (2023). Decoding the impacts of space and time on honey bees: GIS-based fuzzy AHP and fuzzy overlay to assess land suitability for apiary sites in Queensland, Australia, Applied Geography, 155, 102951, ISSN 0143-6228, DOI: 10.1016/j.apgeog.2023.102951
  • Tunçkol, B., Aksoy, N., & Haşayacak, H. (2020). Classification of Endemic Plants and Priority Conservation Areas in Küre Mountains National Park (Kastamonu Section). Düzce Üniversitesi Orman Fakültesi Ormancılık Dergisi, 16(2), 148- 160.
  • Turoğlu, H., & Özdemir, H. (2005). Determination of Ecotourism Potential in Bartın City. Dogu Cografya Dergisi, 10 (13), 97-116.
  • Wang, J., Xu, C., & Pausas, J.G. (2021). Quantifying the relative roles of climate change and human activities in vegetation greening across China. Ecological Indicators, 121, 107014. DOI: 10.1016/j.ecolind.2020.107014
  • Wildlife Conservation Society-WCS, & Center For International Earth Science Information Network-CIESIN-Columbia University. (2005). Last of the Wild Project, Version 2, 2005 (LWP-2): Global Human Footprint Dataset (Geographic) (Version 2.00) [Data set]. Palisades, NY: NASA Socioeconomic Data and Applications Center (SEDAC). DOI: 10.7927/H4M61H5F

The Naturalness Level of Terrestrial Areas in Bartin Province (Northern Türkiye)

Year 2025, Volume: 10 Issue: 3, 292 - 300, 30.05.2025

Celalettin Duran

https://doi.org/10.35229/jaes.1659880

Abstract

The level of naturalness of terrestrial ecosystems is the degree to which they are exposed to human influence. The high level of naturalness reflects low human impact and high biodiversity. Determining the level of naturalness of terrestrial ecosystems is extremely important for long-term land planning and conservation, sustainability, and resource management. This study examined the naturalness level of natural/anthropogenic areas within the administrative borders of Bartin province. Six spatial factors were used. These are settlement density, population density, road density, land cover/use, Normalized Difference Vegetation Index (NDVI), and Topographic Roughness Index (TRI). These six essential factors were inverted into the spatial fuzzy memberships using Geographic Information Systems (GIS). A final map was obtained by overlaying the fuzzy memberships in the fuzzy overlay model (FOM). According to this resulting map, the city center and its surroundings have a high anthropogenic impact and a low level of naturalness. The Kure Mountains National Park (KMNP) in the east of the province and the rugged mountain ranges in the south have a high level of naturalness, being remote from anthropogenic impact. Anthropogenic land degradation has expanded due to road construction, mining, and forestry activities. Uncontrolled economic activities constitute potential areas of human-induced degradation.

Keywords

Bartin Degradation Fuzzy overlay Mapping The level of naturalness.

References

  • Altunel, A.O., Çağlar, S., & Açıkgöz Altunel, T. (2021). Determining the habitat fragmentation thru geoscience capabilities in Turkey: A case study of wildlife refuges. International Journal of Engineering and Geosciences, 6(2), 104-116. DOI: 10.26833/ijeg.712549
  • Angermeier, P.L. (2000). The natural imperative for biological conservation. Conservation Biology, 14, 373-381.
  • Atalay, İ. (2022). A look at the impact of the natural environment on archaeology and the settlements and cultures of ancient societies, Avrasya Beşeri Bilim Araştırmaları Dergisi, 2(1), 1-32.
  • Baidya, P., Chutia, D., Sudhakar, S., Goswami, C., Goswami, J., Saikhom, V., ... & Sarma, K.K. (2014). Effectiveness of Fuzzy Overlay Function for Multi-Criteria Spatial Modeling-A Case Study on Preparation of Land Resources Map for Mawsynram Block of East Khasi Hills District of Meghalaya, India. Journal of Geographic Information System, 6, 605-612.
  • Carver, S., Tricker, J., & Landres, P., (2013). Keeping it wild: Mapping wilderness character in the United States. J. Environ. Manage. 131, 239-255.
  • Çakıt, E., & Karwowski, W. (2018). A fuzzy overlay model for mapping adverse event risk in an active war theatre, Journal of Experimental & Theoretical Artificial. 30, 691-701, DOI: /10.1080/0952813X.2018.1467494
  • De Jong, L., De Bruin, S., Knoop, J., & Van Vliet, J. (2021). Understanding land-use change conflict: a systematic review of case studies. Journal of Land Use Science, 16(3), 223-239. DOI: 10.1080/1747423X.2021.1933226
  • De Keersmaecker, W., Miralles, D.G., Peñuelas, J., & Veroustraete, F. (2023). Long-term NDVI trends and their drivers in drylands: A meta-analysis. Remote Sensing of Environment, 296, 113732. DOI: 10.1016/j.rse.2023.113732
  • Duran, C., & Günek, H., (2007). Hazar gölü havzası arazi kullanımındaki değişikliklerin belirlenmesi (1956- 2004), Fırat Üniversitesi Sosyal Bilimler Dergisi, 17(2), 31-52.
  • Duran, C. (2024). Spatial Distribution of Natural and Anthropogenic Areas in Kastamonu Province (Northern Turkiye), 7th International Anatolian Agriculture, Food, Environment and Biology Congress, Kastamonu/Türkiye
  • Ellis, E.C. (2015). Ecology in an anthropogenic biosphere. Ecological Monographs, 85, 287-331. DOI: 10.1890/14-2274.1
  • Ellis, E.C. (2021). Land Use and Ecological Change: A 12,000-Year History. Annual Review of Environment and Resources, 46, 1-33. DOI: 10.1146/annurev-environ-012220-010822
  • Ekim, B., Dong, Z., Rashkovetsky, D., & Schmitt, M. (2021). The naturalness index for the identification of natural areas on a regional scale, International Journal of Applied Earth Observation and Geoinformation, 105, 102622, ISSN 1569-8432, DOI: 10.1016/j.jag.2021.102622
  • Fahrig, L., & Rytwinski, T. (2009). Effects of roads on animal abundance: An empirical review and synthesis. Ecology and Society, 14(1), 21. http://www.ecologyandsociety.org/vol14/iss1/art 21/
  • FAO. (2024). https://openknowledge.fao.org/server/api/core/bit streams/bc8810ae-2a13-4cfe-b019- 339158c7e608/content/src/html/chapter-1- 2.html, 01.05.2024
  • Findell, K.L., Berg, A., Gentine, P., Krasting, J.P., Lintner, B.R., Malyshev, S., Santanello, Jr.J.A., & Shevliakova, E. (2017). The impact of anthropogenic land use and land cover change on regional climate extremes. Nature Communications 8, 989 DOI: 10.1038/s41467- 017-01038-w
  • Foley, J.A., DeFries, R., Asner, G.P., Barford, C., Bonan, G., Carpenter, S.R., Chapin, F.S., III, Coe, M.T., Daily, G.C., Gibbs, H.K., Helkowski, J.H., Holloway, T., Howard, E.A., Kucharik, C.J., Monfreda, C., Patz, J.A., Prentice, I.C., Ramankutty, N., & Snyder, P.K. (2005). Global consequences of land use. Science, 309(5734), 570-574. DOI: 10.1126/science.1111772
  • Goward, S.N., Markham, B., Dye, D.G., Dulaney, W., & Yang, J. (1994). Normalized difference vegetation index (NDVI) of the terrestrial biosphere. BioScience, 44(10), 692-703.
  • Grilo, C., Bissonette, J.A., & Santos-Reis, M. (2021). Effects of road traffic noise on wildlife: A meta- analysis. Environmental Pollution, 289, 117913. DOI: 10.1016/j.envpol.2021.117913
  • Lambin, E.F., & Ehrlich, D. (1997). Land-cover change and its drivers in the tropics. Annals of the New York Academy of Sciences, 823(1), 179-196.
  • Lambin, E. F. et al (2001). The causes of land-use and land-cover change: moving beyond the myths. Global Environmental Change, 11(4), 261-269. ISSN 0959-3780, DOI: 10.1016/S0959- 3780(01)00007-3
  • Kainz, W. (2007). Fuzzy Logic in Geography. In Fotheringham, A. S., & Rogerson, P. A. (Eds.), The SAGE Handbook of Quantitative Geography (pp. 227-246). SAGE Publications Ltd.
  • Karra, Kontgis, et al. (2021). “Global land use/land cover with Sentinel-2 and deep learning.” IGARSS 2021-2021 IEEE International Geoscience and Remote Sensing Symposium. IEEE,
  • McKinney, M.L. (2002). Urbanization, biodiversity, and conservation. BioScience, 52(10), 883-890.
  • Morelli, T.L., Barrows, C.W., Ramirez, A.R., Cartwright, J.M., Ackerly, D. D., … & Thorne, J. H.(2020). Climate‐change refugia: biodiversity in the slow lane. Frontiers in Ecology and the Environment, 18(5), 225-308. DOI: 10.1002/fee.2189
  • Newbold, T., Hudson, L.N., Hill, S.L., Contu, S., Lysenko, I., Senior, R.A., ... & Purvis, A. (2015). Global effects of land use on local terrestrial biodiversity. Nature, 520(7545), 45-50.
  • Potapov, P., Hansen, M.C., Laestadius, L., Turubanova, S., Yaroshenko, A., Thies, C., Smith, W., Zhuravleva, I., Komarova, A., Minnemeyer, S., & Esipova, E. (2017). The last frontiers of wilderness: Tracking the loss of intact forest landscapes from 2000 to 2013. Sci. Adv., 3(1), e1600821.
  • Povilitis, T. (2002). What is a natural area? Natural Areas Journal 21, 70-74.
  • Reba, M., Reitsma, F., & Seto, K.C. (2016). Spatializing 6,000 years of global urbanization from 3700 BC to AD 2000. Sci. Data, 3, 160034
  • Rosa, I.M.D. et al. (2023). Future scenarios of global biodiversity and their implications for conservation. Nature Communications, 14(1), 1- 12.
  • Sala, O.E., Chapin, F.S., III, Armesto, J.J., Berlow, E., Bloomfield, J., Dirzo, R., Huber-Sanwald, E., Huenneke, L.F., Jackson, R.B., Jaksic, F. M., Leemans, R., Loreau, M., Mooney, H.A., Oesterheld, M., Poff, N.L., Sykes, M.T., Walker, B.H., Walker, M., & Wall, D.H. (2000). Global biodiversity scenarios for the year 2100. Science, 287(5453), 1770-1774. DOI: 10.1126/science.287.5459.1770
  • Seto, K. C., Güneralp, B., & Hutyra, L. R. (2012). Global forecasts of urban expansion to 2030 and direct impacts on biodiversity and carbon pools. Proceedings of the National Academy of Sciences, 109(40), 16037-16042. DOI: 10.1073/pnas.1211658109
  • Stambaugh, M.C., & Guyette, R.P. (2008). Predicting spatio-temporal variability in fire return intervals using a topographic roughness index. Forest Ecology and Management, 254(3), 463-473, ISSN 0378-1127, DOI: 10.1016/j.foreco.2007.08.029
  • Şen, G., & Erkan Buğday, S. (2015). Kastamonu İlinde Çeşitli Statülerde Koruma ve Kullanma Amaçlı Belirlenmiş Alanlar. Kastamonu University Journal of Forestry Faculty, 15(2), 214-230. DOI: 10.17475/kuofd.62142
  • Tennakoon, S., Apan, A., Maraseni, T., & Altarez, R. D.D. (2023). Decoding the impacts of space and time on honey bees: GIS-based fuzzy AHP and fuzzy overlay to assess land suitability for apiary sites in Queensland, Australia, Applied Geography, 155, 102951, ISSN 0143-6228, DOI: 10.1016/j.apgeog.2023.102951
  • Tunçkol, B., Aksoy, N., & Haşayacak, H. (2020). Classification of Endemic Plants and Priority Conservation Areas in Küre Mountains National Park (Kastamonu Section). Düzce Üniversitesi Orman Fakültesi Ormancılık Dergisi, 16(2), 148- 160.
  • Turoğlu, H., & Özdemir, H. (2005). Determination of Ecotourism Potential in Bartın City. Dogu Cografya Dergisi, 10 (13), 97-116.
  • Wang, J., Xu, C., & Pausas, J.G. (2021). Quantifying the relative roles of climate change and human activities in vegetation greening across China. Ecological Indicators, 121, 107014. DOI: 10.1016/j.ecolind.2020.107014
  • Wildlife Conservation Society-WCS, & Center For International Earth Science Information Network-CIESIN-Columbia University. (2005). Last of the Wild Project, Version 2, 2005 (LWP-2): Global Human Footprint Dataset (Geographic) (Version 2.00) [Data set]. Palisades, NY: NASA Socioeconomic Data and Applications Center (SEDAC). DOI: 10.7927/H4M61H5F
There are 39 citations in total.

Details

Primary Language English
Subjects Natural Resource Management
Journal Section Articles
Authors

Celalettin Duran 0000-0002-6864-5564

Early Pub Date May 24, 2025
Publication Date May 30, 2025
Submission Date March 18, 2025
Acceptance Date May 5, 2025
Published in Issue Year 2025 Volume: 10 Issue: 3

Cite

APA Duran, C. (2025). The Naturalness Level of Terrestrial Areas in Bartin Province (Northern Türkiye). Journal of Anatolian Environmental and Animal Sciences, 10(3), 292-300. https://doi.org/10.35229/jaes.1659880
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