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1. High beta diversity among small islands is due to environmental heterogeneity rather than ecological drift

   https://doi.org/10.1111/jbi.13404  

   Liu, Jinliang ; Vellend, Mark ; Wang, Zuhua ; Yu, Mingjian ( July 2018 , Journal of Biogeography)

   Both ecological drift and environmental heterogeneity can produce high beta diversity among communities, but only the effect of drift is expected to be enhanced in communities of small size. Few studies have explicitly tested the influence of community size on patterns of beta diversity. Here we applied a series of analyses aimed at testing the influence of drift versus environmental heterogeneity on beta diversity among tree communities on islands of variable size.

   Thousand Island Lake, Zhejiang Province, China.

   We used data on mapped tree communities and environmental conditions for 20 small islands (<1 ha) and nine large islands (>1 ha) created via the construction of a hydroelectric dam in 1959. Beta diversity was calculated using abundance‐based multiple‐site dissimilarity based on the Bray–Curtis index. On the basis of the hypothesis of ecological drift among small islands, we tested for higher beta diversity among small than large islands using: (a) raw data (b) controlling for the number of individual sampled on a given island, and (c) controlling for the contiguous sampling area and thus for intra‐island environmental heterogeneity. We also tested the prediction that the relationship between species composition and environmental variables should be weaker on small islands using canonical correspondence analyses.

   Using raw data and controlling for the number of individuals, community dissimilarity was significantly greater among small islands than among large islands. However, when controlling for contiguous sampling area this difference disappeared. Contrary to the prediction based on ecological drift, the strength of overall composition–environment relationships was not significantly weaker for small islands in any of the analyses, and environmental heterogeneity increased faster with area among small islands than among large islands.

   Despite a result using raw data that was consistent with the hypothesis of ecological drift, our full set of results clearly indicated the high beta diversity among small islands was more likely due to environmental heterogeneity rather than ecological drift. This result points to a clear need to control for sampling area among habitats of different size when testing for statistical signatures of drift.

    

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2. Ecological consequences of large herbivore exclusion in an African savanna: 12 years of data from the UHURU experiment

   https://doi.org/10.1002/ecy.3649  

   Alston, Jesse M. ; Reed, Courtney G. ; Khasoha, Leo M. ; Brown, Bianca R. ; Busienei, Gilbert ; Carlson, Nathaniel ; Coverdale, Tyler C. ; Dudenhoeffer, Megan ; Dyck, Marissa A. ; Ekeno, John ; et al ( January 2022 , Ecology)

   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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3. On the relationship between environmental suitability and habitat use for three neotropical mammals

   https://doi.org/10.1093/jmammal/gyab152  

   Contreras-Díaz, Rusby G. ; Falconi, Manuel ; Osorio-Olvera, Luis ; Cobos, Marlon E. ; Soberón, Jorge ; Townsend Peterson, A. ; Lira-Noriega, Andrés ; Álvarez-Loayza, Patricia ; Luis Gonçalves, André ; Hurtado-Astaiza, Johanna ; et al ( January 2022 , Journal of Mammalogy)

   Recent studies have used occupancy models (OM) and ecological niche models (ENM) to provide a better understanding of species’ distributions at different scales. One of the main ideas underlying the theoretical foundations of both OM and ENM is that they are positively related to abundance: higher occupancy implies higher density and more suitable areas are likely to have more abundant populations. Here, we analyze the relationship between habitat use measured in terms of occupancy probabilities from OM and environmental suitability derived from ENM in three different Neotropical mammal species: Leopardus wiedii, Cuniculus paca, and Dasypus novemcinctus. For ENM, we used climatic and vegetation cover variables and implemented a model calibration and selection protocol to select the most competitive models. For OM, we used a single-species, single-season model with site covariates for camera-trap data from six different sites throughout the Neotropical realm. Covariates included vegetation percentage, normalized difference vegetation index, normalized difference water index, and elevation. For each site, we fit OM using all possible combinations of variables and selected the most competitive (ΔAICc < 2) to build an average OM. We explored relationships between estimated suitability and occupancy values using Spearman correlation analysis. Relationships between ENM and OM tended to be positive for the three Neotropical mammals, but the strength varied among sites, which could be explained by local factors such as site characteristics and conservation status of areas. We conjecture that ENM are suitable to understand spatial patterns at coarser geographic scales because the concept of the niche is about the species as a whole, whereas OM are more relevant to explain the distribution locally, likely reflecting transient dynamics of populations resulting from many local factors such as community composition and biotic processes.

    

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4. An empirical evaluation of camera trap study design: How many, how long and when?

   https://doi.org/10.1111/2041-210X.13370  

   Kays, Roland ; Arbogast, Brian S. ; Baker‐Whatton, Megan ; Beirne, Chris ; Boone, Hailey M. ; Bowler, Mark ; Burneo, Santiago F. ; Cove, Michael V. ; Ding, Ping ; Espinosa, Santiago ; et al ( April 2020 , Methods in Ecology and Evolution)

   Camera traps deployed in grids or stratified random designs are a well‐established survey tool for wildlife but there has been little evaluation of study design parameters.

   We used an empirical subsampling approach involving 2,225 camera deployments run at 41 study areas around the world to evaluate three aspects of camera trap study design (number of sites, duration and season of sampling) and their influence on the estimation of three ecological metrics (species richness, occupancy and detection rate) for mammals.

   We found that 25–35 camera sites were needed for precise estimates of species richness, depending on scale of the study. The precision of species‐level estimates of occupancy (ψ) was highly sensitive to occupancy level, with <20 camera sites needed for precise estimates of common (ψ > 0.75) species, but more than 150 camera sites likely needed for rare (ψ < 0.25) species. Species detection rates were more difficult to estimate precisely at the grid level due to spatial heterogeneity, presumably driven by unaccounted habitat variability factors within the study area. Running a camera at a site for 2 weeks was most efficient for detecting new species, but 3–4 weeks were needed for precise estimates of local detection rate, with no gains in precision observed after 1 month. Metrics for all mammal communities were sensitive to seasonality, with 37%–50% of the species at the sites we examined fluctuating significantly in their occupancy or detection rates over the year. This effect was more pronounced in temperate sites, where seasonally sensitive species varied in relative abundance by an average factor of 4–5, and some species were completely absent in one season due to hibernation or migration.

   We recommend the following guidelines to efficiently obtain precise estimates of species richness, occupancy and detection rates with camera trap arrays: run each camera for 3–5 weeks across 40–60 sites per array. We recommend comparisons of detection rates be model based and include local covariates to help account for small‐scale variation. Furthermore, comparisons across study areas or times must account for seasonality, which could have strong impacts on mammal communities in both tropical and temperate sites.

    

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5. Toward Improved Accuracy of Remote Sensing Approaches for Quantifying Suspended Sediment: Implications for Suspended‐Sediment Monitoring

   https://doi.org/10.1029/2019JF005033  

   Dethier, E. N. ; Renshaw, C. E. ; Magilligan, F. J. ( July 2020 , Journal of Geophysical Research: Earth Surface)

   Because of the high logistical and financial costs of direct measurements of riverine suspended sediment, remote sensing is increasingly used to supplement the direct‐observation record. The accuracy of this method is poorly constrained, and its potential as a tool for understanding river sediment transport is thus limited. We introduce and apply global‐scale methods for estimating depth‐integrated suspended‐sediment concentrations (SSCs) using Landsat 5 and 7 satellite imagery calibrated with 134,697 in situ SSC measurements. We account for river‐to‐river variability in the relationship between water optical properties and SSC by (a) categorizing rivers using unsupervised K‐means clustering and/or (b) correcting calibration estimates for individual rivers using local in situ measurements of SSC, suspended‐sediment grain size, and percent organic carbon (POC). In the absence of site‐specific in situ SSC measurements, clustering rivers reduces the average relative error of SSC estimates from 97% to 73%. We show that as few as five site‐specific in situ measurements combined with our algorithm further reduces average relative error to 49% and average relative at‐a‐station bias in SSC to 7%. Little additional improvement in accuracy or bias is gained by including measurements of percent sand or POC of the suspended sediment. Since only modest additional accuracy is gained after ~5–10 paired in situ SSC measurements and satellite observations, sampling campaigns should prioritize limited sampling at diverse locations rather than intensive sampling at a limited number of sites. In addition, we publish standalone calibrations for 151 rivers made solely with in situ SSC measurements local to those sites.

    

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