Antarctic landfast sea ice (fast ice) is stationary sea ice that is attached to the coast, grounded icebergs, ice shelves, or other protrusions on the continental shelf. Fast ice forms in narrow (generally up to 200 km wide) bands, and ranges in thickness from centimeters to tens of meters. In most regions, it forms in autumn, persists through the winter and melts in spring/summer, but can remain throughout the summer in particular locations. Despite its relatively limited horizontal extent (comprising between about 4 and 13 \% of overall sea ice), its presence, variability and seasonality are drivers of a wide range of physical, biological and biogeochemical processes, with both local and far-ranging ramifications for various Earth systems. Antarctic fast ice has, until quite recently, been overlooked in studies, likely due to insufficient knowledge of its distribution, leading to its reputation as a “missing piece of the Antarctic puzzle”. This review presents a synthesis of current knowledge of the physical, biogeochemical and biological aspects of fast ice, based on the sub-domains of: fast ice growth, properties and seasonality; remote-sensing and distribution; interactions with the atmosphere and the ocean; biogeochemical interactions; its role in primary production; and fast ice as a habitat for grazers. Finally, we consider the potential state of Antarctic fast ice at the end of the 21st Century, underpinned by Coupled Model Intercomparison Project model projections. This review also gives recommendations for targeted future work to increase our understanding of this critically-important element of the global cryosphere.
Canada’s boreal forests and tundra ecosystems are responding to unprecedented climate change with implications for the global carbon (C) cycle and global climate. However, our ability to model the response of Canada’s terrestrial ecosystems to climate change is limited and there has been no comprehensive, process-based assessment of Canada’s terrestrial C cycle. We tailor the Canadian Land Surface Scheme Including Biogeochemical Cycles (CLASSIC) to Canada and evaluate its C cycling performance against independent reference data. We utilize skill scores to assess model performance against reference data alongside benchmark scores that quantify the level of agreement between the reference data sets to aid in interpretation. Our results demonstrate CLASSIC’s sensitivity to prescribed vegetation cover. They also show that the addition of five region-specific PFTs improves CLASSIC’s skill at simulating the Canadian C cycle. CLASSIC performs well when tailored to Canada, falls within the range of the reference data sets, and meets or exceeds the benchmark scores for most C cycling processes. New region-specific land cover products, well-informed plant functional type (PFT) parameterizations, and more detailed reference data sets will facilitate improvements to the representation of the terrestrial C cycle in regional and global land surface models (LSMs). Incorporating a parameterization for boreal disturbance processes and explicitly representing peatlands and permafrost soils will improve CLASSIC’s future performance in Canada and other boreal regions. This is an important step toward a comprehensive process-based assessment of Canada’s terrestrial C cycle and evaluating Canada’s net C balance under climate change.
The study was carried out to find significant lipid constituents of Sporotrichum schenckii (S. schenckii), purified lipid extract was assessed, and the ecology of S. schenckii was also studied. Phospholipids, triglycerides, and cholesterol were the three major lipid constituents of S. schenckii (77.9%). Other lipids (22.1%) were too few to be quantitated. 16 different types of fungi were isolated out of 120 samples processed; the maximum isolations were of Aspergillus spp., the most typical contaminant fungus. There was no particular correlation between the fungus isolate and the type of sample or its collection site. The pattern of various fungal isolates was almost identical irrespective of the sample and place. None of the samples processed was positive for S. schenckii. S. schenckii, though said to be a saprophyte, was not grown in the 120 samples studied. The endemicity of the disease, however, points towards the existence of the fungus in the area.
Minerals are information-rich materials that offer researchers a glimpse into the evolution of planetary bodies. Thus it is important to extract, analyze, and interpret this abundance of information in order to improve our understanding of the planetary bodies in our solar system and the role our planet’s geosphere played in the origin and evolution of life. Over the past decades, data-driven efforts in mineralogy have seen a gradual increase. The development and application of data science and analytics methods to mineralogy, while extremely promising, has also been somewhat ad-hoc in nature. In order to systematize and synthesize the direction of these efforts, we introduce the concept of “Mineral Informatics”. Mineral Informatics is the next frontier for researchers working with mineral data. In this paper, we present our vision for Mineral Informatics, the X-Informatics underpinnings that led to its conception, the needs, challenges, opportunities, and future directions. The intention of this paper is not to create a new specific field or a sub-field as a separate silo, but to document the needs of researchers studying minerals in various contexts and fields of study, to demonstrate how the systemization and increased access to mineralogical data will increase cross- and interdisciplinary studies, and how data science and informatics methods are a key next step in integrative mineralogical studies.
Soil biogeochemical models (SBMs) simulate element transfer processes between organic soil pools. These models can be used to specify falsifiable quantitative assertions about soil system dynamics and their responses to global surface temperature warming. To determine whether SBMs are useful for representing and forecasting data-generating processes in soils, it is important to conduct data assimilation and fitting of SBMs conditioned on soil pool and flux measurements to validate model predictive accuracy. SBM data assimilation has previously been carried out in approaches ranging from visual qualitative tuning of model output against data to more statistically rigorous Bayesian inferences that estimate posterior parameter distributions with Markov chain Monte Carlo (MCMC) methods. MCMC inference is better able to account for data and parameter uncertainty, but the computational inefficiency of MCMC methods limits their ability to scale assimilations to larger data sets. With formulation of efficient and statistically rigorous SBM inference frameworks remaining an open problem, we demonstrate the novel application of a variational inference framework that uses a method called normalizing flows to approximate SBMs that have been discretized into state space models. We fit the approximated SBMs to synthetic data sourced from known data-generating processes to identify discrepancies between the inference results and true parameter values and ensure functionality of our method. Our approach trades estimation accuracy for algorithmic efficiency gains that make SBM data assimilation more tractable and achievable under computational time and resource limitations.
[This presentation is published at https://doi.org/10.1111/1440-1703.12317] Dead organic matter (DOM), which consists of leaf litter, fine woody debris (FWD; < 3 cm diameter), downed coarse woody debris (CWDlog), and standing or suspended coarse woody debris (CWDsnag), plays a crucial role in forest carbon cycling. However, the contributions of each DOM type on stand-scale carbon storage (necromass) and stand-scale CO2 efflux (Rstand) estimates are not well understood. In addition, there is little knowledge of the effect of each DOM type on the accuracy of stand-scale estimates of total necromass and Rstand. This study investigated characteristics of necromass and Rstand from DOM in a subtropical forest in Okinawa island, Japan, to quantify the effect of each DOM type on total necromass, total Rstand, and estimate error of total necromass and Rstand. The CWDsnag accounted for the highest proportion (54%) of total necromass (1499.7 g C m–2), followed by CWDlog (24%), FWD (11%), and leaf litter (11%). Leaf litter accounted for the highest proportion (37%) of total Rstand (340.6 g C m–2 yr–1), followed by CWDsnag (25%), CWDlog (20%), and FWD (17%). The CWDsnag was distributed locally with 173% of the coefficient of variation for necromass, which was approximately two times higher than those of leaf litter and FWD (72–73%). Our spatial analysis revealed, for accurate estimates of CWDsnag and CWDlog necromass, sampling areas of ≥ 28750 m2 and ≥ 2058‒42875 m2 were required, respectively, under the condition of 95% confidence level and 0.1 of accepted error. In summary, CWD considerably contributed to stand-scale carbon storage and efflux in this subtropical forest, resulting in a major source of errors in the stand-scale estimates. In forests where frequent tree death is likely to occur, necromass and Rstand of CWD are not negligible in considering the carbon cycling as in this study, and therefore need to be estimated accurately.
To integrate temporal and spatial dimensions of seasonal cycles, we combine two conceptual frameworks: ecological calendars and the “3Hs” model of the biocultural ethic. The latter values the vital links between human and other-than-human co-inhabitants, their life habits (e.g., cultural practices of human communities or life cycles of other-than-human species) and the structure, patterns and processes of their shared habitats. This integration enhances an understanding of core links between cultural practices and the life cycles of biocultural keystone species. As a synthesis, we use the term biocultural calendars to emphasize the co-constitutive nature of calendars that result from continuous interactions between dynamic biophysical and cultural processes. We apply biocultural calendars to examine cultural practices and socio-environmental changes in southwestern South America, specifically in Chile, spanning from (1) Cape Horn at the southern of the Americas in sub-Antarctic habitats inhabited by the Yagan indigenous community, (2) artisanal fisher communities in Chiloe; archipelagoes, (3) coastal regions of central-southern Chile inhabited by Lafkenche and Williche indigenous communities, to (4) high Andean habitats in northern Chile co-inhabited by Aymara communities along with domesticated camelids and a rich biodiversity. To illustrate biocultural calendars, we designed analemma diagrams that show the position of the Sun in the sky as seen from a fixed time and location, and linked to continuous renewal of astronomical, biological and cultural, seasonal cycles that sustain life. These biocultural calendars enhance the integration of indigenous and scientific knowledge to confront complex challenges of climate change faced by local communities and global society.
Several bills moving through Congress are likely to provide significant funding for expanding research and results in climate change solutions (CCS). This is also a priority of the Biden-Harris Administration. The National Science Foundation (NSF) will be expected to distribute and manage much of this funding through its grant processes. Effective solutions require both a continuation and expansion of research on climate change–to understand and thus plan for potential impacts locally to globally and to continually assess solutions against a changing climate–and rapid adoption and implementation of this science with society at all levels. NSF asked AGU to convene its community to help provide guidance and recommendations for enabling significant and impactful CCS outcomes by 1 June. AGU was asked in particular to address the following: 1. Identify the biggest, more important interdisciplinary/convergent challenges in climate change that can be addressed in the next 2 to 3 years 2. Create 2-year and 3-year roadmaps to address the identified challenges. Indicate partnerships required to deliver on the promise. 3. Provide ideas on the creation of an aggressive outreach/communications plan to inform the public and decision makers on the critical importance of geoscience. 4. Identify information, training, and other resources needed to embed a culture of innovation, entrepreneurialism, and translational research in the geosciences. Given the short time frame for this report, AGU reached out to key leaders, including Council members, members of several committees, journal editors, early career scientists, and also included additional stakeholders from sectors relevant to CCS, including community leaders, planners and architects, business leaders, NGO representatives, and others. Participants were provided a form to submit ideas, and also invited to two workshops. The first was aimed at ideation around broad efforts and activities needed for impactful CCS; the second was aimed at in depth development of several broad efforts at scale. Overall, about 125 people participated; 78 responded to the survey, 82 attended the first workshop, and 28 attended the more-focused second workshop (see contributor list). This report provides a high-level summary of these inputs and recommendations, focusing on guiding principles and several ideas that received broader support at the workshops and post-workshop review. These guiding principles and ideas cover a range of activities and were viewed as having high importance for realizing impactful CCS at the scale of funding anticipated. These cover the major areas of the charge, including research and solutions, education, communication, and training. The participants and full list of ideas and suggestions are provided as an appendix. Many contributed directly to this report; the listed authors are the steering committee.
Sexual harassment in STEM continues to be a pervasive barrier to women’s full participation in the sciences. Many studies conclude that workplace culture and lack of clear policies and practices exacerbate the risks of sexual harassment. Remote research environments, such as field stations and ocean platforms, bring additional risk to researchers. Participants already face acute safety concerns related to the remoteness of the field station or oceanographic vessels, fewer and less clear policies and enforcement regulations are in place, and multiple institutions bear responsibility, leading to a challenging environment for preventing and handling incidents. This workshop explored the factors that permit sexual harassment in remote research, and aimed to develop practices to prevent and respond to harassment in the field. The California State University Desert Studies Center and the Center for Ocean Leadership convened workshop in March, 2021 to address sexual harassment in field science. Over three days, field and ocean science leadership and practitioners came together with leadership from professional societies and academia, and experts in sociology, policy, and social justice. The goals were to: 1) open a dialogue between sexual harassment experts and the field research community to develop best practices and recommendations; 2) build coordination and consistency in policy setting and enforcement across field stations and oceanographic platforms; 3) develop processes to monitor the reporting of sexual harassment instances occurring at remote field locations; and 4) promote a safe culture for scientists conducting research at remote field stations and on oceanographic vessels. The workshop compiled and developed best practices and recommendations in four key areas: 1) culture change, 2) policy, 3) accountability, and 4) reporting. These recommendations were targeted at all facets of field and ocean sciences, from academic and research institutions, professional societies, and funding agencies, to departments and field research crews. Here we will give an overview of the workshop findings, with particular focus on the recommendations for research leadership.
Moisture recycling via evapotranspiration (ET) is often invoked as a mechanism for the high deuterium excess signals observed in continental precipitation (dP). However, a global-scale analysis of precipitation monitoring station isotope data shows that metrics of ET contributions to precipitation (van der Ent et al., 2014) explain little dp variability on seasonal timescales. This occurs despite the fact that ET contributions increase by ~50% in continental locations such as the Eurasian interior from wet to dry seasons. To explain this apparent paradox, we hypothesize that the effects of ET on dP are dampened during dry seasons due to contributions from isotopically-evolved residual water storage that act to lower the d-excess of ET fluxes (dET), in combination with changes in transpiration fraction (T/ET). To test this hypothesis, we develop a parsimonious two-season (wet, dry) model for dET incorporating residual water storage and ET partitioning effects. We find that in environments with limited water storage, such as shallow-rooted grasslands, dry season dET is lower than wet season dET despite lower relative humidity. As global average ratios of annual water storage to precipitation are relatively low (Guntner et al., 2007), these dynamics may be widespread over continents. In environments where water storage is not limiting, such as groundwater-dependent ecosystems, dry season dET is still likely lower; however, this effect arises instead due to higher seasonal T/ET when energy-driven plant water use is enhanced and surface evaporation is relatively limited by water availability. Together, these analyses also indicate multiple mechanisms by which dET may be lower than dp during the same season, challenging the view that moisture recycling feedback increases the dp in continental interiors. This work demonstrates the potential complexity of seasonal dp dynamics and cautions against simple interpretations of dP as a process tracer for moisture recycling. References: Guntner et al., 2007. Water Resour. Res., 43, W05416. van der Ent et al., 2014. Earth Syst. Dynam., 5, 471–489.
1. This study combines two approaches to explore the utility of Monod growth kinetics to predict competition outcomes between freshwater cyanobacteria and chlorophytes at low iron Fe. Fe threshold concentrations (FeT) below which growth ceases, and growth affinities (slope of Fe concentration vs growth rate near FeT) were estimated for three large-bodied cyanobacteria (two N-fixers and Microcystis) and two chlorophytes in batch cultures. 2. Mean FeT for N-replete cyanobacteria, N-deplete (when N-fixing) cyanobacteria and chlorophytes were 0.076, 0.736 and 0.245 nmol L-1 , respectively. Mean affinities were 0.937, 0.597 and 0.412 L nmol-1 d-1 , respectively. Assuming that the mean affinities are representative of their groups, affinities predict that N-replete cyanobacteria are more efficient at acquiring Fe than chlorophytes and should dominate when Fe is low but greater than their FeT. 3. A second study evaluated the competitive abilities of a pico-cyanobacterium and a third chlorophyte in dual species, serial dilution culture. The pico-cyanobacterium was dominant at 50 nmol L-1 total Fe (which limited both taxa) and 500 nmol L-1 total Fe. At 0.5 nmol L-1 total Fe, a stressful concentration below FeT during most of the incubation, growth rates and cell densities were extremely low but neither had washed out after several months. 4. These results show that Monod kinetics can successfully predict competition outcomes in laboratory settings at low Fe. While important, Monod kinetics are only one mechanism governing competition between cyanobacteria and eukaryotes in natural systems. Observed deviations from Monod predictions can be partially explained with known mechanisms.
Earth’s Critical Zone (CZ), the near-surface layer where rock is weathered and landscapes co-evolve with life, is profoundly influenced by the type of underlying bedrock. Previous studies employing the CZ framework have focused almost exclusively on landscapes dominated by silicate rocks. However, carbonate rocks crop out on approximately 15% of Earth’s ice-free continental surface and provide important water resources and ecosystem services to ~1.2 billion people. Unlike silicates, carbonate minerals weather congruently and have high solubilities and rapid dissolution kinetics, enabling the development of large, interconnected pore spaces and preferential flow paths that restructure the CZ. Here we review the state of knowledge of the carbonate CZ, exploring parameters that produce contrasts in the CZ in different carbonate settings and identifying important open questions about carbonate CZ processes. We introduce the concept of a carbonate-silicate CZ spectrum and examine whether current conceptual models of the CZ, such as the conveyor model, can be applied to carbonate landscapes.We argue that, to advance beyond site-specific understanding and develop a more general conceptual framework for the role of carbonates in the CZ, we need integrative studies spanning both the carbonate-silicate spectrum and a range of carbonate settings.
Vegetation acts as a critical link between the geosphere, biosphere, and atmosphere, regulating the flux of water to the atmosphere via transpiration (E) and the input of carbon from the atmosphere to plants and soil via photosynthetic carbon assimilation (A). The rate of A is known to be seasonally dynamic, however, few studies have investigated how the ratio between E and A, known as the water use efficiency (WUE), changes with phenology. WUE directly impacts regional to global carbon and water cycles and lack of knowledge regarding the dynamics of WUE remains among the largest uncertainties in current earth system model (ESM) projections of carbon and water exchange in temperate forests. Here we attempt to reduce this knowledge gap by studying these dynamics across a range of eight deciduous tree species common to temperate forests of North America. Using gas exchange and spectroscopic measurements, we investigated seasonal patterns in leaf level physiological, biochemical, and anatomical properties, including the seasonal progress of WUE and foliar capacity for carbon assimilation, which corollate with seasonal leaf phenology. We incorporate these findings into a modeling framework that contains the same representation of A, E, and canopy scaling found in ESMs to explore the impact of parameterization, which tracks phenological status, on model forecasts. Our results indicate that both photosynthetic capacity and WUE are seasonally dynamic processes which are not synchronized. WUE increased from a minimum at leaf out toward a more conservative behavior at the mid-summer growth peak. This pattern was explained by a decreased stomatal aperture and a decrease in cuticular leakage with leaf aging. We also observed a seasonal increase in maximum carboxylation capacity, with maximum rates of A and modeled tree net primary productivity (NPP) occurring later toward the end of the summer. This change was primarily driven by an increase in foliar nitrogen content, and a shift in the ratio of Vcmax to Jmax between expanding and mature leaves. By applying our revised parameterization, which captures seasonal dynamics of gas exchange, into our model framework we aim to improve the process representation of leaf function in a temperate forest, and more faithfully represent dynamics of NPP and E in the early and late growth season.
Mangrove forests are among the most productive ecosystems in the world. These tropical and subtropical coastal forests provide a wide array of ecosystem services, including the ability to sequester and store large amounts of ‘blue carbon’. Given rising concerns over anthropogenic carbon dioxide (CO2) emissions, mangrove forests have been increasingly recognized for their potential in climate change mitigation programs. However, their productivity differs considerably across environments, making it difficult to estimate carbon sequestration potentials at regional scales. Additionally, most research has focused in humid and tropical latitudes, with limited studies in arid and semi-arid regions. A semi-arid mangrove forest in Magdalena Bay, Baja California Sur, Mexico was studied to quantify the average net ecosystem exchange (NEE), determine the annual carbon (C) budget and the environmental controls driving those fluxes. Measurements were taken during 2012-2013 using the eddy covariance technique, with a daily mean NEE of -2.25 +/- 0.4 g C m-2 d-1 and annual carbon uptake of 894 g C m-2 y-1. Daily variations in NEE were primarily regulated by light, but air temperature and vapor pressure deficit were strong seasonal drivers. Our research demonstrates that despite the harsh and arid climate, the mangroves of Magdalena Bay were nearly as productive as mangroves found in tropical and subtropical climates. These results broaden understanding of the ecosystem services of one of the largest mangrove ecosystems in the Baja California peninsula, and highlight the potential role of arid mangrove ecosystems for C accounting, management and mitigation plans for the region.
Ocean governance is characterised by social-ecological complexity and divergence in stakeholder values and perspectives. Meeting the challenges set out in the UN Decade of Ocean Science for Sustainable Development will require transdisciplinary approaches that can embrace multiple ways of knowing to develop shared understandings within interdependent communities of practice and ensure they can be applied in interventions that are adaptive, proactive, socially just, critically reflexive and fit to meet the Decade’s challenges. We present the outcomes of an innovative participatory art process, the Exquisite Corpse Project, with the aim of highlighting multiple perspectives, and developing empathy between participants. We will engage a selected group of researchers from the emerging ‘Ocean Art-Ocean Science’ community to explore the topic of marine heatwaves and their impacts based on data collected in the Northeast Pacific by Ocean Networks Canada and other sources. Through a facilitated process, participants will create three pieces of art that will build on each other and will be exchanged between participants. At the end, all created artworks will be reviewed by the full group to explore emerging insights on marine heatwaves and to surface participants’ underlying values and emotions, which is rarely done in scientific circles where the main mode of discourse employs rational dispassionate exchange. By creating a fun, emotionally-engaging process, we aim to show how the Exquisite Corpse project can strengthen interpersonal bonds, build social cohesion, create opportunities to surface people’s values and perspectives, and develop new transdisciplinary insights in a non-confrontational way. This study is part of an ongoing process exploring transdisciplinary approaches for multidirectional art-science collaborations and developing new research methods for including artistic insight and expression within the scientific discovery process. Instead of the conventional ‘outward looking’ strategy of many art-science projects translating scientific outputs to new formats, our approach is primarily ‘inward looking’. We aim to provide an opportunity for scientists to create art, thus allowing them to explore their own emotions, values and experiences through different ways of knowing.
Inland waters are hotspots of greenhouse gas (GHG) emissions, and small water bodies are now well known to be particularly active in the production and consumption of carbon dioxide (CO2), methane (CH4), and nitrous oxide (N2O). High variability in physical, chemical, and environmental parameters affect the production of these GHG, but currently the mechanistic underpinnings are unclear, leading to high uncertainty in scaling up these fluxes. Here, we compare the relative magnitudes and controls of emissions of all three major GHG in twenty pairs of natural wetland ponds and constructed reservoirs in Canada’s largest agricultural region. While gaseous fluxes of CO2 and CH4 were comparable between the two waterbody types, CH4 ebullition was greater in wetland ponds. Carbon dioxide levels were associated primarily with metabolic indicators in both water body types, with primary productivity paramount in agricultural reservoirs, and heterotrophic metabolism a stronger correlate in wetland ponds. Methane emissions were positively driven by eutrophication in the reservoirs, while competitive inhibition by sulfur-reducing bacteria may have limited CH4 in both waterbody types. Contrary to expectations, N2O was undersaturated in both water body types, with wetlands a significantly stronger and more widespread N2O sink than were reservoirs. These results support the need for natural and constructed water bodies for regional GHG budgets and identification of GHG processing hotspots.
Plant growth and development is impacted by the ability to capture resources including sunlight, determined in part by the arrangement of plant parts throughout the canopy. This is a very complex trait to describe, but has a major impact on downstream traits such as biomass or grain yield per acre. Though some is known about genetic factors contributing to leaf angle, maturity, and leaf size and number, these discrete traits do not encompass the structural complexity of the canopy. In addition, modeling and prediction for plant developmental traits using genomics or phenomics are usually conducted separately. We have developed proof-of-concept models that incorporate spatio-temporal factors from drone-acquired LiDAR features in a maize diversity panel to predict plant growth and development over time to improve our understanding of the biology of canopy formation and development. Briefly, voxel models for probability of beam penetration into the foliage were generated from 3D LiDAR scans collected at seven dates throughout crop canopy development. From the same plots, key architectural features of the maize canopy were measured by hand: stand count; plant, tassel, and flag leaf height; anthesis and silking dates; ear leaf, total leaf, and largest leaf number; and largest leaf length and width. We develop a self-supervised autoencoding neural network architecture that separately encodes plant temporal growth patterns for individual genotypes and plant spatial distributions for each plot. Then, leveraging the resulting latent space encoding of the LiDAR scans, we train and demonstrate accurate prediction of hand-measured crop traits.
Near-term freshwater forecasts, defined as sub-daily to decadal future predictions of a freshwater variable with quantified uncertainty, are urgently needed to improve water quality management as freshwater ecosystems exhibit greater variability due to global change. Shifting baselines in freshwater ecosystems due to land use and climate change prevent managers from relying on historical averages for predicting future conditions, necessitating near-term forecasts to mitigate freshwater risks to human health and safety (e.g., flash floods, harmful algal blooms). To assess the current state of freshwater forecasting and identify opportunities for future progress, we synthesized freshwater forecasting papers published in the past five years. We found that freshwater forecasting is currently dominated by near-term forecasts of water quantity and that near-term water quality forecasts are fewer in number and in early stages of development (i.e., non-operational), despite their potential as important preemptive decision support tools. We contend that more freshwater quality forecasts are critically needed, and that near-term water quality forecasting is poised to make substantial advances based on examples of recent progress in forecasting methodology, workflows, and end user engagement. For example, current water quality forecasting systems can predict water temperature, dissolved oxygen, and algal bloom/toxin events five days ahead with reasonable accuracy. Continued progress in freshwater quality forecasting will be greatly accelerated by adapting tools and approaches from freshwater quantity forecasting (e.g., machine learning modeling methods). In addition, future development of effective operational freshwater quality forecasts necessitates substantive engagement of end users throughout the forecast process, funding, and training opportunities. Looking ahead, near-term forecasting provides a hopeful future for freshwater management in the face of increased variability and risk due to global change, and we encourage the freshwater scientific community to incorporate forecasting approaches in water quality research and management.