## 1 Introduction
It also has a high di-nitrogen fixation capacity; its roots develop symbiosis with N-fixing rhizobia and also interact with arbuscular mycorrhizal fungi that grow in the rhizosphere, allowing black locust to cope with environmental stresses such as aridity and low nutrient availability [28]. Based on its favourable properties, and despite its invasiveness [26], black locust has been widely planted for the restoration of areas that are degraded due to anthropogenic activities, such as intensive agriculture and mining in several countries [29; 30; 31]. To date, black locust occurs in forty-two European countries, in most of which it is naturalized, and it occupies an area of 2.3 million ha in Europe [24]. _R. pseudoaccia_ plantations are established in many semi-arid regions around the world, and growth decline and drought dieback are often experienced (Refs. [32; 33] and the literature therein). However, to our knowledge, there is scarce information on the ecophysiological responses of black locust forests or plantations to climatic drivers at the ecosystem level [8], particularly when it comes to data collected by eddy flux towers [9]. The accurate determination of black locust GPP and ET by means of Eddy Covariance will provide the necessary ground measurements for the development, calibration and cross-validation of ecological, biogeochemical and satellite-based models for the prediction of these parameters (e.g., [34; 35; 36; 37; 38]). Furthermore, the assessment of black locust ecosystems' water and carbon balance and the in-depth understanding of their covariation with environmental drivers will contribute to our knowledge of the responses of the terrestrial biosphere to climate change, thus improving climate projections [39], and will contribute to the sustainable management of water resources and ecosystems [12], which is crucial in the context of ongoing climate change. In a previous study, [PERSON] and [PERSON] [9] tested the combined effect of environmental variables, such as net radiation, VPD and plant phenology, on the ET of the studied black locust plantations by applying multiple linear regression (MLR) and highlighting the partial significance of each variable. Although significant models were produced, this procedure was applied only to ET and was limited by the small dataset. Additionally, the presumed linearity between the environmental variables and the ET for the MLR application could have biased the results. Here, we used a larger dataset of c. 2.5 years to assess the annual GPP and ET and their seasonal variation. Furthermore, we employed Generalised Additive Models (GAM) to isolate and better characterize the effect of different environmental drivers (VPD, SWC, solar radiation, Enhanced Vegetation Index--EVI) on both GPP and ET, during the summer months and within certain thresholds that are important from an ecophysiological point of view. EVI was included in the GAMs as a proxy of the vegetation phenological stage, which is related to ecosystem total leaf area and is, thus, expected to have an impact on ecosystem fluxes. Thus, this study aimed at (a) assessing GPP and ET, and their changes during two consecutive summers, characterized by variability in climatic parameters (particularly VPD and SWC) and (b) understanding the relationships between environmental drivers and ecosystem carbon and water fluxes in the studied _R. pseudoacacia_ planted ecosystem.