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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 51740 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. Key words: carbon accounting, Forest Inventory and Analysis, forest inventory, measurement uncertainty, forestry, 1. Introduction Forest inventories have historically been performed for many purposes (Labau et al. 2007), including estimating merchantable timber, determining risk of fire, evaluating habitat for wildlife, and assessing biodiversity. [...]

A better understanding is needed of how hydrological and biogeochemical processes control dissolved organic carbon (DOC) concentrations and dissolved organic matter (DOM) composition from headwaters downstream to large rivers. We examined a large DOM dataset from the National Water Information System of the US Geological Survey, which represents approximately 100 000 measurements of DOC concentration and DOM composition at many sites along rivers across the United States. Application of quantile regression revealed a tendency towards downstream spatial and temporal homogenization of DOC concentrations and a shift from dominance of aromatic DOM in headwaters to more aliphatic DOM downstream. The DOC concentration-discharge (C-Q) relationships at each site revealed a downstream tendency towards a slope of zero. We propose that despite complexities in river networks that have driven many revisions to the River Continuum Concept, rivers show a tendency towards chemostasis (C-Qslope of zero) because of a downstream shift from a dominance of hydrologic drivers that connect terrestrial DOM sources to streams in the headwaters towards a dominance of instream and near-stream biogeochemical processes that result in preferential losses of aromatic DOM and preferential gains of aliphatic DOM. Une meilleure comprehension de l'influence des processus hydrologiques et biogeochimiques sur les concentrations de carbone organique dissous (COD) et sur la composition des matieres organiques dissoutes (MOD) des cours d'eau d'amont jusqu'aux grands fleuves est necessaire. Nous avons examine un imposant ensemble de donnees sur la MOD du Systeme national d'information sur l'eau de la commission geologique des Etats-Unis (US Geological Survey), qui represente environ 100 000 mesures de concentration de COD et de composition de MOD en de nombreux endroits le long de rivieres a la grandeur des Etats-Unis. L'application de la regression quantile a revele une tendance a l'homogeneisation spatiale et temporelle vers l'aval des concentrations de COD et le passage d'une predominance de MOD aromatiques dans les cours d'eau d'amont a plus de MOD aliphatiques en aval. Les relations concentrations de COD-debit (C-D) a chaque site ont revele une tendance vers une pente nulle vers l'aval. Nous proposons que, malgre les complexites des reseaux hydrographiques qui ont mene a de nombreuses revisions du concept du continuum fluvial, les rivieres tendent vers la chimiostase (pente nulle de la relation C-D) en raison du passage vers l'aval d'une predominance de facteurs hydrologiques qui relient les sources de MOD terrestres aux cours d'eau d'amont, a une predominance de processus biogeochimiques dans le cours d'eau ou a proximite qui se traduisent par des pertes preferentielles de MOD aromatiques et des gains preferentiels de MOD aliphatiques. [Traduit par la Redaction], Introduction In most river ecosystems, the downstream transport of dissolved organic matter (DOM) represents the greatest flux of organic carbon (Schlesinger and Melack 1981; Meybeck 1982). DOM can be defined [...]

Small catchments have served as sentinels of forest ecosystem responses to changes in air quality and climate. The Hubbard Brook Experimental Forest in New Hampshire has been tracking catchment water budgets and their controls – meteorology and vegetation – since 1956. Water budgets in four reference catchments indicated an approximately 30% increase in the evapotranspiration (ET) as estimated by the difference between precipitation (P) and runoff (RO) starting in 2010 and continuing through 2019. We analyzed the annual water budgets, cumulative deviations of the daily P, RO and water budget residual (WBR = P − RO), potential ET (PET) and indicators of subsurface storage to gain greater insight into this shift in the water budgets. The PET and the subsurface storage indicators suggest that this change in WBR was primarily due to increasing ET. While multiple long‐term hydrological and micrometeorological data sets were used to detect and investigate this change in ET, additional measurements of groundwater storage and soil moisture would enable better estimation of ET within the catchment water balance. Increasing the breadth of long‐term measurements across small gauged catchments allows them to serve as more effective sentinels of substantial hydrologic changes like the ET increase that we observed. [ABSTRACT FROM AUTHOR]

Stream solute monitoring has produced many insights into ecosystem and Earth system functions. Although new sensors have provided novel information about the fine‐scale temporal variation of some stream water solutes, we lack adequate sensor technology to gain the same insights for many other solutes. We used two machine learning algorithms – Support Vector Machine and Random Forest – to predict concentrations at 15‐min resolution for 10 solutes, of which eight lack specific sensors. The algorithms were trained with data from intensive stream sensing and manual stream sampling (weekly) for four full years in a hydrologic reference stream within the Hubbard Brook Experimental Forest in New Hampshire, USA. The Random Forest algorithm was slightly better at predicting solute concentrations than the Support Vector Machine algorithm (Nash‐Sutcliffe efficiencies ranged from 0.35 to 0.78 for Random Forest compared to 0.29 to 0.79 for Support Vector Machine). Solute predictions were most sensitive to the removal of fluorescent dissolved organic matter, pH and specific conductance as independent variables for both algorithms, and least sensitive to dissolved oxygen and turbidity. The predicted concentrations of calcium and monomeric aluminium were used to estimate catchment solute yield, which changed most dramatically for aluminium because it concentrates with stream discharge. These results show great promise for using a combined approach of stream sensing and intensive stream discrete sampling to build information about the high‐frequency variation of solutes for which an appropriate sensor or proxy is not available. [ABSTRACT FROM AUTHOR]

Uncertainty in the estimation of hydrologic export of solutes has never been fully evaluated at the scale of a small-watershed ecosystem. We used data from the Gomadansan Experimental Forest, Japan, Hubbard Brook Experimental Forest, USA, and Coweeta Hydrologic Laboratory, USA, to evaluate many sources of uncertainty, including the precision and accuracy of measurements, selection of models, and spatial and temporal variation. Uncertainty in the analysis of stream chemistry samples was generally small but could be large in relative terms for solutes near detection limits, as is common for ammonium and phosphate in forested catchments. Instantaneous flow deviated from the theoretical curve relating height to discharge by up to 10% at Hubbard Brook, but the resulting corrections to the theoretical curve generally amounted to <0.5% of annual flows. Calibrations were limited to low flows; uncertainties at high flows were not evaluated because of the difficulties in performing calibrations during events. However, high flows likely contribute more uncertainty to annual flows because of the greater volume of water that is exported during these events. Uncertainty in catchment area was as much as 5%, based on a comparison of digital elevation maps with ground surveys. Three different interpolation methods are used at the three sites to combine periodic chemistry samples with streamflow to calculate fluxes. The three methods differed by <5% in annual export calculations for calcium, but up to 12% for nitrate exports, when applied to a stream at Hubbard Brook for 1997-2008; nitrate has higher weekly variation at this site. Natural variation was larger than most other sources of uncertainty. Specifically, coefficients of variation across streams or across years, within site, for runoff and weighted annual concentrations of calcium, magnesium, potassium, sodium, sulphate, chloride, and silicate ranged from 5 to 50% and were even higher for nitrate. Uncertainty analysis can be used to guide efforts to improve confidence in estimated stream fluxes and also to optimize design of monitoring programmes. © 2014 The Authors. Hydrological Processes published John Wiley & Sons, Ltd. [ABSTRACT FROM AUTHOR]