In late June 2021, multiple days of record-breaking heat caused an unprecedented amount of foliage death in the forests of the Pacific Northwest, USA. Portions of tree canopies with healthy green foliage prior to the heat changed to red or orange shortly after the event. The change in foliage color could be readily seen in satellite imagery and was corroborated as foliar death (heat scorch) by aerial surveys and extensive observations on the ground. To better understand the patterns and processes driving foliar death, we used satellite imagery to identify 293,546 ha of forest, or ~4.7% of forest area, that were damaged in western Oregon and Washington by this extreme heat event. Analysis of underlying drivers of the observed heat damage indicated greater sensitivity was related to abiotic factors such as sun exposure, aspect, and microclimate, as well as biotic factors like tree species and stand age, budburst phenology, and foliar pathogens impacting tree health. Iconic, culturally and economically significant species like western redcedar, western hemlock, and Sitka spruce were disproportionately sensitive to heat damage, including in old-growth stands where they are canopy dominants. These findings highlight the multifaceted challenges posed to forests by extreme heat waves, and the need to better understand their impact on forest ecosystems in a rapidly warming climate.

An issue of global concern is how climate change forcing is transmitted to ecosystems. Forest ecosystems in mountain landscapes may demonstrate buffering and perhaps decoupling of long‐term rates of temperature change, because vegetation, topography, and local winds (e.g., cold air pooling) influence temperature and potentially create microclimate refugia (areas which are relatively protected from climate change). We tested these ideas by comparing 45‐year regional rates of air temperature change to unique temporal and spatial air temperature records in the understory of regionally representative stable old forest at the H.J. Andrews Experimental Forest, Oregon, USA. The 45‐year seasonal patterns and rates of warming were similar throughout the forested landscape and matched regional rates observed at 88 standard meteorological stations in Oregon and Washington, indicating buffering, but not decoupling of long‐term climate change rates. Consideration of the energy balance explains these results: while shading and airflows produce spatial patterns of temperature, these processes do not counteract global increases in air temperature driven by increased downward, longwave radiation forced by increased anthropogenic greenhouse gases in the atmosphere. In some months, the 45‐year warming in the forest understory equaled or exceeded spatial differences of air temperature between the understory and the canopy or canopy openings and was comparable to temperature change over 1,000 m elevation, while in other months there has been little change. These findings have global implications because they indicate that microclimate refugia are transient, even in this forested mountain landscape.

Journal Article Causes of widespread foliar damage from the June 2021 Pacific Northwest Heat Dome: more heat than drought Get access C J Still, C J Still Department of Forest Ecosystems and Society, Oregon State University, Corvallis, OR 97331, USA Corresponding author (chris.still@oregonstate.edu) https://orcid.org/0000-0002-8295-4494 Search for other works by this author on: Oxford Academic PubMed Google Scholar A Sibley, A Sibley Department of Forest Ecosystems and Society, Oregon State University, Corvallis, OR 97331, USA Search for other works by this author on: Oxford Academic PubMed Google Scholar D DePinte, D DePinte US Department of Agriculture, Forest Service, Pacific Northwest Region, State & Private Forestry, Forest Health Protection, Redmond, OR 97756, USA Search for other works by this author on: Oxford Academic PubMed Google Scholar P E Busby, P E Busby Department of Botany and Plant Pathology, Oregon State University, Corvallis, OR 97331, USA Search for other works by this author on: Oxford Academic PubMed Google Scholar C A Harrington, C A Harrington US Department of Agriculture, Forest Service, Pacific Northwest Research Station, Olympia, WA 98512, USA Search for other works by this author on: Oxford Academic PubMed Google Scholar M Schulze, M Schulze Department of Forest Ecosystems and Society, Oregon State University, Corvallis, OR 97331, USA Search for other works by this author on: Oxford Academic PubMed Google Scholar D R Shaw, D R Shaw Department of Forest Engineering, Resources, and Management, Oregon State University, Corvallis, OR 97331, USA Search for other works by this author on: Oxford Academic PubMed Google Scholar D Woodruff, D Woodruff US Department of Agriculture, Forest Service, Pacific Northwest Research Station, Corvallis, OR 97331, USA Search for other works by this author on: Oxford Academic PubMed Google Scholar D E Rupp, D E Rupp Oregon Climate Change Research Institute, College of Earth, Ocean, and Atmospheric Sciences, Oregon State University, Corvallis, OR 97331, USA Search for other works by this author on: Oxford Academic PubMed Google Scholar C Daly, C Daly PRISM Climate Group, Northwest Alliance for Computational Science and Engineering, Oregon State University, Corvallis, OR 97331, USA Search for other works by this author on: Oxford Academic PubMed Google Scholar ... Show more W M Hammond, W M Hammond Agronomy Department, University of Florida, Institute of Food and Agricultural Sciences, Gainesville, FL 32611, USA https://orcid.org/0000-0002-2904-810X Search for other works by this author on: Oxford Academic PubMed Google Scholar G F M Page G F M Page Biodiversity and Conservation Science, Department of Biodiversity, Conservation and Attractions, Locked Bag 104, Bentley Delivery Centre, Bentley, Western Australia 6983, AustraliaCSIRO Land and Water, Private Bag 5, Wembley, Western Australia 6913, Australia Search for other works by this author on: Oxford Academic PubMed Google Scholar Tree Physiology, Volume 43, Issue 2, February 2023, Pages 203–209, https://doi.org/10.1093/treephys/tpac143 Published: 05 January 2023 Article history Received: 08 June 2022 Accepted: 11 December 2022 Published: 05 January 2023 Corrected and typeset: 17 January 2023

The strategic importance of biodiversity conservation is increasing all over the world to face the threats that the global change bring to forest ecosystems. To accomplish that, Species Distribution Models (SDMs) stand as the most employed statistic models in ecological conservation. Nevertheless, explanatory predictors in these correlative models usually consist in free-air climate variables with coarse spatial (>1 km) and temporal (average of several years) resolution. This approach neglects the real habitat conditions experienced by most of the organisms on their life span. Hence, improving the reliability of these ecological models is crucial for biologists, land managers, and policymakers.Our aim was to compare microclimate temperatures derived from 13 years (2010-2022) of below-canopy hourly data loggers to free-air macroclimate derived from a mechanistic downscaling of global reanalysis data at 30 arcsec (CHELSA). We also tested the role of LiDAR-derived vegetation metrics to improve fine-scale SDMs. We developed three sets of predictors based on their temporal resolution: 1) an average across the years of observation based on the general presence or absence of the species, 2) an ensemble of year models (i.e., the average of the probability for each year weighted on its accuracy), and 3) a random year of observation.Using Bayesian Additive Regression Tree (BART) algorithms, we built SDMs for different species of birds, plants, insects, and mammals in a temperate rainforest landscape of the Pacific Northwest (HJ Andrew Experimental Forest, Oregon, United States). We built 12 different modeling frameworks based on the combination between climate input data (microclimate vs macroclimate), vegetation (with vs without), and temporal resolution (average vs ensemble vs random).We measured the distance between the probability distribution obtained from the different combinations using the Kolmogorov-Smirnov distance. We evaluated and compared three accuracy metrics of the models (AUC, TSS, MCS) through a 5-fold spatial block cross-validation. We tested for differences in distance and accuracy both at the taxa level and on ecological traits of the different species (mobility, prevalence, specialization).Preliminary results for bird species showed that temporal resolution was more important than climate datasets when including vegetation variables in the models. Some insect species showed a greater improvement in accuracy for models trained with microclimate compared to models trained with CHELSA.

The exponential growth in solar radiation measuring stations across the conterminous United States permits the generation of gridded solar irradiance data that capture the spatio-temporal variability of solar irradiance far more accurately than previously possible from ground-based observations. Taking advantage of these observations, we generated a 30-year climatology (1991-2020) of mean monthly global irradiance at a resolution of 30 arcsec (∼800 m) on both a horizontal and sloped ground surface. This paper describes the methods used to generate the gridded data, which include extensive quality control of station data, spatial interpolation of effective cloud transmittance using the “PRISM” method, and simulation of the effects of elevation, shading, and reflection from nearby terrain on solar irradiance. A comparison of the new dataset to several other solar radiation products reveals some spatial features in solar radiation that are either lacking or under-resolved in some or all of the other datasets. Examples of these features include strong gradients near foggy coastlines and along mountain ranges where there is persistent orographically driven cloud formation. The workflow developed to create the long-term means will be used as a template for generating time series of monthly and daily solar radiation grids up to the present.

Cold-air drainage and pooling can have wide-ranging impacts, including affecting ecosystem processes and agricultural crops, and contributing to decreased air quality associated with temperature inversions. Future climate changes may alter both the frequency and intensity of cold-air drainage. This study estimates the response of nocturnal cold-air drainage to warming resulting from anthropogenic greenhouse gases, specifically CO 2 , considering radiative and thermodynamic effects but not changes in background air flow (dynamic effects). A simple index is proposed to represent the propensity for clear-sky nocturnal cold-air drainage as a function of air temperature and humidity near dusk. Decreases in this index with increasing atmospheric emissivity due to increasing anthropogenic greenhouse gase concentrations imply a weakening of cold-air drainage. The magnitude of the decrease in the index is positively related to the initial background temperature and humidity: Warm regions are more sensitive than cold regions, and humid regions are more sensitive than dry regions, implying that warm and/or humid regions are more at risk of decreases in cold-air drainage. Under atmospheric CO 2 concentrations consistent with Representative Concentration Pathway (RCP) 8.5, the magnitude of decrease in the index indicates that nocturnal cold-air drainage intensity may decline by at least 10% by 2100 CE (compared to 1979–1990) with larger decreases in warm and humid regimes. The index should be tested with intentionally designed field or lab experiments, and the relative effects on cold-air drainage of changes in radiative, sensible, and latent heat fluxes, and atmospheric circulation, should be compared.

There is a great need for gridded daily precipitation datasets to support a wide variety of disciplines in science and industry. Production of such datasets faces many challenges, from station data ingest to gridded dataset distribution. The quality of the dataset is directly related to its information content, and each step in the production process provides an opportunity to maximize that content. The first opportunity is maximizing station density from a variety of sources and assuring high quality through intensive screening, including manual review. To accommodate varying data latency times, the Parameter-Elevation Regressions on Independent Slopes Model (PRISM) Climate Group releases eight versions of a day’s precipitation grid, from 24 h after day’s end to 6 months of elapsed time. The second opportunity is to distribute the station data to a grid using methods that add information and minimize the smoothing effect of interpolation. We use two competing methods, one that utilizes the information in long-term precipitation climatologies, and the other using weather radar return patterns. Last, maintaining consistency among different time scales (monthly vs daily) affords the opportunity to exploit information available at each scale. Maintaining temporal consistency over longer time scales is at cross purposes with maximizing information content. We therefore produce two datasets, one that maximizes data sources and a second that includes only networks with long-term stations and no radar (a short-term data source). Further work is under way to improve station metadata, refine interpolation methods by producing climatologies targeted to specific storm conditions, and employ higher-resolution radar products.

Cold‐air pooling and associated air temperature inversions are important features of mountain landscapes, but incomplete understanding of their controlling factors hinders prediction of how they may mediate potential future climate changes at local scales. We evaluated how topographic and forest canopy effects on insolation and local winds altered the expression of synoptic‐scale meteorological forcing on near‐surface air temperature inversions and how these effects varied by time of day, season, and spatial scale. Using ~13 years of hourly temperature measurements in forest canopy openings and under the forest canopy at the H.J. Andrews Experimental Forest in the western Cascade Range of Oregon (USA), we calculated air temperature gradients at the basin scale (high vs. low elevation) and at the cross‐valley scale for two transects that differed in topography and forest canopy cover. ERA5 and NCEP NCAR R1 reanalysis data were used to evaluate regional‐scale conditions. Basin and cross‐valley temperature inversions were frequent, particularly in winter and often persisted for several days. Nighttime inversions were more frequent at the cross‐valley scale but displayed the same intra‐annual pattern at the basin and regional scales, becoming most frequent in summer. Nighttime temperature gradients at basin and cross‐valley scales responded similarly to regional‐scale controls, particularly free‐air temperature gradients, despite differences in topography and forest cover. In contrast, the intra‐annual pattern of daytime inversions differed between the basin and cross‐valley scales and between the two cross‐valley transects, implying that topographic and canopy effects on insolation and local winds were key controls at these scales.

Accounting for within-species variability in the relationship between occurrence and climate is essential to forecasting species’ responses to climate change. Few climate-vulnerability assessments explicitly consider intraspecific variation, and those that do typically assume that variability is best explained by genetic affinity. Here, we evaluate how well heterogeneity in responses to climate by a cold-adapted mammal, the American pika ( Ochotona princeps ), aligns with subdivisions of the geographic range by phylogenetic lineage, physiography, elevation or ecoregion. We find that variability in climate responses is most consistently explained by an ecoregional subdivision paired with background sites selected from a broad spatial extent indicative of long-term (millennial-scale) responses to climate. Our work challenges the common assumption that intraspecific variation in climate responses aligns with genetic affinity. Accounting for the appropriate context and scale of heterogeneity in species’ responses to climate will be critical for informing climate-adaptation management strategies at the local (spatial) extents at which such actions are typically implemented.

Selecting forage crops adapted to the climatic and edaphic conditions of specific locations is essential for economic sustainability and environmental protection. This is particularly true for large countries and regions with diverse climates and soils and intended uses. It is also important for deciding what could be grown instead of what has been grown in areas undergoing substantial changes. Better matching of plants to locations would increase economic returns and reduce environmental hazards associated with suboptimal performance. Historically, deciding what plant to grow in an area was based on tradition or adaptation zones created from qualitative measurements and generalizations. They were not site specific and did not consider more than a few factors, usually annual temperature and precipitation. Currently, species selection could be more precise and accurate because the technology is available but remains difficult to apply due to the absence of user-friendly computer-based selection tools. Climate and soil geographical information system (GIS) layers, matched with a matrix of forage characteristics wrapped in an easy-to-use tool would greatly improve the selection process. GIS-based climate and soils maps are being developed and reviewed. A matrix of species characteristics is being developed for the major forage crops in Australia, People's Republic of China and United States of America. Base layer climate and soils maps and species adaptation maps could be combined on a CD-ROM to help decision-makers match their conditions to suitable forage crop species. World Wide Web segments could provide a source of current information and links to original data sources and supplementary materials. The technology is ripe, but integration of various components is now needed. The future holds the promise of many more improvements for putting each plant in the best location.

To increase the understanding of poplar and willow perennial woody crops and facilitate their deployment for the production of biofuels, bioproducts, and bioenergy, there is a need for broadscale yield maps. For national analysis of woody and herbaceous crops production potential, biomass feedstock yield maps should be developed using a common framework. This study developed willow and poplar potential yield maps by combining data from a network of willow and poplar field trials and the modeling power of PRISM-ELM. Yields of the top three willow cultivars across 17 sites ranged from 3.60 to 14.6Mgha(-1)yr(-1) dry weight, while the yields from 17 poplar trials ranged from 7.5 to 15.2Mgha(-1)yr(-1). Relationships between the environmental suitability estimates from the PRISM-ELM model and results from field trials had an R-2 of 0.60 for poplar and 0.81 for willow. The resulting potential yield maps reflected the range of poplar and willow yields that have been reported in the literature. Poplar covered a larger geographic range than willow, which likely reflects the poplar breeding efforts that have occurred for many more decades using genotypes from a broader range of environments than willow. While the field trial data sets used to develop these models represent the most complete information at the time, there is a need to expand and improve the model by monitoring trials over multiple cutting cycles and across a broader range of environmental gradients. Despite some limitations, the results of these models represent a dramatic improvement in projections of potential yield of poplar and willow crops across the United States.

Current knowledge of yield potential and best agronomic management practices for perennial bioenergy grasses is primarily derived from small‐scale and short‐term studies, yet these studies inform policy at the national scale. In an effort to learn more about how bioenergy grasses perform across multiple locations and years, the U.S. Department of Energy ( US DOE )/Sun Grant Initiative Regional Feedstock Partnership was initiated in 2008. The objectives of the Feedstock Partnership were to (1) provide a wide range of information for feedstock selection (species choice) and management practice options for a variety of regions and (2) develop national maps of potential feedstock yield for each of the herbaceous species evaluated. The Feedstock Partnership expands our previous understanding of the bioenergy potential of switchgrass, Miscanthus, sorghum, energycane, and prairie mixtures on Conservation Reserve Program land by conducting long‐term, replicated trials of each species at diverse environments in the U.S. Trials were initiated between 2008 and 2010 and completed between 2012 and 2015 depending on species. Field‐scale plots were utilized for switchgrass and Conservation Reserve Program trials to use traditional agricultural machinery. This is important as we know that the smaller scale studies often overestimated yield potential of some of these species. Insufficient vegetative propagules of energycane and Miscanthus prohibited farm‐scale trials of these species. The Feedstock Partnership studies also confirmed that environmental differences across years and across sites had a large impact on biomass production. Nitrogen application had variable effects across feedstocks, but some nitrogen fertilizer generally had a positive effect. National yield potential maps were developed using PRISM ‐ ELM for each species in the Feedstock Partnership. This manuscript, with the accompanying supplemental data, will be useful in making decisions about feedstock selection as well as agronomic practices across a wide region of the country.

Several crops have recently been identified as potential dedicated bioenergy feedstocks for the production of power, fuels, and bioproducts. Despite being identified as early as the 1980s, no systematic work has been undertaken to characterize the spatial distribution of their long-term production potentials in the United states. Such information is a starting point for planners and economic modelers, and there is a need for this spatial information to be developed in a consistent manner for a variety of crops, so that their production potentials can be intercompared to support crop selection decisions. As part of the Sun Grant Regional Feedstock Partnership (RFP), an approach to mapping these potential biomass resources was developed to take advantage of the informational synergy realized when bringing together coordinated field trials, close interaction with expert agronomists, and spatial modeling into a single, collaborative effort. A modeling and mapping system called PRISM-ELM was designed to answer a basic question: How do climate and soil characteristics affect the spatial distribution and long-term production patterns of a given crop? This empirical/mechanistic/biogeographical hybrid model employs a limiting factor approach, where productivity is determined by the most limiting of the factors addressed in submodels that simulate water balance, winter low-temperature response, summer high-temperature response, and soil pH, salinity, and drainage. Yield maps are developed through linear regressions relating soil and climate attributes to reported yield data. The model was parameterized and validated using grain yield data for winter wheat and maize, which served as benchmarks for parameterizing the model for upland and lowland switchgrass, CRP grasses, Miscanthus, biomass sorghum, energycane, willow, and poplar. The resulting maps served as potential production inputs to analyses comparing the viability of biomass crops under various economic scenarios. The modeling and parameterization framework can be expanded to include other biomass crops.

The pharmaceutical agent pentosan polysulfate (PPS) is known to induce proliferation and chondrogenesis of mesenchymal progenitor cells (MPCs) in vitro and in vivo. However, the mechanism(s) of action of PPS in mediating these effects remains unresolved.

Daly, Chris D MBBS, M. Phil, BSc; Ghosh, Peter DSc, PhD, FRACI, FRSC; Badal, Tanya BSc; Shimmon, Ronald PhD; Ghosh, Ian; Jenkin, Graham; Oehme, David A MBBS, (hons); Sher, Idrees MBBS, BSc; Chandra, Ronil V MBBS, M. Med Franzck; Vais, Angela; Cohen, Camilla; Goldschlager, Tony