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Linking river metabolism time series and aquatic vegetation biomass at 11 sites along the Klamath River, California (summer 2019)
Algae blooms in rivers are difficult to quantify due to high heterogeneity, deep and swift conditions, seasonally rapid changes, and the high amount of surveyor effort needed to document river conditions. The data presented here were used to test the extent that summer time series of daily metabolism data reflected the quantity and type of vegetation biomass in a highly productive river with variable primary producer assemblages. Two categories of data are included in this data release: 1) Daily ecosystem metabolism estimates (gross primary production, GPP, ecosystem respiration, ER, and net ecosystem production, NEP), and 2) Reach scale biomass of 3 vegetation assemblages. In addition to these data products, we include the input data used to estimate metabolism, which includes high frequency measurements of dissolved oxygen, water temperature, and light. We also included the raw data used to estimate reach scale biomass, including measurements of filamentous algal and macrophyte percent cover and field samples analyzed for ash free dry mass, which were used to scale field observations of cover to reach scale biomass estimates. Metabolism and vegetation biomass data were collected at 11 reaches along the mid and lower Klamath River, California during summer 2019.
Clear Lake water quality monitoring data from 2019 to 2023 by the University of California, Davis
A major barrier to effective water quality restoration at Clear Lake is the absence of quantitative data on the anticipated response to restoration projects. In-lake monitoring (in-situ measurements) is needed to understand better the processes contributing to poor water quality. This data package contains the in-situ measurements collected by the University of California, Davis at Clear Lake between 2019 and 2023, which include: continous stream properties at three locations (Middle, Scott, and Kelsey Creeks); continuous meteorological variables at seven locations around the perimeter of the lake; continuous lake temperature and dissolved oxygen at multiple depths and locations across the lake (six permanent water quality stations); continuous lake surface temperature in the shoreline; and discreate samples to measure nutrient concentrations and phytoplankton biovolumes and species identification throughout the water column and across all three lake basins every 6-8 weeks.
California's Central Valley Project Improvement Act Predation Contact Point Study - 2022: Predator-prey interactions under low artificial lighting in a laboratory setting
The highest rates of piscivorous predation in the field have been recorded during crepuscular light levels associated with sunrise and sunset or artificial lighting at night (ALAN). We conducted a laboratory study where groups of predator-naïve, hatchery-raised juvenile rainbow trout (Oncorhynchus mykiss) were exposed to natural-origin piscivorous largemouth bass (Micropterus salmoides) under three light treatments representative of brighter crepuscular periods or direct ALAN illumination (“high” treatment), dimmer crepuscular periods or sky glow from ALAN (“medium” treatment), and night or no ALAN (“low” treatment). We then statistically evaluated potential associations between light treatment, prey group cohesion, and predator activity.
The Sierra Lakes Inventory Project: Non-Native fish and community composition of lakes and ponds in the Sierra Nevada, California
The Sierra Lakes Inventory Project (SLIP) was a research endeavor that ran from 1995-2002 and has supported research and management of Sierra Nevada aquatic ecosystems and their terrestrial interfaces. We described the physical characteristics of and surveyed aquatic communities for > 8,000 lentic water bodies in the southern Sierra Nevada, including lakes, ponds, marshes, and meadows. We also created digital map layers for these water bodies when such layers did not exist. The original objective of SLIP was to describe impacts of non-native fish on lake communities, but SLIP data has subsequently enabled study of additional ecological issues, including regional amphibian declines and their impacts on communities, and impacts of non-native fish on terrestrial species. In addition, these data are being used to develop fish removal efforts to restore aquatic ecosystems and recover endangered amphibians. The SLIP data is stored in a relational database that collectively describes water bodies (e.g., depth, elevation, location), surveys (conditions, effort), and communities (including approximately 170 fish, amphibian, reptile, benthic macroinvertebrate, and zooplankton taxa).
Interagency Ecological Program and US Fish and Wildlife Service: Juvenile/Larval Fish and Zooplankton collections at Liberty Island, California 2002-2005 & 2013-2019
The U.S. Fish and Wildlife Service (USFWS) Lodi Fish and Wildlife Office (LFWO) Delta Juvenile Fish Monitoring Program (DJFMP) has intermittently sampled Liberty Island with various equipment since 2002. Liberty Island was a reclaimed agricultural island until it flooded in 1997-1998 and we subsequently left to passively restore as a tidally influenced wetland. Larval trawls and beach were the only sampling methods used during both early (2002-2005) and late (2009-2019) sampling periods. The main purpose of the sampling was to gather information about fish presence and abundance in Liberty Island during the passive restoration, with an emphasis on reproductive and early life-stages of native species. Larval trawls, or tow nets, were used to catch larval fish in 2004-2005 and again from 2013-2019. Zooplankton nets were used 2013-2019. Water quality measurements were collected alongside each tow.
Effects of ectomycorrhizal fungi on pine litter decomposition in temperate pine forests in California, Florida, and Minnesota
This experiment is designed to assess the generality of the effect of ECM fungi on leaf litter decomposition in temperate pine forests. To assess ECM fungal effects on decomposition, we established and ECM fungal knockdown experiment (via trenching) in nine temperate pine forests in California, Florida, and Minnesota. In litter bags incubated (July 2021-July 2022) in paired trenched and untrenched plots at each site we compared leaf litter decomposition (of native pine litter and a common Pinus strobus litter), fungal community composition (via high throughput sequencing), fungal abundance (via qPCR), decomposition enzyme expression, and soil nutrient availability. Contrary to widely cited theory and other results from a subset of our field sites, we found that ECM fungi either increased or did not impact pine litter decomposition in temperate pine forests.
SBC LTER: REEF: Net primary production, growth and standing crop of Macrocystis pyrifera in Southern California
The giant kelp Macrocystis pyrifera forms subtidal forests on shallow reefs in temperate regions of the world. It is one of the fastest-growing multicellular autotrophs on Earth and its high productivity supports diverse marine food webs. In 2008, we published a method for estimating biomass and net primary production (NPP) of giant kelp along with five years of data, to provide a more integrated measure of NPP than those yielded by previous methods. Our method combines monthly field measurements of standing crop and loss rates with a model of kelp biomass dynamics to estimate instantaneous mass-specific growth rates and NPP for each season of each year. We have since improved our approach to account for several previously unresolved sources of biomass loss. These improvements have led to a near doubling of our prior estimates of growth and NPP. At our site with the most persistent stand of giant kelp, NPP averages ~5.2 kg dry mass m-2 y-1 and results from the rapid growth (~3.5% per day) of a relatively small standing biomass (~ 0.4 kg dry mass m-2 on average) that turns over ~ 12 times annually. Here we provide revised estimates of seasonal biomass, growth and NPP for the five years covered by our previous publication (2002-2006), along with an additional data collect since then (2007-present). We also present updated relationships for predicting giant kelp biomass and NPP from much more easily obtained measurements of frond density. These data can be used to understand the mechanisms that drive variation in giant kelp NPP at a wide range of temporal scales.
SBC LTER: Reef: Historical Kelp Database for giant kelp (Macrocystis pyrifera) biomass in California and Mexico
ISP Alginates (formerly Kelco Co.) has collected information on the abundance of giant kelp (Macrocystis pyrifera) in California and Mexico from routine aerial surveys since 1957. The standard protocol consists of an observer visually estimating the amount of harvestable giant kelp biomass within designated kelp beds from a small fixed-wing aircraft. Observations were recorded on paper data sheets in the field and archived in notebooks housed at ISP Alginates. With cooperation from ISP Alginates, the SBCLTER converted ISP Alginates long-term records of giant kelp biomass into a digital format. The database consists of a data table containing kelp biomass, a catalog of maps. The format ISP Alginates used to report kelp abundance data changed periodically over the course of the collecting period. These details, pus descriptions of designated kelp beds are described in the protocol document.
SBC LTER: Reef: Abundance, size and fishing effort for California Spiny Lobster (Panulirus interruptus), ongoing since 2012
Data on abundance, size and fishing pressure of California spiny lobster (Panulirus interruptus) are collected along the mainland coast of the Santa Barbara Channel. Spiny lobsters are an important predator in giant kelp forests off southern California. Two SBC LTER study reefs are located in or near the California Fish and Game Network of Marine Protected Areas (MPA), Naples and Isla Vista, both established as MPAs on 2012-01-01. MPAs provide a unique opportunity to investigate the effects of fishing on kelp forest community dynamics. Sampling began in 2012 and is ongoing. This dataset contains two tables. 1) Abundance and size data collected annually by divers in late summer before the start of the fishing season at five SBC LTER long term kelp forest study sites: two within MPAs (Naples and Isla Vista) and three outside (Arroyo Quemado, Mohawk and Carpinteria). 2) Fishing pressure, as determined by counting the number of commercial trap floats. Data are collected every two to four weeks during the lobster fishing season (October to March) at nine sites along the mainland, eight of which are also SBC LTER long-term kelp forest study reefs. See Methods for more information.
InSAR stack of San Francisco Bay, California from Sentinel-1 descending track 42 processed with GMTSAR
<p>A stack of unwrapped interferograms in the San Francisco Bay area, California, USA</p> <p>Sensor: Sentinel-1 descending track 42</p> <p>Processor: <a href="https://github.com/gmtsar/gmtsar" target="_blank" rel="noopener">GMTSAR</a></p> <p>This is an input dataset for the time series analysis with <a href="https://github.com/insarlab/MintPy/">MintPy</a>.</p> <p>The tropospheric delay estimated from ERA-5 using PyAPS is attached.</p> <p><strong>Version 1.x (~2.3 GB)</strong><br>Time: 2014.12.31 - 2024.06.05 (333 acquisitions, 1297 interferograms)</p> <p><strong>Version 0.x (~290 MB; for fast testing of code development)</strong><br>Time: 2020.01.04 - 2021.07.15 (70 acquisitions, 184 interferograms)</p>
Supplementary Material for "Using Unstructured Crowd-sourced Data to Evaluate Urban Tolerance of Terrestrial Native Animal Species within a California Mega-City"
<p>This data repository is for the publication "Using Unstructured Crowd-sourced Data to Evaluate Urban Tolerance of Terrestrial Native Animal Species within a California Mega-City" and contains all R scripts and data files to reproduce results as well as all supplementary tables and figures.</p>
Audio tagging of avian dawn chorus recordings in California, Oregon, and Washington
<p><strong>General Summary</strong></p> <p>This acoustic data collection includes 1,575 5-minute soundscape recordings randomly selected from passive acoustic recordings made at 525 sites during 2022 on federally managed lands in western California, Oregon, and Washington, USA. We fully labeled 141 recordings (11.75 hrs) with 39,717 annotations for 118 sound types, including 58 avian species, two mammalian species, six aggregated biotic sounds, and eight non-biotic sound types. An additional 215 recordings were partially annotated with 1,466 annotations. The remaining unlabeled recordings have been included to facilitate novel research applications and methodological evaluations. Beyond the labeled soundscape recordings, we have included township and range identifications and 38 environmental covariates for each recording location.</p> <p><strong>Data Collection</strong></p> <p>Lesmeister et al. (2021) collected passive acoustic recordings during 2022 in support of long-term monitoring of federally threatened northern spotted owl (<em>Strix occidentalis caurina) </em>populations under the Northwest Forest Plan Effective Monitoring Program (U. S. Fish and Wildlife Service 1990, U. S. Department of Agriculture and U. S. Department of the Interior 1994). These data were collected at 643 hexagons that were randomly selected from a tessellation of 5 km2 hexagons covering the entire range of the northern spotted owl (Northern California, Oregon, Washington) under a selective constraint that hexagons contain ≥ 50 % forest-capable lands (<em>def.</em> forested lands or lands capable of developing closed-canopy forests) and be ≥ 25% federal ownership (Davis et al., 2011).</p> <p>Each hexagon was sampled by four Song Meter 4 (SM4) acoustic recording units (Wildlife Acoustics, Maynard, MA) deployed in a standardized spatial arrangement, such that recorders on a site were placed ≥ 500 m apart and were ≥ 200 m from the edge of the sampling hexagon boundary. Recorders were mounted to small trees (15 – 20 cm diameter at breast height) approximately 1.5 m above the ground and were placed on mid-to-upper slopes and ≥ 50 m from roads, trails, and streams. The SM4 devices each have two built-in omnidirectional microphones with a signal-to-noise ratio of 80 dB, typical at 1 kHz, and a recording bandwidth of 20 Hz – 48 kHz. Each device recorded ~11 hours of audio daily for six weeks from March to August at a sampling rate of 32 kHz. The daily recording schedule included a 4-hour window from two hours before sunrise to two hours after sunrise, a 4-hour window from one hour before sunset to 3 hours after sunset, and 10-minute recordings outside the two longer recording blocks at the start of every hour.</p> <p><strong>Data Sampling</strong></p> <p>The goal of this project was to develop a tagged audio dataset (hereafter project dataset) focused on the avian dawn chorus, which is an ecologically important period for the study of avian behavior (McNamara et al. 1987, Staicer et al. 1996, Zhang et al. 2015) and monitoring avian biodiversity (Bibby et al. 2000), but remains a challenging problem for acoustic classification systems (Duan et al. 2013, Stowell 2022). Passive acoustic monitoring on our sites occurs throughout the day. We filtered the full dataset to recordings collected between May and August during the hour immediately after sunrise. From the recordings meeting our filtering criteria, we randomly selected three 5-minute files from each site, which were assigned ordinal labels 'A, 'B,' or 'C.' The final project dataset comprised 131.25 hours of acoustic data.</p> <p><strong>Annotation Protocol</strong></p> <p>We randomly selected 141 sites from the project dataset and fully annotated each recording at a 2-second resolution. We applied labels to each 2-second window of the selected recordings following a predefined sound phonology library (available in the 'metadata.tsv' file), which concatenated the 2021 eBird taxonomy codes (Clements list; Clements et al. 2022) with standardized sonotype codes that incremented depending on the species repertoire (i.e., 'call_1,' 'song_1,' 'drum_1'). For example, 'herthr_song_1' is the label for Hermit Thrush, song_1. Unknown signals were labeled 'unknown,' and clips with no biotic signals (or noise classes of interest documented in metadata.tsv) were labeled 'empty.' Windows were labeled 'complete' and considered fully annotated when every signal was assigned an annotation. Files were deemed fully annotated when every 2-second window contained the 'complete' label.</p> <p><strong>Environmental Covariates</strong></p> <p>Sampling locations will not be published to afford protections for Federally Threatened or Endangered species which may occur on our sites. However, we provide the State, Township, and Range for each sampling location along with the site-specific values for 38 forest structure, topographic, and climatic environmental covariates developed by the Landscape Ecology, Modeling, Mapping, and Analysis group in the Pacific Northwest (<a href="https://lemma.forestry.oregonstate.edu/data">https://lemma.forestry.oregonstate.edu/data</a>; Ohmann and Gregory 2002). State, Township, and Range values are sufficient to explore geographic variation in species- or community-specific call and song phenology and the extracted environmental covariates may provide useful contextual information for novel machine-learning developments (Liu et al. 2018). </p> <p><strong>Description of Data Format</strong></p> <p>The fully annotated audio files can be accessed by downloading and extracting "annotated_recordings.zip." Partially annotated and non-annotated audio files can be accessed by downloading and extracting "additional_recordings_part_1.zip" or "additional_recordings_part_2.zip." Acoustic file names contain site and replicate indicators, such that file "Site_001_Rep_A.wav' was recorded on site 1 and is the A replicate random draw from the available set of dawn chorus recordings. The site and replicate numbers link to additional recording information in "files.tsv," annotations in "annotations.tsv" and "partial_annotations.tsv," as well as site and replicate specific environmental characteristics in "environmental_characteristics.tsv."</p> <p>Metadata describing sound classes and environmental characteristics can be found in "metadata.tsv," and "environmental_characteristics_metadata.tsv."</p> <p><strong>Acknowledgments</strong></p> <p>Acoustic data collection was funded and collected by the US Forest Service and the US Bureau of Land Management. Annotation work was funded by Google. We would also like to thank the many biologists that collected and processed the data compiled here. The use of trade or firm names in this publication is for reader information and does not imply endorsement by the U.S. Government of any product or service.</p>
Assessment of vulnerability to climate change of coastal communities in the Gulf of California and the Yucatan Peninsula: vulnerability outputs
<p>The dataset includes the outputs of the project: "Assessment of vulnerability to climate change of coastal communities in the Gulf of California and the Yucatan Peninsula: vulnerability outputs" funded by the David and Lucille Packard Foundation and awarded to H. Reyes-Bonilla (UABCS). </p> <p>This study analyzed vulnerability of fisheries-dependent coastal communities based on three components: a) adaptive capacity (84 indicators), which reflect the ability of a community to respond and recover after adverse events; b) susceptibility (11 indicators) which was determined based on fishing dependence; and c) exposure (31 indicators) that was evaluated with current environmental data. Future vulnerability was determined for a 2050 horizon and based on two climate change scenarios: SSP126, which represents low emissions, and SSP585, which takes into consideration that the amount of greenhouse gases will continue to increase. These data come from the Coupled Model Intercomparison Project 6 (CMIP6), which serves as the basis for the 6th IPCC report. We evaluated vulnerability using indicators what were available at the local scale.</p>
Dataset of Survey Results on the Integration of Industry 4.0 in University Education (Baja California, 2024)
<p>This dataset contains the results of a survey conducted in 2024 on the integration of Industry 4.0 concepts and technologies in university education in Baja California. The survey was designed to assess the current state of adoption, challenges, and opportunities related to Industry 4.0 within academic institutions. The data includes responses from engineering students at the Autonomous University of Baja California (UABC) and the Polytechnic University of Baja California (UPBC). The insights gathered aim to inform future strategies for enhancing the implementation of Industry 4.0 in higher education curricula.</p>
Sediment Budget for Timber Harvest in a California Coastal Watershed
<p>Dataset for Publication: Sediment Budget for Timber Harvest in a California Coastal Watershed</p> <p> </p>
Data from: The thermal limits of native plant species in California Coastal Sage Scrub
<p>Field and laboratory data for Goldsmith et al. (<em>In Review</em>) entitled, "The thermal limits of native plant species in California Coastal Sage Scrub." Four data files are included: </p> <p><strong><em>Goldsmithetal_PlantFunctionalTraitMetaData-18July24.xlsx </em></strong>-Provides metadata (header, description, units, measurement type, and expample) for each column of the file entitled "<em>Goldsmithetal_PlantFunctionalTraitData-18July24.csv." </em></p> <p><em><strong>Goldsmithetal_PlantFunctionalTraitData-18July24.csv </strong>- </em>Provides raw data for field and lab observations of plant functional traits as described in the methods section of this data record. </p> <p><em><strong>Goldsmithetal_PlantFvFmLabData-29March24.csv </strong>- </em>Provides raw data for experimental lab observations of leaf fv/fm following experimental heat treatments as described in the methods section of this data record. <em><br></em></p> <p><em><strong>Goldsmithetal_PlantFvFmLabMetaData-2Aug23.xlsx</strong> - </em>Provides metadata (header, description, units, measurement type, and expample) for each column of the file entitled "Goldsmithetal_PlantFvFmLabData-29March24.csv." </p> <p> </p> <p>Contact Greg Goldsmith (goldsmith at chapman dot edu) for additional information. </p>
NLL-SSST-coherence earthquake relocation catalogs for the Parkfield and Lone Pine, California earthquake sequence.
<p>CSV tables of the final, NLL-SSST-coherence earthquake relocation catalogs for the Parkfield and Lone Pine, California earthquake sequence.</p> <p>These datasets are from relocations presented in the article<br> High-precision, earthquake location using source-specific station terms and inter-event waveform similarity<br> submitted to Journal of Geophysical Research Solid Earth</p> <p> </p> <p> </p>
Third Uniform California Earthquake Rupture Forecast (UCERF3) Fault System Solutions
<p>Data files for the Third Uniform California Earthquake Rupture Forecast (UCERF3), as described in <a href="https://doi.org/10.1785/0120130164">https://doi.org/10.1785/0120130164</a>.<br> <br> These data are stored in the original UCERF3 Fault System Solution file format, which uses binary files within zip containers. This format is being revised, and updates to this dataset will be published when the new and more user friendly format is finalized. See <a href="https://opensha.org/File-Formats">https://opensha.org/File-Formats</a> for more information.<br> <br> File descriptions:<br> <br> <strong>Branch Averaged Files</strong></p> <p>These files contain branch-averaged fault system solutions, where rupture properties (magnitude, rake, rate of occurrence, etc) are averaged across all UCERF3 logic tree branches, according to each branch's weighting in the final model. This is the simplest version of the model, and can be used as a quick approximation to mean hazard. One file exists for each fault model, and these files are compatible with the time-dependent version of UCERF3.</p> <ul> <li><em>branch_averaged_ucerf3_sol_FM3_1.zip</em> - fault model 3.1 branch averaged fault system solution</li> <li><em>branch_averaged_ucerf3_sol_FM3_2.zip</em> - fault model 3.2 branch averaged fault system solution</li> </ul> <p><strong>Full Model (Compound Solutions)</strong></p> <p>These files contain the full UCERF3 logic tree, and can be used to extract data for individual logic tree branches (e.g., for use in hazard calculations that consider all epistemic uncertainties).</p> <ul> <li><em>full_ucerf3_compound_sol.zip</em> - full compound solution file with information on all 1,440 time-independent logic tree branches</li> <li><em>full_ucerf3_compound_sol_with_individual_runs.zip</em> - same as above, but also containing rates for each of 10 simulated annealing inversion runs for each logic tree branch (total of 14,400 inversions)</li> </ul> <p><strong>True Mean Solutions</strong></p> <p>A different type of branch averaged solution, the “true mean” solution, is also available. They are similar to the branch averaged fault system solution described above, but instead use duplicate versions of each rupture whenever a key property (rake, magnitude, area) changes. This retains all variability allowing for quick reproduction of mean UCERF3 results with a minimum set of ruptures. The MeanUCERF3 ERF implemented in <a href="https://opensha.org">OpenSHA</a> uses these files and also allows the user to apply various approximations to further reduce the rupture count.</p> <p>Note: These solutions are not compatible with time dependent UCERF3 calculations as multiple instances of each subsection may exist, resulting in rate partitioning between instances and incorrect recurrence intervals for renewal model calculations.</p> <ul> <li><em>true_mean_ucerf3_sol.zip</em> - true mean fault system solution, across both fault models</li> <li><em>true_mean_ucerf3_sol_FM3_1.zip</em> - true mean fault system solution, only for fault model 3.1</li> <li><em>true_mean_ucerf3_sol_FM3_2.zip</em> - true mean fault system solution, only for fault model 3.2</li> </ul> <p><strong>Metadata</strong></p> <p>A copy of the original file format description is included in <em>file_format.md</em>, and is also <a href="https://opensha.org/File-Formats">available online here</a>. A CSV file that includes information on each gridded seismicity location is also included (<em>relm_gridded_region.csv</em>).</p>
Multiple-benefit Conservation in Practice: Metrics Data for Quantifying Multidimensional Impacts of Landscape Change in California's Sacramento–San Joaquin Delta
<p><strong>SUMMARY</strong><br> These data represent estimated mean value, standard error, and units for a range of metrics by land cover class in the Sacramento-San Joaquin Delta. Metrics are grouped into three major categories: Agricultural Livelihoods (including metrics for gross production value, number of agricultural jobs, and annual wages per employee), Water Quality (in terms of the application rates for pesticides identified as critical pesticides, groundwater contaminants, and those posing a high or moderate risk to aquatic organisms), and Climate Change Resilience (qualitative scores representing relative tolerance for heat, drought, and flood).</p> <p><strong>DESCRIPTION</strong><br> These data were developed to facilitate projecting the net impacts of land cover change scenarios on multiple metrics of interest to the Sacramento-San Joaquin Delta, including potential benefits and trade-offs. They were used in initial analyses of scenarios representing habitat restoration and perennial crop expansion, and they are required for using the R package "DeltaMultipleBenefits", which provides the code and work flow for repeating the initial analyses or analyzing new scenarios.</p> <p>For additional details about the development and applications of these data, please see: </p> <ul> <li>Dybala KE, et al. (In review) Multiple-benefit Conservation in Practice: A Framework for Quantifying Multi-dimensional Impacts of Landscape Change in California’s Sacramento–San Joaquin Delta </li> <li>Dybala KE (2023) <em>DeltaMultipleBenefits: Projecting the Multiple Benefits of Land Cover Change in the Sacramento-San Joaquin River Delta.</em> R package version 1.0.0. doi: 10.5281/zenodo.7718620. Available from: https://pointblue.github.io/DeltaMultipleBenefits </li> </ul> <p><strong>FUNDING STATEMENT</strong><br> These data were developed as part of the project "Trade-offs and Co-benefits of Landscape Change on Bird Communities and Ecosystem Services in the Sacramento–San Joaquin River Delta", funded by Proposition 1 Delta Water Quality and Ecosystem Restoration Program, Grant Agreement Number – Q1996022, administered by the California Department of Fish and Wildlife.</p> <p><strong>POINT OF CONTACT</strong><br> Kristen Dybala, Point Blue Conservation Science, kdybala@pointblue.org</p> <p><strong>SUGGESTED CITATION</strong><br> Dybala KE. 2023. Multiple-benefit Conservation in Practice: Metrics Data for Quantifying Multi-dimensional Impacts of Landscape Change in California’s Sacramento–San Joaquin Delta. doi:10.5281/zenodo.7504874.</p> <p><strong>DATA DISTRIBUTION</strong><br> Zenodo (https://doi.org/10.5281/zenodo.7504874)</p> <p><strong>PROGRESS</strong><br> Complete, but note that the accompanying manuscript has not yet undergone peer-review, and thus these data may require future revision.</p> <p><strong>UPDATE FREQUENCY</strong><br> As Needed</p> <p><strong>DATE</strong><br> These data were compiled in 2022, based on data from the Quarterly Census of Employment and Wages 2014-2020 (EDD 2022), annual County Agricultural Commissioners Reports 2014-2020 (CDFA 2022), Pesticide Use Report Data 2014-2018 (CDPR 2022), and qualitative assessments of climate change resilience (Peterson et al. 2020, DSC 2021).</p> <p><strong>Literature Cited:</strong></p> <ul> <li>CDFA. 2022. County Ag Commissioners’ Data Listing. California Department of Food & Agriculture. Available from: https://www.nass.usda.gov/Statistics_by_State/California/Publications/AgComm/index.php</li> <li>CDPR. 2022. Pesticide Use Report Data. California Department of Pesticide Regulation. Available from: https://www.cdpr.ca.gov/docs/pur/purmain.htm</li> <li>DSC. 2021. Delta Adapts: Creating a Climate Resilient Future. Public Review Draft. Delta Stewardship Council. Available from https://deltacouncil.ca.gov/delta-plan/climate-change</li> <li>EDD. 2022. Quarterly Census of Employment and Wages (QCEW). California Employment Development Department. Available from: https://data.edd.ca.gov/Industry-Information-/Quarterly-Census-of-Employment-and-Wages-QCEW-/fisq-v939</li> <li>Peterson C, Marvinney E, Dybala K. 2020. Multiple Benefits from Agricultural and Natural Land Covers in the Central Valley, CA. Migratory Bird Conservation Partnership, Sacramento, CA. Dryad Dataset doi:10.25338/B8061X</li> </ul> <p><strong>FIELD DEFINITIONS</strong></p> <ul> <li><strong>METRIC_CATEGORY: </strong>Broad grouping assigned to each METRIC; one of Agricultural Livelihoods, Water Quality, or Climate Change Resilience</li> <li><strong>METRIC: </strong>Specific metric being estimated; one of Agricultural Jobs, Annual Wages, Gross Production Value, Drought, Flood, Heat, Critical Pesticides, Groundwater Contaminant, or Risk to Aquatic Organisms</li> <li><strong>UNIT: </strong>The units in which the <strong>METRIC </strong>is estimated</li> <li><strong>CODE_NAME:</strong> The land cover class or subclass for which the <strong>METRIC </strong>is estimated</li> <li><strong>LABEL: </strong>A more user-friendly version of <strong>CODE_NAME</strong>, useful for creating figures and tables</li> <li><strong>SCORE_MEAN:</strong> The mean value of each METRIC estimated for each land cover class or subclass</li> <li><strong>SCORE_SE: </strong>The standard error of the mean</li> </ul> <p><strong>ABBREVIATION DEFINITIONS</strong></p> <ul> <li><strong>FTE: </strong>full-time equivalents; refers to converting monthly agricultural jobs data to annual estimates by dividing by 12</li> <li><strong>ha:</strong> hectares</li> <li><strong>kg: </strong>kilograms</li> <li><strong>USD: </strong>U.S. dollars</li> <li><strong>yr: </strong>year</li> </ul> <p><strong>ACCESS & USE CONSTRAINTS</strong><br> CC-by-4.0 (https://creativecommons.org/licenses/by/4.0/)</p> <p><strong>KEYWORDS</strong></p> <ul> <li><strong>Themes:</strong> agriculture, livelihoods, economy, water quality, pesticides, climate change, resilience, multiple-benefit conservation</li> <li><strong>Place:</strong> Sacramento-San Joaquin River Delta, Central Valley, California<br> </li> </ul>
Multiple-benefit Conservation in Practice: Supplemental Spatial Data for Quantifying Multidimensional Impacts of Landscape Change in California's Sacramento–San Joaquin Delta
<p><strong>SUMMARY</strong><br> Spatial data representing climate, proximity to streams, and probability of flooding in the Sacramento-San Joaquin Delta.</p> <p><strong>DESCRIPTION</strong><br> These data were compiled as predictors of the distribution of riparian landbird species and groups of waterbird species, to facilitate projecting the probability of species or group presence across a given landscape. They were used to identify Priority Bird Conservation Areas and in analyses of the impacts of scenarios representing habitat restoration and perennial crop expansion on suitable habitat. These data are required for using the R package "DeltaMultipleBenefits", which provides the code and work flow for repeating the initial analyses or analyzing new scenarios.</p> <p>For additional details about the development and applications of these data, please see: </p> <ul> <li>Dybala KE, et al. (<em>In review</em>) Multiple-benefit Conservation in Practice: A Framework for Quantifying Multi-dimensional Impacts of Landscape Change in California’s Sacramento–San Joaquin Delta</li> <li>Dybala KE, Sesser K, Reiter M, Shuford WD, Golet GH, Hickey C, Gardali T (<em>In review</em>) Priority Bird Conservation Areas in California’s Sacramento–San Joaquin Delta. </li> <li>Dybala KE (2023) <em>DeltaMultipleBenefits: Projecting the Multiple Benefits of Land Cover Change in the Sacramento-San Joaquin River Delta</em>. R package version 1.0.0. doi: 10.5281/zenodo.7718620. Available from: https://pointblue.github.io/DeltaMultipleBenefits.</li> </ul> <p><strong>FUNDING STATEMENT</strong><br> These data were developed as part of the project "Trade-offs and Co-benefits of Landscape Change on Bird Communities and Ecosystem Services in the Sacramento–San Joaquin River Delta", funded by Proposition 1 Delta Water Quality and Ecosystem Restoration Program, Grant Agreement Number – Q1996022, administered by the California Department of Fish and Wildlife.</p> <p><strong>POINT OF CONTACT</strong><br> Kristen Dybala, Point Blue Conservation Science, kdybala@pointblue.org</p> <p><strong>SUGGESTED CITATION</strong><br> Dybala KE. 2023. Multiple-benefit Conservation in Practice: Supplemental Spatial Data for Quantifying Multidimensional Impacts of Landscape Change in California’s Sacramento–San Joaquin Delta. doi:10.5281/zenodo.7672193.</p> <p><strong>DATA DISTRIBUTION</strong><br> Zenodo (https://doi.org/10.5281/zenodo.7672193)</p> <p><strong>PROGRESS</strong><br> Complete</p> <p><strong>UPDATE FREQUENCY</strong><br> None planned</p> <p><strong>DATE</strong><br> These data were compiled in 2022, based on data from WorldClim (representing 1970-2000), National Hydrography Dataset (published 2020), and Point Blue's Water Tracker (representing 2013-2019).</p> <p><strong>FIELD DEFINITIONS</strong></p> <ul> <li><strong>bio_1: </strong>annual mean temperature (C), 1970-2000 (WorldClim; Fick and Hijmans 2017)</li> <li><strong>bio_12:</strong> total annual precipitation (mm), 1970-2000 (WorldClim; Fick and Hijmans 2017)</li> <li><strong>streamdist: </strong>square root of the distance to the nearest stream (m) (National Hydrography Dataset; USGS 2020)</li> <li><strong>pwater_fall:</strong> mean probability of open surface water during the fall, 2013-2019 (Point Blue Water Tracker; Reiter et al. 2018)</li> <li><strong>pwater_win:</strong> mean probability of open surface water during the winter, 2013-2019 (Point Blue Water Tracker; Reiter et al. 2018)</li> </ul> <p><strong>Literature Cited</strong></p> <ul> <li>Fick SE, Hijmans RJ. 2017. WorldClim 2: new 1-km spatial resolution climate surfaces for global land areas. Int J Climatol. 37:4302–4315. <a href="https://doi.org/10.1002/joc.5086">https://doi.org/10.1002/joc.5086</a> </li> <li>Reiter ME, Elliott NK, Barbaree B, Moody D. 2018. An automated open surface water tracking system for California’s Central Valley. Report to the U.S. Fish and Wildlife Service. Petaluma, California: Point Blue Conservation Science. Available from: <a href="https://data.pointblue.org/apps/autowater/ ">https://data.pointblue.org/apps/autowater/ </a></li> <li>[USGS] United States Geological Survey. 2020. National Hydrography Dataset Best Resolution (NHD) for Hydrologic Units (HU) 4 - 1802, 1803, 1804, 1805. Reston (VA): U.S. Geological Survey. Available from: <a href="https://www.usgs.gov/core-science-systems/ngp/national-hydrography/access-national-hydrography-products ">https://www.usgs.gov/core-science-systems/ngp/national-hydrography/access-national-hydrography-products </a></li> </ul> <p><strong>ABBREVIATION DEFINITIONS</strong><br> N/A</p> <p><strong>COORDINATE REFERENCE SYSTEM</strong><br> WGS 84 / UTM zone 10N (EPSG:32610)</p> <p><strong>ACCESS & USE CONSTRAINTS</strong><br> CC-by-4.0 (https://creativecommons.org/licenses/by/4.0/)</p> <p><strong>KEYWORDS</strong></p> <ul> <li><strong>Themes:</strong> climate, temperature, precipitation, hydrology, streams, water, flood, remote sensing </li> <li><strong>Place: </strong>Sacramento-San Joaquin River Delta, Central Valley, California</li> </ul>
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