Dataset for 'Invasive <i>Prunus serotina </i>and <i>Robinia pseudoacacia </i>impact on understory vegetation is species-, habitat- ,and season-specific'

We conducted the study in western Poland managed forests, in five forest inspectorates: Babki, Czerniejewo, Jarocin, Konstantynowo, and Łopuchówko (Fig. 2). We located study plots between 51° 59′ 4.08′′ and 52° 40′ 9.36′′ N and 16° 35′ 28.98′′ and 17° 37′ 13.26′′ E, in two geographical regions: the Greater Poland Lakeland (northern part) and Greater Poland Lowland (southern part). The climatic conditions are similar in the study area, with an annual temperature of 8.5 °C and mean annual precipitation of 500-550 mm (BDL 2024). Designing the study we aimed to cover the quantitative gradient of invader abundance, as most of previous studies focused on comparing invaded and non-invaded sites. Assessment of invader quantity using precise measurements would take much time and effort, therefore we decided to select study plots based on invader cover and then, after measurement, quantify the abundance using aboveground biomass, following the approach in our previous study (Bury and Dyderski 2025). During plot selection we search for control plots (zero individuals of studied invaders &gt;1.3 m height), medium (&lt;30% cover) and high (&gt;50%). We decided to cover two habitat-related environmental contexts: nutrient-rich habitats that are typical of studied species in the native range, and nutrient-poor, where these species had been introduced (Starfinger et al. 2003, Cierjacks et al. 2013). Nutrient-poor sites included Leucobryo-Pinetum W. Mat. (1962) 1973 communities or secondary P. sylvestris forests. In our study, nutrient-rich sites include different subtypes of Galio sylvatici-Carpinetum betuli Oberd. 1957 communities or secondary Quercus spp. forests. Some areas had characteristics of poorer communities or slightly more fertile ones, with species characteristic of Potentillo albae-Quercetum Libb. 1933 or Querco-roboris Pinetum Mat. et Polak. 1955 s.l. We also included two management contexts: stands in the middle of rotation age and close to rotation age, as these age classes differ in light conditions beneath stand canopies. In total we established 160 plots (500 m2), including 32 control plots (8 replications × 2 habitat types × 2 stand age classes), 64 plots with R. pseudoacacia (8 replications × 2 invasion levels × 2 habitat types × 2 stand age classes) and 64 plots with P. serotina (same as R. pseudoacacia). The distance between plots of particular variants were higher than 5 km.To better describe the invader quantity and invasion phase in the autumns of 2021, 2022, 2023 we measured all trees &gt;1.3 m height in each plot. We measured the diameter at breast height (DBH) of all the individuals on the 102 plots. On 58 plots, we accurately measured the diameter at the breast height of trees thicker than 5 cm. We counted trees thinner than 5 cm by species. Then, from a database of 102 plots for each species, we calculated the average thickness of individuals thinner than 5 cm. We imputed these mean DBH in the mentioned 58 plots (see Table S1 for mean and SD values). Then, we used published allometric formulas (Table S2-S3) to calculate the aboveground biomass for individual trees and stands (in the file)<br>We used the modified nine-scaled Braun-Blanquet method (r ─ 1-2 ind.; + ─ &lt;1%; 1 ─ 1-3%; 2m ─ 3-10%; 2a ─ 10-18%; 2b ─ 18-25%; 3 ─ 25-50%; 4 ─ 50-75%; 5 ─ &gt; 75%) to assess the cover of particular understory species of vascular plants. We assessed both herbaceous and woody plants (up to 0.5 m height) on four randomly distributed squared 25 m2 subplots. We made an understory survey in the spring (May) and summer (July) of 2021, 2022, and 2023. For the analysis purposes, we used following coverages for each Braun-Blanquet class (r = 0.1%; + = 0.5%; 1 = 4%; 2m = 7.5%; 2a = 15%; 2b = 20%; 3 = 37.5%; 4 = 62.5%; 5 = 87.5%).We aggregated the results at the plot level by averaging species cover from four subplots

本研究在波兰西部人工管理森林中开展，涉及5个森林监察区：Babki、Czerniejewo、Jarocin、Konstantynowo以及Łopuchówko（见图2）。研究样地的地理位置介于北纬51°59′4.08″至52°40′9.36″、东经16°35′28.98″至17°37′13.26″之间，覆盖两大地理区域：大波兰湖原区（北部）和大波兰低地区（南部）。研究区域气候条件相近，年平均气温8.5℃，年平均降水量500~550mm（BDL 2024）。本次研究旨在覆盖入侵物种多度的数量梯度，因既往多数研究仅聚焦于入侵与未入侵样地的对比。若通过精准测量评估入侵物种多度需耗费大量时间与人力，因此我们参考前期研究（Bury与Dyderski 2025）的方法，先基于入侵物种盖度筛选样地，后续通过地上生物量量化其多度。样地筛选阶段，我们选取了3类样地：对照样地（研究目标入侵物种株高>1.3m的个体数为0）、中度入侵样地（盖度<30%）以及高度入侵样地（盖度>50%）。同时覆盖两类生境相关的环境背景：一是入侵物种原生分布区典型的富营养化生境，二是该物种被引入的贫营养化生境（Starfinger等2003，Cierjacks等2013）。贫营养生境包括Leucobryo-Pinetum W. Mat. (1962) 1973群落或次生欧洲赤松（Pinus sylvestris）林；富营养生境则包括Galio sylvatici-Carpinetum betuli Oberd. 1957群落的不同亚型或次生栎属（Quercus spp.）林。部分区域兼具贫营养与较肥沃生境的特征，伴生有Potentillo albae-Quercetum Libb. 1933或Querco-roboris Pinetum Mat. et Polak. 1955 s.l.的特征物种。此外还涵盖两类经营背景：林分处于轮伐期中期以及接近轮伐期的林分，这两类林分的林冠下光照条件存在差异。最终共设置160个500㎡的样地，其中对照样地32个（8次重复×2种生境类型×2种林分年龄组）；刺槐（Robinia pseudoacacia）入侵样地64个（8次重复×2种入侵等级×2种生境类型×2种林分年龄组）；黑樱桃（Prunus serotina）入侵样地64个（设置方式与刺槐入侵样地一致）。同类型样地之间的间距均大于5km。为更精准描述2021、2022、2023年秋季的入侵物种多度与入侵阶段，我们对每个样地内株高>1.3m的所有树木开展调查。其中102个样地测量了所有个体的胸径（DBH）；剩余58个样地中，仅精准测量了胸径>5cm的树木胸径，胸径<5cm的树木则按物种统计数量。随后，我们基于102个样地的物种数据，计算了胸径<5cm个体的平均胸径，并将该均值代入58个样地的胸径数据中（均值与标准差详见表S1）。最后，利用已发表的异速生长公式（表S2~S3）计算单株树木及林分的地上生物量（详见附件文件）。我们采用修正的9级Braun-Blanquet盖度分级法（Braun-Blanquet）（r ─ 1~2株；+ ─ <1%；1 ─ 1%~3%；2m ─ 3%~10%；2a ─10%~18%；2b ─18%~25%；3 ─25%~50%；4 ─50%~75%；5 ─>75%），评估样地内各维管植物下层物种的盖度。调查在4个随机布设的25㎡方形小样方中开展，涵盖草本植物与株高≤0.5m的木本植物。我们分别于2021、2022、2023年的春季（5月）与夏季（7月）开展下层植被调查。为便于分析，我们将各Braun-Blanquet等级转换为对应盖度值：r=0.1%，+=0.5%，1=4%，2m=7.5%，2a=15%，2b=20%，3=37.5%，4=62.5%，5=87.5%。最终以样地为单位，对4个小样方的物种盖度取平均值，完成数据聚合。