Geology topics

Gretchen J. A. Hansen

Publications and source records attributed to Gretchen J. A. Hansen.

15 recordsLinked to original sources

USGS2024

Asymmetric impacts of climate change on thermal habitat suitability for inland lake fishes

Climate change is altering the thermal habitats of freshwater fish species. We analyze modeled daily temperature profiles from 12,688 lakes in the US to track changes in thermal habitat of 60 lake fish species from different thermal guilds during 1980-2021. We quantify changes in each species’ preferred days, defined as the number of days per year when a lake contains the species’ preferred temperature. We find that cooler-water species are losing preferred days more rapidly than warmer-water species are gaining them. This asymmetric impact cannot be attributed to differences in geographic distribution among species; instead, it is linked to the seasonal dynamics of lake temperatures and increased thermal homogenization of the water column. The potential advantages of an increase in warmer-water species may not fully compensate for the losses in cooler-water species as warming continues, emphasizing the importance of mitigating climate change to support effective freshwater fisheries management.

Arkansas, Illinois, Indiana, Iowa, Michigan, Minne↗

USGS2022

Special section overview: Effects of ecosystem change on North American percid populations.

Walleye Sander vitreus , Sauger S. canadensis , and Yellow Perch Perca flavescens (referred to as percids herein) are collectively among the most culturally and ecologically important fish species in North America. As ecosystems change in response to environmental drivers, such as climate change, nutrient loading, and invasive species, there is a need to understand how percid populations respond to these changes. To address this need, a symposium was held during the 81st Annual Midwest Fish and Wildlife Conference to bring fishery scientists and managers together to describe and discuss percid population responses to ecosystem change. Prevailing symposium themes included the challenge of identifying mechanisms responsible for population-level changes, developing strategies to adaptively manage for resilient fisheries, and consideration of scale, context, and methods when interpreting variable results. Given the uncertainty of how ecosystem changes affect percid populations, participants emphasized the importance of communicating uncertainties to stakeholders, implementing data-driven management strategies, setting realistic goals, and revising management actions in an adaptive framework. There was universal agreement on both the challenge and necessity of facilitating constructive engagement among stakeholders in cooperative decision making. Symposium participants identified knowledge gaps and discussed future efforts to build on our current understanding of percid populations, including continuation of long-term monitoring, improved standardization of evaluation metrics, implementing adaptive management experiments to identify causal relationships, development of more robust analytical methods, use of historical data sources, and refining techniques to realistically convey management options to stakeholders.

North American Journal of Fisheries Management↗

USGS2022

Daily surface temperatures for 185,549 lakes in the conterminous United States estimated using deep learning (1980–2020)

The dataset described here includes estimates of historical (1980–2020) daily surface water temperature, lake metadata, and daily weather conditions for lakes bigger than 4 ha in the conterminous United States ( n = 185,549), and also in situ temperature observations for a subset of lakes ( n = 12,227). Estimates were generated using a long short-term memory deep learning model and compared to existing process-based and linear regression models. Model training was optimized for prediction on unmonitored lakes through cross-validation that held out lakes to assess generalizability and estimate error. On the held-out lakes with in situ observations, median lake-specific error was 1.24°C, and the overall root mean squared error was 1.61°C. This dataset increases the number of lakes with daily temperature predictions when compared to existing datasets, as well as substantially improves predictive accuracy compared to a prior empirical model and a debiased process-based approach (2.01°C and 1.79°C median error, respectively).

Limnology & Oceanography: Letters↗

USGS2021

Do lake-specific characteristics mediate the temporal relationship between walleye growth and warming water temperatures?

Walleye ( Sander vitreus ) population declines have been linked to climate change, but it is unclear how the growth of this cool-water species may be affected by warming water temperatures. Because warming rates vary among lakes, it is uncertain whether lake characteristics may mediate the temperature effects on walleye growth or may vary as a result of differences in lake habitat or productivity. In this study, we ( i ) quantified walleye annual growth from 1983 to 2015 in 61 lakes in midwestern United States; ( ii ) estimated the relationship between annual early life growth ( ω ; mm·year –1 ) and water growing degree days (GDD); and ( iii ) identified lake characteristics affecting log e ( ω )–GDD relationships. On average, ω estimates significantly increased with increasing GDD; however, this relationship varied in direction and magnitude among lakes. We estimated an 84% posterior probability of a negative effect of water clarity on the log e ( ω )–GDD relationship, suggesting that water clarity may mediate the effect of warming water temperatures by affecting the magnitude and direction of the log e ( ω )–GDD relationship. Our results provide insights into the conservation of cool-water species in a changing environment and identify lakes characteristics in which walleye growth may be more resilient to climate change.

Minnesota, Wisconsin↗

USGS2020

Indexing age-0 Walleye abundance in northern Wisconsin lakes Before fall

Age-0 Walleye Sander vitreus recruitment is often indexed using fall electrofishing surveys. However, collecting fish before fall may provide timely information regarding stocking decisions and factors influencing recruitment. We evaluated sampling methods for age-0 Walleye in northern Wisconsin lakes that could be used to assess recruitment in spring and summer. Initial assessments on two lakes indicated surface tows of ichthyoplankton nets at night during May-early June and 0.64-cm micromesh gill nets set in July provided highest catches of age-0 Walleye among the methods we evaluated. Additional sampling on 13 lakes over two years indicated catch-per-effort (CPE) of age-0 Walleye using these two methods did not correlate with age-0 CPE in fall electrofishing. However, presence or absence of age-0 Walleye in micromesh gill nets was 92% accurate in predicting whether age-0 CPE in fall electrofishing was ≥ 15 fish/h, the threshold above which eventual recruitment to the fishery is expected to occur. Micromesh gill netting may provide a useful tool for allocating fingerling Walleye that are stocked in fall, a resource that is often limited due to space and forage constraints associated with propagation. Additionally, our sampling protocol may help to identify timing of potential recruitment bottlenecks occurring in some lakes.

Wisconsin↗

USGS2020

Walleye growth declines following zebra mussel and Bythotrephes invasion

Invasive species represent a threat to aquatic ecosystems globally; however, impacts can be heterogenous across systems. Documented impacts of invasive zebra mussels ( Dreissena polymorpha ) and spiny water fleas ( Bythotrephes cederströmii ; hereafter Bythotrephes ) on native fishes are variable and context dependent across locations and time periods. Here, we use a hierarchical Bayesian analysis of a 35-year dataset on two fish species from 9 lakes to demonstrate that early life growth of ecologically important fishes are influenced by these aquatic invasive species. Walleye ( Sander vitreus ) in their first year of life grew more slowly in the presence of either invader after correcting for temperature (measured by degree days), and were on average 12 or 14% smaller at the end of their first summer following invasion by Bythotrephes or zebra mussels, respectively. Yellow perch ( Perca flavescens ) growth was less affected by invasion. Yellow perch on average grew more slowly in their first year of life following invasion by zebra mussels, although this effect was not statistically distinguishable from zero. Early life growth of both walleye and yellow perch was less tightly coupled to degree days in invaded systems, as demonstrated by increased variance surrounding the degree day-length relationship. Smaller first-year size is related to walleye survival and recruitment to later life stages and has important implications for lake food webs and fisheries management. Future research quantifying effects of zebra mussels and Bythotrephes on other population-level processes and across a wider gradient of lake types is needed to understand the mechanisms driving observed changes in walleye growth.

Minnesota↗

USGS2019

Process-guided deep learning predictions of lake water temperature

The rapid growth of data in water resources has created new opportunities to accelerate knowledge discovery with the use of advanced deep learning tools. Hybrid models that integrate theory with state‐of‐the art empirical techniques have the potential to improve predictions while remaining true to physical laws. This paper evaluates the Process‐Guided Deep Learning (PGDL) hybrid modeling framework with a use‐case of predicting depth‐specific lake water temperatures. The PGDL model has three primary components: a deep learning model with temporal awareness (long short‐term memory recurrence), theory‐based feedback (model penalties for violating conversation of energy), and model pretraining to initialize the network with synthetic data (water temperature predictions from a process‐based model). In situ water temperatures were used to train the PGDL model, a deep learning (DL) model, and a process‐based (PB) model. Model performance was evaluated in various conditions, including when training data were sparse and when predictions were made outside of the range in the training data set. The PGDL model performance (as measured by root‐mean‐square error (RMSE)) was superior to DL and PB for two detailed study lakes, but only when pretraining data included greater variability than the training period. The PGDL model also performed well when extended to 68 lakes, with a median RMSE of 1.65 °C during the test period (DL: 1.78 °C, PB: 2.03 °C; in a small number of lakes PB or DL models were more accurate). This case‐study demonstrates that integrating scientific knowledge into deep learning tools shows promise for improving predictions of many important environmental variables.

Minnesota, Wisconsin↗

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↗

USGS2017

Seasonality of change: Summer warming rates do not fully represent effects of climate change on lake temperatures

Responses in lake temperatures to climate warming have primarily been characterized using seasonal metrics of surface-water temperatures such as summertime or stratified period average temperatures. However, climate warming may not affect water temperatures equally across seasons or depths. We analyzed a long-term dataset (1981–2015) of biweekly water temperature data in six temperate lakes in Wisconsin, U.S.A. to understand (1) variability in monthly rates of surface- and deep-water warming, (2) how those rates compared to summertime average trends, and (3) if monthly heterogeneity in water temperature trends can be predicted by heterogeneity in air temperature trends. Monthly surface-water temperature warming rates varied across the open-water season, ranging from 0.013 in August to 0.073°C yr −1 in September (standard deviation [SD]: 0.025°C yr −1 ). Deep-water trends during summer varied less among months (SD: 0.006°C yr −1 ), but varied broadly among lakes (–0.056°C yr −1 to 0.035°C yr −1 , SD: 0.034°C yr −1 ). Trends in monthly surface-water temperatures were well correlated with air temperature trends, suggesting monthly air temperature trends, for which data exist at broad scales, may be a proxy for seasonal patterns in surface-water temperature trends during the open water season in lakes similar to those studied here. Seasonally variable warming has broad implications for how ecological processes respond to climate change, because phenological events such as fish spawning and phytoplankton succession respond to specific, seasonal temperature cues.

Wisconsin↗

USGS2017

Defining a Safe Operating Space for inland recreational fisheries

The Safe Operating Space (SOS) of a recreational fishery is the multidimensional region defined by levels of harvest, angler effort, habitat, predation and other factors in which the fishery is sustainable into the future. SOS boundaries exhibit trade-offs such that decreases in harvest can compensate to some degree for losses of habitat, increases in predation and increasing value of fishing time to anglers. Conversely, high levels of harvest can be sustained if habitat is intact, predation is low, and value of fishing effort is moderate. The SOS approach recognizes limits in several dimensions: at overly high levels of harvest, habitat loss, predation, or value of fishing effort, the stock falls to a low equilibrium biomass. Recreational fisheries managers can influence harvest and perhaps predation, but they must cope with trends that are beyond their control such as changes in climate, loss of aquatic habitat or social factors that affect the value of fishing effort for anglers. The SOS illustrates opportunities to manage harvest or predation to maintain quality fisheries in the presence of trends in climate, social preferences or other factors that are not manageable.

Fish and Fisheries↗

USGS2017

Large-scale modeled contemporary and future water temperature estimates for 10774 Midwestern U.S. Lakes

Climate change has already influenced lake temperatures globally, but understanding future change is challenging. The response of lakes to changing climate drivers is complex due to the nature of lake-atmosphere coupling, ice cover, and stratification. To better understand the diversity of lake responses to climate change and give managers insight on individual lakes, we modelled daily water temperature profiles for 10,774 lakes in Michigan, Minnesota, and Wisconsin for contemporary (1979–2015) and future (2020–2040 and 2080–2100) time periods with climate models based on the Representative Concentration Pathway 8.5, the worst-case emission scenario. In addition to lake-specific daily simulated temperatures, we derived commonly used, ecologically relevant annual metrics of thermal conditions for each lake. We include all supporting lake-specific model parameters, meteorological drivers, and archived code for the model and derived metric calculations. This unique dataset offers landscape-level insight into the impact of climate change on lakes.

Michigan, Minnesota, Wisconsin↗

USGS2016

Climate-induced warming of lakes can be either amplified or suppressed by trends in water clarity

Climate change is rapidly warming aquatic ecosystems including lakes and reservoirs. However, variability in lake characteristics can modulate how lakes respond to climate. Water clarity is especially important both because it influences the depth range over which heat is absorbed, and because it is changing in many lakes. Here, we show that simulated long-term water clarity trends influence how both surface and bottom water temperatures of lakes and reservoirs respond to climate change. Clarity changes can either amplify or suppress climate-induced warming, depending on lake depth and the direction of clarity change. Using a process-based model to simulate 1894 north temperate lakes from 1979 to 2012, we show that a scenario of decreasing clarity at a conservative yet widely observed rate of 0.92% yr −1 warmed surface waters and cooled bottom waters at rates comparable in magnitude to climate-induced warming. For lakes deeper than 6.5 m, decreasing clarity was sufficient to fully offset the effects of climate-induced warming on median whole-lake mean temperatures. Conversely, a scenario increasing clarity at the same rate cooled surface waters and warmed bottom waters relative to baseline warming rates. Furthermore, in 43% of lakes, increasing clarity more than doubled baseline bottom temperature warming rates. Long-term empirical observations of water temperature in lakes with and without clarity trends support these simulation results. Together, these results demonstrate that water clarity trends may be as important as rising air temperatures in determining how waterbodies respond to climate change.

Limnology and Oceanography Letters↗

USGS2016

Projected shifts in ﬁsh species dominance in Wisconsin lakes under climate change

Temperate lakes may contain both coolwater fish species such as walleye ( Sander vitreus ) and warmwater fish species such as largemouth bass ( Micropterus salmoides ). Recent declining walleye and increasing largemouth bass populations have raised questions regarding the future trajectories and management actions for these species. We developed a thermodynamic model of water temperatures driven by downscaled climate data and lake-specific characteristics to estimate daily water temperature profiles for 2148 lakes in Wisconsin, US, under contemporary (1989–2014) and future (2040–2064 and 2065–2089) conditions. We correlated contemporary walleye recruitment and largemouth bass relative abundance to modeled water temperature, lake morphometry, and lake productivity, and projected lake-specific changes in each species under future climate conditions. Walleye recruitment success was negatively related and largemouth bass abundance was positively related to water temperature degree days. Both species exhibited a threshold response at the same degree day value, albeit in opposite directions. Degree days were predicted to increase in the future, although the magnitude of increase varied among lakes, time periods, and global circulation models (GCMs). Under future conditions, we predicted a loss of walleye recruitment in 33–75% of lakes where recruitment is currently supported and a 27–60% increase in the number of lakes suitable for high largemouth bass abundance. The percentage of lakes capable of supporting abundant largemouth bass but failed walleye recruitment was predicted to increase from 58% in contemporary conditions to 86% by mid-century and to 91% of lakes by late century, based on median projections across GCMs. Conversely, the percentage of lakes with successful walleye recruitment and low largemouth bass abundance was predicted to decline from 9% of lakes in contemporary conditions to only 1% of lakes in both future periods. Importantly, we identify up to 85 resilient lakes predicted to continue to support natural walleye recruitment. Management resources could target preserving these resilient walleye populations.

Wisconsin↗

USGS2016

Adapting inland fisheries management to a changing climate

Natural resource decision makers are challenged to adapt management to a changing climate while balancing short-term management goals with long-term changes in aquatic systems. Adaptation will require developing resilient ecosystems and resilient management systems. Decision makers already have tools to develop or ensure resilient aquatic systems and fisheries such as managing harvest and riparian zones. Because fisheries management often interacts with multiple stakeholders, adaptation strategies involving fisheries managers and other partners focused on land use, policy, and human systems, coupled with long-term monitoring, are necessary for resilient systems. We show how agencies and organizations are adapting to a changing climate in Minnesota and Ontario lakes and Montana streams. We also present how the Florida Fish and Wildlife Commission created a management structure to develop adaptation strategies. These examples demonstrate how organizations and agencies can cope with climate change effects on fishes and fisheries through creating resilient management and ecological systems.

Fisheries↗

USGS2014

Simulating 2,368 temperate lakes reveals weak coherence in stratification phenology

Changes in water temperatures resulting from climate warming can alter the structure and function of aquatic ecosystems. Lake-specific physical characteristics may play a role in mediating individual lake responses to climate. Past mechanistic studies of lake-climate interactions have simulated generic lake classes at large spatial scales or performed detailed analyses of small numbers of real lakes. Understanding the diversity of lake responses to climate change across landscapes requires a hybrid approach that couples site-specific lake characteristics with broad-scale environmental drivers. This study provides a substantial advancement in lake ecosystem modeling by combining open-source tools with freely available continental-scale data to mechanistically model daily temperatures for 2,368 Wisconsin lakes over three decades (1979-2011). The model accurately predicted observed surface layer temperatures (RMSE: 1.74°C) and the presence/absence of stratification (81.1% agreement). Among-lake coherence was strong for surface temperatures and weak for the timing of stratification, suggesting individual lake characteristics mediate some - but not all - ecologically relevant lake responses to climate.

Ecological Modelling↗