Geology topics

Sharon M. Hood

Publications and source records attributed to Sharon M. Hood.

9 recordsLinked to original sources

USGS2026

Basal area loss from fire using field-calibrated remote sensing refines western US fire severity measurements

The spatial patterns of fire effects and tree mortality have profound consequences for forest resilience. Cost-effective, medium-resolution, and spatiotemporally extensive fire severity measurements are essential for informing post-fire restoration and improving our understanding of wildfires—from forest stands to continents and from days to decades. Remote sensing advancements have improved burn severity mapping, but methods vary in interpretability, scalability, generalizability, and alignment with field measurements. One meaningful metric of fire effects on forests is proportion basal area loss, but existing methods are limited by a lack of region-specific field reference data and a scalable mapping framework. To address these issues, we compiled 3280 field reference plots from 123 fires in forests across the Western US to calculate the proportion of fire-induced basal area loss. We then used spatially cross-validated machine learning models with concurrent hyperparameter tuning to select a skillful, parsimonious model from a large candidate set of remotely-sensed, climatic, and topographic predictors. Spectral-only measures of severity over- or underestimated basal area loss in dry versus wet years and across aspects, demonstrating the value of incorporating climatic and topographic context. We also tested model performance on a separate holdout dataset in the Southwest US as a demonstration of reproducibility and transparency. We provide a Google Earth Engine tool for estimating proportional basal area loss for any fire perimeter in the Western US, enabling rapid map creation for land management and ecological modeling. All code, model parameters, and training data are released to support reproducibility, community adoption, regional refinement, and adaptation to new regions.

western United States↗

USGS2024

Drought before fire increases tree mortality after fire

Fire and drought are expected to increase in frequency and severity in temperate forests due to climate change. To evaluate whether drought increases the likelihood of post-fire tree mortality, we used a large database of tree survival and mortality from 32 years of wildland fires covering four dominant western North American conifers. We used Bayesian hierarchical modeling to predict the probability of individual tree mortality after fire based on species— Pinus contorta (lodgepole pine), Abies concolor (white fir), Pseudotsuga menziesii (Douglas-fir), and Pinus ponderosa (ponderosa pine)—bark thickness, bark char, percentage live tree crown scorched or consumed crown volume scorch (CVS), and mean annual climatic water deficit (CWD) anomalies the year pre-fire and fire year relative to the 1985–2015 reference period. Although crown injury was the primary determinant of tree mortality after fire, drought increased likelihood of death, with a 2-SD increase in CWD (+115.7) resulting in a 78% increase in the probability of mortality. We assessed the crown scorch level expected to result in >50% probability of mortality under different CWD scenarios: observed CWD, CWD of +2, and +4°C warming scenarios. Increased climatic moisture stress amplified tree death, reducing the threshold that causes tree mortality across all conifers under +4°C warming, with more subtle and species-specific reductions for the +2°C scenario. Models predicting post-fire tree mortality are components of global and regional carbon estimates, habitat suitability assessments, and forest management planning and decision support systems. The amplifying effects of drought on post-fire tree mortality and predicted future climates are likely to lead to higher tree mortality following fires in forested landscapes of western North America and may have cascading effects on ecosystem services and future forest resilience.

western United States↗

USGS2023

Increased whitebark pine (Pinus albicaulis) growth and defense under a warmer and regionally drier climate

Introduction: Tree defense characteristics play a crucial role in modulating conifer bark beetle interactions, and there is a growing body of literature investigating factors mediating tree growth and resin-based defenses in conifers. A subset of studies have looked at relationships between tree growth, resin duct morphology and climate; however, these studies are almost exclusively from lower-elevation, moisture-limited systems. The relationship between resin ducts and climate in higher-elevation, energy-limited ecosystems is currently poorly understood. Methods: In this study, we: (1) evaluated the relationship between biological trends in tree growth, resin duct anatomy, and climatic variability and (2) determined if tree growth and resin duct morphology of whitebark pine, a high-elevation conifer of management concern, is constrained by climate and/or regional drought conditions. Results: We found that high-elevation whitebark pine trees growing in an energy-limited system experienced increased growth and defense under warmer and regionally drier conditions, with climate variables explaining a substantive proportion of variation (∼20–31%) in tree diameter growth and resin duct anatomy. Discussion: Our results suggest that whitebark pine growth and defense was historically limited by short growing seasons in high-elevation environments; however, this relationship may change in the future with prolonged warming conditions.

Montana↗

USGS2022

Predictive accuracy of post-fire conifer death declines over time in models based on crown and bole injury

A key uncertainty of empirical models of post-fire tree mortality is understanding the drivers of elevated post-fire mortality several years following fire, known as delayed mortality. Delayed mortality can represent a substantial fraction of mortality, particularly for large trees that are a conservation focus in western US coniferous forests. Current post-fire tree mortality models have undergone limited evaluation of how injury level and time since fire interact to influence model accuracy and predictor variable importance. Less severe injuries potentially serve as an indicator for vulnerability to additional stressors such as bark beetle attack or moisture stress. We used a collection of 164,293 individual tree records to examine post-fire tree mortality in eight western USA conifers: Abies concolor , A. grandis , Calocedrus decurrens , Larix occidentalis , Pinus contorta , P. lambertiana , P. ponderosa , and Pseudotsuga menziesii . We evaluated the importance of fire injury predictors on discriminating between surviving trees versus immediate and delayed post-fire mortality. We fit balanced random forest models for each species using cumulative tree mortality from 1–5-years post-fire. We compared these results to multi-class random forest models using first-year mortality, 2–5-year mortality, and survival 5-years post-fire as a response variable. Crown volume scorched, diameter at breast height, and relative bark char height, were used as predictor variables. The cumulative mortality models all predicted trees that died within 1-year of fire with high accuracy but failed to predict 2–5-year mortality. The multi-class models were an improvement but had lower accuracy for predicting 2–5-year mortality. Multi-class model accuracies ranged from 85–95% across all species for predicting 1-year post-fire mortality, 42–71% for predicting 2–5-year mortality, and 64–85% for predicting trees that lived past 5-years. Our study highlights the differences in tree species tolerance to fire injury and suggests that including second-order predictors such as beetle attack or climatic water stress before and after fire will be critical to improve accuracy and better understand the mechanisms and patterns of fire-caused tree death. Random forest models have potential for management applications such as post-fire harvesting and simulating future stand dynamics.

western United States↗

USGS2021

Growth and defense characteristics of whitebark pine (Pinus albicaulis) and lodgepole pine (Pinus contorta var latifolia) in a high-elevation, disturbance-prone mixed-conifer forest in northwestern Montana, USA

Recent, widespread tree mortality in the western U.S. resulting from changes in climate, pathogens, insect activity, and forest management practices has led to concerns for many ecologically and culturally important species. Within conifers, resin-based defenses have long been recognized as a primary defense mechanism against a variety of insects and pathogens. Oleoresin produced by trees contain complex mixtures of terpenoids that have numerous insecticidal and fungicidal properties. Research has also identified links between resin duct characteristics and increased probability of survival during bark beetle outbreaks. Whitebark pine ( Pinus albicaulis ) is a culturally significant high elevation species that provides numerous ecological services within subalpine and alpine ecosystems. Whitebark pine has co-evolved with a suite of biotic and abiotic disturbances. Individual trees allocate resources towards growth and resin-based defenses, making it a good candidate species to evaluate growth and defense relationships and tradeoffs. In this study we compared constitutive resin chemistry, tree growth and resin duct anatomy between similarly aged whitebark and lodgepole pine ( P. contorta var latifolia ) growing in proximity within a disturbance-prone, mixed-conifer forest in northwestern Montana. These two host species have varying degrees of historical exposure to mountain pine beetle. Our research yields four important findings. First, we did not find evidence of a tradeoff between tree growth and tree defenses (resin duct morphology and resin chemistry). This suggests that trees growing under favorable field conditions can experience high growth rates and still allocate ample resources towards defense. Second, we found that resin ducts and constitutive mono- and sesqui- terpenes were not correlated in lodgepole pine while duct production and area were positively related to constitutive monoterpenes, and duct size and area were positively related to constitutive sesquiterpenes, in whitebark pine. The lack of distinct, consistent relationships between these defensive features suggests that both whitebark and lodgepole pine trees present beetles with numerous, complex combinations of resin-based defenses. Third, based on constitutive terpene profiles, bark beetles are more likely to enter lodgepole pine but more likely to successfully elicit mass attacks in whitebark pine, which agrees with beetle attack and success patterns observed in the field. Fourth, overstory competition, particularly by Engelmann spruce ( Picea engelmannii ), can influence tree defenses, specifically by reducing constitutive terpene concentrations in lodgepole and whitebark pine. Competitive tree interactions could lead to altered bark beetle-conifer interactions as host and nonhost species migrate in response to changing climate. Our results suggest that strategies designed to support whitebark pine populations can benefit from better understanding interactions among growth, competition and physical and chemical defenses in response to multiple disturbance.

Montana↗

USGS2020

A large database supports the use of simple models of post-fire tree mortality for thick-barked conifers, with less support for other species

Background Predictive models of post-fire tree and stem mortality are vital for management planning and understanding fire effects. Post-fire tree and stem mortality have been traditionally modeled as a simple empirical function of tree defenses ( e.g., bark thickness) and fire injury ( e.g., crown scorch). We used the Fire and Tree Mortality database (FTM)—which includes observations of tree mortality in obligate seeders and stem mortality in basal resprouting species from across the USA—to evaluate the accuracy of post-fire mortality models used in the First Order Fire Effects Model (FOFEM) software system. The basic model in FOFEM, the Ryan and Amman (R-A) model, uses bark thickness and percentage of crown volume scorched to predict post-fire mortality and can be applied to any species for which bark thickness can be calculated (184 species-level coefficients are included in the program). FOFEM (v6.7) also includes 38 species-specific tree mortality models (26 for gymnosperms, 12 for angiosperms), with unique predictors and coefficients. We assessed accuracy of the R-A model for 44 tree species and accuracy of 24 species-specific models for 13 species, using data from 93 438 tree-level observations and 351 fires that occurred from 1981 to 2016. Results For each model, we calculated performance statistics and provided an assessment of the representativeness of the evaluation data. We identified probability thresholds for which the model performed best, and the best thresholds with either ≥80% sensitivity or specificity. Of the 68 models evaluated, 43 had Area Under the Receiver Operating Characteristic Curve (AUC) values ≥0.80, indicating excellent performance, and 14 had AUCs <0.7, indicating poor performance. The R-A model often over-predicted mortality for angiosperms; 5 of 11 angiosperms had AUCs <0.7. For conifers, R-A over-predicted mortality for thin-barked species and for small diameter trees. The species-specific models had significantly higher AUCs than the R-A models for 10 of the 22 models, and five additional species-specific models had more balanced errors than R-A models, even though their AUCs were not significantly different or were significantly lower. Conclusions Approximately 75% of models tested had acceptable, excellent, or outstanding predictive ability. The models that performed poorly were primarily models predicting stem mortality of angiosperms or tree mortality of thin-barked conifers. This suggests that different approaches—such as different model forms, better estimates of bark thickness, and additional predictors—may be warranted for these taxa. Future data collection and research should target the geographical and taxonomic data gaps and poorly performing models identified in this study. Our evaluation of post-fire tree mortality models is the most comprehensive effort to date and allows users to have a clear understanding of the expected accuracy in predicting tree death from fire for 44 species.

Fire Ecology↗

USGS2020

The Fire and Tree Mortality Database, for empirical modeling of individual tree mortality after fire

Wildland fires have a multitude of ecological effects in forests, woodlands, and savannas across the globe. A major focus of past research has been on tree mortality from fire, as trees provide a vast range of biological services. We assembled a database of individual-tree records from prescribed fires and wildfires in the United States. The Fire and Tree Mortality (FTM) database includes records from 164,293 individual trees with records of fire injury (crown scorch, bole char, etc.), tree diameter, and either mortality or top-kill up to ten years post-fire. Data span 142 species and 62 genera, from 409 fires occurring from 1981-2016. Additional variables such as insect attack are included when available. The FTM database can be used to evaluate individual fire-caused mortality models for pre-fire planning and post-fire decision support, to develop improved models, and to explore general patterns of individual fire-induced tree death. The database can also be used to identify knowledge gaps that could be addressed in future research.

Scientific Data↗

USGS2019

Whitebark pine (Pinus albicaulis) growth and defense in response to mountain pine beetle outbreaks

Whitebark pine (Pinus albicaulis) is a critical forest species of Northern Rocky Mountain upper subalpine ecosystems, yet little is known about the physiological response of whitebark pine to disturbance (e.g. fire, bark beetles, and pathogens) across a range of diverse environmental gradients. Resin–based defenses have long been recognized as the primary mechanism by which conifers respond to attack by bark beetles and pathogens and several studies have linked resin duct properties to survivorship during periods of increased beetle activity. However, to our knowledge, no studies have compared axial resin ducts in the secondary xylem of whitebark pine across pairs of living and dead whitebark pine trees to better understand survivorship following multiple disturbances including mountain pine beetle and white pine blister rust. We found a clear distinction in growth and defense characteristics between live and dead whitebark pine. Across our study sites on the Flathead Indian Reservation in northwestern Montana, live whitebark pine produced larger resin ducts with a greater annual investment in resin–based defenses than whitebark pine that died. Resin duct size, duct area, and relative duct area were all greater in live whitebark pine (by 56%, 48%, and 57%, respectively) and these were the most important variables influencing whitebark pine survivorship. In contrast, whitebark pine that had died grew faster over time (22% larger ring widths) than their live counterparts and also produced more resin duct structures (20% more ducts on average). Whitebark pine at our study sites exhibit differing strategies in the allocation of resources toward growth and defense, with the majority of survivors of recent disturbance investing more in defensive structures than growth. Our results support the idea that maintaining genetic variability and the associated suite of differing physiological traits promotes diverse response strategies to a complex array of biophysical and biological stressors that might leave a species vulnerable to extinction across its range.

Northern Rocky Mountain↗

USGS2018

Fire and tree death: Understanding and improving modeling of fire-induced tree mortality

Each year wildland fires kill and injure trees on millions of forested hectares globally, affecting plant and animal biodiversity, carbon storage, hydrologic processes, and ecosystem services. The underlying mechanisms of fire-caused tree mortality remain poorly understood, however, limiting the ability to accurately predict mortality and develop robust modeling applications, especially under novel future climates. Virtually all post-fire tree mortality prediction systems are based on the same underlying empirical model described in Ryan and Reinhardt (1988 Can. J. For. Res. 18 1291–7), which was developed from a limited number of species, stretching model assumptions beyond intended limits. We review the current understanding of the mechanisms of fire-induced tree mortality, provide recommended standardized terminology, describe model applications and limitations, and conclude with key knowledge gaps and future directions for research. We suggest a two-pronged approach to future research: (1) continued improvements and evaluations of empirical models to quantify uncertainty and incorporate new regions and species and (2) acceleration of basic, physiological research on the proximate and ultimate causes of fire-induced tree mortality to incorporate processes of tree death into models. Advances in both empirical and process fire-induced tree modeling will allow creation of hybrid models that could advance understanding of how fire injures and kills trees, while improving prediction accuracy of fire-driven feedbacks on ecosystems and landscapes, particularly under novel future conditions.

Environmental Research Letters↗