The North American tree-ring fire-scar network

Fire regimes in North American forests are diverse and modern fire records are often too short to capture important patterns, trends, feedbacks, and drivers of variability. Tree-ring fire scars provide valuable perspectives on fire regimes, including centuries-long records of fire year, season, frequency, severity, and size. Here, we introduce the newly compiled North American tree-ring fire-scar network (NAFSN), which contains 2562 sites, >37,000 fire-scarred trees, and covers large parts of North America. We investigate the NAFSN in terms of geography, sample depth, vegetation, topography, climate, and human land use. Fire scars are found in most ecoregions, from boreal forests in northern Alaska and Canada to subtropical forests in southern Florida and Mexico. The network includes 91 tree species, but is dominated by gymnosperms in the genus Pinus. Fire scars are found from sea level to >4000-m elevation and across a range of topographic settings that vary by ecoregion. Multiple regions are densely sampled (e.g., >1000 fire-scarred trees), enabling new spatial analyses such as reconstructions of area burned. To demonstrate the potential of the network, we compared the climate space of the NAFSN to those of modern fires and forests; the NAFSN spans a climate space largely representative of the forested areas in North America, with notable gaps in warmer tropical climates. Modern fires are burning in similar climate spaces as historical fires, but disproportionately in warmer regions compared to the historical record, possibly related to under-sampling of warm subtropical forests or supporting observations of changing fire regimes. The historical influence of Indigenous and non-Indigenous human land use on fire regimes varies in space and time. A 20th century fire deficit associated with human activities is evident in many regions, yet fire regimes characterized by frequent surface fires are still active in some areas (e.g., Mexico and the southeastern United States). These analyses provide a foundation and framework for future studies using the hundreds of thousands of annually- to sub-annually-resolved tree-ring records of fire spanning centuries, which will further advance our understanding of the interactions among fire, climate, topography, vegetation, and humans across North America

Widespread Fire Years in Conifer Forests are Contingent on Both Winter and Monsoon Precipitation in the US-Mexico Sky Islands

The climate of the Southwestern United States and northwestern Mexico is marked by a bimodal precipitation regime with the majority of moisture arriving during (1) the cool season via intermittent frontal storm systems (November to February) and (2) intense, convective storms during the North American Monsoon (NAM) (July to September). Fire season in the region occurs primarily during the arid fore-summer in May and early June prior to the arrival of the NAM. Most long-term tree-ring based studies of fire-climatology in the region have evaluated only the role of winter precipitation. We used tree-ring width based reconstructions of both winter and monsoon precipitation, coupled with fire scar based tree-ring reconstructions of fire history from twelve mountain ranges in the US and Mexico at the northwestern margin of the NAM to quantify the historical role of both seasons of precipitation in modulating widespread fire years. Winter precipitation was the primary driver of widespread fire years in the region, but years with drought in both seasons had the highest fire frequency and most widespread fires. The timing and amount of monsoon precipitation can be important factors in ending the most severe fire weather conditions. Monsoon drought coupled with earlier snow melt in the spring appears to contribute to an extension of fire weather for longer periods, leading to more and larger fires

Trimming and Planing Rough-Cut Wood For Efficient Dendrochronological Sample Preparation and Storage

Wood samples larger than increment cores collected for tree-ring studies are often obtained using chainsaws and, less frequently, 2-person crosscut saws. Saw marks on cross-sectional wood samples can be quite deep and uneven, and sanding rough-cut wood cross-sections is inefficient in terms of processing time and wear on sanding belts. Trimming rough-cut wood samples with a band saw or treating with a surface planer creates a smoother initial surface for sample sanding and polishing. Sample trimming with a band saw or surface planer is also useful for post-analysis archiving and wood storage, when excess wood can be removed and smaller samples entered into storage. Band saw and surface planer safety techniques are also discussed

Widespread fire years in the US–Mexico Sky Islands are contingent on both winter and monsoon precipitation

The climate of the south-western United States and northern Mexico borderlands is marked by a bimodal precipitation regime with the majority of moisture arriving during the cool season via Pacific frontal storm systems, and intense convective storms during the North American Monsoon (NAM). The fire season occurs primarily during the arid foresummer in May and June, before the development of the NAM. Most tree-ring studies of fire climatology in the region have evaluated only the role of winter precipitation. We used tree-ring-width-based reconstructions of both winter and monsoon precipitation, coupled with fire scar reconstructions of fire history from mountain ranges in the US and Mexico, to quantify the historical role and interactions of both seasons of precipitation in modulating widespread fire years. Winter precipitation was the primary driver of widespread fire years in the region, but years with drought in both seasons had the highest fire frequency and most widespread fires. These relationships define a unique monsoon fire regime, in which the timing and amount of monsoon precipitation are important factors in limiting the length of fire season and regulating widespread fire years.Open access articleThis item from the UA Faculty Publications collection is made available by the University of Arizona with support from the University of Arizona Libraries. If you have questions, please contact us at [email protected]

Automation of tree‐ring detection and measurements using deep learning

Abstract Core samples from trees are a critical reservoir of ecological information, informing our understanding of past climates, as well as contemporary ecosystem responses to global change. Manual measurements of annual growth rings in trees are slow, labour‐intensive and subject to human bias, hindering the generation of big datasets. We present an alternative, neural network‐based implementation that automates detection and measurement of tree‐ring boundaries from coniferous species. We trained our Mask R‐CNN extensively on over 8000 manually annotated ring boundaries from microscope‐imaged Norway Spruce Picea abies increment cores. We assessed the performance of the trained model after post‐processing on real‐world data generated from our core processing pipeline. The CNN after post‐processing performed well, with recognition of over 98% of ring boundaries (recall) with a precision in detection of 96% when tested on real‐world data. Additionally, we have implemented automatic measurements based on minimum distance between rings. With minimal editing for missed ring detections, these measurements were 98% correlated with human measurements of the same samples. Tests on other three conifer species demonstrate that the CNN generalizes well to other species with similar structure. We demonstrate the efficacy of automating the measurement of growth increment in tree core samples. Our CNN‐based system provides high predictive performance in terms of both tree‐ring detection and growth rate determination. Our application is readily deployable as a Docker container and requires only basic command line skills. Additionally, an easy re‐training option allows users to expand capabilities to other wood types. Application outputs include both editable annotations of predictions as well as ring‐width measurements in a commonly used .pos format, facilitating the efficient generation of large ring‐width measurement datasets from increment core samples, an important source of environmental data

Fusing tree-ring and forest inventory data to infer influences on tree growth

Better understanding and prediction of tree growth is important because of the many ecosystem services provided by forests and the uncertainty surrounding how forests will respond to anthropogenic climate change. With the ultimate goal of improving models of forest dynamics, here we construct a statistical model that combines complementary data sources, tree-ring and forest inventory data. A Bayesian hierarchical model was used to gain inference on the effects of many factors on tree growth-individual tree size, climate, biophysical conditions, stand-level competitive environment, tree-level canopy status, and forest management treatments-using both diameter at breast height (dbh) and tree-ring data. The model consists of two multiple regression models, one each for the two data sources, linked via a constant of proportionality between coefficients that are found in parallel in the two regressions. This model was applied to a data set of similar to 130 increment cores and similar to 500 repeat measurements of dbh at a single site in the Jemez Mountains of north-central New Mexico, USA. The tree-ring data serve as the only source of information on how annual growth responds to climate variation, whereas both data types inform non-climatic effects on growth. Inferences from the model included positive effects on growth of seasonal precipitation, wetness index, and height ratio, and negative effects of dbh, seasonal temperature, southerly aspect and radiation, and plot basal area. Climatic effects inferred by the model were confirmed by a den-droclimatic analysis. Combining the two data sources substantially reduced uncertainty about non-climate fixed effects on radial increments. This demonstrates that forest inventory data measured on many trees, combined with tree-ring data developed for a small number of trees, can be used to quantify and parse multiple influences on absolute tree growth. We highlight the kinds of research questions that can be addressed by combining the high-resolution information on climate effects contained in tree rings with the rich tree-and stand-level information found in forest inventories, including projection of tree growth under future climate scenarios, carbon accounting, and investigation of management actions aimed at increasing forest resilience.College of Science, University of Arizona; USDA-AFRI Grant [2016-67003-24944]; EU Horizon Project "BACI" [640176]; Swiss National Science Foundation [P300P2_154543]Open Access Journal.This item from the UA Faculty Publications collection is made available by the University of Arizona with support from the University of Arizona Libraries. If you have questions, please contact us at [email protected]

Wild Apple Growth and Climate Change in Southeast Kazakhstan

Wild populations of Malus sieversii [Ldb.] M. Roem are valued genetic and watershed resources in Inner Eurasia. These populations are located in a region that has experienced rapid and on-going climatic change over the past several decades. We assess relationships between climate variables and wild apple radial growth with dendroclimatological techniques to understand the potential of a changing climate to influence apple radial growth. Ring-width chronologies spanning 48 to 129 years were developed from 12 plots in the Trans-Ili Alatau and Jungar Alatau ranges of Tian Shan Mountains, southeastern Kazakhstan. Cluster analysis of the plot-level chronologies suggests different temporal patterns of growth variability over the last century in the two mountain ranges studied. Changes in the periodicity of annual ring-width variability occurred ca. 1970 at both mountain ranges, with decadal-scale variability supplanted by quasi-biennial variation. Seascorr correlation analysis of primary and secondary weather variables identified negative growth associations with spring precipitation and positive associations with cooler fall-winter temperatures, but the relative importance of these relationships varied spatially and temporally, with a shift in the relative importance of spring precipitation ca. 1970 at Trans-Ili Alatau. Altered apple tree radial growth patterns correspond to altered climatology in the Lake Balkhash Basin driven by unprecedented intensified Arctic Oscillations after the late 1970s.Science Committee of Ministry of Education and Science of Republic of Kazakhstan [217, 4165/GF4]; U.S. Forest Service, Rocky Mountain Research Station Research Joint Venture Agreement [12-JV-11221633-161]; University of ArizonaOpen Access Journal.This item from the UA Faculty Publications collection is made available by the University of Arizona with support from the University of Arizona Libraries. If you have questions, please contact us at [email protected]

Ecological Forecasting of Tree Growth: Regional Fusion of Tree-ring and Forest Inventory Data to Quantify Drivers and Characterize Uncertainty

Robust ecological forecasting of tree growth under future climate conditions is critical to anticipate future forest carbon storage and flux. Here, we apply three ingredients of ecological forecasting that are key to improving forecast skill: data fusion, confronting model predictions with new data, and partitioning forecast uncertainty. Specifically, we present the first fusion of tree-ring and forest inventory data within a Bayesian state-space model at a multi-site, regional scale, focusing on Pinus ponderosa var. brachyptera in the southwestern US. Leveraging the complementarity of these two data sources, we parsed the ecological complexity of tree growth into the effects of climate, tree size, stand density, site quality, and their interactions, and quantified uncertainties associated with these effects. New measurements of trees, an ongoing process in forest inventories, were used to confront forecasts of tree diameter with observations, and evaluate alternative tree growth models. We forecasted tree diameter and increment in response to an ensemble of climate change projections, and separated forecast uncertainty into four different causes: initial conditions, parameters, climate drivers, and process error. We found a strong negative effect of fall–spring maximum temperature, and a positive effect of water-year precipitation on tree growth. Furthermore, tree vulnerability to climate stress increases with greater competition, with tree size, and at poor sites. Under future climate scenarios, we forecast increment declines of 22%–117%, while the combined effect of climate and size-related trends results in a 56%–91% decline. Partitioning of forecast uncertainty showed that diameter forecast uncertainty is primarily caused by parameter and initial conditions uncertainty, but increment forecast uncertainty is mostly caused by process error and climate driver uncertainty. This fusion of tree-ring and forest inventory data lays the foundation for robust ecological forecasting of aboveground biomass and carbon accounting at tree, plot, and regional scales, including iterative improvement of model skill

The North American tree‐ring fire‐scar network

Abstract Fire regimes in North American forests are diverse and modern fire records are often too short to capture important patterns, trends, feedbacks, and drivers of variability. Tree‐ring fire scars provide valuable perspectives on fire regimes, including centuries‐long records of fire year, season, frequency, severity, and size. Here, we introduce the newly compiled North American tree‐ring fire‐scar network (NAFSN), which contains 2562 sites, >37,000 fire‐scarred trees, and covers large parts of North America. We investigate the NAFSN in terms of geography, sample depth, vegetation, topography, climate, and human land use. Fire scars are found in most ecoregions, from boreal forests in northern Alaska and Canada to subtropical forests in southern Florida and Mexico. The network includes 91 tree species, but is dominated by gymnosperms in the genus Pinus. Fire scars are found from sea level to >4000‐m elevation and across a range of topographic settings that vary by ecoregion. Multiple regions are densely sampled (e.g., >1000 fire‐scarred trees), enabling new spatial analyses such as reconstructions of area burned. To demonstrate the potential of the network, we compared the climate space of the NAFSN to those of modern fires and forests; the NAFSN spans a climate space largely representative of the forested areas in North America, with notable gaps in warmer tropical climates. Modern fires are burning in similar climate spaces as historical fires, but disproportionately in warmer regions compared to the historical record, possibly related to under‐sampling of warm subtropical forests or supporting observations of changing fire regimes. The historical influence of Indigenous and non‐Indigenous human land use on fire regimes varies in space and time. A 20th century fire deficit associated with human activities is evident in many regions, yet fire regimes characterized by frequent surface fires are still active in some areas (e.g., Mexico and the southeastern United States). These analyses provide a foundation and framework for future studies using the hundreds of thousands of annually‐ to sub‐annually‐resolved tree‐ring records of fire spanning centuries, which will further advance our understanding of the interactions among fire, climate, topography, vegetation, and humans across North America