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Title: Long‐term ecological research and the COVID ‐19 anthropause: A window to understanding social–ecological disturbance
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  1. Abstract

    Biodiversity studies rely heavily on estimates of species' distributions often obtained through ecological niche modelling. Numerous software packages exist that allow users to model ecological niches using machine learning and statistical methods. However, no existing package with a graphical user interface allows users to perform model calibration and selection based on convex forms such as ellipsoids, which may match fundamental ecological niche shapes better, incorporating tools for exploring, modelling, and evaluating niches and distributions that are intuitive for both novice and proficient users.

    Here we describe anrpackage, NicheToolBox(ntbox), that allows users to conduct all processing steps involved in ecological niche modelling: downloading and curating occurrence data, obtaining and transforming environmental data layers, selecting environmental variables, exploring relationships between geographic and environmental spaces, calibrating and selecting ellipsoid models, evaluating models using binomial and partial ROC tests, assessing extrapolation risk, and performing geographic information system operations via a graphical user interface. A summary of the entire workflow is produced for use as a stand‐alone algorithm or as part of research reports.

    The method is explained in detail and tested via modelling the threatened feline speciesLeopardus wiedii. Georeferenced occurrence data for this species are queried to display both point occurrences and the IUCN extent of occurrence polygon (IUCN, 2007). This information is used to illustrate tools available for accessing, processing and exploring biodiversity data (e.g. number of occurrences and chronology of collecting) and transforming environmental data (e.g. a summary PCA for 19 bioclimatic layers). Visualizations of three‐dimensional ecological niches modelled as minimum volume ellipsoids are developed with ancillary statistics. This niche model is then projected to geographic space, to represent a corresponding potential suitability map.

    Usingntboxallows a fast and straightforward means by which to retrieve and manipulate occurrence and environmental data, which can then be implemented in model calibration, projection and evaluation for assessing distributions of species in geographic space and their corresponding environmental combinations.

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  2. Michener, William K. (Ed.)
    Diverse communities of large mammalian herbivores (LMH), once widespread, are now rare. LMH exert strong direct and indirect effects on community structure and ecosystem functions, and measuring these effects is important for testing ecological theory and for understanding past, current, and future environmental change. This in turn requires long-term experimental manipulations, owing to the slow and often nonlinear responses of populations and assemblages to LMH removal. Moreover, the effects of particular species or body-size classes within diverse LMH guilds are difficult to pinpoint, and the magnitude and even direction of these effects often depends on environmental context. Since 2008, we have maintained the Ungulate Herbivory Under Rainfall Uncertainty (UHURU) experiment, a series of size-selective LMH exclosures replicated across a rainfall/productivity gradient in a semi-arid Kenyan savanna. The goals of the UHURU experiment are to measure the effects of removing successively smaller size classes of LMH (mimicking the process of size-biased extirpation) and to establish how these effects are shaped by spatial and temporal variation in rainfall. The UHURU experiment comprises three LMH-exclusion treatments and an unfenced control, applied to 9 randomized blocks of contiguous 1-ha plots (n = 36). The fenced treatments are: “MEGA” (exclusion of megaherbivores, elephant and giraffe); “MESO” (exclusion of herbivores ≥40 kg); and “TOTAL” (exclusion of herbivores ≥5 kg). Each block is replicated three times at three sites across the 20-km rainfall gradient, which has fluctuated over the course of the experiment. The first five years of data were published previously (Ecological Archives E095-064) and have been used in numerous studies. Since that publication, we have (a) continued to collect data following the original protocols, (b) improved the taxonomic resolution and accuracy of plant and small-mammal identifications, and (c) begun collecting several new data sets. Here, we present updated and extended raw data from the first 12 years of the UHURU experiment (2008–2019). Data include daily rainfall data throughout the experiment; annual surveys of understory plant communities; annual censuses of woody-plant communities; annual measurements of individually tagged woody plants; monthly monitoring of flowering and fruiting phenology; every-other-month small-mammal mark-recapture data; and quarterly large-mammal dung surveys. There are no copyright restrictions; notification of when and how data are used is appreciated and users of UHURU data should cite this data paper when using the data. 
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