Controls on coastal overwash morphology in natural and built environments

<p>Overwash is a key mechanism controlling the flux of sediment from the front of a barrier island to the top and back of an island during a storm event. The process is essential for barrier environments to maintain their height and width relative to sea level. Barrier topography and vegetation – and also road networks and buildings – can direct overwash flow, and thus the shape and size of sedimentary deposits that overwash leaves behind. Controls on overwash deposition have been examined more closely in natural settings than in developed zones. But overwash poses a major hazard to coastal infrastructure, and accurate prediction of storm impacts requires quantitative insight into the dynamics of overwash morphology in built settings. Here, we compare barrier floodplain controls across a range of spatial "fabrics", both natural and built (e.g., sparse to dense vegetation coverage; sparse to dense configurations of roads and buildings), to explore how these fabrics affect scaling relationships for overwash morphology. Integrating empirical measurements from post-storm imagery, trials of an analogue model in a small experimental basin, and results from a numerical toy model, we identify thresholds at which floodplain fabrics cause scaling relationships to change, or "break". Our findings illustrate a continuum in overwash pattern formation between endogenous self-organisation and exogenous forcing templates, and set up further inquiry into the dynamics of flood deposition in built environments.</p>

Chaos in Estimates of Climate Change Impacts

<p>Estimates of physical, social and economic impacts of climate change are less accurate than usually thought because the impacts literature has largely neglected the internal variability of the climate system. Climate change scenarios are highly sensitive to the initial conditions of the climate system due the chaotic dynamics of weather. As the initial conditions of the climate system are unknown with a sufficiently high level of precision, each future climate scenario – for any given model parameterization and level of exogenous forcing – is only one of the many possible future realizations of climate. The impacts literature usually relies on only one realization randomly taken out of the full distribution of future climates. Here we use one of the few available large scale ensembles produced to study internal variability and an econometric model of climate change impacts on United States (US) agricultural productivity to show that the range of impacts is much larger than previously thought. Different ensemble members lead to significantly different impacts. Significant sign reversals are frequent. Relying only on one ensemble member leads to incorrect conclusions on the effect of climate change on agriculture in most of the US counties. Impacts studies should start using large scale ensembles of future climate change to predict damages. Climatologists should ramp-up efforts to run large ensembles for all GCMs, for at least the most frequently used scenarios of exogenous forcing.</p>

North American Pancontinental Droughts in Model Simulations of the Last Millennium*

Pancontinental droughts in North America, or droughts that simultaneously affect a large percentage of the geographically and climatically distinct regions of the continent, present significant on-the-ground management challenges and, as such, are an important target for scientific research. The methodology of paleoclimate-model data comparisons is used herein to provide a more comprehensive understanding of pancontinental drought dynamics. Models are found to simulate pancontinental drought with the frequency and spatial patterns exhibited by the paleoclimate record. They do not, however, agree on the modes of atmosphere–ocean variability that produce pancontinental droughts because simulated El Niño–Southern Oscillation (ENSO), Pacific decadal oscillation (PDO), and Atlantic multidecadal oscillation (AMO) dynamics, and their teleconnections to North America, are different between models and observations. Despite these dynamical differences, models are able to reproduce large-magnitude centennial-scale variability in the frequency of pancontinental drought occurrence—an important feature of the paleoclimate record. These changes do not appear to be tied to exogenous forcing, suggesting that simulated internal hydroclimate variability on these time scales is large in magnitude. Results clarify our understanding of the dynamics that produce real-world pancontinental droughts while assessing the ability of models to accurately characterize future drought risks.

Using an individual-based model with four trophic levels to model the effect of predation and competition on squid recruitment

Sinerchia, M., Field, A. J., Woods, J. D., Vallerga, S., and Hinsley, W. R. 2012. Using an individual-based model with four trophic levels to model the effect of predation and competition on squid recruitment. – ICES Journal of Marine Science, 69: 439–447. The Lagrangian Ensemble recruitment model (LERM) is the first prognostic model of fisheries recruitment based upon individuals. It incorporates five functional groups: phytoplankton (diatoms), herbivorous zooplankton (copepods), carnivorous zooplankton (squid paralarvae), and two top predators. Physiology and behaviour are described by equations derived from literature based on reproducible laboratory experiments. LERM is built using the Lagrangian Ensemble metamodel, in which the demography and biofeedback of each dynamic population are diagnostic properties, emerging from the life histories of individuals. The response of the plankton ecosystem and squid recruitment to different scenarios of exogenous forcing is investigated. Simulations were run at 41°N 27°W (Azores) under a stationary annual cycle of atmospheric forcing. The ecosystem adjusts to a stable attractor for each scenario. The emergent properties of each attractor are investigated, with focus on predation, competition for food, and spawning magnitude. Annual recruitment is a complex emergent property dependent on several factors, including food availability, predation, competition, and post-hatching growth rate, as proposed by Hjort's critical period theory, relating recruitment to predation mortality, depending on growth rate and hence food availability. The model provides a useful step towards linking small-scale processes governing the life histories of larvae and fisheries on the large scale.

A Surfeit of Cycles

Chaotic sets are organized about “skeletons” of periodic orbits in the sense that every point on a chaotic set is arbitrarily close to such an orbit. The orbits have the stability property of saddles: attracting in some directions; repelling in others. This topology has implications for changing climates that evidence pronounced variability on time scales ranging from decades to tens of thousands of years. Among these implications are the following: 1. A wide range of periodicities should be (and are) observed. 2. Periodicities should (and do) shift – often abruptly – as the evolving climatic trajectory sequentially shadows first one periodic orbit and then another. 3. Models that have been “tuned” (parametric adjustment) to fit trajectorial evolution in the vicinity of one periodic orbit are likely to fail when the real system moves to another region of the phase space. 4. In response to secular forcing, chaotic sets simplify via the elimination of periodic orbits. If one accepts the reality of anthropogenic warming, the long-term prediction is loss of intrinsic variability. 5. In response to periodic forcing, nonlinear systems can manifest subharmonic resonance i.e., “cyclic” behavior with periods and rotation numbers rationally related to the period of the forcing. Such cycling has been implicated in millennial and stadial variations in paleoclimatic time series. 6. Generically, the dynamics of system observables, such as climate sensitivity, are qualitatively equivalent to those of the whole. If the climate is chaotic, so too is sensitivity. These considerations receive minimal attention in consensus views of climate change that emphasize essentially one-to-one correspondence between global temperatures and exogenous forcing. Caveat emptor.

Linear forest patterns in subalpine environments

Studies of feedback between ecological pattern and process can benefit from the analysis of visually striking patterns, as they may reveal underlying processes and clarify the relative role of exogenous versus endogenous factors in driving vegetation change. Roughly linear forest patches are common in subalpine environments, including `hedges', `ribbon forest', and `Shimagare' or `wave regenerated forests' (waves). The influence of wind is common among these patterns, but the role of positive feedback, the most important component of self-organization in biological systems, varies. Hedges are orientated parallel to prevailing winds in several mid-latitude mountain ranges worldwide. Desiccation and ice-particle abrasion kills windward foliage while the vegetation shelters leeward seedlings and growth, so that the patches migrate slowly across the slope. Ribbon forest consists of strips orientated perpendicular to prevailing winds. They have been examined only in the US Rocky Mountains and are the least studied and understood of these phenomena. There are at least three distinct types of ribbon forest, which appear to develop in different ways. Waves are migrating strips of mortality and regeneration orientated perpendicular to prevailing winds in the USA, Japan and Argentina, and dominant controls vary by site. Hedges and waves can develop endogenously with a constant wind, and so can be considered self-organizing in the sense that feedback at the scale of individual trees creates a pattern across the scale of many trees without exogenous forcing. Most ribbon forests seem to be dominated by exogenous forces, but more work is needed to fully characterize the different types.