Geomatics and Landscape Ecology Laboratory, Department of Biology, Carleton University, 1125 Colonel By Dr, Ottawa, Ontario K1S 5B6, Canada.
Insectarium, Montreal Space for Life, 4581 Sherbrooke St E, Montreal, Quebec H1X 2B2, Canada.
Sci Adv. 2023 Jun 23;9(25):eabq4207. doi: 10.1126/sciadv.abq4207. Epub 2023 Jun 21.
Ecological systems are quintessentially complex systems. Understanding and being able to predict phenomena typical of complex systems is, therefore, critical to progress in ecology and conservation amidst escalating global environmental change. However, myriad definitions of complexity and excessive reliance on conventional scientific approaches hamper conceptual advances and synthesis. Ecological complexity may be better understood by following the solid theoretical basis of complex system science (CSS). We review features of ecological systems described within CSS and conduct bibliometric and text mining analyses to characterize articles that refer to ecological complexity. Our analyses demonstrate that the study of complexity in ecology is a highly heterogeneous, global endeavor that is only weakly related to CSS. Current research trends are typically organized around basic theory, scaling, and macroecology. We leverage our review and the generalities identified in our analyses to suggest a more coherent and cohesive way forward in the study of complexity in ecology.
生态系统是典型的复杂系统。因此，理解和能够预测复杂系统的典型现象，对于在日益加剧的全球环境变化中推进生态学和保护生物学的发展至关重要。然而，复杂性的众多定义和对传统科学方法的过度依赖阻碍了概念上的进步和综合。通过遵循复杂系统科学（CSS）的坚实理论基础，我们可以更好地理解生态复杂性。我们回顾了 CSS 中描述的生态系统特征，并进行了文献计量和文本挖掘分析，以描述引用生态复杂性的文章。我们的分析表明，生态学中的复杂性研究是一项高度多样化的、全球性的努力，与 CSS 的相关性很弱。当前的研究趋势通常围绕基础理论、尺度和宏观生态学展开。我们利用我们的综述和分析中确定的一般性原则，提出了一种更具连贯性和内聚力的方法，以促进生态学中复杂性的研究。
