Browsing by Author "Cavender-Bares, Jeannine"
Now showing 1 - 20 of 25
- Results Per Page
- Sort Options
Item Canopy spectral reflectance detects oak wilt at the landscape scale using phylogenetic discrimination(2022-04-26) Sapes, Gerard; Lapadat, Cathleen; Schweiger, Anna K.; Juzwik, Jennifer; Montgomery, Rebecca; Gholizadeh, Hamed; Townsend, Philip A.; Gamon, John A.; Cavender-Bares, Jeannine; cavender@umn.edu; Cavender-Bares, JeannineThe oak wilt disease caused by the invasive fungal pathogen Bretziella fagacearum is one of the greatest threats to oak-dominated forests across the Eastern United States. Accurate detection and monitoring over large areas are necessary for management activities to effectively mitigate and prevent the spread of oak wilt. Canopy spectral reflectance contains both phylogenetic and physiological information across the visible near-infrared (VNIR) and short-wave infrared (SWIR) ranges that can be used to identify diseased red oaks. We develop partial least square discriminant analysis (PLS-DA) models using airborne hyperspectral reflectance to detect diseased canopies and assess the importance of VNIR, SWIR, phylogeny, and physiology for oak wilt detection. We achieve high ac- curacy through a three-step phylogenetic process in which we first distinguish oaks from other species (90% accuracy), then red oaks from white oaks (Quercus macrocarpa) (93% accuracy), and, lastly, infected from non- infected trees (80% accuracy). Including SWIR wavelengths increased model accuracy by ca. 20% relative to models based on VIS-NIR wavelengths alone; using a phylogenetic approach also increased model accuracy by ca. 20% over a single-step classification. SWIR wavelengths include spectral information important in differentiating red oaks from other species and in distinguishing diseased red oaks from healthy red oaks. We determined the most important wavelengths to identify oak species, red oaks, and diseased red oaks. We also demonstrated that several multispectral indices associated with physiological decline can detect differences between healthy and diseased trees. The wavelengths in these indices also tended to be among the most important wavelengths for disease detection within PLS-DA models, indicating a convergence of the methods. Indices were most significant for detecting oak wilt during late August, especially those associated with canopy photosynthetic activity and water status. Our study suggests that coupling phylogenetics, physiology, and canopy spectral reflectance pro- vides an interdisciplinary and comprehensive approach that enables detection of forest diseases at large scales. These results have potential for direct application by forest managers for detection to initiate actions to mitigate the disease and prevent pathogen spread.Item Content of leaf pigments of tree and grassland species collected at the Cedar Creek Ecosystem Science Reserve in 2015 and 2016(2020-09-01) Schweiger, Anna K; Fredericksen, Brett; Lapadat, Cathleen; Cavender-Bares, Jeannine; cavender@umn.edu; Cavender-Bares, JeannineThis data set contains the content of chlorophyll a, chlorophyll b, β-carotene, lutein, neoxanthin, violaxanthin, antheraxanthin and zeaxanthin pigments from tree and grassland species sampled at the Cedar Creek Ecosystem Science Reserve in East Bethel, MN. Mass- and area-based pigment contents were determined using high-performance liquid chromatography (HPLC). Data were collected as part of the Dimensions of Biodiversity project “Linking remotely sensed optical diversity to genetic, phylogenetic and functional diversity to predict ecosystem processes”. Samples were collected in or near the old fields chronosequence, the oak savanna, and the Forest and Biodiversity Experiment (FAB 1) plots. We used this data together with leaf-level spectral measurements to build partial least squares regression (PLSR) models for predicting leaf traits from spectra.Item Data and Code for Mechanistic links between physiology and spectral reflectance enable pre-visual detection of oak wilt and drought stress(2024-01-04) Sapes, Gerard; Schroeder, Lucy; Scott, Allison; Clark, Isaiah; Juzwik, Jennifer; Montgomery, Rebecca; Guzman Q., J. Antonio; Cavender-Bares, Jeannine; gsapes@ufl.edu; Sapes, Gerard; University of Minnesota; University of Florida; Northern Research Station, USDA Forest ServiceTree mortality due to global change-including range expansion of invasive pests and pathogens- is a paramount threat to forest ecosystems. Oak forests are among the most prevalent and valuable ecosystems both ecologically and economically in the United States. There is increasing interest in monitoring oak decline and death due to both drought and the oak wilt pathogen (Bretziella fagacearum). We combined anatomical and ecophysiological measurements with spectroscopy at leaf, canopy, and airborne levels to enable differentiation of oak wilt and drought, and detection prior to visible symptom appearance. We performed an outdoor potted experiment with Quercus rubra saplings subjected to drought stress and/or artificially inoculated with the pathogen to detect and distinguish both types of stressors. We also performed a field experiment where we validated the capacity of spectral reflectance models to predict physiological status and distinguish oak wilt from healthy trees. The data and code provided here address these goals.Item Data and code for remote spectral detection of biodiversity effects on forest biomass(2020-08-26) Williams, Laura J; Cavender-Bares, Jeannine; Townsend, Philip A; Couture, John J; Wang, Zhihui; Stefanski, Artur; Messier, Christian; Reich, Peter B; will3972@umn.edu; Williams, Laura JQuantifying how biodiversity affects ecosystem functions through time over large spatial extents is needed to meet global biodiversity goals yet is infeasible with field-based approaches alone. Imaging spectroscopy is a tool with potential to help address this challenge. In this study, we demonstrated a spectral approach to assess biodiversity effects in young forests that provides insight into its underlying drivers and could potentially be applied at large spatial scales. Using airborne imaging (NASA AVIRIS-NG) of a tree diversity experiment (IDENT-Cloquet in Cloquet, MN), spectral differences among plots enabled us to quantify net biodiversity effects on stem biomass and canopy nitrogen. In this repository, we present the spectral data and field data along with spectral model coefficients and example code for fitting and applying spectral models to calculate spectral biodiversity effects.Item Data and code for spectral canopy transmittance in diverse tree communities(2024-12-02) Williams, Laura J.; Kovach, Kyle R.; Guzman Q., J. Antonio; Stefanski, Artur; Bermudez, Raimundo; Butler, Ethan E.; Glenn-Stone, Catherine; Hajek, Peter; Klama, Johanna; Moradi, Aboubakr; Park, Maria H.; Scherer-Lorenzen, Michael; Townsend, Philip A.; Reich, Peter B.; Cavender-Bares, Jeannine; Schuman, Meredith C.; laura.williams@westernsydney.edu.au; Williams, LauraLight may shape forest function not only as a source of energy or a cause of stress but also as a context cue: plant photoreceptors can detect specific wavelengths of light, and plants use this information to assess their neighborhoods and adjust their patterns of growth and allocation. Here, we examined how the spectral profile of light (350-2200 nm) transmitted through tree canopies differs among communities within three tree diversity experiments on two continents (200 plots each planted with one to 12 tree species). This dataset includes data and metadata on canopy transmittance and leaf area index (LAI) measured on these plots as well as leaf-level transmittance measured for each species in monoculture plots. Data processing code and example analysis code are also provided.Item Data set used in publication titled: All the light we cannot see: Climate manipulations leave short and long-term imprints in spectral reflectance of trees(2024-12-10) Stefanski, Artur; Butler, Ethan B.; Williams, Laura J.; Bermudez, Raimundo; Guzman, J. Antonio; Larson, Andrew; Townsend, Philip A.; Montgomery, Rebecca A.; Cavender-Bares, Jeannine; Reich, Peter B.; astefans@uwsp.edu; Stefanski, Artur; ASCENDAnthropogenic climate change, particularly changes in temperature and precipitation, affects plants in multiple ways. Because plants respond dynamically to stress and acclimate to changes in growing conditions, diagnosing quantitative plant-environment relationships is a major challenge. One approach to this problem is to quantify leaf responses using spectral reflectance, which provides rapid, inexpensive, and nondestructive measurements that capture a wealth of information about genotype as well as phenotypic responses to the environment. However, it is unclear how warming, and drought affect spectra. To address this gap, we used an open-air field experiment that manipulates temperature and rainfall in 36 plots at two sites in the boreal-temperate ecotone of northern Minnesota, USA. We collected leaf spectral reflectance (400-2400 nm) at the peak of the growing season for three consecutive years on juveniles (two to six years old) of five tree species planted within the experiment. We hypothesized that these mid-season measurements of spectral reflectance capture a snapshot of the leaf phenotype encompassing a suite of physiological, structural, and biochemical responses to both long- and short-time scale environmental conditions. We show that the imprint of environmental conditions experienced by plants hours to weeks before spectral measurements is linked to regions in the spectrum associated with stress, namely the water absorption regions of the near-infrared and shortwave infrared. In contrast, the environmental conditions plants experience during leaf development leave lasting imprints on the spectral profiles of leaves, attributable to leaf structure and chemistry (e.g., pigment content and associated ratios). Our analyses show that after accounting for baseline species spectral differences, spectral responses to the environment do not differ among the species. This suggests that building a general framework for understanding forest responses to climate change through spectral metrics may be possible, likely having broader implications if the common responses among species detected here represent a widespread phenomenon. Consequently, these results demonstrate that examining the entire spectrum of leaf reflectance for environmental imprints in contrast to single features (e.g. indices and traits) improves inferences about plant-environment relationships, which is particularly important in times of unprecedented climate change.Item Do water limitation and species divergence affect physiological traits in Quercus oleoides?(2014-12) Schiffner, Sydney; Ramirez-Valiente, Jose A.; Cavender-Bares, JeannineItem Drought response strategies are coupled with leaf habit in 35 evergreen and deciduous oak (Quercus) species across a climatic gradient in the Americas(2022-04-19) Kaproth, Matthew A.; Fredericksen, Brett W.; González-Rodríguez, Antonio; Cavender-Bares, Jeannine; cavender@umn.edu; Cavender-Bares, Jeannine; Oaks of the Americas project• Survival strategies under contrasting environments often result from trade-offs in plant function. Adaptations to stress involve investment in resistance mechanisms that enhance survivorship but limit growth. We test the hypothesis that among the oaks (Quercus spp.) of the Americas some species will have greater drought resistance at the cost of reduced growth capacity. • We investigate trait variation in relation to native environments in species representing the major lineages within the oak phylogeny and test their response to three experimental water treatments. • Trade-offs between drought resistance strategies, such as osmolyte accumulation in leaves, and growth appear in all lineages, indicating both adaptation and evolutionary constraints in physiological traits. Species from mesic environments did not show evidence of faster growth or more resource-acquisitive traits. Xeric species had higher gas exchange rates despite lower stomatal pore area but did not have the capacity to increase growth in well-watered treatments. • Leaf habit plays an important role in drought resistance strategy. Evergreen species show drought tolerance or drought avoidance but require investment of resources like leaf solutes that limit growth under well-watered conditions. In contrast, deciduous species appear to follow a drought tolerance strategy, growing under all water treatments in spite of the risk. • The data included here was used to develop allometric equations to model growth for the study.Item Forests and Biodiversity cleaned biomass survey data 2013-2018(2021-02-12) Kothari, Shan; Montgomery, Rebecca A; Cavender-Bares, Jeannine; kotha020@umn.edu; Kothari, Shan; University of Minnesota Cavender-Bares Lab; University of Minnesota Montgomery Lab; Cedar Creek Ecosystem Science ReserveThis dataset includes annual growth survey measurements from the Forests and Biodiversity 1 (e271) experiment at Cedar Creek Ecosystem Science Reserve in East Bethel, MN. The dataset also includes a script that allows users to reproduce the figures and statistics reported in the cited paper. This version of the dataset is specifically meant to support the inferences in that paper, rather than serving as the version of record. Please consult the Cedar Creek Data Catalog (https://www.cedarcreek.umn.edu/research/data) to find the authoritative version to be used for general purposes.Item Functional leaf and stem traits of the Oaks of the Americas(2020-06-26) Kaproth, Matthew A; Hahn, Marlene; Manos, Paul S; Hipp, Andrew L; González-Rodríguez, Antonio; Cavender-Bares, Jeannine; cavender@umn.edu; Cavender-Bares, Jeannine; Oaks of the Americas GroupLeaf and stem trait data: Measured interspecific variation of Quercus (L.) - totaling 15+ functional traits for 135* American oak species. Our goal was to hand-measure/characterize as many North American species as possible. Measurements include: (1) specific leaf area (SLA, mm2 mg), an important leaf economic spectrum (LES) trait associated with leaf lifespan, resource acquisition, and nutrient use (Wright et al., 2004; Reich, 2014), (2) perimeter per unit leaf area (PLA, cm−1), a leaf trait that increases with degree of lobing and decreases with leaf size and is associated with hydraulic conductance and boundary layer resistance for all species (Sack et al., 2003; Kaproth and Cavender‐Bares, 2016), (3) total length of major veins per area (cm−1), associated with leaf hydraulic function (Sack and Scoffoni, 2013), (4) leaf length (mm), (5) petiole length (mm), and (6) stem specific density (g·cm−3), associated with mechanical strength and drought tolerance (Cornelissen et al., 2003; Kunstler et al., 2015). Specimens from sunlit branches were pressed and dried alongside samples collected for herbarium specimens as part of the Oaks of the Americas Project (Hipp et al., 2018).Item Horticultural availability and homeowner preferences drive plant diversity and composition in urban yards(2019-12-30) Cavender-Bares, Jeannine; Padullés Cubino, Josep; Pearse, William D.; Hobbie, Sarah E.; Lange, A.J.; Knapp, Sonja; Nelson, Kristen C.; cavender@umn.edu; Cavender-Bares, Jeannine; Twin Cities Household Ecosystem ProjectUnderstanding the factors that influence biodiversity in urban areas is important for informing management efforts aimed at enhancing the ecosystem services in urban settings and curbing the spread of invasive introduced species. We determined the ecological and socioeconomic factors that influence patterns of plant richness, phylogenetic diversity and composition in 133 private household yards in the Minneapolis-Saint Paul Metropolitan area, Minnesota, USA. We compared the composition of spontaneously occurring plant species and those planted by homeowners with composition in natural areas (at the Cedar Creek Ecosystem Science Reserve) and in the horticulture pool of species available from commercial growers. Yard area and fertilizer frequency influenced species richness of the spontaneous species but expressed homeowner values did not. In contrast, the criteria that homeowners articulated as important in their management decisions—including aesthetics, wildlife, neatness and food provision—significantly predicted cultivated species richness. Strikingly, the composition of plant species that people cultivated in their yards resembled the taxonomic and phylogenetic composition of species available commercially. In contrast, the taxonomic and phylogenetic composition of spontaneous species showed high similarity to natural areas. The large fraction of introduced species that homeowners planted was a likely consequence of what was available for them to purchase. The study links the composition and diversity of yard flora to their natural and anthropogenic sources and sheds light on the human factors and values that influence the plant diversity in residential areas of a major urban system. Enhanced understanding of the influences of the sources of plants—both native and introduced—that enter urban systems and the human factors and values that influence their diversity is critical to identifying the levers to manage urban biodiversity and ecosystem services.Item Leaf and canopy spectra, symptom progression, and physiological data from experimental detection of oak wilt in oak seedlings(2019-04-26) Fallon, Beth; Yang, Anna; Nguyen, Cathleen; Armour, Isabella; Juzwik, Jennifer; Montgomery, Rebecca A.; Cavender-Bares, Jeannine; eafallon@gmail.com; Fallon, Beth; University of Minnesota, Department of Ecology, Evolution, and Behavior; University of Minnesota, Department of Forestry; US Forest Service Northern Research StationThese data were collected as part of an experimental effort to accurately detect oak wilt infections in oak seedlings using remote sensing tools and to differentiate that disease stress from other mechanisms of tree decline. Oak wilt disease causes rapid mortality in oaks in the central and eastern United States. Management of the disease requires early diagnosis and tree removal to prevent fungal spread. Hyperspectral tools provide a potential method of early remote diagnosis, but accurately differentiating oak wilt from other agents of oak decline is integral to effective management. We conducted experiments (2017 and 2018) on two year old seedlings of Quercus ellipsoidalis and Q. macrocarpa in which treatments were 1) maintained as healthy individuals, 2) subjected to chronic drought, or inoculated 3) stems with oak wilt fungus (Bretziella fagacearum, a fungal vascular wilt) or 4) leaves with bur oak blight fungus (Tubakia iowensis, a fungal leaf pathogen). We measured leaf and whole plant hyperspectral reflectance (350 to 2400nm, Spectra Vista HR 1024i spectroradiometer (Spectra Vista Corporation, New York, USA)), gas exchange (LI-6440XT with a leaf chamber fluorometer attachment (LI-COR Environmental, Nebraska, USA)), and tracked symptom development in repeated measures of seedlings over the course of each experiment. In 2018, we explicitly measured spectral reflectance and gas exchange on both symptomatic and green leaves, as available and we also measured collected thermal images of leaves twice during the experiment (2018 only).Item Leaf carbon and nitrogen content of tree and grassland species collected at the Cedar Creek Ecosystem Science Reserve in 2015 and 2016(2020-09-01) Schweiger, Anna K; Lapadat, Cathleen; Cavender-Bares, Jeannine; cavender@umn.edu; Cavender-Bares, JeannineThis data set contains carbon and nitrogen content from combustion–reduction elemental analysis (TruSpec CN Analyzer, LECO) from tree and grassland species sampled at the Cedar Creek Ecosystem Science Reserve in East Bethel, MN. Data were collected as part of the Dimensions of Biodiversity project “Linking remotely sensed optical diversity to genetic, phylogenetic and functional diversity to predict ecosystem processes”. Samples were collected in or near the old fields chronosequence, the oak savanna, and the Forest and Biodiversity Experiment (FAB 1) plots. We used this data together with leaf-level spectral measurements to build partial least squares regression (PLSR) models for predicting leaf traits from spectra.Item Leaf carbon fraction data from tree and grassland species collected at the Cedar Creek Ecosystem Science Reserve in 2015 and 2016(2020-08-12) Schweiger, Anna K; Lapadat, Cathleen; Kothari, Shan; Cavender-Bares, Jeannine; cavender@umn.edu; Cavender-Bares, JeannineThis data set contains results from carbon fraction analysis (Fiber Analyzer 200, ANKOM Technology), including non-structural carbohydrates, hemicellulose, cellulose, lignin, neutral detergent fiber, and acid detergent fiber contents in percent (%) from tree and grassland species sampled at the Cedar Creek Ecosystem Science Reserve in East Bethel, MN. The data was collected as part of the Dimensions of Biodiversity project “Linking remotely sensed optical diversity to genetic, phylogenetic and functional diversity to predict ecosystem processes”. Samples were collected in or near the old fields chronosequence, the oak savanna, and the Forest and Biodiversity Experiment (FAB 1) plots. We used this data together with leaf-level spectral measurements to build partial least squares regression (PLSR) models for predicting leaf traits from spectra.Item Leaf-level trade-offs between drought avoidance and desiccation recovery drive elevation stratification in arid oaks: site environmental data, individual tree stem and leaf physiological data, and analyses(2018-02-14) Fallon, Beth; Cavender-Bares, Jeannine; eafallon@umn.edu; Fallon, BethThis dataset and RStudio project includes all processed data, most raw data, and R scripts needed for analysis and figure construction included in the manuscript Fallon and J. Cavender-Bares 2018 (Fallon B. and J. Cavender-Bares. 2018. Leaf-level trade-offs between drought avoidance and desiccation recovery drive elevation stratification in arid oaks. Ecosphere. in press). We investigated whether oak species in the Chiricahua Mountains were 1) elevationally stratified, 2) whether that stratification was correlated with temperature minima, maxima, and water availability, 3) if physiological tolerances to freezing or drought stress correlated with elevation ranges, and 4) if traits important to local (elevation) distributions were correlated with climatic values of the wider species ranges. Data were collected at field sites from wild, adult trees in the Chiricahua Mountains, Arizona, USA from 2014-2015.This research was done with funding to B. Fallon from the Southwestern Research Station (SWRS, American Museum of Natural History), the University of Minnesota Charles J. Brand, Carolyn Crosby, and Dayton Bell Fellowships, and the Department of Plant and Microbial Biology. Additional funding was provided by NSF Award 1146380 (J. Cavender-Bares PI). We performed all data collection under permit with the Coronado National Forest, Douglas Ranger District, managed by the United States Forest Service (USDA).Item Light access and leaf trait variation within and among tree species across diverse mixtures within a common garden(2019-11-05) Williams, Laura J; Cavender-Bares, Jeannine; Reich, Peter B; Paquette, Alain; Messier, Christian; will3972@umn.edu; Williams, Laura JThis dataset includes trait measurements for 2615 leaves of common temperate-boreal tree species alongside estimates of their light access. Trait values affect how plants function, with consequences that propagate through scales of ecological organization to affect ecosystem function. However, the pathway connecting trait expression to ecosystem function is complicated by feedbacks: trait expression may vary within species in response to community diversity, and trait expression also determines a community’s functional diversity. In this study, we quantify the extent to which light access – which past studies suggest affects trait expression and differs as a result of interactions among plants – differs consistently with community diversity and explains intraspecific trait variation in trees. In a common garden, trees of five angiosperm and seven gymnosperm species were planted to form 37 communities ranging widely in species and functional diversity whereby confounding environmental variation was minimized. We sampled leaves of each species to characterize intraspecific variation within crowns, among trees within communities, and among communities in three traits – leaf size, specific leaf area and nitrogen concentration – and estimated each leaf’s access to light.Item Mapping oak wilt disease from space using land surface phenology(Remote Sensing of Environment, 2023-12-01) Guzmán, Jose A; Pinto-Ledezma, Jesús N; Frantz, David; Townsend, Philip A; Juzwik, Jennifer; Cavender-Bares, JeannineProtecting the future of forests relies on our ability to observe changes in forest health. Thus, developing tools for sensing diseases in a timely fashion is critical for managing threats at broad scales. Oak wilt —a disease caused by a pathogenic fungus (Bretziella fagacearum)— is threatening oaks, killing thousands yearly while negatively impacting the ecosystem services they provide. Here we propose a novel workflow for mapping oak wilt by targeting temporal disease progression through symptoms using land surface phenology (LSP) from spaceborne observations. By doing so, we hypothesize that phenological changes in pigments and photosynthetic activity of trees affected by oak wilt can be tracked using LSP metrics derived from the Chlorophyll/Carotenoid Index (CCI). We used dense time-series observations from Sentinel-2 to create Analysis Ready Data across Minnesota and Wisconsin and to derive three LSP metrics: the value of CCI at the start and end of the growing season, and the coefficient of variation of the CCI during the growing season. We integrate high-resolution airborne imagery in multiple locations to select pixels (n = 3872) from the most common oak tree health conditions: healthy, symptomatic for oak wilt, and dead. These pixels were used to train an iterative Partial Least Square Discriminant (PLSD) model and derive the probability of an oak tree (i.e., pixel) in one of these conditions and the associated uncertainty. We assessed these models spatially and temporally on testing datasets revealing that it is feasible to discriminate among the three health conditions with overall accuracy between 80 and 82%. Within conditions, our models suggest that spatial variations among three CCI-derived LSP metrics can identify healthy (Area Under the Curve (AUC) = 0.98), symptomatic (AUC = 0.89), and dead (AUC = 0.94) oak trees with low false positive rates. The model performance was robust across different years as well. The predictive maps were used to guide local stakeholders to locate disease hotspots for ground verification and subsequent decision-making for treatment. Our results highlight the capabilities of LSP metrics from dense spaceborne observations to map diseases and to monitor large-scale change in biodiversity.Item Mechanistic links between physiology and spectral reflectance enable pre-visual detection of oak wilt and drought stress(Proceedings of the National Academy of Sciences, 2024-02) Sapes, Gerard; Schroeder, Lucy; Scott, Allison; Clark, Isaiah; Juzwik, Jennifer; Montgomery, Rebecca; Guzmán Q., J. Antonio; Cavender-Bares, JeannineTree mortality due to global change—including range expansion of invasive pests and pathogens—is a paramount threat to forest ecosystems. Oak forests are among the most prevalent and valuable ecosystems both ecologically and economically in the United States. There is increasing interest in monitoring oak decline and death due to both drought and the oak wilt pathogen (Bretziella fagacearum). We combined anatomical and ecophysiological measurements with spectroscopy at leaf, canopy, and airborne levels to enable differentiation of oak wilt and drought, and detection prior to visible symptom appearance. We performed an outdoor potted experiment with Quercus rubra saplings subjected to drought stress and/or artificially inoculated with the pathogen. Models developed from spectral reflectance accurately predicted ecophysiological indicators of oak wilt and drought decline in both potted and field experiments with naturally grown saplings. Both oak wilt and drought resulted in blocked water transport through xylem conduits. However, oak wilt impaired conduits in localized regions of the xylem due to formation of tyloses instead of emboli. The localized tylose formation resulted in more variable canopy photosynthesis and water content in diseased trees than drought-stressed ones. Reflectance signatures of plant photosynthesis, water content and cellular damage detected oak wilt and drought 13 days before visual symptoms appeared. Our results show that leaf spectral reflectance models predict ecophysiological processes relevant to detection and differentiation of disease and drought. Coupling spectral models that detect physiological change with spatial information enhances capacity to differentiate plant stress types such as oak wilt and drought.Item Models for: Reflectance spectroscopy allows rapid, accurate, and non-destructive estimates of functional traits from pressed leaves(2022-06-23) Kothari, Shan; Beauchamp-Rioux, Rosalie; Laliberté, Etienne; Cavender-Bares, Jeannine; cavender@umn.edu; Cavender-Bares, Jeannine; ASCEND BII, Canadian Airborne Biodiversity ObservatoryMore than ever, ecologists seek to employ herbarium collections to estimate plant functional traits from the past and across biomes. However, many trait measurements are destructive, which may preclude their use on valuable specimens. Researchers increasingly use reflectance spectroscopy to estimate traits from fresh or ground leaves, and to delimit or identify taxa. Here, we extend this body of work to non-destructive measurements on pressed, intact leaves, like those in herbarium collections. Using 618 samples from 68 species, we used partial least-squares regression to build models linking pressed-leaf reflectance spectra to a broad suite of traits, including leaf mass per area (LMA), leaf dry matter content (LDMC), equivalent water thickness, carbon fractions, pigments, and twelve elements. We compared these models to those trained on fresh- or ground-leaf spectra of the same samples. Here, we present the model coefficients and a README that provides examples of how to apply them to other data.Item Natural selection and neutral evolutionary processes contribute to genetic divergence in leaf traits across a precipitation gradient in the tropical oak Quercus oleoides(2018-02-28) Ramírez-Valiente, José A.; Deacon, Nicholas J.; Etterson, Julie; Center, Alyson; Sparks, Jed P.; Sparks, Kimberlee L.; Longwell, Timothy; Pilz, George; Cavender-Bares, Jeannine; cavender@umn.edu; Cavender-Bares, Jeannine; LOARD: Live Oak Adaptation and Response to Drought projectThe impacts of drought are expanding worldwide as a consequence of climate change. However, there is still little knowledge of how species respond to long-term selection in seasonally-dry ecosystems. In this study, we used QST-FST comparisons to investigate (i) the role of natural selection on population genetic differentiation for a set of functional traits related to drought resistance in the seasonally-dry tropical oak Quercus oleoides and (ii) the influence of water availability at the site of population origin and in experimental treatments on patterns of trait divergence. We conducted a thorough phenotypic characterization of 1896 seedlings from ten populations growing in field and greenhouse common gardens under replicated watering treatments. We also genotyped 222 individuals from the same set of populations using eleven nuclear microsatellites. The data sets include all of the raw data used in the analyses include nuclear microsatellites from populations examined in the field common garden, phenotypic data from a field common garden, nuclear microsatellites from populations examined in a greenhouse experiment, and phenotypic data from a field common garden.