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Abstract As on land, oceans exhibit high temporal and spatial temperature variation. This “ocean weather” contributes to the physiological and ecological processes that ultimately determine the patterns of species distribution and abundance, yet is often unrecognized, especially in tropical oceans. Here, we tested the paradigm of temperature stability in shallow waters (<12.5 m) across different zones of latitude. We collated hundreds of in situ, high temporal-frequency ocean temperature time series globally to produce an intuitive measure of temperature variability, ranging in scale from quarter-diurnal to annual time spans. To estimate organismal sensitivity of ectotherms (i.e. microbes, algae, and animals whose body temperatures depend upon ocean temperature), we computed the corresponding range of biological rates (such as metabolic rate or photosynthesis) for each time span, assuming an exponential relationship. We found that subtropical regions had the broadest temperature ranges at time spans equal to or shorter than a month, while temperate and tropical systems both exhibited narrow (i.e. stable) short-term temperature range estimates. However, temperature-dependent biological rates in tropical regions displayed greater ranges than in temperate systems. Hence, our results suggest that tropical ectotherms may be relatively more sensitive to short-term thermal variability. We also highlight previously unexplained macroecological patterns that may be underpinned by short-term temperature variability. 

Monitoring is a crucial tool for measuring the progress and success of environmental policies and management programs. While many studies have evaluated the effectiveness of biodiversity sampling methods, few have compared their efficiency, which is crucial given the funding constraints present in all conservation efforts. In this study we demonstrate how existing analytical tools can be applied to (i) assess the relationship between sampling effort and resulting confidence in biodiversity metrics, and (ii) compare the efficiency of different methods for monitoring biodiversity. We tested this methodology on data from marine fish surveys, including: roving surveys within permanent areas, randomly placed belt transects, and randomly placed transects conducted by citizen scientists using a reduced species list. We constructed efficiency curves describing how increasing effort spent on each method reduced uncertainty in biodiversity estimates and the associated ability to detect change in diversity. All programs produced comparable measurements of species diversity for all metrics despite substantial differences in the species being surveyed by each method. The uncertainty of diversity estimations fell faster and reached a lower level for the roving diver method. Strikingly, the transect method conducted by citizen scientists performed almost identically to the more taxonomically resolved transect method conducted by professional scientists, suggesting that sampling strategies that recorded only a subset of species could still be effective, as long as the excluded species were chosen strategically. The methodology described here can guide decisions about how to measure biodiversity and optimize the resources available for monitoring, ultimately improving management outcomes. 

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.