Multiscale landscape and wetland drivers of lake total phosphorus and water color

Fergus, C. Emi; Soranno, Patricia A.; Cheruvelil, Kendra Spence; Bremigan, Mary T.

doi:10.4319/lo.2011.56.6.2127

Cited by 46 publications

(38 citation statements)

References 52 publications

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“…Landscape data were quantified at two spatial scales: local and regional. Local features were quantified within a 500‐m buffer around lakes, a measure that is strongly correlated with landscape features in the watershed (Fergus et al . 2011).…”

Section: Case Study – Understanding Drivers Of Lake Nutrients At Subcmentioning

confidence: 99%

Cross‐scale interactions: quantifying multi‐scaled cause–effect relationships in macrosystems

Soranno

Cheruvelil

Bissell

et al. 2014

Frontiers in Ecol & Environ

172

148

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Ecologists are increasingly discovering that ecological processes are made up of components that are multi‐scaled in space and time. Some of the most complex of these processes are cross‐scale interactions (CSIs), which occur when components interact across scales. When undetected, such interactions may cause errors in extrapolation from one region to another. CSIs, particularly those that include a regional scaled component, have not been systematically investigated or even reported because of the challenges of acquiring data at sufficiently broad spatial extents. We present an approach for quantifying CSIs and apply it to a case study investigating one such interaction, between local and regional scaled land‐use drivers of lake phosphorus. Ultimately, our approach for investigating CSIs can serve as a basis for efforts to understand a wide variety of multi‐scaled problems such as climate change, land‐use/land‐cover change, and invasive species.

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Section: Case Study – Understanding Drivers Of Lake Nutrients At Subcmentioning

confidence: 99%

Cross‐scale interactions: quantifying multi‐scaled cause–effect relationships in macrosystems

Soranno

Cheruvelil

Bissell

et al. 2014

Frontiers in Ecol & Environ

172

148

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“…We expect that ratios may be related to drivers if one nutrient responds strongly to a driver but the other is unaffected (single nutrient response). For example, wetlands are known to act as a sink for phosphorus in watersheds, but they can also act as a source of phosphorus when there is a low percentage of agriculture in the basin (Fergus et al 2011). In principle, prior knowledge on whether the major drivers of N and P vary across space should inform patterns of nutrient stoichiometry, but that remains largely unknown.…”

Section: Introductionmentioning

confidence: 99%

Lake nutrient stoichiometry is less predictable than nutrient concentrations at regional and sub‐continental scales

Collins

Oliver

Lapierre

et al. 2017

Ecological Applications

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Production in many ecosystems is co-limited by multiple elements. While a known suite of drivers associated with nutrient sources, nutrient transport, and internal processing controls concentrations of phosphorus (P) and nitrogen (N) in lakes, much less is known about whether the drivers of single nutrient concentrations can also explain spatial or temporal variation in lake N:P stoichiometry. Predicting stoichiometry might be more complex than predicting concentrations of individual elements because some drivers have similar relationships with N and P, leading to a weak relationship with their ratio. Further, the dominant controls on elemental concentrations likely vary across regions, resulting in context dependent relationships between drivers, lake nutrients and their ratios. Here, we examine whether known drivers of N and P concentrations can explain variation in N:P stoichiometry, and whether explaining variation in stoichiometry differs across regions. We examined drivers of N:P in ~2,700 lakes at a sub-continental scale and two large regions nested within the sub-continental study area that have contrasting ecological context, including differences in the dominant type of land cover (agriculture vs. forest). At the sub-continental scale, lake nutrient concentrations were correlated with nutrient loading and lake internal processing, but stoichiometry was only weakly correlated to drivers of lake nutrients. At the regional scale, drivers that explained variation in nutrients and stoichiometry differed between regions. In the Midwestern U.S. region, dominated by agricultural land use, lake depth and the percentage of row crop agriculture were strong predictors of stoichiometry because only phosphorus was related to lake depth and only nitrogen was related to the percentage of row crop agriculture. In contrast, all drivers were related to N and P in similar ways in the Northeastern U.S. region, leading to weak relationships between drivers and stoichiometry. Our results suggest ecological context mediates controls on lake nutrients and stoichiometry. Predicting stoichiometry was generally more difficult than predicting nutrient concentrations, but human activity may decouple N and P, leading to better prediction of N:P stoichiometry in regions with high anthropogenic activity.

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“…While the relationships between single driver-response pairs are well-characterized in the literature (e.g., Kirchner 1975), surprising and complex cross-scale interactions have been observed, especially when drivers acting on multiple scales are considered . For example, agricultural activity within a watershed influences lake water quality, but this relationship may be dependent on interactions with local wetlands (Fergus et al 2011) and lake depth (Nielsen et al 2012). Because multiple drivers interact across multiple scales to affect lake water quality, simple scaling from a small number of well-studied systems to a collection of many lakes across the landscape may not be adequate to represent large-scale aquatic ecosystem processes.…”

Section: Introductionmentioning

confidence: 99%

The importance of lake‐specific characteristics for water quality across the continental United States

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Patil

Oliver

et al. 2015

Ecological Applications

115

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Abstract. Lake water quality is affected by local and regional drivers, including lake physical characteristics, hydrology, landscape position, land cover, land use, geology, and climate. Here, we demonstrate the utility of hypothesis testing within the landscape limnology framework using a random forest algorithm on a national-scale, spatially explicit data set, the United States Environmental Protection Agency's 2007 National Lakes Assessment. For 1026 lakes, we tested the relative importance of water quality drivers across spatial scales, the importance of hydrologic connectivity in mediating water quality drivers, and how the importance of both spatial scale and connectivity differ across response variables for five important in-lake water quality metrics (total phosphorus, total nitrogen, dissolved organic carbon, turbidity, and conductivity). By modeling the effect of water quality predictors at different spatial scales, we found that lake-specific characteristics (e.g., depth, sediment area-tovolume ratio) were important for explaining water quality (54-60% variance explained), and that regionalization schemes were much less effective than lake specific metrics (28-39% variance explained). Basin-scale land use and land cover explained between 45-62% of variance, and forest cover and agricultural land uses were among the most important basin-scale predictors. Water quality drivers did not operate independently; in some cases, hydrologic connectivity (the presence of upstream surface water features) mediated the effect of regional-scale drivers. For example, for water quality in lakes with upstream lakes, regional classification schemes were much less effective predictors than lake-specific variables, in contrast to lakes with no upstream lakes or with no surface inflows. At the scale of the continental United States, conductivity was explained by drivers operating at larger spatial scales than for other water quality responses. The current regulatory practice of using regionalization schemes to guide water quality criteria could be improved by consideration of lake-specific characteristics, which were the most important predictors of water quality at the scale of the continental United States. The spatial extent and high quality of contextual data available for this analysis makes this work an unprecedented application of landscape limnology theory to water quality data. Further, the demonstrated importance of lake morphology over other controls on water quality is relevant to both aquatic scientists and managers.

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Multiscale landscape and wetland drivers of lake total phosphorus and water color

Cited by 46 publications

References 52 publications

Cross‐scale interactions: quantifying multi‐scaled cause–effect relationships in macrosystems

Cross‐scale interactions: quantifying multi‐scaled cause–effect relationships in macrosystems

Lake nutrient stoichiometry is less predictable than nutrient concentrations at regional and sub‐continental scales

The importance of lake‐specific characteristics for water quality across the continental United States

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