[Show abstract][Hide abstract] ABSTRACT: While river-borne materials are recognized as important resources supporting coastal ecosystems around the world, estimates of river export from the North Slope of Alaska have been limited by a scarcity of water chemistry and river discharge data. This paper quantifies water, nutrient, and organic matter export from the three largest rivers (Sagavanirktok, Kuparuk, Colville) that drain Alaska's North Slope and discusses the potential importance of river inputs for biological production in coastal waters of the Alaskan Beaufort Sea. Together these rivers export ~297,000 metric tons of organic carbon and ~18,000 metric tons of organic nitrogen each year. Annual fluxes of nitrate-N, ammonium-N, and soluble reactive phosphorus are approximately 1750, 200, and 140 metric tons per year respectively. Constituent export from Alaska's North Slope is dominated by the Colville River. This is in part due to its larger size, but also because constituent yields are greater in the Colville watershed. River-supplied nitrogen may be more important to productivity along the Alaskan Beaufort Sea coast than previously thought. However, given the dominance of organic nitrogen export, the potential role of river-supplied nitrogen in support of primary production depends strongly on remineralization mechanisms. Although rivers draining the North Slope of Alaska make only a small contribution to overall river export from the pan-arctic watershed, comparisons with major arctic rivers reveal unique regional characteristics as well as remarkable similarities among different regions and scales. Such information is crucial for development of robust river export models that represent the arctic system as a whole.
[Show abstract][Hide abstract] ABSTRACT: We used a new ecohydrological model, Visualizing Ecosystems for Land
Management Assessments (VELMA), to analyze the effects of forest harvest
on catchment carbon and nitrogen dynamics. We applied the model to a 10
ha headwater catchment in the western Oregon Cascade Range where two
major disturbance events have occurred during the past 500 years: a
stand-replacing fire circa 1525 and a clear-cut in 1975. Hydrological
and biogeochemical data from this site and other Pacific Northwest
forest ecosystems were used to calibrate the model. Model parameters
were first calibrated to simulate the postfire buildup of ecosystem
carbon and nitrogen stocks in plants and soil from 1525 to 1969, the
year when stream flow and chemistry measurements were begun. Thereafter,
the model was used to simulate old-growth (1969-1974) and postharvest
(1975-2008) temporal changes in carbon and nitrogen dynamics. VELMA
accurately captured observed changes in carbon and nitrogen dynamics
before and after harvest. The interaction of hydrological and
biogeochemical processes in the model provided a means for interpreting
these changes. Results show that (1) losses of dissolved nutrients in
the preharvest old-growth forest were generally low and consisted
primarily of organic nitrogen and carbon; (2) following harvest, carbon
and nitrogen losses from the terrestrial system to the stream and
atmosphere increased as a result of reduced plant nitrogen uptake,
increased soil organic matter decomposition, and high soil moisture; and
(3) the rate of forest regrowth following harvest was lower than that
after fire because post-clear-cut stocks and turnover of detritus
nitrogen were substantially lower than after fire.
Water Resources Research 03/2013; 49(3):1292-1313. · 3.71 Impact Factor
[Show abstract][Hide abstract] ABSTRACT: Background/Question/Methods
The effectiveness of riparian forest buffers and other green infrastructure for reducing nitrogen export to agricultural streams has been well described experimentally, but a clear understanding of process-level hydrological and biogeochemical controls can be difficult to ascertain from data alone. We previously applied a new ecohydrological model, Visualizing Ecosystems for Land Management Assessments (VELMA), to further elucidate how riparian forest buffers reduce stream inputs of dissolved nitrogen in runoff from upland agricultural practices in an intensively studied catchment in the Rhode River Watershed along the western shore of Chesapeake Bay, USA. Simulated and observed daily stream flow and export of ammonium and nitrate were in generally good agreement over the period of record (2000-2003) for which complete daily stream flow and chemistry data were available. For the present study we used sensitivity analysis to explore the model’s potential for extending the experimental data to identify upland and riparian best management practices (BMPs) that most effectively reduce stream nitrogen loads. Candidate BMPs considered the sensitivity of nitrogen reduction to the timing and rate of upland fertilization and to green infrastructure extent (buffer width), type (forest or grass) and management (stand age).
The model suggests that riparian forest buffers are more effective than grass buffers in reducing stream nitrogen loads. Greater buffer width and stand age increase nitrogen reductions, but gains in effectiveness diminish asymptotically for both variables. Green infrastructure solutions alone may be insufficient for achieving water quality standards where riparian flow paths are predominantly deep or where upland fertilization approaches rates often used for intensive agriculture. The model also quantitatively describes the trade-off between agronomic production and nitrogen export to surface waters and the relative importances of denitrification and plant uptake in reducing nitrogen export under different upland and riparian management scenarios.
[Show abstract][Hide abstract] ABSTRACT: The accuracy of six combined methods formed by three commonly-used soil hydraulic functions and two methods to determine soil hydraulic parameters based on a soil hydraulic parameter look-up table and soil pedotransfer functions was examined for simulating soil moisture. A novel data analysis and modelling approach was used that eliminated the effects of evapotranspiration so that specific sources of error among the six combined methods could be identified and quantified. By comparing simulated and observed soil moisture at six sites of the USDA Soil Climate Analysis Network, we identified the optimal soil hydraulic functions and parameters for predicting soil moisture. Through sensitivity tests, we also showed that adjusting only the soil saturated hydraulic conductivity, Ks, is insufficient for representing important effects of macropores on soil hydraulic conductivity. Our analysis illustrates that, in general, soil hydraulic conductivity is less sensitive to Ks than to the soil pore-size distribution parameter.Editor D. Koutsoyiannis; Associate editor D. HughesCitation Pan, F., McKane, R.B. and Stieglitz, M., 2012. Identification of optimal soil hydraulic functions and parameters for predicting soil moisture. Hydrological Sciences Journal, 57 (4), 1–15.
[Show abstract][Hide abstract] ABSTRACT: 1] Digital elevation model (DEM) data are essential to hydrological applications and have been widely used to calculate a variety of useful topographic characteristics, e.g., slope, flow direction, flow accumulation area, stream channel network, topographic index, and others. Except for slope, none of the other topographic characteristics can be calculated until the flow direction at each pixel within a DEM is determined. However, flow direction cannot be accurately calculated until depressions and flat areas within a DEM have been rectified. This is a routine problem in hydrologic modeling, because virtually all DEMs contain flat and sink pixels, both real and artifactual, that if left untreated will prevent accurate simulation of hydrologic flow paths. Although a number of algorithms are available for rectifying flat and sink pixels in DEM data, treatment of flat areas and depressions and calculation of flow direction remain problematic for reasons of complexity and uncertainty. A new algorithm that effectively rectifies flat and sink pixels was developed and tested. The approach is to use linear interpolation between low elevation grid cells on the edge of each flat area or depression defined as outlets and higher elevation grid cells on the opposite side defined as inflow pixels. The implementation requires an iterative solution to accommodate the irregular geometry of flat areas or depressions and exceptions that arise. Linear interpolation across flat areas or depressions provides a natural way to scale elevation adjustments based on the vertical scale of the surrounding topography, thereby avoiding the addition or subtraction of arbitrary small numbers that we regard as a disadvantage in some prior techniques. Tests for two virtual terrains and one real terrain show that our algorithm effectively rectifies flat areas and depressions, even in low-relief terrain, and produces realistic patterns of flow accumulation and extracted channel networks., An algorithm for treating flat areas and depressions in digital elevation models using linear interpolation, Water Resour. Res., 48, W00L10, doi:10.1029/2011WR010735.
Water Resources Research 01/2012; 48(6). · 3.71 Impact Factor
[Show abstract][Hide abstract] ABSTRACT: The effects of riparian vegetation on the reduction of agricultural
nitrogen export to streams have been well described experimentally, but
a clear understanding of process-level hydrological and biogeochemical
controls can be difficult to ascertain from data alone. We apply a new
model, Visualizing Ecosystems for Land Management Assessments (VELMA),
to further elucidate how riparian forest buffers reduce stream inputs of
dissolved nitrogen in runoff from upland agricultural practices in an
intensively studied catchment in the Rhode River Watershed along the
western shore of Chesapeake Bay, USA. VELMA is a spatially distributed
eco-hydrology model that links hydrological and biogeochemical processes
within watersheds. Simulated and observed daily stream flow and export
of nitrogen (ammonium, nitrate and organic nitrogen) are in generally
good agreement for the period of record (2000-2003) for which complete
daily stream flow and chemistry data were available. A sensitivity
analysis of the model demonstrates its potential for isolating specific
hydrologic and biogeochemical controls on attenuation of dissolved
nitrogen within the riparian forest zone, and for identifying upland and
riparian best management practices concerning water quality. The results
indicate that subsurface flow pathways, forest buffer design (width),
and management (stand age) have a significant influence on stream
nitrogen loads. However, forest buffers alone may be insufficient for
achieving water quality standards, particularly where upland
fertilization rates approach those often used for intensive agriculture.
These insights include a quantitative description of the trade-off
between agronomic production and nitrogen export to surface waters, and
the relative importance of denitrification in reducing nitrogen export
under different upland and riparian management scenarios.
[Show abstract][Hide abstract] ABSTRACT: Linear increase in stream discharge with increasing harvest areaLarge absolute fall changes and large relative summer changes in streamflowChanges in streamflow were strongly sensitive to harvest location
Water Resources Research 09/2011; 47(9). · 3.71 Impact Factor
[Show abstract][Hide abstract] ABSTRACT: Wetland ecosystems are often characterized by distinct vegetation patterns. Various mechanisms have been proposed to explain the formation of these patterns; including spatially variable peat accumulation and water ponding. Recently, short-range facilitation and long-range competition for resources (a.k.a scale dependent feedback) has been proposed as a possible mechanism for pattern formation in wetland ecosystems. We modify an existing, spatially explicit, advection-reaction-diffusion model to include for a regional hydraulic gradient and effective anisotropy in hydraulic conductivity. This effective anisotropic hydraulic conductivity implicitly represents the effect of ponding: a reduction in the long-range inhibition of vegetation growth in the direction perpendicular to the prevailing hydraulic gradient. We demonstrate that by accounting for effective anisotropy in a simple modeling framework that encompasses only a scale dependent feedback between biomass and nutrient flow, we can reproduce the various vegetation patterns observed in wetland ecosystems: maze, and vegetation bands both perpendicular and parallel to prevailing flow directions. We examine the behavior of this model over a range of plant transpiration rates and regional hydraulic gradients. Results show that by accounting for the effective x-y anisotropy that results from biomass-water interaction (i.e., ponding) we can better understand the mechanisms that drive ecosystem patterning.
Geophysical Research Letters - GEOPHYS RES LETT. 02/2011; 38(4).
[Show abstract][Hide abstract] ABSTRACT: The potential interacting effects of climate change and future land-use on hydrological and biogeochemical dynamics rarely have been described at the catchment level and are difficult or impossible to capture through experimentation or observation alone. We apply a new model, Visualizing Ecosystems for Land Management Assessment (VELMA), to the H.J. Andrews (HJA) Experimental Forest in western Oregon, USA, to simulate the effects of multiple, future climate and land-use scenarios on catchment hydrology and soil C and N dynamics. VELMA is a spatially distributed eco-hydrology model that links hydrological and biogeochemical processes within watersheds. The model simulates daily to century-scale changes in soil water infiltration and redistribution, evapo-transpiration, surface and subsurface runoff, carbon (C) and nitrogen (N) cycling in plants and soils, and the transport of dissolved forms of carbon and nitrogen from the terrestrial landscape to streams. VELMA was previously calibrated and validated for the HJA based on long-term data (1975-2008) describing daily to decadal changes in stream discharge and chemistry, soil and plant carbon, and nitrogen dynamics in response to climate, harvest and fire. That exercise demonstrated that the same set of model parameters accurately simulates hydro-biogeochemical dynamics at multiple spatial scales at HJA, from a small (10-ha) catchment to the 64 km2 HJA basin. Here we use this validated VELMA model to (1) explore the effects of climate change scenarios on catchment hydro-biogeochemical dynamics, and (2) examine forest harvest effects (clearcutting) across climate scenarios on catchment hydro-biogeochemical dynamics in this old growth forest of the Pacific Northwest.
[Show abstract][Hide abstract] ABSTRACT: The interactions between vegetation and hydrology in mountainous terrain are difficult to represent in mathematical models. There are at least three primary reasons for this difficulty. First, expanding plot-scale measurements to the watershed scale requires finding the balance between computational intensity and physical significance. Second, parameters that affect soil, plant and hydrologic processes are distributed heterogeneously across mountain landscapes, and these patterns and processes may be spatially connected. Third, temporal variation in water availability (particularly in seasonal rainfall climates) may involve a ``topographical memory'' that may be expressed as ``lags'' between biological and hydrological processes. A unique opportunity for examining the implications of scaling and spatio-temporal variability on ecohydrological models exists at the H.J. Andrews Experimental Forest (HJA) in Blue River, Oregon. HJA is a National Science Foundation Long Term Ecological Research (LTER) site, and has been monitoring climate, stream, and vegetation characteristics of small watersheds for more than 50 years. A recent LIDAR (Light Detection and Ranging) reconnaissance has produced watershed scale estimations of vegetation and soil surface parameters at a very high spatial resolution, allowing spatially-explicit expansion of long-term data. An ecohydrological model, Visualizing Ecosystems for Land Management Assessments (VELMA) developed by the Stieglitz lab at Georgia Tech in collaboration with EPA has also been calibrated specifically for watershed topographies in HJA. VELMA is a coupled ecohydrological model that simulates the cycling and transport of water and nutrients in three dimensions by specific parameterization of hydrological and biogeochemical functions. It contains submodels for plant, soil, and water processes including surface and sub-surface flow on a daily time step. We are using the VELMA model to explore three sequential and fundamental questions in ecohydrological modeling in mountainous terrain. 1) How does the topographical structure of mountains (elevation, slope, and aspect) impact hydrological parameters such as temperature, rainfall, soil depth, canopy structure, and airflow? 2) To what degree are the model results from high-resolution, spatially-explicit parameterization different from results based on broadly distributed means, and when different, on what scale(s) are the discrepancies most pronounced? 3) Is there an optimal scale for the process-based ecohydrological modeling, and if so, what are the computational limits at this scale? This poster will present our overall experimental plan and initial findings. Experimentation on and establishment of a standard procedure for spatial and temporal partitioning in ecohydrological models is a fundamental step from which advancement towards more comprehensive, dynamic models can be developed.
[Show abstract][Hide abstract] ABSTRACT: The Simple Land-Interface Model (SLIM) was modified to evolve daily
ground temperatures from surface air temperatures (SAT) in
snow-dominated areas. Daily ground surface temperature (GST) was
modeled as a function of daily surface air temperature and snow depth.
Analytical solution to the 1-D thermal diffusion equation was then used
to simulate subsequent propagation of the GST signals into the
subsurface. Time dependent apparent thermal diffusivity was modeled as
a simple sinusoid and incorporated into the framework to account for the
effects of seasonal latent heat and nonconductive heat transfer
processes. The model was tested in snow-dominated sites such as Barrow,
Council and Ivotuk in Alaska, and Reynolds Creek Experimental Watershed
in Idaho. The model captured much of the seasonal dynamics of the
ground thermal regime at all sites. It underestimated the fall ground
temperatures in Barrow and Ivotuk in some years and overestimated spring
ground temperatures in Council.
Journal of Hydrometeorology 12/2010; · 3.57 Impact Factor
[Show abstract][Hide abstract] ABSTRACT: Background/Question/Methods
The U.S. Environmental Protection Agency recently established the Ecosystem Services Research Program to help formulate methods and models for conducting comprehensive risk assessments that quantify how multiple ecosystem services interact and respond in concert to environmental changes. A major goal is to assess how alternative land use and climate scenarios will simultaneously affect food and fiber production, water quality and quantity, regulation of greenhouse gases, and other ecosystem services. Essential to this goal are highly integrated models that can be used to define policy and management strategies for entire ecosystems, not simply individual components of the ecosystem. In this context, an ideal model is one that (1) can unambiguously link effects to causes by identifying key processes that control ecosystem service tradeoffs, (2) can be applied to a wide variety of ecosystems and regions, (3) can be implemented using readily available data, (4) can efficiently map “bundles” of ecosystem services across wide spatial and temporal scales, and (5) can provide a decision support framework for assessing outcomes of alternative policies and management decisions. We developed an eco-hydrologic modeling framework that aims to meet these emerging risk assessment objectives more closely than other currently available models.
VELMA (Visualizing Ecosystems for Land Management Assessments) is a spatially-distributed eco-hydrologic model that links a land surface hydrologic model with a terrestrial biogeochemistry model for simulating the integrated responses of vegetation, soil, and water resources to interacting stressors. Here we describe a proof-of-concept application of VELMA to the H.J. Andrews
Forest, a forested 64 km2 headwater basin and LTER site in the Cascade Range of Oregon. We used VELMA to simulate the effects of three different land use scenarios (100% old-growth, 100% clearcut harvest, and present-day land cover consisting of 45% old-growth and 55% harvested) on changes in five ecosystem services: timber production, carbon sequestration, greenhouse gas regulation, water quantity, and water quality. Compared to the old-growth simulation, over a 60-year period the clearcut simulation reduced total ecosystem carbon stocks by 40%, increased total stream discharge by 15%, increased stream nitrogen export by almost 300%, and increased total CO2 and N2O radiative forcing by over 200%. The simulation for present-day land cover resulted in intermediate values in most cases. Ongoing work is focused on model validation tests for several other LTER sites (Konza Prairie, Hubbard Brook, arctic tundra), and regional applications for Oregon’s Willamette River Basin and Central Plains rangelands.
[Show abstract][Hide abstract] ABSTRACT: Continuous time-series estimates of net ecosystem carbon exchange (NEE) are routinely made using eddy covariance techniques. Identifying and compensating for errors in the NEE time series can be automated using a signal processing filter like the ensemble Kalman filter (EnKF). The EnKF compares each measurement in the time series to a model prediction and updates the NEE estimate by weighting the measurement and model prediction relative to a specified measurement error estimate and an estimate of the model-prediction error that is continuously updated based on model predictions of earlier measurements in the time series. Because of the covariance among model variables, the EnKF can also update estimates of variables for which there is no direct measurement. The resulting estimates evolve through time, enabling the EnKF to be used to estimate dynamic variables like changes in leaf phenology. The evolving estimates can also serve as a means to test the embedded model and reconcile persistent deviations between observations and model predictions. We embedded a simple arctic NEE model into the EnKF and filtered data from an eddy covariance tower located in tussock tundra on the northern foothills of the Brooks Range in northern Alaska, USA. The model predicts NEE based only on leaf area, irradiance, and temperature and has been well corroborated for all the major vegetation types in the Low Arctic using chamber-based data. This is the first application of the model to eddy covariance data. We modified the EnKF by adding an adaptive noise estimator that provides a feedback between persistent model data deviations and the noise added to the ensemble of Monte Carlo simulations in the EnKF. We also ran the EnKF with both a specified leaf-area trajectory and with the EnKF sequentially recalibrating leaf-area estimates to compensate for persistent model-data deviations. When used together, adaptive noise estimation and sequential recalibration substantially improved filter performance, but it did not improve performance when used individually. The EnKF estimates of leaf area followed the expected springtime canopy phenology. However, there were also diel fluctuations in the leaf-area estimates; these are a clear indication of a model deficiency possibly related to vapor pressure effects on canopy conductance.
[Show abstract][Hide abstract] ABSTRACT: Feedbacks between water use, biomass and infiltration capacity in semiarid ecosystems have been shown to lead to the spontaneous formation of vegetation patterns in a simple model. The formation of patterns permits the maintenance of larger overall biomass at low rainfall rates compared with homogeneous vegetation. This results in a bias of models run at larger scales neglecting subgrid-scale variability. In the present study, we investigate the question whether subgrid-scale heterogeneity can be parameterized as the outcome of optimal partitioning between bare soil and vegetated area. We find that a two-box model reproduces the time-averaged biomass of the patterns emerging in a 100 x 100 grid model if the vegetated fraction is optimized for maximum entropy production (MEP). This suggests that the proposed optimality-based representation of subgrid-scale heterogeneity may be generally applicable to different systems and at different scales. The implications for our understanding of self-organized behaviour and its modelling are discussed.
Philosophical Transactions of The Royal Society B Biological Sciences 05/2010; 365(1545):1449-55. · 6.23 Impact Factor
[Show abstract][Hide abstract] ABSTRACT: It has long been a challenge to theoretical ecologists to describe vegetation pattern formations such as the "tiger bush" stripes and "leopard bush" spots in Niger, and the regular maze patterns often observed in bogs in North America and Eurasia. To date, most of simulation models focus on reproducing the spot and labyrinthine patterns, and on the vegetation bands which form perpendicular to surface and groundwater flow directions. Various hypotheses have been invoked to explain the formation of vegetation patterns: selective grazing by herbivores, fire, and anisotropic environmental conditions such as slope. Recently, short distance facilitation and long distance competition between vegetation (a.k.a scale dependent feedback) has been proposed as a generic mechanism for vegetation pattern formation. In this paper, we test the generality of this mechanism by employing an existing, spatially explicit, advection-reaction-diffusion type model to describe the formation of regularly spaced vegetation bands, including those that are parallel to flow direction. Such vegetation patterns are, for example, characteristic of the ridge and slough habitat in the Florida Everglades and which are thought to have formed parallel to the prevailing surface water flow direction. To our knowledge, this is the first time that a simple model encompassing a nutrient accumulation mechanism along with biomass development and flow is used to demonstrate the formation of parallel stripes. We also explore the interactive effects of plant transpiration, slope and anisotropic hydraulic conductivity on the resulting vegetation pattern. Our results highlight the ability of the short distance facilitation and long distance competition mechanism to explain the formation of the different vegetation patterns beyond semi-arid regions. Therefore, we propose that the parallel stripes, like the other periodic patterns observed in both isotropic and anisotropic environments, are self-organized and form as a result of scale dependent feedback. Results from this study improve upon the current understanding on the formation of parallel stripes and provide a more general theoretical framework for future empirical and modeling efforts.
[Show abstract][Hide abstract] ABSTRACT: Fluxes of nutrients and organic matter from watersheds to the coastal ocean are tightly coupled with climate variables that control the water balance as well as biological and geochemical activity. Consequently, major changes in nutrient and organic matter export from rivers are expected to accompany global climate change. These changes in river export may significantly alter biological production in coastal waters. In densely populated regions of the world, these linkages are confounded by many additional anthropogenic influences (such as land-use and fisheries). However, climate remains the dominant control over river export in many regions of the Arctic. This presentation will focus on nutrient and organic matter export from the Sagavanirktok, Kuparuk, and Colville rivers to the Alaskan Beaufort Sea. Together these three rivers capture most of the runoff from the North Slope of Alaska. Data from intensive field efforts in 2006 and 2007 will be used as a basis for discussion of potential watershed contributions to coastal productivity and changes that may be expected as climate and the landscape of Alaska's North Slope change. River-borne contributions of nutrients and organic matter to coastal waters of the Alaskan Beaufort Sea are highly seasonal, with the majority of export occurring during the spring snowmelt period. Organic matter quality (as demonstrated by stable isotope values of particulate organic matter as well as lability assays) also changes dramatically between seasons. Potential effects of changing seasonality will be given particular attention in this presentation.
[Show abstract][Hide abstract] ABSTRACT: We apply a new model, Visualizing Ecosystems for Land Management Assessment (VELMA), to Watershed 10 (WS10) in the H.J. Andrews Experimental Forest to simulate the effects of harvest intensity and spatial pattern on catchment hydrological and biogeochemical processes. Specifically, we test for the occurrence of hydrological and biogeochemical threshold behavior in the catchment response. VELMA is a spatially-distributed eco-hydrology model that simulates the effects of climate, and land cover on daily changes in soil water storage, surface and subsurface runoff, vertical drainage, evapotranspiration, vegetation and soil C and N dynamics, and transport of nitrate, ammonium, DON, and DOC to streams. We simulate pre- and post-disturbance hydrological and biogeochemical responses of the WS10 catchment. Model parameters were initialized to simulate the post-fire build-up of ecosystem C and N stocks from 1725 to 1975. These parameters are then fixed and used to simulate the hydro-biogeochemical response after the 1975 clear-cut. Comparison of modeled and observed soil moisture, streamflow, DIN, DON and DOC losses for the post-clear-cut period (1975-2007) show that VELMA accurately captures spatial and temporal dynamics of hydrological and biogeochemical processes in WS10. We then examine the catchment response to alternative clear-cut scenarios for which the location and fraction of harvested area varied. These alternative clear-cut simulations suggest that the streamflow and harvest area relationship in this rain-dominated catchment is nearly linear, irrespective of clear-cut area and location. Simulations designed to identify threshold responses of DOC, DON and DIN export in relation to harvest area and location will be presented.
[Show abstract][Hide abstract] ABSTRACT: Pattern formation in vegetated communities reflects the underlying mechanisms governing resource utilization and distribution across the landscape. An example of a patterned ecosystem is the Florida Everglades, which is characterized by parallel and slightly elevated peat "ridges" separated by deeper water "slough" communities (R&S). Ridges are dominated by sawgrass (Cladium jamaiscence). These patterns are thought to be aligned with and develop in response to the historic surface water flow direction, though the precise mechanisms which lead to their formation are poorly understood. Over the years this R&S habitat has degraded in areas where the natural flow regime, hydroperiod, and water depths have been impacted by human development. Managing and restoring this habitat has been an objective of the U.S. Federal and Florida State governments since the Comprehensive Everglades Restoration Plan (CERP) was authorized in 2000. It is imperative, however, to develop a mechanistic understanding of ridge-slough formation before the potential benefits of hydrologic forecasts associated with CERP can be evaluated. Recently, Cheng et al (see Cheng et al, session NG14) employed a simple 2D advection-diffusion model developed by Rietkerk et al (2004) to describe for the first time, the formation of parallel stripes from hydrologic interactions. To simulate parallel stripes, Cheng et al retained the basic equations of the Rietkerk model but allowed for constant advection of water and nutrient in one direction to simulate slope conditions, with evapotranspiration driven advection of water and nutrient perpendicular to the downhill flow direction. We employ this modeling framework and parameterize the model with Everglades field data to simulate ridge-slough formation. In this model, the relatively higher rates of evapotranspiration on the ridges compared to the sloughs create hydraulic gradients which carry dissolved nutrients from the sloughs to the faster growing ridges. With time, the patches aggregate and spread laterally in the direction of the downhill flow. The characteristic wavelengths and spatial patterning of the ridge-slough habitat found in the historic Everglades is reproduced by the model. Nutrient distributions across the landscape and across the ridge-slough interfaces also match observations. Perturbations to the system are modeled in the form of altered hydraulic gradients and nutrient input functions, similar to actual stressors on the system. Under the altered conditions, a loss of patterning in the habitat is observed, in some cases leading to ridge expansion into the sloughs, and in others leading to a complete loss of vegetation pattern. Simulations indicate that the hydrologic changes required to regenerate coherence in the ridge slough patterns in degraded areas are different from those in which the system originally formed. Plant-nutrient interactions and the overall nutrient status are shown to be a major determinant in how the system will respond to hydrologic changes associated with CERP.
[Show abstract][Hide abstract] ABSTRACT: Background/Question/Methods Are the predictions of a simple ecosystem C flux model that was well corroborated with chamber data consistent with eddy-flux time series data? Is there information in the eddy-flux time series that can be used to improve the model? We embedded a simple model of arctic carbon exchange into the Ensemble Kalman Filter (EnKF) and used it to assimilate data from an eddy-covariance tower located in moist tussock tundra on the North Slope of Alaska. The model predicts net ecosystem carbon exchange based only on leaf area, irradiance, and temperature and has been well corroborated for all the major vegetation types in the low Arctic using chamber-based data. This is the first application of the model to eddy-covariance data. We modified the EnKF by adding an adaptive noise estimator that provides a feedback between persistent model-data deviations and the noise added to the ensemble of Monte-Carlo simulations in the EnKF. Because the leaf area index (LAI) within the tower foot print is difficult to quantify, we augmented the Kalman state vector with a parameter representing LAI and allowed LAI to adapt through time, providing a model-EnKF-based estimate of LAI. The adaptation of LAI also compensated for latent variables missing from the model structure and thereby allowed us to test the model based on deviations of the LAI trajectory from expectation.
Results/Conclusions On a weekly time scale, the EnKF estimates of LAI followed a general trend expected of canopy phenology. However, there were also nonrandom, diel deviations in the LAI estimates. Although the model tracked the eddy-covariance data closely, these deviations indicate an inadequate representation of some latent variable missing from the model. The latent variable might be associated with daily fluctuations in the metabolism of the ecosystem. For example the deviations are consistent with vapor pressure driven stomatal closure. The deviations are also correlated with changes in wind direction, which would change the tower footprint. However, the deviations could equally be associated with responses of the open-path eddy-covariance instrumentation to changes in temperature and humidity. A distinction among these possibilities could not be made based on the data available.
[Show abstract][Hide abstract] ABSTRACT: We employ a simple 2-D model to explore vegetation growth and development on an initially bare hillslope. We show how vegetation evolves from simple unconnected patches into complex patterns that optimize resource allocation. This optimization (and additional system complexity) leads to greater system stability and resilience. During the period of spatial optimization, biomass growth is zero, system entropy is unexpectedly dropping, and information content is rising, which suggests phase-change like behavior. We further show that optimization leads to hysteretic growth-death trajectories. A series of simulations are employed to explore issues of nutrient limitation. Finally, we examine another system characterized by striped vegetation patterns, specifically those found in the Florida Everglades.