Assessing the utility of death assemblages as reference conditions in a common benthic index (M-AMBI) with simulations

biorxiv(2022)

引用 0|浏览7
暂无评分
摘要
Incorporating paleontological data into the methods and formats already familiar to conservation practitioners may facilitate greater use of paleontological data in conservation practice. Benthic indices (e.g., Multivariate - AZTI Marine Biotic Index; M-AMBI) already incorporate reference conditions and are a good candidate for integration. In simulations of living communities under constant and changing environmental conditions, we evaluate the capacity of death assemblage reference conditions to replicate M-AMBI values when used in place of reference conditions from the final ten generations of the simulation or all five hundred simulated generations. Reference conditions from all death assemblage scenarios successfully replicated correct remediation decisions in the majority of simulation runs with environmental change and stability. Variations in M-AMBI values were due to overestimated richness and diversity in the death assemblages but effects of changes to these parameters varied across scenarios, emphasizing the importance of evaluating multiple metrics. Time averaging was largely beneficial, particularly when environmental change occurred and short-term ecological observations (ten generations) produced incorrect remediation decisions. When the duration of time averaging is known, death assemblages can provide valuable long-term perspectives with the potential to outperform temporally constrained baseline information from monitoring the living community. Supplementary material All R code used to produce the simulation, analyze outputs, and create figures is available at: . The simulated data is also available at this location. Supplementary figures and analyses referred to in the text are available at the end of this document. ### Competing Interest Statement The authors have declared no competing interest.
更多
查看译文
关键词
common benthic index,death assemblages,m-ambi
AI 理解论文
溯源树
样例
生成溯源树,研究论文发展脉络
Chat Paper
正在生成论文摘要