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Studies of community assembly often explore the role of niche selection in limiting the diversity of functional traits (underdispersion) or increasing the diversity of functional traits (overdispersion) within local communities. While these patterns have primarily been explored with morphological functional traits related to environmental tolerances and resource acquisition, plant metabolomics may provide an additional functional dimension of community assembly to expand our understanding of how niche selection changes along environmental gradients. Here, we examine how the functional diversity of leaf secondary metabolites and traditional morphological plant traits changes along local environmental gradients in three temperate forest ecosystems across North America. Specifically, we asked whether co‐occurring tree species exhibit local‐scale over‐ or underdispersion of metabolomic and morphological traits, and whether differences in trait dispersion among local communities are associated with environmental gradients of soil resources and topography. Across tree species, we find that most metabolomic traits are not correlated with morphological traits, adding a unique dimension to functional trait space. Within forest plots, metabolomic traits tended to be overdispersed while morphological traits tended to be underdispersed. Additionally, local environmental gradients had site‐specific effects on metabolomic and morphological trait dispersion patterns. Taken together, these results show that different suites of traits can result in contrasting patterns of functional diversity along environmental gradients and suggest that multiple community assembly mechanisms operate simultaneously to structure functional diversity in temperate forest ecosystems. [ABSTRACT FROM AUTHOR]

Warming and more variable climates threaten to upend historical tree ranges, climatic sensitivity, and vigor. In western North America, the species Picea engelmannii var. engelmannii Parry ex Engelmann (Engelmann spruce) and Picea pungens Engelmann (Colorado blue spruce) are widespread spruce that act as foundational species in their montane to subalpine habitats. However, there is currently a lack of knowledge on P. pungens climatic responses, and how it differs from P. engelmannii. To address this gap, we assessed the climatic sensitivity and correlates of tree growth in a co‐occurring old‐growth stand of P. engelmannii and P. pungens, at high elevation in southern Utah, USA. We report the putative oldest cross‐dated P. pungens, with 457 rings, and sampled multiple P. pungens >400 years old. Both Picea populations had strongly positive growth responses to May–July precipitation and negative responses to maximum May–July temperature. Notably, October in the previous year had the strongest correlation with growth for both Picea species. Neither population exhibited signs of directional changes in climate–growth responses. Spectral analysis identified peaks associated with El Niño–Southern Oscillation at 3–4 years and quasi‐decadal oscillations (18–20 years) in both species. Cumulatively, our results highlight the growth–climate relationships of two frequently understudied subalpine tree species. In particular, P. pungens may warrant further study across its range and identification of other ancient populations. [ABSTRACT FROM AUTHOR]

Tree radial growth is one of the most direct measures of tree performance and is also sensitive to climate. Growth performance is the consequence of the interplay between ecological and evolutionary processes. However, the effect of the evolutionary relatedness among species (i.e., phylogeny) on tree radial growth, especially under stressful conditions, remains largely unknown. Furthermore, there is still no ecological evidence for the influence of phylogeny on tree growth across different tree attributes (i.e., tree diameter variation and tree canopy height) and topographic habitat types. We used Blomberg's K to quantify the tree growth phylogenetic signal (TGPS) using two long‐term dendrometer data sets: one a continuous census of 225 tree species at 3‐month intervals in a tropical forest in southwest China from 2009 to 2017; the other, 12 tree species measured at 6‐month intervals in a temperate forest in Washington State, USA from 2013 to 2019. We found that TGPS values were higher in the temperate forest than in the tropical forest. Precipitation, tree diameter, canopy strata, and habitat types all influenced TGPS values. TGPS values were significantly (p < 0.05) and negatively related to precipitation in Xishuangbanna, and the three of four tree diameter classes in the temperate forest, respectively. Stressful growing conditions arose from either based on low precipitation or among large‐diameter trees competing with each other in the upper canopy led to phylogenetic conservatism in trees' radial growth performance. We conclude that phylogeny is pivotal to understanding the growth response differences among species and their responses to climate variability. Key Points: This study examined phylogeny‐based tree radial growth across precipitation gradients and tree attributes (i.e., tree diameter and canopy height) in tropical and temperate forestsTemperate trees showed a stronger phylogenetic growth effect than tropical treesTree radial growth phylogenetic conservatism was higher during stress events (i.e., drought) than in normal climatic situations [ABSTRACT FROM AUTHOR]

Copyright of Functional Ecology is the property of Wiley-Blackwell and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Objective. Using continuous glucose monitoring (CGM), we examined patterns in glycemia during school hours for children with type 1 diabetes, exploring differences between school and nonschool time. Methods. We conducted a retrospective analysis of CGM metrics in children 7–12 years (n = 217, diabetes duration 3.5 ± 2.5 years, hemoglobin A1c 7.5 ± 0.8%). Metrics were obtained for weekday school hours (8 AM to 3 PM) during four weeks in fall 2019. Two comparison settings included weekend (fall 2019) and weekday (spring 2020) data when children had transitioned to virtual school due to COVID-19. We used multilevel mixed models to examine factors associated with time in range (TIR) and compare glycemia between in-school, weekends, and virtual school. Results. Though CGM metrics were clinically similar across settings, TIR was statistically higher, and time above range (TAR), mean glucose, and standard deviation (SD) were lower, for weekends and virtual school (p < 0.001). Hour and setting exhibited a significant interaction for several metrics (p < 0.001). TIR in-school improved from a mean of 40.9% at the start of the school day to 58.0% later in school, with a corresponding decrease in TAR. TIR decreased on weekends (60.8 to 50.7%) and virtual school (62.2 to 47.8%) during the same interval. Mean glucose exhibited a similar pattern, though there was little change in SD. Younger age (p = 0.006), lower hemoglobin A1c (p < 0.001), and insulin pump use (p = 0.02) were associated with higher TIR in-school. Conclusion. Although TIR was higher for weekends and virtual school, glycemic metrics improve while in-school, possibly related to beneficial school day routines. Keywords: type 1 diabetes, school health, continuous glucose monitoring, time in range, glycemic control. [ABSTRACT FROM AUTHOR]

Fungal communities can influence the productivity, composition and survival of trees through cycling nutrients, providing resources and altering pathogens. Thus, shifts in fungal communities could impact forests by altering interactions between trees and their environments. Fungal community composition may be shaped by stochastic and deterministic processes such as dispersal limitation, environmental filtering and partner specificity between trees and fungi. For tree species with large geographical ranges, we expect fungal assembly processes to change with environmental variation across the range of the tree partner. Due to specificity between trees and symbiotic fungi, we expect deterministic to outweigh stochastic processes in root compared with soil fungi. As some tree species have exceptional longevity, we also expected tree age to influence fungal community assembly.We surveyed fungi in four stands of Pseudotsuga menziesii with tree ages up to 800 years along an 1,800 km transect. We sampled roots and soil around 12 P. menziesii in each stand, aged the trees, and sequenced fungal rDNA to determine composition and richness from which we calculated the relative role of deterministic and stochastic assembly processes. We used null models to evaluate the relative importance of deterministic variable and homogenizing selection, and stochastic dispersal limitation, drift and homogenizing dispersal in fungal community assembly.We detected 7,280 amplicon sequence variants with 5,270 associated with soil, 3,887 with roots and 1,877 found across both roots and soils. Deterministic processes dominated root and soil fungal communities at all sites except one where stochastic processes (i.e. dispersal limitation and drift) controlled root fungi. Despite the dominance of determinism in fungal community assembly, the proportion of processes differed by site. Assembly processes did not vary with tree age.Synthesis. Taken together, we suggest that the local environment, water limitation and partner‐preference between trees and their associated fungi, influence fungal community composition across the range of P. menziesii. We conclude that while fungal communities occurring near P. menziesii are dominated by homogenizing selection, the role of neutral processes still has a minor influence on community assembly and may be important in spatially isolated communities and those with strong gradients of fungal diversity. [ABSTRACT FROM AUTHOR]

Aim: Leaf phenology regulates multiple aspects of plant vital activities and provides feedback to climate change. Despite its importance, an effective parameterization method to predict continental‐scale leaf phenology has been elusive. Here, we aimed to develop a new parameterization method using local climatic conditions instead of species or plant functional types to calibrate the phenology parameters of forests. Location: North America. Time period: 1985–2016. Major taxa studied: Forests. Methods: We used the average temperature and photoperiod from the first day to the phenological date in a given year to express the climatic conditions. Using this parameterization method and the typical phenology models, we examined the predictions of start (SOS), end (EOS) and length (GSL) of the growing season with observations from 114 phenology cameras in North American forests. We extrapolated to the continental scale using satellite‐derived leaf area index product as a basis to predict the distribution and changes of forest leaf phenology. Results: We found that the optimum parameters could explain the 81%, 84% and 88% variation in SOS, EOS and GSL of the plot‐scale phenology, respectively. Continental‐scale results over the past decades showed that EOS was delayed by 1.6 days/decade and that GSL increased by 2.2 days/decade, but that there was no significant trend for SOS. Main conclusions: Our study provides strong empirical evidence that the phenology parameters vary with local climatic conditions, and this new parameterization method has potential application for predicting and evaluating future changes in continental‐scale phenology. [ABSTRACT FROM AUTHOR]

Copyright of Journal of Ecology is the property of Wiley-Blackwell and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Plant competition may intensify with climate warming, but whether this will occur equally for conspecific and heterospecific competition remains unknown. Competitive shifts have the potential to instigate community change because the relative strengths of conspecific and heterospecific negative density dependence mediate the stabilizing mechanisms underpinning species coexistence. We examined a mature temperate forest to assess both direct and indirect climate effects at multiple scales: individual species, interspecies relationships, and community stability mechanisms. Our coupled approach (1) quantified tree mortality risk dependence on the interactive effects of competition, climatic water deficit, snowpack, and soil moisture for 28,913 trees over 8 years (3149 mortalities), then (2) used a climate‐projection ensemble to forecast changes in conspecific and heterospecific competition from 2020 to 2100. We predict that projected climate warming will destabilize the foundational forest community by increasing the strength of heterospecific competition at a greater rate and to a greater degree than conspecific competition for four of five abundant tree species, particularly on dry microsites. Modeling showed that these findings were most pronounced after the year 2038, at which point snowpacks were projected to be too small to ameliorate the effects of drought on competitive interactions. Our finding that heterospecific competition is more sensitive than conspecific competition to climate warming may indicate the impending loss of ecosystem functioning. We join the growing body of work showing a predominance of indirect drought effects, yet coupled climate models still fail to consider how changing community dynamics may impact forest cover and, in turn, disrupt forest–climate carbon feedbacks. Ecosystems sharing characteristics with our example forest—those with low species richness and therefore a limited biodiversity insurance effect—may be similarly vulnerable to climate‐mediated destabilization. In such communities, increased heterospecific competition among even a small number of species can more easily destabilize communities without recourse from redundant species. This study of an overlooked but vital mechanism of community change can be adapted by research in a range of ecosystems to improve the understanding of climate change consequences. [ABSTRACT FROM AUTHOR]

Snow duration in post‐fire forests is influenced by neighbourhoods of trees, snags, and deadwood. We used annually resolved, spatially explicit tree and tree mortality data collected in an old‐growth, mixed‐conifer forest in the Sierra Nevada, California, that burned at low to moderate severity to calculate 10 tree neighbourhood metrics for neighbourhoods up to 40 m from snow depth and snow disappearance sampling points. We developed two linear mixed models, predicting snow disappearance timing as a function of tree neighbourhood, litter density, and simulated incoming solar radiation, and two multiple regression models explaining variation in snow depth as a function of tree neighbourhood. Higher densities of post‐fire large‐diameter snags within 10 m of a sampling point were related to higher snow depth (indicating reduced snow interception). Higher densities of large‐diameter trees within 5 m and larger amounts of litter were associated with shorter snow duration (indicating increased longwave radiation emittance and accelerated snow albedo decay). However, live trees with diameters >60 cm within 10 m of a snow disappearance sampling point were associated with a longer‐lasting spring snowpack. This suggests that, despite the local effects of canopy interception and emitted longwave radiation from boles of large trees, shading from their canopies may prolong snow duration over a larger area. Therefore, conservation of widely spaced, large‐diameter trees is important in old‐growth forests because they are resistant to fire and can enhance the seasonal duration of snowmelt. [ABSTRACT FROM AUTHOR]

In an emerging era of megadisturbance, bolstering forest resilience to wildfire, insects, and drought has become a central objective in many western forests. Climate has received considerable attention as a driver of these disturbances, but few studies have examined the complexities of climate–vegetation–disturbance interactions. Current strategies for creating resilient forests often rely on retrospective approaches, seeking to impart resilience by restoring historical conditions to contemporary landscapes, but historical conditions are becoming increasingly unattainable amidst modern bioclimatic conditions. What becomes an appropriate benchmark for resilience when we have novel forests, rapidly changing climate, and unprecedented disturbance regimes? We combined two longitudinal datasets—each representing some of the most comprehensive spatially explicit, annual tree mortality data in existence—in a post‐hoc factorial design to examine the nonlinear relationships between fire, climate, forest spatial structure, and bark beetles. We found that while prefire drought elevated mortality risk, advantageous local neighborhoods could offset these effects. Surprisingly, mortality risk (Pm) was higher in crowded local neighborhoods that burned in wet years (Pm = 42%) compared with sparse neighborhoods that burned during drought (Pm = 30%). Risk of beetle attack was also increased by drought, but lower conspecific crowding impeded the otherwise positive interaction between fire and beetle attack. Antecedent fire increased drought‐related mortality over short timespans (<7 years) but reduced mortality over longer intervals. These results clarify interacting disturbance dynamics and provide a mechanistic underpinning for forest restoration strategies. Importantly, they demonstrate the potential for managed fire and silvicultural strategies to offset climate effects and bolster resilience to fire, beetles, and drought. [ABSTRACT FROM AUTHOR]

Allometric equations for calculation of tree above‐ground biomass (AGB) form the basis for estimates of forest carbon storage and exchange with the atmosphere. While standard models exist to calculate forest biomass across the tropics, we lack a standardized tool for computing AGB across boreal and temperate regions that comprise the global extratropics.Here we present an integrated R package, allodb, containing systematically selected published allometric equations and proposed functions to compute AGB. The data component of the package is based on 701 woody species identified at 24 large Forest Global Earth Observatory (ForestGEO) forest dynamics plots representing a wide diversity of extratropical forests.A total of 570 parsed allometric equations to estimate individual tree biomass were retrieved, checked and combined using a weighting function designed to ensure optimal equation selection over the full tree size range with smooth transitions across equations. The equation dataset can be customized with built‐in functions that subset the original dataset and add new equations.Although equations were curated based on a limited set of forest communities and number of species, this resource is appropriate for large portions of the global extratropics and can easily be expanded to cover novel forest types. [ABSTRACT FROM AUTHOR]

Tree rings provide an invaluable long‐term record for understanding how climate and other drivers shape tree growth and forest productivity. However, conventional tree‐ring analysis methods were not designed to simultaneously test effects of climate, tree size, and other drivers on individual growth. This has limited the potential to test ecologically relevant hypotheses on tree growth sensitivity to environmental drivers and their interactions with tree size. Here, we develop and apply a new method to simultaneously model nonlinear effects of primary climate drivers, reconstructed tree diameter at breast height (DBH), and calendar year in generalized least squares models that account for the temporal autocorrelation inherent to each individual tree's growth. We analyze data from 3811 trees representing 40 species at 10 globally distributed sites, showing that precipitation, temperature, DBH, and calendar year have additively, and often interactively, influenced annual growth over the past 120 years. Growth responses were predominantly positive to precipitation (usually over ≥3‐month seasonal windows) and negative to temperature (usually maximum temperature, over ≤3‐month seasonal windows), with concave‐down responses in 63% of relationships. Climate sensitivity commonly varied with DBH (45% of cases tested), with larger trees usually more sensitive. Trends in ring width at small DBH were linked to the light environment under which trees established, but basal area or biomass increments consistently reached maxima at intermediate DBH. Accounting for climate and DBH, growth rate declined over time for 92% of species in secondary or disturbed stands, whereas growth trends were mixed in older forests. These trends were largely attributable to stand dynamics as cohorts and stands age, which remain challenging to disentangle from global change drivers. By providing a parsimonious approach for characterizing multiple interacting drivers of tree growth, our method reveals a more complete picture of the factors influencing growth than has previously been possible. [ABSTRACT FROM AUTHOR]

Mycorrhizal mutualisms are nearly ubiquitous across plant communities. Yet, it is still unknown whether facilitation among plants arises primarily from these mycorrhizal networks or from physical and ecological attributes of plants themselves. Here, we tested the relative contributions of mycorrhizae and plants to both positive and negative biotic interactions to determine whether plant–soil feedbacks with mycorrhizae neutralize competition and enemies within multitrophic forest community networks. We used Bayesian hierarchical generalized linear modeling to examine mycorrhizal‐guild‐specific and mortality‐cause‐specific woody plant survival compiled from a spatially and temporally explicit data set comprising 101,096 woody plants from three mixed‐conifer forests across western North America. We found positive plant–soil feedbacks for large‐diameter trees: species‐rich woody plant communities indirectly promoted large tree survival when connected via mycorrhizal networks. Shared mycorrhizae primarily counterbalanced apparent competition mediated by tree enemies (e.g., bark beetles, soil pathogens) rather than diffuse competition between plants. We did not find the same survival benefits for small trees or shrubs. Our findings suggest that lower large‐diameter tree mortality susceptibility in species‐rich temperate forests resulted from greater access to shared mycorrhizal networks. The interrelated importance of aboveground and belowground biodiversity to large tree survival may be critical for counteracting increasing pathogen, bark beetle, and density threats. [ABSTRACT FROM AUTHOR]

Carbon sequestration is a key ecosystem service provided by forests. Inventory data based on individual trees are considered to be the most accurate method for estimating forest productivity. However, the estimations of forest photosynthesis from inventory data remain understudied, particularly when considering the growth and development of individual trees under the background of global change.Here, we used the leaf growth process with phenology and non‐structural carbohydrates (NSC) storage to revise an individual‐tree‐based carbon model, FORCCHN. This model couples leaf development and biomass to quantify gross primary productivity (GPP) in the forests, where growth is decoupled from photosynthesis in daily step. The model was initialized with inventory‐based forest data rather than the more widely used satellite‐based data.We tested the model against measured above‐ground woody biomass, growth of leaf biomass, daily gross ecosystem exchange (GEE) and yearly GEE at five representative forest sites in the Northern Hemisphere. We also compared the results from the original model and the revised model at five forest sites. Including leaf growth dynamics and inventory‐based initialization improved the predicted performance (r2) of GPP by an average of 33%.Synthesis and applications. Our results suggest that the appropriate vegetation data sources (i.e. inventory or satellite selection) and the effective predictions of the growth process should be considered when developing future carbon cycle models and forest carbon estimation options. Applying and improving such carbon models to evaluate carbon sequestration is an important part of forest carbon sink management. [ABSTRACT FROM AUTHOR]

Mycorrhizae alter global patterns of CO2 fertilization, carbon storage, and elemental cycling, yet knowledge of their global distributions is currently limited by the availability of forest inventory data. Here, we show that maps of tree‐mycorrhizal associations (hereafter "mycorrhizal maps") can be improved by the novel technology of imaging spectroscopy because mycorrhizal signatures propagate up from plant roots to impact forest canopy chemistry. We analyzed measurements from 143 airborne imaging spectroscopy surveys over 112,975 individual trees collected across 13 years. Results show remarkable accuracy in capturing ground truth observations of mycorrhizal associations from canopy signals across disparate landscapes (R2 = 0.92, p < 0.01). Upcoming imaging spectroscopy satellite missions can reveal new insights into landscape‐scale variations in water, nitrogen, phosphorus, carotenoid/anthocyanin, and cellulose/lignin composition. Applied globally, this approach could improve the spatial precision of mycorrhizal distributions by a factor of roughly 104 and facilitate the incorporation of dynamic shifts in forest composition into Earth system models. Plain Language Summary: Mycorrhizae (plant root‐fungus symbioses) play a central role in ecosystems, and differences in form and function between the two main types of mycorrhizae can influence ecosystem sensitivity to global environmental changes. While the symbioses are located belowground, we show here that they are also associated with subtle but detectable signatures in the structure and composition of forest canopies. As a result, the abundance of each mycorrhizal type can be mapped with both accuracy and precision across a diverse set of ecosystems using the emerging technology of imaging spectroscopy. This advance opens the door to a roughly 10,000x improvement in the precision of current global mycorrhizal maps, which should facilitate advances in several fields of Earth system science. Key Points: First retrieval of mycorrhizal type from imaging spectroscopyMycorrhizhal type can be mapped with accuracy (R2 = 0.92) across disparate landscapesImprovement in spatial precision of roughly 104 over current methods [ABSTRACT FROM AUTHOR]

Recent studies suggest that the mycorrhizal type associated with tree species is an important trait influencing ecological processes such as response to environmental conditions and conspecific negative density dependence (CNDD). However, we lack a general understanding of how tree mycorrhizal type influences CNDD strength and the resulting patterns of species abundance and richness at larger spatial scales. We assessed 305 species across 15 large, stem‐mapped, temperate forest dynamics plots in Northeastern China and North America to explore the relationships between tree mycorrhizal type and CNDD, species abundance, and species richness at a regional scale. Tree species associated with arbuscular mycorrhizal (AM) fungi showed a stronger CNDD and a more positive relationship with species abundance than did tree species associated with ectomycorrhizal (ECM) fungi. For each plot, both basal area and stem abundance of AM tree species was lower than that of ECM tree species, suggesting that AM tree species were rarer than ECM tree species. Finally, ECM tree dominance showed a negative effect on plant richness across plots. These results provide evidence that tree mycorrhizal type plays an important role in influencing CNDD and species richness, highlighting this trait as an important factor in structuring plant communities in temperate forests. [ABSTRACT FROM AUTHOR]

Forest ecosystems are an important sink for terrestrial carbon sequestration. Hence, accurate modeling of the intra‐ and interannual variability of forest photosynthetic productivity remains a key objective in global biology. Applying climate‐driven leaf phenology and growth in models may improve predictions of the forest gross primary productivity (GPP). We used a dynamic non‐structural carbohydrates (NSC) model (FORCCHN2) that couples leaf development and phenology to investigate the relationships among photosynthesis and environmental factors. FORCCHN2 simulates spring and autumn phenological events from heat and chilling, respectively. Leaf area index data from satellites along with climate data estimated localized phenological parameters. NSC limitation, immediate temperature, accumulated heat, and growth potential comprised a daily leaf‐growth model. Functionally, leaf growth was decoupled from photosynthesis. Leaf biomass determined overall photosynthetic production. We compared this model with outputs of the other six terrestrial biospheric models and with observations from the North American Carbon Program Site Interim Synthesis in 18 forest sites. This model improved the predicted performance of yearly GPP with a 57%–210% increase in correlation (median) and up to a 102% reduction in biases (median), compared to three prognostic models and three prescribed models. At the North America continental scale, the model predicted the average annual GPP of 7.38 Pg C/year from forest ecosystems during 1985–2016. The results showed an increasing trend of GPP in North America (1.0 Pg C/decade). The inclusion of climate‐driven phenology and growth has a significant potential for improving dynamic vegetation models, and promotes a further understanding of the complex relationship between environment and photosynthesis. [ABSTRACT FROM AUTHOR]

Background tree mortality is a complex process that requires large sample sizes and long timescales to disentangle the suite of ecological factors that collectively contribute to tree stress, decline, and eventual mortality. Tree mortality associated with acute disturbance events, in contrast, is conspicuous and frequently studied, but there remains a lack of research regarding the role of background mortality processes in mediating the severity and delayed effects of disturbance. We conducted an empirical study by measuring the rates, causes, and spatial pattern of mortality annually among 32,989 individual trees within a large forest demography plot in the Sierra Nevada. We characterized the relationships between background mortality, compound disturbances (fire and drought), and forest spatial structure, and we integrated our findings with a synthesis of the existing literature from around the world to develop a conceptual framework describing the spatio‐temporal signatures of background and disturbance‐related tree mortality. The interactive effects of fire, drought, and background mortality processes altered the rate, spatial structuring, and ecological consequences of mortality. Before fire, spatially non‐random mortality was only evident among small (1 < cm DBH ≤ 10)‐ and medium (10 < cm DBH ≤ 60)‐diameter classes; mortality rates were low (1.7% per yr), and mortality was density‐dependent among small‐diameter trees. Direct fire damage caused the greatest number of moralities (70% of stems ≥1 cm DBH), but the more enduring effects of this disturbance on the demography and spatial pattern of large‐diameter trees occurred during the post‐fire mortality regime. The combined effects of disturbance and biotic mortality agents provoked density‐dependent mortality among large‐diameter (≥60 cm DBH) trees, eliciting a distinct post‐disturbance mortality regime that did not resemble the pattern of either pre‐fire mortality or direct fire effects. The disproportionate ecological significance of the largest trees renders this mortality regime acutely consequential to the long‐term structure and function of forests. [ABSTRACT FROM AUTHOR]

Following a wildfire, regeneration to forest can take decades to centuries and is no longer assured in many western U.S. environments given escalating wildfire severity and warming trends. After large fire years, managers prioritize where to allocate scarce planting resources, often with limited information on the factors that drive successful forest establishment. Where occurring, long‐term effects of postfire salvage operations can increase uncertainty of establishment. Here, we collected field data on postfire regeneration patterns within 13‐ to 28‐yr‐old burned patches in eastern Washington State. Across 248 plots, we sampled tree stems <4 m height using a factorial design that considered (1) fire severity, moderate vs. high severity; (2) salvage harvesting, salvaged vs. no management; and (3) potential vegetation type (PVT), sample resides in a dry, moist, or cold mixed‐conifer forest environment. We found that regeneration was abundant throughout the study region, with a median of 4414 (IQR 19,618) stems/ha across all plots. Only 15% of plots fell below minimum timber production stocking standards (350 trees/ha), and <2% of plots were unstocked. Densities were generally highest in high‐severity patches and following salvage harvesting, although high variability among plots and across sites led to variable significance for these factors. Post hoc analyses suggested that mild postfire weather conditions may have reduced water stress on tree establishment and early growth, contributing to overall high stem densities. Douglas fir was the most abundant species, particularly in moderate‐severity patches, followed by ponderosa pine, lodgepole pine, western larch, and Engelmann spruce. Generalized additive models (GAMs) revealed species‐level climatic tolerances and seed dispersal limits that portend future challenges to regeneration with expected future climate warming and increased fire activity. Postfire regeneration will occur on sites with adequate seed sources within their climatic tolerances. [ABSTRACT FROM AUTHOR]

Maps of snow cover serve as early indicators for hydrologic forecasts and as inputs to hydrologic models that inform water management strategies. Advances in snow cover mapping have led to increasing accuracy, but unsatisfactory treatment of vegetation's interference when mapping snow has led to maps that have limited utility for water forecasting. Vegetation affects snow mapping because ground surfaces not visible to the satellite produce uncertainty as to whether the ground is snow covered. At nadir, the forest canopy obscures the satellite view below the canopy. At oblique viewing angles, the forest floor is obscured by both the canopy and the projection of tree profiles onto the forest floor. We present a canopy correction method based on Moderate Resolution Imaging Spectroradiometer satellite imagery validated with field observations that mitigates geometric and georegistration issues associated with changing satellite acquisition angles in forested areas. The largest effect from a variable viewing zenith angle on the viewable gap fraction in forested areas occurs in moderately forested areas with 30–40% tree canopy coverage. Cloud cover frequently causes errors in snow identification, with some clouds identified as snow and some snow identified as cloud. A snow‐cloud identification method utilizes a time series of fractional vegetation and rock land‐surface data to flag snow‐cloud identification errors and improve snow‐map accuracy reducing bias by 20% over previous methods. Together, these contributions to snow‐mapping techniques could advance hydrologic forecasting in forested, snow‐dominated basins that comprise an estimated one fifth of Northern Hemisphere snow‐covered areas. Plain Language Summary: Mapping snow cover extent informs water resources stored in the winter snowpack, providing important information for planning how and when to utilize available water. Tree canopies shield the forest floor and hinder the determination of snow‐covered area in vegetated terrain from above, where satellites view the Earth's surface. Moreover, satellites that scan the surface (like the Moderate Resolution Imaging Spectroradiometer) are most often not directly overhead, and as the view from the satellite to the surface slants, trees obscure a greater portion of the land surface that a satellite can "see," especially where trees are tall, adding uncertainty to the satellite‐based maps. This effect is greatest in forests where 30–40% of the land area is covered by tree canopy and has little effect in very dense forests where most of the forest floor is obscured already. Here we present a method to accommodate the stretched and hidden forest footprint when a satellite is not directly overhead. A new method for identifying snow‐mapping errors caused by clouds is also presented by flagging unusually large changes in the non‐snow surfaces over sequential images. These methodological advancements are important because snow‐melt water comprises a major portion of the water supply in many regions where humans live. Key Points: The canopy correction methodology improves remotely sensed snow mapping accuracy in forested environments, reducing bias by 20%A novel cloud detection algorithm that uses fractional vegetation and rock coverage can reduce snow‐cloud identification errorsImproved performance over previous snow mapping approaches enable melt out date identification within days of actual snow disappearance [ABSTRACT FROM AUTHOR]

Non‐structural carbohydrates (NSC) are considered important in the metabolism of wood plants, and they are highly dynamic. Accurate and detailed modelling of NSC dynamics may increase the understanding of physiological processes.We constructed a physiological model that simulates NSC dynamics from photosynthesis, transpiration and growth carbon demand. With this model, we tested the hypotheses that production, allocation and storage explain tree‐ and forest‐level carbohydrates balance, and especially that cambial activities explain the major portion of carbon consumption.We applied this model at one plot in Harvard Forest, Massachusetts, USA. The predicted results of stem‐wood NSC dynamics of 20 deciduous broad‐leaved trees corresponded well with measurements. NSC (i.e. product from photosynthesis) allocations depended on thermal time and the development stage of each organ. Water movements driven by water potential gradients in whole‐trees also influenced tree growth, which was a necessary process for predicting the daily NSC dynamics.Synthesis. This model combined wood growth at whole‐tree scale and carbohydrates balance at cellular scale with short‐term vegetation hydraulics. The model provides a foundation to further understand the complex interactions between environmental factors and tree carbon allocation. [ABSTRACT FROM AUTHOR]

Wildfire is an essential earth‐system process, impacting ecosystem processes and the carbon cycle. Forest fires are becoming more frequent and severe, yet gaps exist in the modeling of fire on vegetation and carbon dynamics. Strategies for reducing carbon dioxide (CO2) emissions from wildfires include increasing tree harvest, largely based on the public assumption that fires burn live forests to the ground, despite observations indicating that less than 5% of mature tree biomass is actually consumed. This misconception is also reflected though excessive combustion of live trees in models. Here, we show that regional emissions estimates using widely implemented combustion coefficients are 59%–83% higher than emissions based on field observations. Using unique field datasets from before and after wildfires and an improved ecosystem model, we provide strong evidence that these large overestimates can be reduced by using realistic biomass combustion factors and by accurately quantifying biomass in standing dead trees that decompose over decades to centuries after fire ("snags"). Most model development focuses on area burned; our results reveal that accurately representing combustion is also essential for quantifying fire impacts on ecosystems. Using our improvements, we find that western US forest fires have emitted 851 ± 228 Tg CO2 (~half of alternative estimates) over the last 17 years, which is minor compared to 16,200 Tg CO2 from fossil fuels across the region. [ABSTRACT FROM AUTHOR]

Questions: We examined the spatial patterns of dominant canopy species in a tropical forest to investigate: (a) what is the niche occupancy of canopy species with respect to topographic gradients; (b) what are the dominant ecological processes that explain their distribution; (c) what are the interactions among the most prevalent canopy species; and (d) what are the interactions between canopy species adults and juveniles trees? Location: Rabi permanent CTFS‐ForestGEO plot, Gabon. Methods: We selected the four most abundant canopy species and one timber species. We used Berman's test to determine the effect of three topographic variables on the distribution of each species and univariate analysis to model the spatial pattern of each species using either an inhomogeneous Poisson process or an inhomogeneous Cox process. We also used a bivariate form of the pair correlation function (PCF) to determine the spatial interaction between species and the correlation among conspecific adult and juvenile trees. Results: Four of the five species had aggregated spatial patterns while Lophira alata showed spatial randomness. Most of the variance in the local tree density was explained by within‐population dispersal processes rather than environmental factors. Bivariate PCF tests showed significant segregation between species associations. Two species exhibited aggregation at small distances between young and adult trees, while others showed either complete spatial randomness at small inter‐tree distances or segregation at large distances. Conclusions: This study showed that the spatial pattern in the majority of canopy species was aggregation. Seed dispersal limitation mainly explained the observed aggregation pattern. Habitat filtering, as evidenced by the influence of topographic variables on niche occupancy, marginally, yet significantly, explained this pattern. The different spatial patterns of the principal species permit their coexistence. Spatial segregation among adult and juvenile trees reveals a strong pattern of either species‐specific seed predation or pathogens. [ABSTRACT FROM AUTHOR]

Aim: The relationship between the proportion of sites occupied by a species and the area of a site [occupancy–area relationship (OAR)] offers key information for biodiversity management and has long fascinated ecologists. We quantified the variation in OAR for 3,157 woody species in 17 forest plots worldwide and tested the relative importance of environment and species traits for explaining this variation and evaluated overall model predictive ability. Location: Global. Time period: Early 21st century. Major taxa studied: Woody plants. Methods: We used mixed‐effect regression to examine the observed shape of the OAR (its "slope") against species‐specific and plot‐wide predictors: coarse‐grain occupancy, tree size, plot species richness, energy availability and topographic complexity. Results: We found large variation in OAR slopes, and the variation was strongest among species within plots. The OAR slopes showed a latitudinal trend and were steeper near the equator. As predicted, coarse‐grain occupancy and tree size negatively affected OAR slopes, whereas species richness had a positive effect and explained most of the variance between plots. Although hypothesized directionalities were broadly confirmed, traits and environment had relatively limited overall predictive power. Main conclusions: These results document the variation of the OAR for 3,157 species at near‐global extent. We found a latitudinal gradient in OAR slopes and confirmed key hypothesized predictors. But at this global extent and over the large set of species analysed, the remaining unexplained variation in OAR slopes was substantial. Nevertheless, this large‐scale empirical analysis of the OAR offers an initial step towards a more general use of OARs for the fine‐scale prediction of species distributions and abundance. [ABSTRACT FROM AUTHOR]

Climate is widely recognised as an important determinant of the latitudinal diversity gradient. However, most existing studies make no distinction between direct and indirect effects of climate, which substantially hinders our understanding of how climate constrains biodiversity globally. Using data from 35 large forest plots, we test hypothesised relationships amongst climate, topography, forest structural attributes (stem abundance, tree size variation and stand basal area) and tree species richness to better understand drivers of latitudinal tree diversity patterns. Climate influences tree richness both directly, with more species in warm, moist, aseasonal climates and indirectly, with more species at higher stem abundance. These results imply direct limitation of species diversity by climatic stress and more rapid (co‐)evolution and narrower niche partitioning in warm climates. They also support the idea that increased numbers of individuals associated with high primary productivity are partitioned to support a greater number of species. [ABSTRACT FROM AUTHOR]

Aim: To examine the contribution of large-diameter trees to biomass, stand structure, and species richness across forest biomes. Location: Global. Time period: Early 21st century. Major taxa studied: Woody plants. Methods: We examined the contribution of large trees to forest density, richness and biomass using a global network of 48 large (from 2 to 60 ha) forest plots representing 5,601,473 stems across 9,298 species and 210 plant families. This contribution was assessed using three metrics: the largest 1% of trees ≥ 1 cm diameter at breast height (DBH), all trees ≥ 60 cm DBH, and those rank-ordered largest trees that cumulatively comprise 50% of forest biomass. Results: Averaged across these 48 forest plots, the largest 1% of trees ≥ 1 cm DBH comprised 50% of aboveground live biomass, with hectare-scale standard deviation of 26%. Trees ≥ 60 cm DBH comprised 41% of aboveground live tree biomass. The size of the largest trees correlated with total forest biomass (r2=.62, p<.001). Large-diameter trees in high biomass forests represented far fewer species relative to overall forest richness (r2=.45, p<.001). Forests with more diverse large-diameter tree communities were comprised of smaller trees (r2=.33, p<.001). Lower largediameter richness was associated with large-diameter trees being individuals of more common species (r2=.17, p5.002). The concentration of biomass in the largest 1% of trees declined with increasing absolute latitude (r2=.46, p<.001), as did forest density (r2=.31, p<.001). Forest structural complexity increased with increasing absolute latitude (r2=.26, p<.001). Main conclusions: Because large-diameter trees constitute roughly half of the mature forest biomass worldwide, their dynamics and sensitivities to environmental change represent potentially large controls on global forest carbon cycling. We recommend managing forests for conservation of existing large-diameter trees or those that can soon reach large diameters as a simple way to conserve and potentially enhance ecosystem services. [ABSTRACT FROM AUTHOR]

Abstract: Questions: What drives individual species–area relationships in temperate coniferous forests? Location: Two 25.6‐ha forest plots on the Pacific Slope of North America, one in California, and one in Washington State. Methods: We mapped all trees ≥1 cm in diameter and examined tree species diversity of their local neighbourhoods by calculating the individual species–area relationship for each species and for each of three diameter classes (saplings, mature trees and large‐diameter trees). Results: In the California plot, small trees in four of the five major species occurred in neighbourhoods with higher levels of diversity than would be expected at random. In the Washington plot, small trees for four of five abundant species had neighbourhoods with lower than expected diversity at distances ≤5 m for small trees. However, at distances >5 m, all five species showed higher than expected diversity in their neighbourhoods. Larger trees at both plots tended to occur in neighbourhoods with lower than expected diversity, and no large‐diameter focal species had neighbourhoods with higher than expected diversity. Conclusion: Diversity and co‐existence in temperate conifer‐dominated forests do not appear to be the result of random processes. Competitive interactions appear to dominate for the largest trees of most species, resulting in neighbourhoods with lower diversity. For smaller trees, we suggest that a positive response to environmental heterogeneity is the likely driver of neighbourhoods with higher than expected diversity, although we cannot rule out the possibility that facilitation or conspecific negative density dependence (CNDD) also play a role. [ABSTRACT FROM AUTHOR]

A warming climate, fire exclusion, and land cover changes are altering the conditions that produced historical fire regimes and facilitating increased recent wildfire activity in the northwestern United States. Understanding the impacts of changing fire regimes on forest recruitment and succession, species distributions, carbon cycling, and ecosystem services is critical, but challenging across broad spatial scales. One important and understudied aspect of fire regimes is the unburned area within fire perimeters; these areas can function as fire refugia across the landscape during and after wildfire by providing habitat and seed sources. With increasing fire activity, there is speculation that fire intensity and combustion completeness are also increasing, which we hypothesized would yield smaller unburned proportions and changes in fire refugia patterns. We sought to determine (1) whether the unburned proportion of wildfires decreased across the northwestern United States from 1984 to 2014 and (2) whether patterns of unburned patches were significantly different across ecoregions, land cover type, and land ownership. We utilized a Landsat-derived geospatial database of unburned islands within 2298 fires across the inland northwestern USA (including eastern Washington, eastern Oregon, and Idaho) from 1984 to 2014. We evaluated patterns of the total unburned proportion and spatial patterns of unburned patches of the fires across different ecoregions, land cover types, and land ownership. We found that unburned area proportion exhibited no change over the three decades, suggesting that recent trends in area burned and overall severity have not affected fire refugia, important to post-fire ecosystem recovery. There were ecoregional differences in mean unburned proportion, patch area, and patch density, suggesting influences of vegetation and topography on the formation of unburned area. These foundation findings suggest that complex drivers control unburned island formation, and yield insights to locate potential important fire refugia across the inland northwest. [ABSTRACT FROM AUTHOR]

Historical forest conditions are often used to inform contemporary management goals because historical forests are considered to be resilient to ecological disturbances. The General Land Office ( GLO) surveys of the late 19th and early 20th centuries provide regionally quasi-contiguous data sets of historical forests across much of the Western United States. Multiple methods exist for estimating tree density from point-based sampling such as the GLO surveys, including distance-based and area-based approaches. Area-based approaches have been applied in California mixed-conifer forests but their estimates have not been validated. To assess the accuracy and precision of plotless density estimators with potential for application to GLO data in this region, we imposed a GLO sampling scheme on six mapped forest stands of known densities (159-784 trees/ha) in the Sierra Nevada in California, USA, and Baja California Norte, Mexico. We compared three distance-based plotless density estimators (Cottam, Pollard, and Morisita) as well as two Voronoi area ( VA) estimators, the Delincé and mean harmonic Voronoi density ( MHVD), to the true densities. We simulated sampling schemes of increasing intensity to assess sampling error. The relative error ( RE) of density estimates for the GLO sampling scheme ranged from 0.36 to 4.78. The least biased estimate of tree density in every stand was obtained with the Morisita estimator and the most biased was obtained with the MHVD estimator. The MHVD estimates of tree density were 1.2-3.8 times larger than the true densities and performed best in stands subject to fire exclusion for 100 yr. The Delincé approach obtained accurate estimates of density, implying that the Voronoi approach is theoretically sound but that its application in the MHVD was flawed. The misapplication was attributed to two causes: (1) the use of a crown scaling factor that does not correct for the number of trees sampled and (2) the persistent underestimate of the true VA due to a weak relationship between tree size and VA. The magnitude of differences between true densities and MHVD estimates suggest caution in using results based on the MHVD to inform management and restoration practices in the conifer forests of the American West. [ABSTRACT FROM AUTHOR]

Throughout the Sierra Nevada, nearly a century of fire suppression has altered the tree species composition, forest structure, and fire regimes that were previously characteristic of montane forests. Species composition is fundamentally important because species differ in their tolerances to fire and environmental stressors, and these differences dictate future forest structure and influence fire regime attributes. In some lower montane stands, shade-tolerant, fire-sensitive species have driven a threefold increase in tree density that may intensify the risk of high-severity fire. In upper montane forests, which were historically characterized by longer fire return intervals, the effects of fire exclusion are both less apparent and less studied. Although land managers have been reintroducing fire to lower and upper montane forests for >4 decades, the potentially restorative effects of these actions on species composition remain largely unassessed. We used tree diameter and species data from 51 recently burned and 46 unburned plots located throughout lower and upper montane forests in Yosemite National Park and Sequoia & Kings Canyon National Parks to examine the effects of low- to moderate-severity (hereafter, lower-severity) fire on the demography of seven prevalent tree species. The density of Abies concolor <30 cm diameter at breast height (dbh) was significantly lower in burned plots than unburned plots; densities of A. concolor 30-45 cm dbh, A. magnifica <30 cm dbh, and Calocedrus decurrens <15 cm dbh were lower in burned plots than unburned plots at a marginal level of significance. These diameter thresholds represent the maximum size at which each species is likely to experience significant mortality from lower-severity fire. We overlaid these thresholds on historical and contemporary diameter distributions to show that: (1) lower-severity fire has reduced mean tree density to historical levels for A. concolor but not for C. decurrens, and (2) variability in tree density among plots that burned at lower severity exceeded the range of tree densities reported in historical data sets. High proportions of shade-tolerant species in some postfire stands may increase the prevalence of shade-tolerant species in the future, a potential concern for managers who seek to minimize ladder fuels and promote forest structure that is less prone to high-severity fire. [ABSTRACT FROM AUTHOR]

Rates and spatial patterns of tree mortality are predicted to change during forest structural development. In young forests, mortality should be primarily density dependent due to competition for light, leading to an increasingly spatially uniform pattern of surviving trees. In contrast, mortality in old-growth forests should be primarily caused by contagious and spatially autocorrelated agents (e.g., insects, wind), causing spatial aggregation of surviving trees to increase through time. We tested these predictions by contrasting a threedecade record of tree mortality from replicated mapped permanent plots located in young (<60-year-old) and old-growth (>300-year-old) Abies amabilis forests. Trees in young forests died at a rate of 4.42% per year, whereas trees in old-growth forests died at 0.60% per year. Tree mortality in young forests was significantly aggregated, strongly density dependent, and caused live tree patterns to become more uniform through time. Mortality in old-growth forests was spatially aggregated, but was density independent and did not change the spatial pattern of surviving trees. These results extend current theory by demonstrating that densitydependent competitive mortality leading to increasingly uniform tree spacing in young forests ultimately transitions late in succession to a more diverse tree mortality regime that maintains spatial heterogeneity through time. [ABSTRACT FROM AUTHOR]

Spatially distributed snow depth and snow duration data were collected over two to four snow seasons during water years 2011-2014 in experimental forest plots within the Cedar River Municipal Water-shed, 50 km east of Seattle, Washington, USA. These 40 × 40 m forest plots, situated on the western slope of the Cascade Range, include unthinned second-growth coniferous forests, variable density thinned forests, forest gaps in which a 20 m diameter (approximately equivalent to one tree height) gap was cut in the middle of each plot, and old-growth forest. Together, this publicly available data set includes snow depth and density observations from manual snow surveys, distributed snow duration observations from ground temperature sensors and time-lapse cameras, meteorological data collected at two open locations and three forested locations, and forest canopy data from airborne light detection and ranging (LiDAR) data and hemispherical photographs. These colocated snow, meteorological, and forest data have the potential to improve understanding of forest influences on snow processes, and provide a unique model-testing data set for hydrological analyses in a forested, maritime watershed. We present empirical snow depletion curves within forests to illustrate an application of these data to improve subgrid representation of snow cover in distributed modeling. [ABSTRACT FROM AUTHOR]

Forests cover almost 40% of the seasonally snow-covered regions in North America. However, operational snow networks are located primarily in forest clearings, and optical remote sensing cannot see through tree canopies to detect forest snowpack. Due to the complex influence of the forest on snowpack duration, ground observations in forests are essential. We therefore consider the effectiveness of different strategies to observe snow-covered area under forests. At our study location in the Pacific Northwest, we simultaneously deployed fiber-optic cable, stand-alone ground temperature sensors, and time-lapse digital cameras in three diverse forest treatments: control second-growth forest, thinned forest, and forest gaps (one tree height in diameter). We derived fractional snow-covered area and snow duration metrics from the colocated instruments to assess optimal spatial resolution and sampling configuration, and snow duration differences between forest treatments. The fiber-optic cable and the cameras indicated that mean snow duration was 8 days longer in the gap plots than in the control plots ( p < 0.001). We conducted Monte Carlo experiments for observing mean snow duration in a 40 m forest plot, and found the 95% confidence interval was ±5 days for 10 m spacing between instruments and ±3 days for 6 m spacing. We further tested the representativeness of sampling one plot per treatment group by observing snow duration across replicated forest plots at the same elevation, and at a set of forest plots 250 m higher. Relative relationships between snow duration in the forest treatments are consistent between replicated plots, elevation, and two winters of data. [ABSTRACT FROM AUTHOR]

Mortality processes in old-growth forests are generally assumed to be driven by gap-scale disturbance, with only a limited role ascribed to density-dependent mortality, but these assumptions are rarely tested with data sets incorporating repeated measurements. Using a 12-ha spatially explicit plot censused 13 years apart in an approximately 500-year-old Pseudotsuga-Tsuga forest, we demonstrate significant density-dependent mortality and spatially aggregated tree recruitment. However, the combined effect of these strongly nonrandom demographic processes was to maintain tree patterns in a state of dynamic equilibrium. Density-dependent mortality was most pronounced for the dominant latesuccessional species, Tsuga heterophylla. The long-lived, early-seral Pseudotsuga menziesii experienced an annual stem mortality rate of 0.84% and no new recruitment. Late-seral species Tsuga and Abies amabilis had nearly balanced demographic rates of ingrowth and mortality. The 2.34% mortality rate for Taxus brevifolia was higher than expected, notably less than ingrowth, and strongly affected by proximity to Tsuga. Large-diameter Tsuga structured both the regenerating conspecific and heterospecific cohorts with recruitment of Tsuga and Abies unlikely in neighborhoods crowded with large-diameter competitors (P < 0.001). Densitydependent competitive interactions strongly shape forest communities even five centuries after stand initiation, underscoring the dynamic nature of even equilibrial old-growth forests [ABSTRACT FROM AUTHOR]

Many regions of the world are dependent on snow cover for frost protection and summer water supplies. These same regions are predominantly forested, with forests highly vulnerable to change. Here we combine a meta-analysis of observational studies across the globe with modeling to show that in regions with average December-January-February (DJF) temperatures greater than −1°C, forest cover reduces snow duration by 1-2 weeks compared to adjacent open areas. This occurs because the dominant effect of forest cover shifts from slowing snowmelt by shading the snow and blocking the wind to accelerating snowmelt from increasing longwave radiation. In many locations, midwinter melt removes forest snow before solar radiation is great enough for forest shading to matter, and with warming temperatures, midwinter melt is likely to become more widespread. This temperature-effect in forest-snow-climate interactions must be considered in representations of the combined ecohydrological system and can be used advantageously in forest management strategies. [ABSTRACT FROM AUTHOR]

[1] Tree canopy snow interception is a significant hydrological process, capable of removing up to 60% of snow from the ground snowpack. Our understanding of canopy interception has been limited by our ability to measure whole canopy water storage in an undisturbed forest setting. This study presents a relatively inexpensive technique for directly measuring snow canopy water storage using an interceptometer, adapted from Friesen et al. (2008). The interceptometer is composed of four linear motion position sensors distributed evenly around the tree trunk. We incorporate a trunk laser-mapping installation method for precise sensor placement to reduce signal error due to sensor misalignment. Through calibration techniques, the amount of canopy snow required to produce the measured displacements can be calculated. We demonstrate instrument performance on a western hemlock (Tsuga heterophylla) for a snow interception event in November 2011. We find a snow capture efficiency of 83 ± 15% of accumulated ground snowfall with a maximum storage capacity of 50 ± 8 mm snow water equivalent (SWE). The observed interception event is compared to simulated interception, represented by the variable infiltration capacity (VIC) hydrologic model. The model generally underreported interception magnitude by 33% using a leaf area index (LAI) of 5 and 16% using an LAI of 10. The interceptometer captured intrastorm accumulation and melt rates up to 3 and 0.75 mm SWE h-1, respectively, which the model failed to represent. While further implementation and validation is necessary, our preliminary results indicate that forest interception magnitude may be underestimated in maritime areas. [ABSTRACT FROM AUTHOR]

Stem exclusion and understory reinitiation are commonly described, but poorly understood, stages of forest development. It is assumed that overstory trees exert strong controls on understory herbs and shrubs during the transition from open- to closed-canopy forests, but long-term observations of this process are rare. We use long-term data from 188 plots to explore patterns and correlates of variation in understory richness and abundance 15-45 years after clear-cut logging and burning of two experimental watersheds in western Oregon, USA. We test whether variation in the temporal dynamics of plots can be explained by topoedaphic factors that influence resource availability (insolation and soil moisture), variation in the pace and intensity of overstory development, or characteristics of the vegetation prior to canopy closure. Changes in forest structure were substantial over the study period; canopy cover increased fourfold, stem density by 75%, and bole biomass by two orders of magnitude, although trends were highly variable among individual plots. In contrast, understory richness, foliar cover, and biomass declined only 30-40%, driven by loss of early-seral colonists, not residual forest species. Canopy closure occurred earlier on north aspects but declines in understory biomass, reflecting loss of colonizing shrubs (without concomitant increases in forest shrubs), were limited to south aspects. In contrast, variation in effective soil moisture had little influence on the pace of decline. Temporal trends were highly asynchronous among plots: nearly 50% of plots experienced some form of decline, but >35% showed no discernible trend. Declines were more likely in plots with greater tree influence before or at peak overstory development, but also in plots with greater understory development prior to canopy closure. Quantile regression models indicated weak relationships between understory biomass and overstory structure at most points in time. Our long-term data support a model of understory dynamics in which characteristics of the pre-closure vegetation are as important as overstory structure in determining the timing and nature of decline. Long-term studies are critical for elucidating patterns and processes that canndt be inferred from short-term experiments or space-for-time substitutions. [ABSTRACT FROM AUTHOR]

Reducing the water use of plumbing products-toilets, urinals, faucets, and showerheads-has become a popular conservation measure, and improved technologies have created opportunities for further progress. Plumbing products do not operate in a vacuum, however. This article reviews the literature related to plumbing products and organizes it into a framework comprising the following categories: water use efficiency, product components, product performance, source water, energy, and plumbing and sewer infrastructure. This framework provides a starting point for professionals considering water efficiency and conservation measures to identify relevant technologies and trends as well as crosscutting issues that should be considered [ABSTRACT FROM AUTHOR]

An Abstract of the article "Potential Site Productivity Influences the Rate of Forest Structural Development," by Andrew J. Larson is presented.

Tree mortality is a critical but understudied process in coniferous forest development. Current successional models assume that mortality during early forest development is dominated by density-dependent processes, but few long-term studies exist to test this assumption. We examined changes in forest structure and patterns of tree mortality 14-38 years (1979-2001) after clear-cut logging of two experimental watersheds in the western Cascade Range of Oregon, USA. We sampled 193 permanent plots (250 m²) six times generating 75 126 data records and 7146 incidents of mortality. Mean density peaked at > 3000 stems/ha (≥ 1.4 m tall) after 22-25 years; bole biomass increased continuously to >100 Mg/ha. At final sampling, stem density varied by two orders of magnitude and biomass by a factor of 10 among sample plots. Suppression mortality occurred in >80% of plots and was >2.5 times as frequent as mechanical damage (uprooting, stem snap, and crushing). However, biomass lost to mortality via mechanical damage was nearly four times that lost to suppression, a result of episodic storms that created windthrow patches, with some plots losing 30-50% of biomass. Total annual mortality increased from 1.0% to 5.3% of stems over the study period and was highly variable among species. Although mortality rates were highest for sprouting hardwoods (reaching 9.7% in Cornus nuttallii), biomass of most hardwood species increased through canopy closure as dominant stems achieved large sizes. Shade-tolerant conifers (Tsuga heterophylla and Thuja plicata), typically assumed to be absent or to play a minor role in early forest development, accounted for 26% of stems after 38 years. In regression tree models, environmental attributes of plots had limited ability to predict mortality. Instead, stem density prior to canopy closure was the strongest predictor of cumulative mortality (either suppression or mechanical damage). Our long-term studies suggest that current models of early forest development are overly simplistic, particularly in their treatment of mortality. Although suppression was the dominant demographic process, mechanical damage yielded greater loss of biomass and greater structural heterogeneity through creation of windthrow gaps. Thus, gap-forming processes that operate late in succession and contribute to structural complexity in old-growth forests can also occur early in stand development. [ABSTRACT FROM AUTHOR]

Estimating historical forest density from land-survey data: a response to Baker and Williams (2018) Levine et al. ([19]) found that the Morisita estimator was the least biased and most precise estimator for estimating density from GLO survey data, with a relative root mean square error ranging from 0.11 to 0.78 for the six study sites. Tree size (i.e., DSH) and neighborhood density (i.e., MND) are crucial to the calculation of MHVD since both are used in the projection of Voronoi area (Williams and Baker [32]). The scaling factor (MND) used by Williams and Baker ([32]) in Voronoi area equations is identical to the Cottam plotless density estimator for four-tree (4nn) corners (Cottam and Curtis [9]). [Extracted from the article]

Variation in tree recruitment, mortality, and growth can alter forest community composition and structure. Because tree recruitment and mortality events are generally infrequent, long‐time scales are needed to confirm trends in forests. We performed a 50‐yr demographic census of a forest plot located on the southern edge of the Canadian boreal forest, a region currently experiencing forest die‐back in response to direct and indirect effects of recent severe droughts. Here, we show that over the last 30 yr biomass, basal area, growth, and recruitment have decreased along with a precipitous rise in mortality across the dominant tree species. The stand experienced periods of drought in combination with multiple outbreaks of forest tent caterpillar (Malacosoma disstria) and bark beetles. These insect disturbances interacted to increase mortality rates within the stand and decrease stand density. The interaction of endogenous and exogenous factors may shift forests in this region onto novel successional trajectories with the possibility of changes in regional vegetation type. [ABSTRACT FROM AUTHOR]

Megafires have lasting social, ecological, and economic impacts and are increasing in the western contiguous United States. Because of their infrequent nature, there is a limited sample of megafires to investigate their unique behavior, drivers, and relationship to forest management practices. One approach is to characterize critical information pre-, during, and post-fire using remote sensing. In August 2013, the Rim Fire burned 104,131 ha and in September 2014, the King Fire burned 39,545 ha. Both fires occurred in California's Sierra Nevada. The areas burned by these fires were fortuitously surveyed by airborne campaigns, which provided the most recent remote sensing technologies not currently available from satellite. Technologies include an imaging spectrometer spanning the visible to shortwave infrared (0.38-2.5 μm), a multispectral, high-spatial resolution thermal infrared (3.5-13 μm) spectroradiometer, and Light Detection and Ranging that provide spatial resolutions of pixels from 1 × 1 m to 35 × 35 m. Because of the unique information inherently derived from these technologies before the fires, the areas were subsequently surveyed after the fires. We processed and provide free dissemination of these airborne datasets as products of surface reflectance, spectral metrics and forest structural metrics ( ). These data products provide a unique opportunity to study relationships among and between remote sensing observations and fuel and fire characteristics (e.g., fuel type, condition, structure, and fire severity). The novelty of these data is not only in the unprecedented types of information available from them before, during, and after two megafires, but also in the synergistic use of multiple state of the art technologies for characterizing the environment. The synergy of these data can provide novel information that can improve maps of fuel type, structure, abundance, and condition that may improve predictions of megafire behavior and effects, thus aiding management before, during, and after such events. Key questions that these data could address include: What drives, extinguishes, and results from megafires? How does megafire behavior relate to fire and fuel management? How does the size and severity of a megafire affect the ecological recovery of the system? [ABSTRACT FROM AUTHOR]

The article discusses the characteristics of mid-career ecology graduates students, the difference in their educational needs and the strengths in the U.S. It discourses the survey conducted by the National Science Board (NSB) which examines the characteristics, motivations, and strategies for success of the mid-career students. It asserts the importance of an advisor for mid-career students in guiding their education as well as mentions the academic, personal, and financial challenges in their education which claims to have been characterized at their undergraduate level. Moreover, it notes that mixing traditional and mid-career students improves productivity that leads interpersonal relationships.