Collaborative Understanding of Cyanobacteria in Lake Ecosystems

We describe a collaboration between mathematicians and ecologists studying the cyanobacterium Gloeotrichia echinulata and its possible role in eutrophication of New England lakes. The mathematics includes compartmental modeling, differential equations, difference equations, and testing models against high-frequency data. The ecology includes observation, field sampling, and parameter estimation based on observed data and the related literature. Mathematically and ecologically, a collaboration like this progresses in ways it never would have if either group worked alone

Spatial and Temporal Variability in Recruitment of the Cyanobacterium Gloeotrichia echinulata in an Oligotrophic Lake

Recruitment from dormant stages in the benthos can provide a critically important inoculum for surface populations of phytoplankton, including bloom-forming cyanobacteria. For example, water-column populations of the large (1–3-mm diameter) colonial cyanobacterium Gloeotrichia echinulata (Smith) P. Richter can be strongly subsidized by benthic recruitment. Therefore, understanding controls on recruitment is essential to an investigation of the factors controlling Gloeotrichiablooms, which are increasing in low-nutrient lakes across northeastern North America. We quantified surface abundances and recruitment from littoral sediments at multiple near-shore sampling sites in oligotrophic Lake Sunapee, New Hampshire, USA, during the summers of 2005–2012 and used this data set—the longest known record of cyanobacterial recruitment—to investigate potential drivers of interannual differences in Gloeotrichia recruitment. We found extensive spatiotemporal variability in recruitment. Recruitment was higher at some sites than others, and within seasons, recruitment into replicate traps at the same site was generally more similar than recruitment at different sites. These data suggest that local factors, such as substrate quality or the size of the seed bank, may be important controls on recruitment. Benthic recruitment probably accounted forGloeotrichia recruitment may be related to regional climatic variability

Cyanobacteria as biological drivers of Lake Nitrogen and Phosphorus Cycling

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 N2 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

“New” cyanobacterial blooms are not new: two centuries of lake production are related to ice cover and land use

Recent cyanobacterial blooms in otherwise unproductive lakes may be warning signs of impending eutrophication in lakes important for recreation and drinking water, but little is known of their historical precedence or mechanisms of regulation. Here, we examined long-term sedimentary records of both general and taxon-specific trophic proxies from seven lakes of varying productivity in the northeastern United States to investigate their relationship to historical in-lake, watershed, and climatic drivers of trophic status. Analysis of fossil pigments (carotenoids and chlorophylls) revealed variable patterns of past primary production across lakes over two centuries despite broadly similar changes in regional climate and land use. Sediment abundance of the cyanobacterium Gloeotrichia, a large, toxic, nitrogen-fixing taxon common in recent blooms in this region, revealed that this was not a new taxon in the phytoplankton communities but rather had been present for centuries. Histories of Gloeotrichia abundance differed strikingly across lakes and were not consistently associated with most other sediment proxies of trophic status. Changes in ice cover most often coincided with changes in fossil pigments, and changes in watershed land use were often related to changes in Gloeotrichia abundance, although no single climatic or land-use factor was associated with proxy changes across all seven lakes. The degree to which changes in lake sediment records co-occurred with changes in the timing of ice-out or agricultural land use was negatively correlated with the ratio of watershed area to lake area. Thus, both climate and land management appeared to play key roles in regulation of primary production in these lakes, although the manner in which these factors influenced lakes was mediated by catchment morphometry. Improved understanding of the past interactions between climate change, land use, landscape setting, and water quality underscores the complexity of mechanisms regulating lake and cyanobacterial production and highlights the necessity of considering these interactions—rather than searching for a singular mechanism—when evaluating the causes of ongoing changes in low-nutrient lakes

Quantitative Factors Proposed to Influence the Prevalence of Canine Tick-Bourne Disease Agents in the United States

The Companion Animal Parasite Council hosted a meeting to identify quantifiable factors that can influence the prevalence of tick-borne disease agents among dogs in North America. This report summarizes the approach used and the factors identified for further analysis with mathematical models of canine exposure to tick-borne pathogens

Quantitative Factors Proposed to Influence the Prevalence of Canine Tick-Borne Disease Agents in the United States

The Companion Animal Parasite Council hosted a meeting to identify quantifiable factors that can influence the prevalence of tick-borne disease agents among dogs in North America. This report summarizes the approach used and the factors identified for further analysis with mathematical models of canine exposure to tick-borne pathogens

Using near-term forecasts and uncertainty partitioning to improve predictions of low-frequency cyanobacterial events

Near-term ecological forecasts provide resource managers advance notice of changes in ecosystem services, such as fisheries stocks, timber yields, or water and air quality. Importantly, ecological forecasts can identify where uncertainty enters the forecasting system, which is necessary to refine and improve forecast skill and guide interpretation of forecast results. Uncertainty partitioning identifies the relative contributions to total forecast variance (uncertainty) introduced by different sources, including specification of the model structure, errors in driver data, and estimation of initial state conditions. Uncertainty partitioning could be particularly useful in improving forecasts of high-density cyanobacterial events, which are difficult to predict and present a persistent challenge for lake managers. Cyanobacteria can produce toxic or unsightly surface scums and advance warning of these events could help managers mitigate water quality issues. Here, we calibrate fourteen Bayesian state-space models to evaluate different hypotheses about cyanobacterial growth using data from eight summers of weekly cyanobacteria density samples in an oligotrophic (low nutrient) lake that experiences sporadic surface scums of the toxin-producing cyanobacterium, Gloeotrichia echinulata. We identify dominant sources of uncertainty for near-term (one-week to four-week) forecasts of G. echinulata densities over two years. Water temperature was an important predictor in calibration and at the four-week forecast horizon. However, no environmental covariates improved over a simple autoregressive (AR) model at the one-week horizon. Even the best fit models exhibited large variance in forecasted cyanobacterial densities and often did not capture rare peak density occurrences, indicating that significant explanatory variables in calibration are not always effective for near-term forecasting of low-frequency events. Uncertainty partitioning revealed that model process specification and initial conditions uncertainty dominated forecasts at both time horizons. These findings suggest that observed densities result from both growth and movement of G. echinulata, and that imperfect observations as well as spatial misalignment of environmental data and cyanobacteria observations affect forecast skill. Future research efforts should prioritize long-term studies to refine process understanding and increased sampling frequency and replication to better define initial conditions. Our results emphasize the importance of ecological forecasting principles and uncertainty partitioning to refine and understand predictive capacity across ecosystems.Accepted manuscrip

Ruxolitinib versus best available therapy for polycythemia vera intolerant or resistant to hydroxycarbamide in a randomized trial

Purpose Polycythemia vera (PV) is characterized by JAK/STAT activation, thrombotic/hemorrhagic events, systemic symptoms, and disease transformation. In high-risk PV, ruxolitinib controls blood counts and improves symptoms. Patients and Methods MAJIC-PV is a randomized phase II trial of ruxolitinib versus best available therapy (BAT) in patients resistant/intolerant to hydroxycarbamide (HC-INT/RES). Primary outcome was complete response (CR) within 1 year. Secondary outcomes included duration of response, event-free survival (EFS), symptom, and molecular response. Results One hundred eighty patients were randomly assigned. CR was achieved in 40 (43%) patients on ruxolitinib versus 23 (26%) on BAT (odds ratio, 2.12; 90% CI, 1.25 to 3.60; P = .02). Duration of CR was superior for ruxolitinib (hazard ratio [HR], 0.38; 95% CI, 0.24 to 0.61; P < .001). Symptom responses were better with ruxolitinib and durable. EFS (major thrombosis, hemorrhage, transformation, and death) was superior for patients attaining CR within 1 year (HR, 0.41; 95% CI, 0.21 to 0.78; P = .01); and those on ruxolitinib (HR, 0.58; 95% CI, 0.35 to 0.94; P = .03). Serial analysis of JAK2V617F variant allele fraction revealed molecular response was more frequent with ruxolitinib and was associated with improved outcomes (progression-free survival [PFS] P = .001, EFS P = .001, overall survival P = .01) and clearance of JAK2V617F stem/progenitor cells. ASXL1 mutations predicted for adverse EFS (HR, 3.02; 95% CI, 1.47 to 6.17; P = .003). The safety profile of ruxolitinib was as previously reported. Conclusion The MAJIC-PV study demonstrates ruxolitinib treatment benefits HC-INT/RES PV patients with superior CR, and EFS as well as molecular response; importantly also demonstrating for the first time, to our knowledge, that molecular response is linked to EFS, PFS, and OS

Effects of antiplatelet therapy on stroke risk by brain imaging features of intracerebral haemorrhage and cerebral small vessel diseases: subgroup analyses of the RESTART randomised, open-label trial

Background Findings from the RESTART trial suggest that starting antiplatelet therapy might reduce the risk of recurrent symptomatic intracerebral haemorrhage compared with avoiding antiplatelet therapy. Brain imaging features of intracerebral haemorrhage and cerebral small vessel diseases (such as cerebral microbleeds) are associated with greater risks of recurrent intracerebral haemorrhage. We did subgroup analyses of the RESTART trial to explore whether these brain imaging features modify the effects of antiplatelet therapy

Do the effects of early childhood education programs differ by gender? A meta-analysis

A meta-analysis was conducted to examine gender differences in the effects of early childhood education programs on children's cognitive, academic, behavioral, and adult outcomes. Significant and roughly equal impacts for boys and girls on cognitive and achievement measures were found, although there were no significant effects for either gender on child behavior and adult outcomes such as employment and educational attainment. Boys benefited significantly more from these programs than girls on other school outcomes such as grade retention and special education classification. We also examined important indicators of program quality that could be associated with differential effects by gender