US Forest Service

High-resolution temperature models are needed to describe and predict the thermal regime of streams/rivers under current and future management. Statistical models (e.g., spatial stream network models – SSN) can cover large extents at fine resolutions. Mechanistic models (e.g., Soil and Water Assessment Tool – SWAT) offer refined temporal resolution and process-based drivers in predictions, but are time consuming to parameterize. Hybrid modeling (e.g., hybrid SSN-SWAT) approaches can leverage benefits of both types to improve temporal robustness of thermal regime model predictions across entire networks. In the Upper Rogue River Basin, OR, we compared performance of a NorWeST August mean temperature (AMT) SSN model with a hybrid SSN-SWAT AMT (Hybrid AMT) model. We extended the hybrid SSN-SWAT approach to the 7-day average daily maximum temperature metric (Hybrid 7DADM). The Hybrid AMT and Hybrid 7DADM models performed well, with similar model diagnostics between the Hybrid AMT and NorWeST AMT models, and with other SSN and mechanistic temperature models (used for temperature total maximum daily loads – TMDLs). The hybrid SSN-SWAT approach was able to incorporate the effect of dams on downstream hydrology and temperature regimes. The best-fitting hybrid SSN models incorporated upstream shade effects spanning distances of 1-5 kilometers or 1-3 hours travel time, highlighting the need to maintain upstream riparian zones to protect downstream thermal regimes.

Tropical peatland forests are significant sources and sinks of greenhouse gases (GHG), yet the relative contributions of soil and tree stem fluxes have remained poorly quantified, particularly CH4 and N2O fluxes across gradients of nutrient availability. We conducted simultaneous measurements of CO2, CH4 and N2O fluxes from both soil and tree stems using soil and stem chamber in two contrasting tropical peat swamp forests: a nutrient-rich in Quistococha, Peru and a nutrient-poor in Maludam, Sarawak, Malaysia. Our results showed higher soil CO2, CH4 and N2O fluxes from Quistococha nutrient-rich forest. Tree stem respiration was consistently higher in the nutrient-poor forest across all dominant species in both forests. Tree stem CH4 fluxes exhibited distinct patterns, with significantly higher emissions from the nutrient-rich forest, while displaying species-specific behaviour among dominant tree species. Mauritia flexuosa palm stems in Quistococha showed high emission of CH4 from stems with potential CH4 sinks from specific species from both forests. N2O emissions were also species-specific and higher from the nutrient-rich forest, with negligible fluxes observed from the species in the nutrient-poor forest. From stem fluxes to tree fluxes upscaling, we found that the majority of total ecosystem GHG flux originated from soil with minimal contribution from the dominant tree species. In conclusion, these findings highlighted tree stems from tropical peatland can act as sources and sinks and that nutrient availability influence on the magnitude of greenhouse gas emissions.

Abstract Over 90% of U.S. homes are wood-based, making the residential construction sector both a major consumer of wood products and an important carbon sink. Understanding its long-term dynamics is critical for economic planning and carbon mitigation. Current U.S. models typically apply an exponential decay function to estimate carbon stored in wood products. However, recent research suggests this may not accurately reflect the time dynamics of wood products in housing, which remain in use for extended periods before disposal. This study compares the projections of U.S. single-family, multifamily, and manufactured housing inventories and associated carbon stocks from 2022 to 2070 using the conventional exponential decay model and an alternative chi- squared decay model, combined with three half-live assumptions (short, base, and long). Results reveal substantial differences in projected outcomes: under exponential decay, U.S. housing inventory declines, depending on half-life assumption, by 3 to 19% relative to 2022 levels, while chi-squared decay shows reductions of 3 to 52%. In contrast, total carbon stocks in housing inventory increase in the exponential model with all three half-life assumptions (14% to 16% relative to 2022 levels) and the chi-squared decay model with base and long half-life assumptions (10 to 18%). However, they decrease slightly (1%) for the chi-squared decay model with the short half-life assumption. These findings highlight the housing sector’s role in carbon storage and calls for a need to empirically validate decay functions and half-life parameters using updated time series data to improve long-term projections of housing inventories and associated carbon stocks.

Voluntary carbon markets (VCMs) are crucial yet complex mechanisms for forest conservation, particularly in highly biodiverse regions. This study investigates the rapid expansion of carbon forestry projects (CFPs) across 26 million hectares in Colombia, with 92% overlapping indigenous peoples, Afro-descendant, and local communities (IPALC) territories. Using spatial and qualitative analyses, a novel IPALC participation ladder framework and Colombia's first publicly available CFP geodatabase, we assess IPALC engagement dynamics, including market share, distribution, conflicts, and participation barriers. Findings show VCMs, despite significant conservation finance, often yield moderate IPALC participation, exacerbate governance deficits, and inequitable benefit sharing, compromising integrity, social legitimacy, and the potential for durable, community-driven conservation outcomes. Effective VCM climate action demands robust, community-driven governance, and inclusive policy reform. Lessons from Colombia offer critical insights for global VCM evolution toward more just, sustainable outcomes.

Abstract Observations of atmospheric carbon dioxide (CO 2 ) are expected to play a critical role in monitoring, reporting, and verification designed to track progress toward the reduction goals of greenhouse gas emissions. In this study, we construct a comprehensive regional carbon budget for seven National Climate Assessment regions of the contiguous United States (CONUS) over 2015–2020. We demonstrate that lateral carbon movement across regions, along with their resulting endpoint CO 2 emissions, represent a major contributor to the interpretation of regional net surface‐atmosphere fluxes of CO 2 . When accounting for lateral carbon fluxes, “top‐down” flux estimates from v10 Orbiting Carbon Observatory 2 (OCO‐2) Modeling Intercomparison Project (MIP) agree, within uncertainty, with inventory‐based carbon stock change estimates in six out of seven National Climate Assessment regions ‐ except for the Southwest. The total net carbon exchange from the top down is 925 ± 339 Tg carbon per year (Tg C/year), consistent with the 974 Tg C/year estimate from the inventory. Notably, lateral carbon flows in the form of harvested wood products and riverine carbon burial are responsible for an estimated 16% of the total carbon stock changes occurring across CONUS. Averaged over the seven regions, accounting for lateral transport and their endpoint carbon emissions improves the consistency between inventory and top‐down estimates by 31%. Our study presents a roadmap for reconciling the inventories and top‐down atmospheric inversions at sub‐national scale and highlights the importance of accurate representation of lateral carbon flows for using top‐down estimates with national inventories.

The California Prescribed Fire Monitoring Program dataset (2019–2024) provides comprehensive ecological monitoring data from prescribed fire treatments across California’s diverse forest ecosystems. This dataset encompasses forest structure and cover, fuel loads, and post-fire recovery metrics, collected using a standardized protocol, from over 36 disparate sites (114 burn units, 972 plots, and 1,838 total surveys). Data collected during pre-fire, immediate, and multi-year post-fire sampling episodes allow for robust analysis of prescribed fire effects across variable environmental conditions. The monitoring framework captures key ecological indicators, including tree mortality, fuel consumption, understory vegetation response, species composition, and regeneration. This dataset can address critical knowledge gaps regarding prescribed fire effectiveness for ecological restoration, hazardous fuel reduction, and ecosystem resilience objectives. These data can support evidence-based fire management decisions, validate fire effects models, and establish baseline reference conditions for future prescribed fire implementation throughout California’s fire-prone landscapes.

Abstract Introduction The augmentation of small populations with individuals from other local sites is often proposed as a management tool to overcome the negative impacts of fragmentation but is rarely employed due to concerns of outbreeding depression. This hesitancy is compounded by the lack of examples with genetic monitoring over multiple generations needed to measure the impacts of genetic augmentation. Objectives This study assesses how seeding populations of Platanthera leucophaea (eastern prairie fringed orchid) have altered population genetic structure over multiple generations. Methods We compared DNA samples collected prior to 1998 and 17 years (2015) post seeding. These genetic data were paired with measurements of fruit set and seed viability to test for evidence of inbreeding depression. Results We found genetic management (the combined treatment of hand pollination and seed addition) leading to an increase in all measures of genetic variation. Populations with no genetic management or only population reinforcement via hand pollination had little to no change in genetic variation. Seed viability differed significantly among these populations, and results suggest hand pollination in combination with seed addition is likely to increase seed viability over time. We observed no difference between treatment types solely considering genetic status in 2015. Conclusions This work highlights the importance of genetic monitoring over time to accurately measure the impact of restoration work and offers the rare opportunity to assess a history of well‐documented restoration and management widely applicable to species facing reduced reproductive success in isolated habitats.

This archive contains research data collected and/or funded by Forest Service Research and Development (FS R&D), U.S. Department of Agriculture. It is a resource for accessing both short and long-term FS R&D research data, which includes Experimental Forest and Range data. It is a way to both preserve and share the quality science of our researchers.

This archive contains research data collected and/or funded by Forest Service Research and Development (FS R&D), U.S. Department of Agriculture. It is a resource for accessing both short and long-term FS R&D research data, which includes Experimental Forest and Range data. It is a way to both preserve and share the quality science of our researchers.