کد مقاله کد نشریه سال انتشار مقاله انگلیسی ترجمه فارسی نسخه تمام متن
6461759 1421863 2017 8 صفحه PDF سفارش دهید دانلود رایگان
عنوان انگلیسی مقاله ISI
A rapid urban site index for assessing the quality of street tree planting sites
ترجمه فارسی عنوان
شاخص سریع سایت شهری برای ارزیابی کیفیت سایت های کاشت درخت در خیابان
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کلمات کلیدی
AHOR؛ افق A؛ EC؛ رسانایی الکتریکی؛ ERA؛ منطقه رونده برآورد شده؛ EXP؛ قرار گرفتن در معرض؛ GDD؛ روزهای درجه در حال رشد INFR؛ زیر ساخت؛ MAI؛ متوسط افزایش سالیانه؛ خودکار؛ نفوذ؛ PPT؛ بارش؛ RUSI؛ شاخص شهری سریع RAI؛
موضوعات مرتبط
علوم زیستی و بیوفناوری علوم کشاورزی و بیولوژیک جنگلداری
چکیده انگلیسی


- A rapid urban site index (RUSI) model for assessing the quality of urban tree planting sites was tested.
- The RUSI model was found to accurately relate urban tree health and growth.
- The RUSI model requires some minor revisions and training modules need to be developed prior to widespread usage.

Urban trees experience site-induced stress and this leads to reduced growth and health. A site assessment tool would be useful for urban forest managers to better match species tolerances and site qualities, and to assess the efficacy of soil management actions. Toward this goal, a rapid urban site index (RUSI) model was created and tested for its ability to predict urban tree performance. The RUSI model is field-based assessment tool that scores 15 parameters in approximately five minutes. This research was conducted in eight cities throughout the Midwest and Northeast USA to test the efficacy of the RUSI model. The RUSI model accurately predicted urban tree health and growth metrics (P < 0.0001; R2 0.18-0.40). While the RUSI model did not accurately predict mean diameter growth, it was significantly correlated with recent diameter growth. Certain parameters in the RUSI model, such as estimated rooting area, soil structure and aggregate stability appeared to be more important than other parameters, such as growing degree days. Minimal improvements in the RUSI model were achieved by adding soil laboratory analyses. Field assessments in the RUSI model were significantly correlated with similar laboratory analyses. Other users may be able to use the RUSI model to assess urban tree planting sites (<5 min per site and no laboratory analyses fee), but training will be required to accurately utilize the model. Future work on the RUSI model will include developing training modules and testing across a wider geographic area with more urban tree species and urban sites.

ناشر
Database: Elsevier - ScienceDirect (ساینس دایرکت)
Journal: Urban Forestry & Urban Greening - Volume 27, October 2017, Pages 279-286
نویسندگان
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