Volatility in coral cover erodes niche structure, but not diversity, in reef fish assemblages

Archived file name: “Tsai_etal_2022_ScienceAdvances_archive.RData” 1. “Tsai_etal_sumzdata”: Reef fish community structure variables and environmental variables across 40 reefs are stored as R data.frame object. Within this data.frame object, the reef IDs (“reefID”), latitude (“lat”), cross-shelf position (“shelf”), mean coral cover (“mC”), and standard deviation (“sdC”) and log-standard deviation (“logsdC”) in coral cover, (time-averaged) Poisson-lognormal estimated richness (“plnRichness”), (time-averaged) Poisson-lognormal estimated unevenness (“plnUnevenness”), and VPRSA variance components due to persistent species differences (“Vr”), stochastic fluctuations (“Ve”), and overdispersion (demographic/sampling stochasticity) (“Vd”) are recorded. A transformed shelf position, 1 - “shelf”, was used for the piecewise SEM analysis in the MS. 2. “AIMSLTMPfishcomm.list” and “AIMSLTMPfishcomm.list.reefID”: We extracted and compiled the community dynamics data of LTMP from 1994 to 2004 (11 years) for analyses. We pooled fish community and coral cover data at the scale of the entire reef, summing species abundances over all 15 transects laid on each reef. Percentage living hard coral cover is averaged across transects and sites within reefs. We adopted this approach to reduce stochastic sampling error, thereby obtaining more precise estimates of the community structure statistics that are of interest. Because the small-sized fish taxa (mainly Pomacentridae) were surveyed in narrower transects than other, larger fish taxa, we used subsampling (Poisson samples) to rescale the abundances of large-sized species to standardize sampling effort. Each fish counted on the wider transects was given a 20% probability of appearing in the sub-sample (because the small-fish transects cover only 20% of the area of large-fish transects). Sub-sampled data were used for the analyses.

归档文件名："Tsai_etal_2022_ScienceAdvances_archive.RData"
1. 数据集"Tsai_etal_sumzdata"：存储为R数据框（R data.frame）对象的40个珊瑚礁的鱼类群落结构变量与环境变量。该数据框内包含以下字段：珊瑚礁ID（reefID）、纬度（lat）、跨陆架位置（shelf）、平均珊瑚覆盖率（mC）、珊瑚覆盖率的标准差（sdC）与对数标准差（logsdC）、（时间平均的）泊松对数正态估计物种丰富度（plnRichness）、（时间平均的）泊松对数正态估计物种不均匀度（plnUnevenness），以及由持久性物种差异引起的VPRSA方差分量（Vr）、随机波动（Ve）与过度离散（人口统计/抽样随机性）（Vd）。在论文的分段结构方程模型（piecewise SEM）分析中，我们使用了转换后的陆架位置：1 - "shelf"。
2. 数据集"AIMSLTMPfishcomm.list"与"AIMSLTMPfishcomm.list.reefID"：我们提取并汇编了1994年至2004年（共11年）的长期监测计划（Long-Term Monitoring Program, LTMP）鱼类群落动态数据以用于分析。我们将鱼类群落与珊瑚覆盖率数据按整个珊瑚礁尺度进行合并：将每个珊瑚礁上布设的全部15条调查断面的物种丰度进行求和。活硬珊瑚覆盖率取每个珊瑚礁内所有断面与样点的平均值。我们采用该方法以降低随机抽样误差，从而获得更精准的目标群落结构统计量估计值。由于小型鱼类类群（主要为雀鲷科（Pomacentridae））的调查断面宽度小于其他大型鱼类类群，我们采用泊松抽样（Poisson samples）子抽样方法对大型物种的丰度进行重缩放，以统一采样工作量。宽断面中统计的每条鱼有20%的概率被纳入子样本（因小型鱼类断面的覆盖面积仅为大型鱼类断面的20%）。子抽样后的数据用于后续分析。