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Abstract Prediction of abrupt ecosystem transitions resulting from climatic change will be an essential element of adaptation strategies in the coming decades. In the arid southwest USA, the collapse and recovery of long‐lived perennial grasses have important effects on ecosystem services, but the causes of these variations have been poorly understood. Here we use a quality‐controlled vegetation monitoring dataset initiated in 1915 to show that grass cover dynamics during the 20th century were closely correlated to the Pacific decadal oscillation (PDO) index. The relationship out‐performed models correlating grasses to yearly precipitation and drought indices, suggesting that ecosystem transitions attributed only to local disturbances were instead influenced by climate teleconnections. Shifts in PDO phase over time were associated with the persistent loss of core grass species and recovery of transient species, so recovery of grasses in aggregate concealed significant changes in species composition. However, the relationship between PDO and grass cover broke down after 1995; grass cover is consistently lower than PDO would predict. The decoupling of grass cover from the PDO suggests that a threshold had been crossed in which warming or land degradation overwhelmed the ability of any grass species to recover during favorable periods. 

ABSTRACT MotivationHere, we make available a second version of the BioTIME database, which compiles records of abundance estimates for species in sample events of ecological assemblages through time. The updated version expands version 1.0 of the database by doubling the number of studies and includes substantial additional curation to the taxonomic accuracy of the records, as well as the metadata. Moreover, we now provide an R package (BioTIMEr) to facilitate use of the database. Main Types of Variables IncludedThe database is composed of one main data table containing the abundance records and 11 metadata tables. The data are organised in a hierarchy of scales where 11,989,233 records are nested in 1,603,067 sample events, from 553,253 sampling locations, which are nested in 708 studies. A study is defined as a sampling methodology applied to an assemblage for a minimum of 2 years. Spatial Location and GrainSampling locations in BioTIME are distributed across the planet, including marine, terrestrial and freshwater realms. Spatial grain size and extent vary across studies depending on sampling methodology. We recommend gridding of sampling locations into areas of consistent size. Time Period and GrainThe earliest time series in BioTIME start in 1874, and the most recent records are from 2023. Temporal grain and duration vary across studies. We recommend doing sample‐level rarefaction to ensure consistent sampling effort through time before calculating any diversity metric. Major Taxa and Level of MeasurementThe database includes any eukaryotic taxa, with a combined total of 56,400 taxa. Software Formatcsv and. SQL.