Objective: The present study aims to examine the spatial distribution pattern and flow of Miyandoab saplings across Iran
Methods: This study is applied in terms of purpose and descriptive–analytical in terms of nature and methodology, and is grounded in the pragmatist paradigm. To identify the causal factors affecting sapling production and its spatial distribution, a qualitative grounded theory approach was employed. In addition, UCINET and ArcGIS software were used to gain a better understanding of the spatial distribution pattern of saplings. The statistical population consisted of 360 nursery units in Miyandoab County, managed by 218 specialized sapling producers. Participants were selected through purposive snowball sampling, and theoretical saturation was achieved after conducting 31 semi-structured interviews. Data analysis was carried out simultaneously based on the three-stage coding model of Strauss and Corbin.
Results: Data analysis led to the identification of 39 general concepts, while axial coding resulted in 30 categories and 21 indicators, which were ultimately classified into three major dimensions: natural production resources, human resources, and the Miyandoab sapling brand. A directed graph of sapling flows was developed using UCINET software, illustrating the distribution of more than 29 million saplings to 24 provinces across the country, with neighboring provinces receiving the highest volumes.
Conclusions: The formation and consolidation of Miyandoab County’s position in the production and distribution of Saplings is the result of the synergy of a set of natural, human, and institutional factors that, over time, have evolved into a relatively coherent production–spatial system. Within this system, favorable environmental conditions-such as fertile soil, abundant water resources, and a suitable climate-constituted the initial foundation. However, what transformed this initial advantage into a sustainable and extensive economic activity has been the gradual accumulation of indigenous knowledge, specialized skills, and the emergence of cooperative and competitive relationships among stakeholders in this sector. The development of a cluster-based structure, professional interactions, and the expansion of national markets have strengthened the Miyandoab Saplings brand and established the region as one of the country’s main centers for Saplings distribution. Moreover, the spatial distribution pattern of Miyandoab Saplings closely resembles Hägerstrand’s spatial diffusion and adaptive expansion diffusion models, in which Miyandoab functions as the central hub directing the flow of supply toward various provinces. In this context, the existence of 24 flows toward different provinces across the country and a network density of 0.086 indicate the spatial diffusion of Saplings from this center to other parts of the country. Among these, West Azerbaijan and East Azerbaijan provinces receive the highest volumes of Saplings. Provinces such as Ardabil, Zanjan, Tehran, and Markazi are ranked in the second tier, while Kurdistan, Gilan, Ilam, Kermanshah, Golestan, Fars, Isfahan, and Hamedan occupy the third tier in terms of Saplings inflow. This expansion diffusion and spatial pattern indicate the emergence of a production pole at the national scale, which—relying on product quality, the trust of distant markets, and extensive communication linkages—has assumed a central role in the Saplings supply network