Browsing by Author "Weathers, Kathleen C."

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    Can interactive data visualizations promote waterfront best management practices?
    Ward, Nicole K.; Sorice, Michael G.; Reynolds, Mikaila S.; Weathers, Kathleen C.; Weng, Weizhe; Carey, Cayelan C. (Taylor & Francis, 2022-01-02)
    Lake water quality management often requires private property owner engagement since land-use change generally occurs on private property. Educational components of lake management outreach must connect current property owner behaviors with future water quality. However, it may be challenging for property owners to associate their current behaviors with water quality outcomes due to the time lag between a behavior (e.g., fertilizer application) and a water quality outcome (e.g., decreased water clarity). Interactive data visualizations, characterized by user-determined selections that change visualization output, may be well suited to help property owners connect current behavior to future water quality. We tested the effectiveness of an online, interactive visualization as an educational intervention to alter property owners' perspectives related to applying lawn fertilizer and installing waterfront buffers. We used cognitive psychology measures to quantify intervention effectiveness. Since property owners' decision making may be driven by connections to their property, we also explored relationships between seasonal and permanent residents and intentions to apply fertilizer or install waterfront buffers and intervention effectiveness. Despite no significant difference in effectiveness between the interactive and noninteractive versions, the combined responses demonstrated a positive shift in behavioral beliefs and intentions related to lawn fertilizer application and waterfront buffer installation. Seasonal residents were less likely than permanent residents to apply lawn fertilizer before the intervention and more likely to shift their intentions after the intervention. This study provides evidence that brief educational interventions-regardless of their interactivity-can shift private property owner beliefs and intentions regarding lakefront property management.
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    Cyanobacteria as biological drivers of lake nitrogen and phosphorus cycling
    Cottingham, Kathryn L.; Ewing, Holly A.; Greer, Meredith L.; Carey, Cayelan C.; Weathers, Kathleen C. (Ecological Society of America, 2015-01)
    Here we draw attention to the potential for pelagic bloom-forming cyanobacteria to have substantial effects on nutrient cycling and ecosystem resilience across a wide range of lakes. Specifically, we hypothesize that cyanobacterial blooms can influence lake nutrient cycling, resilience, and regime shifts by tapping into pools of nitrogen (N) and phosphorus (P) not usually accessible to phytoplankton. The ability of many cyanobacterial taxa to fix dissolved N-2 gas is a well-known potential source of N, but some taxa can also access pools of P in sediments and bottom waters. Both of these nutrients can be released to the water column via leakage or mortality, thereby increasing nutrient availability for other phytoplankton and microbes. Moreover, cyanobacterial blooms are not restricted to high nutrient (eutrophic) lakes: blooms also occur in lakes with low nutrient concentrations, suggesting that changes in nutrient cycling and ecosystem resilience mediated by cyanobacteria could affect lakes across a gradient of nutrient concentrations. We used a simple model of coupled N and P cycles to explore the effects of cyanobacteria on nutrient dynamics and resilience. Consistent with our hypothesis, parameters reflecting cyanobacterial modification of N and P cycling alter the number, location, and/or stability of model equilibria. In particular, the model demonstrates that blooms of cyanobacteria in low-nutrient conditions can facilitate a shift to the high-nutrient state by reducing the resilience of the low-nutrient state. This suggests that cyanobacterial blooms warrant attention as potential drivers of the transition from a low-nutrient, clear-water regime to a high-nutrient, turbid-water regime, a prediction of particular concern given that such blooms are reported to be increasing in many regions of the world due in part to global climate change.
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    Differential Responses of Maximum Versus Median Chlorophyll‐a to Air Temperature and Nutrient Loads in an Oligotrophic Lake Over 31 Years
    Ward, Nicole K.; Steele, Bethel G.; Weathers, Kathleen C.; Cottingham, Kathryn L.; Ewing, Holly A.; Hanson, Paul C.; Carey, Cayelan C. (AGU, 2020-05-28)
    Globally, phytoplankton abundance is increasing in lakes as a result of climate change and land‐use change. The relative importance of climate and land‐use drivers has been examined primarily for mesotrophic and eutrophic lakes. However, oligotrophic lakes show different sensitivity to climate and land‐use drivers than mesotrophic and eutrophic lakes, necessitating further exploration of the relative contribution of the two drivers of change to increased phytoplankton abundance. Here, we investigated how air temperature (a driver related to climate change) and nutrient load (a driver related to land‐use and climate change) interact to alter water quality in oligotrophic Lake Sunapee, New Hampshire, USA. We used long‐term data and the one‐dimensional hydrodynamic General Lake Model (GLM) coupled with Aquatic EcoDyanmics (AED) modules to simulate water quality. Over the 31‐year simulation, summer median chlorophyll‐a concentration was positively associated with summer air temperature, whereas annual maximum chlorophyll‐a concentration was positively associated with the previous 3 years of external phosphorus load. Scenario testing demonstrated a 2°C increase in air temperature significantly increased summer median chlorophyll‐a concentration, but not annual maximum chlorophyll‐a concentration. For both maximum and median chlorophyll‐a concentration, doubling external nutrient loads of total nitrogen and total phosphorus at the same time, or doubling phosphorus alone, resulted in a significant increase. This study highlights the importance of aligning lake measurements with the ecosystem metrics of interest, as maximum chlorophyll‐a concentration may be more uniquely sensitive to nutrient load and that typical summer chlorophyll‐a concentration may increase due to warming alone.
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    Dynamic modeling of organic carbon fates in lake ecosystems
    McCullough, Ian M.; Dugan, Hilary A.; Farrell, Kaitlin J.; Morales-Williams, Ana M.; Ouyang, Zutao; Roberts, Derek C.; Scordo, Facundo; Bartlett, Sarah L.; Burke, Samantha M.; Doubek, Jonathan P.; Krivak-Tetley, Flora E.; Skaff, Nicholas K.; Summers, Jamie C.; Weathers, Kathleen C.; Hanson, Paul C. (2018-10-24)
    Lakes are active processors of organic carbon (OC) and play important roles in landscape and global carbon cycling. Allochthonous OC loads from the landscape, along with autochthonous OC loads from primary production, are mineralized in lakes, buried in lake sediments, and exported via surface or groundwater outflows. Although these processes provide a basis for a conceptual understanding of lake OC budgets, few studies have integrated these fluxes under a dynamic modeling framework to examine their interactions and relative magnitudes. We developed a simple, dynamic mass balance model for OC, and applied the model to a set of five lakes. We examined the relative magnitudes of OC fluxes and found that long-term (> 10 year) lake OC dynamics were predominantly driven by allochthonous loads in four of the five lakes, underscoring the importance of terrestrially-derived OC in northern lake ecosystems. Our model highlighted seasonal patterns in lake OC budgets, with increasing water temperatures and lake productivity throughout the growing season corresponding to a transition from burial- to respiration-dominated OC fates. Ratios of respiration to burial, however, were also mediated by the source (autochthonous vs. allochthonous) of total OC loads. Autochthonous OC is more readily respired and may therefore proportionally reduce burial under a warming climate, but allochthonous OC may increase burial due to changes in precipitation. The ratios of autochthonous to allochthonous inputs and respiration to burial demonstrate the importance of dynamic models for examining both the seasonal and inter-annual roles of lakes in landscape and global carbon cycling, particularly in a global change context. Finally, we highlighted critical data needs, which include surface water DOC observations in paired tributary and lake systems, measurements of OC burial rates, groundwater input volume and DOC, and budgets of particulate OC.
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    Dynamics of the stream-lake transitional zone affect littoral lake metabolism
    Ward, Nicole K.; Brentrup, Jennifer A.; Richardson, David C.; Weathers, Kathleen C.; Hanson, Paul C.; Hewett, Russell J.; Carey, Cayelan C. (Springer, 2022-07)
    Lake ecosystems, as integrators of watershed and climate stressors, are sentinels of change. However, there is an inherent time-lag between stressors and whole-lake response. Aquatic metabolism, including gross primary production (GPP) and respiration (R), of stream-lake transitional zones may bridge the time-lag of lake response to allochthonous inputs. In this study, we used high-frequency dissolved oxygen data and inverse modeling to estimate daily rates of summer epilimnetic GPP and R in a nutrient-limited oligotrophic lake at two littoral sites located near different major inflows and at a pelagic site. We examined the relative importance of stream variables in comparison to meteorological and in-lake predictors of GPP and R. One of the inflow streams was substantially warmer than the other and primarily entered the lake's epilimnion, whereas the colder stream primarily mixed into the metalimnion or hypolimnion. Maximum GPP and R rates were 0.2-2.5 mg O-2 L-1 day(-1) (9-670%) higher at littoral sites than the pelagic site. Ensemble machine learning analyses revealed that > 30% of variability in daily littoral zone GPP and R was attributable to stream depth and stream-lake transitional zone mixing metrics. The warm-stream inflow likely stimulated littoral GPP and R, while the cold-stream inflow only stimulated littoral zone GPP and R when mixing with the epilimnion. The higher GPP and R observed near inflows in our study may provide a sentinel-of-the-sentinel signal, bridging the time-lag between stream inputs and in-lake processing, enabling an earlier indication of whole-lake response to upstream stressors.
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    From concept to practice to policy: modeling coupled natural and human systems in lake catchments
    Cobourn, Kelly M.; Carey, Cayelan C.; Boyle, Kevin J.; Duffy, Christopher J.; Dugan, Hilary A.; Farrell, Kaitlin J.; Fitchett, Leah Lynn; Hanson, Paul C.; Hart, Julia A.; Henson, Virginia Reilly; Hetherington, Amy L.; Kemanian, Armen R.; Rudstam, Lars G.; Shu, Lele; Soranno, Patricia A.; Sorice, Michael G.; Stachelek, Joseph; Ward, Nicole K.; Weathers, Kathleen C.; Weng, Weizhe; Zhang, Yu (Ecological Society of America, 2018-05-03)
    Recent debate over the scope of the U.S. Clean Water Act underscores the need to develop a robust body of scientific work that defines the connectivity between freshwater systems and people. Coupled natural and human systems (CNHS) modeling is one tool that can be used to study the complex, reciprocal linkages between human actions and ecosystem processes. Well‐developed CNHS models exist at a conceptual level, but the mapping of these system representations in practice is limited in capturing these feedbacks. This article presents a paired conceptual–empirical methodology for functionally capturing feedbacks between human and natural systems in freshwater lake catchments, from human actions to the ecosystem and from the ecosystem back to human actions. We address extant challenges in CNHS modeling, which arise from differences in disciplinary approach, model structure, and spatiotemporal resolution, to connect a suite of models. In doing so, we create an integrated, multi‐disciplinary tool that captures diverse processes that operate at multiple scales, including land‐management decision‐making, hydrologic‐solute transport, aquatic nutrient cycling, and civic engagement. In this article, we build on this novel framework to advance cross‐disciplinary dialogue to move CNHS lake‐catchment modeling in a systematic direction and, ultimately, provide a foundation for smart decision‐making and policy.
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    Granular measures of agricultural land use influence lake nitrogen and phosphorus differently at macroscales
    Stachelek, Joseph; Weng, W.; Carey, Cayelan C.; Kemanian, Armen R.; Cobourn, Kelly M.; Wagner, Tyler K.; Weathers, Kathleen C.; Soranno, Patricia A. (2020-12)
    Agricultural land use is typically associated with high stream nutrient concentrations and increased nutrient loading to lakes. For lakes, evidence for these associations mostly comes from studies on individual lakes or watersheds that relate concentrations of nitrogen (N) or phosphorus (P) to aggregate measures of agricultural land use, such as the proportion of land used for agriculture in a lake's watershed. However, at macroscales (i.e., in hundreds to thousands of lakes across large spatial extents), there is high variability around such relationships and it is unclear whether considering more granular (or detailed) agricultural data, such as fertilizer application, planting of specific crops, or the extent of near-stream cropping, would improve prediction and inform understanding of lake nutrient drivers. Furthermore, it is unclear whether lake N and P would have different relationships to such measures and whether these relationships would vary by region, since regional variation has been observed in prior studies using aggregate measures of agriculture. To address these knowledge gaps, we examined relationships between granular measures of agricultural activity and lake total phosphorus (TP) and total nitrogen (TN) concentrations in 928 lakes and their watersheds in the Northeastern and Midwest U.S. using a Bayesian hierarchical modeling approach. We found that both lake TN and TP concentrations were related to these measures of agriculture, especially near-stream agriculture. The relationships between measures of agriculture and lake TN concentrations were more regionally variable than those for TP. Conversely, TP concentrations were more strongly related to lake-specific measures like depth and watershed hydrology relative to TN. Our finding that lake TN and TP concentrations have different relationships with granular measures of agricultural activity has implications for the design of effective and efficient policy approaches to maintain and improve water quality.
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    Integrating fast and slow processes is essential for simulating human-freshwater interactions
    Ward, Nicole K.; Fitchett, Leah Lynn; Hart, Julia A.; Shu, Lele; Stachelek, Joseph; Weng, Weizhe; Zhang, Yu; Dugan, Hilary A.; Hetherington, Amy L.; Boyle, Kevin J.; Carey, Cayelan C.; Cobourn, Kelly M.; Hanson, Paul C.; Kemanian, Armen R.; Sorice, Michael G.; Weathers, Kathleen C. (Springer, 2019-10-01)
    Integrated modeling is a critical tool to evaluate the behavior of coupled human–freshwater systems. However, models that do not consider both fast and slow processes may not accurately reflect the feedbacks that define complex systems. We evaluated current coupled human–freshwater system modeling approaches in the literature with a focus on categorizing feedback loops as including economic and/or socio-cultural processes and identifying the simulation of fast and slow processes in human and biophysical systems. Fast human and fast biophysical processes are well represented in the literature, but very few studies incorporate slow human and slow biophysical system processes. Challenges in simulating coupled human–freshwater systems can be overcome by quantifying various monetary and non-monetary ecosystem values and by using data aggregation techniques. Studies that incorporate both fast and slow processes have the potential to improve complex system understanding and inform more sustainable decision-making that targets effective leverage points for system change.
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    Intra- and inter-annual variability in metabolism in an oligotrophic lake
    Richardson, David C.; Carey, Cayelan C.; Bruesewitz, Denise A.; Weathers, Kathleen C. (2017-04)
    Lakes are sentinels of change in the landscapes in which they are located. Changes in lake function are reflected in whole-system metabolism, which integrates ecosystem processes across spatial and temporal scales. Recent improvements in high-frequency open-water metabolism modeling techniques have enabled estimation of rates of gross primary production (GPP), respiration (R), and net ecosystem production (NEP) at high temporal resolution. However, few studies have examined metabolic rates over daily to multi-year temporal scales, especially in oligotrophic ecosystems. Here, we modified a metabolism modeling technique to reveal substantial intra- and inter-annual variability in metabolic rates in Lake Sunapee, a temperate, oligotrophic lake in New Hampshire, USA. Annual GPP and R increased each summer, paralleling increases in littoral, but not pelagic, total phosphorus concentrations. Storms temporarily decoupled GPP and R, resulting in greater decreases in GPP than R. Daily rates of GPP and R were positively correlated on warm days that had stable water columns, and metabolism model fits were best on warm, sunny days, indicating the importance of lake physics when evaluating metabolic rates. These metabolism data span a range of temporal scales and together suggest that Lake Sunapee may be moving toward mesotrophy. We suggest that functional, integrative metrics, such as metabolic rates, are useful indicators and sentinels of ecosystem change. We also highlight the challenges and opportunities of using high-frequency measurements to elucidate the drivers and consequences of intra- and inter-annual variability in metabolic rates, especially in oligotrophic lakes.
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    Modeling lake ecosystem change within coupled human-natural systems to improve water resources management
    Ward, Nicole Kristine (Virginia Tech, 2021-05-24)
    Lake ecosystems are sentinels of change in a landscape, integrating upstream terrestrial and aquatic effects of climate and land use drivers. Climate and land use change is mediated by socio-cultural and economic processes, resulting in complex responses in lake ecosystems as a part of coupled natural human (CNH) systems. I used multiple approaches within a CNH framework to better understand the effects of climate and land use on freshwater-human interactions. I first conducted a literature synthesis and found that slow processes (e.g., cultural change) are underrepresented in CNH-freshwater models relative to fast processes (e.g., daily decision-making), though both fast and slow processes are key to assessing decadal trajectories of change. I then examined the interaction of fast and slow variables in lakes through two ecosystem modeling assessments. I used a process-based model to assess drivers of annual chlorophyll-a concentration, a metric of phytoplankton biomass, over three decades in a low-nutrient lake and found that increases in summer median versus maximum chlorophyll-a are related to rising air temperatures and external phosphorus load, respectively. I also conducted a single-year study in the same lake to examine variability in site-specific gross primary production (GPP) and respiration (R), two fast-changing variables that serve as robust indicators of slowly-changing trophic state. I found that higher rates of near-shore GPP and R were partially due to stream-related variables, providing insight into how inflowing streams connect to in-lake processes. These two ecosystem assessment studies indicate fast-changing response variables can be indicative of specific slow-changing variables: annual maximum versus median chlorophyll-a can be used to assess differing impacts from climate and land use change, and estimation of GPP and R near inflow streams integrate sub-catchment drivers. Finally, I evaluated the effectiveness of an online model visualization relating current land use decisions, a fast process, to future water quality outcomes, a slow process, and found that the visualization was effective in altering property owner beliefs and intended behavior related to applying lawn fertilizer and installing waterfront buffers. Collectively, this work advances our understanding of how fast and slow variables interact to improve assessments of changes in CNH-lake systems.
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    A Practical Guide for Managing Interdisciplinary Teams: Lessons Learned from Coupled Natural and Human Systems Research
    Henson, V. Reilly; Cobourn, Kelly M.; Weathers, Kathleen C.; Carey, Cayelan C.; Farrell, Kaitlin J.; Klug, Jennifer L.; Sorice, Michael G.; Ward, Nicole K.; Weng, Weizhe (MDPI, 2020-07-09)
    Interdisciplinary team science is essential to address complex socio-environmental questions, but it also presents unique challenges. The scientific literature identifies best practices for high-level processes in team science, e.g., leadership and team building, but provides less guidance about practical, day-to-day strategies to support teamwork, e.g., translating jargon across disciplines, sharing and transforming data, and coordinating diverse and geographically distributed researchers. This article offers a case study of an interdisciplinary socio-environmental research project to derive insight to support team science implementation. We evaluate the project’s inner workings using a framework derived from the growing body of literature for team science best practices, and derive insights into how best to apply team science principles to interdisciplinary research. We find that two of the most useful areas for proactive planning and coordinated leadership are data management and co-authorship. By providing guidance for project implementation focused on these areas, we contribute a pragmatic, detail-oriented perspective on team science in an effort to support similar projects.
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    The Roles of Local Organizations in Collaborative Resource Governance: A Qualitative Case Study of Lake Associations
    Fitchett, Leah Lynn (Virginia Tech, 2019-09-05)
    Human communities across the globe are currently facing an epidemic of lake water quality degradation, primarily resulting from resource and land-use decisions that introduce excessive amounts of nutrients into the lake system. In many of these communities, local volunteer groups called lake associations work to protect these cherished lake resources. Lake associations and similar groups commonly respond to issues that are most prevalent in their respective watersheds including, but not limited to, algae blooms, declines in water transparency, and fish kills. Yet, there is little research on the role these groups actively or potentially play in lake governance and management. This study investigates the specific structures and strategies lake associations use to address lake water quality challenges using a comparative case analysis of two organizations: Lake Sunapee Protective Association (LSPA; Sunapee, NH) and Clean Lakes Alliance (CLA; Madison, WI). I performed a content analysis of self-published newsletters, annual reports, and news publications mentioning either lake association, and supplemented this data with semi-structured interviews of key individuals from each organization. I characterized and compared the missions, capacity, and activity of the two case studies by applying a conceptual framework as a lens through which to better understand the function these groups serve in their communities and what makes them effective. I found that, although the two groups structure themselves differently, take on distinct activity pathways, and orient themselves differently with respect to lake conservation, they have both been effective in achieving decision-making or management outcomes. This is a first step in identifying the diversity of ways community-based conservation organizations, such as lake associations, can meaningfully contribute to collaborative environmental governance processes on the local scale.
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    Salting our freshwater lakes
    Dugan, Hilary A.; Bartlett, Sarah L.; Burke, Samantha M.; Doubek, Jonathan P.; Krivak-Tetley, Flora E.; Skaff, Nicholas K.; Summers, Jamie C.; Farrell, Kaitlin J.; McCullough, Ian M.; Morales-Williams, Ana M.; Roberts, Derek C.; Ouyang, Zutao; Scordo, Facundo; Hanson, Paul C.; Weathers, Kathleen C. (NAS, 2017-03-08)
    The highest densities of lakes on Earth are in north temperate ecosystems, where increasing urbanization and associated chloride runoff can salinize freshwaters and threaten lake water quality and the many ecosystem services lakes provide. However, the extent to which lake salinity may be changing at broad spatial scales remains unknown, leading us to first identify spatial patterns and then investigate the drivers of these patterns. Significant decadal trends in lake salinization were identified using a dataset of long-term chloride concentrations from 371 North American lakes. Landscape and climate metrics calculated for each site demonstrated that impervious land cover was a strong predictor of chloride trends in Northeast and Midwest North American lakes. As little as 1% impervious land cover surrounding a lake increased the likelihood of long-term salinization. Considering that 27% of large lakes in the United States have >1% impervious land cover around their perimeters, the potential for steady and long-term salinization of these aquatic systems is high. This study predicts that many lakes will exceed the aquatic life threshold criterion for chronic chloride exposure (230 mg L⁻¹), stipulated by the US Environmental Protection Agency (EPA), in the next 50 y if current trends continue.
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    Training macrosystems scientists requires both interpersonal and technical skills
    Farrell, Kaitlin J.; Weathers, Kathleen C.; Sparks, Sarah H.; Brentrup, Jennifer A.; Carey, Cayelan C.; Dietze, Michael C.; Foster, John R.; Grayson, Kristine L.; Matthes, Jaclyn H.; SanClements, Michael D. (2021-02)
    Macrosystems science strives to integrate patterns and processes that span regional to continental scales. The scope of such research often necessitates the involvement of large interdisciplinary and/or multi-institutional teams composed of scientists across a range of career stages, a diversity that requires researchers to hone both technical and interpersonal skills. We surveyed participants in macrosystems projects funded by the US National Science Foundation to assess the perceived importance of different skills needed in their research, as well as the types of training they received. Survey results revealed a mismatch between the skills participants perceive as important and the training they received, particularly for interpersonal and management skills. We highlight lessons learned from macrosystems training case studies, explore avenues for further improvement of undergraduate and graduate education, and discuss other training opportunities for macrosystems scientists. Given the trend toward interdisciplinary research beyond the macrosystems community, these insights are broadly applicable for scientists involved in diverse, collaborative projects.
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    Transparency, Geomorphology and Mixing Regime Explain Variability in Trends in Lake Temperature and Stratification across Northeastern North America (1975–2014)
    Richardson, David C.; Melles, Stephanie J.; Pilla, Rachel M.; Hetherington, Amy L.; Knoll, Lesley B.; Williamson, Craig E.; Kraemer, Benjamin M.; Jackson, James R.; Long, Elizabeth C.; Moore, Karen; Rudstam, Lars G.; Rusak, James A.; Saros, Jasmine E.; Sharma, Sapna; Strock, Kristin E.; Weathers, Kathleen C.; Wigdahl-Perry, Courtney R. (MDPI, 2017-06-20)
    Lake surface water temperatures are warming worldwide, raising concerns about the future integrity of valuable lake ecosystem services. In contrast to surface water temperatures, we know far less about what is happening to water temperature beneath the surface, where most organisms live. Moreover, we know little about which characteristics make lakes more or less sensitive to climate change and other environmental stressors. We examined changes in lake thermal structure for 231 lakes across northeastern North America (NENA), a region with an exceptionally high density of lakes. We determined how lake thermal structure has changed in recent decades (1975–2012) and assessed which lake characteristics are related to changes in lake thermal structure. In general, NENA lakes had increasing near-surface temperatures and thermal stratification strength. On average, changes in deepwater temperatures for the 231 lakes were not significantly different than zero, but individually, half of the lakes experienced warming and half cooling deepwater temperature through time. More transparent lakes (Secchi transparency >5 m) tended to have higher near-surface warming and greater increases in strength of thermal stratification than less transparent lakes. Whole-lake warming was greatest in polymictic lakes, where frequent summer mixing distributed heat throughout the water column. Lakes often function as important sentinels of climate change, but lake characteristics within and across regions modify the magnitude of the signal with important implications for lake biology, ecology and chemistry.
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    Uncertainty in projections of future lake thermal dynamics is differentially driven by lake and global climate models
    Wynne, Jacob H.; Woelmer, Whitney M.; Moore, Tadhg N.; Thomas, R. Quinn; Weathers, Kathleen C.; Carey, Cayelan C. (PeerJ, 2023-06-02)
    Freshwater ecosystems provide vital services, yet are facing increasing risks from global change. In particular, lake thermal dynamics have been altered around the world as a result of climate change, necessitating a predictive understanding of how climate will continue to alter lakes in the future as well as the associated uncertainty in these predictions. Numerous sources of uncertainty affect projections of future lake conditions but few are quantified, limiting the use of lake modeling projections as management tools. To quantify and evaluate the effects of two potentially important sources of uncertainty, lake model selection uncertainty and climate model selection uncertainty, we developed ensemble projections of lake thermal dynamics for a dimictic lake in New Hampshire, USA (Lake Sunapee). Our ensemble projections used four different climate models as inputs to five vertical one-dimensional (1-D) hydrodynamic lake models under three different climate change scenarios to simulate thermal metrics from 2006 to 2099. We found that almost all the lake thermal metrics modeled (surface water temperature, bottom water temperature, Schmidt stability, stratification duration, and ice cover, but not thermocline depth) are projected to change over the next century. Importantly, we found that the dominant source of uncertainty varied among the thermal metrics, as thermal metrics associated with the surface waters (surface water temperature, total ice duration) were driven primarily by climate model selection uncertainty, while metrics associated with deeper depths (bottom water temperature, stratification duration) were dominated by lake model selection uncertainty. Consequently, our results indicate that researchers generating projections of lake bottom water metrics should prioritize including multiple lake models for best capturing projection uncertainty, while those focusing on lake surface metrics should prioritize including multiple climate models. Overall, our ensemble modeling study reveals important information on how climate change will affect lake thermal properties, and also provides some of the first analyses on how climate model selection uncertainty and lake model selection uncertainty interact to affect projections of future lake dynamics.
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    Using near-term forecasts and uncertainty partitioning to inform prediction of oligotrophic lake cyanobacterial density
    Lofton, Mary E.; Brentrup, Jennifer A.; Beck, Whitney S.; Zwart, Jacob A.; Bhattacharya, Ruchi; Brighenti, Ludmila S.; Burnet, Sarah H.; McCullough, Ian M.; Steele, Bethel G.; Carey, Cayelan C.; Cottingham, Kathryn L.; Dietze, Michael C.; Ewing, Holly A.; Weathers, Kathleen C.; LaDeau, Shannon L. (Wiley, 2022-03)
    Near-term ecological forecasts provide resource managers advance notice of changes in ecosystem services, such as fisheries stocks, timber yields, or water quality. Importantly, ecological forecasts can identify where there is uncertainty in the forecasting system, which is necessary to improve forecast skill and guide interpretation of forecast results. Uncertainty partitioning identifies the relative contributions to total forecast variance introduced by different sources, including specification of the model structure, errors in driver data, and estimation of current states (initial conditions). Uncertainty partitioning could be particularly useful in improving forecasts of highly variable cyanobacterial densities, which are difficult to predict and present a persistent challenge for lake managers. As cyanobacteria can produce toxic and unsightly surface scums, advance warning when cyanobacterial densities are increasing could help managers mitigate water quality issues. Here, we fit 13 Bayesian state-space models to evaluate different hypotheses about cyanobacterial densities in a low nutrient lake that experiences sporadic surface scums of the toxin-producing cyanobacterium, Gloeotrichia echinulata. We used data from several summers of weekly cyanobacteria samples to identify dominant sources of uncertainty for near-term (1- to 4-week) forecasts of G. echinulata densities. Water temperature was an important predictor of cyanobacterial densities during model fitting and at the 4-week forecast horizon. However, no physical covariates improved model performance over a simple model including the previous week's densities in 1-week-ahead forecasts. Even the best fit models exhibited large variance in forecasted cyanobacterial densities and did not capture rare peak occurrences, indicating that significant explanatory variables when fitting models to historical data are not always effective for forecasting. Uncertainty partitioning revealed that model process specification and initial conditions dominated forecast uncertainty. These findings indicate that long-term studies of different cyanobacterial life stages and movement in the water column as well as measurements of drivers relevant to different life stages could improve model process representation of cyanobacteria abundance. In addition, improved observation protocols could better define initial conditions and reduce spatial misalignment of environmental data and cyanobacteria observations. Our results emphasize the importance of ecological forecasting principles and uncertainty partitioning to refine and understand predictive capacity across ecosystems.
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    Virtual Growing Pains: Initial Lessons Learned from Organizing Virtual Workshops, Summits, Conferences, and Networking Events during a Global Pandemic
    Meyer, Michael F.; Ladwig, Robert; Dugan, Hilary A.; Anderson, Alyssa; Bah, Abdou R.; Boehrer, Bertram; Borre, Lisa; Chapina, Rosaura J.; Doyle, Chris; Favot, Elizbaeth J.; Flaim, Giobanna; Forsberg, Philip; Hanson, Paul C.; Ibelings, Bas W.; Isles, Peter; Lin, Fang-Pang; Lofton, Dendy; Moore, Tadhg N.; Peel, Sara; Peters, Jody A.; Pierson, Don; de Senerpont Domis, Lisette N.; Schloss, Jeffrey A.; Shikhani, Muhammed; Smagula, Amy P.; Stockwell, Jason D.; Thomas, Perry; Thomas, R. Quinn; Tietjen, Todd; Weathers, Kathleen C. (Wiley, 2021-02-01)
    For many, 2020 was a year of abrupt professional and personal change. For the aquatic sciences community, many were adapting to virtual formats for conducting and sharing science, while simultaneously learning to live in a socially distanced world. Understandably, the aquatic sciences community postponed or canceled most in-person scientific meetings. Still, many scientific communities either transitioned annual meetings to a virtual format or inaugurated new virtual meetings. Fortunately, increased use of video conferencing platforms, networking and communication applications, and a general comfort with conducting science virtually helped bring the in-person meeting experience to scientists worldwide. Yet, the transition to conducting science virtually revealed new barriers to participation whereas others were lowered. The combined lessons learned from organizing a meeting constitute a necessary knowledge base that will prove useful, as virtual conferences are likely to continue in some form. To concentrate and synthesize these experiences, we showcase how six scientific societies and communities planned, organized, and conducted virtual meetings in 2020. With this consolidated information in hand, we look forward to a future, where scientific meetings embrace a virtual component, so to as help make science more inclusive and global.