A spatially explicit model of iron loading to lakes
نویسندگان
چکیده
Terrestrial and aquatic ecosystems are intimately linked by the export of elements from watersheds. Although export is influenced by land cover within watersheds, few models evaluate how the spatial configuration of land cover influences loading. In this study we examined spatial variation of land cover at a 10 3 10 m resolution by developing a mass balance, maximum likelihood model of lake iron (Fe) concentrations in 93 watersheds. The model estimated lake iron concentrations based on loading, within-lake processes and losses. Two models were developed. One considered loading from eight land cover types, whereas the second model included the distance of each grid cell to account for Fe losses along flow paths to the lake. In-lake production and losses were accounted for as a function of lake area, water color, and discharge. If we treated watersheds as homogeneous source areas, export was estimated as 450 mg Fe m22 yr21; however, in spatial models export varied from negligible to 5,400 mg Fe m22 yr21 based on differential loadings from eight cover types. Accounting for losses of Fe based on distance from the lake did not improve the model. Although areal export of Fe was greater from wetlands, upland forests dominate the landscape and thus accounted for on average 75% of the total Fe load. Fe losses from lakes were primarily regulated by discharge; however, water color and lake depth were also important. Overall, the analysis revealed that lake Fe concentrations are related to land cover based on strong differential Fe loadings. The chemical composition of a lake is influenced by several features of its watershed, including the area and spatial distribution of vegetation and land-use (Rasmussen et al. 1989; Gergel et al. 1999; Canham et al. 2004). Lake loading models have focused largely on determining the factors influencing the export of phosphorus, nitrogen, and dissolved organic carbon (DOC) because of their biological importance and impacts of human activity on the loading of these elements (Dillon and Molot 1997). There are also models to describe the inputs of toxic metals such as mercury and aluminum (Driscoll et al. 1995), but few models describe the loading and cycling of biologically important metals such as iron (Nürnberg and Dillon 1993). Iron is an essential micronutrient to all organisms with the exception of Lactobacillus. Iron is a cofactor for hemoglobin and for many important enzymes including those required for respiration, photosynthesis, and nitrogen metabolism (Hewitt 1983). Although iron (Fe) is the fourth most abundant element in the earth’s crust, Fe, in general, is not in a form that is readily available to organisms. In the presence of oxygen at biologically relevant pH, iron readily forms hydroxides and binds to other elements forming a variety of complexes. Indeed, the reactive nature of Fe often mediates 1 To whom correspondence should be addressed. Present address: Département des sciences biologiques, Université de Montréal, C.P. 6128, succursale centre-ville, Montréal QC H3C 3J7, Canada. ([email protected]). Acknowledgments We thank Heather Malcom, Denise Schmidt, Mark Maglienti, and Ben Conaway for excellent technical and field assistance, and comments from two anonymous reviewers greatly improved the manuscript. We also thank Edward McNeil for flying us in to some of the more remote lakes. This research was supported by an EPA grant to M.L.P. and C.D.C. R.M. was supported by an NSERC of Canada postdoctoral fellowship. This is a contribution to the Institute of Ecosystem Studies. the bioavailability, transformation, and mobilization of many elements, thus influencing the biogeochemical cycling of C, N, and P in both terrestrial and aquatic systems. In terrestrial ecosystems, the Fe oxide layer in soil Bhorizons plays an important role in regulating dissolved organic matter mobilization through the watershed (Moore et al. 1992). In highly calcareous soils, plants are often limited by the availability of Fe due to the formation of biologically inaccessible complexes (Morris et al. 1990). High concentrations of Fe in the humus layer can limit the availability of P to trees (Geisler et al. 2002). Recently, it has been suggested that through a series of dark oxidation and reduction reactions in the presence of DOC, Fe can transform NO3 into dissolved organic nitrogen species, enhancing N storage in soils (Davidson et al. 2003). In oxygenated aquatic environments with circum-neutral pH, Fe readily hydrolyzes and is deposited out of the water column (Stumm and Morgan 1996). Orthophosphate sorbs to these hydroxides and as a consequence is removed from the water column. Indeed the addition of Fe salts to eutrophied lakes has been used to precipitate and immobilize P to the sediment, thus reducing internal phosphorus loading (Smolders et al. 2001). However, in some cases when bottom waters of the hypolimnion become anaerobic, the Fe hydroxides become reduced and both Fe and P are released from lake sediments. Lakes that are brown have elevated concentrations of humic and fulvic acids. The aliphatic and aromatic carboxyl and hydroxyl functional groups of this DOC can readily bind Fe, thereby keeping Fe in the dissolved state in surface waters (Pullin and Canabiss 2003; McKnight et al. 2003). These Fe-DOC complexes also bind P, keeping this limiting element in suspension (Shaw et al. 2000). However the bioavailability of the Fe-P complex is unclear (Maranger and Pullin 2003). Indeed it has been suggested that Fe chelated to DOC is not readily available and may limit primary production in some lakes (Jackson and Hecky 1980).
منابع مشابه
Multiscale Spatial Sensitivity Analysis for Agent- Based Modelling of Coupled Landscape and Aquatic Systems
Models of coupled landscape and aquatic systems (CLAS) are prone to input uncertainties that vary over space. To address this challenge, we employ a comprehensive model evaluation that: [1] quantifies the variability of model results (uncertainty analysis), and [2] decomposes this variability based on the relative contribution of inputs to identify major drivers in the model (sensitivity analys...
متن کاملمدلسازی عددی جریانهای لایهبندی شدهی غیرهمسان با استفاده از مدل آشفتگی صریح جبری تنش رینولدز
Flows of natural hydro-environments are usually turbulent and mostly stratified, like the flows in lakes, reservoirs, estuaries and atmosphere to name a few. In stratified flows due to the buoyancy forces, the turbulent stresses are usually non-isotropic. Therefore the accuracy of the numerical simulations for such flows is highly dependent on the turbulence model and the implementation of non-...
متن کاملA review of acidity generation and consumption in acidic coal mine lakes and their watersheds.
Lakes developing in former coal mine pits are often characterized by high concentrations of sulfate and iron and low pH. The review focuses on the causes for and fate of acidity in these lakes and their watersheds. Acidification is primarily caused by the generation of ferrous iron bearing and mineralized groundwater, transport through the groundwater-surface water interface, and subsequent iro...
متن کاملModeling Spatial Distributions of Point and Nonpoint Source Pollution Loadings in the Great Lakes Watersheds
A physically based, spatially-distributed water quality model is being developed to simulate spatial and temporal distributions of material transport in the Great Lakes Watersheds of the U.S. Multiple databases of meteorology, land use, topography, hydrography, soils, agricultural statistics, and water quality were used to estimate nonpoint source loading potential in the study watersheds. Anim...
متن کاملERDC TN-SWWRP-10-1, Integration of an Individual-Based Fish Bioenergetics Model into a Spatially Explicit Water Quality Model (CE-QUAL-ICM)
PURPOSE: This technical note presents the results of incorporating a fish bioenergetics module into CE-QUAL-ICM, a spatially explicit eutrophication model. In addition to fish consumption of algae, zooplankton, and detritus, fish biomass accumulation and recycling to the water column are explicitly accounted for. Schools of fish are tracked individually, allowing for spatial resolution of their...
متن کامل