Pathways to global-change effects on biodiversity: New opportunities for dynamically forecasting demography and species interactions

In structured populations, persistence under environmental change is threatened when abiotic factors simultaneously negatively affect survival and reproduction of several life-cycle stages. Such effects can then be exacerbated when species interactions generate reciprocal feedbacks between the demographic rates of the different species. Despite the importance of such demographic feedbacks, forecasts that account for them are severely limited as individual-based data on interacting species are perceived to be essential for such mechanistic forecasting - but are rarely available. This dataset is the input to showcase a state-of-the-art Bayesian method  to infer and  project stage-specific survival and reproduction from abundance data for several interacting species in a Mediterranean shrub community., In order to assess community composition before, during, and after a severe drought event in Doñana National Park, 18 permanent plots of 25 m2 were established in November 2007 (two years after the drought) on a gradient of drought impact. The plots were located at three sites (with six plots per site): Raposo, Marquas, and Ojillo. To avoid spatial autocorrelation, all plots were separated by at least 50 m from each other. Species plant cover was estimated from contacts with branches along transects within plots; these contacts were divided into two categories corresponding to living or dead canopy. Relative abundance of each species per plot in years after the extreme drought was calculated as the proportion of their contacts of living canopy relative to the sum of the contacts of living canopy of all species. Similarly, the total vegetation cover per plot was calculated as the summed contacts of living canopy of all species., All data were processed in R statistical software, version 4.0.1 (and packages as described in the R scripts). Code to analyze the data is presented on https://github.com/MariaPaniw/shrub_forecast.

在结构化种群中，当非生物因子（abiotic factors）同时对多个生活史阶段的存活与繁殖产生负面影响时，种群在环境变化下的存续将受到威胁。而当物种间相互作用在不同物种的种群动态速率（demographic rates）之间产生互惠反馈时，这类负面影响会进一步加剧。尽管此类种群动态反馈至关重要，但考虑到这类反馈的预测模型却严重受限——因为学界普遍认为，针对相互作用物种的个体水平数据（individual-based data）是实现此类机制性预测的必要条件，而这类数据往往难以获取。本数据集旨在展示一套前沿的贝叶斯方法（Bayesian method），该方法可从丰度数据中推断并预测地中海灌丛群落（Mediterranean shrub community）内多个相互作用物种的阶段特异性存活与繁殖情况。
为评估多尼亚纳国家公园（Doñana National Park）极端干旱事件发生前、发生期间及发生后的群落组成，研究团队于2007年11月（即干旱发生两年后）在干旱影响梯度上设立了18块25平方米的永久样地。这些样地分布于3个样点：拉波索（Raposo）、马尔克斯（Marquas）与奥希略（Ojillo），每个样点设置6块样地。为避免空间自相关（spatial autocorrelation），所有样地之间的间距至少为50米。
研究人员通过样线内枝条接触法估算物种的植物盖度（plant cover），并将接触情况分为活冠层与枯冠层两类。针对极端干旱发生后各年份的样地内各物种的相对多度（relative abundance），研究人员以该物种活冠层接触次数占所有物种活冠层总接触次数的比例进行计算。同理，样地内总植被盖度以所有物种活冠层的总接触次数计算。
所有数据均通过R统计软件（R statistical software）版本4.0.1及配套R脚本中提及的扩展包完成处理。数据分析代码可访问https://github.com/MariaPaniw/shrub_forecast获取。