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Showing 2 results for Qazvin Province

A. Darvishi, N. Mobarghaee Dinan, Sh. Barghjelveh, M. Yousefi,
Volume 9, Issue 1 (5-2020)
Abstract

Habitat and ecosystem fragmentation and, consequently, the loss of landscape connectivity are major causes of biodiversity destruction, leading to disruption of material, energy, and information flow at the landscape scale. Given the importance of this issue, the current study aimed to evaluate the ecological connectivity and spatial planning of Qazvin Province, in order to re-establish and protect material, energy, and information flow corridors, using a landscape ecology approach. With that in mind, land use/land cover map was used to identify ecologically functional areas and to map barrier effect and ecological connectivity indicies by mathematical modeling techniques using model builder algorithms in Geographic Information System (GIS). Appropriate patches were, then, spatially selected for restoration and conservation across the landscape. The results showed that 90% of the province has the ecological function, but 10% of the area lacks the function. Three percent of the area has lost its ecological function by physical barriers such as road networks and industrial and residential expantions, and 7% of the area lost its functionality due to anthropogenic effects. In this research, four corridors were identified for spatial planning. Results of this study can be used for management of protected areas and land use planning, as well as environmental impact assessment and envuronmental strategic assessment.

A. Darvishi, M. Yousefi, N. Mobarghaee Dinan,
Volume 10, Issue 1 (5-2021)
Abstract

Pollination is an ecological service with high economic values related to human and ecological wellbeing. This study aims to evaluate the correlation between landscape complexity and pollination service (bee) in Qazvin province at the landscape scale. Landscape pattern metrics (Number of Patches (NP), Patch Richness (PR), Edge Density (ED), and Shannon Index (H)), as a proxy of landscape complexity, were calculated by the model builder in the ArcGIS and pollination service was generated by InVEST. The correlation between landscape complexity and pollination service was evaluated by SPSS software. Results of the correlation between landscape metrics and pollination service, using Linear regression, showed that H has the highest and the most significant relationship with pollination at the 0.01 level (0.420**). Correlation between other metrics and pollination was found to better explauned by Quadratic regression, showing a significant correlation with NP (0.171**) and PR (0.352**) at the 0.01 level and a non-significant relationship with ED (0.002). It was concluded from our results that in the low NP and PR, correlation is high and positive, and in the high NP and PR, correlation is negative, indicating the effect of fragmentation on pollination service. The results of this study can be used in agricultural system planning and biodiversity management to preserve the ecological processes.


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