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An integrated information retrieval and document management system

This paper describes the requirements and prototype development for an intelligent document management and information retrieval system that will be capable of handling millions of pages of text or other data. Technologies for scanning, Optical Character Recognition (OCR), magneto-optical storage, and multiplatform retrieval using a Standard Query Language (SQL) will be discussed. The semantic ambiguity inherent in the English language is somewhat compensated-for through the use of coefficients or weighting factors for partial synonyms. Such coefficients are used both for defining structured query trees for routine queries and for establishing long-term interest profiles that can be used on a regular basis to alert individual users to the presence of relevant documents that may have just arrived from an external source, such as a news wire service. Although this attempt at evidential reasoning is limited in comparison with the latest developments in AI Expert Systems technology, it has the advantage of being commercially available.

Coles, L. Stephen↗

Improving Carbon Estimation of Large Tropical Trees by Linking Airborne Lidar Crown Size to Field Inventory

Quantifying tropical aboveground biomass (agb) is an outstanding challenge that requires knowledge on the 3D structure of forests. Recent studies suggest that the uncertainty in estimating agb of large trees is significantly reduced if tree height and crown size are accounted for in addition to the traditional trunk diameter and wood density. Due to the fact that field inventory techniques are not adapted to characterize the 3D forest structure, crown size metrics (e.g. height and radius) are commonly estimated as a function of trunk diameter using allometric models with limitations in explaining crown variability. Airborne lidar techniques have the potential for characterizing tree height and crown size but are not adapted to estimate trunk diameter, which is a strong predictor of agb. Here, we investigate the synergy of field inventory and airborne lidar techniques to characterize the forest structure by assessing the uncertainty introduced by the field-based allometric models in the estimation of agb at the tree-level. We focus in 1454 large individual trees (trunk diameter > 60 cm) located within the La Selva Biological Station for which we dispose of field observations (trunk diameter and wood density) and lidar derived metrics (tree height and crown radius). We show that the field-based allometric models overestimate tree height and underestimate crown radius. As a result, the allometric approach overestimates the tree-level agb in 0.8 Mg when considering the 1454 individuals and the errors can reach more than 50% of the agb of individual trees. These errors on the large trees agb highly impact on the plot-level results and then propagate to the estimation of carbon stocks at the regional and national-levels.

Clark, David↗

Effect of species structure and dielectric constant on C-band forest backscatter

A joint experiment between Canadian and USA research teams was conducted early in Oct. 1992 to determine the effect of species structure and dielectric variations on forest backscatter. Two stands, one red pine and one jack pine, in the Petawawa National Forestry Institute (PNFI) were utilized for the experiment. Extensive tree architecture measurements had been taken by the Canada Centre for Remote Sensing (CCRS) several months earlier by employing a Total Station surveying instrument which provides detailed information on branch structure. A second part of the experiment consisted of cutting down several trees and using dielectric probes to measure branch and needle permittivity values at both sites. The dielectric and the tree geometry data were used in the George Washington University (GWU) Vegetation Model to determine the C band backscattering coefficients of the individual stands for VV polarization. The model results show that backscatter at C band comes mainly from the needles and small branches and the upper portion of the trunks acts only as an attenuator. A discussion of variation of backscatter with specie structure and how dielectric variations in needles for both species may affect the total backscatter returns is provided.

Lang, R. H.↗

Carbon cycling across ecosystem succession in a north temperate forest: Controls and management implications

Despite decades of progress, much remains unknown about successional trajectories of carbon (C) cycling in north temperate forests. Drivers and mechanisms of these changes, including the role of different types of disturbances, are particularly elusive. To address this gap, we synthesized decades of data from experimental chronosequences and long-term monitoring at a well-studied, regionally representative field site in northern Michigan, USA. Our study provides a comprehensive assessment of changes in above- and belowground ecosystem components over two centuries of succession, links temporal dynamics in C pools and fluxes with underlying drivers, and offers several conceptual insights to the field of forest ecology. Our first advance shows how temporal dynamics in some ecosystem components are consistent across severe disturbances that reset succession and partial disturbances that slightly modify it: both of these disturbance types increase soil N availability, alter fungal community composition, and alter growth and competitive interactions between short-lived pioneer and longer-lived tree taxa. Further, these changes in turn affect soil C stocks, respiratory emissions, and other belowground processes. Second, we show that some other ecosystem components have effects on C cycling that are not consistent over the course of succession. For example, canopy structure does not influence C uptake early in succession but becomes important as stands develop, and the importance of individual structural properties changes over the course of two centuries of stand development. Third, we show that in recent decades, climate change is masking or overriding the influence of community composition on C uptake, while respiratory emissions are sensitive to both climatic and compositional change. In synthesis, we emphasize that time is not a driver of C cycling; it is a dimension within which ecosystem drivers such as canopy structure, tree and microbial community composition change. Changes in those drivers, not in forest age, are what control forest C trajectories, and those changes can happen quickly or slowly, through natural processes or deliberate intervention. Stemming from this view and a whole-ecosystem perspective on forest succession, we offer management applications from this work and assess its broader relevance to understanding long-term change in other north temperate forest ecosystems.

54 ENVIRONMENTAL SCIENCES↗

Crown damage and the mortality of tropical trees

Summary What causes individual tree death in tropical forests remains a major gap in our understanding of the biology of tropical trees and leads to significant uncertainty in predicting global carbon cycle dynamics. We measured individual characteristics (diameter at breast height, wood density, growth rate, crown illumination and crown form) and environmental conditions (soil fertility and habitat suitability) for 26 425 trees ≥ 10 cm diameter at breast height belonging to 416 species in a 52‐ha plot in Lambir Hills National Park, Malaysia. We used structural equation models to investigate the relationships among the different factors and tree mortality. Crown form (a proxy for mechanical damage and other stresses) and prior growth were the two most important factors related to mortality. The effect of all variables on mortality (except habitat suitability) was substantially greater than expected by chance. Tree death is the result of interactions between factors, including direct and indirect effects. Crown form/damage and prior growth mediated most of the effect of tree size, wood density, fertility and habitat suitability on mortality. Large‐scale assessment of crown form or status may result in improved prediction of individual tree death at the landscape scale.

Arellano, Gabriel↗

Flame Synthesis Used to Create Metal-Catalyzed Carbon Nanotubes

Metal-catalyzed carbon nanotubes are highly ordered carbon structures of nanoscale dimensions. They may be thought of as hollow cylinders whose walls are formed by single atomic layers of graphite. Such cylinders may be composed of many nested, concentric atomic layers of carbon or only a single layer, the latter forming a single-walled carbon nanotube. This article reports unique results using a flame for their synthesis. Only recently were carbon nanotubes discovered within an arc discharge and recognized as fullerene derivatives. Today metal-catalyzed carbon nanotubes are of great interest for many reasons. They can be used as supports for the metal catalysts like those found in catalytic converters. Open-ended nanotubes are highly desirable because they can be filled by other elements, metals or gases, for battery and fuel cell applications. Because of their highly crystalline structure, they are significantly stronger than the commercial carbon fibers that are currently available (10 times as strong as steel but possessing one-sixth of the weight). This property makes them highly desirable for strengthening polymer and ceramic composite materials. Current methods of synthesizing carbon nanotubes include thermal pyrolysis of organometallics, laser ablation of metal targets within hydrocarbon atmospheres at high temperatures, and arc discharges. Each of these methods is costly, and it is unclear if they can be scaled for the commercial synthesis of carbon nanotubes. In contrast, flame synthesis is an economical means of bulk synthesis of a variety of aerosol materials such as carbon black. Flame synthesis of carbon nanotubes could potentially realize an economy of scale that would enable their use in common structural materials such as car-body panels. The top figure is a transmission electron micrograph of a multiwalled carbon nanotube. The image shows a cross section of the atomic structure of the nanotube. The dark lines are individual atomic layer planes of carbon, seen here in cross section. They form a nested series of concentric cylinders, much like the growth rings on a tree. This sample was obtained by the supported catalyst method, whereby the nanoscale catalysts are dispersed on a substrate providing their support. The substrate with catalyst particles was immersed within an acetylene diffusion flame to which nitrogen had been added to eliminate soot formation. Upon removal from the flame, the nanotubes were dispersed on a holder suitable for electron microscopy. Although not seen in the figure, the tube diameter reflects that of the catalyst particle.

VanderWal, Randy L.↗

Climate sensitive size-dependent survival in tropical trees

Survival rates of large trees determine forest biomass dynamics. Survival rates of small trees are linked to mechanisms that maintain biodiversity across tropical forests. How species survival rates change with size offers insight into the links between biodiversity and ecosystem function across tropical forests. We tested patterns of size-dependent tree survival across the tropics using data from 1781 species and over two million individuals to assess whether tropical forests can be characterized by size-dependent life-history survival strategies. We found species were classifiable into four “survival modes” that explain life-history variation that shapes carbon-cycling and the relative abundances within forests. Frequently collected functional traits, such as wood density, leaf mass per area, and seed mass, were not generally predictive of species’ survival modes. Mean annual temperature and cumulative water deficit predicted the proportion of biomass of survival modes, indicating important links between evolutionary strategies, climate, and carbon cycling. The application of survival modes in demographic simulations predicted biomass change across forest sites. Our results reveal globally identifiable size-dependent survival strategies that differ across diverse systems in a consistent way. The abundance of survival modes and interaction with climate ultimately determine forest structure, carbon storage in biomass, and future forest trajectories.

Johnson, Daniel J.↗

Microfibril orientation and compositional heterogeneity in fiber and vessel cell walls of poplar xylem studied by AFM-IR and SFG spectroscopy

Understanding the structural organization of cellulose microfibrils (CMFs) within individual plant cell walls is essential for connecting cell wall architecture to its mechanical and physiological functions. However, due to the complex hierarchical structure and nanoscale heterogeneity of cell walls, it remains technically challenging to resolve detailed compositional and orientational information at subcellular levels of individual cell walls. This study investigates the internal 3D structure, chemical composition, and sublayer organization of fiber and vessel cell walls in the xylem tissue of a two-year-old field-grown hybrid poplar tree (Populus alba × P. glandulosa) using photothermal atomic force microscopy coupled with infrared spectroscopy (AFM-IR) and sum frequency generation (SFG) hyperspectral microscopy. AFM-IR provided nanoscale chemical imaging, revealing localized compositional heterogeneity, including variations between adjacent cell walls and transitional layers beyond the traditional S1, S2, and S3 sublayers. SFG microscopy revealed that CMFs in fiber walls are highly aligned along the stem axis, consistent with their role in mechanical support, while vessel cell walls exhibited slightly tilted CMFs, reflecting their function in hydraulic transport. Together, these results offer new insights into cell-type-specific CMF organization and compositional gradients in hybrid poplar xylem. These findings highlight the structural and chemical complexity of secondary cell walls in woody plants and demonstrate the value of AFM-IR and SFG spectroscopy in elucidating plant cell wall architecture.

60 APPLIED LIFE SCIENCES↗

Sap flux measurements in wet tropical forests: unique challenges and opportunities

Tropical rainforests often have great tree species and functional diversity, complex age and stand structure, deep active sapwood, and potential factors that reduce transpiration, such as frequent cloud cover and wet leaves. Such factors generate challenges for estimating transpiration from sap flux measurements. In fact, upscaling approaches have rarely been attempted for diverse tropical forests. Thus, the objective of this paper is to build upon past efforts to scale transpiration and optimize strategies for wet tropical forests. Over a five-year period, we instrumented 44 trees with heat dissipation sap flow sensors within a premontane wet tropical rainforest in Costa Rica (5000 mm MAP). Given high diversity, few instrumented trees belonged to the same species, genus, or even family. In a subset of trees, radial profiles across the full range of active xylem were examined. Measurements were scaled to the stand in two plots using sapwood area. In association with extensive micrometeorological measurements, only ~10% of rainfall was transpired from this forested watershed due to persistent low radiation, evaporative demand, and frequent wet canopy conditions. Contrary to temperate trees, we observed minimal flow reductions in deeper sapwood among the largest trees, whose water use amounted to nearly 80% of the total stand water use, even though they contributed less than 15% to total stand basal area. We found that transpiration was suppressed when leaves were wet, even after accounting for lower vapor pressure deficit and reduced solar radiation. Since soil moisture conditions at this site remain continually above deficit levels, flow reversal has been assumed to be minor and thus has not yet been investigated. The driest month on record resulted in higher, not lower transpiration. Given the high diversity of these forests, herein we propose practical and innovate approaches to group trees by function or degree of canopy exposure. Finally, these efforts are critical for accurate scaling of measurements from individual sensors to stands and for improving global land surface models that increasingly partition canopy components to better represent these functionally and structurally diverse ecosystems.

54 ENVIRONMENTAL SCIENCES↗

Tallo: A global tree allometry and crown architecture database

Abstract Data capturing multiple axes of tree size and shape, such as a tree's stem diameter, height and crown size, underpin a wide range of ecological research—from developing and testing theory on forest structure and dynamics, to estimating forest carbon stocks and their uncertainties, and integrating remote sensing imagery into forest monitoring programmes. However, these data can be surprisingly hard to come by, particularly for certain regions of the world and for specific taxonomic groups, posing a real barrier to progress in these fields. To overcome this challenge, we developed the Tallo database, a collection of 498,838 georeferenced and taxonomically standardized records of individual trees for which stem diameter, height and/or crown radius have been measured. These data were collected at 61,856 globally distributed sites, spanning all major forested and non‐forested biomes. The majority of trees in the database are identified to species (88%), and collectively Tallo includes data for 5163 species distributed across 1453 genera and 187 plant families. The database is publicly archived under a CC‐BY 4.0 licence and can be access from: https://doi.org/10.5281/zenodo.6637599 . To demonstrate its value, here we present three case studies that highlight how the Tallo database can be used to address a range of theoretical and applied questions in ecology—from testing the predictions of metabolic scaling theory, to exploring the limits of tree allometric plasticity along environmental gradients and modelling global variation in maximum attainable tree height. In doing so, we provide a key resource for field ecologists, remote sensing researchers and the modelling community working together to better understand the role that trees play in regulating the terrestrial carbon cycle.

Jucker, Tommaso↗

Increased Occurrence of Large–Scale Windthrows Across the Amazon Basin

Convective storms with strong downdrafts create windthrows: snapped and uprooted trees that locally alter the structure, composition, and carbon balance of forests. Comparing Landsat imagery from subsequent years, we documented temporal and spatial variation in the occurrence of large (≥30 ha) windthrows across the Amazon basin from 1985 to 2020. Over 33 individual years, we detected 3179 large windthrows. Windthrow density was greatest in the central and western Amazon regions, with ~33% of all events occurring in ~3% of the monitored area. Return intervals for large windthrows in the same location of these “hotspot” regions are centuries to millennia, while over the rest of the Amazon they are >10,000 years. Our data demonstrate a nearly 4–fold increase in windthrow number and affected area between 1985 (78 windthrows and 6,900 ha) and 2020 (264 events and 32,170 ha), with more events of >500 ha size since 1990. Such extremely large events (>500 ha up to 2,543 ha) are responsible for interannual variation in the overall median (84 ± 5.2 ha; ±95% CI) and mean (147 ± 13 ha) windthrow area, but we did not find significant temporal trends in the size distribution of windthrows with time. Our results document increased damage from convective storms over the past 40 years in the Amazon, filling a gap in temporal records for tropical regions. Our publicly accessible large windthrow database provides a valuable tool for exploring dynamic conditions leading to damaging storms and their ecological impact on Amazon forests.

54 ENVIRONMENTAL SCIENCES↗

An Open-source Llm Enhanced-tool Specialized In Helping Moose Related Problems And Tasks

MOOSEenger is an open-source, terminal-first chat application for the MOOSE ecosystem that couples specialized parsing of MOOSE documentation and “.i” input files with retrieval-augmented generation to deliver grounded answers about multiphysics modeling and workflows. It includes dedicated readers for MOOSE-style HTML and a pyhit-based parser that uses the MOOSE syntax tree to preserve block structure and attach retrieval metadata. A data-ingestion pipeline performs semantic chunking into atomic facts and stores them hierarchically in a local Chroma vector database that maintains parent–child relationships across documents; the system can ingest directories, individual files, and single-page web content, and it provides CRUD operations (insert, update, delete) to manage the corpus. At query time, relevant chunks are embedded, retrieved, and fused into the model context, with interactive features such as token streaming, persistent chat history, and dynamic RAG (retrieval triggered by user input or intermediate model output). Deployment is flexible: MOOSEenger runs with local Ollama models or remote Hugging Face/OpenAI backends—typically coordinating generation, lightweight tagging/summarization, and embeddings across three models—and it also supports a server mode and integration with the VS Code Continue interface.

Li, Mengnan [Idaho National Laboratory (INL), Idah↗

ADAPT

The purpose of the ADAPT code is to generate Dynamic Event Trees (DET) using a user specified set of simulators. ADAPT can utilize any simulation tool which meets a minimal set of requirements. ADAPT is based on the concept of DET which uses explicit modeling of the deterministic dynamic processes that take place during a nuclear reactor plant system (or other complex system) evolution along with stochastic modeling. When DET are used to model various aspects of Probabilistic Risk Assessment (PRA), all accident progression scenarios starting from an initiating event are considered simultaneously. The DET branching occurs at user specified times and/or when an action is required by the system and/or the operator. These outcomes then decide how the dynamic system variables will evolve in time for each DET branch. Since two different outcomes at a DET branching may lead to completely different paths for system evolution, the next branching for these paths may occur not only at separate times, but can be based on different branching criteria. The computational infrastructure allows for flexibility in ADAPT to link with different system simulation codes, parallel processing of the scenarios under consideration, on-line scenario management (initiation as well as termination), analysis of results, and user friendly graphical capabilities. The ADAPT system is designed for a distributed computing environment; the scheduler can track multiple concurrent branches simultaneously. The scheduler is modularized so that the DET branching strategy can be modified (e.g. biasing towards the worst-case scenario/event). Independent database systems store data from the simulation tasks and the DET structure so that the event tree can be constructed and analyzed later. ADAPT is provided with a user-friendly client which can easily sort through and display the results of an experiment, precluding the need for the user to manually inspect individual simulator runs.

Reynolds, John↗

Quantifying Boreal Forest Structure and Composition Using UAV Structure from Motion

The vast extent and inaccessibility of boreal forest ecosystems are barriers to routine monitoring of forest structure and composition. In this research, we bridge the scale gap between intensive but sparse plot measurements and extensive remote sensing studies by collecting forest inventory variables at the plot scale using an unmanned aerial vehicle (UAV) and a structure from motion (SfM) approach. At 20 Forest Inventory and Analysis (FIA) subplots in interior Alaska, we acquired overlapping imagery and generated dense, 3D, RGB (red, green, blue) point clouds. We used these data to model forest type at the individual crown scale as well as subplot-scale tree density (TD), basal area (BA), and aboveground biomass (AGB). We achieved 85% cross-validation accuracy for five species at the crown level. Classification accuracy was maximized using three variables representing crown height, form, and color. Consistent with previous UAV-based studies, SfM point cloud data generated robust models of TD (r(sup 2) = 0.91), BA (r(sup 2) = 0.79), and AGB (r(sup 2) = 0.92), using a mix of plot- and crown-scale information. Precise estimation of TD required either segment counts or species information to differentiate black spruce from mixed white spruce plots. The accuracy of species-specific estimates of TD, BA, and AGB at the plot scale was somewhat variable, ranging from accurate estimates of black spruce TD (+/−1%) and aspen BA (−2%) to misallocation of aspen AGB (+118%) and white spruce AGB (−50%). These results convey the potential utility of SfM data for forest type discrimination in FIA plots and the remaining challenges to develop classification approaches for species-specific estimates at the plot scale that are more robust to segmentation error.

aboveground biomass↗

Advancing coupled fire-atmosphere research with HIGRAD/FIRETEC (w20_firetec) (CY 2021 Institutional Computing Annual Progress Report) [Slides]

LANL’s HIGRAD and FIRETEC models were used in a multi-scale simulation framework to investigate impacts of small-scale fuel heterogeneities on large-scale Pyro-Cb formation. Forest structural diversity is found to increase canopy fire spread, and thus risk of tree mortality in FIRETEC simulations. Structural diversity is associated with an increase in ladder fuels, which facilitate fire spread into the canopy. Low-intensity fire burning in marginal conditions is highly sensitive to small perturbation in atmospheric turbulence. These results highlight predictive limitations of individual fire simulations, and emphasize the need for ensemble simulations, especially for low-intensity, prescribed fire.

36 MATERIALS SCIENCE↗

Predicting biomass of hyperdiverse and structurally complex central Amazonian forests - a virtual approach using extensive field data

Notice on corrigendum: This paper has a corresponding corrigendum published. Please read the corrigendum first. Old-growth forests are subject to substantial changes in structure and species composition due to the intensification of human activities, gradual climate change and extreme weather events. Trees store ca. 90 % of the total aboveground biomass (AGB) in tropical forests and precise tree biomass estimation models are crucial for management and conservation. In the central Amazon, predicting AGB at large spatial scales is a challenging task due to the heterogeneity of successional stages, high tree species diversity and inherent variations in tree allometry and architecture. We parameterized generic AGB estimation models applicable across species and a wide range of structural and compositional variation related to species sorting into height layers as well as frequent natural disturbances. We used 727 trees (diameter at breast height ≥ 5 cm) from 101 genera and at least 135 species harvested in a contiguous forest near Manaus, Brazil. Sampling from this data set we assembled six scenarios designed to span existing gradients in floristic composition and size distribution in order to select models that best predict AGB at the landscape level across successional gradients. We found that good individual tree model fits do not necessarily translate into reliable predictions of AGB at the landscape level. When predicting AGB (dry mass) over scenarios using our different models and an available pantropical model, we observed systematic biases ranging from -31 % (pantropical) to +39 %, with root-mean-square error (RMSE) values of up to 130 Mg ha -1 (pantropical). Our first and second best models had both low mean biases (0.8 and 3.9 %, respectively) and RMSE (9.4 and 18.6 Mg ha -1 ) when applied over scenarios. Predicting biomass correctly at the landscape level in hyperdiverse and structurally complex tropical forests, especially allowing good performance at the margins of data availability for model construction/calibration, requires the inclusion of predictors that express inherent variations in species architecture. The model of interest should comprise the floristic composition and size-distribution variability of the target forest, implying that even generic global or pantropical biomass estimation models can lead to strong biases. Reliable biomass assessments for the Amazon basin (i.e., secondary forests) still depend on the collection of allometric data at the local/regional scale and forest inventories including species-specific attributes, which are often unavailable or estimated imprecisely in most regions.

54 ENVIRONMENTAL SCIENCES↗

Corrigendum to "Predicting biomass of hyperdiverse and structurally complex central Amazonian forests — a virtual approach using extensive field data" Published in Biogeosciences, 13, 1553-1570, 2016

Old-growth forests are subject to substantial changes in structure and species composition due to the intensification of human activities, gradual climate change and extreme weather events. Trees store ca. 90% of the total aboveground biomass (AGB) in tropical forests and precise tree biomass estimation models are crucial for management and conservation. In the central Amazon, predicting AGB at large spatial scales is a challenging task due to the heterogeneity of successional stages, high tree species diversity and inherent variations in tree allometry and architecture. We parameterized generic AGB estimation models applicable across species and a wide range of structural and compositional variation related to species sorting into height layers as well as frequent natural disturbances. We used 727 trees (diameter at breast height ≥5 cm) from 101 genera and at least 135 species harvested in a contiguous forest near Manaus, Brazil. Sampling from this data set we assembled six scenarios designed to span existing gradients in floristic composition and size distribution in order to select models that best predict AGB at the landscape level across successional gradients. We found that good individual tree model fits do not necessarily translate into reliable predictions of AGB at the landscape level. We observed systematic biases ranging from -31% (pantropical) to +39 %, with root-mean-square error (RMSE) values of up to 130-Mg ha -1 (pantropical), when predicting AGB (dry mass) over scenarios using our different models and an available pantropical model. Our first and second best models had both low mean biases (0.8 and 3.9 %, respectively) and RMSE (9.4 and 18.6 Mg ha -1 ) when applied over scenarios. Predicting biomass correctly at the landscape level in hyperdiverse and structurally complex tropical forests, especially allowing good performance at the margins of data availability for model construction/calibration, requires the inclusion of predictors that express inherent variations in species architecture. Furthermore, the model of interest should comprise the floristic composition and size-distribution variability of the target forest, implying that even generic global or pantropical biomass estimation models can lead to strong biases. Reliable biomass assessments for the Amazon basin (i.e., secondary forests) still depend on the collection of allometric data at the local/regional scale and forest inventories including species-specific attributes, which are often unavailable or estimated imprecisely in most regions.

54 ENVIRONMENTAL SCIENCES↗

Tropical Cyclone Ecology: A Scale-Link Perspective

Tropical cyclones are increasing in intensity and size and, thus, are poised to increase in importance as disturbance agents. Our understanding of cyclone ecology is biased towards the North Atlantic Basin, because cyclone effects do differ across oceanic basins. Cyclones have both short and long-term effects across the levels of biological organization, but we lack a scale-perspective of cyclone ecology. Effects on individual trees, such as defoliation or branch stripping and uprooting, are mechanistically linked to effects at the community and ecosystem levels, including forest productivity and stand regeneration time. Forest dwarfing via the gradual removal of taller trees by cyclones over many generations illustrates that cyclones shape forest structure through the accumulation of short-term effects over longer timescales.

54 ENVIRONMENTAL SCIENCES↗