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Walleye ( Sander vitreus) are an ecologically important species managed for recreational, tribal, and commercial harvest. Walleye prefer cool water and low light conditions, and therefore changing water temperature and clarity potentially impacts walleye habitat and populations across the landscape. Using survey data collected from 1993 to 2018 from 312 lakes in Minnesota, we evaluated the relationship between thermal-optical habitat and the relative abundance of small (0–300 mm), medium (300–450 mm), and large (450 + mm) walleye. Thermal-optical habitat was positively correlated with the relative abundance of small and medium walleye but not large walleye. Walleye were more abundant in larger, naturally reproducing lakes opposed to smaller, stocked lakes. Thermal-optical habitat changed in 59% of lakes since 1980 (26% increasing and 33% decreasing) and appears to be driven primarily by changes in water clarity and thus optical habitat area. Our study provides important insights into local and regional drivers that influence walleye populations that can be used to assist fisheries managers in setting population goals and managing harvest.

Poikilothermic animals comprise most species on Earth and are especially sensitive to changes in environmental temperatures. Species conservation in a changing climate relies upon predictions of species responses to future conditions, yet predicting species responses to climate change when temperatures exceed the bounds of observed data is fraught with challenges. We present a physiologically guided abundance (PGA) model that combines observations of species abundance and environmental conditions with laboratory-derived data on the physiological response of poikilotherms to temperature to predict species geographical distributions and abundance in response to climate change. The model incorporates uncertainty in laboratory-derived thermal response curves and provides estimates of thermal habitat suitability and extinction probability based on site-specific conditions. We show that temperature-driven changes in distributions, local extinction, and abundance of cold, cool, and warm-adapted species vary substantially when physiological information is incorporated. Notably, cold-adapted species were predicted by the PGA model to be extirpated in 61% of locations that they currently inhabit, while extirpation was never predicted by a correlative niche model. Failure to account for species-specific physiological constraints could lead to unrealistic predictions under a warming climate, including underestimates of local extirpation for cold-adapted species near the edges of their climate niche space and overoptimistic predictions of warm-adapted species.

Aim Availability of uniformly collected presence, absence, and abundance data remains a key challenge in species distribution modeling (SDM). For invasive species, abundance and impacts are highly variable across landscapes, and quality occurrence and abundance data are critical for predicting locations at high risk for invasion and impacts, respectively. We leverage a large aquatic vegetation dataset comprising point‐level survey data that includes information on the invasive plant Myriophyllum spicatum (Eurasian watermilfoil) to: (a) develop SDMs to predict invasion and impact from environmental variables based on presence–absence, presence‐only, and abundance data, and (b) compare evaluation metrics based on functional and discrimination accuracy for presence–absence and presence‐only SDMs. Location Minnesota, USA. Methods Eurasian watermilfoil presence–absence and abundance information were gathered from 468 surveyed lakes, and 801 unsurveyed lakes were leveraged as pseudoabsences for presence‐only models. A Random Forest algorithm was used to model the distribution and abundance of Eurasian watermilfoil as a function of lake‐specific predictors, both with and without a spatial autocovariate. Occurrence‐based SDMs were evaluated using conventional discrimination accuracy metrics and functional accuracy metrics assessing correlation between predicted suitability and observed abundance. Results Water temperature degree days and maximum lake depth were two leading predictors influencing both invasion risk and abundance, but they were relatively less important for predicting abundance than other water quality measures. Road density was a strong predictor of Eurasian watermilfoil invasion risk but not abundance. Model evaluations highlighted significant differences: Presence–absence models had high functional accuracy despite low discrimination accuracy, whereas presence‐only models showed the opposite pattern. Main conclusion Complementing presence–absence data with abundance information offers a richer understanding of invasive Eurasian watermilfoil's ecological niche and enables evaluation of the model's functional accuracy. Conventional discrimination accuracy measures were misleading when models were developed using pseudoabsences. We thus caution against the overuse of presence‐only models and suggest directing more effort toward systematic monitoring programs that yield high‐quality data., Multiple niche models for invasive Eurasian watermilfoil were developed and compared to evaluate the importance of response data and model accuracy metrics. Abundance data are crucial in gaining a fuller understanding of EWM invasion and improve model evaluation metrics. Thus, the study cautions against the overuse of simple presence–absence niche models.

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 loge(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 loge(ω)–GDD relationship, suggesting that water clarity may mediate the effect of warming water temperatures by affecting the magnitude and direction of the loge(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.

Small nearshore fishes are an important part of lacustrine and functional diversity and link pelagic and benthic habitats by serving as prey for larger nearshore and offshore fishes. However, the trophic complexity of these small nearshore fishes is often unrecognized and detailed studies of their role in food webs are lacking. Here, we examined niche space patterns of small nearshore fish species using Bayesian analyses of carbon and nitrogen stable isotope data in nine freshwater lakes that are among the largest lakes in Minnesota. We found considerable variability in niche areas within species and high variability in niche overlap across species. At the assemblage level, niche overlap (average diet overlap of all species pairs at a lake) decreased as whole-lake species richness increased, possibly indicating a greater degree of resource specialization in more speciose lakes. Overall fish niche space was weakly but significantly related to niche space of their invertebrate prey. Although nearshore benthic resources contributed to fish diets in all lakes, all fish species also had non-negligible and variable contributions from pelagic zooplankton. This inter- and intraspecific variability in trophic niche space likely contributes to the multi-level trophic complexity, functional diversity, and potentially food web resilience to ecosystem changes.

Fish recruitment is complex and difficult to predict. Data-driven approaches show promise for predicting recruitment and understanding its drivers. We used a random forest model to infer relationships between year-class strength and 17 variables describing potential recruitment drivers across 30+ years of walleye (Sander vitreus) data from Minnesota’s nine largest inland lakes. Our model explained 20% of the variation in year-class strength overall, with predictive performance varying among lakes (–8% to 37% explained variance). Of the variables analyzed, degree-days during the first year of life and first winter severity were the most important for predicting recruitment, with relatively weak year classes predicted to occur with cold first growing seasons and severe first winters. Other thermal variables were secondarily important predictors of year-class strength. Predicted year-class strength was positively related to stock size and stocking and negatively related to the presence of invasive species; however, these variables were less important than thermal variables. Our results indicate that thermal conditions in early life can have a substantial impact on walleye recruitment and highlight the potential for differing recruitment drivers and dynamics among lakes.

Two primary goals in fisheries research are to (i) understand how habitat and environmental conditions influence the distribution of fishes across the landscape and (ii) make predictions about how fish communities will respond to environmental and anthropogenic change. In inland, freshwater ecosystems, quantitative approaches traditionally used to accomplish these goals largely ignore the effects of species interactions (competition, predation, mutualism) on shaping community structure, potentially leading to erroneous conclusions regarding habitat associations and unrealistic predictions about species distributions. Using two contrasting case studies, we highlight how joint species distribution models (JSDMs) can address the aforementioned deficiencies by simultaneously quantifying the effects of abiotic habitat variables and species dependencies. In particular, we show that conditional predictions of species occurrence from JSDMs can better predict species presence or absence compared with predictions that ignore species dependencies. JSDMs also allow for the estimation of site-specific probabilities of species co-occurrence, which can be informative for generating hypotheses about species interactions. JSDMs provide a flexible framework that can be used to address a variety of questions in fisheries science and management.

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.

The concentration of dissolved oxygen in aquatic systems helps to regulate biodiversity1,2, nutrient biogeochemistry3, greenhouse gas emissions4, and the quality of drinking water5. The long-term declines in dissolved oxygen concentrations in coastal and ocean waters have been linked to climate warming and human activity6,7, but little is known about the changes in dissolved oxygen concentrations in lakes. Although the solubility of dissolved oxygen decreases with increasing water temperatures, long-term lake trajectories are difficult to predict. Oxygen losses in warming lakes may be amplified by enhanced decomposition and stronger thermal stratification8,9 or oxygen may increase as a result of enhanced primary production10. Here we analyse a combined total of 45,148 dissolved oxygen and temperature profiles and calculate trends for 393 temperate lakes that span 1941 to 2017. We find that a decline in dissolved oxygen is widespread in surface and deep-water habitats. The decline in surface waters is primarily associated with reduced solubility under warmer water temperatures, although dissolved oxygen in surface waters increased in a subset of highly productive warming lakes, probably owing to increasing production of phytoplankton. By contrast, the decline in deep waters is associated with stronger thermal stratification and loss of water clarity, but not with changes in gas solubility. Our results suggest that climate change and declining water clarity have altered the physical and chemical environment of lakes. Declines in dissolved oxygen in freshwater are 2.75 to 9.3 times greater than observed in the world’s oceans6,7 and could threaten essential lake ecosystem services2,3,5,11., The concentration of dissolved oxygen in aquatic systems helps to regulate biodiversity, nutrient biogeochemistry, greenhouse gas emissions, and the quality of drinking water. The long-term declines in dissolved oxygen concentrations in coastal and ocean waters have been linked to climate warming and human activity, but little is known about the changes in dissolved oxygen concentrations in lakes. Although the solubility of dissolved oxygen decreases with increasing water temperatures, long-term lake trajectories are difficult to predict. Oxygen losses in warming lakes may be amplified by enhanced decomposition and stronger thermal stratification8,9 or oxygen may increase as a result of enhanced primary production10. Here we analyse a combined total of 45,148 dissolved oxygen and temperature profiles and calculate trends for 393 temperate lakes that span 1941 to 2017. We find that a decline in dissolved oxygen is widespread in surface and deep-water habitats. The decline in surface waters is primarily associated with reduced solubility under warmer water temperatures, although dissolved oxygen in surface waters increased in a subset of highly productive warming lakes, probably owing to increasing production of phytoplankton. By contrast, the decline in deep waters is associated with stronger thermal stratification and loss of water clarity, but not with changes in gas solubility. Our results suggest that climate change and declining water clarity have altered the physical and chemical environment of lakes. Declines in dissolved oxygen in freshwater are 2.75 to 9.3 times greater than observed in the world’s oceans and could threaten essential lake ecosystem services.

Tingley RW III, Paukert CP, Sass GG, Jacobson PC, Hansen GJA, Lynch AJ, Shannon PD. 2019. Adapting to climate change: Guidance for the management of inland glacial lake fisheries. Lake Rese...

Magee, MR, Hein CL, Walsh JR, Shannon PD, Vander Zanden MJ, Campbell TB, Hansen GJA, Hauxwell J, LaLiberte, GD, Parks TP, Sass GG, Swanston CW, Janowiak MK. 2019. Scientific advances and adaptation strategies for Wisconsin lakes facing climate change. Lake Reserv Manage. XX:XXX–XXX.Climate change threatens inland lakes, which are highly valued for their ecological and economic benefits. Here, we synthesize adaptation strategies that could offset climate impacts on Midwestern lakes. Our synthesis is based on results from the Wisconsin Initiative on Climate Change Impacts lake adaptation workshop, in which 48 researchers and managers with expertise on Wisconsin’s inland lakes gathered to provide input on climate adaptation strategies. We identified recent scientific advances, knowledge gaps, and examples of successful climate adaptation strategies with respect to four key themes: lake levels, water quality, aquatic invasive species, and fisheries. While adaptation strategies for each theme differed,...

Ecosystems are changing in complex and unpredictable ways, and analysis of these changes is facilitated by coordinated, long‐term research. Meeting diverse societal needs requires an understanding of what populations and communities will be dominant in 20, 50, and 100 yr. This paper is a product of a synthesis effort of the U.S. National Science Foundation funded Long‐Term Ecological Research (LTER) network addressing the LTER core research area of populations and communities. This analysis revealed that each LTER site had at least one compelling story about what their site would look like in 50 or 100 yr. As the stories were prepared, themes emerged, and the stories were grouped into papers along five themes for this special issue: state change, connectivity, resilience, time lags, and cascading effects. This paper addresses the resilience theme and includes stories from the Baltimore (urban), Hubbard Brook (northern hardwood forest), Andrews (temperate rain forest), Moorea (coral reef), Cedar Creek (grassland), and North Temperate Lakes (lakes) sites. The concept of resilience (the capacity of a system to maintain structure and processes in the face of disturbance) is an old topic that has seen a resurgence of interest as the nature and extent of global environmental change have intensified. The stories we present here show the power of long‐term manipulation experiments (Cedar Creek), the value of long‐term monitoring of forests in both natural (Andrews, Hubbard Brook) and urban settings (Baltimore), and insights that can be gained from modeling and/or experimental approaches paired with long‐term observations (North Temperate Lakes, Moorea). Three main conclusions emerge from the analysis: (1) Resilience research has matured over the past 40 yr of the LTER program; (2) there are many examples of high resilience among the ecosystems in the LTER network; (3) there are also many warning signs of declining resilience of the ecosystems we study. These stories highlight the need for long‐term studies to address this complex topic and show how the diversity of sites within the LTER network facilitates the emergence of overarching concepts about this important driver of ecosystem structure, function, services, and futures.

Lakes are warming globally at variable rates with important consequences for species survival. Now, research quantifies change in thermal habitat of lakes around the world and shows that season or depth restrictions on species responses may increase thermal habitat change threefold.

Walleye (Sander vitreus) populations are declining in Wisconsin and neighboring regions, motivating broader interest in walleye biology amidst ecological change. In fishes, growth integrates variation in ecological drivers and provides a signal of changing ecological conditions. We used a 23-year data set of length-at-age from 353 walleye populations across Wisconsin to test whether walleye growth rates changed over time and what ecological factors best predicted these changes. Using hierarchical models, we tested whether spatiotemporal variation in walleye growth was related to adult walleye density (density-dependent effects), water temperature, and largemouth bass (Micropterus salmoides) catch per unit effort (CPUE; predator or competitor effects). The average length of young walleye increased over time, and as a result, time to reach harvestable size declined significantly. In contrast, average lengths of older walleye have remained relatively constant over time. Juvenile walleye length-at-age was positively correlated with largemouth bass CPUE and surface water temperatures, but negatively correlated with adult walleye density. Our finding of widespread and long-term changes in walleye growth rates provides additional insights into how inland fisheries are responding to environmental change.

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.

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.

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.

Non-native species are a major component of global environmental change, and aquatic systems are especially vulnerable to non-native species impacts. Much of the research on aquatic non-native species impact has occurred at the local or site level. In reality, non-native species impacts play out across multiple spatial scales on heterogeneous landscapes. How can we ‘scale up’ our understanding of site-level impacts to the broader landscape scale? To address this disconnect, we synthesize our current understanding of key components of landscape-scale non-native species impacts: geographic range, abundance, and local impacts. Most aquatic non-native species have small ranges, while a few have large ranges. However, aquatic non-native species are often far from saturated on landscapes, and occurrence records are often woefully incomplete. Aquatic non-native species are often at low abundances where they are present, reaching high abundance in a small number of locations. Finally, local-scale impact can be estimated from abundance, but this requires knowledge of the abundance–impact relationship. Considering these multiple components enables understanding of non-native species impacts at broader spatial scales. Although the landscape-level impacts of aquatic non-native species may be high, the spatial distribution of site-level impacts is uneven, and highly impacted sites may be relatively uncommon. This heterogeneity in impacts provides an opportunity to optimize and prioritize non-native species management and prevention efforts.

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.

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 degrees C during the test period (DL: 1.78 degrees C, PB: 2.03 degrees 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. Department of the Interior Northeast Climate Adaptation Science Center; Midwest Glacial Lakes Fish Habitat Partnership grant through FWS; NSF Expedition in Computing Grant [1029711]; NSFNational Science Foundation (NSF) [EAR-PF-1725386]; Digital Technology Center at the University of MinnesotaUniversity of Minnesota System; Department of the Interior North Central Climate Adaptation Science Center; North Temperate Lakes Long-Term Ecological Research [NSF DEB-1440297]; Global Lake Ecological Observatory Network [NSF 1702991] See supporting information for data access, extended methods details, and example code. See https://doi.org/10.5066/P9AQPIVD for this study's data release and https://doi.org/10.5281/zenodo.3497495 for the versioned code repository. This research was funded by the Department of the Interior Northeast and North Central Climate Adaptation Science Centers, a Midwest Glacial Lakes Fish Habitat Partnership grant through F&WS, NSF Expedition in Computing Grant 1029711 to the University of Minnesota, a postdoctoral fellowship awarded to J.A.Z. under NSF EAR-PF-1725386, and a seed grant from the Digital Technology Center at the University of Minnesota. Access to computing facilities was provided by the University of Minnesota Supercomputing Institute and USGS Advanced Research Computing, USGS Yeti Supercomputer (https://doi.org/10.5066/F7D798MJ). We thank North Temperate Lakes Long-Term Ecological Research (NSF DEB-1440297) and Global Lake Ecological Observatory Network (NSF 1702991) for modeling discussions and data sharing, and Arka Daw, Randy Hunt, Jeff Sadler, Emily Read, and Mike Fienen for the PGDL discussions and ideas. We thank Luke Winslow, Noah Lottig, Madeline Magee, and along with MN DNR and WI DNR for temperature and bathymetric data, with special thanks to Pete Jacobson, Katie Hein, and Madeline Humphrey for collating thousands of temperature records, and Dave Wolock, the editorial group at WRR, and three anonymous reviewers for input that was used to improve this paper. Public domain – authored by a U.S. government employee

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...

In Wisconsin, the management of Walleyes Sander vitreus relies on a set of log-linear regressions to predict Walleye abundance and to set safe harvest. The regression models predict mean Walleye abundance from lake area, but they ignore variability among years; they also predict equal Walleye populations in lakes with the same size and recruitment source. We evaluated three alternative models in terms of predictive accuracy and the risk of overharvest. We used 899 mark–recapture population estimates (collected between 1953 and 2013) from 219 lakes to develop and evaluate (1) a log-linear mixed-effects model that used all individual observations and estimated adult Walleye abundance from lake area and lake-specific deviations from the overall intercept; (2) a mixed-effects model that builds on model 1 by adding a linear fixed effect of sampling year; and (3) a mixed-effects model that builds on model 1 by adding a random year effect. Walleye abundance was positively correlated with lake area in all...

We classified walleye (Sander vitreus) recruitment with 81% accuracy (recruitment success and failure predicted cor- rectly in 84% and 78% of lake-years, respectively) using a random forest model. Models were constructed using 2779 surveys collected from 541 Wisconsin lakes between 1989 and 2013 and predictor variables related to lake morphometry, thermal habitat, land use, and fishing pressure. We selected predictors to minimize collinearity while maximizing classification accuracy and data availability. The final model classified recruitment success based on lake surface area, water temperature degree-days, shoreline development factor, and conductivity. On average, recruitment was most likely in lakes larger than 225 ha. Low degree-days also increased the probability of successful recruitment, but primarily in lakes smaller than 150 ha. We forecasted the probability of walleye recruitment in 343 lakes considered for walleye stocking; lakes with high probability of natural reproduction but recent history of recruitment failure were prioritized for restoration stocking. Our results highlight the utility of models designed to predict recruitment for guiding management decisions, provided models are validated appropriately. Resume : Un modele de foret aleatoire pour la categorisation du recrutement de dores jaunes (Sander vitreus) s'est avere exact dans 81 % des cas (prediction correcte du succes ou de l'echec du recrutement pour 84 % et 78 % des annees-lac, respectivement). Des modeles ont ete elabores apartir de 2779 evaluations obtenues pour 541 lacs du Wisconsin de 1989 a ` 2013, et de variables predictives reliees ala morphometrie des lacs, al'habitat thermique, al'utilisation du sol et ala pression de peche. Nous avons selectionne les variables predictives de maniere aminimiser la colinearite tout en maximisant l'exactitude de la categorisation et la disponibilite des donnees. Le modele final categorisait le succes de recrutement en fonction de la superficie du lac, des degres-jours de temperature du lac, d'un facteur d'amenagement des berges et de la conductivite. En moyenne, le recrutement etait plus probable dans les lacs de plus de 225 ha. De faibles degres-jours se traduisaient egalement par une probabilite accrue de succes du recrutement, mais principalement dans les lacs de moins de 150 ha. Nous avons predit la probabilite de recrutement de dores jaunes dans 343 lacs consideres comme candidats pour l'ensemencement de dores; la priorite en ce qui concerne l'ensemencement aux fins de retablissement a ete donnee aux lacs presentant une forte probabilite de reproduction naturelle, mais un historique recent d'echec du recrutement. Nos resultats soulignent l'utilite de modeles concus pour predire le recrutement pour ce qui est d'orienter les decisions de gestion, pourvu que ces modeles soient valides adequatement. (Traduit par la Redaction)

Freshwaters are being transformed by multiple environmental drivers, creating uncertainty about future conditions. One way of coping with uncertainty is to manage for resilience to unanticipated events while facilitating learning through adaptive management. We outline the application of these strategies to freshwater recreational fisheries management using a case study in Wisconsin, USA, where black bass (Micropterus spp.) populations are increasing, while Walleye (Sander vitreus) populations are decreasing. Managing for heterogeneity in functional groups (e.g., age classes and prey species of sport fishes), fishery objectives, and regulations can increase resilience, although heterogeneity must be balanced with replication to facilitate learning. Monitoring designed to evaluate management objectives and inform about critical uncertainties, when combined with heterogeneity, creates opportunities for adaptive management, another critical resilience strategy. Although barriers exist to implementing resilie...

Water temperature observations were collected from 142 lakes across Wisconsin, USA, to examine variation in temperature of lakes exposed to similar regional climate. Whole lake water temperatures increased across the state from 1990 to 2012, with an average trend of 0.042°C yr−1 ± 0.01°C yr−1. In large (>0.5 km2) lakes, the positive temperature trend was similar across all depths. In small lakes ( 0.5 times the maximum lake depth. The differing response of small versus large lakes is potentially a result of wind-sheltering reducing turbulent mixing magnitude in small lakes. These results demonstrate that small lakes respond differently to climate change than large lakes, suggesting that current predictions of impacts to lakes from climate change may require modification.

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.

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 2368 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.

Rapid transitions in ecosystem structure, or regime shifts, are a hallmark of alternative stable states (ASS). However, regime shifts can occur even when feedbacks are not strong enough to cause ASS. We investigated the potential for ASS to explain transitions between dominance of an invasive species, rusty crayfish (Orconectes rusticus), and native sunfishes (Lepomis spp.) in northern Wisconsin (USA) lakes. A rapid transition from Lepomis to rusty crayfish dominance occurred as rusty crayfish invaded Trout Lake, and the reverse transition resulted from an eight-year experimental removal of rusty crayfish from Sparkling Lake. We fit a stage-structured population model of species interactions to 31 years of time-series data from each lake. The model identified water level as an important driver, with drought conditions reducing rusty crayfish recruitment and allowing Lepomis dominance. The maximum-likelihood parameter estimates of the negative interaction between rusty crayfish and Lepomis led to ASS in the model, where each species was capable of excluding the other within a narrow range of environmental conditions. However, uncertainty in parameter estimates made it impossible to exclude the potential that rapid transitions were caused by a simpler threshold response lacking alternative equilibria. Simulated forward and backward transitions between species dominance occurred at different environmental conditions (i.e., hysteresis), even when the parameters used for simulation did not predict ASS as a result of slow species responses to environmental drivers. Thus, ASS are possible, but by no means certain, explanations for rapid transitions in this system, and our results highlight the difficulties associated with distinguishing ASS from other types of threshold responses. However, whether regime shifts are caused by ASS may be relatively unimportant in this system, as the range of conditions over which transitions occur is narrow, and under most conditions, the system is predicted to exist in only a single state.

Controlling invasive species can restore ecosystems while also quantifying species interaction strengths. We experimentally removed invasive rusty crayfish (Orconectes rusticus) from a Wisconsin lake. Rusty crayfish abundance declined by 99% in 8 years and did not significantly increase 4 years postharvest, with no compensatory recruitment response observed. Native crayfish (Orconectes virilis) and sunfish (Lepomis spp.) abundances increased by two orders of magnitude as rusty crayfish abundance declined, and macrophyte cover increased significantly in 2–4 m waters. We expected benthic macroinvertebrate densities to increase as rusty crayfish were removed; however, fish consumption of invertebrates increased as rusty crayfish density declined, and macroinvertebrate responses varied among families and habitats. Total Gastropoda density increased 300-fold in cobble, while the density of one gastropod family declined in macrophytes. Ephemeroptera, Odonata, and Amphipoda densities also declined in certain habitats as rusty crayfish were removed, suggesting that they are indirectly facilitated by rusty crayfish. This study highlights the importance of considering indirect effects when assessing the impacts of invasive species and demonstrates that these impacts may be reversed over relatively short time scales.

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.

Invasive species have substantial impacts across the globe. While management efforts should aim to minimize undesirable impacts, we have a poor understanding of how impacts of a given invasive species vary spatially. Here, we develop a framework for considering heterogeneity of invasive species impacts that allows us to explore the range of possible spatial patterns of impact. This framework incorporates two factors—how invasive species abundance varies among sites (i.e., abundance distributions) and how invasive species impact varies as a function of abundance (i.e., abundance–impact curves). Combining these two factors allows for the creation of probability distributions that represent how invasive species impacts may vary spatially among sites. We used published abundance distributions and inferred abundance–impact curves to generate impact distributions for two problematic invasive species—zebra mussel and Eurasian watermilfoil—across lakes in Wisconsin, USA. Impact distributions of these species tended to be right‐skewed (i.e., the majority of sites had low impacts), although the tail thickness varied. We also simulated how a broader range of combinations of invasive species abundance distributions and abundance–impact curves produce different patterns of invasive species impact. These simulations illustrate a remarkable diversity of invasive species spatial impact patterns—probability distributions of impact were left‐skewed, right‐skewed, bimodal, and normal. Total landscape‐level impacts, estimated by summing site‐level impacts, were similarly variable depending on the distribution of site‐level impacts. Our results indicate that invasive species abundance and abundance–impact curves ultimately affect how invasive species impacts are distributed across the landscape, which has important implications for invasive species management.

Long-term research on freshwater ecosystems provides insights that can be difficult to obtain from other approaches. Widespread monitoring of ecologically relevant water-quality parameters spanning decades can facilitate important tests of ecological principles. Unique long-term data sets and analytical tools are increasingly available, allowing for powerful and synthetic analyses across sites. Long-term measurements or experiments in aquatic systems can catch rare events, changes in highly variable systems, time-lagged responses, cumulative effects of stressors, and biotic responses that encompass multiple generations. Data are available from formal networks, local to international agencies, private organizations, various institutions, and paleontological and historic records; brief literature surveys suggest much existing data are not synthesized. Ecological sciences will benefit from careful maintenance and analyses of existing long-term programs, and subsequent insights can aid in the design of effective future long-term experimental and observational efforts. Long-term research on freshwaters is particularly important because of their value to humanity.