A data-driven evaluation of lichen climate change indicators in Central Europe

被引:0
|
作者
Matthew P. Nelsen
H. Thorsten Lumbsch
机构
[1] The Field Museum,Negaunee Integrative Research Center
来源
Biodiversity and Conservation | 2020年 / 29卷
关键词
Lichens; Climate change; Biomonitoring; Europe;
D O I
暂无
中图分类号
学科分类号
摘要
Lichens are widely utilized as indicators of air quality, forest health and climate change. In Central Europe, specific lichens have been designated as climate change indicators; however, the lichen biota of central Europe has been substantially altered by air pollution and only re-established during the past decades—complicating the interpretation of recent changes in lichen composition. To assess their validity as climate change indicators, we aggregated georeferenced records of these taxa and compared their historic and modern distributions. Modern distributions substantially differed for fewer than half of the indicator taxa with sufficient data to enable evaluation—reinforcing their utility as climate change indicators. However, modern distributions for approximately half of the taxa evaluated were largely confined to historically suitable climates—raising questions about their utility as climate change indicators. We were unable to model historic distributions for nearly two-thirds of all indicator taxa due to insufficient data. About one-third of these had multiple modern records but one or fewer historic records, suggesting they may indeed be expanding their range; however, about half had comparable or greater numbers of historic records relative to modern records, complicating their interpretation as climate change indicators. Together, our work illustrates that distributions for fewer than half of the lichen climate change indicators have substantially shifted in the recent past, and calls into question whether the remaining designated taxa are indeed strong positive indicators of climate change. We argue that more quantitative, evidence-based derivations of climate change indicators are required to accurately detect climate change.
引用
收藏
页码:3959 / 3971
页数:12
相关论文
共 50 条
  • [11] Data-driven projections suggest large opportunities to improve Europe’s soybean self-sufficiency under climate change
    Nicolas Guilpart
    Toshichika Iizumi
    David Makowski
    Nature Food, 2022, 3 : 255 - 265
  • [12] A Data Driven Approach for Analyzing the Effect of Climate Change on Mosquito Abundance in Europe
    Tsantalidou, Argyro
    Arvanitakis, George
    Georgoulias, Aristeidis K.
    Akritidis, Dimitris
    Zanis, Prodromos
    Fornasiero, Diletta
    Wohlgemuth, Daniel
    Kontoes, Charalampos
    REMOTE SENSING, 2023, 15 (24)
  • [13] Newly found and rediscovered hornworts (Anthocerotophyta) in Poland: Indicators of climate change impact in Central Europe
    Plasek, Vitezslav
    Cihal, Lukas
    Muller, Frank
    Poltl, Martina
    Wierzgon, Mariusz
    Ochyra, Ryszard
    PHYTOKEYS, 2024, (248) : 237 - 261
  • [14] Contribution of data-driven methods to risk reduction and climate change adaptation in Hungary and beyond
    Birinyi, Edina
    Lakatos, Boglarka O.
    Belenyesi, Marta
    Kristof, Daniel
    Hetesi, Zsolt
    Mrekva, Laszlo
    Mikus, Gabor
    IDOJARAS, 2023, 127 (04): : 421 - 446
  • [15] Accountability and data-driven urban climate governance
    Hughes, Sara
    Giest, Sarah
    Tozer, Laura
    NATURE CLIMATE CHANGE, 2020, 10 (12) : 1085 - 1090
  • [16] Data-Driven Insights into Climate Change Effects on Groundwater Levels Using Machine Learning
    Lu, Xinyong
    Wang, Zimo
    Zhao, Menghao
    Peng, Songzhe
    Geng, Song
    Ghorbani, Hamzeh
    WATER RESOURCES MANAGEMENT, 2025,
  • [17] Predicting the impact of climate change on building energy consumption by using data-driven approaches
    Khalil, Mohamad
    Akhlaghi, Yousef G.
    Ben, Hui
    Royapoor, Mohammad
    Walker, Sara
    PROCEEDINGS OF THE INSTITUTION OF CIVIL ENGINEERS-ENERGY, 2025, 178 (02) : 61 - 76
  • [18] Accountability and data-driven urban climate governance
    Sara Hughes
    Sarah Giest
    Laura Tozer
    Nature Climate Change, 2020, 10 : 1085 - 1090
  • [19] Groundwater Modeling with Process-Based and Data-Driven Approaches in the Context of Climate Change
    Menichini, Matia
    Franceschi, Linda
    Raco, Brunella
    Masetti, Giulio
    Scozzari, Andrea
    Doveri, Marco
    WATER, 2022, 14 (23)
  • [20] Understanding climate phenomena with data-driven models
    Knuesel, Benedikt
    Baumberger, Christoph
    STUDIES IN HISTORY AND PHILOSOPHY OF SCIENCE, 2020, 84 : 46 - 56