Distinguishing Impatiens capensis from Impatiens pallida (Balsaminaceae) using leaf traits

Leaf collections We identified three nature reserves (sites) on the University of Wisconsin – Madison campus in Madison, Wisconsin, USA: Muir Woods, Bill’s Woods, and Picnic Point Marsh (Fig. 1 in published paper) that contained co-occurring populations of I. capensis and I. pallida. These sites varied in light, soil moisture, and likely genetic composition. Within each site, we collected 3 leaves from each of 5-10 randomly selected plants of each species within each of 3 sub-locations (areas). We sampled until we reached 25 plants of each species in each site. We collected from areas where both species were growing in intermixed stands to standardize the range of environmental variability sampled across species. We could only find two areas of intermixed Impatiens in Bill’s Woods so we sampled two additional areas where only one of the species was present. We could only find two areas of I. capensis to sample in Muir Woods. We collected leaves from three standardized locations within each plant (Supp. Fig. 1 in published paper) to test for differences in leaf shape or size depending on where they were growing on the plant (essentially leaf height, age, and susceptibility to herbivory and disease). We defined leaf position 1 as the lowest leaf on the plant borne on the main stem. The second leaf came from the middle of a branch that diverged from the main stem in the leafiest region of the plant. The third leaf was the fully expanded leaf closest to the top of the plant on the main stem. We collected leaves into envelopes labeled with the leaf position, species, site, and area and pressed them in a plant press. All leaves were collected between August and September of 2017. Leaf scanning and image processing We scanned pressed leaves one at a time using a CanoScan 8800F desktop scanner at a resolution of 300dpi in color photo mode with auto exposure settings and saved the scans in TIFF format. All leaves were scanned with the leaf tip positioned at twelve o’clock on the scanner bed. Using the program FIJI (Schindelin et al. 2012), we converted leaf scans into binary black and white images. We removed any leaves that did not have entire margins and filled in any interior holes using the black paint tool. We removed leaf petioles in the scans by painting over them with the white paint tool (petioles were torn at variable lengths when collected). We retained a total of 342 leaf blade silhouettes for morphometric analysis. The exposure settings on our original scans were not standardized to allow for meaningful comparisons of color, so we re-scanned “leaf 2” from 2 randomly selected individuals from each area and species (N = 34) to investigate differences in leaf color. We used leaf 2 for the color analysis because it was most representative of leaf color on the plant as a whole based on our field observations. Often, leaf 1 was partially senesced and leaf 3 was too young to have developed full color. We used a color card to ensure the color parameters of all leaves were standardized across scans. Using FIJI, we adjusted color threshold values to exclude the ink markings on each leaf (denoting leaf number) from the analysis. We then generated a distribution of the RGB values present in each leaf (FIJI: Analyze, Color Histogram) and calculated the mean, mode, and variance of this leaf color distribution. We chose the mode (as opposed to the mean) because it is not influenced by minor blemishes and imperfections on the leaf surface and is likely closer to the color we perceive than the mean value.叶片采集 我们在美国威斯康星州麦迪逊市的威斯康星大学麦迪逊分校校园内确定了三处自然保护区样地：缪尔树林（Muir Woods）、比尔树林（Bill’s Woods）与野餐点沼泽（Picnic Point Marsh），即已发表论文中的图1，这些样地共存有I. capensis与I. pallida的种群。各采样点在光照条件、土壤湿度以及潜在遗传组成上均存在差异。 在每个样地内，我们于3个亚采样区域中，从每个物种的5至10株随机选取的植株上各采集3片叶片。我们持续采样直至每个样地内每个物种的样本量达到25株。为标准化跨物种采样的环境变异范围，我们选择两种植物混生的区域开展采集工作。但在比尔树林中仅能找到两处凤仙花混生区域，因此我们额外增设了两处仅单一种群分布的区域进行采样。此外在缪尔树林中仅能找到两处可采样的I. capensis分布区。 我们从每株植株的三个标准化位置采集叶片（对应已发表论文的补充图1），以探究叶片形状或大小随植株上生长位置的差异，这些位置本质上对应叶片的着生高度、发育年龄以及受草食动物和病害侵袭的程度。我们将叶位1定义为主茎上最低的叶片；叶位2取自植株最繁茂区域中从主茎分出的枝条中部；叶位3为主茎上靠近植株顶端的完全展开叶片。我们将采集的叶片装入标注有叶位、物种、样地和区域的信封，并置于植物标本夹中压制。所有叶片均采集于2017年8月至9月期间。 叶片扫描与图像处理 我们使用CanoScan 8800F台式扫描仪，以300dpi分辨率、彩色照片模式并启用自动曝光设置，逐张扫描压制后的叶片，并将扫描结果保存为TIFF格式。所有叶片扫描时均将叶尖置于扫描仪台的12点钟位置。我们使用FIJI软件（Schindelin等人，2012）将叶片扫描件转换为二值黑白图像。我们剔除了叶缘不完整的叶片，并使用黑色画笔工具填补图像内的孔洞。由于采集时叶柄被扯断的长度不一，我们使用白色画笔工具涂抹去除扫描图像中的叶柄。最终我们共保留342个叶片剪影用于形态计量分析。 初始扫描的曝光设置未标准化，无法进行有意义的颜色比较，因此我们从每个区域和物种的2株随机选取个体中重新扫描"叶位2"的叶片（样本量N=34），以探究叶片颜色差异。我们选择叶位2进行颜色分析，因为根据野外观察，该叶位最能代表整株植物的叶片颜色。通常叶位1的叶片会部分衰老，而叶位3的叶片过于幼嫩，尚未形成完整的颜色。我们使用色卡确保所有叶片的颜色参数在扫描过程中保持标准化。 使用FIJI软件，我们调整颜色阈值以排除叶片上的墨水标记（用于标注叶位编号）参与分析。随后我们生成了每片叶片内RGB颜色值的分布（FIJI软件操作：分析→颜色直方图），并计算了该叶片颜色分布的均值、众数和方差。我们选择众数（而非均值）作为统计量，因为它不受叶片表面微小瑕疵和缺陷的影响，且相较于均值，更贴近我们肉眼感知的叶片颜色。