Thesis Type: Doctorate
Institution Of The Thesis: Orta Doğu Teknik Üniversitesi, Faculty of Engineering, Department of Civil Engineering, Turkey
Approval Date: 2018
Student: ÖNDER GÜLBEYAZ
Supervisor: SEVDA ZUHAL AKYÜREKAbstract:
Understanding the ﬂuctuations in carbon balance and global warming with respect to the global climate change and creating solutions, has become one of the most important topics in ecological studies especially during last decades. These changes, in particular for the terrestrial ecosystems, can be monitored using gross primary productivity (GPP), its derivative net primary productivity (NPP) (the subtraction of autotrophicrespirationfromGPP)andnetecosystemproductivity(NEP)(subtraction of both plant respiration and autotrophic use from GPP) as key components, which are directly affected from climate change. Despite their importance for the ecological researches, the difﬁculties in ﬁeld measurements forced the scientists to ﬁnd new methods such as statistical methods and process based modelling techniques to estimate these quantities. The aims of this study are (i) to evaluate a widely used global model’s outputs for Turkey’s forest ecosystems using ﬁeld measurements, (ii) to improve the accuracy of a global model using local datasets and (iii) to create a new modelling approach to increase the accuracy of NPP estimation over forest ecosystems. Results show that the global model has a signiﬁcant correlation with ﬁeld data of Turkey (R2 = 0.34). However, it still lacks reﬂecting actual conditions over the area. Theusageoflocaldataslightlyimprovestheaccuracyofthemodel(R2 =0.35). Inthisstudy,anewmodellingapproachfortheoptimumtemperaturewasalsoimplemented. The results show that, the distribution of the optimum temperature values is more meaningful (the value of each pixel with respect to its neighbours). Moreover, the model accuracy was increased from 35% to 43% and from 39% to 43% for two different APAR (Absorbed Photosynthetically Active Radiation) estimation methods which are discussed in the thesis. The analysis showed that only 51% accuracy can be achieved using the ﬁeld data. The potential reasons are discussed in the study.