Effects of teleconnection indices on net primary production (NPP) in bioclimatic zones of Iran

One of the key topics in scientific research on the effect of global climate change is to study the variations in the global carbon cycle. In this respect, net primary production (NPP) is an important component of carbon storage and a key indicator for evaluating ecosystem functions. However, there are many climatic factors and variables, both at the local and global levels, that can influence NPP variations at various time scales, including daily, monthly, seasonal, and even annual. So, it is of crucial significance for stakeholders and ecosystem managers to understand these variables and their relationship with NPP variations in different ecosystems with different vegetation types, especially in arid and semi-arid regions. Thus, this research investigated the spatiotemporal linear and nonlinear relationships between NPP variations of different bioclimatic zones of Iran and the atmospheric-oceanic oscillations on a monthly and seasonal basis from 2000 to 2016 using generalized linear and additive regression models (GLMs and GAMs). For this purpose, the NPP values were derived from the MODIS satellite products to check the effect of teleconnection indices including Arctic Oscillation (AO), Antarctic Oscillation (AAO), Atlantic Multi-decadal Oscillation (AMO), North Atlantic Oscillation (NAO), Southern Oscillation Index (SOI), Western Mediterranean Oscillation (WMO), and El Niño-Southern Oscillation indices (NINO) including NINO1.2, NINO3.4, NINO3, and NINO4 on it. Findings showed that almost all of the studied climatic indices were influential on the seasonal NPP variations in Iran’s bioclimatic regions with various temporal and spatial patterns. It is revealed that AO, AAO, AMO, NAO, SOI, and WMO indices influence the bioclimatic zones perpetually over the year. However, some indices, such as NINO3.4 in spring, NINO.4 and SOI in summer, and NAO and AMO during warm phases in autumn, have more significant impacts on NPP variations in a given season of the year. However, the model adequacy statistics showed that the NINO family indices and the NAO index were more influential on NPP variations, especially in the winter and spring, than the other climatic indices. In general, the results revealed that the relationship between the NINO family indices and NPP was ascending, either in the linear form or in the nonlinear form. In other words, the NPP value will increase in the bioclimatic regions of Iran during the El Niño phases.