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.

Ecosystem metabolism and the contribution of carbon dioxide from lakes to the atmosphere can be estimated from free-water gas measurements through the use of mass balance models, which rely on a gas transfer coefficient (k) to model gas exchange with the atmosphere. Theoretical and empirically based models of k range in complexity from wind-driven power functions to complex surface renewal models; however, model choice is rarely considered in most studies of lake metabolism. This study used high-frequency data from 15 lakes provided by the Global Lake Ecological Observatory Network (GLEON) to study how model choice of k influenced estimates of lake metabolism and gas exchange with the atmosphere. We tested 6 models of k on lakes chosen to span broad gradients in surface area and trophic states; a metabolism model was then fit to all 6 outputs of k data. We found that hourly values for k were substantially different between models and, at an annual scale, resulted in significantly different estimates of lake metabolism and gas exchange with the atmosphere.

The nested blocks and guidelines model is a useful template for creating design and evaluation criteria, because it aligns design to need [17]. Characterizing the outermost block of the nested model-the domain problem-is challenging, mainly due to the nature of contemporary inquiries in various domains, which are dynamic and, by definition, difficult to problematize. We offer here our emerging conceptual framework, based on the central question in our research study-what visualization works for whom and in which situation, to consider when characterizing the outermost block, the domain problem, of the nested model [18].

In spite of their perceived value, the widespread implementation of ecosystem services assessments has been limited because of perceptions of being too technical, too expensive, or requiring special expertise. For example, federal estuary management programs have widely used ecosystem services concepts to frame management issues and communicate with stakeholders. Yet, indicators assessed, monitored, and reported in estuarine management still have traditionally focused on ecological conditions, with weak connections, if any, to social or economic outcomes. Approaches are needed which expand the range of ecosystem services that can be considered, link ecosystem services explicitly to different stakeholder groups, facilitate effective communication with economists and other social scientists, and expand the array of available valuation techniques. We applied the concept of final ecosystem goods and services to review the broad suite of ecosystem services and their beneficiaries relevant to the management of two federal programs for estuary management, the National Estuary Program (NEP) and the National Estuarine Research Reserve System (NERRS). The Final Ecosystem Goods and Services Classification System provided a structured framework for connecting ecosystem services to their beneficiaries and the environments providing them. Document analysis of management plans assessed the degree to which these programs consider ecosystem services, their beneficiaries, and habitats within the estuarine watershed. The hierarchical list of final ecosystem goods and services generated from document analysis serves as a tool for defining management goals, identifying stakeholders, developing meaningful indicators, and conducting valuation studies in estuarine management planning efforts. Though developed here for estuarine management, the keyword hierarchy and final ecosystem goods and services approach have broad applicability and transferability to other environmental management scenarios.

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The Visualization for Terrestrial and Aquatic Systems project (VISTAS) aims to help scientists produce effective environmental science visualizations for their own use and for use in presenting their work to a wide range of stakeholders (including other scientists, decision makers, and the public). The need for better visualization tools for environmental science is well-documented, but little prior work has been done to determine what kinds of visualizations work and with whom. The VISTAS research and development project has applied social science methods to this question, and has identified issues relevant to visualization software development, particularly where the application area involves wicked problems such as climate change. This paper presents visualization problems of scientists whose presentations of scientific results might be enhanced if they and software developers were consciously aware of the nature of so-called wicked problems and the considerations of non-scientist secondary users. While VISTAS focuses on visualization software, we believe results are generalizable to software in general. The primary lesson learned from our work is that extending the scope of the domain context will likely provide scientists with software that is more effective and relevant to nonscientist stakeholders, but that doing so can be time consuming and more costly unless the nature of the underlying science problem is recognized and characterized early in the product cycle.

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