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Foliar functional traits are widely used to characterize leaf and canopy properties that drive ecosystem processes and to infer physiological processes in Earth system models. Imaging spectroscopy provides great potential to map foliar traits to characterize continuous functional variation and diversity, but few studies have demonstrated consistent methods for mapping multiple traits across biomes.

With airborne imaging spectroscopy data and field data from 19 sites, we developed trait models using partial least squares regression, and mapped 26 foliar traits in seven NEON (National Ecological Observatory Network) ecoregions (domains) including temperate and subtropical forests and grasslands of eastern North America.

Model validation accuracy varied among traits (normalized root mean squared error, 9.1–19.4%; coefficient of determination, 0.28–0.82), with phenolic concentration, leaf mass per area and equivalent water thickness performing best across domains. Across all trait maps, 90% of vegetated pixels had reasonable values for one trait, and 28–81% provided high confidence for multiple traits concurrently.

Maps of 26 traits and their uncertainties for eastern US NEON sites are available for download, and are being expanded to the western United States and tundra/boreal zone. These data enable better understanding of trait variations and relationships over large areas, calibration of ecosystem models, and assessment of continental‐scale functional diversity.

 

Interactions between above- and below-ground monoculture forest plantation components are critical to tree growth and development. Within the Central Hardwoods Region (CHR), synergistic relationships between tree species and soil microbial community structure and function have received limited research attention. Soil microbes are integral to forest ecosystems as their activities intrinsically promote soil organic matter decomposition, nutrient cycling, and ecosystem functioning. Here, we examined soils from two perfectly aligned stands of black walnut (BW, Juglans nigra L.) and Northern red oak (RO, Quercus rubra L.) trees. Measurements of selected soil chemical properties, microbial community structure using ester-linked fatty acid methyl ester (EL-FAME), and soil enzyme activities (EAs) were used. Analysis of modifications within microbial communities showed a significant positive response to BW based upon soil EAs and microbial indicators, compared to RO. Seasonal comparisons predictably revealed higher microbial activities during summer. Fungi dominated the soil microbial community structure with a fungal/bacterial ratio of 2:1. Gram-positive rather than Gram-negative bacteria or actinomycetes dominated the bacterial community. The activity of the soil enzymes ß-glucosidase and arylsulfatase increased, but ß-glucosaminidase and acid phosphatase decreased. Additionally, acid phosphatase and arbuscular mycorrhizal fungi revealed strong correlations. The differences observed in biological properties, specifically microbial communities and EAs, highlight the varied responses to BW and RO soil biology and subsequent soil ecosystem functions. These results indicate that variations in microbial abundance and soil functions occur throughout the course of an entire year.

 

Basal area is a key measure of forest stocking and an important proxy of forest productivity in the face of climate change. Black walnut ( Juglans nigra ) is one of the most valuable timber species in North America. However, little is known about how the stocking of black walnut would change with differed bioclimatic conditions under climate change. In this study, we projected the current and future basal area of black walnut. We trained different machine learning models using more than 1.4 million tree records from 10,162 Forest Inventory and Analysis (FIA) sample plots and 42 spatially explicit bioclimate and other environmental attributes. We selected random forests (RF) as the final model to estimate the basal area of black walnut under climate change because RF had a higher coefficient of determination ( R 2 ), lower root mean square error (RMSE), and lower mean absolute error (MAE) than the other two models (XGBoost and linear regression). The most important variables to predict basal area were the mean annual temperature and precipitation, potential evapotranspiration, topology, and human footprint. Under two emission scenarios (Representative Concentration Pathway 4.5 and 8.5), the RF model projected that black walnut stocking would increase in the northern part of the current range in the USA by 2080, with a potential shift of species distribution range although uncertainty still exists due to unpredictable events, including extreme abiotic (heat, drought) and biotic (pests, disease) occurrences. Our models can be adapted to other hardwood tree species to predict tree changes in basal area based on future climate scenarios. 

Intensively managed forest plantations often require fertilization to maintain site fertility and to improve growth and yield over successive rotations. We applied urea-based “enhanced-efficiency fertilizers” (EEF) containing 0.5 atom% 15N at a rate of 224 kg N ha−1 to soils under mid-rotation black walnut (Juglans nigra L.) plantations to track the fate of applied 15N within aboveground ecosystem components during the 12-month period after application. Treatments included Agrotain Ultra (urea coated with a urease inhibitor), Arborite EC (urea coated with water-soluble boron and phosphate), Agrium ESN (polymer-coated urea), uncoated urea, and an unfertilized control. Agrotain Ultra and Arborite EC increased N concentrations of competing vegetation within one month after fertilization, while neither Agrium ESN nor uncoated urea had any effect on competing vegetation N concentrations during the experiment. Agrotain Ultra and Arborite EC increased δ15N values in leaves of crop trees above those of controls at one and two months after fertilization, respectively. By contrast, Agrium ESN and uncoated urea had no effect on δ15N values in leaves of crop trees until three months after fertilization. Fertilizer N recovery (FNR) varied among ecosystem components, with competing vegetation acting as a sink for applied nutrients. There were no significant differences in FNR for all the urea-based EEF products compared to uncoated urea. Agrium ESN was the only EEF that exhibited controlled-release activity in this study, with other fertilizers behaving similarly to uncoated urea. 

Abstract Plant hydraulics is key for plant survival and growth because it is linked to gas exchange and drought resistance. Although the environment influences plant hydraulics, there is no clear consensus on the effect of nitrogen (N) supply, which may be, in part, due to different hydraulic conductance normalization criteria and studied species. The objective of this study was to compare the variation of root hydraulic properties using several normalization criteria in four pine species in response to three contrasting N fertilization regimes. We studied four closely related, yet ecologically distinct species: Pinus nigra J.F. Arnold, Pinus pinaster Ait., Pinus pinea L. and Pinus halepensis Mill. Root hydraulic conductance (Kh) was measured with a high-pressure flow meter, and values were normalized by total leaf area (leaf specific conductance, Kl), xylem cross-section area (xylem specific conductance, Ks), total root area (root specific conductance, Kr) and the area of fine roots (fine root specific conductance, Kfr). Controlling for organ size differences allowed comparison of the hydraulic efficiency of roots to supply or absorb water among fertilization treatments and species. The effect of N on the root hydraulic efficiency depended on the normalization criteria. Increasing N availability reduced Kl and Ks, but increased Kh, Kr and especially Kfr. The positive effect of N on Kr and Kfr was positively related to seedling relative growth rate and was also consistent with published results at the interspecific level, whereby plant hydraulics is positively linked to photosynthesis and transpiration rate and fast growth. In contrast, normalization by leaf area and xylem cross-sectional area (Kl and Ks) reflected opposite responses to Kr and Kfr. This indicates that the normalization criteria determine the interpretation of the effect of N on plant hydraulics, which can limit species and treatment comparisons.