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1. Developmental onset of enduring long‐term potentiation in mouse hippocampus

   https://doi.org/10.1002/hipo.23257  

   Ostrovskaya, Olga I.; Cao, Guan; Eroglu, Cagla; Harris, Kristen M. (September 2020, Hippocampus)

   Abstract Analysis of long‐term potentiation (LTP) provides a powerful window into cellular mechanisms of learning and memory. Prior work shows late LTP (L‐LTP), lasting >3 hr, occurs abruptly at postnatal day 12 (P12) in thestratum radiatumof rat hippocampal area CA1. The goal here was to determine the developmental profile of synaptic plasticity leading to L‐LTP in the mouse hippocampus. Two mouse strains and two mutations known to affect synaptic plasticity were chosen: C57BL/6J andFmr1^−/yon the C57BL/6J background, and 129SVE andHevin^−/−(Sparcl1^−/−) on the 129SVE background. Like rats, hippocampal slices from all of the mice showed test pulse‐induced depression early during development that was gradually resolved with maturation by 5 weeks. All the mouse strains showed a gradual progression between P10‐P35 in the expression of short‐term potentiation (STP), lasting ≤1 hr. In the 129SVE mice, L‐LTP onset (>25% of slices) occurred by 3 weeks, reliable L‐LTP (>50% slices) was achieved by 4 weeks, andHevin^−/−advanced this profile by 1 week. In the C57BL/6J mice, L‐LTP onset occurred significantly later, over 3–4 weeks, and reliability was not achieved until 5 weeks. Although some of theFmr1^−/ymice showed L‐LTP before 3 weeks, reliable L‐LTP also was not achieved until 5 weeks. L‐LTP onset was not advanced in any of the mouse genotypes by multiple bouts of theta‐burst stimulation at 90 or 180 min intervals. These findings show important species differences in the onset of STP and L‐LTP, which occur at the same age in rats but are sequentially acquired in mice. 

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2. Spring photosynthetic onset and net CO ₂ uptake in Alaska triggered by landscape thawing

   https://doi.org/10.1111/gcb.14283  

   Parazoo, Nicholas C.; Arneth, Almut; Pugh, Thomas A. M.; Smith, Ben; Steiner, Nicholas; Luus, Kristina; Commane, Roisin; Benmergui, Josh; Stofferahn, Eric; Liu, Junjie; et al (May 2018, Global Change Biology)

   Abstract The springtime transition to regional‐scale onset of photosynthesis and net ecosystem carbon uptake in boreal and tundra ecosystems are linked to the soil freeze–thaw state. We present evidence from diagnostic and inversion models constrained by satellite fluorescence and airborneCO₂from 2012 to 2014 indicating the timing and magnitude of spring carbon uptake in Alaska correlates with landscape thaw and ecoregion. Landscape thaw in boreal forests typically occurs in late April (DOY111 ± 7) with a 29 ± 6 day lag until photosynthetic onset. North Slope tundra thaws 3 weeks later (DOY133 ± 5) but experiences only a 20 ± 5 day lag until photosynthetic onset. These time lag differences reflect efficient cold season adaptation in tundra shrub and the longer dehardening period for boreal evergreens. Despite the short transition from thaw to photosynthetic onset in tundra, synchrony of tundra respiration with snow melt and landscape thaw delays the transition from net carbon loss (at photosynthetic onset) to net uptake by 13 ± 7 days, thus reducing the tundra net carbon uptake period. Two globalCO₂inversions using aCASA‐GFEDmodel prior estimate earlier northern high latitude net carbon uptake compared to our regional inversion, which we attribute to (i) early photosynthetic‐onset model prior bias, (ii) inverse method (scaling factor + optimization window), and (iii) sparsity of available AlaskanCO₂observations. Another global inversion with zero prior estimates the same timing for net carbon uptake as the regional model but smaller seasonal amplitude. The analysis of Alaskan eddy covariance observations confirms regional scale findings for tundra, but indicates that photosynthesis and net carbon uptake occur up to 1 month earlier in evergreens than captured by models orCO₂inversions, with better correlation to above‐freezing air temperature than date of primary thaw. Further collection and analysis of boreal evergreen species over multiple years and at additional subarctic flux towers are critically needed. 

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3. 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. 

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4. 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)
5. 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. 

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