Data from: The effects of temporal resolution on species turnover and on testing metacommunity models

Patterns of low temporal turnover in species composition found within
long paleoecological time series contrast with the high turnover
predicted by dispersal-limited neutral metacommunity models and thus have been used to support non-neutral models. However, predictions assume temporal resolution on the scale of a season or year whereas
individual fossil assemblages are typically time-averaged to decadal
or centennial time scales. Here, we simulate the effects of time
averaging by building time-averaged assemblages from local
dispersal-limited non-averaged (living) assemblages and compare the
predicted species turnover with observed patterns in mollusk and
ostracod fossil records. Time averaging substantially reduces temporal
turnover such that neutral predictions converge with those of
trade-off and density-dependent models, and tends to decrease species
dominance and increase the proportion of rare species. Observed
turnover rates are comparable to an appropriately scaled neutral model: patterns of high community stability can be produced or
reinforced by time averaging alone. The community attributes of local
time-averaged assemblages approach those of the metacommunity.
Time-averaged assemblages are thus unlikely to capture attributes
arising from processes operating at small spatial scales, but should
do well at capturing the turnover and diversity parameters of
metacommunities, and thus will be a valuable basis for analyzing the
large-scale processes that determine metacommunity evolution.

长期古生态学时间序列中观测到的物种组成低时间更替率模式，与扩散限制中性集合群落（dispersal-limited neutral metacommunity）模型预测的高更替率形成鲜明反差，该模式因此常被用于佐证非中性模型。但这类模型的预测前提均为时间分辨率可达季节或年际尺度，而单个化石组合通常已被时间平均化，对应的时间跨度可达十年乃至百年尺度。本研究通过从局地扩散限制的非时间平均化（现生生物）组合中构建时间平均化组合，模拟时间平均化的生态效应，并将模型预测的物种更替率与软体动物和介形类的化石记录观测模式进行对比。结果表明，时间平均化可显著降低物种时间更替率，使得中性模型的预测结果与权衡及密度依赖模型的预测结果趋于一致；同时还会降低物种优势度，提升稀有种的占比。观测到的物种更替率与经合理尺度校正的中性模型结果相当：仅通过时间平均化作用，即可产生乃至强化群落高稳定性的观测模式。局地时间平均化组合的群落属性逐渐趋近于集合群落（metacommunity）的特征。因此，时间平均化组合难以捕捉小空间尺度下生态过程所产生的群落属性，但能够较好地反映集合群落的更替率与多样性参数，故而可作为解析调控集合群落演化的大尺度生态过程的重要研究基础。