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Tyler Wagner

Publications and source records attributed to Tyler Wagner.

At least 91 records · Page 5Linked to original sources
USGS2018

Walleye recruitment success is less resilient to warming water temperatures in lakes with abundant largemouth bass populations

Lakes respond heterogeneously to climate, with implications for fisheries management. We analyzed walleye ( Sander vitreus ) recruitment to age-0 in 359 lakes in Wisconsin, USA, to ( i ) quantify the relationship between annual water temperature degree days (DD) and walleye recruitment success and ( ii ) identify the influence of lake characteristics — area, conductivity, largemouth bass ( Micropterus salmoides ) catch rates, and mean DD — on this relationship. The relationship between walleye recruitment and annual DD varied among lakes and was not distinguishable from zero overall (posterior mean = −0.11, 90% CI = −0.34, 0.15). DD effects on recruitment were negative in 198 lakes (55%) and positive in 161 (45%). The effect of annual DD was most negative in lakes with high largemouth bass densities, and, on average, the probability of recruitment was highest in large lakes with low largemouth bass densities. Conductivity and mean DD influenced neither recruitment nor the effect of annual DD. Walleye recruitment was most resilient to warming in lakes with few largemouth bass, suggesting that the effects of climate change depend on lake-specific food-web and habitat contexts.

Wisconsin↗
USGS2018

Evaluating spatial and temporal variability in growth and mortality for recreational fisheries with limited catch data

Understanding the spatial and temporal variability in life-history traits among populations is essential for the management of recreational fisheries. However, valuable freshwater recreational fish species often suffer from a lack of catch information. In this study, we demonstrated the use of an approach to estimate the spatial and temporal variability in growth and mortality in the absence of catch data and apply the method to riverine smallmouth bass ( Micropterus dolomieu ) populations in Pennsylvania, USA. Our approach included a growth analysis and a length-based analysis that estimates mortality. Using a hierarchical Bayesian approach, we examined spatial variability in growth and mortality by assuming parameters vary spatially but remain constant over time and temporal variability by assuming parameters vary spatially and temporally. The estimated growth and mortality of smallmouth bass showed substantial variability over time and across rivers. We explored the relationships of the estimated growth and mortality with spring water temperature and spring flow. Growth rate was likely to be positively correlated with these two factors, while young mortality was likely to be positively correlated with spring flow. The spatially and temporally varying growth and mortality suggest that smallmouth bass populations across rivers may respond differently to management plans and disturbance such as environmental contamination and land-use change. The analytical approach can be extended to other freshwater recreational species that also lack of catch data. The approach could also be useful in developing population assessments with erroneous catch data or be used as a model sensitivity scenario to verify traditional models even when catch data are available.

Pennsylvania↗
USGS2017

Macroscale patterns of synchrony identify complex relationships among spatial and temporal ecosystem drivers

Ecology has a rich history of studying ecosystem dynamics across time and space that has been motivated by both practical management needs and the need to develop basic ideas about pattern and process in nature. In situations in which both spatial and temporal observations are available, similarities in temporal behavior among sites (i.e., synchrony) provide a means of understanding underlying processes that create patterns over space and time. We used pattern analysis algorithms and data spanning 22–25 yr from 601 lakes to ask three questions: What are the temporal patterns of lake water clarity at sub‐continental scales? What are the spatial patterns (i.e., geography) of synchrony for lake water clarity? And, what are the drivers of spatial and temporal patterns in lake water clarity? We found that the synchrony of water clarity among lakes is not spatially structured at sub‐continental scales. Our results also provide strong evidence that the drivers related to spatial patterns in water clarity are not related to the temporal patterns of water clarity. This analysis of long‐term patterns of water clarity and possible drivers contributes to understanding of broad‐scale spatial patterns in the geography of synchrony and complex relationships between spatial and temporal patterns across ecosystems.

Ecosphere↗
USGS2017

Evidence for regional nitrogen stress on chlorophyll a in lakes across large landscape and climate gradients

Nitrogen (N) and phosphorus (P) commonly stimulate phytoplankton production in lakes, but recent observations from lakes from an agricultural region suggest that nitrate may have a subsidy‐stress effect on chlorophyll a (Chl a ). It is unclear, however, how generalizable this effect might be. Here, we analyzed a large water quality dataset of 2385 lakes spanning 60 regions across 17 states in the Northeastern and Midwestern U.S. to determine if N subsidy‐stress effects on phytoplankton are common and to identify regional landscape characteristics promoting N stress effects in lakes. We used a Bayesian hierarchical modeling framework to test our hypothesis that Chl a –total N (TN) threshold relationships would be common across the central agricultural region of the U.S. (“the Corn Belt”), where lake N and P concentrations are high. Data aggregated across all regions indicated that high TN concentrations had a negative effect on Chl a in lakes with concurrent high total P. This large‐scale pattern was driven by relationships within only a subset of regions, however. Eight regions were identified as having Chl a –TN threshold relationships, but only two of these regions located within the Corn Belt clearly demonstrated this subsidy‐stress relationship. N stress effects were not consistent across other intense agricultural regions, as we hypothesized. These findings suggest that interactions among regional land use and land cover, climate, and hydrogeology may be important in determining the synergistic conditions leading to N subsidy‐stress effects on lake phytoplankton.

Limnology and Oceanography↗
USGS2017

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.

Connecticut, Iowa, Illinois, Indiana, Massachusett↗
USGS2017

Unexpected stasis in a changing world: Lake nutrient and chlorophyll trends since 1990

The United States (U.S.) has faced major environmental changes in recent decades, including agricultural intensification and urban expansion, as well as changes in atmospheric deposition and climate—all of which may influence eutrophication of freshwaters. However, it is unclear whether or how water quality in lakes across diverse ecological settings has responded to environmental change. We quantified water quality trends in 2913 lakes using nutrient and chlorophyll (Chl) observations from the Lake Multi-Scaled Geospatial and Temporal Database of the Northeast U.S. (LAGOS-NE), a collection of preexisting lake data mostly from state agencies. LAGOS-NE was used to quantify whether lake water quality has changed from 1990 to 2013, and whether lake-specific or regional geophysical factors were related to the observed changes. We modeled change through time using hierarchical linear models for total nitrogen (TN), total phosphorus (TP), stoichiometry (TN:TP), and Chl. Both the slopes (percent change per year) and intercepts (value in 1990) were allowed to vary by lake and region. Across all lakes, TN declined at a rate of 1.1% year −1 , while TP, TN:TP, and Chl did not change. A minority (7%–16%) of individual lakes had changing nutrients, stoichiometry, or Chl. Of those lakes that changed, we found differences in the geospatial variables that were most related to the observed change in the response variables. For example, TN and TN:TP trends were related to region-level drivers associated with atmospheric deposition of N; TP trends were related to both lake and region-level drivers associated with climate and land use; and Chl trends were found in regions with high air temperature at the beginning of the study period. We conclude that despite large environmental change and management efforts over recent decades, water quality of lakes in the Midwest and Northeast U.S. has not overwhelmingly degraded or improved.

Global Change Biology↗
USGS2017

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

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.

Ecological Applications↗
USGS2017

Fall and winter survival of brook trout and brown trout in a north-central Pennsylvania watershed

Stream-dwelling salmonids that spawn in the fall generally experience their lowest survival during the fall and winter due to behavioral changes associated with spawning and energetic deficiencies during this time of year. We used data from Brook Trout Salvelinus fontinalis and Brown Trout Salmo trutta implanted with radio transmitters in tributaries of the Hunts Run watershed of north-central Pennsylvania to estimate survival from the fall into the winter seasons (September 2012–February 2013). We examined the effects that individual-level covariates (trout species, size, and movement rates) and stream-level covariates (individual stream and cumulative drainage area of a stream) have on survival. Brook Trout experienced significantly lower survival than Brown Trout, especially in the early fall during their peak spawning period. Besides a significant species effect, none of the other covariates examined influenced survival for either species. A difference in life history between these species, with Brook Trout having a shorter life expectancy than Brown Trout, is likely the primary reason for the lower survival of Brook Trout. However, Brook Trout also spawn earlier in the fall than Brown Trout and low flows during Brook Trout spawning may have resulted in a greater risk of predation for Brook Trout compared with Brown Trout, thereby also contributing to the observed differences in survival between these species. Our estimates of survival can aid parameterization of future population models for Brook Trout and Brown Trout through the spawning season and into winter.

Pennsylvania↗
USGS2017

Evaluation of genetic population structure of smallmouth bass in the Susquehanna River basin, Pennsylvania

The Smallmouth Bass Micropterus dolomieu was introduced into the Susquehanna River basin, Pennsylvania, nearly 150 years ago. Since introduction, it has become an economically and ecologically important species that supports popular recreational fisheries. It is also one of the most abundant top predators in the system. Currently, there is no information on the level of genetic diversity or genetic structuring that may have occurred since introduction. An understanding of genetic diversity is important for the delineation of management units and investigation of gene flow at various management scales. The goals of this research were to investigate population genetic structure of Smallmouth Bass at sites within the Susquehanna River basin and to assess genetic differentiation relative to Smallmouth Bass at an out-of-basin site (Allegheny River, Pennsylvania) located within the species’ native range. During spring 2015, fin clips ( n = 1,034) were collected from adults at 11 river sites and 13 tributary sites in the Susquehanna River basin and at one site on the Allegheny River. Fin clips were genotyped at 12 polymorphic microsatellite loci. Based on our results, adults sampled throughout the Susquehanna River basin did not represent separate genetic populations. There were only subtle differences in genetic diversity among sites (mean pairwise genetic differentiation index F ST = 0.012), and there was an overall lack of population differentiation ( K = 3 admixed populations). The greatest genetic differentiation was observed between fish collected from the out-of-basin site and those from the Susquehanna River basin sites. Knowledge that separate genetic populations of Smallmouth Bass do not exist in the Susquehanna River basin is valuable information for fisheries management in addition to providing baseline genetic data on an introduced sport fish population.

Pennsylvania↗
USGS2017

Population dynamics of brown trout (Salmo trutta) in Spruce Creek Pennsylvania: A quarter-century perspective

We examined the relationship between density-independent and density-dependent factors on the demography of a dense, relatively unexploited population of brown trout in Spruce Creek Pennsylvania between 1985 and 2011. Individual PCAs of flow and temperature data elucidated groups of years with multiple high flow versus multiple low flow characteristics and high versus low temperature years, although subtler patterns of variation also were observed. Density and biomass displayed similar temporal patterns, ranging from 710 to 1,803 trout/ha and 76–263 kg/ha. We detected a significantly negative linear stock-recruitment relationship ( R 2 = .39) and there was no evidence that flow or water temperature affected recruitment. Both annual survival and the per-capita rate of increase ( r ) for the population varied over the study, and density-dependent mechanisms possessed the greatest explanatory power for annual survival data. Temporal trends in population r suggested it displayed a bounded equilibrium with increases observed in 12 years and decreases detected in 13 years. Model selection analysis of per-capita rate of increase data for age 1, and adults ( N = eight interpretable models) indicated that both density-dependent (five of eight) and negative density-independent processes (five of eight, i.e. high flows or temperatures), affected r . Recruitment limitation also was identified in three of eight models. Variation in the per-capita rate of increase for the population was most strongly affected by positive density independence in the form of increasing spring–summer temperatures and recruitment limitation. Model selection analyses describing annual variation in both mean length and mass data yielded similar results, although maximum w i values were low ranging from 0.09 to 0.23 (length) and 0.13 to 0.22 (mass). Density-dependence was included in 15 of 15 interpretable models for length and all ten interpretable models for mass. Similarly, positive density-independent effects in the form of increasing autumn–winter flow were present in seven of 15 interpretable models for length and five of ten interpretable models for mass. Negative density independent effects also were observed in the form of high spring–summer flows or temperatures ( N = 4), or high autumn–winter temperatures ( N = 1). Our analyses of the factors affecting population regulation in an introduced population of brown trout demonstrate that density-dependent forces affected every important demographic characteristic (recruitment, survivorship, the rate of increase, and size) within this population. However, density-independent forces in the form of seasonal variations in flow and temperature also helped explain annual variation in the per-capita rate of increase, and mean length and mass data. Consequently, population regulation within this population is driven by a complex of biotic and environmental factors, although it seems clear that density-dependent factors play a dominant role.

Pennsylvania↗
USGS2017

Using variance structure to quantify responses to perturbation in fish catches

We present a case study evaluation of gill-net catches of Walleye Sander vitreus to assess potential effects of large-scale changes in Oneida Lake, New York, including the disruption of trophic interactions by double-crested cormorants Phalacrocorax auritus and invasive dreissenid mussels. We used the empirical long-term gill-net time series and a negative binomial linear mixed model to partition the variability in catches into spatial and coherent temporal variance components, hypothesizing that variance partitioning can help quantify spatiotemporal variability and determine whether variance structure differs before and after large-scale perturbations. We found that the mean catch and the total variability of catches decreased following perturbation but that not all sampling locations responded in a consistent manner. There was also evidence of some spatial homogenization concurrent with a restructuring of the relative productivity of individual sites. Specifically, offshore sites generally became more productive following the estimated break point in the gill-net time series. These results provide support for the idea that variance structure is responsive to large-scale perturbations; therefore, variance components have potential utility as statistical indicators of response to a changing environment more broadly. The modeling approach described herein is flexible and would be transferable to other systems and metrics. For example, variance partitioning could be used to examine responses to alternative management regimes, to compare variability across physiographic regions, and to describe differences among climate zones. Understanding how individual variance components respond to perturbation may yield finer-scale insights into ecological shifts than focusing on patterns in the mean responses or total variability alone.

Transactions of the American Fisheries Society↗
USGS2017

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 km 2 ); (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.

Ecology and Evolution↗
USGS2017

Annual changes in seasonal river water temperatures in the eastern and western United States

Changes in river water temperatures are anticipated to have direct effects on thermal habitat and fish population vital rates, and therefore, understanding temporal trends in water temperatures may be necessary for predicting changes in thermal habitat and how species might respond to such changes. However, many investigations into trends in water temperatures use regression methods that assume long-term monotonic changes in temperature, when in fact changes are likely to be nonmonotonic. Therefore, our objective was to highlight the need and provide an example of an analytical method to better quantify the short-term, nonmonotonic temporal changes in thermal habitat that are likely necessary to determine the effects of changing thermal conditions on fish populations and communities. To achieve this objective, this study uses Bayesian dynamic linear models (DLMs) to examine seasonal trends in river water temperatures from sites located in the eastern and western United States, regions that have dramatically different riverine habitats and fish communities. We estimated the annual rate of change in water temperature and found little evidence of seasonal changes in water temperatures in the eastern U.S. We found more evidence of warming for river sites located in the western U.S., particularly during the fall and winter seasons. Use of DLMs provided a more detailed view of temporal dynamics in river thermal habitat compared to more traditional methods by quantifying year-to-year changes and associated uncertainty, providing managers with the information needed to adapt decision making to short-term changes in habitat conditions that may be necessary for conserving aquatic resources in the face of a changing climate.

Upper Colorado River Basin↗
USGS2017

Catchment-scale determinants of nonindigenous minnow richness in the eastern United States

Understanding the drivers of biological invasions is critical for preserving aquatic biodiversity. Stream fishes make excellent model taxa for examining mechanisms driving species introduction success because their distributions are naturally limited by catchment boundaries. In this study, we compared the relative importance of catchment-scale abiotic and biotic predictors of native and nonindigenous minnow (Cyprinidae) richness in 170 catchments throughout the eastern United States. We compared historic and contemporary cyprinid distributional data to determine catchment-wise native/nonindigenous status for 152 species. Catchment-scale model predictor variables described natural (elevation, precipitation, flow accumulation) and anthropogenic (developed land cover, number of dams) abiotic features, as well as native congener richness. Native congener richness may represent either biotic resistance via interspecific competition, or trait preadaptation according to Darwin's naturalisation hypothesis. We used generalised linear mixed models to examine evidence supporting the relative roles of abiotic and biotic predictors of cyprinid introduction success. Native congener richness was positively correlated with nonindigenous cyprinid richness and was the most important variable predicting nonindigenous cyprinid richness. Mean elevation had a weak positive effect, and effects of other abiotic factors were insignificant and less important. Our results suggest that at this spatial scale, trait preadaptation may be more important than intrageneric competition for determining richness of nonindigenous fishes.

Ecology of Freshwater Fish↗
USGS2017

Can personality predict individual differences in brook trout spatial learning ability?

While differences in individual personality are common in animal populations, understanding the ecological significance of variation has not yet been resolved. Evidence suggests that personality may influence learning and memory; a finding that could improve our understanding of the evolutionary processes that produce and maintain intraspecific behavioural heterogeneity. Here, we tested whether boldness, the most studied personality trait in fish, could predict learning ability in brook trout. After quantifying boldness, fish were trained to find a hidden food patch in a maze environment. Stable landmark cues were provided to indicate the location of food and, at the conclusion of training, cues were rearranged to test for learning. There was a negative relationship between boldness and learning as shy fish were increasingly more successful at navigating the maze and locating food during training trials compared to bold fish. In the altered testing environment, only shy fish continued using cues to search for food. Overall, the learning rate of bold fish was found to be lower than that of shy fish for several metrics suggesting that personality could have widespread effects on behaviour. Because learning can increase plasticity to environmental change, these results have significant implications for fish conservation.

Behavioural Processes↗
USGS2017

Predation of freshwater fish in environments with elevated carbon dioxide

Carbon dioxide (CO 2 ) in fresh-water environments is poorly understood, yet in marine environments CO 2 can affect fish behaviour, including predator–prey relationships. To examine changes in predator success in elevated CO 2 , we experimented with predatory Micropterus salmoides and Pimephales promelas prey. We used a two-factor fully crossed experimental design; one factor was 4-day (acclimation) CO 2 concentration and the second factor CO 2 concentration during 20-min predation experiments. Both factors had three treatment levels, including ambient partial pressure of CO 2 ( p CO 2 ; 0–1000 μatm), low p CO 2 (4000–5000 μatm) and high p CO 2 (8000–10 000 μatm). Micropterus salmoides was exposed to both factors, whereas P. promelas was not exposed to the acclimation factor. In total, 83 of the 96 P. promelas were consumed ( n = 96 trials) and we saw no discernible effect of CO 2 on predator success or time to predation. Failed strikes and time between failed strikes were too infrequent to model. Compared with marine systems, our findings are unique in that we not only saw no changes in prey capture success with increasing CO 2 , but we also used CO 2 treatments that were substantially higher than those in past experiments. Our work demonstrated a pronounced resiliency of freshwater predators to elevated CO 2 exposure, and a starting point for future work in this area.

Marine and Freshwater Research↗
USGS2017

Multi-level multi-task learning for modeling cross-scale interactions in nested geospatial data

Predictive modeling of nested geospatial data is a challenging problem as the models must take into account potential interactions among variables defined at different spatial scales. These cross-scale interactions, as they are commonly known, are particularly important to understand relationships among ecological properties at macroscales. In this paper, we present a novel, multi-level multi-task learning framework for modeling nested geospatial data in the lake ecology domain. Specifically, we consider region-specific models to predict lake water quality from multi-scaled factors. Our framework enables distinct models to be developed for each region using both its local and regional information. The framework also allows information to be shared among the region-specific models through their common set of latent factors. Such information sharing helps to create more robust models especially for regions with limited or no training data. In addition, the framework can automatically determine cross-scale interactions between the regional variables and the local variables that are nested within them. Our experimental results show that the proposed framework outperforms all the baseline methods in at least 64% of the regions for 3 out of 4 lake water quality datasets evaluated in this study. Furthermore, the latent factors can be clustered to obtain a new set of regions that is more aligned with the response variables than the original regions that were defined a priori from the ecology domain.

Conference Paper↗
USGS2016

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.

Maine, Michigan, New York, Wisconsin↗