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The data set covers a 101-yr period (1915–2016) of quadrat-based plant sampling at the Jornada Experimental Range in southern New Mexico. At each sampling event, a pantograph was used to record the location and perimeter of living plants within permanent quadrats. Basal area was recorded for perennial grass species, canopy cover area was recorded for shrub species, and all other perennial species were recorded as point data. The data set includes 122 1 × 1 m permanent quadrats, although not all quadrats were sampled in each year of the study and there is a gap in monitoring from 1980 to 1995. These data provide a unique opportunity to investigate changes in the plant community over 100 yr of variation in precipitation and other environmental conditions. We provide the following data and data formats: (1) the digitized maps in shapefile format; (2) a data table containing coordinates (x, y) of perennial species within quadrats, including cover area for grasses and shrubs; (3) a data table of counts of annual plant individuals per quadrat; (4) a species list indicating growth form and habit of recorded species; (5) a table of dates when each quadrat was sampled; (6) a table of the pasture each quadrat was located within (note that pasture boundaries have changed over time); (7) a table of depth to petrocalcic layer measurements taken at quadrat locations; (8) a table of particle size analysis of soil samples taken at quadrat locations; (9) a table of topographic characteristics of quadrat locations (e.g., concave or convex topography). Pantograph sampling is currently conducted at 5-yr intervals by USDA-ARS staff, and new data will be added periodically to the EDI Data Portal Repository (see section V.E.2). This information is released under the Creative Commons license—Attribution—CC BY and the consumer of these data is required to cite it appropriately in any publication that results from its use. 

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 Regional long‐term monitoring can enhance the detection of biodiversity declines associated with climate change, improving future projections by reducing reliance on space‐for‐time substitution and increasing scalability. Rodents are diverse and important consumers in drylands, regions defined by the scarcity of water that cover 45% of Earth's land surface and face increasingly drier and more variable climates. We analyzed abundance data for 22 rodent species across grassland, shrubland, ecotone, and woodland ecosystems in the southwestern USA. Two time series (1995–2006 and 2004–2013) coincided with phases of the Pacific Decadal Oscillation (PDO), which influences drought in southwestern North America. Regionally, rodent species diversity declined 20%–35%, with greater losses during the later time period. Abundance also declined regionally, but only during 2004–2013, with losses of 5% of animals captured. During the first time series (wetter climate), plant productivity outranked climate variables as the best regional predictor of rodent abundance for 70% of taxa, whereas during the second period (drier climate), climate best explained variation in abundance for 60% of taxa. Temporal dynamics in diversity and abundance differed spatially among ecosystems, with the largest declines in woodlands and shrublands of central New Mexico and Colorado. Which species were winners or losers under increasing drought and amplified interannual variability in drought depended on ecosystem type and the phase of the PDO. Fewer taxa were significant winners (18%) than losers (30%) under drought, but the identities of winners and losers differed among ecosystems for 70% of taxa. Our results suggest that the sensitivities of rodent species to climate contributed to regional declines in diversity and abundance during 1995–2013. Whether these changes portend future declines in drought‐sensitive consumers in the southwestern USA will depend on the climate during the next major PDO cycle. 

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.