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  1. Functional balance theory predicts that plants will allocate less carbon belowground when the availability of nutrients is elevated. We tested this prediction in two successional northern hardwood forest stands by quantifying fine root biomass and growth after 5–7 years of treatment in a nitrogen (N) x phosphorus (P) factorial addition experiment. We quantified root responses at two different levels of treatment: the whole-plot scale fertilization and small-patch scale fertilization of ingrowth cores. Fine root biomass was higher in plots receiving P, and fine root growth was highest in plots receiving both N and P. Thus, belowground productivity did not decrease in response to long-term addition of nutrients. We did not find conclusive evidence that elevated availability of one nutrient at the plot scale induced foraging for the other nutrient at the core scale, or that foraging for nutrients at the core scale responded to addition of limiting nutrients. Our observations suggest NP co-limitation of fine root growth and indicate complex interactions of N and P affecting aboveground and belowground production in early successional northern hardwood forest ecosystems. 
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    Free, publicly-accessible full text available January 1, 2025
  2. Inselsbacher, Erich (Ed.)
    Abstract

    Stomatal density, stomatal length and carbon isotope composition can all provide insights into environmental controls on photosynthesis and transpiration. Stomatal measurements can be time-consuming; it is therefore wise to consider efficient sampling schemes. Knowing the variance partitioning at different measurement levels (i.e., among stands, plots, trees, leaves and within leaves) can aid in making informed decisions around where to focus sampling effort. In this study, we explored the effects of nitrogen (N), phosphorus (P) and calcium silicate (CaSiO3) addition on stomatal density, length and carbon isotope composition (δ13C) of sugar maple (Acer saccharum Marsh.) and yellow birch (Betula alleghaniensis Britton). We observed a positive but small (8%) increase in stomatal density with P addition and an increase in δ13C with N and CaSiO3 addition in sugar maple, but we did not observe effects of nutrient addition on these characteristics in yellow birch. Variability was highest within leaves and among trees for stomatal density and highest among stomata for stomatal length. To reduce variability and increase chances of detecting treatment differences in stomatal density and length, future protocols should consider pretreatment and repeated measurements of trees over time or measure more trees per plot, increase the number of leaf impressions or standardize their locations, measure more stomata per image and ensure consistent light availability.

     
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    Free, publicly-accessible full text available December 9, 2024
  3. Successional, second-growth forests dominate much of eastern North America; thus, patterns of biomass accumulation in standing trees and downed wood are of great interest for forest management and carbon accounting. The timing and magnitude of biomass accumulation in later stages of forest development are not fully understood. We applied a “chronosequence with resampling” approach to characterize live and dead biomass accumulation in 16 northern hardwood stands in the White Mountains of New Hampshire. Live aboveground biomass increased rapidly and leveled off at about 350 Mg/ha by 145 years. Downed wood biomass fluctuated between 10 and 35 Mg/ha depending on disturbances. The species composition of downed wood varied predictably with overstory succession, and total mass of downed wood increased with stand age and the concomitant production of larger material. Fine woody debris peaked at 30–50 years during the self-thinning of early successional species, notably pin cherry. Our data support a model of northern hardwood forest development wherein live tree biomass accumulates asymptotically and begins to level off at ∼140–150 years. Still, 145-year-old second-growth stands differed from old-growth forests in their live ( p = 0.09) and downed tree diameter distributions ( p = 0.06). These patterns of forest biomass accumulation would be difficult to detect without a time series of repeated measurements of stands of different ages.

     
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    Free, publicly-accessible full text available October 26, 2024
  4. Quantifying uncertainty in forest assessments is challenging because of the number of sources of error and the many possible approaches to quantify and propagate them. The uncertainty in allometric equations has sometimes been represented by propagating uncertainty only in the prediction of individuals, but at large scales with large numbers of trees uncertainty in model fit is more important than uncertainty in individuals. We compared four different approaches to representing model uncertainty: a formula for the confidence interval, Monte Carlo sampling of the slope and intercept of the regression, bootstrap resampling of the allometric data, and a Bayesian approach. We applied these approaches to propagating model uncertainty at four different scales of tree inventory (10 to 10,000 trees) for four study sites with varying allometry and model fit statistics, ranging from a monocultural plantation to a multi-species shrubland with multi-stemmed trees. We found that the four approaches to quantifying uncertainty in model fit were in good agreement, except that bootstrapping resulted in higher uncertainty at the site with the fewest trees in the allometric data set (48), because outliers could be represented multiple times or not at all in each sample. The uncertainty in model fit did not vary with the number of trees in the inventory to which it was applied. In contrast, the uncertainty in predicting individuals was higher than model fit uncertainty when applied to small numbers of trees, but became negligible with 10,000 trees. The importance of this uncertainty source varied with the forest type, being largest for the shrubland, where the model fit was most poor. Low uncertainties were observed where model fit was high, as was the case in the monoculture plantation and in the subtropical jungle where hundreds of trees contributed to the allometric model. In all cases, propagating uncertainty only in the prediction of individuals would underestimate allometric uncertainty. It will always be most correct to include both uncertainty in predicting individuals and uncertainty in model fit, but when large numbers of individuals are involved, as in the case of national forest inventories, the contribution of uncertainty in predicting individuals can be ignored. When the number of trees is small, as may be the case in forest manipulation studies, both sources of allometric uncertainty are likely important and should be accounted for. 
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  5. Abstract

    Few previous studies have described the patterns of leaf characteristics in response to nutrient availability and depth in the crown. Sugar maple has been studied for both sensitivity to light, as a shade-tolerant species, and sensitivity to soil nutrient availability, as a species in decline due to acid rain. To explore leaf characteristics from the top to bottom of the canopy, we collected leaves along a vertical gradient within mature sugar maple crowns in a full-factorial nitrogen (N) by phosphorus (P) addition experiment in three forest stands in central New Hampshire, USA. Thirty-two of the 44 leaf characteristics had significant relationships with depth in the crown, with the effect of depth in the crown strongest for leaf area, photosynthetic pigments and polyamines. Nitrogen addition had a strong impact on the concentration of foliar N, chlorophyll, carotenoids, alanine and glutamate. For several other elements and amino acids, N addition changed patterns with depth in the crown. Phosphorus addition increased foliar P and boron (B); it also caused a steeper increase of P and B with depth in the crown. Since most of these leaf characteristics play a direct or indirect role in photosynthesis, metabolic regulation or cell division, studies that ignore the vertical gradient may not accurately represent whole-canopy performance.

     
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  6. The Multiple Element Limitation in Northern Hardwood Ecosystems (MELNHE) project studies N , P, and Ca acquisition and limitation of forest productivity through a series of nutrient manipulations in northern hardwood forests. This data set includes data testing effects of elevated N and P availability on fine root growth (using ingrowth cores) and biomass in the MELNHE project. Subsets of ingrowth cores were treated with nutrients differing from the plot-scale nutrient treatments to test fine root foraging. Additional detail on the MELNHE project, including a datatable of site descriptions and a pdf file with the project description and diagram of plot configuration can be found in this data package: https://portal.edirepository.org/nis/mapbrowse?scope=knb-lter-hbr&identifier=344 These data were gathered as part of the Hubbard Brook Ecosystem Study (HBES). The HBES is a collaborative effort at the Hubbard Brook Experimental Forest, which is operated and maintained by the USDA Forest Service, Northern Research Station. 
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  7. Stomatal density and length were measured on leaves of sugar maple (Acer sacharrum Marsh.) and yellow birch (Betula alleghaniensis Britton.) trees in New Hampshire at the Bartlett Experimental Forest, Hubbard Brook Experimental Forest, and Jeffers Brook as part of the Multiple Elementation Limitation in Northern Hardwood Ecosystems (MELNHE) study. Leaves were collected in late July and early August in 2021 and 2022 from the tops of dominant and codominant trees using a shotgun. These measurements were made on 3 leaves from each tree. These data correspond with other foliar trait data collected from the same trees in 2021 and 2022. That EDI package is as follows: Hong, S.D., K.E. Gonzales, C.R. See, and R.D. Yanai. 2021. MELNHE: Foliar Chemistry 2008-2016 in Bartlett, Hubbard Brook, and Jeffers Brook (12 stands) ver 1. Environmental Data Initiative. https://doi.org/10.6073/pasta/b23deb8e1ccf1c1413382bf911c6be19 This data package contains the raw images underlying the data reported in a separate data package on stomatal density and length: https://portal.edirepository.org/nis/mapbrowse?scope=knb-lter-hbr&identifier=372 These data were gathered as part of the Hubbard Brook Ecosystem Study (HBES). The HBES is a collaborative effort at the Hubbard Brook Experimental Forest, which is operated and maintained by the USDA Forest Service, Northern Research Station. 
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  8. Stomatal density and length were measured on leaves of sugar maple (Acer sacharrum Marsh.) and yellow birch (Betula alleghaniensis Britton.) trees in New Hampshire at the Bartlett Experimental Forest, Hubbard Brook Experimental Forest, and Jeffers Brook as part of the Multiple Elementation Limitation in Northern Hardwood Ecosystems (MELNHE) study. Leaves were collected in late July and early August in 2021 and 2022 from the tops of dominant and codominant trees using a shotgun. These measurements were made on 3 leaves from each tree. These data correspond with other foliar trait data collected from the same trees in 2021 and 2022. That EDI package is as follows: Hong, S.D., K.E. Gonzales, C.R. See, and R.D. Yanai. 2021. MELNHE: Foliar Chemistry 2008-2016 in Bartlett, Hubbard Brook, and Jeffers Brook (12 stands) ver 1. Environmental Data Initiative. https://doi.org/10.6073/pasta/b23deb8e1ccf1c1413382bf911c6be19 This data package contains the stomatal density and length derived from the raw images in a separate EDI data package: https://portal.edirepository.org/nis/mapbrowse?scope=knb-lter-hbr&identifier=321 These data were gathered as part of the Hubbard Brook Ecosystem Study (HBES). The HBES is a collaborative effort at the Hubbard Brook Experimental Forest, which is operated and maintained by the USDA Forest Service, Northern Research Station. 
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  9. Statistical confidence in estimates of timber volume, carbon storage, and other forest attributes depends, in part, on the uncertainty in field measurements. Surprisingly, measurement uncertainty is rarely reported, even though national forest inventories routinely repeat field measurements for quality assurance. We compared measurements made by field crews and quality assurance crews in the Forest Inventory and Analysis program of the U.S. Forest Service, using data from 2790 plots and 51 740 trees and saplings across the 24 states of the Northern Region. We characterized uncertainty in 12 national core tree-level variables; seven tree crown variables used in forest health monitoring; three variables describing seedlings; and 11 variables describing the site, such as elevation, slope, and distance from a road. Discrepancies in measurement were generally small but were higher for some variables requiring judgment, such as tree class, decay class, and cause of mortality. When scaled up to states, forest types, or the region, uncertainties in basal area, timber volume, and aboveground biomass were negligible. Understanding all sources of uncertainty is important to designing forest monitoring systems, managing the conduct of the inventory, and assessing the uncertainty of forest attributes required for making regional and national forest policy decisions. 
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