Anthropogenic climate change is increasingly reshaping settlement patterns through rising temperatures and declining bioclimatic comfort, particularly in climatevulnerable regions such as the Mediterranean Basin. Climate pressures often shape internal and gradual mobility rather than longdistance migration. In Türkiye, intensified thermal stress in coastal cities is creating new adaptation pathways linked to elevation. In this context, climate information products, including bioclimatic comfort assessments and climate projections, can provide valuable evidence for understanding emerging mobility responses and supporting climate adaptation planning.This study examines vertical residential mobility from coastal urban areas toward higher-altitude yayla settlements as an emerging, localized form of climate adaptation in Antalya. Adopting a mixedmethods approach, the research integrates bioclimatic comfort analyses, climate projections, landuse and land surface temperature analyses, and semistructured in-depth interviews. The findings reveal a persistent and intensifying thermal differentiation between coastal and highland areas, functioning as a thermal spatial threshold that influences settlement preferences and residential decisions. While yaylas continue to offer relative thermal relief, climate projections indicate continued warming across all elevation zones toward 2100. Qualitative findings show that declining urban comfort, health concerns, and seasonal heat stress are primary drivers of elevationbased residential mobility, while traditional yayla practices are increasingly being transformed into more permanent forms of residence. At the same time, access to vertical residential mobility remains uneven and is increasingly shaped by socioeconomic resources, housing availability, and infrastructure conditions.The study argues that climateinfluenced mobility should be understood not as a direct or crisisdriven outcome of environmental change, but as a socially differentiated and context-dependent adaptation process. Interview findings indicate that changing thermal comfort conditions are influencing residential preferences and contributing to the functional transformation of yayla settlements from seasonal and recreational spaces toward more permanent residential environments. The results further suggest that PETbased bioclimatic comfort assessments, climate projections, and locally grounded evidence derived from household interviews can serve as climate information products that support adaptationoriented decisionmaking by households, planners, and local authorities. By foregrounding vertical residential mobility and bioclimatic comfort as key mechanisms, the study contributes to ongoing discussions on climate adaptation, internal mobility, and the role of climate information in responding to environmental change in climatevulnerable regions.

The western and southern regions of Türkiye are strongly influenced by the Mediterranean thermal regime during the summer season, with prolonged summer drought representing one of the defining characteristics of the Mediterranean climate. Over the last decade, both the frequency and intensity of drought and extreme heat events have increased. In particular, the summer of 2025 was drier than long-term climatological normals. At the same time, increasing influence of climate change has intensified the frequency and severity of compound climatic extremes, substantially increasing wildfire risk, within climate transition zones. Under these exceptionally hot and dry atmospheric conditions, environmental settings became highly favorable for wildfire ignition and rapid-fire spread, such that even minor physical or anthropogenic disturbances were sufficient to trigger wildfire. This study investigates the relationship between compound climatic extremes and large-scale 2025 wildfires in Sakarya. Meteorological analyses were conducted using long-term daily temperature, relative humidity, wind speed, and precipitation. Heatwave characteristics were evaluated using the HWN, HWDx, and HWMn indices, while drought were assessed using the SPI. In addition, Sentinel-2 images and GEE platform were employed to evaluate post-fire vegetation damage and burn severity through dNDVI, dNDMI, and dNBR indices. The findings reveal that fire days were strongly associated with compound extreme conditions characterized by above-threshold maximum temperatures and low relative humidity. Prolonged drought observed during pre-fire period further intensified fuel dryness and wildfire susceptibility. Remote sensing analyses indicate that substantial reductions in vegetation density, moisture content, and ecosystem functionality within burned areas. In conclusion, satellite-based dNBR analyses indicate that approximately 20,000 hectares of land were affected by the 2025 wildfires in Sakarya. The findings demonstrate that these wildfire events were associated not with a single meteorological factor alone, but rather with the interaction of heatwaves, prolonged drought and compound hot–dry atmospheric processes. These results clearly indicate that climate change has become an increasingly important factor in the occurrence and spread of wildfires, particularly within climate transition zones. The study provides important scientific evidence for improving wildfire early warning systems, strengthening regional climate adaptation policies, and developing sustainable wildfire management strategies under future climate change scenarios.

Understanding the dynamics between past global climate events and their impact on marine ecosystems and paleoclimate is essential for the estimation of potential future changes. Accordingly, sedimentary archives accumulating on the seafloor provide crucial information on climate-driven environmental variability during the late Quaternary. Sediment cores were taken from the Gulf of Edremit, which is located in the northern Aegean Sea. We aimed to provide a preliminary, multi-proxy parameters, including sedimentological and geochemical records during the Holocene. During the marine survey with the R/V TÜBİTAK MARMARA Research Vessel, three sediment cores (E-01, E-02, and E-03A) obtained from different water depths across the gulf were investigated. Lithological observations from all cores indicate a sedimentation pattern dominated by fine-grained clay- and silt-sized deposits. However, locally occurring black laminae and FeS bands reflect depositional conditions sensitive to variations in bottom-water oxygenation. Fluctuations in the density and magnetic susceptibility measured by MSCL further support variability in sediment input and depositional processes at the sea floor. TOC data from core E-02 (at a water depth of 86 m) show low values (0.8–1.0 wt%) in the lower part, indicating low productivity and/or poor preservation of organic matter. TOC then rises to ~1.0–1.5 wt% further up the core, suggesting improved productivity or preservation. The highest values (1.5–2.0 wt%) in the uppermost 0–10 cm may reflect the presence of sapropelic material. XRF data from core E-03A reveal a Sr/Ca peak at 40–50 cm, which indicates increased salinity during drier periods. At 140–150 cm, the Sr/Ca ratio decreases while the Ca/Ti ratio increases, suggesting enhanced carbonate deposition relative to detrital input. In core E-01, a Mn/Fe peak at 10–15 cm reflects changes in redox and oxygen conditions. There is strong variability in Ca/Ti and Sr/Ca at 45–50 cm: higher Sr/Ca above this depth indicates greater carbonate production, while lower Ca/Ti implies reduced clastic input. Below 65 cm, falling Sr/Ca and rising Ca/Ti suggest diminished carbonate production and a return to lithogenic dominance. As a conclusion, sedimentation in the Gulf of Edremit appears to be highly sensitive to climate and carbon cycle changes.This study was granted and supported by the TÜBİTAK (The Scientific and Technological Research Council of Türkiye) with Project number 123Y108.Keywords: Gulf of Edremit, Holocene, multi-proxy analysis, TOC, XRF.

Türkiye is one of the most vulnerable countries in the Mediterranean Basin; the assessment of changes in soil erosion driven by both climate variability and anthropogenic factors is of great importance. This study aims to examine the current state and potential future changes in soil erosion in Sakarya Province, situated in the eastern part of the Mediterranean Basin, by employing the GIS-based RUSLE (Revised Universal Soil Loss Equation) model. Considering the impact of climate change on precipitation regimes, rainfall projections for the 2061–2080 period under the high-emission SSP5-8.5 scenario were evaluated. The analysis revealed that the current average annual soil loss in Sakarya is 2.9 t/ha, with the highest erosion risk occurring on steep slopes, bare surfaces, and agricultural lands. By 2080, under the SSP5-8.5 scenario, the annual average soil loss is projected to be 2.6 t/ha, while slight and very slight erosion levels are expected to increase. These results provide important insights for identifying current risk areas and critical zones for conservation, as well as for projecting future erosion scenarios, thus contributing to sustainable land management policies at the watershed scale. The study suggests that strategies to reduce erosion risk in Sakarya should particularly focus on land management practices such as slope stabilization, afforestation, land cover improvement, and terracing. These approaches are crucial for mitigating land degradation (SDG 15.3) and ensuring sustainable agricultural production (SDG 2.4) within the framework of the Sustainable Development Goals.

Liquidambar orientalis, a relict and endemic tree species of the Eastern Mediterranean, is increasingly threatened due to its narrow distribution and intense anthropogenic pressures. This study aims to model the spatiotemporal changes in its habitat suitability from the Last Glacial Maximum (LGM) to future climate scenarios (2050 and 2070) using a robust ensemble species distribution modeling (SDM) framework. By integrating paleobotanical data with predictive modeling, we provide crucial insights into the species' ecological resilience and future conservation priorities. The ensemble models showed excellent predictive performance (AUC = 0.96, TSS = 0.91, Boyce Index = 0.84, Kappa = 0.89), identifying mean diurnal range (Bio2) and precipitation of coldest quarter (Bio19) as the most influential variables. Fossil pollen records confirm the species long–term persistence in southwestern Anatolia since the early Miocene. While projections under the RCP 2.6 scenario suggest potential habitat expansion or stability, especially in mountainous refugia, the RCP 8.5 scenario indicates a reduction in highly suitable areas. Nevertheless, key ecological niches are expected to persist, particularly along the southern slopes of the Taurus Mountains. This is the first study to combine multi temporal ensemble SDMs and fossil records for L. orientalis, revealing its ecological flexibility over millennia. The findings underscore the necessity of prioritizing genetically diverse populations and climatically stable refugia in conservation strategies. Our integrative approach provides a valuable framework for assessing the climate resilience of other Mediterranean relict species.

With its millennia-long agricultural history, Olive (Olea europaea L.) is one of the most strategic crops of the Mediterranean basin and a key component of the Turkish economy. This study assessed the effects of climate change on the potential distribution of olive in Türkiye using machine learning-based species distribution models (SDMs). Analyses were conducted using the 1970–2000 reference period and future projections for 2041–2060 and 2081–2100 under the SSP2-–4.5 and SSP5–8.5 scenarios, incorporating bioclimatic variables as well as topographic factors such as elevation, slope, and aspect. The model showed strong predictive performance (AUC = 0.93; TSS = 0.77) and identified elevation, winter precipitation (Bio19), and mean temperature of driest quarter (Bio9) as the primary variables influencing the distribution of olive trees. Model results predict a significant shift in suitable areas for olive cultivation, both northward—from the traditional Aegean and Mediterranean coastal belt toward the Marmara and Black Sea regions—and upward in elevation into higher-altitude inland areas. High-suitability areas, which accounted for 4.4% of Türkiye’s land area during the reference period, are projected to decline to 0.2% by the end of the century under the SSP5–8.5 scenario. UNEP Aridity Index analyses indicate increasing aridity pressure on olive habitats. While 87.2% of suitable habitats were classified as sub-humid in the reference period, projections for 2081–2100 under SSP5–8.5 suggest that 40.1% of these areas will shift to dry sub-humid and 26.4% to semi-arid conditions.

Zelkova carpinifolia is a Tertiary relict tree distributed in Hyrcanian and Colchic forests. Most of its habitat has been destroyed in the last century. This study aimed to model potentially suitable habitat areas for Zelkova carpinifolia from the past to the future. The Last Glacial Maximum (LGM) and Future (2061-2080) models include 19 bioclimatic variables from the CCSM4 global circulation model Pearson correlation coefficient was used to assess collinearity between variables and ten variables were selected for distribution modelling. Habitat suitability was estimated using the Biodiversity Modelling (BIOMOD) ensemble modelling method by combining the results of ten algorithm models using the R package "biomod2". The area under the curve (AUC) of the receiver operating characteristic (ROC) curve and true skills statistics (TSS) were calculated to evaluate the performance of the models. The contributions of the environmental variables were calculated separately for each algorithm model. According to the results obtained, the most effective bioclimatic variable in the distribution of the species is temperature seasonality (Bio4). The modelling results revealed that Zelkova carpinifolia survived in suitable refuge areas in western Asia during the LGM. These distribution areas have remained largely unchanged and even expanded. The future model results predict that the suitable habitats of the species will narrow in the Hyrcanian forests south of Caspian Sea and that more suitable conditions will be found around the Caucasus. Given the increasing destruction of these valuable plant species due to human activities and the expected negative impacts of climate change in the future, it is important to develop policies and strategies for the protection of Zelkova carpinifolia's habitat, the creation of nature reserves, and sustainability.

Türkiye is one of the first regions where olives were domesticated, and olives reflect the country’s millennia-old agricultural and cultural heritage. Moreover, Türkiye is one of the leading nations in olive and olive oil production in terms of quality and diversity. This study aims to determine the current and future distribution areas of olives, which is important for Türkiye’s socio-economic structure. For this purpose, 19 different bioclimatic variables, such as annual mean temperature (Bio1), temperature seasonality (Bio4), and annual precipitation (Bio12), have been used. The RCP4.5 and RCP8.5 emission scenarios of the CCSM4 model were used for future projections (2050 and 2070). MaxEnt software, which uses the principle of maximum entropy, was employed to determine the current and future habitat areas of the olives. Currently and in the future, it is understood that the Mediterranean, Aegean, Marmara, and Black Sea coastlines have areas with potential suitability for olives. However, the model projections indicate that the species may shift from south to north and to higher elevations in the future. Analyses indicate that the Aegean Region is the most sensitive area and that a significant portion of habitats in the Marmara Region will remain unaffected by climate change.

Hazelnuts are a vital agricultural commodity, contributing significantly to global food systems and public health due to their nutritional value and economic importance as an export crop. Turkiye is a leading global producer of hazelnuts as a major source of income and a strategic agricultural product. In this study, we selected two regions named Acmabasi and Parali from Sakarya province which ranks third in the production of hazelnut among Turkish provinces and utilized very high-resolution (VHR) aerial photographs to classify hazelnut fields. In addition to the standard CORINE Land Cover (LC) classes, we defined a specific hazelnut class, verified through field observations. Various machine learning-based classification algorithms, including Support Vector Machine (SVM), Random Forest (RF), K-Nearest Neighbors (KNN), and Bayesian classification, were employed with object-based classification with different feature values. The performance of the models was evaluated using overall accuracy and F1-score metrics and the best results are obtained with Support Vector Machines (SVM) with Radial Basis Function (rbf) and Bayes classifier. We obtain 96.20% overall accuracy and 93.40% F1-Score for Acmabasi while using Bayes with feature combination as a best result. For Parali region, the highest overall accuracy is obtained with SVM - rbf using feature combination while F1-score is the highest for Bayes classifier with 90.57%.

The objective of this research is to propose an integrated approach to create a Geographic Information System (GIS) based spatial decision support system for sustainable hazelnut agriculture in the process of adaptation to climate change within the scope of a newly started interdisciplinary project. Hazelnut is a temperate climate fruit species. In Turkiye, the Black Sea coastal zone, which has favorable climatic conditions, is naturally a hazelnut growing area and hazelnut is one of the climax plant species. Hazelnut is one of the most important agricultural export products of Turkiye and according to 2023 data, Turkiye is ranked as the first place in the world hazelnut exports with 298.557 tons of hazelnut kernel. Since hazelnut is an economically valuable product and its cultivation is directly dependent on topographical and climatic conditions in large areas, monitoring and planning of hazelnut cultivation under changing climatic conditions is very important for the country's economy. Turkiye is one of the most affected Mediterranean countries due to climate change. The results of temperature, precipitation, and humidity simulations in regional climate models created especially for the Black Sea provide important findings in terms of the necessity for spatial planning based on the ecological requirements of hazelnut. Sustainable and rational use of land, determination of the suitability and quality of land, and integrated evaluation of information such as climate, topography, and soil properties are of great importance and are considered natural resources/heritage for future generations. For this purpose, the province of Sakarya, which is ranked as 3rd in hazelnut production in Turkiye with 82.581 tons, was selected as the study area in this research. In the process of creating the spatial decision support system in the study, many interrelated variables, such as climate, topography, geological conditions, and soil properties, will be evaluated using geostatistical methods and weights obtained from the literature and expert opinion surveys. With the data will be used in the spatial decision support system to be designed with the Analytic Hierarchy Process method approach will be used for the integrated analysis of various geospatial data related to the hazelnut cultivation to determine the most suitable hazelnut cultivation areas and the most appropriate hazelnut cultivars within the scope of adaptation to climate change. We will design a spatial decision support system in the process of climate change adaptation by determining the characteristics of the criteria based on varieties that support rural development in order to ensure sustainable production of hazelnut, which has strategic importance for Turkiye and strengthens competition in the global market.

Land cover change due to rapid urbanization and industrialization has been known to increase the land surface temperature around the world. For this reason, examining the variation of land surface temperatures and mitigating the related impacts remain a challenge. The changing land cover pattern in urban areas also affects the quality of life in urban areas by altering its environment, deteriorating air quality and increasing the frequency of extreme climatic events like high-intensity rainfall, drought, and development of urban heat islands conditions. Düzce, located in the Western Black Sea Region, where urbanization and industrialization have been expanding rapidly in Türkiye since 2000s, was selected as the study area. In the study area, natural disasters with hydrometeorological character have occurred frequently in recent years. Düzce is climate change sensitive and ecologically vulnerable areas. For this purpose, temporal and spatial changes in the land surface temperature were determined by Land Surface Temperature and Normalized Difference Vegetation Index Analysis with Landsat 7 ETM + in 2000 and Landsat 9 OLI in 2022. Landsat 7 ETM + in 2000 and Sentinel-2 in 2022 were analysed for land cover with object-based classification. Daily temperature and precipitation data were used for climatological analysis. Statistical data were used for population growth and hydrometeorological disaster. According to the results, settlement areas expanded, and an average temperature increase was observed in 2022 compared with 2000. The areas where land surface temperature values increase are determined as settlement areas, industrial and agricultural areas.

Bu çalışma, MaxEnt modelleme aracı kullanılarak zeytinin (Olea europaea L.) dağılımında etkili olan biyoiklim değişkenlerini belirlemeyi ve yetiştiricilik için günümüzdeki potansiyel ile gelecekteki olası uygunluk modellerini oluşturmayı amaçlamaktadır. Günümüzdeki potansiyel habitat alanlarının belirlenebilmesi için yakın geçmişe (1970-2000) ilişkin biyoiklim değişkenleri kullanılmıştır. Gelecek tahminleri ise MRI-ESM2-0 modelinin SSP2-4.5 ve SSP5-8.5 emisyon senaryolarına dayalı olarak 2041-2060 ve 2081-2100 dönemlerine ait biyoiklim değişkenlerinden yararlanılarak yapılmıştır. Modelleme sonucunda, zeytinin dağılımına en fazla katkı sağlayan değişkenlerin Bio12 (yıllık yağış), Bio7 (yıllık sıcaklık değişim aralığı) ve Bio9 (en kurak 3 ayın ortalama sıcaklığı) olduğu belirlenmiştir. SSP2-4.5 ve SSP5-8.5 senaryolarından simüle edilen gelecek iklim modelleri, genel olarak günümüzle kıyaslandığında, uygun alanların gelecekte daha yüksek rakımlı alanlara ve kuzey yönüne doğru kayma olasılığı gösterebileceğini tahmin etmektedir. Ayrıca daha önce zeytin yetiştiriciliğine elverişsiz olan bazı alanların, gelecek dönemlerde daha uygun hale gelebileceğini öngörmektedir. Özellikle, ilerleyen yıllarda Karadeniz ve Marmara kıyılarının zeytin yetiştiriciliği için daha elverişli hale gelmesi beklenmektedir. İklim değişikliğinin zeytin üzerindeki zorlayıcı etkilerini hafifletmek ve sürdürülebilirliğini sağlamak amacıyla iklim değişikliğine uyum stratejilerinin geliştirilmesi ve uygulanması önemlidir. Bu doğrultuda, çalışmada sulama ve toprak yönetimi, çeşit seçimi, hastalık ve zararlılarla mücadele, hasat teknikleri, teknoloji kullanımı ve eğitim gibi faktörler ele alınmış ve uyum stratejileri açısından değerlendirilmiştir.

Türkiye is located in the Mediterranean Basin, one of the hotspot areas most affected by climate change. Extreme events in weather conditions in the last 10 years are one of the most obvious reflections of global warming. Variations in temperature and precipitationPrecipitation regimes directly affect agriculture, water resourcesResource, biodiversity, etc. Climate changeClimate change is a serious threat, especially in countries such as TürkiyeTürkiye, with a dominant agricultural economy. For this purpose, in this study, (a) examples of extreme events in Türkiye will be given; (b) Türkiye's temperatureTemperature and precipitationPrecipitation conditions in the period 1929–2020 will be determined by analysing 217 meteorological observation data; (c) areas in Türkiye where the Mediterranean climate is dominant or not, according to the Emberger Bioclimate Classification; (d) future temperature and precipitationPrecipitation conditions will be determined based on 19 bioclimate variables obtained from the WorldClim database for the future 2061-2080 CMIP 5 model and RCP 4.5 and 8.5 scenarios. The results obtained will be shared with public and non-governmental organizations in order to develop adaptation strategiesStrategy at national, regional and local levels to prevent the serious damage of climate changeClimate change to humans and the environmentEnvironments and ensure sustainable developmentDevelopment in changing climate conditions.

Çalışmada Kocaeli ilinin önemli su kaynaklarından birisi olan Yuvacık Barajı’nın alt havzalarından Kirazdere havzası ve çevresinde iklim değişikliğinin günümüzdeki etkisi ve gelecekteki olası etkileri belirlenmeye çalışılmıştır. Mann Kendall trend analizi sonuçlarına göre; 1975-2020 yılları arasında sıcaklığın artış trendinde olduğu, bu artışın belirgin olarak 2000’li yıllardan sonra oluştuğu, yağışta anlamlı bir trend olmadığı, akımın ise azalış trendinde olduğu gözlemlenmiştir. R Studio programı kullanılarak Standartlaştırılmış Yağış İndeksi (SYİ) analizi ile incelenen periyotta kuraklıkların olduğu saptanmıştır. Baraj gölünde kuraklığın da etkisiyle meydana gelen su seviyesindeki azalmalar, arazi çalışmalarında alınan drone görüntüleri ile de gözlemlenmiştir. HadGEM2-ES ve MPI-ESM-MR iklim modellerinden RCP 4.5 ve RCP 8.5 iklim senaryoları ile elde edilen sonuçlara göre 2020-2098 periyodunda sıcaklıklarda artış trendi gözlemlenmiştir. Yağışlarda ise MPI-ESM-MR RCP8.5’e senaryosuna göre azalma yönünde bir trend olduğu gözlemlenmiş, ancak diğer model ve senaryolardan elde edilen sonuçlarda anlamlı bir trend gözlemlenmemiştir. İklim projeksiyonlarına bağlı olarak SYİ metoduyla elde edilen kuraklık analizi sonuçlarına göre; havzada gelecekte de kısa ve uzun dönemli kuraklıklar yaşanacağı, 2050 yılından sonra daha da şiddetleneceği öngörülmektedir. Bu sebeple su sıkıntısını en aza indirgemek için Sürdürülebilir Kalkınma Amaçları içerisinde yer alan “İklim Eylemi” ve “Temiz Su” ya erişim kapsamında suyu doğru kullanma teknolojilerinin yaygın hale getirilmesi gerekmektedir.

Akdeniz Havzası’nda yer alan Türkiye coğrafi konumu itibariyle iklim değişikliğinden en fazla etkilenen ülkelerden birisidir. İklim değişikliği başta su kaynakları olmak üzere birçok doğal ve beşerî sistemi olumsuz yönde etkilemektedir. Bunlar içerisinde sulak alanlar sahip oldukları zengin biyolojik çeşitlilik nedeni ile dünyanın en önemli ekosistemlerinden biridir. Son yıllarda gerek kuraklık gerekse sulak alanların bilinçsiz kullanımı ve yönetimi sulak alanların yok olma sürecini hızlandırmaktadır. Bu çalışmada iklim değişikliğinin Türkiye’nin önemli sulak alanlarıdan birisi olan Marmara Gölü’nde mekânsal değişime etkisi 2013-2023 yılları arasında uzaktan algılama veri ve metotları kullanılarak ve arazi çalışmalarından elde edilen bulgularla analiz edilecektir. Çalışmada veri olarak Landsat 8 OLI ve Sentinel 2 uydu görüntüleri; metot olarak ise Arc GIS Pro yazılımında Nesne Tabanlı Sınıflandırma Yöntemi uygulanacaktır. Çalışmanın sürdürülebilir kalkınma ilkeleri doğrultusunda “İklim Eylemi”, “Sudaki Yaşam” ve “Sürdürülebilir Şehirler ve Topluluklar” hedeflerine uygun sürdürülebilir göl havzası yönetimine güncel ve farklı bir bakış açısı sunarak literatüre katkı sağlaması amaçlanmaktadır.

This research aims to find crop-based residue burning (CRB) amounts for the Southeastern Anatolia Region of Türkiye, where versatile and diverse of agricultural fields are available. We used the time series of Sentinel-2 images to identify spatial distribution of different crop types and to determine the burned agricultural fields in 2019 using Google Earth Engine platform. We implemented Intergovernmental Panel on Climate Change standards to calculate the emissions from Greenhouse gases and Particulate Matter. We also analyzed Sentinel-5P images to generate Nitrogen Dioxide maps and compared them with crop-based emission calculations. Our analysis illustrated that 14,444.307 Gg of Greenhouse Gases and 117.809 Gg of Particulate Matters were released in 2019 due to CRB practices. Our results can potentially improve the national statistics by providing spatio-temporal field-based CRB emissions and supporting country-level agricultural decision-making processes. Researchers could implement our proposed data and methodology in other regions suffering from the CRB problem.

Akdeniz Havzası’nda yer alan Türkiye coğrafi konumu itibariyle iklim değişikliğinden en fazla etkilenen ülkelerden birisidir. İklim değişikliği başta su kaynakları olmak üzere birçok doğal ve beşerî sistemi olumsuz yönde etkilemektedir. Bunlar içerisinde sulak alanlar sahip oldukları zengin biyolojik çeşitlilik nedeni ile dünyanın en önemli ekosistemlerinden biridir. Son yıllarda gerek kuraklık gerekse sulak alanların bilinçsiz kullanımı ve yönetimi sulak alanların yok olma sürecini hızlandırmaktadır. Bu çalışmada iklim değişikliğinin Türkiye’nin önemli sulak alanlarıdan birisi olan Marmara Gölü’nde mekânsal değişime etkisi 2013-2023 yılları arasında uzaktan algılama veri ve metotları kullanılarak ve arazi çalışmalarından elde edilen bulgularla analiz edilecektir. Çalışmada veri olarak Landsat 8 OLI ve Sentinel 2 uydu görüntüleri; metot olarak ise Arc GIS Pro yazılımında Nesne Tabanlı Sınıflandırma Yöntemi uygulanacaktır. Çalışmanın sürdürülebilir kalkınma ilkeleri doğrultusunda “İklim Eylemi”, “Sudaki Yaşam” ve “Sürdürülebilir Şehirler ve Topluluklar” hedeflerine uygun sürdürülebilir göl havzası yönetimine güncel ve farklı bir bakış açısı sunarak literatüre katkı sağlaması amaçlanmaktadır.

Bodrum Peninsula is one of the most important tourism centers of Turkey with its geographical location, coastal and marine tourism, natural and cultural features. It has been determined that the winter population has also increased in Bodrum in recent years, and it is thought that this may cause an increasing permanent resident population and urbanization. The objective of this study is to determine the changes in land cover due to the rapid increase in urbanization in Bodrum Peninsula. For this purpose, object-based classification analysis was applied to Landsat 4-5 TM 1990, 2000, 2010 and Landsat 8 OLI 2021 multispectral satellite images. Within the scope of the analysis, the objects were created by applying the segmentation process to satellite images. Secondly, land cover classes were determined according to the Corine land cover classification with levels 1-2-3. Thirdly, the classification process based on a decision tree was carried out with the classes defined using the threshold values determined for spectral and texture properties of the objects using multiresolution segmentation. In the last stage, accuracy assessment analysis was applied to the classification results. According to the results, it is obtained that while Urban Fabric and Burnt Areas are increased in 32 years, Forest and semi-natural areas are decreased. As a result of population pressure due to tourism, Urban Fabric areas have moved closer to Forests and Semi-Natural Areas. Wildfires with the effect of heatwaves were increased, biodiversity has been endangered in the study area located in the Mediterranean basin, where human-related climate change is most clearly detected. Significantly, there has been a wildfire in Bodrum in August 2021, which lasted for days and caused severe degradation on the land cover. For this, sustainable land cover management is recommended to protect the natural ecosystem by minimizing the risks that cause land degradation in the Bodrum peninsula.

In the last century climate change has been a major threat to biodiversity, ecosystem services, and human well‐being. Atmospheric oscillations that occur at the regional oceanic flow pattern may affect significantly the climate of the Earth. In this study, we investigate the effects of ENSO (El Nino Southern Oscillation) and NAO (North Atlantic Oscillation) on the Mediterranean crop yield using the Nino 3, Nino3.4, Nino 4, ONI and NAO indices. Olive, which is a bioindicator type in the Mediterranean, and cotton and grapes with high yield and economic value crops were examined. According to the average production amounts in the Mediterranean Region between 1991 and 2020, 39% of cotton production is in Adana (205319 tone), 43% of grape production is in Mersin (228471 tone) and 37% of olive production is in Hatay (103854 tone). As a method, firstly, Mann Kendall rank correlation test was applied to the yield values of the crops. After the 2000s, it has been determined that the trend of yield has changed and was obtained an increasing trend. Secondly, the correlation between the yields and Nino 3, Nino3.4, Nino 4, and NAO indices were determined with the Spearman correlation coefficient. Accordingly, a high correlation of 50% and 80% was found at the p ≤ 0.05 and p ≤ 0.00 significance level in the phenological periods of the crops. The highest correlations were determined especially during the flowering period (April, May, June) for olive and grape yield with El Nino indices. The frequency of the correlation detected with the NAO index is weak. The effect on the efficiency of the phases when El Nino indices are strong was examined graphically. Accordingly, in the 1997 and 2015-2016 periods, when the El Nino phenomen was very strong, there were sharp decreases in the crop yields. This variability affects the countries whose economic activity is based on agriculture in the Mediterranean Basin, and it is likely to affect the food industry in the future.