LCZO -- Soil Survey -- Northeastern Puerto Rico and the Luquillo Mountain -- (2011-2012)

We sampled soils from 216 profiles representing 24 sites in the El Yunque National Forest to determine amounts C, N and neutral-salt-extractable Ca++, Mg++ and K+. Following the classic paradigm, we assessed the influence of climate (modeled precipitation, modeled temperature and/or elevation as a surrogate variable for both), forest type (tabonuco, colorado, palm), parent material (quartz diorite, volcaniclastics), and topography (catena positions ridge, slope, valley and % slope) on the distribution of these nutrients. To separate the effects of vegetation from those of climate, half of the sites were located between 500 and 700 m in the three forest types where rainfall and temperature were not significantly different. Using a combination of ANOVA (or Kruskal-Wallis) and univariate regression trees we determined that the amount of carbon in the top 80 cm of soil was influenced primarily by forest type (c > p > t) probably driven by differences in litter and/or root C:N ratios. Topographic position was significantly correlated with C amount (v > s, r), with the higher C amounts in the valleys probably driven by low O2 levels. Bedrock type was significantly correlated with C amount in c and p stands, but not in the tabonuco type. N was strongly correlated with C as expected. Exchangeable Ca was different across forest types (t > c, p) and bedrock type (qd > vc). Mg and K were differed by forest type, but not by bedrock type (t > c, p) or any other variables.

The next phases of this project are (1) to determine levels of these nutrients below the root zone (80-140 cm) and the factors controlling their distribution; and (2) establish field experiments to test the results of the regression trees which indicate that the C:N ratio of litter and/or root inputs is the most important variable influencing C distribution. The latter represents a first step in exploring the usefulness of regression trees as a way of sorting out the relative importance of each of the state factors (climate, topography, organisms, parent material and time) in the classic paradigm relating environmental variables to soil properties.

Soil C differs markedly across forest types (c> p> t, p s, r, p

本研究自巴拿马雨林国家森林公园的24个地点采集了216个土壤剖面样本，以测定其中碳、氮以及中性盐提取的钙离子、镁离子和钾离子的含量。遵循经典范式，本研究评估了气候（模拟降水、模拟温度以及/或海拔作为气候和海拔的替代变量）、森林类型（塔博努科、科罗拉多、棕榈）、母质（石英二长岩、火山碎屑岩）以及地形（流域位置、山脊、斜坡和斜坡百分比）对这些营养元素分布的影响。为区分植被与气候的影响，选取了位于三种森林类型（塔博努科、科罗拉多、棕榈）之间，海拔500至700米，且降水和温度无显著差异的半数地点。通过结合方差分析（或Kruskal-Wallis检验）和单变量回归树分析，确定了土壤表层80厘米中碳含量主要受森林类型影响（c > p > t），这可能是由于凋落物和/或根系碳氮比率的差异所致。地形位置与碳含量呈显著相关性（v > s, r），山谷中的碳含量较高可能是由于低氧水平所驱动。基岩类型与c和p类型的碳含量显著相关，但与塔博努科类型无关。氮含量与碳含量呈强相关性，如预期。可交换钙含量在不同森林类型（t > c, p）和基岩类型（qd > vc）中存在差异。镁和钾含量在不同森林类型中存在差异，但与基岩类型（t > c, p）或任何其他变量无关。

本项目下一阶段的任务包括：（1）确定这些营养素在根系以下（80-140厘米）的分布水平和控制其分布的因素；（2）建立田间实验以验证回归树分析的结果，这些结果表明，凋落物和/或根系输入的碳氮比是影响碳分布的最重要变量。后者是探索回归树作为区分经典范式中所涉及的状态因素（气候、地形、生物、母质和时间）相对重要性的有用工具的第一步。

土壤碳在不同森林类型之间存在显著差异（c> p> t, p s, r, p）