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CARBON CYCLE : Fertilizing change
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Carbon cycle–climate feedbacks are expected to diminish the size of the terrestrial carbon sink over the next century. Model simulations suggest that nitrogen availability is likely to play a key role in mediating this response.
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A general integrative model for scaling plant growth, carbon flux, and functional trait spectra
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Linking functional traits to plant growth is critical for scaling attributes of organisms to the dynamics of ecosystems (1,2) and for understanding how selection shapes integrated botanical phenotypes (3). However, a general mechanistic theory showing how traits specifically influence carbon and biomass flux within and across plants is needed. Building on foundational work on relative growth rate (4–6), recent work on functional trait spectra (7–9), and metabolic scaling theory (10,11), here we derive a generalized trait-based model of plant growth. In agreement with a wide variety of empirical data, our model uniquely predicts how key functional traits interact to regulate variation in relative growth rate, the allometric growth normalizations for both angiosperms and gymnosperms, and the quantitative form of several functional trait spectra relationships. The model also provides a general quantitative framework to incorporate additional leaf-level trait scaling relationships (7,8) and hence to unite functional trait spectra with theories of relative growth rate, and metabolic scaling. We apply the model to calculate carbon use efficiency. This often ignored trait, which may influence variation in relative growth rate, appears to vary directionally across geographic gradients. Together, our results show how both quantitative plant traits and the geometry of vascular transport networks can be merged into a common scaling theory. Our model provides a framework for predicting not only how traits covary within an integrated allometric phenotype but also how trait variation mechanistically influences plant growth and carbon flux within and across diverse ecosystems.
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El Nino in a changing climate
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El Nino events, characterized by anomalous warming in the eastern equatorial Pacific Ocean, have global climatic teleconnections and are the most dominant feature of cyclic climate variability on subdecadal timescales. Understanding changes in the frequency or characteristics of El Nino events in a changing climate is therefore of broad scientific and socioeconomic interest. Recent studies (1–5) show that the canonical El Nino has become less frequent and that a different kind of El Nino has become more common during the late twentieth century, in which warm sea surface temperatures (SSTs) in the central Pacific are flanked on the east and west by cooler SSTs. This type of El Nino, termed the central Pacific El Nino (CP-El Nino; also termed the dateline El Nino (2), El Nino Modoki (3) or a warm pool El Nino (5), differs from the canonical eastern Pacific El Nino (EP-El Nino) in both the location of maximum SST anomalies and tropical–midlatitude teleconnections. Here we show changes in the ratio of CP-El Nino to EP-El Nino under projected global EQ warming scenarios from the Coupled Model Intercomparison Project phase 3 multi-model data set (6). Using calculations based 10o S on historical El Nino indices, we find that projections of anthropogenic climate change are associated with an increased frequency of the CP-El Nino compared to the EP-El Nino. When restricted to the six climate models with the best representation of the twentieth-century ratio of CP-El Nino to EP-El Nino, the occurrence ratio of CP-El Nino/EP-El Nino is projected to increase as 10o N much as five times under global warming. The change is related to a flattening of the thermocline in the equatorial Pacific.
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Coastal habitats shield people and property from sea-level rise and storms
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Extreme weather, sea-level rise and degraded coastal ecosystems are placing people and property at greater risk of damage from coastal hazards 1–5. The likelihood and magnitude of losses may be reduced by intact reefs and coastal vegetation 1, especially when those habitats fringe vulnerable communities and infrastructure. Using five sea-level-rise scenarios, we calculate a hazard index for every 1 km2 of the United States coastline. We use this index to identify the most vulnerable people and property as indicated by being in the upper quartile of hazard for the nation’s coastline. The number of people, poor families, elderly and total value of residential property that are most exposed to hazards can be reduced by half if existing coastal habitats remain fully intact. Coastal habitats defend the greatest number of people and total property value in Florida, New York and California. Our analyses deliver the first national map of risk reduction owing to natural habitats and indicates where conservation and restoration of reefs and vegetation have the greatest potential to protect coastal communities.
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Comment: Time to Model all Life on Earth
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To help transform our understanding of the biosphere, ecologists — like climate scientists — should simulate whole ecosystems, argue Drew Purves and colleagues. FROM THE TEXT: General circulation models, which simulatethe physics and chemistry of Earth’s land, ocean and atmosphere, embody scientists’ best understanding of how the climate system works and are crucial to making predictions and shaping policies. We think that analogous general ecosystem models (GEMs) could radically improve understanding of the biosphere and inform policy decisions about biodiversity and conservation.
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Comment:Nuclear winter is a real and present danger
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Models show that even a ‘small’ nuclear war would cause catastrophic climate change. Such findings must inform policy, says Alan Robock.
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An emerging movement ecology paradigm
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1st 2 paragraphs: Movement of individual organisms, one of the most fundamental features of life on Earth, is a crucial component of almost any ecological and evolutionary process, including major problems associated with habitat fragmentation, climate change, biological invasions, and the spread of pests and diseases. The rich variety of movement modes seen among microorganisms, plants, and animals has fascinated mankind since time immemorial. The prophet Jeremiah (7th century B.C.),for instance, described the temporal consistency in migratory patterns of birds, and Aristotle (4th centur y B.C.) searched for common features unifying animal movements (see ref. 1). Modern movement research, however, is characterized by a broad range of specialized scientific approaches, each developed to explore a different type of movement carried out by a specific group of organisms (2). Beyond this separation across movement types and taxonomic (or functional) groups, movement research divides into four different ‘‘paradigms,’’ the random, biomechanical, cognitive, and optimality approaches (1), which are loosely linked to each other. Although movement research is extensive and is growing rapidly (2),
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Climate negotiations under scientific uncertainty
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How does uncertainty about “dangerous” climate change affect the prospects for international cooperation? Climate negotiations usually are depicted as a prisoners’ dilemma game; collectively, countries are better off reducing their emissions, but self-interest impels them to keep on emitting. We provide experimental evidence, grounded in an analytical framework, showing that the fear of crossing a dangerous threshold can turn climate negotiations into a coordination game, making collective action to avoid a dangerous threshold virtually assured. These results are robust to uncertainty about the impact of crossing a threshold, but uncertainty about the location of the threshold turns the game back into a prisoners’ dilemma, causing cooperation to collapse. Our research explains the paradox of why countries would agree to a collective goal, aimed at reducing the risk of catastrophe, but act as if they were blind to this risk.
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Disturbance−diversity models: what do they really predict and how are they tested?
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The intermediate disturbance hypothesis (IDH) and the dynamic equilibrium model (DEM) are influential theories in ecology. The IDH predicts large species numbers at intermediate levels of disturbance and the DEM predicts that the effect of disturbance depends on the level of productivity. However, various indices of diversity are considered more commonly than the predicted number of species in tests of the hypotheses. This issue reaches beyond the scientific community as the predictions of the IDH and the DEM are used in the management of national parks and reserves. In order to compare responses with disturbance among measures of biodiversity, we used two different approaches of mathematical modelling and conducted an extensive meta-analysis. Two-thirds of the surveyed studies present different results for different diversity measures. Accordingly, the meta-analysis showed a narrow range of negative quadratic regression components for richness, but not evenness. Also, the two models support the IDH and the DEM, respectively, when biodiversity is measured as species richness, but predict evenness to increase with increasing disturbance, for all levels of productivity. Consequently, studies that use compound indices of diversity should present logical arguments, a priori, to why a specific index of diversity should peak in response to disturbance.
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Effects of Urbanization and Climate Change on Stream Health
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Estimation of stream health involves the analysis of changes in aquatic species, riparian vegetation, microinvertebrates, and channel degradation due to hydrologic changes occurring from anthropogenic activities. In this study, we quantified stream health changes arising from urbanization and climate change using a combination of the widely accepted Indicators of Hydrologic Alteration (IHA) and Dundee Hydrologic Regime Assessment Method (DHRAM) on a rapidly urbanized watershed in the Dallas-Fort Worth metropolitan area in Texas. Historical flow data were split into pre-alteration and post-alteration periods. The influence of climate change on stream health was analyzed by dividing the precipitation data into three groups of dry, average, and wet conditions based on recorded annual precipitation. Hydrologic indicators were evaluated for all three of the climate scenarios to estimate the stream health changes brought about by climate change. The effect of urbanization on stream health was analyzed for a specific subwatershed where urbanization occurred dramatically but no stream flow data were available using the widely used watershed-scale Soil and Water Assessment Tool (SWAT) model. The results of this study identify negative impacts to stream health with increasing urbanization and indicate that dry weather has more impact on stream health than wet weather. The IHA-DHRAM approach and SWAT model prove to be useful tools to estimate stream health at the watershed scale.
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