More Like this

1. Long‐term seedling and small sapling census data from the B arro C olorado I sland 50 ha F orest D ynamics P lot, P anama

   https://doi.org/10.1002/ecy.4140  

   Comita, Liza S.; Aguilar, Salomón; Hubbell, Stephen P.; Pérez, Rolando (July 2023, Ecology)

   Abstract Tropical forests are well known for their high woody plant diversity. Processes occurring at early life stages are thought to play a critical role in maintaining this high diversity and shaping the composition of tropical tree communities. To evaluate hypothesized mechanisms promoting tropical tree species coexistence and influencing composition, we initiated a census of woody seedlings and small saplings in the permanent 50 ha Forest Dynamics Plot (FDP) on Barro Colorado Island (BCI), Panama. Situated in old‐growth, lowland tropical moist forest, the BCI FDP was originally established in 1980 to monitor trees and shrubs ≥1 cm diameter at 1.3 m above ground (dbh) at ca. 5‐year intervals. However, critical data on the dynamics occurring at earlier life stages were initially lacking. Therefore, in 2001 we established a 1‐m²seedling plot in the center of every 5 × 5 m section of the BCI FDP. All freestanding woody individuals ≥20 cm tall and <1 cm dbh (hereafter referred to as seedlings) were tagged, mapped, measured, and identified to species in 19,313 1‐m²seedling plots. Because seedling dynamics are rapid, we censused these seedling plots every 1–2 years. Here, we present data from the 14 censuses of these seedling plots conducted between the initial census in 2001 to the most recent census, in 2018. This data set includes nearly 1 M observations of ~185,000 individuals of >400 tree, shrub, and liana species. These data will permit spatially‐explicit analyses of seedling distributions, recruitment, growth, and survival for hundreds of woody plant species. In addition, the data presented here can be linked to openly‐available, long‐term data on the dynamics of trees and shrubs ≥1 cm dbh in the BCI FDP, as well as existing data sets from the site on climate, canopy structure, phylogenetic relatedness, functional traits, soil nutrients, and topography. This data set can be freely used for non‐commercial purposes; we request that users of these data cite this data paper in all publications resulting from the use of this data set. 

   more » « less
2. The Movement Ecology of Mutualism ( CSEE / ESA 2022, OOS17 )

   https://doi.org/10.1002/bes2.2063  

   Moore, Christopher M.; Shaw, Allison K.; Bruninga‐Socolar, Bethanne; Caves, Eleanor M.; Karnish, Alex T.; Kiesewetter, Kasey N.; Nelson, Annika S.; Pringle, Elizabeth G. (April 2023, The Bulletin of the Ecological Society of America)
3. Climate data from the R ocky M ountain B iological L aboratory (1975–2022)

   https://doi.org/10.1002/ecy.4153  

   Prather, Rebecca M.; Underwood, Nora; Dalton, Rebecca M.; barr, billy; Inouye, Brian D. (September 2023, Ecology)

   Abstract The Rocky Mountain Biological Laboratory (RMBL; Colorado, USA) is the site for many research projects spanning decades, taxa, and research fields from ecology to evolutionary biology to hydrology and beyond. Climate is the focus of much of this work and provides important context for the rest. There are five major sources of data on climate in the RMBL vicinity, each with unique variables, formats, and temporal coverage. These data sources include (1) RMBL resident billy barr, (2) the National Oceanic and Atmospheric Administration (NOAA), (3) the United States Geological Survey (USGS), (4) the United States Department of Agriculture (USDA), and (5) Oregon State University's PRISM Climate Group. Both the NOAA and the USGS have automated meteorological stations in Crested Butte, CO, ~10 km from the RMBL, while the USDA has an automated meteorological station on Snodgrass Mountain, ~2.5 km from the RMBL. Each of these data sets has unique spatial and temporal coverage and formats. Despite the wealth of work on climate‐related questions using data from the RMBL, previous researchers have each had to access and format their own climate records, make decisions about handling missing data, and recreate data summaries. Here we provide a single curated climate data set of daily observations covering the years 1975–2022 that blends information from all five sources and includes annotated scripts documenting decisions for handling data. These synthesized climate data will facilitate future research, reduce duplication of effort, and increase our ability to compare results across studies. The data set includes information on precipitation (water and snow), snowmelt date, temperature, wind speed, soil moisture and temperature, and stream flows, all publicly available from a combination of sources. In addition to the formatted raw data, we provide several new variables that are commonly used in ecological analyses, including growing degree days, growing season length, a cold severity index, hard frost days, an index of El Niño‐Southern Oscillation, and aridity (standardized precipitation evapotranspiration index). These new variables are calculated from the daily weather records. As appropriate, data are also presented as minima, maxima, means, residuals, and cumulative measures for various time scales including days, months, seasons, and years. The RMBL is a global research hub. Scientists on site at the RMBL come from many countries and produce about 50 peer‐reviewed publications each year. Researchers from around the world also routinely use data from the RMBL for synthetic work, and educators around the United States use data from the RMBL for teaching modules. This curated and combined data set will be useful to a wide audience. Along with the synthesized combined data set we include the raw data and the R code for cleaning the raw data and creating the monthly and yearly data sets, which facilitate adding additional years or data using the same standardized protocols. No copyright or proprietary restrictions are associated with using this data set; please cite this data paper when the data are used in publications or scientific events. 

   more » « less
4. GW / SW‐MST : A Groundwater/ Surface‐Water Method Selection Tool

   https://doi.org/10.1111/gwat.13194  

   Hammett, Steven; Day‐Lewis, Frederick D.; Trottier, Brett; Barlow, Paul M.; Briggs, Martin A.; Delin, Geoffrey; Harvey, Judson W.; Johnson, Carole D.; Lane, John W.; Rosenberry, Donald O.; et al (November 2022, Groundwater)

   Abstract Groundwater/surface‐water (GW/SW) exchange and hyporheic processes are topics receiving increasing attention from the hydrologic community. Hydraulic, chemical, temperature, geophysical, and remote sensing methods are used to achieve various goals (e.g., inference of GW/SW exchange, mapping of bed materials, etc.), but the application of these methods is constrained by site conditions such as water depth, specific conductance, bed material, and other factors. Researchers and environmental professionals working on GW/SW problems come from diverse fields and rarely have expertise in all available field methods; hence there is a need for guidance to design field campaigns and select methods that both contribute to study goals and are likely to work under site‐specific conditions. Here, we present the spreadsheet‐based GW/SW‐Method Selection Tool (GW/SW‐MST) to help practitioners identify methods for use in GW/SW and hyporheic studies. The GW/SW‐MST is a Microsoft Excel‐based decision support tool in which the user selects answers to questions about GW/SW‐related study goals and site parameters and characteristics. Based on user input, the tool indicates which methods from a toolbox of 32 methods could potentially contribute to achieving the specified goals at the site described. 

   more » « less
5. The changes in plant and soil C pools and their C : N stoichiometry control grassland N retention under elevated N inputs

   https://doi.org/10.1002/eap.2517  

   Yang, Sen; Liu, Weixing; Guo, Lulu; Wang, Chengzhang; Deng, Meifeng; Peng, Ziyang; Liu, Lingli (March 2022, Ecological Applications)