Gowda Karna, Chen Yuxin, Iams Sarah, Silber Mary
Department of Engineering Sciences and Applied Mathematics , Northwestern University , Evanston, IL 60208, USA.
Paulson School of Engineering and Applied Sciences , Harvard University , Cambridge, MA 02138, USA.
Proc Math Phys Eng Sci. 2016 Mar;472(2187):20150893. doi: 10.1098/rspa.2015.0893.
A particular sequence of patterns, 'gaps→labyrinth→spots', occurs with decreasing precipitation in previously reported numerical simulations of partial differential equation dryland vegetation models. These observations have led to the suggestion that this sequence of patterns can serve as an early indicator of desertification in some ecosystems. Because parameter values in the vegetation models can take on a range of plausible values, it is important to investigate whether the pattern sequence prediction is robust to variation. For a particular model, we find that a quantity calculated via bifurcation-theoretic analysis appears to serve as a proxy for the pattern sequences that occur in numerical simulations across a range of parameter values. We find in further analysis that the quantity takes on values consistent with the standard sequence in an ecologically relevant limit of the model parameter values. This suggests that the standard sequence is a robust prediction of the model, and we conclude by proposing a methodology for assessing the robustness of the standard sequence in other models and formulations.
在先前报道的偏微分方程旱地植被模型的数值模拟中,随着降水量的减少,会出现一种特定的模式序列,即“间隙→迷宫→斑点”。这些观测结果表明,这种模式序列可以作为某些生态系统荒漠化的早期指标。由于植被模型中的参数值可以取一系列合理的值,因此研究模式序列预测对变化的稳健性很重要。对于一个特定的模型,我们发现通过分岔理论分析计算出的一个量似乎可以作为一系列参数值下数值模拟中出现的模式序列的代理。我们在进一步分析中发现,在模型参数值的生态相关极限内,该量的值与标准序列一致。这表明标准序列是该模型的稳健预测,我们最后提出了一种方法,用于评估其他模型和公式中标准序列的稳健性。