-
An emerging movement ecology paradigm
-
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),
Located in
Resources
/
Climate Science Documents
-
Comment:Nuclear winter is a real and present danger
-
Models show that even a ‘small’ nuclear war would cause catastrophic climate change. Such findings must inform policy, says Alan Robock.
Located in
Resources
/
Climate Science Documents
-
Comment: Time to Model all Life on Earth
-
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.
Located in
Resources
/
Climate Science Documents
-
Coastal habitats shield people and property from sea-level rise and storms
-
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.
Located in
Resources
/
Climate Science Documents
-
El Nino in a changing climate
-
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.
Located in
Resources
/
Climate Science Documents
-
A general integrative model for scaling plant growth, carbon flux, and functional trait spectra
-
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.
Located in
Resources
/
Climate Science Documents
-
CARBON CYCLE : Fertilizing change
-
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.
Located in
Resources
/
Climate Science Documents
-
A paradigm shift in understanding and quantifying the effects of forest harvesting on floods in snow environments
-
A well-established precept in forest hydrology is that any reduction of forest cover will always have a progressively smaller effect on floods with increasing return period. The underlying logic in snow environments is that during the largest snowmelt events the soils and vegetation canopy have little additional storage capacity and under these conditions much of the snowmelt will be converted to runoff regardless of the amount or type of vegetation cover. Here we show how this preconceived physical understanding, reinforced by the outcomes of numerous paired watershed studies, is indefensible because it is rationalized outside the flood frequency distribution framework. We conduct a meta-analysis of postharvest data at four catchments (3–37 km2) with moderate level of harvesting (33%–40%) to demonstrate how harvesting increases the magnitude and frequency of all floods on record (19–99 years) and how such effects can increase unchecked with increasing return period as a consequence of changes to both the mean (þ11% to þ35%) and standard deviation (12% to þ19%) of the flood frequency distribution. We illustrate how forest harvesting has substantially increased the frequency of the largest floods in all study sites regardless of record length and this also runs counter to the prevailing wisdom in hydrological science. The dominant process responsible for these newly emerging insights is the increase in net radiation associated with the conversion from longwave-dominated snowmelt beneath the canopy to shortwave-dominated snowmelt in harvested areas, further amplified or mitigated by basin characteristics such as aspect distribution, elevation range, slope gradient, amount of alpine area, canopy closure, and drainage density. Investigating first order environmental controls on flood frequency distributions, a standard research method in stochastic hydrology, represents a paradigm shift in the way harvesting effects are physically explained and quantified in forest hydrology literature.
Located in
Resources
/
Climate Science Documents
-
Climate Change Challenges and Opportunities for Global Health
-
Editorial: Journal of the American Medical Association. Health is inextricably linked to climate change. It is important for clinicians to understand this relationship in order to discuss associated health risks with their patients and to inform public policy. To provide new US-based temperature projections from downscaledclimate modeling and to review recent studies on health risks related to climate change and the cobenefits of efforts to mitigate greenhouse gas emissions. We searched PubMed from 2009 to 2014 for articles related to climate change and health, focused on governmental reports, predictive models, and empirical epidemiological studies. Of the more than 250 abstracts reviewed, 56 articles were selected. In addition, we analyzed climate data averaged over 13 climate models and based future projections on downscaled probability distributions of the daily maximum temperature for 2046-2065. We also compared maximum daily 8-hour average with air temperature data taken from the National Oceanic and Atmospheric Administration National Climate Data Center. By 2050, many US cities may experience more frequent extreme heat days. For example, New York and Milwaukee may have 3 times their current average number of days hotter than 32°C (90°F). The adverse health aspects related to climate change may include heat-related disorders, such as heat stress and economic consequences of reduced work capacity; and respiratory disorders, including those exacerbated by fine particulate pollutants, such as asthma and allergic disorders; infectious diseases, including vectorborne diseases and water-borne diseases, such as childhood gastrointestinal diseases; food insecurity, including reduced crop yields and an increase in plant diseases; and mental health disorders, such as posttraumatic stress disorder and depression, that are associated with natural disasters. Substantial health and economic co-benefits could be associated with reductions in fossil fuel combustion. For example, the cost of greenhouse gas emission policies may yield net economic benefit, with health benefits from air quality improvements potentially offsetting the cost of US carbon policies. Evidence over the past 20 years indicates that climate change can be associated with adverse health outcomes. Health care professionals have an important role in understanding and communicating the related potential health concerns and the cobenefits from reducing greenhouse gas emissions.
Located in
Resources
/
Climate Science Documents
-
A dispersal-induced paradox: synchrony and stability in stochastic metapopulations
-
Understanding how dispersal influences the dynamics of spatially distributed populations is a major priority of both basic and applied ecologists. Two well-known effects of dispersal are spatial synchrony (positively correlated population dynamics at different points in space) and dispersal-induced stability (the phenomenon whereby populations have simpler or less extinction-prone dynamics when they are linked by dispersal than when they are isolated). Although both these effects of dispersal should occur simultaneously, they have primarily been studied separately. Herein, I summarise evidence from the literature that these effects are expected to interact, and I use a series of models to characterise that interaction. In particular, I explore the observation that although dispersal can promote both synchrony and stability singly, it is widely held that synchrony paradoxically prevents dispersal-induced stability. I show here that in many realistic scenarios, dispersal is expected to promote both synchrony and stability at once despite this apparent destabilising influence of synchrony. This work demonstrates that studying the spatial and temporal impacts of dispersal together will be vital for the conservation and management of the many communities for which human activities are altering natural dispersal rates.
Keywords
Autoregressive model, correlated environmental stochasticity, dispersal, dispersal-induced stability, metapopulation, negative binomial model, Ricker model, spatial heterogeneity, synchrony.
Located in
Resources
/
Climate Science Documents
