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Sewage released from lakeside development can introduce nutrients and micropollutants that can restructure aquatic ecosystems. Lake Baikal, the world's most ancient, biodiverse, and voluminous freshwater lake, has been experiencing localized sewage pollution from lakeside settlements. Nearby increasing filamentous algal abundance suggests benthic communities are responding to localized pollution. We surveyed 40‐km of Lake Baikal's southwestern shoreline from 19 to 23 August 2015 for sewage indicators, including pharmaceuticals, personal care products, and microplastics, with colocated periphyton, macroinvertebrate, stable isotope, and fatty acid samplings. The data are structured in a tidy format (a tabular arrangement familiar to limnologists) to encourage reuse. Unique identifiers corresponding to sampling locations are retained throughout all data files to facilitate interoperability among the dataset's 150+ variables. For Lake Baikal studies, these data can support continued monitoring and research efforts. For global studies of lakes, these data can help characterize sewage prevalence and ecological consequences of anthropogenic disturbance across spatial scales.

Predicting how food webs will respond to global environmental change is difficult because of the complex interplay between the abiotic forcing and biotic interactions. Mechanistic models of species interactions in seasonal environments can help understand the effects of global change in different ecosystems. Seasonally ice-covered lakes are warming faster than many other ecosystems and undergoing pronounced food web changes, making the need to forecast those changes especially urgent. Using a seasonally forced food web model with a generalist zooplankton grazer and competing cold-adapted winter and warm-adapted summer phytoplankton, we show that with declining ice cover, the food web moves through different dynamic regimes, from annual to biennial cycles, with decreasing and then disappearing winter phytoplankton blooms and a shift of maximum biomass to summer season. Interestingly, when predator-prey interactions were not included, a declining ice cover did not cause regime shifts, suggesting that both are needed for regime transitions. A cluster analysis of long-term data from Lake Baikal, Siberia, supports the model results, revealing a change from regularly occurring winter blooms of endemic diatoms to less frequent winter bloom years with decreasing ice cover. Together, the results show that even gradual environmental change, such as declining ice cover duration, may cause discontinuous or abrupt transitions between dynamic regimes in food webs.

Pharmaceuticals and personal care products (PPCPs) garner increasing attention globally for both their usefulness as indicators of human waste and their potency as emerging organic toxicants. Three decades of rapid increase in PPCP study combined with an increasing number of PPCPs on the global market have created an opportunity (1) to review trends in diversity of compounds, sewage treatment techniques (STTs), and ecosystems investigated as well as (2) to identify knowledge gaps in the literature. We conducted a quantitative evidence synthesis of 6517 abstracts from primary articles in the environmental PPCP literature by examining relative abundance of specific PPCP classes, STTs, and ecosystem types. Our results demonstrate that non-prescription drugs and antibiotics dominated PPCP abstracts, appearing in 51% and 39% of reviewed abstracts, respectively, in comparison to hormones (18%), prescription drugs (18%), fragrances (0.3%), and antioxidants (0.0%), which can all elicit physiological and ecological responses even at low concentrations. References to centralized STTs (e.g., activated sludge, 37%) were more frequent than decentralized STTs (e.g., septic, 2%), despite decentralized STTs being common and frequently high impact sources of sewage pollution worldwide. Freshwater lotic systems (63%) were more prevalent than freshwater lentic (24%) and terrestrial (20%) systems. This discrepancy is notable because the longer residence times of lentic and terrestrial systems may enable PPCPs to concentrate and thus increase risk of biological consequences. These results highlight distinct opportunities to address knowledge gaps in the environmental PPCP literature, including underrepresented compounds (e.g., fragrances), sewage treatment techniques (e.g., septic systems), and ecosystem types (e.g., lakes).

Among its many impacts, climate warming is leading to increasing winter air temperatures, decreasing ice cover extent, and changing winter precipitation patterns over the Laurentian Great Lakes and their watershed. Understanding and predicting the consequences of these changes is impeded by a shortage of winter-period studies on most aspects of Great Lake limnology. In this review, we summarize what is known about the Great Lakes during their 3–6 months of winter and identify key open questions about the physics, chemistry, and biology of the Laurentian Great Lakes and other large, seasonally frozen lakes. Existing studies show that winter conditions have important effects on physical, biogeochemical, and biological processes, not only during winter but in subsequent seasons as well. Ice cover, the extent of which fluctuates dramatically among years and the five lakes, emerges as a key variable that controls many aspects of the functioning of the Great Lakes ecosystem. Studies on the properties and formation of Great Lakes ice, its effect on vertical and horizontal mixing, light conditions, and biota, along with winter measurements of fundamental state and rate parameters in the lakes and their watersheds are needed to close the winter knowledge gap. Overcoming the formidable logistical challenges of winter research on these large and dynamic ecosystems may require investment in new, specialized research infrastructure. Perhaps more importantly, it will demand broader recognition of the value of such work and collaboration between physicists, geochemists, and biologists working on the world's seasonally freezing lakes and seas.

Highlights • A novel semantic analysis offers insight into the diversity of scientific publications. • Synthesis center publications are more topically diverse than others. • Article diversity is strongly and negatively related to a paper's visibility (measured using citations)., Synthesis centers are a form of scientific organization that catalyzes and supports research that integrates diverse theories, methods and data across spatial or temporal scales to increase the generality, parsimony, applicability, or empirical soundness of scientific explanations. Synthesis working groups are a distinctive form of scientific collaboration that produce consequential, high-impact publications. But no one has asked if synthesis working groups synthesize: are their publications substantially more diverse than others, and if so, in what ways and with what effect? We investigate these questions by using Latent Dirichlet Analysis to compare the topical diversity of papers published by synthesis center collaborations with that of papers in a reference corpus. Topical diversity was operationalized and measured in several ways, both to reflect aggregate diversity and to emphasize particular aspects of diversity (such as variety, evenness, and balance). Synthesis center publications have greater topical variety and evenness, but less disparity, than do papers in the reference corpus. The influence of synthesis center origins on aspects of diversity is only partly mediated by the size and heterogeneity of collaborations: when taking into account the numbers of authors, distinct institutions, and references, synthesis center origins retain a significant direct effect on diversity measures. Controlling for the size and heterogeneity of collaborative groups, synthesis center origins and diversity measures significantly influence the visibility of publications, as indicated by citation measures. We conclude by suggesting social processes within collaborations that might account for the observed effects, by inviting further exploration of what this novel textual analysis approach might reveal about interdisciplinary research, and by offering some practical implications of our results.

The study of environmental communication originated as a diverse multidisciplinary field encompassing a wide array of communicator perspectives. However, as the field evolved, mass media and journalism became its perceived scholarly focus. As a result, environmental communication processes may be less well-understood across other settings, such as scientific and research institutions, non-governmental organizations, and federal agencies. To understand how communicators describe their goals, ethics, and strategies within these contexts, we conducted a three-part study of researchers and practitioners working on environmental issues in the Washington, DC, region between October 2019 and January 2020. Employing Q methodology, we identified four distinct perspectives: capacity-builders, translators, policy and decision-supporters, and cultural changemakers. Each of these perspectives is associated with a different range of goals, ethics, and strategic approaches. We describe graduate educational competencies for each of the perspectives and discuss implications for the design of communication research to meet practitioners’ needs.

Scientists long eschewed studying lakes in winter, expecting that cold temperatures and ice cover limited activity below the surface. Recent findings to the contrary are changing limnologists’ views.

Lake Baikal, one of the world’s largest and most biologically diverse lakes, has recently begun to experience uncharacteristic nuisance blooms of filamentous benthic algae. To contribute to...

Elevated allochthonous inputs of organic matter are increasingly recognized as a driver of ecosystem change in lakes, particularly when concurrent with eutrophication. Evaluation of lakes in a nutrient-color paradigm (i.e., based on total phosphorus and true color) enables a more robust approach to research and management. To assess temporal and spatial patterns in nutrient-color status for U.S. lakes and associated food web attributes, we analyzed the U.S. Environmental Protection Agency's National Lakes Assessment (NLA) data. With 1000+ lakes sampled in 2007 and 2012 in a stratified random sampling design, the NLA enables rigorous assessment of lake condition across the continental U.S. We demonstrate that many U.S. lakes are simultaneously experiencing eutrophication and brownification to produce an abundance of "murky" lakes. Overall, "blue" lakes decreased by ~ 18% (46% of lakes in 2007 to 28% in 2012) while "murky" lakes increased by almost 12% (24% of lakes in 2007 to 35.4% in 2012). No statistical differences were observed in the proportions of "green" or "brown" lakes. Regionally, murky lakes significantly increased in the Northern Appalachian, Southern Plains, and Xeric ecoregions. Murky lakes exhibited the highest epilimnetic chlorophyll a concentrations, cyanobacterial densities, and microcystin concentrations. Total zooplankton biomass was also highest in murky lakes, primarily due to increased rotifer and copepod biomass. However, zooplankton : phytoplankton biomass ratios were low, suggesting reduced energy transfer to higher trophic levels. These results emphasize that many lakes in the U.S. are simultaneously "greening" and "browning", with potentially negative consequences for water quality and food web structure.

In lakes that experience seasonal ice cover, understanding of nitrogen–oxygen coupling and nitrification has been dominated by observations during open water, ice-free conditions. To address knowledge gaps about nitrogen–oxygen linkages under ice, we examined long-term winter data (30 + years, 2–3 sample events per winter) in 7 temperate lakes of forested northern Wisconsin, USA. Across lakes and depths, there were strong negative relationships between dissolved oxygen (DO) and the number of days since ice-on, reflecting consistent DO consumption rates under ice. In two bog lakes that routinely experience prolonged winter DO concentrations below 1.0 mg L−1, nitrate accumulated near the ice surface mainly in late winter, suggesting nitrification may depend on biogenic oxygen from photosynthesis. In contrast, within five oligotrophic-mesotrophic lakes, nitrate accumulated more consistently over winter and often throughout the water column, especially at intermediate depths. Exogenous inputs of nitrate to these lakes were minimal compared to rates of nitrate accumulation. To produce the nitrate via in-lake nitrification, substantial oxygen consumption by ammonium oxidizing microbes would be required. Among lakes and depths that had significant DO depletion over winter, the stoichiometric nitrifier oxygen demand ranged from 1 to 25% of the DO depletion rate. These estimates of nitrifier-driven DO decline are likely conservative because we did not account for nitrate consumed by algal uptake or denitrification. Our results provide an example of nitrification at temperatures

The duration of winter ice cover on lakes varies substantially with climate variability, and has decreased over the last several decades in many temperate lakes. However, little is known of how changes in seasonal ice cover may affect biogeochemical processes under ice. We examined winter nitrogen (N) dynamics under ice using a 30+ yr dataset from five oligotrophic/mesotrophic north temperate lakes to determine how changes in inorganic N species varied with ice duration. Nitrate accumulated during winter and was strongly related to the number of days since ice‐on. Exogenous inputs accounted for less than 3% of nitrate accumulation in four of the five lakes, suggesting a paramount role of nitrification in regulating N transformation and the timing of chemical conditions under ice. Winter nitrate accumulation rates ranged from 0.15 μg N L−1 d−1 to 2.7 μg N L−1 d−1 (0.011–0.19 μM d−1), and the mean for intermediate depths was 0.94 μg N L−1 d−1 (0.067 μM d−1). Given that winters with shorter ice duration (< 120 d) have become more frequent in these lakes since the late 1990s, peak winter nitrate concentrations and cumulative nitrate production under ice may be declining. As ice extent and duration change, the physical and chemical conditions supporting life will shift. This research suggests we may expect changes in the form and amount of inorganic N, and altered dissolved nitrogen : phosphorus ratios, in lakes during winters with shorter ice duration.

The scale and magnitude of complex and pressing environmental issues lend urgency to the need for integrative and reproducible analysis and synthesis, facilitated by data-intensive research approaches. However, the recent pace of technological change has been such that appropriate skills to accomplish data-intensive research are lacking among environmental scientists, who more than ever need greater access to training and mentorship in computational skills. Here, we provide a roadmap for raising data competencies of current and next-generation environmental researchers by describing the concepts and skills needed for effectively engaging with the heterogeneous, distributed, and rapidly growing volumes of available data. We articulate five key skills: (1) data management and processing, (2) analysis, (3) software skills for science, (4) visualization, and (5) communication methods for collaboration and dissemination. We provide an overview of the current suite of training initiatives available to environmental scientists and models for closing the skill-transfer gap.

Freshwater ecosystems are heavily impacted by multiple stressors, and a freshwater biodiversity crisis is underway. This realization has prompted calls to integrate global freshwater ecosystem data, including traditional taxonomic and newer types of data (e.g., eDNA, remote sensing), to more comprehensively assess change among systems, regions, and organism groups. We argue that data integration should be done, not only with the important purpose of filling gaps in spatial, temporal, and organismal representation, but also with a more ambitious goal: to study fundamental cross-scale biological phenomena. Such knowledge is critical for discerning and projecting ecosystem functional dynamics, a realm of study where generalizations may be more tractable than those relying on taxonomic specificity. Integration could take us beyond cataloging biodiversity losses, and toward predicting ecosystem change more broadly. Fundamental biology questions should be central to integrative, interdisciplinary research on causal ecological mechanisms, combining traditional measures and more novel methods at the leading edge of the biological sciences. We propose a conceptual framework supporting this vision, identifying key questions and uncertainties associated with realizing this research potential. Our framework includes five interdisciplinary "complementarities." First, research approaches may provide comparative complementarity when they offer separate realizations of the same focal phenomenon. Second, for translational complementarity, data from one research approach is used to translate that from another, facilitating new inferences. Thirdly, causal complementarity arises when combining approaches allows us to "fill in" cause-effect relationships. Fourth, contextual complementarity is realized when together research methodologies establish the wider ecological and spatiotemporal context within which focal biological responses occur. Finally, integration may allow us to cross inferential scales through scaling complementarity. Explicitly identifying the modes and purposes of integrating research approaches, and reaching across disciplines to establish appropriate collaboration will allow researchers to address major biological questions that are more than the sum of the parts.

As an increasing variety and complexity of environmental issues confront scientists and natural resource managers, assembling the most relevant and informative data into accessible data systems becomes critical to timely problem solving. Data interoperability is the key criterion for succeeding in that assembly, and much informatics research is focused on data federation, or synthesis to produce interoperable data. However, when candidate data come from numerous, diverse, and high‐value legacy data sources, the issue of data variety or heterogeneity can be a significant impediment to interoperability. Research in informatics, computer science and philosophy has frequently focused on resolving data heterogeneity with automation, but subject matter expertise still plays a large role. In particular, human expertise is a large component in the development of tools such as data dictionaries, crosswalks, and ontologies. Such representations may not always match from one data system to another, presenting potentially inconsistent results even with the same data. Here, we use a long‐term data set on management actions designed to improve stream habitat for endangered salmon in the Pacific Northwest, to illustrate how different representations can change the underlying information content in the data system. We pass the same data set comprised of 49,619 records through three ontologies, each developed to address a rational management need, and show that the inferences drawn from the data can change with choice of data representation or ontology. One striking example shows that the use of one ontology would suggest water quality improvement projects are the rarest and most expensive restoration actions undertaken, while another will suggest these actions to be the most common and least expensive type of management actions. The discrepancy relates to the origins of the data dictionaries themselves, with one designed to catalog management actions and the other focused on ecological processes. Thus, we argue that in data federation efforts humans are “in the loop” rationally, in the form of the ontologies they have chosen, and diminishing the human component in favor of automation carries risks. Consequently, data federation exercises should be accompanied by validations in order to evaluate and manage those risks.

Climate warming impacts ecosystems through multiple interacting pathways, including via direct thermal responses of individual taxa and the combined responses of closely interacting species. In this study we examined how warming and infection by an oomycete parasite affect the dominant zooplankter of Russia’s Lake Baikal, the endemic cold-adapted stenotherm Epischura baikalensis (Copepoda). We used a combination of laboratory experiments, long-term monitoring data and population modeling. Experiments showed large thermal mismatch between host and parasite, with strong negative effects of warm temperatures on E. baikalensis survival and reproduction and a negative synergistic effect of Saprolegnia infection. However, Saprolegnia infection had an unexpected positive effect on E. baikalensis reproductive output, which may be consistent with fecundity compensation by infected females. Long-term monitoring data showed that Saprolegnia infections were most common during the warmest periods of the year and that infected individuals tended to accumulate in deep water. Population models, parameterized with experimental and literature data, correctly predicted the timing of Saprolegnia epizootics, but overestimated the negative effect of warming on E.baikalensis populations. Models suggest that diel vertical migration may allow E. baikalensis to escape the negative effects of increasing temperatures and parasitism and enable E. baikalensis to persist as Lake Baikal warms. Our results contribute to understanding of how multiple interacting stressors affect warming pelagic ecosystems of cold lakes and oceans and show that the population-level consequences of thermal mismatch between hosts and parasites can vary seasonally, interannual and spatially.

Food production hinges largely upon access to phosphorus (P) fertilizer. Most fertilizer P used in the global agricultural system comes from mining of nonrenewable phosphate rock deposits located within few countries. However, P contained in livestock manure or urban wastes represents a recyclable source of P. To inform development of P recycling technologies and policies, we examined subnational, national, and global spatial patterns for two intersections of land use affording high P recycling potential: (a) manure-rich cultivated areas and (b) populous cultivated areas. In turn, we examined overlap between P recycling potential and nation-level P fertilizer import dependency. Populous cultivated areas were less abundant globally than manure-rich cultivated areas, reflecting greater segregation between crops and people compared to crops and livestock, especially in the Americas. Based on a global hexagonal grid (290-km(2) grid cell area), disproportionately large shares of subnational "hot spots" for P recycling potential occurred in India, China, Southeast Asia, Europe, and parts of Africa. Outside of China, most of the remaining manure-rich or pulous cultivated areas occurred within nations that had relatively high imports of P fertilizer (net P import:consumption ratios amp;gt;= 0.4) or substantial increases in fertilizer demand between the 2000s (2002-2006) and 2010s (2010-2014). Manure-rich cultivated grid cells (those above the 75th percentiles for both manure and cropland extent) represented 12% of the global grid after excluding cropless cells. Annually, the global sum of animal manure P was at least 5 times that contained in human excreta, and among cultivated cells the ratio was frequently higher (median = 8.9). The abundance of potential P recycling hot spots within nations that have depended on fertilizer imports or experienced rising fertilizer demand could prove useful for developing local P sources and maintaining agricultural independence. Funding Agencies|Washington State University; National Socio-Environmental Synthesis Center (SESYNC) under National Science Foundation [DBI-1052875]; PBL Netherlands Environmental Assessment Agency [869.15.015, 869.15.014]

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As lakes warm worldwide, temperature may alter plankton community structure and abundance by affecting not only metabolism but also trophic interactions. Siberia’s Lake Baikal presents special opportunity for studying shifting trophic interactions among cryophilic zooplankton species in a rapidly warming lake. To understand how warming may affect trophic interactions among plankton, we studied predator–prey relationships of a copepod predator (Cyclops kolensis) with three prey types: two rotifer species (Gastropus stylifer and Keratella cochlearis) and copepod nauplii. We hypothesized that the less evasive Gastropus and Keratella would be more susceptible to predation than nauplii. We exposed a starved predator to individuals of each prey type and observed encounters, ingestions, and escapes. Contrary to our hypothesis, Keratella were consumed at lower rates than nauplii, due to higher probability of ingestion after encounter with nauplii. In a second experiment, we assessed how predation varied across a thermal gradient, confining all three prey types and one starved predator at 5° temperature increments (5–20°C). Predation outcomes mirrored observational feeding trials, and predation outcomes were independent of temperature. Rotifers’ relatively high reproductive rate may present a mechanism to withstand predation should copepod’s preferred nauplii prey become less abundant in a warmer Baikal.

Limited information is available about threshold lake nitrogen concentrations necessary to stimulate phytoplankton species and biomass responses in remote nitrogen-limited mountain lakes. We conducted in situ enrichment bioassays in mountain lakes within Mount Rainier, North Cascades, and Olympic National Parks in Washington State, USA to characterize phytoplankton species and biomass responses to nitrogen enrichment, and associated dissolved inorganic nitrogen (DIN) concentration thresholds. Based on biomass and growth measurements, phytoplankton were nitrogen-limited or co-limited by nitrogen and phosphorus in the nine bioassay lakes. We identified 20 taxa that responded to nitrogen enrichment, and estimated response thresholds using nitrogen Monod half-saturation constants (K s) for 18 of these taxa. DIN thresholds in nitrogen-limited lakes were 13 μg N l−1 for any increase in chlorophyll a, and 25 μg N l−1, for an increase beyond typical inter-annual chlorophyll a variation. K s values ranged from 0.02 to 77 μg N l−1 across most N-responsive taxa, and diatom K s values were higher than those previously quantified in U.S. Rocky Mountain lakes. Approximately, 75% of sampled mountain lakes in the parks have summer dissolved inorganic nitrogen concentrations below biomass response thresholds. This finding suggests that phytoplankton in park mountain lakes are likely sensitive to future deposition-induced lake nitrogen enrichment.

Eutrophication and warming of lakes are occurring globally. Lake Baikal, a large ancient lake composed of three basins, has recently experienced benthic eutrophication at local sites and lake warming in the south basin. Here, we look for signals of warming and pelagic eutrophication across the entire lake using physical and biological data collected at a subset of 79 stations sampled ca. annually (1977–2003) during the period of summer stratification. Lake-wide, surface waters warmed 2.0 °C; and, consistent with this warming, the abundance of two warm-water, cosmopolitan zooplankton taxa increased between two (pelagic cladocerans) and 12-fold (Cyclops kolensis). C. kolensis increased throughout the lake, whereas cladocerans increased significantly only in the north basin. In contrast, abundance of the cold-water endemic copepod, Epischura baikalensis, that dominates the crustacean zooplankton community, did not change. With the exception of one coastal station in the north basin, there is no evidence of pelagic eutrophication. Although chlorophyll concentrations increased 46% lake-wide (0.82 to 1.20 μg/L), the increasing trend was significant only in the south basin. Surprisingly, mean Secchi transparency increased by 1.4 m lake-wide across the 26-year time series with significant deepening of water transparency occurring in the central and north basins. This suggests a decline in productivity in the north and middle basins, but an increase in the south basin. Taken together, these findings suggest that physical and biological changes associated with warming have occurred in Lake Baikal, but wide-spread pelagic eutrophication in the lake's three basins has not.

The lower Columbia River (Washington and Oregon, USA) has been heavily invaded by a large number of planktonic organisms including the invasive copepod Pseudodiaptomus forbesi and the planktonic juveniles of the invasive clam, Corbicula fluminea. In order to assess the ecological impacts of these highly abundant invaders, we developed a multivariate auto-regressive (MAR) model of food web dynamics based upon a 12-year time-series of plankton community and environmental data from the Columbia River. Our model results indicate that plankton communities in the lower Columbia River are strongly impacted by the copepod P. forbesi at multiple trophic levels. We observed different ecological effects across different life stages of P. forbesi, with nauplii negatively impacting ciliates and autotrophs, and copepodite stages negatively impacting Daphnia and cyclopoid copepods. Although juvenile C. fluminea were highly abundant in the summer and autumn of each year, our best fit MAR model did not show significant C. fluminea impacts. Our results illustrate the strong ecological impact that some zooplankton invaders may cause within rivers and estuarine systems, and highlight the need for further research on the feeding ecology of the planktonic life-stage of C. fluminea. Overall, our study demonstrates the manner in which long-term, high resolution data sets can be used to better understand the ecological impacts of invasive species among complex and highly dynamic communities.

Synthesis centers are a recently-developed form of scientific organization that catalyzes and supports a form of interdisciplinary research that integrates diverse theories, methods and data across spatial or temporal scales, scientific phenomena, and forms of expertise to increase the generality, parsimony, applicability, or empirical soundness of scientific explanations. Research has shown the synthesis working group to be a distinctive form of scientific collaboration that reliably produces consequential, high-impact publications, but no one has asked: do synthesis working groups produce publications that are substantially more diverse than those produced outside of synthesis centers, and if so, how and with what effects? We have investigated these questions through a novel textual analysis. We found that if diversity is measured solely by mean difference in the Rao-Stirling (aggregate) measure of diversity, then the answer is no. But synthesis center papers have significantly greater variety and balance, but significantly lower disparity, than papers in the reference corpus. Synthesis center influence is mediated by the greater size of synthesis center collaborations (numbers of authors, distinct institutions, and references) but even when taking size into account, there is a persistent direct effect: synthesis center papers have significantly greater variety and balance, but less disparity, than papers in the reference corpus. We conclude by inviting further exploration of what this novel textual analysis approach might reveal about interdisciplinary research and by offering some practical implications of our results.

Winter is an important season for many limnological processes, which can range from biogeochemical transformations to ecological interactions. Interest in the structure and function of lake ecosyst ...

There is an increasing appreciation that food–energy–water (FEW) nexus problems are approaching criticality in both the developing and developed world. As researchers and managers attempt to address these complex resource management issues, the concept of the FEW nexus has generated a rapidly growing footprint in global sustainability discourse. However, this momentum in the FEW nexus space could be better guided if researchers could more clearly identify what is and is not a FEW problem. Without this conceptual clarity, it can be difficult to defend the position that FEW innovations will produce desired outcomes and avoid unintended consequences. Here we examine the growing FEW nexus scholarship to critically evaluate what features are necessary to define a FEW nexus. This analysis suggests that the FEW nexus differs from sector-focused natural resource or sustainability problems in both complexity and stakes. It also motivates two new foci for research: the identification of low-dimension indexes of FEW system status and approaches for identifying boundaries of specific FEW nexuses.

Winter primary production in seasonally ice-covered lakes historically has not been well studied, but it is increasingly recognized as an important component of lake metabolism. Lake Baikal in Siberia is not only the World's oldest, deepest, and most biologically diverse lake, but also where large under-ice blooms of the diatom Aulacoseira baicalensis (formerly Melosira) occur in some years. The phenomenon of “Melosira years” is noteworthy both for the intensity of the diatom blooms, in which total under-ice production can be a majority of total annual production, and for the enigmatic regularity of their occurrence every 3–4 yr. The degree to which these episodic blooms might be controlled by external forcing and endogenous lake processes has been debated for decades. We used a 50-yr time series of phytoplankton observations to statistically model the occurrence of Aulacoseira blooms as a function of meteorological and climatological predictor variables. The results support the hypothesis that a confluence of meteorological conditions in the preceding fall season, which favor clear ice formation with minimal snow cover, also favor Aulacoseira blooms in the following spring. Further, we observe that this confluence of factors is related to relatively strong states of the Siberian High which, while not strictly periodic, do explain a significant fraction of the interannual bloom pattern. Finally, our analyses show that the timing of the peak abundance of A. baicalensis shifted 1.6 months later across the 50-yr time series, corresponding with the delay in ice-on timing that has been associated with climate change.

Long-term patterns and drivers of ecosystem structure may be misunderstood if knowledge of an ecosystem is derivedprimarily from a single season, a situation common in many temperate lakes where the role of winter has been lessstudied. In lakes, avoidance of winter research has been especially pronounced for those that experience winter ice,but critical ecological processes can take place under ice. Even when obscured bysnow, ice transmitting as little as 2%incident light can allow relatively high rates of photosynthesis, and winter trophic interactions may have year-roundrepercussions. Here, we offer a suite of research questions that require attention, in order to build a mature under-standing of seasonal plankton dynamics in lakes. Specifically, we ask freshwater ecologists to consider the extent towhich abundance and nutrition of winter primary productivity supports consumers under the ice, reorganizes foodwebs,and how long the effects of winter trophic dynamics extend throughout theyear. In addition, we recognize somecritical gaps in knowledge about physical and biogeochemical conditions at the time of ice-off. Worldwide shorteningin ice duration lends imperative to under-ice studies, in order to more fully understand changes in ecosystem structureand function that mayalready be underway.KEYWORDS: winter; ice; plankton; trophic interactions; nutritional quality; state transitions

The ice‐covered period on lakes in the northern hemisphere has often been neglected or assumed to have less importance relative to the open water season. However, recent studies challenge this convention, suggesting that the winter period is more dynamic than previously thought. In this review, we synthesize the current understanding of under‐ice carbon dioxide (CO2) and methane (CH4) dynamics, highlighting the annual importance of CO2 and CH4 emissions from lakes at ice‐melt. We compiled data from 25 studies that showed that the ice‐melt period represents 17% and 27% of the annual CO2 and CH4 emissions, respectively. We also found evidence that the magnitude and type of emission (i.e., CO2 and CH4) varies with characteristics of lakes including geographic location, lake morphometry, and physicochemical conditions. The scarcity of winter and spring carbon data from northern lakes represents a major gap in our understanding of annual budgets in these lakes and calls for future research during this key period. Special Issue: Carbon cycling in inland waters: Progress and perspectives

The fundamental properties of organisms—what they are, how and where they live, and the biotic and abiotic interactions that link them to communities and ecosystems—are the domain of natural history. We provide examples illustrating the vital importance of natural history knowledge to many disciplines, from human health and food security to conservation, management, and recreation. We then present several lines of evidence showing that traditional approaches to and support for natural history in developed economies has declined significantly over the past 40 years. Finally, we argue that a revitalization of the practice of natural history—one that is focused on new frontiers in a rapidly changing world and that incorporates new technologies—would provide significant benefits for both science and society.

Long-term ecological data sets present opportunities for identifying drivers of community dynamics and quantifying their effects through time series analysis. Multivariate autoregressive (MAR) models are well known in many other disciplines, such as econometrics, but widespread adoption of MAR methods in ecology and natural resource management has been much slower despite some widely cited ecological examples. Here we review previous ecological applications of MAR models and highlight their ability to identify abiotic and biotic drivers of population dynamics, as well as community-level stability metrics, from long-term empirical observations. Thus far, MAR models have been used mainly with data from freshwater plankton communities; we examine the obstacles that may be hindering adoption in other systems and suggest practical modifications that will improve MAR models for broader application. Many of these modifications are already well known in other fields in which MAR models are common, although they are frequently described under different names. In an effort to make MAR models more accessible to ecologists, we include a worked example using recently developed R packages (MAR1 and MARSS), freely available and open-access software.

Multivariate autoregressive (MAR) models have been useful in elucidating food web dynamics and stability from freshwater plankton monitoring data, but their applicability to marine datasets has not been as well explored. Characteristics of marine systems, such as the movement of water masses by tides and currents, may present unique challenges to MAR modeling of data gathered in marine environments. To explore the behavior of MAR models with marine plankton data, in the context of what we know about applying MAR to freshwater data, we applied MARs to each of three freshwater and four marine long-term datasets and compared results among them. We generated sets of replicate MAR models for each dataset and used the consistency of models within each set of replicates as a measure of MAR performance. Overall, replicate MAR models generated from the marine datasets were less consistent than those generated from the freshwater datasets, suggesting that MAR methods need fundamental reconfigurations to be applied to standard marine plankton data. Higher variability observed within the marine MAR results may be attributable to weaker biotic interactions as represented by the data, and to overparameterization when the criteria for lumping freshwater plankton taxa into model variables are directly applied to marine plankton taxa. Adjustments to dataset preparation for MAR application and to the modeling framework itself may address these issues associated with analyzing data from highly dynamic systems.