Brenden E. McNeil

Do Nutrient Limitation Patterns Shift from Nitrogen Toward Phosphorus with Increasing Nitrogen Deposition Across the Northeastern United States

Atmospheric nitrogen (N) deposition is altering biogeochemical cycling in forests and interconnected lakes of the northeastern US, and may shift nutrient limitation from N toward other essential elements, such as phosphorus (P). Whether this shift is occurring relative to N deposition gradients across the northeastern US has not been investigated. We used datasets for the northeastern US and the Adirondack sub-region to evaluate whether P limitation is increasing where N deposition is high at two geographic scales, based on N:P mass ratios. Using a model-selection approach, we determined that foliar N for dominant tree species and lake dissolved inorganic N (DIN) increased coincident with increasing N deposition, independent of relationships between foliar N or lake DIN and precipitation or temperature. Foliar P also increased with N deposition across the northeastern US for seven of eight deciduous species, but changed less across the Adirondacks. Foliar N:P therefore declined at the highest levels of N deposition for most deciduous species across the region (remaining nearly constant for most conifers and increasing only for black cherry and hemlock), but increased across all species in the Adirondacks. Ratios between DIN and total P (DIN:TP) in lakes were unrelated to N deposition regionally but increased across the Adirondacks. Thus, nutrient limitation patterns shifted from N toward P for dominant trees, and further toward P for predominantly P-limited lakes, at the sub-regional but not regional scale. For the northeastern US overall, accumulated N deposition may be insufficient to drive nutrient limitation from N toward P; alternatively, elements other than P (for example, calcium, magnesium) may become limiting as N accumulates. The consistent Adirondack foliar and lake response could provide early indication of shifts toward P limitation within the northeastern US, and together with regional patterns, suggests that foliar chemistry could be a predictor of lake chemistry in the context of N deposition across the region.

Spectroscopic determination of leaf morphological and biochemical traits for northern temperate and boreal tree species

The morphological and biochemical properties of plant canopies are strong predictors of photosynthetic capacity and nutrient cycling. Remote sensing research at the leaf and canopy scales has demonstrated the ability to characterize the biochemical status of vegetation canopies using reflectance spectroscopy, including at the leaf level and canopy level from air- and spaceborne imaging spectrometers. We developed a set of accurate and precise spectroscopic calibrations for the determination of leaf chemistry (contents of nitrogen, carbon, and fiber constituents), morphology (leaf mass per area, Marea), and isotopic composition (δ15N) of temperate and boreal tree species using spectra of dried and ground leaf material. The data set consisted of leaves from both broadleaf and needle-leaf conifer species and displayed a wide range in values, determined with standard analytical approaches: 0.7–4.4% for nitrogen (Nmass), 42–54% for carbon (Cmass), 17–58% for fiber (acid-digestible fiber, ADF), 7–44% for lignin (acid-digestible lignin, ADL), 3–31% for cellulose, 17–265 g/m2 for Marea, and −9.4‰ to 0.8‰ for δ15N. The calibrations were developed using a partial least-squares regression (PLSR) modeling approach combined with a novel uncertainty analysis. Our PLSR models yielded model calibration (independent validation shown in parentheses) R2 and the root mean square error (RMSE) values, respectively, of 0.98 (0.97) and 0.10% (0.13%) for Nmass, R2 = 0.77 (0.73) and RMSE = 0.88% (0.95%) for Cmass, R2 = 0.89 (0.84) and RMSE = 2.8% (3.4%) for ADF, R2 = 0.77 (0.69) and RMSE = 2.4% (3.9%) for ADL, R2 = 0.77 (0.72) and RMSE = 1.4% (1.9%) for leaf cellulose, R2 = 0.62 (0.60) and RMSE = 0.91‰ (1.5‰) for δ15N, and R2 = 0.88 (0.87) with RMSE = 17.2 g/m2 (22.8 g/m2) for Marea. This study demonstrates the potential for rapid and accurate estimation of key foliar traits of forest canopies that are important for ecological research and modeling activities, with a single calibration equation valid over a wide range of northern temperate and boreal species and leaf physiognomies. The results provide the basis to characterize important variability between and within species, and across ecological gradients using a rapid, cost-effective, easily replicated method.

Imaging spectroscopy algorithms for mapping canopy foliar chemical and morphological traits and their uncertainties

A major goal of remote sensing is the development of generalizable algorithms to repeatedly and accurately map ecosystem properties across space and time. Imaging spectroscopy has great potential to map vegetation traits that cannot be retrieved from broadband spectral data, but rarely have such methods been tested across broad regions. Here we illustrate a general approach for estimating key foliar chemical and morphological traits through space and time using NASAs Airborne Visible/Infrared Imaging Spectrometer (AVIRIS-Classic). We apply partial least squares regression (PLSR) to data from 237 field plots within 51 images acquired between 2008 and 2011. Using a series of 500 randomized 50/50 subsets of the original data, we generated spatially explicit maps of seven traits (leaf mass per area (M(area)), percentage nitrogen, carbon, fiber, lignin, and cellulose, and isotopic nitrogen concentration, δ15N) as well as pixel-wise uncertainties in their estimates based on error propagation in the analytical methods. Both M(area) and %N PLSR models had a R2 > 0.85. Root mean square errors (RMSEs) for both variables were less than 9% of the range of data. Fiber and lignin were predicted with R2 > 0.65 and carbon and cellulose with R2 > 0.45. Although R2 of %C and cellulose were lower than M(area) and %N, the measured variability of these constituents (especially %C) was also lower, and their RMSE values were beneath 12% of the range in overall variability. Model performance for δ15N was the lowest (R2 = 0.48, RMSE = 0.95 per thousand), but within 15% of the observed range. The resulting maps of chemical and morphological traits, together with their overall uncertainties, represent a first-of-its-kind approach for examining the spatiotemporal patterns of forest functioning and nutrient cycling across a broad range of temperate and sub-boreal ecosystems. These results offer an alternative to categorical maps of functional or physiognomic types by providing non-discrete maps (i.e., on a continuum) of traits that define those functional types. A key contribution of this work is the ability to assign retrieval uncertainties by pixel, a requirement to enable assimilation of these data products into ecosystem modeling frameworks to constrain carbon and nutrient cycling projections.

Is the growth of temperate forest trees enhanced along an ambient nitrogen deposition gradient

The extent to which atmospheric N deposition is enhancing primary production and CO2 sequestration along the ambient N deposition gradients found within many regional temperate forest ecosystems remains unknown. We used tree diameter measurements from 1984 and 2004, allometric equations, and estimates of wet N deposition from 32 permanent plots located along an ambient N deposition gradient in the Adirondack Park, New York, U.S.A., to determine the effects of N deposition on the basal area and woody biomass increments (BAI and WBI, respectively) of individual stems from all the major tree species. Nitrogen deposition had either a neutral or positive effect on BAI and WBI, with the positive effects especially apparent within the smaller size classes of several species. The nature of these growth responses suggests that other co-varying factors (e.g., temperature, tropospheric ozone, soil acidification) may be partially counteracting the species-dependent fertilization effect of N deposition that was suggested by recent foliar N data across this gradient. Nevertheless, in documenting a fertilization effect from chronic, low-level, ambient rates of N deposition, this study underscores the need for more research on how N deposition is affecting rates of primary production, CO2 sequestration, and even vegetation dynamics in many forests worldwide.

Foliar Nitrogen Responses to the Environmental Gradient Matrix of the Adirondack Park, New York

Maps derived from remote sensing of canopy nitrogen (N) provide a potential avenue to make spatially explicit, regional-scale predictions of the vital forest ecosystem services that are coupled to the cycling of N and carbon. Yet, to fully use canopy N maps in this capacity, it is necessary to understand how canopy species with differing resource strategies will adjust foliar N in response to environmental variability. In this study, we relate a regional survey of foliar N data from a diverse set of forest tree species in the Adirondack Park, New York, to a holistic matrix of environmental gradients thought to control spatial variability of foliar N. Stepwise multiple regression models developed for each species indicate that neighboring species and abiotic gradients of resource availability play a lesser role, and anthropogenic influences (caused by historic disturbances and atmospheric N deposition) are the strongest drivers of spatial variability in foliar N. Moreover, we find that the plasticity of the total foliar N response to measured environmental variability is strongly related to two indexes of a species’ resource strategy—leaf mass per area and shade tolerance. Collectively, these results (1) further demonstrate the utility of an environmental gradient matrix approach to studying complex ecosystems; (2) emphasize the potentially dominant role of humans in controlling future nutrient cycling, even within this “forever wild” forest ecosystem; and (3) suggest that spatially explicit measurements of foliar N, environmental gradients, and plant resource strategies might provide a pathway to map and forecast ecosystem services at regional scales.

Does spatial resolution matter? A multi-scale comparison of object-based and pixel-based methods for detecting change associated with gas well drilling operations

An implicit assumption of the geographic object-based image analysis (GEOBIA) literature is that GEOBIA is more accurate than pixel-based methods for high spatial resolution image classification, but that the benefits of using GEOBIA are likely to be lower when moderate resolution data are employed. This study investigates this assumption within the context of a case study of mapping forest clearings associated with drilling for natural gas. The forest clearings varied from 0.2 to 9.2 ha, with an average size of 0.9 ha. National Aerial Imagery Program data from 2004 to 2010, with 1 m pixel size, were resampled through pixel aggregation to generate imagery with 2, 5, 15, and 30 m pixel sizes. The imagery for each date and at each of the five spatial resolutions was classified into Forest and Non-forest classes, using both maximum likelihood and GEOBIA. Change maps were generated through overlay of the classified images. Accuracy evaluation was carried out using a random sampling approach. The 1 m GEOBIA classification was found to be significantly more accurate than the GEOBIA and per-pixel classifications with either 15 or 30 m resolution. However, at any one particular pixel size (e.g. 1 m), the pixel-based classification was not statistically different from the GEOBIA classification. In addition, for the specific class of forest clearings, accuracy varied with the spatial resolution of the imagery. As the pixel size coarsened from 1 to 30 m, accuracy for the per-pixel method increased from 59% to 80%, but decreased from 71% to 58% for the GEOBIA classification. In summary, for studying the impact of forest clearing associated with gas extraction, GEOBIA is more accurate than pixel-based methods, but only at the very finest resolution of 1 m. For coarser spatial resolutions, per-pixel methods are not statistically different from GEOBIA.

THE SPATIAL PATTERN OF NITROGEN CYCLING IN THE ADIRONDACK PARK, NEW YORK

Maps of canopy nitrogen obtained through analysis of high-resolution, hyperspectral, remotely sensed images now offer a powerful means to make landscape-scale to regional-scale estimates of forest N cycling and net primary production (NPP). Moreover, recent research has suggested that the spatial variability within maps of canopy N may be driven by environmental gradients in such features as historic forest disturbance, temperature, species composition, moisture, geology, and atmospheric N deposition. Using the wide variation in these six features found within the diverse forest ecosystems of the 2.5 million ha Adirondack Park, New York, USA, we examined linkages among environmental gradients and three measures of N cycling collected during the 2003 growing season: (1) field survey of canopy N, (2) field survey of soil C:N, and (3) canopy N measured through analysis of two 185 x 7.5 km Hyperion hyperspectral images. These three measures of N cycling strongly related to forest type but related poorly to all other environmental gradients. Further analysis revealed that the spatial pattern in N cycling appears to have distinct inter- and intraspecific components of variability. The interspecific component, or the proportional contribution of species functional traits to canopy biomass, explained 93% of spatial variability within the field canopy N survey and 37% of variability within the soil C:N survey. Residual analysis revealed that N deposition accounted for an additional 2% of variability in soil C:N, and N deposition and historical forest disturbance accounted for an additional 2.8% of variability in canopy N. Given our finding that 95.8% of the variability in the field canopy N survey could be attributed to variation in the physical environment, our research suggests that remotely sensed maps of canopy N may be useful not only to assess the spatial variability in N cycling and NPP, but also to unravel the relative importance of their multiple controlling factors.

Coordinating a Northeast Regional Phenology Network

recognized as a vital aspect of understanding how organisms and their associated ecosystems respond to climatic variability. Similar to studies conducted elsewhere, recent studies in forests of the northeastern United States and adjacent Canada (i.e., “the Northeast region”) indicate that recent warming trends have resulted in an extension of the growing season (earlier springs and later autumns), a phenological

Site-level importance of broadleaf deciduous trees outweighs the legacy of high nitrogen (N) deposition on ecosystem N status of Central Appalachian red spruce forests

Background and aimsAtmospheric nitrogen (N) deposition can influence forest ecosystem N status, and the resilience of forests to the effects of N deposition depends on a number of co-occurring environmental factors that regulate N retention or loss. In this study, we test the idea that N deposition may have important and long-lasting impacts on patterns of N cycling by using field and laboratory techniques to assess N status in seven high-elevation Central Appalachian red spruce (Picea rubens Sarg.) forests located at sites that historically received moderate to high inputs of N atmospheric deposition.MethodsDuring 2011 and 2012, we measured multiple indices of N availability (e.g. foliar/soil C:N and δ15N, resin ion-exchange, and N transformation rates) that integrate N cycling over seasonal to decadal time scales. Using a model selection approach, we compared the strength of the association between various environmental factors and temporally-integrated indices of N status in a series of regression models.ResultsSite-level differences in the relative importance value of broadleaf deciduous (BD) trees consistently explained most of the observed variation in N status. Soil C:N was significantly lower for sites with greater BD importance (R2 = 0.67–0.77), and there was a strong positive relationship between BD importance and soil δ15N content (R2 = 0.64–0.85). Despite a four-fold difference in historic deposition across the seven forest sites, we did not observe any significant relationships between site N status and N deposition.ConclusionsThese findings suggest that potential legacy effects of N deposition were obscured by the influence of BD importance on N status at these sites. Our results add strong support to the idea that predicting the resilience of forests to the effects of N deposition requires detailed knowledge on the contribution of tree species composition to soil N cycling and retention.

A Framework to Assess Biogeochemical Response to Ecosystem Disturbance Using Nutrient Partitioning Ratios

Disturbances affect almost all terrestrial ecosystems, but it has been difficult to identify general principles regarding these influences. To improve our understanding of the long-term consequences of disturbance on terrestrial ecosystems, we present a conceptual framework that analyzes disturbances by their biogeochemical impacts. We posit that the ratio of soil and plant nutrient stocks in mature ecosystems represents a characteristic site property. Focusing on nitrogen (N), we hypothesize that this partitioning ratio (soil N: plant N) will undergo a predictable trajectory after disturbance. We investigate the nature of this partitioning ratio with three approaches: (1) nutrient stock data from forested ecosystems in North America, (2) a process-based ecosystem model, and (3) conceptual shifts in site nutrient availability with altered disturbance frequency. Partitioning ratios could be applied to a variety of ecosystems and successional states, allowing for improved temporal scaling of disturbance events. The generally short-term empirical evidence for recovery trajectories of nutrient stocks and partitioning ratios suggests two areas for future research. First, we need to recognize and quantify how disturbance effects can be accreting or depleting, depending on whether their net effect is to increase or decrease ecosystem nutrient stocks. Second, we need to test how altered disturbance frequencies from the present state may be constructive or destructive in their effects on biogeochemical cycling and nutrient availability. Long-term studies, with repeated sampling of soils and vegetation, will be essential in further developing this framework of biogeochemical response to disturbance.