We examined the local community incentive programs to improve traditional forest management in three forested villages in Baneh city, Kurdistan province in the northern Zagros forests of western Iran. Zagros forests c...We examined the local community incentive programs to improve traditional forest management in three forested villages in Baneh city, Kurdistan province in the northern Zagros forests of western Iran. Zagros forests cover 6.07 million ha and support rich plant and animal diversity. Changes in local community social and economic sys-tems and the inefficiency of traditional forest management led to a criti-cal situation in the stability of forest regeneration in recent decades. Due to a shortage of productive and arable lands and resulting unemployment and poverty, people overexploited the Zagros forests. Outside interven-tion in traditional forest management creates conflicts between local peoples and forest management organizations. To achieve sustainable forest management, including forest resources conservation and im-provement of natural resource based livelihoods of communities, it is desirable to implement Forestry Incentive Programs （FIP） based on the important functions of forests. Detailed information on the so-cio-economics of communities, the effect of forests on local livelihoods, and lists of products extracted from the forest were obtained from a sur-vey of local communities though questionnaire, interview and observa-tion. We studied 276 households in three villages and completed 76 ques-tionnaires by householders in the quantitative analysis. Sampling was performed by simple random sampling （SRS）. The needs of rural com-munities, such as livestock husbandry, mainly arise from the characteris-tics and environmental features of villages. We identified the driving forces, pressures, status, impacts and responses （DPSIR） to design incen-tive programs, by DPSIR analysis and interaction analysis. Evaluation of local community benefits from forests showed that in order to improve forest management, 319 dollars per year would be needed by each family as an incentive in 2010 to prevent lopping and firewood collecting, the main causes of forest degradation.展开更多
Environmental impact prediction is an important step in many environmental studies. A wide variety of methods have been developed in this concern. During this study, remote sensing images were used for environmental i...Environmental impact prediction is an important step in many environmental studies. A wide variety of methods have been developed in this concern. During this study, remote sensing images were used for environmental impact prediction in Ro-batkarim area, Iran, during the years of 2005～2007. It was assumed that environmental impact could be predicted using time series satellite imageries. Natural vegetation cover was chosen as a main environmental element and a case study. Environmental impacts of the regional development on natural vegetation of the area were investigated considering the changes occurred on the extent of natural vegetation cover and the amount of biomass. Vegetation data, land use and land cover classes (as activity factors) within several years were prepared using satellite images. The amount of biomass was measured by Soil-adjusted Vegetation Index (SAVI) and Normalized Difference Vegetation Index (NDVI) based on satellite images. The resulted biomass estimates were tested by the paired samples t-test method. No significant difference was observed between the average biomass of estimated and control samples at the 5% significance level. Finally, regression models were used for the environmental impacts prediction. All obtained regression models for prediction of impacts on natural vegetation cover show values over 0.9 for both correlation coefficient and R-squared. According to the resulted methodology, the prediction models of projects and plans impacts can also be developed for other environmental elements which may be derived using time series remote sensing images.展开更多
文摘We examined the local community incentive programs to improve traditional forest management in three forested villages in Baneh city, Kurdistan province in the northern Zagros forests of western Iran. Zagros forests cover 6.07 million ha and support rich plant and animal diversity. Changes in local community social and economic sys-tems and the inefficiency of traditional forest management led to a criti-cal situation in the stability of forest regeneration in recent decades. Due to a shortage of productive and arable lands and resulting unemployment and poverty, people overexploited the Zagros forests. Outside interven-tion in traditional forest management creates conflicts between local peoples and forest management organizations. To achieve sustainable forest management, including forest resources conservation and im-provement of natural resource based livelihoods of communities, it is desirable to implement Forestry Incentive Programs （FIP） based on the important functions of forests. Detailed information on the so-cio-economics of communities, the effect of forests on local livelihoods, and lists of products extracted from the forest were obtained from a sur-vey of local communities though questionnaire, interview and observa-tion. We studied 276 households in three villages and completed 76 ques-tionnaires by householders in the quantitative analysis. Sampling was performed by simple random sampling （SRS）. The needs of rural com-munities, such as livestock husbandry, mainly arise from the characteris-tics and environmental features of villages. We identified the driving forces, pressures, status, impacts and responses （DPSIR） to design incen-tive programs, by DPSIR analysis and interaction analysis. Evaluation of local community benefits from forests showed that in order to improve forest management, 319 dollars per year would be needed by each family as an incentive in 2010 to prevent lopping and firewood collecting, the main causes of forest degradation.
文摘Environmental impact prediction is an important step in many environmental studies. A wide variety of methods have been developed in this concern. During this study, remote sensing images were used for environmental impact prediction in Ro-batkarim area, Iran, during the years of 2005～2007. It was assumed that environmental impact could be predicted using time series satellite imageries. Natural vegetation cover was chosen as a main environmental element and a case study. Environmental impacts of the regional development on natural vegetation of the area were investigated considering the changes occurred on the extent of natural vegetation cover and the amount of biomass. Vegetation data, land use and land cover classes (as activity factors) within several years were prepared using satellite images. The amount of biomass was measured by Soil-adjusted Vegetation Index (SAVI) and Normalized Difference Vegetation Index (NDVI) based on satellite images. The resulted biomass estimates were tested by the paired samples t-test method. No significant difference was observed between the average biomass of estimated and control samples at the 5% significance level. Finally, regression models were used for the environmental impacts prediction. All obtained regression models for prediction of impacts on natural vegetation cover show values over 0.9 for both correlation coefficient and R-squared. According to the resulted methodology, the prediction models of projects and plans impacts can also be developed for other environmental elements which may be derived using time series remote sensing images.
