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

Abstract

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.

Combining nutrient, productivity, and landscape‐based regressions improves predictions of lake nutrients and provides insight into nutrient coupling at macroscales

“…The effects of landscape predictors on nutrientproductivity variables were as expected, and similar to those reported by other studies that examined landscape drivers of lake nutrients across large spatial extents (Wagner et al 2011;Read et al 2015;Collins et al 2017). In addition, we found the effects of landscape predictors to vary spatially (i.e., between subregions), which suggests regional differences in the dominant drivers of, and their effects on, lake nutrients and productivity.…”

“…The increase in use of landscape-based regression models is driven by the importance of lake morphometric properties and landscape characteristics to the source, delivery, and processing of nutrients in lakes (Soranno et al 1996;Carpenter et al 1998;Collins et al 2017). Likewise, empirical nutrient-productivity models are widely used because many nutrient-productivity variables are correlated with one another (Ostrofsky and Rigler 1987;Phillips et al 2008).…”

Similarity in spatial structure constrains ecosystem relationships: Building a macroscale understanding of lakes

“…Therefore, full interpretation of this simple model needs to account for known ecological relationships and the inherent spatial structure in the variables involved (Table ; Figure ). It appears that broad‐scale patterns in hydrology and land cover at regional and continental scales induce strong spatial structure in lake TP across the study extent, but that lake and catchment morphometry, which have been associated with terrestrial loadings and in‐lake processing of nutrients (Collins et al, ; Read et al, ), affect lake TP locally and tend to mute the broad‐scale effects (see Figure e). Along the same line, patterns in lake dissolved organic carbon (DOC) within an individual region are mainly related to lake area and perimeter (Frost et al, ), but at the global scale the main drivers are long‐term averages of precipitation, runoff and soil carbon content (Sobek, Tranvik, Prairie, Kortelainen, & Cole, ).…”

Functional shifts in lake zooplankton communities with hypereutrophication

“…However, zooplankton can also experience bottom-up growth limitation from imbalances in nutrient supply relative to their stoichiometric demand (Urabe, Clasen, & Sterner, 1997). Hypereutrophic lakes may function differently than oligotrophic lakes because the ratio of N:P supplied to lakes can still be above the threshold where primary production is P-limited while high P loading could shift zooplankton consumers below the threshold elemental ratio where excess P limits growth (Collins et al, 2017;Elser et al, 2016;Filstrup et al, 2014). Further, increased reliance on heterotrophic microbes in hypereutrophic systems may buffer taxa with flexible diets from these impacts (Christoffersen, Riemann, Hansen, Klysner, & Sørensen, 1990).…”