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Raven point counts were related to landscape covariates using Bayesian hierarchical occupancy models and the mean of the predicted posterior distribution for raven occurrence was used to visualize results.
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An index of anthropogenic influences on raven populations. Raven point counts were related to landscape covariates using Bayesian hierarchical occupancy models and the means of the posterior distributions for relevant effects were used to generate the predictions.
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We developed a framework that strategically targets burned areas for restoration actions (e.g., seeding or planting sagebrush) that have the greatest potential to positively benefit Greater Sage-grouse (Centrocercus urophasianus; hereafter sage-grouse) populations through time. Specifically, we estimated sagebrush (Artemisia Spp.) recovery following wildfire and risk of non-native annual grass invasion under three scenarios: passive recovery, active restoration with seeding, and active restoration with seedling transplants. We then applied spatial predictions of integrated nest site selection and survival models before wildfire, immediately following wildfire, and at 30 and 50 years post-wildfire based on each restoration...
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Future sea-level rise poses a risk to mangrove forests. To better understand potential vulnerability, we developed a new numerical model of soil elevation for mangrove forests. We used the model to generate projections of elevation and mangrove forest composition change under four sea-level rise scenarios through 2100 (37, 52, 67, and 117 cm by 2100). We employed a data-driven modeling approach, utilizing new and existing data to inform model parameters. The model was calibrated using dated soil cores and used a spin-up period to establish the soil column prior to future projections. Additional field data, including water level monitoring and elevation surveys, were used to estimate the initial elevation of the...
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We compiled time series of egg mass counts (an index of adult female abundance) from Rana boylii populations in 36 focal streams and fit a Multiple Population Viability Analysis (MPVA) model to quantify how streamflow metrics, stream temperature, and surrounding land cover affect population growth. In addition, data on streamflow, stream temperature, and surrounding land cover for each stream were compiled from existing sources. These data support the following publication: Rose, J.P., Kupferberg, S.J., Peek, R.A., Ashton, D., Bettaso, J.B., Bobzien, S., Bourque, R.M., Breedveld, K.G., Catenazzi, A., Drennan, J.E., Gonsolin, E., Grefsrud, M., Herman, A.E., House, M.R., Kluber, M.R., Lind, A.J., Marlow, K.R., Striegle,...
Supplement to article “Climate-Driven Geomorphic Alteration of Intertidal Habitats for Foraging Migratory Birds in the San Francisco Bay Estuary; A California Landscape Conservation Cooperative Project”. Additional information regarding sampling methodology and habitat modeling ofdiving ducks.
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Accurate elevation data in coastal ecosystems are crucial for understanding vulnerability to sea-level rise. Lidar has become increasingly available; however, in tidal wetlands such as mangroves and salt marsh, vertical bias from dense vegetation reduces accuracy of the delivered 'base earth' products. To increase accuracy of elevation models across south Florida, we applied the LEAN technique to six different lidar collections from 2007-2018. On average, LEAN correction increased DEM accuracy by 46.1 percent, reducing the vertical bias. After correction and post-processing, the DEMs were merged together with a bathymetric dataset to create a seamless topobathy product.
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These snag (dead tree) fall data were collected as part of long term forest dynamics data. Tree fall data were collected non-systematically as text comments until 2013, after which explicit snag fall data were collected on an annual basis. This particular dataset includes data from 23 plots in old-growth mixed conifer and montane conifer forests in Sequoia-Kings Canyon and Yosemite National Parks. The plots range in size from 0.9 ha to 2.5 ha and were established from 1982 to 2001. We used demography plot data through 2021 (collected before the extensive KNP Complex wildfire burned many of the plots). Before 2021, four of the 23 plots had experienced relatively recent prescribed burns or wildfires. When established,...
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Primary and secondary consumers are important links in the trophic transfer of methylmercury, and their methylmercury concentrations are often measured to assess the potential risk of toxicity to higher trophic level consumers, including humans. A better understanding of the link between methylmercury production in sediments and methylmercury bioaccumulation in tidal marsh primary and secondary consumers will improve the design of contaminant monitoring, remediation, and restoration efforts, thereby protecting human and wildlife health. To advance this goal, we characterized spatial variation in sediment biogeochemistry and methylmercury concentrations of sediments, water, and consumer tissues at a meso-scale among...
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Fifty-one tidal marsh sites across five regions (sub-embayments) were surveyed in the Delta, Suisun Bay, San Pablo Bay, central San Francisco Bay, and South San Francisco Bay. Vegetation surveys spanned ten years, from July 2008 to January 2018. A total of 5,112 plots were surveyed. Plots were positioned on transects along an elevation gradient and evenly distributed across each site, where possible, to capture spatial variability along elevation and distance gradients. At each plot, percent cover of all plant species, bare ground, and litter as well as average height was visually assessed within a 0.25 m2 quadrat. Total plant cover in a plot could exceed 100 percent due to vegetation layering. Bare ground and litter...
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This data release contains three files. The first (Table S1 Bibliography Dataset) contains the entire bibliography for the 435 publications examined for potential inclusion into at least one of the meta-analyses for the effects of environmental mercury (Hg) on birds. For those 168 publications that were included in at least one meta-analysis, the worksheet titled Bibliography contains data describing each sub-dataset, including the type of study, data extraction methods, biological endpoints measured, age class, tissue-residue Hg concentrations, dosing Hg concentrations, the measured effect of Hg, bird taxonomy, life history, and the study’s citation. The worksheet titled Header Explanation describes each column...


map background search result map search result map Predicted probability of raven occurrence across the Great Basin, USA, 2007 – 2016 (Fig. 3) Anthropogenic influence index for raven populations in the Great Basin, 2007-2016 (Fig. 4C) Mangrove Elevation and Species' Responses to Sea-level Rise Across Pohnpei, Federated States of Micronesia (ver. 1.1, December 2021) Sagebrush Restoration Following Fire Disturbance in the Virginia Mountains, Nevada (2018) Mojave Desert Ecoregion Bias-Corrected Topobathymetric Elevation Model for South Florida, 2018 Egg Mass Counts from Foothill Yellow-Legged Frogs (Rana boylii) in California from 1992-2021 Snag Fall Data from Long Term Forest Dynamics Plots in the Sierra Nevada of California through 2021 Mercury Concentrations and Stable Isotope Ratios of Consumers from Different Subhabitats of Wetlands in the San Francisco Bay, CA Marsh Vegetation Surveys Across the San Francisco Bay Estuary, 2008-2018 Mangrove Elevation and Species' Responses to Sea-level Rise Across Pohnpei, Federated States of Micronesia (ver. 1.1, December 2021) Mercury Concentrations and Stable Isotope Ratios of Consumers from Different Subhabitats of Wetlands in the San Francisco Bay, CA Marsh Vegetation Surveys Across the San Francisco Bay Estuary, 2008-2018 Snag Fall Data from Long Term Forest Dynamics Plots in the Sierra Nevada of California through 2021 Bias-Corrected Topobathymetric Elevation Model for South Florida, 2018 Mojave Desert Ecoregion Egg Mass Counts from Foothill Yellow-Legged Frogs (Rana boylii) in California from 1992-2021 Predicted probability of raven occurrence across the Great Basin, USA, 2007 – 2016 (Fig. 3) Anthropogenic influence index for raven populations in the Great Basin, 2007-2016 (Fig. 4C)