Data from: Landscape-scale range filling and dispersal limitation of woody plants

This is the data from the article Landscape-scale range filling and dispersal limitation of woody plants (DOI: 10.1111/jbi.14485) Matilda Arnell and Ove Eriksson <br> RANGE FILLING ESTIMATES We estimated landscape-scale range filling for 64 species, each representing a different genera of woody plants, from two different dispersal systems:vertebrate dispersal and abiotic dispersal (mainly wind dispersed). Landscape-scale range filling was estimated as the proportion realized range within the potential range, at a 1km2 resolution. We estimated potential ranges using species distribution models (SDMs) in continuous suitability scores (Seliger et al. 2020). This method avoids loss of information by not converting the SDM outputs into presence/absence using an arbitrary threshold of suitability. Realized ranges were estimated from presence records, restricting the estimations to areas with high sampling efforts: low ignorance areas (Ruete 2015), in order to increase the likelihood that absences represented true absences. Regional range filling was estimated for a 5000 pixel subset of the low ignorance areas. The aditional low ignorance pixels and accompanying occurence datat was used when trining the SDMs. Please consult to the original article as well as the R-script "range filling analyses_Arnell_Eriksson_2022.R" for details on regional range filling estimates. LOCATION We estimated regional range filling in the nemoral and boreo-nemoral vegetation zones in Sweden. The species distribution models providing the estimated suatability scores were trained with ocurrence data, climate and land-use data from all of Sweden. PHYLOGENETIC REGRESSION We thested the effect of dispersal system and habitat affinities on landscape-scale range filling using phylogenetic regressions. Phylogenetic information was obtained from Zanne et al. (2014). Please consult the original article as well as the R-script "PGLS models_Arnell_Eriksson_2022.R" for details on regional range filling estimates. HABITAT AFFINITIES Plant indicator values (Tyler et al. 2021) used to assess the effect of habitat affinities: Light indicator value Moisture indicator value <br> Please contact Matilda Arnell ([e-mail]) for information or collaboration. Please cite also the original article when using these data (DOI: 10.1111/jbi.14485). <br> REFERENCES Ruete, A. (2015). Displaying bias in sampling effort of data accessed from biodiversity databases using ignorance maps. Biodiversity Data Journal, 3, e5361. https://doi.org/10.3897/BDJ.3.e5361 Seliger, B. J., McGill, B. J., Svenning, J., &amp; Gill, J. L. (2020). Widespread underfilling of the potential ranges of North American trees. Journal of Biogeography, 48(2), 359–371. https://doi.org/10.1111/jbi.14001 Tyler, T., Herbertsson, L., Olofsson, J., &amp; Olsson, P. A. (2021). Ecological indicator and traits values for Swedish vascular plants. Ecological Indicators, 120, 106923. https://doi.org/10.1016/j.ecolind.2020.106923 Zanne, A. E., Tank, D. C., Cornwell, W. K. et al. (2014). Three keys to the radiation of angiosperms into freezing environments. Nature, 506(7486), 89–92. https://doi.org/10.1038/nature12872本数据集源自论文《木本植物的景观尺度分布区填充与扩散限制》（Landscape-scale range filling and dispersal limitation of woody plants，DOI: 10.1111/jbi.14485），作者为Matilda Arnell与Ove Eriksson。 ### 分布区填充估算 本研究针对64种木本植物开展景观尺度分布区填充估算，每种植物分属不同的木本植物属，涵盖两类扩散系统：脊椎动物扩散与非生物扩散（主要为风媒扩散）。景观尺度分布区填充以1平方千米分辨率下，潜在分布区内实际分布区的占比进行计算。 潜在分布区通过物种分布模型（SDMs）生成连续适宜性得分进行估算（Seliger et al. 2020），该方法无需通过任意适宜性阈值将物种分布模型输出转换为存在/不存在数据，避免了信息损失。实际分布区基于物种出现记录进行估算，且将估算范围限定在低信息缺失区域（Ruete 2015）——即采样强度较高的区域，以确保物种缺失记录真实反映物种未出现的情况。 区域尺度分布区填充通过低信息缺失区域内的5000个像素子集进行估算，其余低信息缺失像素及配套的物种出现数据则用于训练物种分布模型。关于区域尺度分布区填充估算的详细方法，请参阅原论文及R脚本"range filling analyses_Arnell_Eriksson_2022.R"。 ### 研究区域 本研究在瑞典的温带落叶林与北温带落叶林植被带开展区域尺度分布区填充估算。用于生成适宜性得分的物种分布模型，其训练数据涵盖瑞典全境的物种出现记录、气候数据与土地利用数据。 ### 系统发育回归分析 本研究采用系统发育回归方法，检验扩散系统与生境偏好对景观尺度分布区填充的影响，系统发育数据源自Zanne等人（2014）的研究。关于区域尺度分布区填充估算的详细方法，请参阅原论文及R脚本"PGLS models_Arnell_Eriksson_2022.R"。 ### 生境偏好指标 本研究采用植物指示值（Tyler et al. 2021）评估生境偏好的影响，包括光照指示值与湿度指示值。 如需获取相关信息或开展合作，请联系Matilda Arnell（邮箱：[e-mail]）。使用本数据集时，请同时引用原论文（DOI: 10.1111/jbi.14485）。 ### 参考文献 1. Ruete, A. (2015). 利用无知地图展示生物多样性数据库访问数据的采样偏差. 《生物多样性数据期刊》, 3, e5361. https://doi.org/10.3897/BDJ.3.e5361 2. Seliger, B. J., McGill, B. J., Svenning, J., & Gill, J. L. (2020). 北美树木潜在分布区的普遍填充不足. 《生物地理学杂志》, 48(2), 359–371. https://doi.org/10.1111/jbi.14001 3. Tyler, T., Herbertsson, L., Olofsson, J., & Olsson, P. A. (2021). 瑞典维管植物的生态指示值与功能性状值. 《生态指标》, 120, 106923. https://doi.org/10.1016/j.ecolind.2020.106923 4. Zanne, A. E., Tank, D. C., Cornwell, W. K. 等. (2014). 被子植物辐射适应寒冷环境的三大关键因素. 《自然》, 506(7486), 89–92. https://doi.org/10.1038/nature12872