Data from: Phylogenetic history of vascular plant metabolism revealed using a macroevolutionary common garden

AbstractWhile the fundamental biophysics of C3 photosynthesis is highly conserved across plants, substantial variation in leaf structure and enzymatic activity translates into variability in rates of photosynthesis. Although this variation is well-documented, it remains poorly understood how photosynthetic rates evolve over short and long time scales, and whether these macroevolutionary changes are related to the evolution of key morphological and biochemical leaf traits. Large-scale comparative studies have been hampered by the substantial logistical and statistical challenges in disentangling evolutionary adaptation from environmental acclimation. Here we get around this limitation with a ‘macroevolutionary common garden’ approach in which we measured the metabolic traits Jmax and Vcmax from 111 phylogenetically diverse species in a shared environment. Using several phylogenetic comparative methods, we find substantial phylogenetic signal in these traits at shallow phylogenetic scales, but this signal dissipates quickly at deeper time scales. Leaf morphological traits exhibit phylogenetic signal over much deeper time scales, suggesting that these traits are less evolutionarily constrained than metabolic traits. Furthermore, we find that while morphological and biochemical traits (LMA, Narea and Carea) are weakly predictive of Jmax and Vcmax, evolutionary changes in these traits are mostly decoupled from changes in metabolic traits. This lack of tight evolutionary coupling implies that it may not be possible to use changes in these functional traits in response to global change to infer that photosynthetic strategy is also evolving., Usage notesThere are 3 sets of data files, corresponding to measurements taken for 138 individuals growing at the UBC and Van Dusen Botanical Gardens in Vancouver, BC, Canada. All of these data have been measured on the same set of leaves, between May and September of 2019. n.b. Following data processing and quality checks, only data for 111 species were used in the final analysis. 1. Rapid A/Ci Response (RACiR) data Find these data in neto-bradley_et_al_2021_physiological_data.zip Files are named in the following format yyyy-mm-dd-hhmm_genus_species Provided in .txt format, as output by the LiCor6800 machine. Blurb: RACiR curves (as described in Stinziano et al. 2017) characterize the change in Net photosynthesis A relative to changes in CO2. Functionally this describes the physiological constraints of how quickly and efficiently a plant can take up CO2. During our RACiR curve measurements, CO2 is ramped from 10 ppm to 1010 ppm at a rate of + 100 ppm per minute. While this is ongoing, CO2 accumulates in the chamber such that the true CO2 contents of the chamber are slightly out of sync with the concentration of CO2 measured by the machine. In order to correct for this lag, two curves are measured - a data curve and an empty curve for callibrating the data curve. Data Specifics: The RACiR data is comprised of 2 data files: an \"empty curve\" and a \"data curve\" (see above.) The empty curve characterizes how CO2 accumulates in an empty chamber throughout the course of the A/Ci measurement, and the data curve characterizes a leaf's photosynthetic rates change in response to increasing CO2. Empty curves were collected every hour to two hours - for every empty curve multiple that were collected in close temporal proximity can be corrected (for the lag in CO2 measured - as described above.) Every measurement has its own txt file that was generated by the LiCor6800 machine when the measurement was finalized. Time & Place: RACiR curves were measured on the youngest fully expanded leaves of each of the 138 species studied here. These measurements were taken between May 5th and July 18th 2019 at the UBC and VanDusen Botanical Garden. 2. Morphological data Find these data in neto-bradley_et_al_2021_morphological_data.csv Blurb: After each RACiR curve was measured, the leaf (or several leaves in the case of small leaves/needles) on which this was taken were harvested and put in a sealed bag, which was stored in a cooler overnight. The next morning, the leaves were measured for fresh mass and leaf area. The leaves were then dried for 48 hours in an oven at 60 degrees Celsius. After this the leaves were weighed for dry mass. Time & Place: These measurements were taken the day of, or the following day at the Beaty Biodiversity Research Centre at the UBC Vancouver Campus. 3. Biochemical data Find these data in neto-bradley_et_al_2021_biochemical_data.csv Blurb: Once the leaf tissues were dried, these were sent off for chemical analysis for the Nitrogen and Carbon contents by combustion. Time & Place: These measurements were done at the Analytical Chemical Services Laboratory (at the BC Ministry of Environment and Climate Change Strategy), during September 2019.摘要：尽管C3光合作用（C3 photosynthesis）的基础生物物理机制在植物中高度保守，但叶片结构与酶活性的显著差异会导致光合速率产生变异。尽管该类变异已有大量文献记录，但人们对光合速率在短时间与长时间尺度上的演化模式，以及这些宏演化变化是否与叶片关键形态和生化性状的演化相关仍知之甚少。大型比较研究长期受限于难以区分进化适应与环境驯化的大量后勤与统计挑战。本研究采用“宏演化共同花园”（macroevolutionary common garden）研究策略，在统一环境中对111个系统发育多样性物种的代谢性状Jmax与Vcmax进行了测定。通过多种系统发育比较方法，我们发现这些性状在较浅的系统发育尺度上存在显著的系统发育信号，但该信号在更深的演化时间尺度上会快速消散。叶片形态性状则在更深的时间尺度上表现出系统发育信号，这表明相较于代谢性状，形态性状的演化约束更弱。此外，尽管形态与生化性状（叶面积干重比LMA、单位面积氮含量Narea、单位面积碳含量Carea）对Jmax和Vcmax仅有较弱的预测能力，但这些性状的演化变化大多与代谢性状的变化相互解耦。这种缺乏紧密演化耦合的现象意味着，无法通过植物响应全球变化的这些功能性状变化，推断其光合策略也在发生演化。 使用说明：本数据集包含3组数据文件，对应加拿大不列颠哥伦比亚省温哥华市不列颠哥伦比亚大学（UBC）与范杜森植物园（Van Dusen Botanical Gardens）内种植的138个植株的测定数据。所有数据均采集自2019年5月至9月间的同一组叶片。注意：经过数据处理与质量校验后，最终分析仅使用了111个物种的测定数据。 1. 快速A/Ci响应（Rapid A/Ci Response, RACiR）数据集：该数据存放在neto-bradley_et_al_2021_physiological_data.zip压缩包中。文件命名格式为`yyyy-mm-dd-hhmm_属名_种名`，采用LiCor6800仪器输出的纯文本（.txt）格式存储。 数据集说明：RACiR曲线（详见Stinziano等，2017）用于表征净光合速率A随CO₂浓度变化的响应模式，本质上反映了植物摄取CO₂的速率与效率所受的生理约束。本次RACiR曲线测定中，CO₂浓度以每分钟100 ppm的速率从10 ppm升至1010 ppm。测定过程中，气室内部的CO₂会持续累积，导致气室实际CO₂浓度与仪器测定值存在轻微滞后偏差。为校正该滞后效应，我们同时测定了两条曲线：样品曲线与用于校准的空白曲线。 数据细节：RACiR数据集包含两类数据文件：空白曲线与样品曲线。空白曲线用于表征A/Ci测定过程中空白气室内的CO₂累积情况，样品曲线则用于表征叶片光合速率随CO₂浓度升高的变化规律。空白曲线每1至2小时采集一次，若短时间内采集了多条空白曲线，可按照前述方法校正CO₂测定滞后偏差。每一次测定都会生成独立的.txt文件，由LiCor6800仪器在测定完成时自动导出。 测定时间与地点：本次RACiR曲线测定采集自本研究中138个物种的最幼嫩完全展开叶片，于2019年5月5日至7月18日在不列颠哥伦比亚大学与范杜森植物园完成。 2. 形态学数据集：该数据存放在neto-bradley_et_al_2021_morphological_data.csv文件中。 数据集说明：每完成一条RACiR曲线测定后，我们会采集对应的叶片（若为小型叶片或针叶，则采集多片叶片），装入密封袋后置于冷藏箱中过夜保存。次日清晨，对叶片进行鲜重与叶面积测定，随后将叶片置于60℃烘箱中干燥48小时，最后称量其干重。 测定时间与地点：该批测定于采样当日或次日在不列颠哥伦比亚大学温哥华校区的比蒂生物多样性研究中心（Beaty Biodiversity Research Centre）完成。 3. 生物化学数据集：该数据存放在neto-bradley_et_al_2021_biochemical_data.csv文件中。 数据集说明：叶片组织干燥后，我们将其送至实验室通过燃烧法进行氮与碳含量的化学分析。 测定时间与地点：该批测定于2019年9月在不列颠哥伦比亚省环境与气候变化策略部下属的分析化学服务实验室（Analytical Chemical Services Laboratory）完成。