Jorge Assis, Salvador Jesús Fernández Bejarano, Vinícius W. Salazar, Lennert Schepers, Lidiane Gouvêa, Eliza Fragkopoulou, Frederic Leclercq, Bart Vanhoorne, Lennert Tyberghein, Ester A. Serrão, Heroen Verbruggen, Olivier De Clerck
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Yet, the available data layers (1) have not been updated to incorporate data of the Sixth Phase of the Coupled Model Intercomparison Project (CMIP6), which comprise the Shared Socioeconomic Pathway (SSP) scenarios; (2) consider a limited number of Earth System Models (ESMs), and (3) miss important variables expected to influence future biodiversity distributions. These limitations might undermine biodiversity impact assessments, by failing to integrate them within the context of the most up-to-date climate change projections, raising the uncertainty in estimates and misinterpreting the exposure of biodiversity to extreme conditions. Here, we provide a significant update of Bio-ORACLE, extending biologically relevant data layers from present-day conditions to the end of the 21st century Shared Socioeconomic Pathway scenarios based on a multi-model ensemble with data from CMIP6. Alongside, we provide R and Python packages for seamless integration in modelling workflows. 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引用次数: 0
摘要
动因气候变化对海洋生物多样性的影响通常是利用代表全球海洋物理、化学和生物条件的标准化数据层进行物种分布建模预测的。然而，现有的数据层（1）尚未更新以纳入第六阶段耦合模式相互比较项目（CMIP6）的数据，这些数据包括共享社会经济路径（SSP）方案；（2）考虑的地球系统模式（ESM）数量有限；（3）遗漏了预计会影响未来生物多样性分布的重要变量。这些局限性可能会破坏生物多样性影响评估，因为它们未能将生物多样性影响评估与最新的气候变化预测结合起来，增加了评估的不确定性，并误解了生物多样性在极端条件下的暴露程度。在此，我们对 Bio-ORACLE 进行了重大更新，基于 CMIP6 数据的多模型集合，将生物相关数据层从当今条件扩展到 21 世纪末的共享社会经济路径情景。同时，我们还提供了 R 和 Python 软件包，以便无缝集成到建模工作流程中。这些数据层旨在提高人们对气候变化对生物多样性潜在影响的认识，并为知情的研究、保护和管理提供支持。包含的主要变量类型表层和底层：叶绿素-a、扩散衰减系数、溶解铁、溶解氧、硝酸盐、海洋温度、pH 值、磷酸盐、光合有效辐射、浮游植物总量、总云量、盐度、硅酸盐、海水流向、海水流速、地形坡度、地形剖面、地形崎岖指数、地形位置指数和水深，以及表层的气温、混合层深度、海冰覆盖率和海冰厚度。空间位置和粒度全球，分辨率为 0.05°。时间段和粒度从现在到 21 世纪末（2000-2100 年）的十年。主要分类群和测量水平与表层和底栖栖息地相关的海洋生物多样性。软件格式为 Python 和 R 软件开发的功能包。
Bio-ORACLE v3.0. Pushing marine data layers to the CMIP6 Earth System Models of climate change research
Motivation
Impacts of climate change on marine biodiversity are often projected with species distribution modelling using standardized data layers representing physical, chemical and biological conditions of the global ocean. Yet, the available data layers (1) have not been updated to incorporate data of the Sixth Phase of the Coupled Model Intercomparison Project (CMIP6), which comprise the Shared Socioeconomic Pathway (SSP) scenarios; (2) consider a limited number of Earth System Models (ESMs), and (3) miss important variables expected to influence future biodiversity distributions. These limitations might undermine biodiversity impact assessments, by failing to integrate them within the context of the most up-to-date climate change projections, raising the uncertainty in estimates and misinterpreting the exposure of biodiversity to extreme conditions. Here, we provide a significant update of Bio-ORACLE, extending biologically relevant data layers from present-day conditions to the end of the 21st century Shared Socioeconomic Pathway scenarios based on a multi-model ensemble with data from CMIP6. Alongside, we provide R and Python packages for seamless integration in modelling workflows. The data layers aim to enhance the understanding of the potential impacts of climate change on biodiversity and to support well-informed research, conservation and management.
Main Types of Variable Contained
Surface and benthic layers for, chlorophyll-a, diffuse attenuation coefficient, dissolved iron, dissolved oxygen, nitrate, ocean temperature, pH, phosphate, photosynthetic active radiation, total phytoplankton, total cloud fraction, salinity, silicate, sea-water direction, sea-water velocity, topographic slope, topographic aspect, terrain ruggedness index, topographic position index and bathymetry, and surface layers for air temperature, mixed layer depth, sea-ice cover and sea-ice thickness.
Spatial Location and Grain
Global at 0.05° resolution.
Time Period and Grain
Decadal from present-day to the end of the 21st century (2000–2100).
Major Taxa and Level of Measurement
Marine biodiversity associated with surface and epibenthic habitats.
Software Format
A package of functions developed for Python and R software.
期刊介绍：
Global Ecology and Biogeography (GEB) welcomes papers that investigate broad-scale (in space, time and/or taxonomy), general patterns in the organization of ecological systems and assemblages, and the processes that underlie them. In particular, GEB welcomes studies that use macroecological methods, comparative analyses, meta-analyses, reviews, spatial analyses and modelling to arrive at general, conceptual conclusions. Studies in GEB need not be global in spatial extent, but the conclusions and implications of the study must be relevant to ecologists and biogeographers globally, rather than being limited to local areas, or specific taxa. Similarly, GEB is not limited to spatial studies; we are equally interested in the general patterns of nature through time, among taxa (e.g., body sizes, dispersal abilities), through the course of evolution, etc. Further, GEB welcomes papers that investigate general impacts of human activities on ecological systems in accordance with the above criteria.
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