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California policy is incentivizing rapid adoption of zero emission electric vehicles for light duty and freight applications. In this project, we explored how locating charging facilities at California’s highway rest stops, might impact electricity demand, grid operation, and integration of renewables like solar and wind into California’s energy mix. Assuming a growing population of electric vehicles to meet state goals, we estimated state-wide growth of electricity demand, and identified the most attractive rest stop locations for siting chargers. Using a California-specific electricity dispatch model developed at ITS, we estimated how charging vehicles at these stations would impact renewable energy curtailment in California. We estimated the impacts of charging infrastructures on California’s electricity system and how they can be utilized to decrease the duck curve effect resulting from a large amount of solar energy penetration by 2050.

Project: Coupled Model Intercomparison Project Phase 6 (CMIP6) datasets - These data have been generated as part of the internationally-coordinated Coupled Model Intercomparison Project Phase 6 (CMIP6; see also GMD Special Issue: http://www.geosci-model-dev.net/special_issue590.html). The simulation data provides a basis for climate research designed to answer fundamental science questions and serves as resource for authors of the Sixth Assessment Report of the Intergovernmental Panel on Climate Change (IPCC-AR6). CMIP6 is a project coordinated by the Working Group on Coupled Modelling (WGCM) as part of the World Climate Research Programme (WCRP). Phase 6 builds on previous phases executed under the leadership of the Program for Climate Model Diagnosis and Intercomparison (PCMDI) and relies on the Earth System Grid Federation (ESGF) and the Centre for Environmental Data Analysis (CEDA) along with numerous related activities for implementation. The original data is hosted and partially replicated on a federated collection of data nodes, and most of the data relied on by the IPCC is being archived for long-term preservation at the IPCC Data Distribution Centre (IPCC DDC) hosted by the German Climate Computing Center (DKRZ). The project includes simulations from about 120 global climate models and around 45 institutions and organizations worldwide. Summary: These data include the subset used by IPCC AR6 WGI authors of the datasets originally published in ESGF for 'CMIP6.ScenarioMIP.CNRM-CERFACS.CNRM-ESM2-1.ssp434' with the full Data Reference Syntax following the template 'mip_era.activity_id.institution_id.source_id.experiment_id.member_id.table_id.variable_id.grid_label.version'. The CNRM-ESM2-1 climate model, released in 2017, includes the following components: aerosol: TACTIC_v2, atmos: Arpege 6.3 (T127; Gaussian Reduced with 24572 grid points in total distributed over 128 latitude circles (with 256 grid points per latitude circle between 30degN and 30degS reducing to 20 grid points per latitude circle at 88.9degN and 88.9degS); 91 levels; top level 78.4 km), atmosChem: REPROBUS-C_v2, land: Surfex 8.0c, ocean: Nemo 3.6 (eORCA1, tripolar primarily 1deg; 362 x 294 longitude/latitude; 75 levels; top grid cell 0-1 m), ocnBgchem: Pisces 2.s, seaIce: Gelato 6.1. The model was run by the CNRM (Centre National de Recherches Meteorologiques, Toulouse 31057, France), CERFACS (Centre Europeen de Recherche et de Formation Avancee en Calcul Scientifique, Toulouse 31057, France) (CNRM-CERFACS) in native nominal resolutions: aerosol: 250 km, atmos: 250 km, atmosChem: 250 km, land: 250 km, ocean: 100 km, ocnBgchem: 100 km, seaIce: 100 km.

Project: Coupled Model Intercomparison Project Phase 6 (CMIP6) datasets - These data have been generated as part of the internationally-coordinated Coupled Model Intercomparison Project Phase 6 (CMIP6; see also GMD Special Issue: http://www.geosci-model-dev.net/special_issue590.html). The simulation data provides a basis for climate research designed to answer fundamental science questions and serves as resource for authors of the Sixth Assessment Report of the Intergovernmental Panel on Climate Change (IPCC-AR6). CMIP6 is a project coordinated by the Working Group on Coupled Modelling (WGCM) as part of the World Climate Research Programme (WCRP). Phase 6 builds on previous phases executed under the leadership of the Program for Climate Model Diagnosis and Intercomparison (PCMDI) and relies on the Earth System Grid Federation (ESGF) and the Centre for Environmental Data Analysis (CEDA) along with numerous related activities for implementation. The original data is hosted and partially replicated on a federated collection of data nodes, and most of the data relied on by the IPCC is being archived for long-term preservation at the IPCC Data Distribution Centre (IPCC DDC) hosted by the German Climate Computing Center (DKRZ). The project includes simulations from about 120 global climate models and around 45 institutions and organizations worldwide. Summary: These data include the subset used by IPCC AR6 WGI authors of the datasets originally published in ESGF for 'CMIP6.ScenarioMIP.NCAR.CESM2' with the full Data Reference Syntax following the template 'mip_era.activity_id.institution_id.source_id.experiment_id.member_id.table_id.variable_id.grid_label.version'. The CESM2 climate model, released in 2018, includes the following components: aerosol: MAM4 (same grid as atmos), atmos: CAM6 (0.9x1.25 finite volume grid; 288 x 192 longitude/latitude; 32 levels; top level 2.25 mb), atmosChem: MAM4 (same grid as atmos), land: CLM5 (same grid as atmos), landIce: CISM2.1, ocean: POP2 (320x384 longitude/latitude; 60 levels; top grid cell 0-10 m), ocnBgchem: MARBL (same grid as ocean), seaIce: CICE5.1 (same grid as ocean). The model was run by the National Center for Atmospheric Research, Climate and Global Dynamics Laboratory, 1850 Table Mesa Drive, Boulder, CO 80305, USA (NCAR) in native nominal resolutions: aerosol: 100 km, atmos: 100 km, atmosChem: 100 km, land: 100 km, landIce: 5 km, ocean: 100 km, ocnBgchem: 100 km, seaIce: 100 km.

Meeting end-of-century global warming targets requires aggressive action on multiple fronts. Recent reports note the futility of addressing mitigation goals without fully engaging the agricultural sector, yet no available assessments combine both nature-based solutions (reforestation, grassland and wetland protection, and agricultural practice change) and cellulosic bioenergy for a single geographic region. Collectively, these solutions might offer a suite of climate, biodiversity, and other benefits greater than either alone. Nature-based solutions are largely constrained by the duration of carbon accrual in soils and forest biomass; each of these carbon pools will eventually saturate. Bioenergy solutions can last indefinitely but carry significant environmental risk if carelessly deployed. We detail a simplified scenario for the U.S. that illustrates the benefits of combining approaches. We assign a portion of non-forested former cropland to bioenergy sufficient to meet projected mid-century transportation needs, with the remainder assigned to nature-based solutions such as reforestation. Bottom-up mitigation potentials for the aggregate contributions of crop, grazing, forest, and bioenergy lands are assessed by including in a Monte Carlo model conservative ranges for cost-effective local mitigation capacities, together with ranges for (a) areal extents that avoid double counting and include realistic adoption rates and (b) the projected duration of different carbon sinks. The projected duration illustrates the net effect of eventually saturating soil carbon pools in the case of most strategies, and additionally saturating biomass carbon pools in the case of reforestation. Results show a conservative end-of-century mitigation capacity of 110 (57 – 178) Gt CO2e for the U.S., ~50% higher than existing estimates that prioritize nature-based or bioenergy solutions separately. Further research is needed to shrink uncertainties but there is sufficient confidence in the general magnitude and direction of a combined approach to plan for deployment now. The dataset is a synthesis of literature values selected based on criteria described in the parent paper’s narrative. The files can be opened in Microsoft Excel or any other spreadsheet that can load Excel-format files.

Estimated population trends can identify declining species to focus biological conservation, but monitoring may fail to illuminate causes of population change and strategies for reversing declines. Monitoring programs can relate trends with environmental attributes to test causal hypotheses, but typical analytical approaches do not explicitly support causal inference, diluting available data for informing conservation. The U.S. Bureau of Land Management (BLM) extended Integrated Monitoring in Bird Conservation Regions with a quasi-experimental sampling design over a 10-year period (2010–2019) to evaluate impacts of oil and gas development on sagebrush birds within the Atlantic Rim Natural Gas Development Project in southern Wyoming. We analyzed resulting data using a multi-scale community occupancy model to estimate trends in species occupancy and richness relevant to management triggers. Additionally, we employed path analysis to evaluate mechanisms underlying observed trends to inform potential management responses. Fine-scale occupancy for sage thrasher (Oreoscoptes montanus) declined within the high-development stratum at a rate sufficient to meet an a priori management trigger established by the BLM. Two additional sagebrush-associated species, Brewer’s (Spizella breweri) and sagebrush sparrow (Artemisiospiza nevadensis), exhibited negative development relationships with trend, as did overall species richness, and richness of grassland, sagebrush, and generalist guilds. We identified well pad density and invasive plants associated with energy development as causal factors contributing to these negative development impacts. We demonstrate an analytical approach for both estimating occupancy trends and identifying underlying causes to inform conservation action. Reducing the development footprint, including well pad density and associated invasive plants, could help reduce or limit impacts on birds within this landscape. Scripts for analyzing data in this repository are archived at https://doi.org/10.5281/zenodo.7566617. Data were analyzed in Program R with modeling implemented using the R package nimble. Most data provided here are stored in an R workspace and thus require Program R to access them. Bird data were collected in conjunction with the Integrated Monitoring and Bird Conservation Regions program, and environmental data were retrieved primarily from online repositories. Detailed methods are described in the manuscript accompanying this repository.

Habitat loss and fragmentation are leading contributors to the endangered status of species. In 2006, the Nakai Plateau contained the largest known Asian elephant (Elephas maximus) population in the Lao People’s Democratic Republic (Lao PDR), and the population was among those with the highest genetic diversity reported for Asian elephants. In 2008, completion of the Nam Theun 2 hydroelectric dam inundated much of the Plateau, resulting in the loss of 40% of elephant habitat. We studied elephant presence, movements, and the incidence of human–elephant conflict (HEC) on the Nakai Plateau and surrounding areas from 2004-2020, before and for 12 years after dam completion. To examine contemporary population dynamics in the Nakai elephants, we used genetic sampling to compare minimum population numbers, demography, and levels of genetic diversity from the wet and dry seasons in 2018/2019, 10 years after dam completion, with those reported in a pre-dam-completion genetic survey. After dam completion, we found a major increase in HEC locally and the creation of new, serious, and persistent HEC problems as far as 100 km away. While we were unable to compare estimated population sizes before and after dam completion, our data revealed a decrease in genetic diversity, a male-biased sex ratio, and evidence of dispersal from the Plateau by breeding-age females. Our results raise concerns about the long-term viability of this important population as well as that of other species in this region. Given that hydropower projects are of economic importance throughout Laos and elsewhere in southeast Asia, this study has important implications for understanding and mitigating their impact. From 2004 to 2020, teams from The Wildlife Conservation Society, The District Agriculture and Forestry Offices (DAFO) of affected districts in Lao PDR and the Nam Theun 2 Power Company (NTPC) conducted studies of the dynamics of elephant populations and the incidence of HEC on the Nakai Plateau and surrounding areas. They recorded the GPS location of each HEC incident, any available details about the elephants involved such as sex, age and group size, and the types of damage incurred. We analyzed the number and distribution of incidences of HEC in the periods before (2004-early 2009) and after dam completion. To characterize the elephant population on the Nakai Plateau 10 years after dam completion, we collected fresh dung samples on the Nakai Plateau from 01 March 2018 – 01 May 2018 (dry season), and from 01 October 2019 – 01 November 2019 (wet season). We genotyped those samples at 18 microsatellite loci and one sexing marker. We regenotyped 10 samples from our Nakai 2006 study (DOI: 10.1007/s10592-010-0148-y) and 9 samples from our Sepon 2011 study (Eggert and Ruiz-Lopez 2012) at the 9 loci that all studies had in common. We compared levels of genetic diversity, sex ratio and age structure across the three studies. Literature cited: Eggert LS, Ruiz-Lopez M. 2012. Analysis of fecal DNA samples to estimate the sex ratio and size of the Sepon Asian elephant population in the Lao PDR using capture-recapture methods. Report to the Wildlife Conservation Society. None, these genotypes are provided in a Microsoft Excel file using GenePop 6 digit (2 alleles, 3 digits each) format.

We captured, banded, and genotyped a total of 104 female sparrows across the two sites and years. We monitored 202 nests (including 301 nestlings) of pure and admixed Saltmarsh and Nelson’s Sparrows across the two sites across the 2016 and 2017 breeding seasons. We conducted nest monitoring at both sites during May-August, encompassing three nesting cycles each in 2016 and 2017, as described in Maxwell et al. 2021 and following protocols from Saltmarsh Habitat and Avian Research Program (SHARP, www.tidalmarshbirds.org). Nests were visited every 3–4 days until completed and assigned an overall fate (fledged, failed due to flooding, failed due to predation, or failed due to unknown causes), following established standardized protocols (Ruskin et al., 2017). We calculated date of nest initiation based on known duration of egg-laying (3–5 days), incubation (11–12 days), and chick development (8–11 days) to determine first egg date following methods developed by Shriver et al. (2007). We collected vegetation and nest characteristic data to test predictions about nesting characteristics as drivers of reproductive success. Vegetation data were collected within 1 m2 surrounding each nest upon its completion (fledge/fail/unknown failure). Measurements included thatch depth (height of vegetative thatch layer from marsh surface in cm) at nest and across four cardinal points in 1 square meter surrounding the nest, average vegetation height directly above and surrounding the nest (in cm across four cardinal points in 1 square meter and at the center), as well as species composition of the vegetation to determine the percent high marsh vegetation surrounding the nest (percent Spartina patens). We recorded physical characteristics of the nests including, height above the ground (cm from cup lip and cup bottom to surface of the marsh), presence/absence of nest canopy (woven/domed structure that effectively covers the nest cup and prevents eggs from washing out of the nest during high tides (Humphreys et al. 2007)), percent of nest visible from above, and the species of vegetation of which the nest was made. To determine timing of nest initiation in relation to the nearest flood tide, we calculated the number of days after the new moon (the highest tidal amplitudes and flooding were on new moon dates due to lunar tidal cycles) that the nest was initiated, with initiation determined as described above, following Shriver et al. (2007). HOBO water level loggers (ONSET, Bourne, MA) were placed at the bottom of a central channel at each study site to monitor the water levels on each day of the breeding season. These loggers measure the total pressure above their location at 15-minute intervals. With barometric pressure collected from the National Oceanic and Atmospheric Administration Stations nearest the study site locations, a compensation was made using HOBOware Pro software to determine water level seen at each marsh in 15-minute intervals throughout the entire three-month breeding season (in 2016 and 2017). Nestlings were banded with a USGS aluminum leg band and a single site-specific color band when they were ~6 days old. Additionally, standard morphological measurements were taken on each nestling during banding, including weight, tarsus length, bill length, head length, and wing cord. Proxys of fitness used in this study were short-term reproductive metrics taken across the two-year study period and included: daily nest survival estimates, fledging success (number of offspring fledged from each nest, including 0), hatching success (number of eggs hatched from each nest, including 0), clutch size (maximum number of eggs/nestlings in a nest), average nestling size, and maximum nestling size in a nest (measured in grams at ~ 6 days of age at banding). These measures of reproductive success represent a snapshot in time (one breeding cycle), and do not reflect lifetime fitness of an individual. Data are provided in their raw form in columns in Excel spreadsheets.  Hybridization and introgression can promote adaptive potential and evolutionary resilience in response to increased pressures of climate change; they can also disrupt local adaptation and lead to outbreeding depression. We investigated female fitness consequences of hybridization in two sister species that are endemic to a threatened tidal marsh ecosystem: Saltmarsh (Ammospiza caudacutus) and Nelson’s Sparrows (A. nelsoni). We found increasing nest flooding rates due to rising sea levels are outpacing potential adaptive benefits of hybridization due to very low overall nesting success in both the Nelson’s and Saltmarsh Sparrows. In the center of the hybrid zone across two years, we determined the success of 201 nests of 104 pure and admixed Saltmarsh and Nelson’s Sparrow females, genotyped using a panel of Single Nucleotide Polymorphisms (SNPs) from double digest restriction-site associated DNA (ddRAD) Sequencing. We evaluated five metrics of female fitness and modeled nesting success in relation to genotypic, environmental, and nesting characteristics. We found differential fitness among Saltmarsh, Nelson’s, and hybrid females, such that birds with predominantly Saltmarsh Sparrow alleles had higher reproductive success than birds with predominantly Nelson’s Sparrow alleles, and hybrids were intermediate. Fledging success increased with two known tidal marsh nesting adaptations: nest height and nesting synchrony with tidal cycles. We found a positive relationship between hybrid index and fitness in daily nest survival in 2016, but not in 2017, likely due to differing levels of precipitation and nest flooding between years. The strongest and most consistent predictors of daily nest survival were nesting synchrony with lunar tidal flooding cycles and daily maximum tide height. Fitness patterns suggest there may be an adaptive benefit of interspecific geneflow for the Nelson’s Sparrow at the detriment of the Saltmarsh Sparrow; however, flooding rates are so high in many years they mask any fitness differences between the species, and all females had poor nesting success, regardless of genetic makeup. Data files are provided as CSV spreadsheet files and do not require any special software to open or use. From here, data can be used for modeling or for creation of capture histories for survival analysis. 

Project: Coupled Model Intercomparison Project Phase 6 (CMIP6) datasets - These data have been generated as part of the internationally-coordinated Coupled Model Intercomparison Project Phase 6 (CMIP6; see also GMD Special Issue: http://www.geosci-model-dev.net/special_issue590.html). The simulation data provides a basis for climate research designed to answer fundamental science questions and serves as resource for authors of the Sixth Assessment Report of the Intergovernmental Panel on Climate Change (IPCC-AR6). CMIP6 is a project coordinated by the Working Group on Coupled Modelling (WGCM) as part of the World Climate Research Programme (WCRP). Phase 6 builds on previous phases executed under the leadership of the Program for Climate Model Diagnosis and Intercomparison (PCMDI) and relies on the Earth System Grid Federation (ESGF) and the Centre for Environmental Data Analysis (CEDA) along with numerous related activities for implementation. The original data is hosted and partially replicated on a federated collection of data nodes, and most of the data relied on by the IPCC is being archived for long-term preservation at the IPCC Data Distribution Centre (IPCC DDC) hosted by the German Climate Computing Center (DKRZ). The project includes simulations from about 120 global climate models and around 45 institutions and organizations worldwide. Summary: These data include the subset used by IPCC AR6 WGI authors of the datasets originally published in ESGF for 'CMIP6.CMIP.MPI-M.ICON-ESM-LR' with the full Data Reference Syntax following the template 'mip_era.activity_id.institution_id.source_id.experiment_id.member_id.table_id.variable_id.grid_label.version'. The ICON-ESM-LR climate model, released in 2017, includes the following components: aerosol: none, prescribed MACv2-SP, atmos: ICON-A (icosahedral/triangles; 160 km; 47 levels; top level 80 km), land: JSBACH4.20, landIce: none/prescribed, ocean: ICON-O (icosahedral/triangles; 40 km; 40 levels; top grid cell 0-12 m), ocnBgchem: HAMOCC, seaIce: unnamed (thermodynamic (Semtner zero-layer) dynamic (Hibler 79) sea ice model). The model was run by the Max Planck Institute for Meteorology, Hamburg 20146, Germany (MPI-M) in native nominal resolutions: aerosol: 250 km, atmos: 250 km, land: 250 km, landIce: none, ocean: 50 km, ocnBgchem: 50 km, seaIce: 50 km.

Methane emissions from aquatic and terrestrial ecosystems play a crucial role in global warming, which is particularly affecting high-latitude ecosystems. As major contributors to methane emissions in natural environments, the microbial communities involved in methane production and oxidation deserve a special attention. Microbial diversity and activity are expected to be strongly affected by the already observed (and further predicted) temperature increase in high-latitude ecosystems, eventually resulting in disrupted feedback methane emissions. The METHANOBASE project has been designed to investigate the intricate relations between microbial diversity and methane emissions in Arctic, Subarctic and Subantarctic ecosystems, under natural (baseline) conditions and in response to simulated temperature increments. We report here a small subunit ribosomal RNA (16S rRNA) analysis of lake, peatland and mineral soil ecosystems.