Zıtlığa dayalı kenar yoğunluk indeksi kullanılarak arazinin mekânsal heterojenliğindeki zamansal değişimin haritalanması

Yıl 2018, Cilt: 19 Sayı: 4, 355 - 361, 30.12.2018

Özdemir Şentürk İbrahim Özdemir

https://doi.org/10.18182/tjf.487107

Öz

Bu çalışmanın amacı, Akdeniz Bölgesi’ndeki kızılçam (Pinus brutia Ten.) ormanlarında son 40 yılda meydana gelen yapısal heterojenliğin zamansal değişimlerini haritalamak ve analiz etmektedir. Değişikliklerin tespit edilmesinde 1966 ve 2006 yıllarına ait meşcere tipleri haritaları esas alınmıştır. Arazinin yapısal heterojenliğini ölçmek için Zıtlığa Dayalı Kenar Yoğunluk İndeksi (CWEDI) kullanılmıştır. Çalışma alanı 500 x 500 m grid hücrelere bölünmüş ve daha sonra her hücre için bir CWEDI değeri hesaplanmıştır. Zamansal farklılıklar, 2006 yılındaki heterojenlik haritasındaki hücre değerlerinin 1966 yılı haritasındaki hücre değerlerinden çıkarılmasıyla elde edilmiştir. Elde edilen haritada, bölgenin %24'ünde meydana gelen değişikliklerin (2364.93 ha) yönetim faaliyetlerinden kaynaklandığı görülmüştür. Çalışma alanının geriye kalan kısmında (7471.75 ha) meydana gelen değişiklikler, meşcerelerdeki doğal büyüme ya da iki zaman ölçüm zamanı arasındaki foto-yorum farkları gibi yönetim faaliyetleri dışındaki diğer faktörlerden kaynaklanmıştır. Çalışma, eski planların, doğal kenarları azaltarak, farklı yaşlı kızılçam meşcereleri arasındaki yapay kenarları desteklediğini göstermektedir. Odun üretimi odaklı yönetim planlarının meydana getirdiği parçalar, kenarda yaşayan türleri olumlu yönde etkilesede kenara duyarlı türleri olumsuz etkileyebilir. Sonuç olarak, kızılçam ormanlardaki odun üretimi ve odun dışı orman ürünleri arasında iyi bir denge sağlamak için biyoçeşitlilik dostu bir orman yönetimi stratejisi geliştirilmelidir.

Anahtar Kelimeler

Kenar, Kızılçam, Yama, Zıtlığa dayalı kenar yoğunluk indeksi

Mapping temporal changes in landscape spatial heterogeneity using the contrast weighted edge density index

Öz

The aim of this study is to map and analyze the temporal changes in the landscape structural heterogeneity over the past 40 years in a brutian pine (Pinus brutia Ten.) dominated forest area in the Mediterranean region of Turkey. The change detection analysis was done based on two forest stand maps belonging to 1966 and 2006 years. We used the Contrast Weighted Edge Density Index (CWEDI) for quantifying landscape structural heterogeneity. The study area was converted to 500 x 500 m grid cells and then a CWEDI value was calculated for each cell. The temporal differences were determined by subtracting the cell values in the heterogeneity map of 2006 year from the corresponding cell values in the map of 1966 year. In the change map, we perceived that the changes in 24% of the area (2364.93 ha) resulted from the management activities. The changes in the rest of study area (7471.75 ha) might occur due to other factors except management activities such as the natural growth in the stands or the photo-interpretation differences between the two measurement times. The study results show that the even-aged management has promoted the artificial edges between brutian pine stands with different ages while it has reduced the natural edges. Although the patchiness generated by the wood-oriented management may positively affect edge-dwelling species, it may have negatively influences on edge-sensitive species. As a result, a biodiversity-friendly forest management strategy should be developed to maintain a good balance between wood production and non-wood forest values in the brutian forests.

Anahtar Kelimeler

Edge, Brutian pine, Patch, Contrast weighted edge density index

Kaynakça

• Cardinal, E., Martin, J.L., Tremblay, J.P., Côté, S. D., 2012. An experimental study of how variation in deer density affects vegetation and songbird assemblages of recently harvested boreal forests. Canadian Journal of Zoology, 90(6): 704-713.
• Crooks, K.R., Burdett, C.L., Theobald, D.M., Rondinini, C., Boitani, L., 2011. Global patterns of fragmentation and connectivity of mammalian carnivore habitat. Philosophical Transactions of the Royal Society B: Biological Sciences, 366(1578): 2642-2651.
• De Groot, R.S., Alkemade, R., Braat, L., Hein, L., Willemen, L., 2010. Challenges in integrating the concept of ecosystem services and values in landscape planning, management and decision making. Ecological complexity, 7(3): 260-272.
• Drummond, M.A., Loveland, T.R., 2010. Land-use pressure and a transition to forest-cover loss in the eastern United States. BioScience, 60(4): 286-298.
• Fahrig, L., Baudry, J., Brotons, L., Burel, F.G., Crist, T.O., Fuller, R.J., Sirami, C., Siriwardena, G.M., Martin, J.L., 2011. Functional landscape heterogeneity and animal biodiversity in agricultural landscapes. Ecology letters, 14(2): 101-112.
• GDF, 2013. Forest Atlas. Republic of Turkey Ministry of Forestry And Water Affairs, Genaral Directorate of Forestry. http://www.ogm.gov.tr/ekutuphane/Yayinlar/Orman%20Atlasi.pdf. Accessed: 11.12.2018.
• Hansson, L., Fahrig, L., Merriam, G., (Eds.) 2012. Mosaic landscapes and ecological processes. Springer Science & Business Media.
• Kamieniarz, R., Voigt, U., Panek, M., Strauss, E., Niewęgłowski, H., 2013. The effect of landscape structure on the distribution of brown hare Lepus europaeus in farmlands of Germany and Poland. Acta theriologica, 58(1): 39-46. Kelly, M., Tuxen, K.A., Stralberg, D., 2011. Mapping changes to vegetation pattern in a restoring wetland: Finding pattern metrics that are consistent across spatial scale and time. Ecological Indicators, 11(2): 263-273.
• Lausch, A., Blaschke, T., Haase, D., Herzog, F., Syrbe, R.U., Tischendorf, L., Walz, U., 2015. Understanding and quantifying landscape structure–A review on relevant process characteristics, data models and landscape metrics. Ecological Modelling, 295: 31-41.
• Lindenmayer, D.B., Franklin, J.F., Lõhmus, A., Baker, S.C., Bauhus, J., Beese, W., Brodie, A., Kiehl, B., Kouki, J., Martínez Pastur, G., Messier, C., Neyland, M., Palik, B., Sverdrup‐Thygeson, A., Volney, J., Wayne, A., Gustafsson, L., 2012. A major shift to the retention approach for forestry can help resolve some global forest sustainability issues. Conservation Letters, 5(6): 421-431.
• Matte, A.L.L., Müller, S.C., Becker, F.G., 2015. Forest expansion or fragmentation? Discriminating forest fragments from natural forest patches through patch structure and spatial context metrics. Austral Ecology, 40(1): 21-31.
• Mert, A., Yalcinkaya, B., 2016. The relation of edge effect on some wild mammals in Burdur-Ağlasun (Turkey) district. Biological Diversity and Conservation, 9(2): 193-201.
• Mert, A., Yalcinkaya, B., 2017. Relationship between some wild mammals and forest structural diversity parameters. Journal of Environmental Biology, 38(5): 879-884.
• McGarigal, K., Cushman S. A., Neel, M. C. and Ene, E., 2002. FRAGSTATS: Spatial Pattern Analysis Program for Categorical Maps. Computer software program produced by the authors at the University of Massachusetts, Amherst. http://www.umass.edu/landeco/research/fragstats/fragstats.html. Accessed: 20.10.2018.
• McGarigal, K., 2001. Landscape Metrics for Categorical Map Patterns, Lecture Notes. http://www.umass.edu /landeco/teaching/landscape_ecology/schedule/chapter9_metrics.pdf. Accessed: 24.10.2018.
• Morrison, J. A., Lubchansky, H. A., Mauck, K. E., McCartney, K. M., Dunn, B., 2007. Ecological comparison of two co-invasive species in eastern deciduous forests: Alliaria petiolata and Microstegium vimineum. The Journal of the Torrey Botanical Society, 134(1): 1-17.
• Ode, Å., Hagerhall, C. M., Sang, N., 2010. Analysing visual landscape complexity: Theory and application. Landscape Research, 35(1): 111-131.
• Paillet, Y., Bergès, L., Hjältén, J., Ódor, P., Avon, C., Bernhardt‐Römermann, Bijlsma, R., Bruyn, L., Fuhr, M., Grandın, U., Kanka, R., Lundin, L., Luque, S., Magura, T., Matesanz, S., Mészáros, I., Sebastià, M., Schmidt, W., Standovár, T., Tóthmérész, B., Uotila, A., Valladares, F., Vellak, K., Virtanen, R., 2010. Biodiversity differences between managed and unmanaged forests: meta‐analysis of species richness in Europe. Conservation biology, 24(1): 101-112. Plexida, S. G., Sfougaris, A. I., Ispikoudis, I. P., Papanastasis, V. P., 2014. Selecting landscape metrics as indicators of spatial heterogeneity-A comparison among Greek landscapes. International Journal of Applied Earth Observation and Geoinformation, 26: 26-35.
• Ries, L., Sisk, T. D., 2010. What is an edge species? The implications of sensitivity to habitat edges. Oikos, 119(10): 1636-1642.
• Šálek, M., Kreisinger, J., Sedláček, F., Albrecht, T., 2010. Do prey densities determine preferences of mammalian predators for habitat edges in an agricultural landscape? Landscape and Urban Planning, 98(2): 86-91.
• Šímová, P., Gdulová, K., 2012. Landscape indices behavior: a review of scale effects. Applied geography, 34:385-394.
• Tscharntke, T., Tylianakis, J. M., Rand, T. A., Didham, R. K., Fahrig, L., Batary, P., Bengtsson, J., Clough, Y., Crist, O.T., Dormann, F. C., Ewers, R. M., Fründ, J., Holt, R. D., Holzschuh, A., Klein, A. M., Kleijn, D., Kremen, C., Landis, D. A., Laurance, W., Lindenmayer, D., Scherber, C., Sodhi, N., Steffan‐Dewenter, I., Thies, C., van der Putten, W. H., Westphal, C., 2012. Landscape moderation of biodiversity patterns and processes‐eight hypotheses. Biological Reviews, 87(3): 661-685.