Belowground traits predict juvenile grass demography in microsites

Plant functional traits can be a powerful tool for predicting species demography in response to variable environmental conditions. However, accurate predictions of juvenile plant response require ontogenetically relevant traits that capture response to microsite variability. This is particularly important when considering drivers of seedling emergence, survival, growth, and recruitment of species in the context of population persistence or community assembly. We tested the effect of two different microsites on juvenile demography for eight perennial grass species in a semi-arid system in Colorado along the western edge of the Great Plains. We used seed and root functional traits across multiple life stages to predict these responses and identify mechanisms driving species’ emergence, survival, growth, and recruitment. Contrary to our expectations, we found that microsites with increased soil moisture (i.e., furrows) had a negative effect on grass emergence early in the season but n..., To determine emergence and recruitment response to microsites, we counted grass abundance throughout the growing season. In addition to using row-level abundances to determine emergence and recruitment, we tracked individual survival and growth of a subset of individuals across three life stages. We used seed and seedling trait data obtained from the greenhouse trait sampling effort described in (Larson, 2021). To quantify the effects of the furrows on microsite conditions, we measured soil moisture, soil temperature, and surface temperature within these rows with TOMST TMS-4 loggers (Wild et al., 2019)., , # Belowground traits predict juvenile grass demography in microsites [https://doi.org/10.5061/dryad.c866t1ghq](https://doi.org/10.5061/dryad.c866t1ghq) ## Description of the data and file structure We tested the effect of two different microsites on juvenile demography for eight perennial grass species in a semi-arid system in Colorado along the western edge of the Great Plains. We used seed and root functional traits across multiple life-stages to predict these responses and identify mechanisms driving species’ emergence, survival, growth, and recruitment. ### Files and variables #### File: Grass\_Traits.csv **Description:** ##### Variables * species: species ID codes * c3_c4: photosythetic pathway * canopy_e: canopy volume per day for the emergent life stage (2 weeks); cm3/day * height_e: height per day for the emergent life stage (2 weeks); cm/day * biomass_e: biomass per day for the emergent life stage (2 weeks); g/day * rootlength_e: root length per day for the emergent li...植物功能性状（plant functional traits）是预测物种响应环境变化的种群统计学特征的有力工具。然而，要精准预测幼龄植物的响应，需要能够捕捉微生境（microsite）变异的个体发育相关性状。在探讨种群维持或群落构建背景下的物种幼苗出土、存活、生长与定植驱动因子时，这一点尤为关键。 本研究在位于大平原（Great Plains）西缘、科罗拉多州的半干旱生态系统中，针对8种多年生草本植物，检验了两种不同微生境对其幼龄种群统计学特征的影响。我们利用多生命阶段的种子与根系功能性状来预测上述响应，并解析驱动物种出土、存活、生长与定植的内在机制。与我们的预期相反，我们发现土壤湿度更高的微生境（即垄沟）在季节早期对草本植物的出土产生了负效应，但[原文内容截断]。 为明确幼苗出土与定植对微生境的响应，我们在整个生长季统计了草本植物的多度。除利用行级多度来判断出土与定植情况外，我们还追踪了亚群个体在三个生命阶段的存活与生长状况。我们采用了Larson（2021）所述的温室性状采样工作所获得的种子与幼苗性状数据。为量化垄沟对微生境条件的影响，我们使用TOMST TMS-4记录仪（TOMST TMS-4 loggers，Wild等，2019）测定了这些样行内的土壤湿度、土壤温度与地表温度。 # 地下性状预测微生境中幼龄草本的种群统计学特征 https://doi.org/10.5061/dryad.c866t1ghq ## 数据与文件结构说明 本研究在位于大平原西缘、科罗拉多州的半干旱生态系统中，针对8种多年生草本植物，检验了两种不同微生境对其幼龄种群统计学特征的影响。我们利用多生命阶段的种子与根系功能性状来预测上述响应，并解析驱动物种出土、存活、生长与定植的内在机制。 ### 文件与变量 #### 文件：Grass_Traits.csv **描述：** ##### 变量 * species：物种编号（species ID codes） * c3_c4：光合途径（photosynthetic pathway） * canopy_e：萌发阶段（2周）的日冠层体积；单位：cm³/天 * height_e：萌发阶段（2周）的日株高；单位：cm/天 * biomass_e：萌发阶段（2周）的日生物量；单位：g/天 * rootlength_e：萌发阶段的日根长[原文内容截断]