16 اردیبهشت 1403

اعظم خسروی مشیزی

مرتبه علمی: دانشیار
نشانی: جیرفت، کیلومتر 8 جاده بندرعباس، دانشگاه جیرفت، دانشکده منابع طبیعی، گروه مهندسی طبیعت، کد پستی: 7867161167
تحصیلات: دکترای تخصصی / علوم مرتع
تلفن: 43347061-(034)
دانشکده: دانشکده منابع طبیعی

مشخصات پژوهش

عنوان
Exploring the most important indicators for environmental condition assessment using structural equation modeling and InVEST habitat quality model
نوع پژوهش مقاله چاپ شده
کلیدواژه‌ها
Degradation · Climate · Ecosystem · Indicators · Soil · Vegetation
پژوهشگران محسن شرافتمندراد، اعظم خسروی مشیزی

چکیده

Land degradation threatens the social welfare of human societies. In order to identify the most important indicators for land degradation assessment, this article quantified 36 vegetation and soil indicators. Ecosystem condition was determined based on the ecosystem threats using the InVEST habitat quality model, dividing the region to five degradation classes, i.e., negligible, little, medium, high, and very high degradation classes. The structural equation modeling showed that vegetation indicators were more important than soil indicators for land degradation assessment. Climate had a significant mediation on the relationships between soil and vegetation indicators and degradation (P < 0.05). Warning indicators were identified for each degradation stage. The mean changes of degradation indicators were 18, 35, 56, and 78% in little, medium, high, and very high degradation classes, respectively. Cold and semi-arid climates were more influenced by vegetation indicators which had the most variations in the early stages of degradation. Warm and arid regions were more affected by soil indicators, which had the most variations in the high and very high degradation stages. This approach provides comprehensive and necessary information about the condition of ecosystems by determining the severity of degradation in an area, the most important warning indicators of degradation, and the deviation of ecosystems from normal condition at each degradation classes, which helps a lot to managers to choose appropriate restoration plans.