Seidl Rupert
Institute of Silviculture, Department of Forest- and Soil Science, University of Natural Resources and Life Sciences (BOKU) Vienna, Peter Jordan Straße 82, 1190 Vienna, Austria.
Ecosystems. 2017 Mar;20(2):222-228. doi: 10.1007/s10021-016-0068-x.
Here, I argue that we should abandon the division between "field ecologists" and "modelers," and embrace modeling and empirical research as two powerful and often complementary approaches in the toolbox of 21st century ecologists, to be deployed alone or in combination depending on the task at hand. As empirical research has the longer tradition in ecology, and modeling is the more recent addition to the methodological arsenal, I provide both practical and theoretical reasons for integrating modeling more deeply into ecosystem research. Empirical research has epistemological priority over modeling; however, that is, for models to realize their full potential, and for modelers to wield this power wisely, empirical research is of fundamental importance. Combining both methodological approaches or forming "super ties" with colleagues using different methods are promising pathways to creatively exploit the methodological possibilities resulting from increasing computing power. To improve the proficiency of the growing group of model users and ensure future innovation in model development, we need to increase the modeling literacy among ecology students. However, an improved training in modeling must not curtail education in basic ecological principles and field methods, as these skills form the foundation for building and applying models in ecology.
在此,我认为我们应该摒弃“野外生态学家”和“建模者”之间的划分,将建模和实证研究视为21世纪生态学家工具库中两种强大且往往相辅相成的方法,根据手头的任务单独或结合使用。由于实证研究在生态学中有更长的传统,而建模是方法库中较新的补充,我提供了将建模更深入地融入生态系统研究的实践和理论原因。实证研究在认识论上优先于建模;然而,也就是说,为了使模型充分发挥其潜力,为了建模者明智地运用这种力量,实证研究至关重要。将这两种方法结合起来,或者与使用不同方法的同事形成“超级纽带”,是创造性地利用计算能力不断提高所带来的方法可能性的有前途的途径。为了提高越来越多的模型使用者的熟练程度,并确保模型开发的未来创新,我们需要提高生态学学生的建模素养。然而,改进建模培训绝不能减少对基本生态原理和野外方法的教育,因为这些技能是在生态学中构建和应用模型的基础。