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城市森林表层土壤性质的空间变异性:迈向具有代表性和稳健性的采样设计

Spatial variability of urban forest topsoil properties: towards representative and robust sampling design.

作者信息

Galle Nadina, Brinton William, Vos Robin, Duarte Fábio, Collier Marcus, Ratti Carlo, Pilla Francesco

机构信息

Senseable City Laboratory, Massachusetts Institute of Technology, MIT 9-216, 77 Massachusetts Avenue, Cambridge, MA, 02139, USA.

Spatial Dynamics Lab, College of Engineering and Architecture, University College Dublin, Belfield, Dublin, D04 V1W8, Ireland.

出版信息

Open Res Eur. 2023 Oct 18;1:45. doi: 10.12688/openreseurope.13502.2. eCollection 2021.

Abstract

Soil spatial variability is a major concern when deciding how to collect a representative topsoil sample for laboratory analysis. Sampling design to capture site-specific variability is documented in the agricultural literature, but poorly understood for urban forest soils where soils may be characterized by strong horizontal and vertical variability and large temporal anthropogenic disturbances. This paper evaluates the spatial variability of selected topsoil properties under urban trees to define a statistically robust sampling design that optimizes the number of samples to reliably characterize basal soil respiration (BSR), a property associated with soil health. To provide a reference on variability, two additional soil properties were measured, unrelated to BSR: electrical conductivity (EC) and bulk density (BD). Thirteen sampling sites comprising both park and street trees ( ) were selected in Cambridge, MA, USA. Results indicate street tree topsoil had approximately twice as much variation, requiring more intensive sampling, as did park tree topsoil, even though street trees had smaller soil sampling zones, constricted by tree pits. The variability of BSR was nearly identical to that of EC, and BD results varied least. A large number of samples would be required for acceptable levels of statistical reliability (90% CI - 10% ER) of 44.4, 41.7, and 6.4 for BSR, EC, and BD, respectively, whereas by accepting a lower level of certainty (80% CI - 20% ER) the number of required soil samples was calculated as 6.8, 6.4, and 0.4 for BSR, EC, and BD, respectively. The use of EC testing as a baseline measure to determine spatial variation in the topsoil is proposed, to alleviate the financial implications of more expensive BSR testing. Factors of topsoil disturbance and soil access restrictions at sites with severe root-sidewalk conflicts and the overall generalizability of the results are also discussed.

摘要

在决定如何采集具有代表性的表层土壤样本用于实验室分析时,土壤空间变异性是一个主要问题。农业文献中记载了用于捕捉特定地点变异性的采样设计,但对于城市森林土壤来说,人们对此了解甚少,因为城市森林土壤可能具有强烈的水平和垂直变异性以及较大的人为时间干扰。本文评估了城市树木下选定表层土壤属性的空间变异性,以确定一种统计上稳健的采样设计,该设计可优化样本数量,以可靠地表征与土壤健康相关的基础土壤呼吸(BSR)属性。为了提供变异性参考,还测量了另外两个与BSR无关的土壤属性:电导率(EC)和容重(BD)。在美国马萨诸塞州剑桥市选择了13个采样点,包括公园和街道树木( )。结果表明,尽管街道树木的土壤采样区因树池而受限较小,但街道树木表层土壤的变异性大约是公园树木表层土壤的两倍,需要更密集的采样。BSR的变异性与EC几乎相同,而BD结果的变异性最小。对于BSR、EC和BD,分别需要44.4、41.7和6.4个样本才能达到可接受的统计可靠性水平(90%置信区间 - 10%误差范围),而如果接受较低的确定性水平(80%置信区间 - 20%误差范围),则BSR、EC和BD所需的土壤样本数量分别计算为6.8、6.4和0.4个。建议使用EC测试作为确定表层土壤空间变异的基线测量方法,以减轻更昂贵的BSR测试的财务影响。还讨论了在根系与人行道冲突严重的地点表层土壤干扰和土壤获取限制因素以及结果的总体普遍性。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/9576/10587747/63079f25ded9/openreseurope-1-18020-g0000.jpg

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