کد مقاله کد نشریه سال انتشار مقاله انگلیسی نسخه تمام متن
4392850 1618241 2015 4 صفحه PDF دانلود رایگان
عنوان انگلیسی مقاله ISI
Amount vs. temporal pattern: On the importance of intra-annual climatic conditions on tree growth in a dry environment
ترجمه فارسی عنوان
مقدار در مقابل الگوی زمانی: بر اهمیت شرایط آب و هوای داخل سالانه بر رشد درختان در محیط خشک
موضوعات مرتبط
مهندسی و علوم پایه علوم زمین و سیارات فرآیندهای سطح زمین
چکیده انگلیسی


• We examine trees' response to rainfall timing and proportion of large events.
• Dry season length did not have a significant effect on growth.
• Large rain events (LRE) positively affected growth under dry conditions.
• A big increase in LRE may balance the impact of annual rain decline on growth.

Forests in semi-arid regions are at particular risk for climate change impacts. Although it has been recently acknowledged that vulnerability to climate change depends on changes in climatic variability and the occurrence of extreme events, and not just the mean climatic conditions, the relative importance of such effects remains largely unexamined. In the present study we investigated the effects of intra-annual rainfall distribution characteristics, as opposed to total rainfall amount, on tree growth. More specifically, proportion of large rain events and dry season length – two climatic characteristics considered key to the survival of planted Pinus halepensis forests in a semi-arid region – were evaluated based on a tree-rings dataset. Dry season length did not have a significant effect on growth, highlighting the high resilience of this species when facing harsh climatic conditions. Proportion of large rain events had a positive effect on growth under dry conditions, as expected. The magnitude of this effect was relatively small, compared to that of total rainfall amount. Nevertheless, an increase in the proportion of large rain events as a result of climate change may potentially balance the decline in its total amount, in terms of trees growth rate, to an extent quantifiable using our statistical model predictions.

ناشر
Database: Elsevier - ScienceDirect (ساینس دایرکت)
Journal: Journal of Arid Environments - Volume 118, July 2015, Pages 65–68
نویسندگان
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