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At least 1,117 records · Page 62

The effect of the vertical gradients of photosynthetic parameters on the CO 2 assimilation and transpiration of a Panamanian tropical forest

Terrestrial biosphere models (TBMs) include the representation of vertical gradients in leaf traits associated with modeling photosynthesis, respiration, and stomatal conductance. However, model assumptions associated with these gradients have not been tested in complex tropical forest canopies. Here we compared TBM representation of the vertical gradients of key leaf traits with measurements made in a tropical forest in Panama, and then quantified the impact of the observed gradients on simulated canopy scale CO 2 and water fluxes. Comparison between observed and TBM trait gradients showed divergence that impacted canopy scale simulations of water vapor and CO 2 exchange. Notably, the ratio between the dark respiration rate and the maximum carboxylation rate was lower near the ground than at the top-of-canopy, leaf-level water-use efficiency was markedly higher at the top-of-canopy, and the decrease in maximum carboxylation rate from the top-of-canopy to the ground was less than TBM assumptions. The representation of the gradients of leaf traits in TBMs is typically derived from measurements made within-individual plants, or, for some traits, assumed constant due to a lack of experimental data. Our work shows that these assumptions are not representative of the trait gradients observed in species-rich, complex tropical forests.

54 ENVIRONMENTAL SCIENCES↗

Carbon isotopic composition of forest soil respiration in the decade following bark beetle and stem girdling disturbances in the Rocky Mountains: Carbon isotopes of soil respiration following disturbance

Bark beetle outbreaks are widespread in western North American forests, reducing primary productivity and transpiration, leading to forest mortality across large areas and altering ecosystem carbon cycling. Here the carbon isotope composition (δ13C) of soil respiration (δJ) was monitored in the decade after disturbance for forests affected naturally by mountain pine beetle infestation and artificially by stem girdling. The seasonal mean δJ changed along both chronosequences. We found (a) enrichment of δJ relative to controls (<1 ‰) in near-surface soils in the first 2 years after disturbance; (b) depletion (1‰ or no change) during years 3–7; and (c) a second period of enrichment (1–2‰) in years 8–10. Results were consistent with isotopic patterns associated with the gradual death and decomposition of rhizosphere organisms, fine roots, conifer needles and woody roots and debris over the course of a decade after mortality. Finally, δJ was progressively more 13C-depleted deeper in the soil than near the surface, while the bulk soil followed the well-established pattern of 13C-enrichment at depth. Overall, differences in δJ between mortality classes (<1‰) and soil depths (<3‰) were smaller than variability within a class or depth over a season (up to 6‰).

59 BASIC BIOLOGICAL SCIENCES↗

Experimental warming across a tropical forest canopy height gradient reveals minimal photosynthetic and respiratory acclimation

Abstract Tropical forest canopies cycle vast amounts of carbon, yet we still have a limited understanding of how these critical ecosystems will respond to climate warming. We implemented in situ leaf‐level + 3°C experimental warming from the understory to the upper canopy of two Puerto Rican tropical tree species, Guarea guidonia and Ocotea sintenisii . After approximately 1 month of continuous warming, we assessed adjustments in photosynthesis, chlorophyll fluorescence, stomatal conductance, leaf traits and foliar respiration. Warming did not alter net photosynthetic temperature response for either species; however, the optimum temperature of Ocotea understory leaf photosynthetic electron transport shifted upward. There was no Ocotea respiratory treatment effect, while Guarea respiratory temperature sensitivity ( Q 10 ) was down‐regulated in heated leaves. The optimum temperatures for photosynthesis ( T opt ) decreased 3–5°C from understory to the highest canopy position, perhaps due to upper canopy stomatal conductance limitations. Guarea upper canopy T opt was similar to the mean daytime temperatures, while Ocotea canopy leaves often operated above T opt . With minimal acclimation to warmer temperatures in the upper canopy, further warming could put these forests at risk of reduced CO 2 uptake, which could weaken the overall carbon sink strength of this tropical forest.

Carter, Kelsey R.↗

A minimum spanning forest based classification method for dedicated breast CT images

Purpose: To develop and test an automated algorithm to classify different types of tissue in dedicated breast CT images. Methods: Images of a single breast of five different patients were acquired with a dedicated breast CT clinical prototype. The breast CT images were processed by a multiscale bilateral filter to reduce noise while keeping edge information and were corrected to overcome cupping artifacts. As skin and glandular tissue have similar CT values on breast CT images, morphologic processing is used to identify the skin based on its position information. A support vector machine (SVM) is trained and the resulting model used to create a pixelwise classification map of fat and glandular tissue. By combining the results of the skin mask with the SVM results, the breast tissue is classified as skin, fat, and glandular tissue. This map is then used to identify markers for a minimum spanning forest that is grown to segment the image using spatial and intensity information. To evaluate the authors’ classification method, they use DICE overlap ratios to compare the results of the automated classification to those obtained by manual segmentation on five patient images. Results: Comparison between the automatic and the manual segmentation shows that the minimum spanning forest based classification method was able to successfully classify dedicated breast CT image with average DICE ratios of 96.9%, 89.8%, and 89.5% for fat, glandular, and skin tissue, respectively. Conclusions: A 2D minimum spanning forest based classification method was proposed and evaluated for classifying the fat, skin, and glandular tissue in dedicated breast CT images. The classification method can be used for dense breast tissue quantification, radiation dose assessment, and other applications in breast imaging.

60 APPLIED LIFE SCIENCES↗

Automated segmentation of dental CBCT image with prior-guided sequential random forests

Purpose: Cone-beam computed tomography (CBCT) is an increasingly utilized imaging modality for the diagnosis and treatment planning of the patients with craniomaxillofacial (CMF) deformities. Accurate segmentation of CBCT image is an essential step to generate 3D models for the diagnosis and treatment planning of the patients with CMF deformities. However, due to the image artifacts caused by beam hardening, imaging noise, inhomogeneity, truncation, and maximal intercuspation, it is difficult to segment the CBCT. Methods: In this paper, the authors present a new automatic segmentation method to address these problems. Specifically, the authors first employ a majority voting method to estimate the initial segmentation probability maps of both mandible and maxilla based on multiple aligned expert-segmented CBCT images. These probability maps provide an important prior guidance for CBCT segmentation. The authors then extract both the appearance features from CBCTs and the context features from the initial probability maps to train the first-layer of random forest classifier that can select discriminative features for segmentation. Based on the first-layer of trained classifier, the probability maps are updated, which will be employed to further train the next layer of random forest classifier. By iteratively training the subsequent random forest classifier using both the original CBCT features and the updated segmentation probability maps, a sequence of classifiers can be derived for accurate segmentation of CBCT images. Results: Segmentation results on CBCTs of 30 subjects were both quantitatively and qualitatively validated based on manually labeled ground truth. The average Dice ratios of mandible and maxilla by the authors’ method were 0.94 and 0.91, respectively, which are significantly better than the state-of-the-art method based on sparse representation (p-value < 0.001). Conclusions: The authors have developed and validated a novel fully automated method for CBCT segmentation.

61 RADIATION PROTECTION AND DOSIMETRY↗

Multidecadal shifts in forest plant diversity and community composition across glacial landforms in northern lower Michigan, USA

Understanding how plant community assemblage is affected by spatial and temporal patterns is crucial to understanding forest ecosystem responses to disturbance, including future climate change. In this article, we tracked how diversity and composition are distributed through space and time in a midsuccessional mixed hardwood forest in northern lower Michigan, United States. This region’s geographically and abiotically distinct glacial landforms influence both the spatial and temporal dynamics of its forest communities. Vegetation sampling plots (n = 87) were established at the University of Michigan Biological Station in 1990 and resampled in 2015. Vegetation in the overstory, sapling, and groundcover layers was censused. Abiotic variables, including elevation, pH, and soil nutrients, were measured in a subset of plots (n = 40). There were strong differences in diversity and community composition among glacial landforms, with the moraine having a 31% greater species richness in the groundcover layer compared with those of the other glacial landforms. Surprisingly, plant communities across all three vegetation layers showed little change over the 25-year period, and we found no evidence of differences in successional rates among glacial landforms. Our findings indicate that glacial landforms have a large influence on the production and maintenance of local plant diversity and community composition in this area and suggest that successional dynamics may manifest themselves over much longer time periods in these northern biomes.

Forestry↗

Variation in forest root image annotation by experts, novices, and AI

Abstract Background The manual study of root dynamics using images requires huge investments of time and resources and is prone to previously poorly quantified annotator bias. Artificial intelligence (AI) image-processing tools have been successful in overcoming limitations of manual annotation in homogeneous soils, but their efficiency and accuracy is yet to be widely tested on less homogenous, non-agricultural soil profiles, e.g., that of forests, from which data on root dynamics are key to understanding the carbon cycle. Here, we quantify variance in root length measured by human annotators with varying experience levels. We evaluate the application of a convolutional neural network (CNN) model, trained on a software accessible to researchers without a machine learning background, on a heterogeneous minirhizotron image dataset taken in a multispecies, mature, deciduous temperate forest. Results Less experienced annotators consistently identified more root length than experienced annotators. Root length annotation also varied between experienced annotators. The CNN root length results were neither precise nor accurate, taking ~ 10% of the time but significantly overestimating root length compared to expert manual annotation ( p = 0.01). The CNN net root length change results were closer to manual ( p = 0.08) but there remained substantial variation. Conclusions Manual root length annotation is contingent on the individual annotator. The only accessible CNN model cannot yet produce root data of sufficient accuracy and precision for ecological applications when applied to a complex, heterogeneous forest image dataset. A continuing evaluation and development of accessible CNNs for natural ecosystems is required.

Handy, Grace↗

Moisture Content of Baled Forest and Urban Woody Biomass during Long-term Open Storage

Abstract. This article describes how the moisture content of baled woody biomass varied during long-term open-air storage under conditions in the Pacific Northwest region of the United States. Large rectangular bales of forest and urban biomass were produced beginning in August 2015 and periodically until June 2016. Weights were measured approximately monthly until the entire lot of bales was ground into fuel in December 2016. Because it was impractical to non-destructively obtain moisture content samples during the study, final moisture content was measured from the ground material. Estimated temporal moisture contents were back-calculated from the final dry weight and moisture content of bales. All bales dried considerably during the spring and summer months, achieving a minimum moisture content in the early fall of 15 to 29% (wb). Minimum early fall moisture content had no correlation with the initial moisture content at time of baling. The ending moisture content in December 2016 ranged from 44% to 57% (wb), with a mean moisture content of 53% (wb). Ending moisture content had no correlation with initial moisture content at the time of baling, but appeared to be related to the amount of fine versus coarse woody material in the bales. Bales of forest and urban woody biomass proved to be structurally stable during long-term storage to enable handling and final transport to a centralized grinding location. Keywords: Density, Logging, Baling, Bioenergy, Biofuel, Bundling, Forest operations, Forestry, MC, Seasonality, Transport, Woody biomass.

Agriculture↗

Strategies for Reducing Moisture Content in Forest Residues at the Harvest Site

Abstract. The moisture content (MC) of biomass derived from forest residues can pose a challenge to biomass utilization. It plays a significant role in determining the cost of transportation and subsequent market price. Additionally, emerging biomass conversion technologies, such as gasification, torrefaction, and briquetting, have very narrow specifications for the MC (e.g., <15%) in their feedstocks. The goal of this study was to develop strategies for reducing moisture content by evaluating different arrangement patterns of forest residues and its effect on MC reduction at the harvest site. The study compared four different arrangement patterns including criss-cross, teepees, traditional piling (processor piled), and scattered residues in three different timber harvest units in northern California. Two of the arrangement patterns (criss-cross and processor piled) were also covered with a plastic cover. Samples were collected from each treatment using a transect method and were recorded for 12 months. There was an overall drop of MC from 52% (freshly cut) to 12% between all arrangements over the study period. The cost of construction per pile, averaged $37, $41, and $48 for teepees, criss-cross, and processor piles, respectively. Even though, there was no significant difference in MC reduction between piles (except scattered), each pile arrangement of forest residues directly affected biomass feedstock operations, logistics, and costs. Keywords: Feedstock quality, Logging slash, Transect sampling method, Woody biomass energy.

Agriculture↗

Porewater data across a catena in the Luquillo Experimental Forest, Puerto Rico.

Landscape topography can influence biogeochemical processes in wet tropical forest soils. This dataset contains porewater concentrations of organic acid (acetate) from 2018 (February 22 to November 14) across a catena in the Luquillo Experimental Forest (LEF), Puerto Rico. The attached CSV file contains information on sampling date, location (El Verde field station) in LEF, topographic positions (ridge, slope, and valley, respectively), depth (unit: cm), and acetate concentration (unit: µM). Porewater concentrations of acetate were lower in the valley as compared to the ridge and slope topographic positions. This dataset can facilitate our understanding of the biogeochemical cycling of carbon and nutrient associated with complex topography in wet tropical forest soils.

54 ENVIRONMENTAL SCIENCES↗

Soil chemistry data across a catena in the Luquillo Experimental Forest, Puerto Rico

Landscape topography can influence biogeochemical processes across the wet tropical forest soils. This dataset contains soil chemistry data such as pH and dissolved organic carbon (DOC) from April 1, 2017 to May 1, 2018 across a catena in the Luquillo Experimental Forest, Puerto Rico. The attached CSV file contains information on sampling date, location (El Verde field station) in LEF, topographic positions (ridge, slope, and valley, respectively), field replicate number, laboratory replicate number, water extractable pH, CaCl2 extractable pH, and DOC (unit: mg/g). Overall, soil pH values were highest in the valley, followed by slope, and lowest in the ridge topographic positions. However, DOC values followed the opposite trend: ridge>slope>valley. This dataset can facilitate our understanding of the biogeochemical cycling of carbon and nutrient associated with complex topography in wet tropical forest soils.

54 ENVIRONMENTAL SCIENCES↗

Data from: "Warming and provenance limit tree recruitment across and beyond the elevation range of subalpine forest"

This data package contains data used to support conclusions drawn in “Warming and provenance limit tree recruitment across and beyond the elevation range of subalpine forest”, by Kueppers et al. 2017. Data were collected in field sites within the Alpine Treeline Warming Experiment (ATWE), located on Niwot Ridge, on the eastern slope of the Colorado Rocky Mountains, USA. Files containing geospatial data are also included, to provide additional locational context.There are four document formats associated with this archive: three comma-separated values (.csv) files, three Microsoft Excel (.xlsx) files, one .pdf data user’s guide, four keyhole markup language (.kml) files, and a compressed folder containing seven ESRI shapefiles (.shp). The .csv files can be opened using any simple text-editor software, R, or Microsoft Excel. The .xlsx files can only be opened using Microsoft Excel. The .kml file can be opened by Google Earth and Google Maps, and the shapefiles can be opened with any GIS application compatible with the file type, such as ESRI’s ArcGIS, and QGIS.We provide two versions of the seedling data file: “PIEN_PIFLseedlings20150522_20150525rev12222020.csv/.xlsx” (hereafter PIEN_PIFLseedlings2015) and “PIEN_PIFLseedlings20160408rev12222020.csv/.xlsx” (hereafter PIEN_PIFLseedlings2016). PIEN_PIFLseedlings2015 contains the data we used in the paper. PIEN_PIFLseedlings2016 contains an updated version of these data that includes sampling from later years. The main differences between the two files lie in the columns titled “k[YEAR],” which describe the number of seedlings that were killed in a particular year. In PIEN_PIFLseedlings2016, there also is an additional year of data for k2015, and k2014 also has additional data input for the 2014 cohort. Additionally, in years 2010-2014, there are minor differences in the number of seedlings killed -- in as few as 0 plots (in 2011) to as many as 5 plots (in 2014) -- due to errors in data input that were rectified in later years.------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------Upslope range shifts by subalpine tree species are a widely anticipated effect of climate change. Climate niche models predict subalpine forests to expand upslope, given more suitable growing conditions for adult trees. However, these models do not take into account climates required for successful seedling recruitment and establishment, an essential element for expansion. Further, localized upper treeline populations are hypothesized to contain favorable traits for colonizing the alpine. To test these expectations and to expand our knowledge of seedling recruitment under climate change, we designed a common garden, climate-warming experiment spread across an elevation gradient at Niwot Ridge in the Colorado Rocky Mountains. We focus on two widespread Western North American species, Engelmann spruce (Picea engelmannii Parry ex. Engelm) and limber pine (Pinus flexilis James), which occur at treeline. While the former is considered a late-seral species more tolerant of shade, limber pine is a shade-intolerant pioneer species able to establish on infertile sites.Every autumn, seeds of the two species were collected from high- (3370 m–3570 m) and low-provenance (2910–3240 m) sources close to the experimental sites and sown in our plots. A subset of plots were heated and another subset watered over the summer months to offset the effects of warming. Across five years, we found that seeds originating from low elevation recruited more strongly for both species, although this provenance difference diminished by the fourth year for Engelmann spruce, likely due to small sample sizes. Despite the recruitment of low-provenance seed, warming treatments decreased recruitment at all elevations. Combining this with the likeliness and availability of lower-quality, high provenance seed moving upslope at the treeline, tree migration into the alpine may be slowed. Overall, our findings suggest that the hardier limber pine is likely to become a more significant species in subalpine forest communities in the future, while the more sensitive Engelmann spruce may experience range contraction.

54 ENVIRONMENTAL SCIENCES↗

Model output from simulations of manganese-carbon interactions in temperate forest soil profiles

This archive contains model output, code, and scripts for simulations of coupled manganese-carbon cycling in temperate forest soil profiles. These model results were generated as part of a study investigating how manganese availability influences soil organic carbon stocks and demonstrating a new model framework for coupling carbon and manganese cycling. The simulations were in support of a manuscript: "Modeling interactive effects of manganese bioavailability, nitrogen deposition, and warming on soil carbon storage." The study addresses the research questions: How does Mn bioavailability, as driven by subsurface mineral properties, pH, and redox status, affect temperate forest soil organic carbon and litter carbon stocks?How is the relationship between Mn bioavailability and carbon cycling affected by changes in temperature and nitrogen deposition?"Model simulations were conducted in a reactive transport modeling framework using PFLOTRAN coupled to python. Multiple model simulations testing different Mn-bearing mineral solubilities, hydrological patterns, nitrogen deposition rates, and temperatures are included. Soil properties, including total and exchangeable Mn concentrations, are based on values reported for the Susquehanna Shale Hills Critical Zone Observatory (SSHCZO), a temperate forested watershed in central Pennsylvania, U.S.A where Mn cycling through vegetation has been documented.File formats include netCDF (.nc), python script (.py), shell script (.sh), plain text PFLOTRAN input file (.in), and plain text PFLOTRAN database file (.dat), and gzipped tar archive (tar.gz).

54 ENVIRONMENTAL SCIENCES↗

Radiocarbon of soil CO2 efflux and soils with experimental soil warming and drying in lowland tropical forests in Panama

In 2019, we measured the Δ14C and δ13C of soil respired carbon dioxide (CO2) in Panamanian forests that are subject to either in situ experimental soil warming (4C above ambient temperature to 1.2 m depth) or in situ experimental drying (50% throughfall exclusion). The warming site and one drying site are both within the Barro Colorado Nature Monument in nearby and similar forests on similar soils, enabling direct comparison of warming and drying effects on soil CO2 efflux. A second drying experiment is on the northern side of the Panama Isthmus on infertile soils where mean annual precipitation is greater, representative of a broad geographic area of the tropics. Given the seasonality of these forests, we performed measurements at stages of the seasonal cycle for which we expected the largest variation in CO2 efflux between control and experimental plots based on previous studies – the wet season (October-December) and dry season (March/April) or dry-to-wet season transition (May). This dataset includes Δ14C and δ13C of in situ soil surface CO2 flux as well as CO2 flux rates, volumetric soil moisture, soil temperature, and calculated partitioning of the fraction of total soil respiration from heterotrophs vs roots at the time of isotope sampling in AllSites_SoilResp_14C_data.xlsx. This dataset also includes Δ14C and δ13C of bulk soil, density fractions, and CO2 respired during laboratory incubations in AllSites_bulk_soil14C.xlsx. Datafiles are also available in csv format.

54 ENVIRONMENTAL SCIENCES↗

Data for Myers-Pigg et al. (2026), "Short-term coastal forest responses to a hurricane-scale freshwater and saltwater flooding experiment"

Coastal upland forests are exposed to intensifying precipitation regimes and sea level rise, increasing tree mortality and transforming these coastal forests into wetland ecosystems. Despite these well-known risks, the differing degrees to which hydrological, biogeochemical, and biological components of upland forests respond to novel salinity exposure is relatively unknown. The Terrestrial Ecosystem Manipulation to Probe the Effects of Storm Treatments (TEMPEST) experiment decouples two distinct disturbances associated with hydrological extremes: (1) flooding from heavy precipitation and (2) exposure to saline conditions from storm surge. This dataset includes data reported in Myers-Pigg et al. (2025), which analyzed data from the first TEMPEST flooding treatment in 2022. This includes: - Colored dissolved organic matter in porewaters - Soil temperature and oxygen - Groundwater temperature and chemistry - Dissolved organic carbon concentrations in porewaters - Soil-to-atmosphere CH4 and CO2 fluxes - Soil temperature, water content, and electrical conductivity - Root-influenced CH4 and CO2 flux - Tree sap flow velocity - The R analytical code and documentation about the computational environmental in which it was run (the "sessionInfo.txt" file) All data files are plain-text comma separated value (CSV) and no special software is required to read them.

54 ENVIRONMENTAL SCIENCES↗

Dataset for Cruz-O'Byrne et al (2026): "Divergent biogeochemical responses in upland coastal forest soils to repeated flooding and shifts in water chemistry"

Hydrologic disturbances from accelerated sea-level rise and the increasing frequency and intensity of storms and tidal flooding are altering biogeochemical processes in upland coastal forests, transforming these ecosystems into wetlands. However, the initial effects of flooding on belowground biogeochemistry and the mechanisms driving greenhouse gas dynamics and soil organic matter stability during the early stages of this transition remain poorly understood. This dataset presents the results of a mesocosm experiment conducted in a controlled, highly instrumented laboratory environment, in which freshwater and brackish water pulses were applied to intact soil monoliths from a temperate upland coastal forest to examine how floodwater chemistry influences soil biogeochemistry and organo-mineral interactions. All data files are plain-text CSV (comma-separated value), and no special software is required to read them. Details about the content of each file are available in the document “Dataset_readme”. The dataset consists of the following data: • rcruzobyrne_moisture: Soil volumetric water content (VWC) • rcruzobyrne_GHG: Headspace greenhouse gas (GHG) concentration and fluxes • rcruzobyrne_methane_isotopes: Headspace methane isotope signature • rcruzobyrne_porewater: Porewater chemistry • rcruzobyrne_CDOM: Porewater colored dissolved organic matter (CDOM) • rcruzobyrne_FTIR: Soil Fourier-transform infrared (FTIR) spectroscopy Details of the experimental setup, data collection, and data analysis are provided in the manuscript by Cruz-O’Byrne et al (2026) Divergent biogeochemical responses in upland coastal forest soils to repeated flooding and shifts in water chemistry. Biogeochemistry. https://doi.org/10.1007/s10533-026-01340-0

EARTH SCIENCE > ATMOSPHERE > GREENHOUSE GAS↗

Panama tropical forest digital camera imagery for vegetation phenology, Dec2016-May2019, PA-SLZ, PA-PNM, PA-BCI

Tropical forest phenology monitoring undertaken by use of Wingscapes timelapse cameras (phenocams) at three tropical evergreen forests in Panama: San Lorenzo, Parque Natural Metropolitano, and Barro Colorado Island. Following installation in December 2016, images were acquired every 10 minutes from 10 am to 2 pm daily, ending in May 2019. A total of 37 cameras were mounted on towers and tree branches, and view sunlit canopy or understory forest as follows: PA-SLZ, 11 canopy, 14 understory; PA-PNM, 6 canopy, 2 understory, PA-BCI, 4 canopy (trees also monitored for sap flow). This data package contains a full data description, metadata, species identification guides and summary files showing example fields of view from each camera location as csv and pdf files. The data description provides instructions for download of the full resolution image files, and other summary data products stored on external servers.

54 ENVIRONMENTAL SCIENCES↗

AmeriFlux US-GMF Great Mountain Forest

This is the AmeriFlux version of the carbon flux data for the site US-GMF Great Mountain Forest. Site Description - The experimental site is in the Great Mountain Forest on moderately hilly terrain in Norfolk, Connecticut. The site is a naturally regenerating forest impacted by fires, logging, hurricanes, and cultivation over the past century. The site switched from a continuous measurement mode to a campaign mode on DOY 125, 2004.

Lee, Xuhui↗