Ecotypic differences in the phenology of the tundra species Eriophorum vaginatum reflect sites of origin

Eriophorum vaginatum is a tussock-forming sedge that contributes significantly to the structure and primary productivity of moist acidic tussock tundra. Locally adapted populations (ecotypes) have been identified across the geographical distribution of E. vaginatum; however, little is known about how their growth and phenology differ over the course of a growing season. The growing season is short in the Arctic and therefore exerts a strong selection pressure on tundra species. This raises the hypothesis that the phenology of arctic species may be poorly adapted if the timing and length of the growing season change. Mature E. vaginatum tussocks from across a latitudinal gradient (65–70°N) were transplanted into a common garden at a central location (Toolik Lake, 68°38′N, 149°36′W) where half were warmed using open-top chambers. Over two growing seasons (2015 and 2016), leaf length was measured weekly to track growth rates, timing of senescence, and biomass accumulation. Growth rates were similar across ecotypes and between years and were not affected by warming. However, southern populations accumulated significantly more biomass, largely because they started to senesce later. In 2016, peak biomass and senescence of most populations occurred later than in 2015, probably induced by colder weather at the beginning of the growing season in 2016, which caused a delayed start to growth. The finish was delayed as well. Differences in phenology between populations were largely retained between years, suggesting that the amount of time that these ecotypes grow has been selected by the length of the growing seasons at their respective home sites. As potential growing seasons lengthen, E. vaginatum may be unable to respond appropriately as a result of genetic control and may have reduced fitness in the rapidly warming Arctic tundra

Flocking to fire: How climate and natural hazards shape human migration across the United States

As global climate change progresses, the United States (US) is expected to experience warmer temperatures as well as more frequent and severe extreme weather events, including heat waves, hurricanes, and wildfires. Each year, these events cost dozens of lives and do billions of dollars' worth of damage, but there has been limited research on how they influence human decisions about migration. Are people moving toward or away from areas most at risk from these climate threats? Here, we examine recent (2010–2020) trends in human migration across the US in relation to features of the natural landscape and climate, as well as frequencies of various natural hazards. Controlling for socioeconomic and environmental factors, we found that people have moved away from areas most affected by heat waves and hurricanes, but toward areas most affected by wildfires. This relationship may suggest that, for many, the dangers of wildfires do not yet outweigh the perceived benefits of life in fire-prone areas. We also found that people have been moving toward metropolitan areas with relatively hot summers, a dangerous public health trend if mean and maximum temperatures continue to rise, as projected in most climate scenarios. These results have implications for policymakers and planners as they prepare strategies to mitigate climate change and natural hazards in areas attracting migrants

Machine Learning for Early Warning of Cyanobacteria Blooms in Lake Champlain

Cyanobacteria blooms are a major problem in Lake Champlain, producing toxins that can harm swimmers, poison pets, and disrupt aquatic ecosystems. Every summer, bays along the lakeshore see recurrent blooms that close beaches and endanger public health. Blooms are driven by the complex interactions of multiple factors. Phosphorus is thought to be a key driver, but nitrogen, water temperature, and mixing by wind and weather events may all play a role. Untangling these multiple drivers makes it difficult to understand, let alone predict, the formation and timing of blooms. While severe blooms can be identified visually, measuring cyanobacteria levels in water samples is time and resource intensive, making it impractical to track levels on a daily basis or catch rising levels before a bloom becomes visible. Monitoring cyanobacteria would be simpler if levels could be reliably predicted from other factors that are easier to measure. Predicting blooms a few days in advance would benefit public safety by giving municipalities advanced warning to prevent or better-manage blooms and their public health impacts. Machine learning algorithms can find patterns among multiple variables that might be missed by traditional statistical methods. They may lend insight into this problem by helping to identify combinations of factors linked to bloom formation, or even allowing us to forecast blooms a few days in advance by using data on current water and weather conditions. We will apply a variety of machine learning methods to a unique, public, long-term data set produced by the VT Department of Environmental Conservation. We will analyze ten years of data on water quality and cyanobacteria levels from around Lake Champlain with the goal of predicting cyanobacteria levels from easily measured water quality indicators

Data_Sheet_1_Flocking to fire: How climate and natural hazards shape human migration across the United States.pdf

As global climate change progresses, the United States (US) is expected to experience warmer temperatures as well as more frequent and severe extreme weather events, including heat waves, hurricanes, and wildfires. Each year, these events cost dozens of lives and do billions of dollars' worth of damage, but there has been limited research on how they influence human decisions about migration. Are people moving toward or away from areas most at risk from these climate threats? Here, we examine recent (2010–2020) trends in human migration across the US in relation to features of the natural landscape and climate, as well as frequencies of various natural hazards. Controlling for socioeconomic and environmental factors, we found that people have moved away from areas most affected by heat waves and hurricanes, but toward areas most affected by wildfires. This relationship may suggest that, for many, the dangers of wildfires do not yet outweigh the perceived benefits of life in fire-prone areas. We also found that people have been moving toward metropolitan areas with relatively hot summers, a dangerous public health trend if mean and maximum temperatures continue to rise, as projected in most climate scenarios. These results have implications for policymakers and planners as they prepare strategies to mitigate climate change and natural hazards in areas attracting migrants.</p

Data from: Ecotypic differences in the phenology of the tundra species Eriophorum vaginatum reflect sites of origin

Eriophorum vaginatum is a tussock-forming sedge that contributes significantly to the structure and primary productivity of moist acidic tussock tundra. Locally adapted populations (ecotypes) have been identified across the geographical distribution of E. vaginatum; however, little is known about how their growth and phenology differ over the course of a growing season. The growing season is short in the Arctic and therefore exerts a strong selection pressure on tundra species. This raises the hypothesis that the phenology of arctic species may be poorly adapted if the timing and length of the growing season change. Mature E. vaginatum tussocks from across a latitudinal gradient (65–70°N) were transplanted into a common garden at a central location (Toolik Lake, 68°38′N, 149°36′W) where half were warmed using open-top chambers. Over two growing seasons (2015 and 2016), leaf length was measured weekly to track growth rates, timing of senescence, and biomass accumulation. Growth rates were similar across ecotypes and between years and were not affected by warming. However, southern populations accumulated significantly more biomass, largely because they started to senesce later. In 2016, peak biomass and senescence of most populations occurred later than in 2015, probably induced by colder weather at the beginning of the growing season in 2016, which caused a delayed start to growth. The finish was delayed as well. Differences in phenology between populations were largely retained between years, suggesting that the amount of time that these ecotypes grow has been selected by the length of the growing seasons at their respective home sites. As potential growing seasons lengthen, E. vaginatum may be unable to respond appropriately as a result of genetic control and may have reduced fitness in the rapidly warming Arctic tundra

Toolik Lake Common garden Phenology Dataset

Toolik Lake Common garden Phenology Datase

Cerebral malaria: We have come a long way

Despite decades of research, cerebral malaria remains one of the most serious complications of Plasmodium infection and is a significant burden in Sub-Saharan Africa, where, despite effective antiparasitic treatment, survivors develop long-term neurological sequelae. Although much remains to be discovered about the pathogenesis of cerebral malaria, The American Journal of Pathology has been seminal in presenting original research from both human and experimental models. These studies have afforded significant insight into the mechanism of cerebral damage in this devastating disease. The present review highlights information gleaned from these studies, especially in terms of their contributions to the understanding of cerebral malaria