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For 76 annual, biennial, and perennial species common in the grasslands of central Minnesota, USA, we determined the patterns of correlations among seven organ-level traits (specific leaf area, leaf thickness, leaf tissue density, leaf angle, specific root length, average fine root diameter, and fine root tissue density) and their relationships with two traits relating to growth form (whether species existed for part of the growing season in basal, non-caulescent form and whether species were rhizomatous or not). The first correlation of traits showed that grasses had thin, dense leaves and thin roots while forbs had thick, low-density leaves and thick roots without any significant differences in growth form or life history. The second correlation of traits showed a gradient of species from those with high-density roots and high-density erect leaves to species with low-density roots and low-density leaves that were held parallel to the ground. High tissue density species were more likely to exist as a basal rosette for part of the season, were less likely to be rhizomatous, and less likely to be annuals. We examined the relationships between the two axes that represent the correlations of traits and previously collected data on the relative abundance of species across gradients of nitrogen addition and disturbance. Grasses were generally more abundant than forbs and the relative abundance of grasses and forbs did not change with increasing nitrogen addition or soil disturbance. High tissue density species became less common as fertility and disturbance increased.

Grasses and forbs are often classified into separate functional types, although systematic differences between the types have only been verified for a few functional traits. Since leaf longevity has been shown to be a key trait linking plant ecophysiology, whole-plant growth and ecosystem resource cycling, we compared the leaf longevity of 14 species to determine if there were consistent differences between grasses and forbs or other functional classifications, such as persistence of leaves into winter. Leaf longevity was assessed in 6-yr-old monoculture plots in central North America by tagging and sequentially monitoring the phenological states of whole forb leaves and sections of grass leaves. This new approach enables a calculation of leaf longevity unbiased by the manner in which grass leaves grow and provides a more accurate comparison between grasses and forbs. Lupinus perennis had the shortest leaf longevity (4 wk) and Koeleria cristata, Poa pratensis, and Solidago rigida the longest (13–14 wk). Average leaf longevity for the 14 species was c. 9 wk, with no significant differences between grasses and forbs nor between current alternative functional classifications.

Fertilization experiments in an 8-yr-old field demonstrated that N was the major limiting nutrient of N, P, K, Ca, and Mg, and suggested that Mg became limiting when N was added. After the fertilization experiments, this field was disturbed via thorough disking and divided into 36 plots for a Latin square design experiment on the effect of N:Mg fertilization ratios on vegetation patterns. By the second year, the major species had separated along the imposed N:Mg gradient, with Agrostis scabra dominant at the low Mg but high N end, followed by Agropyron repens, Berteroa incana, Oenothera biennis, and Aristida basiramea, which was dominant at the high Mg but low N end of the gradient. An unmanipulated resource, light availability at the soil surface, was significantly affected by the treatments. The results demonstrate that spatial heterogeneity in the relative availability of soil nutrient may be one cause of spatial heterogeneity in early successional vegetation.

Nitrogen is a key element controlling the species composition, diversity, dynamics, and functioning of many terrestrial, freshwater, and marine ecosystems. Many of the original plant species living in these ecosystems are adapted to, and function optimally in, soils and solutions with low levels of available nitrogen. The growth and dynamics of herbivore populations, and ultimately those of their predators, also are affected by N. Agriculture, combustion of fossil fuels, and other human activities have altered the global cycle of N substantially, generally increasing both the availability and the mobility of N over large regions of Earth. The mobility of N means that while most deliberate applications of N occur locally, their influence spreads regionally and even globally. Moreover, many of the mobile forms of N themselves have environmental consequences. Although most nitrogen inputs serve human needs such as agricultural production, their environmental consequences are serious and long term. Based on our review of available scientific evidence, we are certain that human alterations of the nitrogen cycle have: approximately doubled the rate of nitrogen input into the terrestrial nitrogen cycle, with these rates still increasing; increased concentrations of the potent greenhouse gas N2O globally, and increased concentrations of other oxides of nitrogen that drive the formation of photochemical smog over large regions of Earth; caused losses of soil nutrients, such as calcium and potassium, that are essential for the long‐term maintenance of soil fertility; contributed substantially to the acidification of soils, streams, and lakes in several regions; and greatly increased the transfer of nitrogen through rivers to estuaries and coastal oceans. In addition, based on our review of available scientific evidence we are confident that human alterations of the nitrogen cycle have: increased the quantity of organic carbon stored within terrestrial ecosystems; accelerated losses of biological diversity, especially losses of plants adapted to efficient use of nitrogen, and losses of the animals and microorganisms that depend on them; and caused changes in the composition and functioning of estuarine and nearshore ecosystems, and contributed to long‐term declines in coastal marine fisheries.

Rules for applying the Kyoto Protocol and national cap-and-trade laws contain a major, but fixable, carbon accounting flaw in assessing bioenergy. The accounting now used for assessing compliance with carbon limits in the Kyoto Protocol and in climate legislation contains a far-reaching but fixable flaw that will severely undermine greenhouse gas reduction goals ( 1 ). It does not count CO 2 emitted from tailpipes and smokestacks when bioenergy is being used, but it also does not count changes in emissions from land use when biomass for energy is harvested or grown. This accounting erroneously treats all bioenergy as carbon neutral regardless of the source of the biomass, which may cause large differences in net emissions. For example, the clearing of long-established forests to burn wood or to grow energy crops is counted as a 100% reduction in energy emissions despite causing large releases of carbon.

Recent developments in complex systems analysis have led to new techniques for detecting causal relationships using relatively short time series, on the order of 30 sequential observations. Although many ecological observation series are even shorter, perhaps fewer than ten sequential observations, these shorter time series are often highly replicated in space (i.e., plot replication). Here, we combine the existing techniques of convergent cross mapping (CCM) and dewdrop regression to build a novel test of causal relations that leverages spatial replication, which we call multispatial CCM. Using examples from simulated and real-world ecological data, we test the ability of multispatial CCM to detect causal relationships between processes. We find that multispatial CCM successfully detects causal relationships with as few as five sequential observations, even in the presence of process noise and observation error. Our results suggest that this technique may constitute a useful test for causality in systems where experiments are difficult to perform and long time series are not available. This new technique is available in the multispatialCCM package for the R programming language.

Pediatric malignancies including Ewing sarcoma (EwS) feature a paucity of somatic alterations except for pathognomonic driver-mutations that cannot explain overt variations in clinical outcome. Here, we demonstrate in EwS how cooperation of dominant oncogenes and regulatory germline variants determine tumor growth, patient survival and drug response. Binding of the oncogenic EWSR1-FLI1 fusion transcription factor to a polymorphic enhancer-like DNA element controls expression of the transcription factor MYBL2 mediating these phenotypes. Whole-genome and RNA sequencing reveals that variability at this locus is inherited via the germline and is associated with variable inter-tumoral MYBL2 expression. High MYBL2 levels sensitize EwS cells for inhibition of its upstream activating kinase CDK2 in vitro and in vivo, suggesting MYBL2 as a putative biomarker for anti-CDK2-therapy. Collectively, we establish cooperation of somatic mutations and regulatory germline variants as a major determinant of tumor progression and highlight the importance of integrating the regulatory genome in precision medicine. Interactions between germline variants and somatic mutations is a relatively unexplored topic in cancer. Here, in Ewing sarcoma, the authors show that binding of the oncogenic EWSR1-FLI1 fusion transcription factor to a polymorphic enhancer-like DNA element controls MYBL2, whose high expression correlates with prognosis.

In this trial, patients with secondary hyperparathyroidism who were undergoing dialysis were assigned to receive either the calcimimetic agent cinacalcet or placebo. Cinacalcet did not significantly reduce the risk of death or major cardiovascular events. Cardiovascular disease is very common among patients with chronic kidney disease, including those treated with hemodialysis, among whom the risk of death from cardiovascular disease is increased by a factor of 10 or more as compared with the risk in the general population. 1 , 2 Cardiovascular risk factors that have been linked to chronic kidney disease include heightened states of inflammation, 3 oxidative stress, 4 activation of the renin–angiotensin–aldosterone system 5 and the sympathetic nervous system, 6 endothelial dysfunction, 7 retention of uremic toxins promoting atherosclerosis and arteriosclerosis, 8 abnormalities in platelet aggregation, 9 anemia, 10 and disorders of bone and mineral metabolism, including hyperphosphatemia, hypercalcemia, and secondary hyperparathyroidism. . . .