Determining the immigrant acceptance capacity in counties of Guilan province with ecosystem service sustainability approach

Introduction
Human existence relies heavily on ecosystems. However, in recent decades, humans have altered land cover at unprecedented rates, causing a decline in the quality of ecosystem services. These disruptions can have far-reaching and often irreversible consequences for both local and global environmental conditions. From 1996 to 2006, Guilan Province shifted from being a region that primarily sent migrants to one that began to accept them. Various factors, including climate change and water resource depletion in other regions of the country, may further escalate migration to Guilan. Such migration can result in profound changes to the province’s land cover, including deforestation, increased strain on ecosystems, and a reduction in ecosystem services. This research examines the capacity of each county within Guilan Province to accept immigrants. By calculating this capacity, the study evaluates and compares the current immigrant acceptance status of counties with the index determined in the analysis.
 
Materials and Methods
To track changes in land cover, satellite imagery from Landsat 5 and 9 was used for the years 1996, 2006, 2016, and 2023. Furthermore, criteria were identified through library research and semi-structured interviews. Using the Analytic Hierarchy Process (AHP), the immigrant acceptance capacity for each county was calculated.
 
Results and Discussion
Analysis of satellite images from 1996 to 2023 reveals a 99% increase in Build-up land cover, amounting to an expansion of 25,614 ha. During the same period, forest cover—the province’s most extensive and ecologically significant land cover for providing ecosystem services—declined by 107,069 ha. This reduction accounts for 7.74% of Guilan Province’s total area. Over these 37 years, the province’s population grew by 409,902, and 385,069 migrants arrived in Guilan between 2006 and 2016. A strong inverse correlation (-0.99) was observed between the population growth rate and the forest cover reduction rate, underscoring the close relationship between demographic changes and forest cover loss. To develop population and migration management plans that align with the sustainability of ecosystem services and the region’s ecological capacity, five ecological criteria were identified at the county scale. These criteria were derived from Guilan Province’s Territorial Management Document (2017).
Additionally, following the findings of Ronchi and imposing restrictions on forest cover alteration to sustain ecosystem services, mountainous and foothill areas—which host over 95% of the province’s forest cover—were excluded from settlement development planning. Consequently, the ratio of each county’s plain area to the province’s total plain area was established as a sixth criterion. With identified ecological and ecosystem service criteria, the Analytic Hierarchy Process was employed to calculate the capacity index for accepting immigrants in each county. A comparison between these indexes and actual immigrant acceptance rates revealed significant ecological pressure discrepancies across some counties. Rasht County demonstrated the highest ecological pressure and discrepancy. Between 2006 and 2016, Rasht accommodated 36.76% of all migrants to the province, while the study determined its immigrant acceptance capacity to be 16%. This indicates that the county absorbed 20.76% more migrants than its obtained ecological capacity. In contrast, Bandar Anzali exhibited the most favorable immigrant acceptance conditions with minimal ecological strain. With an immigrant acceptance capacity of 12.5%, only 6.34% of the province’s migrants settled in Bandar Anzali during the same period, reflecting a positive alignment with its ecological capacity.
Conclusion
Since 2006, migrants arriving in Guilan have played a significant role in the region’s population growth. As migration to Guilan is expected to increase in the coming years, the associated demographic changes will undoubtedly impact land cover and ecosystem services. These developments underscore the critical need for population-migration planning based on ecological constraints and the vulnerabilities of ecosystem services. By calculating the immigrant acceptance capacity for each county, it becomes possible to identify the ecological pressure caused by migration. This analysis compares the current number of incoming migrants in each county with the index derived for that county. For counties like Rasht, which bear a heavier ecological burden, implementing policies to regulate and manage incoming migration in the years ahead is strongly recommended. Additionally, improving the ecological indicators used to calculate the immigrant acceptance capacity will help mitigate further environmental damages and prevent a reduction in the county’s ecological carrying capacity. On the other hand, attempts to improve the indicators used to calculate the immigrant acceptance capacity might result in increased ecological stability for counties like Bandar Anzali, where the number of arriving migrants is less than the calculated index. Long-term sustainability of ecosystem services and ecological stability would be preserved with the help of such actions.