Abstract
Forest plays a key role in spatial distribution of rainfall and nutrients at fine spatial scales. Areas of localized rainfall and nutrient input at the soil surface may have a large effect on several hydrological and biogeochemical processes. In this paper, a Douglas-fir stand was revisited to evaluate the changes in the throughfall spatial distribution and its temporal stability due to forest growth and thinning. We used 32 funnel-type collectors distributed in a random stratified array within a 0.2 ha plot to measure throughfall amounts from February to November 2015. The throughfall variability was much lower as compared to the values reported ~25 years ago in the same site. We further assessed the spatial patterns of throughfall in spring and summer. We detected a spatial correlation length of 12 m and 8 m for spring and summer, respectively, which are higher than the values reported for other mature Douglas-fir forests in similar climatic conditions. Temporal stability plots confirmed that detected spatial patterns were stable in time.
Highlights
Forest ecosystems play a significant role in the redistribution of water and nutrients that reaches the terrestrial surface by means of throughfall (Tf ) and stemflow (Sf ) [1,2,3,4]
Less common in the literature is the description of spatial patterns of throughfall using geostatistical methods, which can be used to produce Tf distribution maps as long as structured variograms are found
The spatial variability of Tf was lower than that reported by similar studies
Summary
Forest ecosystems play a significant role in the redistribution of water and nutrients that reaches the terrestrial surface by means of throughfall (Tf ) and stemflow (Sf ) [1,2,3,4]. Throughfall and stemflow patterns below forest canopies have been shown to be highly variable in time and space [2,5,6]. The spatial variability of throughfall is known to affect the accuracy of estimates on stand-scale interception losses [12,13]. Several studies demonstrated that CV decreases asymptotically with the increase in size of the rainfall events, e.g., [13,15,17,18,19]. CV decreases with the increase of the total rainfall depth in studies that aggregate Tf from several events at larger temporal resolution (i.e., weekly, monthly) [6]. Keim et al [20]
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