数据科学
领域(数学)
生态学
生物多样性
宏观进化
环境资源管理
地理
计算机科学
环境科学
生物
生物化学
数学
基因
纯数学
系统发育树
作者
Florian Härtig,Nerea Abrego,Alex Bush,Jonathan M. Chase,Gurutzeta Guillera‐Arroita,Mathew A. Leibold,Otso Ovaskainen,Loïc Pellissier,M Pichler,Giovanni Poggiato,Laura J. Pollock,Sara Si-Moussi,Wilfried Thuiller,Duarte S. Viana,David I. Warton,Damaris Zurell,Douglas W. Yu
标识
DOI:10.1016/j.tree.2023.09.017
摘要
New technologies for acquiring biological information such as eDNA, acoustic or optical sensors, make it possible to generate spatial community observations at unprecedented scales. The potential of these novel community data to standardize community observations at high spatial, temporal, and taxonomic resolution and at large spatial scale ('many rows and many columns') has been widely discussed, but so far, there has been little integration of these data with ecological models and theory. Here, we review these developments and highlight emerging solutions, focusing on statistical methods for analyzing novel community data, in particular joint species distribution models; the new ecological questions that can be answered with these data; and the potential implications of these developments for policy and conservation.
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