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A network of more than 130 permanent vegetation plots provides long-term information on patterns and rates of forest succession in most of the major forest zones of the Pacific Northwest. The plot network extends from the coast to the Cascades in western Oregon and Washington and east to ponderosa pine forests in the Oregon Cascades. Most of the permanent plots were established during two intervals: from 1910 to 1948, and from 1970 to 1989. The earlier plots were established by U.S. Forest Service researchers to quantify timber growth in young stands of important commercial species and to help answer other applied forestry questions. The more recent period of plot establishment began under the Coniferous Forest Biome program of the International Biological Program during the 1970s, and continued under the Long-term Ecological Research program. A broader set of objectives motivated plot establishment since 1970, especially quantification of composition, structure, and population and ecosystem dynamics of natural forests. Plots have one of three spatial arrangements: (1) contiguous rectangles subjectively placed within an area of homogeneous forest; (2) circular plots subjectively placed within an area of homogeneous forest; and (3) circular plots systematically located on long transects to sample an entire watershed, ridge, or reserve. Rectangular study areas are mostly 1.0 ha or 0.4 ha (1.0 ac) in size (slope-corrected). Circular plots are 0.1 ha (0.247 ac), not corrected for slope. The tree stratum is the focus of work in closed-forest study areas. All trees larger than a minimum diameter (5 cm for most areas) are permanently tagged. Plots are censused every 5 or 6 years. Attributes measured or assessed at each census include tree diameter, tree vigor, and the condition of the crown and stem. The same attributes are recorded for trees (ingrowth) that have exceeded the minimum diameter since the previous census. In many plots tree locations are surveyed to provide a plot-specific x-y location. A mortality assessment is done for trees that have died since the previous census. The assessment characterizes rooting, stem, and crown condition, obvious signs of distress or disturbance, and the apparent predisposing and proximate causes of tree death. 

A network of more than 130 permanent vegetation plots provides long-term information on patterns and rates of forest succession in most of the major forest zones of the Pacific Northwest. The plot network extends from the coast to the Cascades in western Oregon and Washington and east to ponderosa pine forests in the Oregon Cascades. Most of the permanent plots were established during two intervals: from 1910 to 1948, and from 1970 to 1989. The earlier plots were established by U.S. Forest Service researchers to quantify timber growth in young stands of important commercial species and to help answer other applied forestry questions. The more recent period of plot establishment began under the Coniferous Forest Biome program of the International Biological Program during the 1970s, and continued under the Long-term Ecological Research program. A broader set of objectives motivated plot establishment since 1970, especially quantification of composition, structure, and population and ecosystem dynamics of natural forests. Plots have one of three spatial arrangements: (1) contiguous rectangles subjectively placed within an area of homogeneous forest; (2) circular plots subjectively placed within an area of homogeneous forest; and (3) circular plots systematically located on long transects to sample an entire watershed, ridge, or reserve. Rectangular study areas are mostly 1.0 ha or 0.4 ha (1.0 ac) in size (slope-corrected). Circular plots are 0.1 ha (0.247 ac), not corrected for slope. The tree stratum is the focus of work in closed-forest study areas. All trees larger than a minimum diameter (5 cm for most areas) are permanently tagged. Plots are censused every 5 or 6 years. Attributes measured or assessed at each census include tree diameter, tree vigor, and the condition of the crown and stem. The same attributes are recorded for trees (ingrowth) that have exceeded the minimum diameter since the previous census. In many plots tree locations are surveyed to provide a plot-specific x-y location. A mortality assessment is done for trees that have died since the previous census. The assessment characterizes rooting, stem, and crown condition, obvious signs of distress or disturbance, and the apparent predisposing and proximate causes of tree death. 

Arthropods contribute importantly to ecosystem functioning but remain understudied. This undermines the validity of conservation decisions. Modern methods are now making arthropods easier to study, since arthropods can be mass-trapped, mass-identified, and semi-mass-quantified into ‘many-row (observation), many-column (species)‘ datasets, with homogeneous error, high resolution, and copious environmental-covariate information. These ‘novel community datasets’ let us efficiently generate information on arthropod species distributions, conservation values, uncertainty, and the magnitude and direction of human impacts. We use a DNA-based method (barcode mapping) to produce an arthropod-community dataset from 121 Malaise-trap samples, and combine it with 29 remote-imagery layers using a deep neural net in a joint species distribution model. With this approach, we generate distribution maps for 76 arthropod species across a 225 km²temperate-zone forested landscape. We combine the maps to visualize the fine-scale spatial distributions of species richness, community composition, and site irreplaceability. Old-growth forests show distinct community composition and higher species richness, and stream courses have the highest site-irreplaceability values. With this ‘sideways biodiversity modelling’ method, we demonstrate the feasibility of biodiversity mapping at sufficient spatial resolution to inform local management choices, while also being efficient enough to scale up to thousands of square kilometres. This article is part of the theme issue ‘Towards a toolkit for global insect biodiversity monitoring’. 

Abstract Plants display a range of temporal patterns of inter‐annual reproduction, from relatively constant seed production to “mast seeding,” the synchronized and highly variable interannual seed production of plants within a population. Previous efforts have compiled global records of seed production in long‐lived plants to gain insight into seed production, forest and animal population dynamics, and the effects of global change on masting. Existing datasets focus on seed production dynamics at the population scale but are limited in their ability to examine community‐level mast seeding dynamics across different plant species at the continental scale. We harmonized decades of plant reproduction data for 141 woody plant species across nine Long‐Term Ecological Research (LTER) or long‐term ecological monitoring sites from a wide range of habitats across the United States. Plant reproduction data are reported annually between 1957 and 2021 and based on either seed traps or seed and/or cone counts on individual trees. A wide range of woody plant species including trees, shrubs, and lianas are represented within sites allowing for direct community‐level comparisons among species. We share code for filtering of data that enables the comparison of plot and individual tree data across sites. For each species, we compiled relevant life history attributes (e.g., seed mass, dispersal syndrome, seed longevity, sexual system) that may serve as important predictors of mast seeding in future analyses. To aid in phylogenetically informed analyses, we also share a phylogeny and phylogenetic distance matrix for all species in the dataset. These data can be used to investigate continent‐scale ecological properties of seed production, including individual and population variability, synchrony within and across species, and how these properties of seed production vary in relation to plant species traits and environmental conditions. In addition, these data can be used to assess how annual variability in seed production is associated with climate conditions and how that varies across populations, species, and regions. The dataset is released under a CC0 1.0 Universal public domain license. 

Iodine oxoacids are recognised for their significant contribution to the formation of new particles in marine and polar atmospheres. Nevertheless, to incorporate the iodine oxoacid nucleation mechanism into global simulations, it is essential to comprehend how this mechanism varies under various atmospheric conditions. In this study, we combined measurements from the CLOUD (Cosmic Leaving OUtdoor Droplets) chamber at CERN and simulations with a kinetic model to investigate the impact of temperature, ionisation, and humidity on iodine oxoacid nucleation. Our findings reveal that ion-induced particle formation rates remain largely unaffected by changes in temperature. However, neutral particle formation rates experience a significant increase when the temperature drops from +10 ^oC to −10 ^oC. Running the kinetic model with varying ionisation rates demonstrates that the particle formation rate only increases with a higher ionisation rate when the iodic acid concentration exceeds 1.5 × 10⁷ cm^sup>−3, a concentration rarely reached in pristine marine atmospheres. Consequently, our simulations suggest that, despite higher ionisation rates, the charged cluster nucleation pathway of iodic acid is unlikely to be enhanced in the upper troposphere by higher ionisation rates. Instead, the neutral nucleation channel is likely to be the dominant channel in that region. Notably, the iodine oxoacid nucleation mechanism remains unaffected by changes in relative humidity from 2% to 80%. However, under unrealistically dry conditions (below 0.008% RH at +10 ^oC), iodine oxides (I₂O₄ and I₂O₅) significantly enhance formation rates. Therefore, we conclude that iodine oxoacid nucleation is the dominant nucleation mechanism for iodine nucleation in the marine and polar boundary layer atmosphere. 

Inhomogeneities in temperature and ammonia concentrations can cause rapid growth of nanoparticles in polluted environments.