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Predicting the effects of warming temperatures on the abundance and distribution of organisms under future climate scenarios often requires extrapolating species–environment correlations to climatic conditions not currently experienced by a species, which can result in unrealistic predictions. For poikilotherms, incorporating species' thermal physiology to inform extrapolations under novel thermal conditions can result in more realistic predictions. Furthermore, models that incorporate species and spatial dependencies may improve predictions by capturing correlations present in ecological data that are not accounted for by predictor variables. Here, we present a joint species, spatially dependent physiologically guided abundance (jsPGA) model for predicting multispecies responses to climate warming. The jsPGA model uses a basis function approach to capture both species and spatial dependencies. We apply the jsPGA model to predict the response of eight fish species to projected climate warming in thousands of lakes in Minnesota, USA. By the end of the century, the cold‐adapted species was predicted to have high probabilities of extirpation across its current range—with 10% of lakes currently inhabited by this species having an extirpation probability >0.90. The remaining species had varying levels of predicted changes in abundance, reflecting differences in their thermal physiology. Though the model did not identify many strong species dependencies, the variation in estimated spatial dependence across species suggested that accounting for both dependencies was important for predicting the abundance of these fishes. The jsPGA model provides a new tool for predicting changes in the abundance, distribution, and extirpation probability of poikilotherms under novel thermal conditions. [ABSTRACT FROM AUTHOR]

Freshwater ecosystems can serve as model systems that reveal insights into biological invasions. In this article, we summarize nine lessons about aquatic invasive species from the North Temperate Lakes Long-Term Ecological Research program and affiliated projects. The lessons about aquatic invasive species are as follows: Invasive species are more widespread than has been documented; they are usually at low abundance; they can irrupt from low-density populations in response to environmental triggers; they can occasionally have enormous and far-reaching impacts; they can affect microbial communities; reservoirs act as invasive species hotspots; ecosystem vulnerability to invasion can be estimated; invasive species removal can produce long-term benefits; and the impacts of invasive species control may be greater than the impacts of the invasive species. This synthesis highlights how long-term research on a freshwater landscape can advance our understanding of invasions. [ABSTRACT FROM AUTHOR]

Forecasting invasion risk under future climate conditions is critical for the effective management of invasive species, and species distribution models (SDMs) are key tools for doing so. However, SDM‐based forecasts are uncertain, especially when correlative statistical models extrapolate to nonanalog environmental domains, such as future climate conditions. Different assumptions about the functional form of the temperature–suitability relationship can impact predicted habitat suitability under novel conditions. Hence, methods to understand the sources of uncertainty are critical when applying SDMs. Here, we use high‐resolution predictions of lake water temperatures to project changes in habitat suitability under future climate conditions for an invasive macrophyte (Myriophyllym spicatum). Future suitability was predicted using five global circulation models and three statistical models that assumed different species–temperature functional responses. The suitability of lakes for M. spicatum was overall predicted to increase under future climate conditions, but the magnitude and direction of change in suitability varied greatly among lakes. Variability was most pronounced for lakes under nonanalog temperature conditions, indicating that predictions for these lakes remained highly uncertain. Integrating predictions from SDMs that differ in their species–environment response function, while explicitly quantifying uncertainty across analog and nonanalog domains, can provide a more robust and useful approach to forecasting invasive species distribution under climate change. [ABSTRACT FROM AUTHOR]

Estimating relative abundance is critical for informing conservation and management efforts and for making inferences about the effects of environmental change on populations. Freshwater fisheries span large geographic regions, occupy diverse habitats and consist of varying species assemblages. Monitoring schemes used to sample these diverse populations often result in populations being sampled at different times and under different environmental conditions. Varying sampling conditions can bias estimates of abundance when compared across time, location and species, and properly accounting for these biases is critical for making inferences.We develop a joint species distribution model (JSDM) that accounts for varying sampling conditions due to the environment and time of sampling when estimating relative abundance. The novelty of our JSDM is that we explicitly model sampling effort as the product of known quantities based on time and gear type and an unknown functional relationship to capture seasonal variation in species life history.We use the model to study relative abundance of six freshwater fish species across the state of Minnesota, USA. Our model enables estimates of relative abundance to be compared both within and across species and lakes, and captures the inconsistent sampling present in the data. We discuss how gear type, water temperature and day of the year impact catchability for each species at the lake level and throughout a year. We compare our estimates of relative abundance to those obtained from a model that assumes constant catchability to highlight important differences within and across lakes and species.Synthesis and applications: Our method illustrates that assumptions relating indices of abundance to observed catch data can greatly impact model inferences derived from JSDMs. Specifically, not accounting for varying sampling conditions can bias inference of relative abundance, restricting our ability to detect responses to management interventions and environmental change. While our focus is on freshwater fisheries, this model architecture can be adopted to other systems where catchability may vary as a function of space, time and species. [ABSTRACT FROM AUTHOR]

Lake morphometry is a driver of limnological processes, yet digitized bathymetry is lacking for most lakes. Here, we describe a method for efficiently extracting hypsography from bathymetric maps using ImageJ. To validate our method, we compared results generated from two independent users to those obtained from digital elevation models for 100 lakes. The mean absolute difference between hypsographic curves extracted using ImageJ vs. digital elevation models (DEMs) was 0.049 (95% CI 0.041–0.056) proportion of lake area, suggesting that ImageJ provides accurate hypsography. We calculated the mean absolute difference between the two users (0.016; 95% CI: 0.011–0.021), which suggests high interobserver reliability. Finally, we compared DEMs to an interpolated hypsography using only the maximum lake depth and found large differences. We apply this method to extract data for 1012 lakes. Our data and approach will be useful where bathymetric maps exist but are not digitized. [ABSTRACT FROM AUTHOR]

Lake water clarity is an indicator of water quality, trophic status, and habitat condition. Changes in clarity impact lake ecosystems and may reflect land use changes or presence of invasive species. Quantifying temporal changes in water clarity can be challenging because clarity varies seasonally, annually, and spatially within and among lakes. We developed a hierarchical generalized additive model to quantify trends in water clarity (Secchi depth) from 1979 to 2018 for 909 Minnesota lakes, accounting for seasonal and spatial variability. Water clarity increased by 0.41 m across lakes from 1984 to 1988 and 2014 to 2018. Lake‐specific clarity trends varied: clarity did not change significantly in 59.0% of lakes, increased in 34.5% of lakes, and decreased in 6.5% of lakes. Water clarity dynamics caused considerable variability in littoral area between seasons and years. Our results have wide applications in aquatic ecology, including understanding changes to food webs, assessing fish habitat, and evaluating impacts of invasive species. [ABSTRACT FROM AUTHOR]

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. Weshow 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. [ABSTRACT FROM AUTHOR]

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. [ABSTRACT FROM AUTHOR]

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). [ABSTRACT FROM AUTHOR]

Managing ecological systems for resilience can increase their capacity to maintain key functions even under global change. Oxygenated coldwater (oxythermal) habitat in lakes is an important ecological resource that is threatened by both climate change and eutrophication. Here, we quantify the resilience of oxythermal habitat in over 10,000 glacial lakes in the upper Midwestern United States to climate change and watershed disturbance and classify lakes for conservation prioritization based on their current conditions and resilience. Oxythermal habitat was predicted by lake morphometry, July air temperatures, and watershed land use. Temperatures are projected to increase by mid‐century, and the magnitude of warming, its effect on oxythermal habitat, and the uncertainty surrounding that effect varied among lakes. Under mid‐century climate conditions, the number of lakes containing suitable coldwater habitat was predicted to decline by 67%, while the number of lakes with unsuitable habitat was predicted to increase by over 200%. Lakes varied in the amount of temperature increase that they could sustain without a resultant change in habitat tier (i.e., their climate resilience). Median climate resilience was 4.3°C, with some lakes capable of remaining in their habitat tier even with temperature increases up to 14°C. Changing watershed land use was predicted to influence oxythermal habitat in 24% of lakes (n = 2391). We used the magnitude of increase in watershed development that a lake could sustain while remaining in its current habitat class as a measure of its resilience to watershed disturbance. Conversely, decreased watershed development may improve oxythermal habitat conditions and push a lake into an improved condition, and this value represented a lake's restoration potential. We classified lakes into seven management classes based on their current oxythermal habitat conditions and the resilience of oxythermal habitat to climate and watershed disturbance. To facilitate management on individual lakes, we also assessed the vulnerability and resilience of individual lakes and the uncertainty surrounding these estimates. By quantifying the resilience of lakes and how it is influenced by local action across a multistate region, we can prioritize conservation action across multiple scales to maintain the critical habitat and ecosystem function of glacial lakes. [ABSTRACT FROM AUTHOR]

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. [ABSTRACT FROM AUTHOR]

Walleye Sander vitreus and Yellow Perch Perca flavescens are culturally, economically, and ecologically significant fish species in North America that are affected by drivers of global change. Here, we review and synthesize the published literature documenting the effects of ecosystem changes on Walleye and Yellow Perch. We focus on four drivers: climate (including temperature and precipitation), aquatic invasive species, land use and nutrient loading, and water clarity. We identified 1,232 tests from 370 papers, split evenly between Walleye (n = 613) and Yellow Perch (n = 619). Climate was the most frequently studied driver (n = 572), and growth or condition was the most frequently studied response (n = 297). The most commonly reported relationship was "no effect" (42% of analyses), usually because multiple variables were tested and only a few were found to be significant. Overall responses varied among studies for most species‐response–driver combinations. For example, the influence of invasive species on growth of both Walleye and Yellow Perch was approximately equally likely to be positive, negative, or have no effect. Even when results were variable, important patterns emerged; for example, growth responses of both species to temperature were variable, but very few negative responses were observed. A few relationships were relatively consistent across studies. Invasive species were negatively associated with Walleye recruitment and abundance, and higher water clarity was negatively associated with Walleye abundance, biomass, and production. Some variability in responses may be due to differences in methodology or the range of variables studied; others represent true context dependence, where the effect of a driver depends on the influence of other variables. Using common metrics of impact, publishing negative results, and robust analytical approaches could facilitate comparisons among systems and provide a more comprehensive understanding of the responses of Walleye and Yellow Perch to ecosystem change. [ABSTRACT FROM AUTHOR]

Aim: Recurrent species assemblages integrate important biotic interactions and joint responses to environmental and spatial filters that enable local coexistence. Here, we applied a bipartite (site–species) network approach to develop a natural typology of lakes sharing distinct fish faunas and provide a detailed, hierarchical view of their bioregions. We then compared the roles of key biogeographical factors to evaluate alternative hypotheses about how fish communities are assembled from the regional species pool. Location: Ontario, Canada and the Upper Midwest, USA. Time period: 1957–2017. Major taxa studied: Freshwater fishes. Methods: Bipartite modularity analysis was performed on 90 taxa from 10,016 inland lakes in the Southwestern Hudson Bay, Mississippi River and St. Lawrence River drainages, uncovering bioregionalization of North American fishes at a large, subcontinental scale. We then used a latent variable approach, pairing non‐metric partial least‐squares structural equation modelling with multiple logistic regression, to show differences in the biogeographical templates of each type of community. Indicators of contemporary and historical connectivity, climate and habitat constructs were estimated using a geographical information system. Results: Fish assemblages reflected broad, overlapping patterns of postglacial colonization, climate and geological setting, but community differentiation was most linked to temperature, precipitation and, for certain groups, lake area and water quality. Bioregions were also marked by non‐native species, showing broad‐scale impacts of introductions to the Great Lakes and surrounding basins. Main conclusions: The dominant effects of climate across broad spatial gradients indicate differing sensitivities of fish communities to rapidly accelerating climate change and opportunities for targeted conservation strategies. By assessing biological variation at the level of recurrent assemblages, we accounted for the non‐stationarity of macroecological processes structuring different sets of species on the landscape and offer novel inference on the assembly of inland fish communities. [ABSTRACT FROM AUTHOR]

Understanding where, when, and how native species persist in the face of invasive species‐driven ecosystem change is critical for invasive species management and native species conservation. In some cases, ecological interactions among native and invasive species are spatially structured, and spatial segregation can be a key coexistence mechanism for ecologically similar taxa.We evaluated 19‐years of spatially explicit crayfish community data from a long‐term whole‐lake experiment, which includes 8 years of invasive rusty crayfish (Faxonius rusticus) removal followed by 11 years of post‐removal data collection. We quantified the within lake spatiotemporal patterns of virile crayfish (F. virilis) and rusty crayfish, and relate their dynamics to site‐level habitat conditions.In response to removal efforts, rusty crayfish catch rates declined by >95%, and native virile crayfish catch rates increased by more than 20‐fold. Ten years after ceasing removals, rusty crayfish have stayed at this relatively low abundance, and the virile crayfish population has remained stable. During removal, rusty crayfish abundances decreased non‐uniformly throughout the lake. Only after rusty crayfish populations were at their lowest levels did the native virile crayfish population begin to show signs of a recovery.Virile crayfish recovery was highly localized within the lake, and likely influenced by habitat and rusty crayfish abundance. Initially, virile crayfish made the most substantial resurgence in an area of the lake with rocky habitat conditions, but through time their distribution shifted into adjacent suboptimal macrophyte and muck habitats as rusty crayfish became more abundant in nearby areas. In general, when the two species overlapped in space, virile crayfish abundance stayed low, or the population shifted to adjacent areas with fewer competitively dominant rusty crayfish.Our results suggest that habitat heterogeneity allowed virile crayfish to maintain a foothold despite high rusty crayfish densities. Removal efforts led to the recovery of virile crayfish, and spatial segregation facilitated both species coexisting at comparable abundances for a decade. Our results highlight that invasive species control, even in the absence of complete eradication, can benefit native species and that spatially structured interactions can promote coexistence. [ABSTRACT FROM AUTHOR]

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. [ABSTRACT FROM AUTHOR]

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. [ABSTRACT FROM AUTHOR]

Recruitment of age‐0 Walleye Sander vitreus 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 to early June and 0.64‐cm‐micromesh gill nets set in July provided the highest catches of age‐0 Walleye among the methods we evaluated. Additional sampling on 13 lakes over 2 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. [ABSTRACT FROM AUTHOR]

Understanding invasive species spread and projecting how distributions will respond to climate change is a central task for ecologists. Typically, current and projected air temperatures are used to forecast future distributions of invasive species based on climate matching in an ecological niche modeling approach. While this approach was originally developed for terrestrial species, it has also been widely applied to aquatic species even though aquatic species do not experience air temperatures directly. In the case of lakes, species respond to lake thermal regimes, which reflect the interaction of climate and lake attributes such as depth, size, and clarity. The result is that adjacent waterbodies can differ notably in thermal regime. Given these obvious limitations of modeling aquatic species distributions using climate data, we take advantage of recent advances in simulating lake thermal regimes to model the distributions of invasive spiny water flea (Bythotrephes cederströmii) for current and projected future climates in the upper Midwest of the USA. We compared predictions and future projections from models based on modeled air temperatures with models based on modeled water temperature. All models predicted that the number of suitable lakes in the region will decrease with climate change. Models based on air and water temperature differed dramatically in the extent of this decrease. The air temperature model predicted 89% of study lakes to be suitable, with suitability declining dramatically in the late century with climate warming to just a single suitable lake. Lake suitability predictions from the water temperature model declined to a much lesser degree with warming (42% of lakes were predicted to be suitable, declining to 19% in the late century) and were more spatially independent. Our results expose the limitations of using air temperatures to model habitat suitability for aquatic species, and our study further highlights the importance of understanding lake‐specific responses to climate when assessing aquatic species responses to climate change. While we project a contraction in the potential range of Bythotrephes with warming in the study region, we anticipate that Bythotrephes will likely continue to expand into new lakes that will remain suitable in the following decades. [ABSTRACT FROM AUTHOR]

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 Reserv Manage. 35:435–452. Climate change is altering glacial lake fisheries in the United States, presenting a complex challenge for fisheries managers. Here we provide a regional perspective to guide management of heterogeneous and yet interdependent fishery resources in glacial lakes of the upper Midwest. Our main objective was to promote the adaptation of inland glacial lakes fisheries management to climate change by outlining processes that support regional plans. Using examples from the glacial lakes region, we outline an approach for regional prioritization, specify strategies for moving from regional prioritization to on-the-ground action, and provide guidance on the implementation of management plans given resource limitations and potential stakeholder conflict. We find that integrating ecological, social, and economic data with climate change vulnerability assessments can be useful in generating "lake-priority levels" to help identify where to focus actions to support system resilience. Managers can use lake-priority levels and ecosystem-specific strategies to make decisions about where and when to apply fisheries management action ranging from traditional (i.e., stocking, harvest regulations) to nontraditional approaches (i.e., catchment land management). Although the implementation of several approaches may be beyond an agency's financial and logistical capacity, funds can be secured through other sources ranging from grant programs to nontraditional partnerships identified by "thinking outside the lake." Regional plans may be an important step toward successful climate adaptation for inland glacial lakes fisheries management, and the proactive efforts of managers may help facilitate their development and implementation. [ABSTRACT FROM AUTHOR]

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. 35:364–381. 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, there was consensus around the need for a multifaceted approach that incorporates communication and outreach, policy and regulation changes, traditional resource conservation approaches, and novel engineering designs. Managers should focus on protecting high-quality lakes, building lake resilience, and retaining beneficial ecosystem services. Most importantly, thoughtful and strategic interactions with stakeholders, policymakers, and researchers across multiple disciplines will be key to implementing climate adaptation strategies. [ABSTRACT FROM AUTHOR]

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. Key Points: Process‐Guided Deep Learning (PGDL) models integrate advanced empirical techniques with process knowledgeWe used PGDL to accurately predict lake water temperatures for various conditionsPGDL performance improved significantly when pretraining data included diverse conditions generated by an existing process‐based model [ABSTRACT FROM AUTHOR]

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. [ABSTRACT FROM AUTHOR]

Eutrophication and climate warming are profoundly affecting fish in many freshwater lakes. Understanding the specific effects of these stressors is critical for development of effective adaptation and remediation strategies for conserving fish populations in a changing environment. Ecological niche models that incorporated the individual effects of nutrient concentration and climate were developed for 25 species of fish sampled in standard gillnet surveys from 1,577 Minnesota lakes. Lake phosphorus concentrations and climates were hindcasted to a pre-disturbance period of 1896–1925 using existing land use models and historical temperature data. Then historical fish assemblages were reconstructed using the ecological niche models. Substantial changes were noted when reconstructed fish assemblages were compared to those from the contemporary period (1981–2010). Disentangling the sometimes opposing, sometimes compounding, effects of eutrophication and climate warming was critical for understanding changes in fish assemblages. Reconstructed abundances of eutrophication-tolerant, warmwater taxa increased in prairie lakes that experienced significant eutrophication and climate warming. Eutrophication-intolerant, warmwater taxa abundance increased in forest lakes where primarily climate warming was the stressor. Coolwater fish declined in abundance in both ecoregions. Large changes in modeled abundance occurred when the effects of both climate and eutrophication operated in the same direction for some species. Conversely, the effects of climate warming and eutrophication operated in opposing directions for other species and dampened net changes in abundance. Quantifying the specific effects of climate and eutrophication will allow water resource managers to better understand how lakes have changed and provide expectations for sustainable fish assemblages in the future. [ABSTRACT FROM AUTHOR]

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. [ABSTRACT FROM AUTHOR]

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 models and was negatively correlated with sampling year (when included). Alternative models improved predictive accuracy by 17–22% over the current regression model. Restricting data to those collected during the most recent 20 years improved model responsiveness to new data and reduced the value of including a linear time trend. When all data were used for model construction, the relative risk of overharvest was lowest under the mixed‐effects model with a linear time trend; when the most recent 20 years of data were used, the risk was lowest under the mixed‐effects model with a random year effect. Accounting for variability among years would allow harvest to track changing Walleye populations and would allow management to be more adaptive. We recommend using the mixed‐effects model with a random year effect and restricting the data inputs to the most recent 20 years. Received May 20, 2015; accepted September 17, 2015 [ABSTRACT FROM AUTHOR]

Temporal patterns of species abundance, although less well-studied than spatial patterns, provide valuable insight to the processes governing community assembly. We compared temporal abundance distributions of two communities, phytoplankton and fish, in a north temperate lake. We used both 17 years of observed relative abundance data as well as resampled data from Monte Carlo simulations to account for the possible effects of non-detection of rare species. Similar to what has been found in other communities, phytoplankton and fish species that appeared more frequently were generally more abundant than rare species. However, neither community exhibited two distinct groups of “core” (common occurrence and high abundance) and “occasional” (rare occurrence and low abundance) species. Both observed and resampled data show that the phytoplankton community was dominated by occasional species appearing in only one year that exhibited large variation in their abundances, while the fish community was dominated by core species occurring in all 17 years at high abundances. We hypothesize that the life-history traits that enable phytoplankton to persist in highly dynamic environments may result in communities dominated by occasional species capable of reaching high abundances when conditions allow. Conversely, longer turnover times and broad environmental tolerances of fish may result in communities dominated by core species structured primarily by competitive interactions. [ABSTRACT FROM AUTHOR]

Invasive species are leading drivers of environmental change. Their impacts are often linked to their population size, but surprisingly little is known about how frequently they achieve high abundances. A nearly universal pattern in ecology is that species are rare in most locations and abundant in a few, generating right-skewed abundance distributions. Here, we use abundance data from over 24,000 populations of 17 invasive and 104 native aquatic species to test whether invasive species differ from native counterparts in statistical patterns of abundance across multiple sites. Invasive species on average reached significantly higher densities than native species and exhibited significantly higher variance. However, invasive and native species did not differ in terms of coefficient of variation, skewness, or kurtosis. Abundance distributions of all species were highly right skewed (skewness>0), meaning both invasive and native species occurred at low densities in most locations where they were present. The average abundance of invasive and native species was 6% and 2%, respectively, of the maximum abundance observed within a taxonomic group. The biological significance of the differences between invasive and native species depends on species-specific relationships between abundance and impact. Recognition of cross-site heterogeneity in population densities brings a new dimension to invasive species management, and may help to refine optimal prevention, containment, control, and eradication strategies. [ABSTRACT FROM AUTHOR]

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. INSET: What is long term with respect to ecological data?. [ABSTRACT FROM AUTHOR]

The US National Science Foundation-funded Long Term Ecological Research (LTER) Network supports a large (around 240) and diverse portfolio of long-term ecological experiments. Collectively, these long-term experiments have (a) provided unique insights into ecological patterns and processes, although such insight often became apparent only after many years of study; (b) influenced management and policy decisions; and (c) evolved into research platforms supporting studies and involving investigators who were not part of the original design. Furthermore, this suite of long-term experiments addresses, at the site level, all of the US National Research Council's Grand Challenges in Environmental Sciences. Despite these contributions, we argue that the scale and scope of global environmental change requires a more-coordinated multisite approach to long-term experiments. Ideally, such an approach would include a network of spatially extensive multifactor experiments, designed in collaboration with ecological modelers that would build on and extend the unique context provided by the LTER Network. INSET: Definition of long-term ecological experiments. [ABSTRACT FROM AUTHOR]

We developed and evaluated an alternative method (rapid assessment or RA) for assessment of larval sea lampreys, Petromyzon marinus. We determined that using RA would result in at least as many, if not more, sea lampreys being killed than would using the current assessment method (quantitative assessment sampling or QAS) to select streams for lampricide treatment. Both assessment methods were carried out simultaneously throughout the entire Great Lakes basin from 2005 to 2007. RA required fewer resources than the current method and thus allowed for the chemical treatment of additional streams with lampricides, given a fixed overall budget for control. Population estimates generated from the QAS surveys showed that using RA would result in approximately equal numbers of metamorphosing lamprey and greater numbers of larval lamprey killed than by using QAS. Mark–recapture results indicated that prioritizing streams for treatment using RA may result in higher numbers of metamorphosing and larval lampreys killed than by using QAS. RA is currently being adopted throughout the Great Lakes as the method for assessing larval sea lamprey populations. Other fishery management programs may benefit from examining the value of their assessment programs relative to other uses of resources. [ABSTRACT FROM AUTHOR]

Aquatic invasive species (AIS) are a global threat to freshwater biodiversity and ecosystem services. Documenting AIS prevalence at broad spatial scales is critical to effective management and early detection. However, conventional monitoring for AIS is costly and is rarely applied at the resolution and scale required for effective management. Monitoring of AIS using environmental DNA (eDNA) has the potential to enable broadscale surveillance at a fraction of the cost of conventional methods, but key questions must first be addressed related to how eDNA detection probability varies among environments, seasons, and multiple species with different life histories. To quantify spatiotemporal variation in the detection probability of AIS using eDNA sampling, we surveyed 20 lakes with known populations of four aquatic invasive species: common carp (Cyprinus carpio), rusty crayfish (Faxonius rusticus), spiny waterflea (Bythotrephes longimanus), and zebra mussels (Dreissena polymorpha). We collected water samples at 10 locations per lake, five times throughout the open water season resulting in a total of 1,000 water samples. Quantitative polymerase chain reaction was used with species‐specific assays to determine the presence of each species' eDNA in water samples. With Bayesian occupancy models, we quantified the effects of lake and site characteristics and Julian date on eDNA detection probability. The probability of eDNA detection varied seasonally, and the seasonal variation was species‐specific and related to species life histories. Zebra mussel eDNA was generally the most detectable among the species we targeted, and detection probability peaked in midsummer when only six water samples were required to achieve a 95% probability of detection (80% Bayesian credible interval: 3–12 samples). Spiny waterflea eDNA detections also peaked in mid to late summer, but were overall the most difficult species to detect, requiring 160 samples for a 95% probability of detection (80% Bayesian credible interval: 67–1,616 samples). Common carp eDNA was most detectable in the spring and rusty crayfish eDNA was most detectable in the early autumn, corresponding to key life history events. Sampling for eDNA during the optimal time of the year for each species decreased the number of samples required to reach a 95% probability of detection by an order of magnitude or more. Our results are relevant for decision makers interested in using eDNA as a multi‐species monitoring tool and highlight the importance of life history in the efficacy of eDNA monitoring. [ABSTRACT FROM AUTHOR]

Successful management of natural resources requires local action that adapts to larger‐scale environmental changes in order to maintain populations within the safe operating space (SOS) of acceptable conditions. Here, we identify the boundaries of the SOS for a managed freshwater fishery in the first empirical test of the SOS concept applied to management of harvested resources. Walleye (Sander vitreus) are popular sport fish with declining populations in many North American lakes, and understanding the causes of and responding to these changes is a high priority for fisheries management. We evaluated the role of changing water clarity and temperature in the decline of a high‐profile walleye population in Mille Lacs, Minnesota, USA, and estimated safe harvest under changing conditions from 1987 to 2017. Thermal–optical habitat area (TOHA)—the proportion of lake area in which the optimal thermal and optical conditions for walleye overlap—was estimated using a thermodynamic simulation model of daily water temperatures and light conditions. We then used a SOS model to analyze how walleye carrying capacity and safe harvest relate to walleye thermal–optical habitat. Thermal–optical habitat area varied annually and declined over time due to increased water clarity, and maximum safe harvest estimated by the SOS model varied by nearly an order of magnitude. Maximum safe harvest levels of walleye declined with declining TOHA. Walleye harvest exceeded safe harvest estimated by the SOS model in 16 out of the 30 yr of our dataset, and walleye abundance declined following 14 of those years, suggesting that walleye harvest should be managed to accommodate changing habitat conditions. By quantifying harvest trade‐offs associated with loss of walleye habitat, this study provides a framework for managing walleye in the context of ecosystem change. [ABSTRACT FROM AUTHOR]