Disentangling natural and anthropogenic effects on benthic macroinvertebrate assemblages in western US streams.

Stream macroinvertebrate assemblages are shaped by natural and human-related factors that operate through complex hierarchical pathways. Quantifying these relationships can provide additional insights into stream ecological assessment. We applied a structural equation modeling framework to evaluate hypothesized pathways by which watershed, riparian, and in-stream factors affect benthic macroinvertebrate condition in the Western Mountains (WMT) and Xeric (XER) ecoregions in the United States. We developed a conceptual model grounded in theory, empirical evidence, and expert opinion to evaluate the following hypotheses: (1) macroinvertebrate assemblages are primarily driven by proximal, in-stream factors (e.g., water quality and physical habitat); (2) anthropogenic land uses affect macroinvertebrates indirectly by altering in-stream characteristics; and (3) riparian vegetation cover attenuates land use effects. We tested our model separately on three measures of benthic macroinvertebrate assemblage condition: ratio of observed-to-expected taxonomic richness (O/E); a multimetric index (MMI); and richness of Ephemeroptera, Plecoptera, and Trichoptera taxa (EPT). In the WMT, site-level riparian cover, in-stream physical habitat (relative bed stability), and water chemistry (total nitrogen) were the top three predictors of macroinvertebrate assemblages, each having over two times the magnitude of effect on macroinvertebrates compared with watershed-level predictors. In the arid XER, annual precipitation and stream flow characteristics were top predictors of macroinvertebrate assemblages and had similar magnitudes of effect as in-stream water chemistry. Path analyses revealed that land use activities in the watershed and at the stream site degraded macroinvertebrate assemblages indirectly by altering relative bed stability, water quality, and riparian cover/complexity. Increased riparian cover was associated with greater macroinvertebrate condition by reducing land use impacts on stream flow, streambed substrate, and water quality, but the pathways differed among ecoregions. In the WMT, site-level riparian cover affected macroinvertebrate assemblages partly through indirect pathways associated with greater streambed stability and reduced total nitrogen concentrations. In contrast, in the XER, watershed-level riparian cover affected macroinvertebrate assemblages through greater specific stream power. Identifying the relative effects of and pathways by which natural and anthropogenic factors affect macroinvertebrates can serve as a framework for prioritizing management and conservation efforts.

Natural and anthropogenic controls on lake water-level decline and evaporation-to-inflow ratio in the conterminous United States.

Lake water levels are integral to lake function, but hydrologic changes from land and water management may alter lake fluctuations beyond natural ranges. We constructed a conceptual model of multifaceted drivers of lake water-levels and evaporation-to-inflow ratio (Evap:Inflow). Using a structural equation modeling framework, we tested our model on 1) a national subset of lakes in the conterminous United States with minimal water management to describe natural drivers of lake hydrology and 2) five ecoregional subsets of lakes to explore regional variation in water management effects. Our model fit the national and ecoregional datasets and explained up to 47% of variation in Evap:Inflow, 38% of vertical water-level decline, and 79% of horizontal water-level decline (littoral exposure). For lakes with minimal water management, Evap:Inflow was related to lake depth (ß = -0.31) and surface inflow (ß = -0.44); vertical decline was related to annual climate (e.g., precipitation ß = -0.18) and water management (ß = -0.21); and horizontal decline was largely related to vertical decline (ß = 0.73) and lake morphometry (e.g., depth ß = -0.18). Anthropogenic effects varied by ecoregion and likely reflect differences in regional water management and climate. In the West, water management indicators were related to greater vertical decline (ß = 0.38), whereas in the Midwest, these indicators were related to more stable and full lake levels (ß = -0.22) even during drought conditions. National analyses show how human water use interacts with regional climate resulting in contrasting impacts to lake hydrologic variation in the US.

National framework for ranking lakes by potential for anthropogenic hydro-alteration.

Lakes face multiple anthropogenic pressures that can substantially alter their hydrology. Dams and land use in the watershed (e.g., irrigated agriculture) can modify lake water regimes beyond natural ranges, and changing climate may exacerbate anthropogenic stresses on lake hydrology. However, we lack cost-effective indicators to quantify anthropogenic hydrologic alteration potential in lakes at regional and national extents. We developed a framework to rank lakes by the potential for dams and land use to alter lake hydrology (HydrAP) that can be applied at a national scale. The HydrAP framework principles are that 1) dams are primary drivers of lake hydro-alteration, 2) land use activities are secondary drivers that alter watershed hydrology, and 3) topographic relief limits where land use and dams are located on the landscape. We ranked lakes in the United States Environmental Protection Agency National Lakes Assessment (NLA) on a HydrAP scale from zero to seven, where a zero indicates lakes with no potential for anthropogenic hydro-alteration, and a seven indicates large dams and/or intensive land use with high potential to alter lake hydrology. We inferred HydrAP population distributions in the conterminous US (CONUS) using the NLA probabilistic weights. Half of CONUS lakes had moderate to high hydro-alteration potential (HydrAP ranks 3-7), the other half had minimal to no hydro-alteration potential (HydrAP ranks 0-2). HydrAP ranks generally corresponded with natural and man-made lake classes, but >15% of natural lakes had moderate to high HydrAP ranks and ~10% of man-made lakes had low HydrAP ranks. The Great Plains, Appalachians, and Coastal Plains had the largest percentages (>50%) of high HydrAP lakes, and the West and Midwest had the lowest percentages (~30%). Water residence time (τ) and water-level change were associated with HydrAP ranks, demonstrating the framework's intended ability to differentiate anthropogenic stressors that can alter lake hydrology. Consistently across ecoregions high HydrAP lakes had shorter τ. But HydrAP relationships with water-level change varied by ecoregion. In the West and Appalachians, high HydrAP lakes experienced excessive water-level declines compared to low-ranked lakes. In contrast, high HydrAP lakes in the Great Plains and Midwest showed stable water levels compared to low-ranked lakes. These differences imply that water management in western and eastern mountainous regions may result in large water-level fluctuations, but water management in central CONUS may promote water-level stabilization. The HydrAP framework using accessible, national datasets can support large-scale lake assessments and be adapted to specific locations where data are available.

State of the ART: Using artificial refuge traps to control invasive crayfish in southern California streams.

Invasive species are a widespread threat to stream ecosystems across the planet. In Southern California, USA, the invasive red swamp crayfish Procambarus clarkii (Girard, 1852) poses a significant threat to native aquatic fauna. Studies have suggested that artificial refuge traps (ARTs) resembling crayfish burrows can be used to remove invasive crayfish, but, to date, no studies have focused on optimizing ART design and deployment to maximize crayfish catch. This month-long study tested the effect of modifications on ART diameter, color, and soak time on P. clarkii catch effectiveness across 160 traps. We evaluated catch data by creating multiple candidate generalized linear mixed models predicting P. clarkii catches with different modeling parameterizations and a priori hypothesized predictor variables. During the study period, ARTs removed a total of 240 red swamp crayfish with no incidental bycatch. Larger P. clarkii (2-6-cm carapace length) were found more frequently in 5.1-cm-diameter traps, and smaller P. clarkii (1-4 cm) were found more frequently in 2.5-cm-diameter traps. Catch numbers varied between trap types, with black-colored 5.1-cm-diameter traps removing the greatest amount of the total P. clarkii caught in the study (mean = 0.27, SD = 0.29; 35% of the total caught) and black-colored 2.5-cm-diameter traps removing the least amount (mean = 0.09, SD = 0.55; 12% of the total). Further, ART deployment duration was an important predictor variable for candidate models, where ARTs with 4-d and 7-d deployment durations had lower catch/unit effort than traps with 1-d and 2-d deployments. This factorial experiment is the 1st study to suggest specific design modifications to ARTs that optimize invasive red swamp crayfish removal without incurring non-target incidental bycatch. This study demonstrates that ARTs can be a valuable tool for conservation managers interested in restoring streams through invasive crayfish removal, especially where there are sensitive biological resources.

Lake Water Levels and Associated Hydrologic Characteristics in the Conterminous U.S.

Establishing baseline hydrologic characteristics for lakes in the U.S. is critical to evaluate changes to lake hydrology. We used the U.S. EPA National Lakes Assessment 2007 and 2012 surveys to assess hydrologic characteristics of a population of ~45,000 lakes in the conterminous U.S. based on probability samples of ~1,000 lakes/yr distributed across nine ecoregions. Lake hydrologic study variables include water-level drawdown (i.e., vertical decline and horizontal littoral exposure) and two water stable isotope-derived parameters: evaporation-to-inflow (E:I) and water residence time. We present 1) national and regional distributions of the study variables for both natural and man-made lakes and 2) differences in these characteristics between 2007 and 2012. In 2007, 59% of the population of U.S. lakes had Greater than normal or Excessive drawdown relative to water levels in ecoregional reference lakes with minimal human disturbances; while in 2012, only 20% of lakes were significantly drawn down beyond normal ranges. Water isotope-derived variables did not differ significantly between survey years in contrast to drawdown. Median E:I was 20% indicating that flow-through processes dominated lake water regimes. For 75% of U.S. lakes, water residence time was < 1 year and was longer in natural vs. man-made lakes. Our study provides baseline ranges to assess local and regional lake hydrologic status and inform management decisions in changing environmental conditions.

LAGOS-NE: a multi-scaled geospatial and temporal database of lake ecological context and water quality for thousands of US lakes.

Understanding the factors that affect water quality and the ecological services provided by freshwater ecosystems is an urgent global environmental issue. Predicting how water quality will respond to global changes not only requires water quality data, but also information about the ecological context of individual water bodies across broad spatial extents. Because lake water quality is usually sampled in limited geographic regions, often for limited time periods, assessing the environmental controls of water quality requires compilation of many data sets across broad regions and across time into an integrated database. LAGOS-NE accomplishes this goal for lakes in the northeastern-most 17 US states.LAGOS-NE contains data for 51 101 lakes and reservoirs larger than 4 ha in 17 lake-rich US states. The database includes 3 data modules for: lake location and physical characteristics for all lakes; ecological context (i.e., the land use, geologic, climatic, and hydrologic setting of lakes) for all lakes; and in situ measurements of lake water quality for a subset of the lakes from the past 3 decades for approximately 2600-12 000 lakes depending on the variable. The database contains approximately 150 000 measures of total phosphorus, 200 000 measures of chlorophyll, and 900 000 measures of Secchi depth. The water quality data were compiled from 87 lake water quality data sets from federal, state, tribal, and non-profit agencies, university researchers, and citizen scientists. This database is one of the largest and most comprehensive databases of its type because it includes both in situ measurements and ecological context data. Because ecological context can be used to study a variety of other questions about lakes, streams, and wetlands, this database can also be used as the foundation for other studies of freshwaters at broad spatial and ecological scales.

Creating multithemed ecological regions for macroscale ecology: Testing a flexible, repeatable, and accessible clustering method.

Understanding broad-scale ecological patterns and processes often involves accounting for regional-scale heterogeneity. A common way to do so is to include ecological regions in sampling schemes and empirical models. However, most existing ecological regions were developed for specific purposes, using a limited set of geospatial features and irreproducible methods. Our study purpose was to: (1) describe a method that takes advantage of recent computational advances and increased availability of regional and global data sets to create customizable and reproducible ecological regions, (2) make this algorithm available for use and modification by others studying different ecosystems, variables of interest, study extents, and macroscale ecology research questions, and (3) demonstrate the power of this approach for the research question-How well do these regions capture regional-scale variation in lake water quality? To achieve our purpose we: (1) used a spatially constrained spectral clustering algorithm that balances geospatial homogeneity and region contiguity to create ecological regions using multiple terrestrial, climatic, and freshwater geospatial data for 17 northeastern U.S. states (~1,800,000 km2); (2) identified which of the 52 geospatial features were most influential in creating the resulting 100 regions; and (3) tested the ability of these ecological regions to capture regional variation in water nutrients and clarity for ~6,000 lakes. We found that: (1) a combination of terrestrial, climatic, and freshwater geospatial features influenced region creation, suggesting that the oft-ignored freshwater landscape provides novel information on landscape variability not captured by traditionally used climate and terrestrial metrics; and (2) the delineated regions captured macroscale heterogeneity in ecosystem properties not included in region delineation-approximately 40% of the variation in total phosphorus and water clarity among lakes was at the regional scale. Our results demonstrate the usefulness of this method for creating customizable and reproducible regions for research and management applications.

Spatial Variation in Nutrient and Water Color Effects on Lake Chlorophyll at Macroscales.

The nutrient-water color paradigm is a framework to characterize lake trophic status by relating lake primary productivity to both nutrients and water color, the colored component of dissolved organic carbon. Total phosphorus (TP), a limiting nutrient, and water color, a strong light attenuator, influence lake chlorophyll a concentrations (CHL). But, these relationships have been shown in previous studies to be highly variable, which may be related to differences in lake and catchment geomorphology, the forms of nutrients and carbon entering the system, and lake community composition. Because many of these factors vary across space it is likely that lake nutrient and water color relationships with CHL exhibit spatial autocorrelation, such that lakes near one another have similar relationships compared to lakes further away. Including this spatial dependency in models may improve CHL predictions and clarify how well the nutrient-water color paradigm applies to lakes distributed across diverse landscape settings. However, few studies have explicitly examined spatial heterogeneity in the effects of TP and water color together on lake CHL. In this study, we examined spatial variation in TP and water color relationships with CHL in over 800 north temperate lakes using spatially-varying coefficient models (SVC), a robust statistical method that applies a Bayesian framework to explore space-varying and scale-dependent relationships. We found that TP and water color relationships were spatially autocorrelated and that allowing for these relationships to vary by individual lakes over space improved the model fit and predictive performance as compared to models that did not vary over space. The magnitudes of TP effects on CHL differed across lakes such that a 1 µg/L increase in TP resulted in increased CHL ranging from 2-24 µg/L across lake locations. Water color was not related to CHL for the majority of lakes, but there were some locations where water color had a positive effect such that a unit increase in water color resulted in a 2 µg/L increase in CHL and other locations where it had a negative effect such that a unit increase in water color resulted in a 2 µg/L decrease in CHL. In addition, the spatial scales that captured variation in TP and water color effects were different for our study lakes. Variation in TP-CHL relationships was observed at intermediate distances (~20 km) compared to variation in water color-CHL relationships that was observed at regional distances (~200 km). These results demonstrate that there are lake-to-lake differences in the effects of TP and water color on lake CHL and that this variation is spatially structured. Quantifying spatial structure in these relationships furthers our understanding of the variability in these relationships at macroscales and would improve model prediction of chlorophyll a to better meet lake management goals.

Building a multi-scaled geospatial temporal ecology database from disparate data sources: fostering open science and data reuse.

Although there are considerable site-based data for individual or groups of ecosystems, these datasets are widely scattered, have different data formats and conventions, and often have limited accessibility. At the broader scale, national datasets exist for a large number of geospatial features of land, water, and air that are needed to fully understand variation among these ecosystems. However, such datasets originate from different sources and have different spatial and temporal resolutions. By taking an open-science perspective and by combining site-based ecosystem datasets and national geospatial datasets, science gains the ability to ask important research questions related to grand environmental challenges that operate at broad scales. Documentation of such complicated database integration efforts, through peer-reviewed papers, is recommended to foster reproducibility and future use of the integrated database. Here, we describe the major steps, challenges, and considerations in building an integrated database of lake ecosystems, called LAGOS (LAke multi-scaled GeOSpatial and temporal database), that was developed at the sub-continental study extent of 17 US states (1,800,000 km(2)). LAGOS includes two modules: LAGOSGEO, with geospatial data on every lake with surface area larger than 4 ha in the study extent (~50,000 lakes), including climate, atmospheric deposition, land use/cover, hydrology, geology, and topography measured across a range of spatial and temporal extents; and LAGOSLIMNO, with lake water quality data compiled from ~100 individual datasets for a subset of lakes in the study extent (~10,000 lakes). Procedures for the integration of datasets included: creating a flexible database design; authoring and integrating metadata; documenting data provenance; quantifying spatial measures of geographic data; quality-controlling integrated and derived data; and extensively documenting the database. Our procedures make a large, complex, and integrated database reproducible and extensible, allowing users to ask new research questions with the existing database or through the addition of new data. The largest challenge of this task was the heterogeneity of the data, formats, and metadata. Many steps of data integration need manual input from experts in diverse fields, requiring close collaboration.