Incorporating stakeholder decision support needs into an integrated regional Earth system model

A new modeling effort exploring the opportunities, constraints, and interactions between mitigation and adaptation at regional scale is utilizing stakeholder engagement in an innovative approach to guide model development and demonstration, including uncertainty characterization, to effectively inform regional decision making. This project, the integrated Regional Earth System Model (iRESM), employs structured stakeholder interactions and literature reviews to identify the most relevant adaptation and mitigation alternatives and decision criteria for each regional application of the framework. The information is used to identify important model capabilities and to provide a focus for numerical experiments. This paper presents the stakeholder research results from the first iRESM pilot region. The pilot region includes the Great Lakes Basin in the Midwest portion of the United States as well as other contiguous states. This geographic area (14 states in total) permits cohesive modeling of hydrologic systems while also providing strong gradients in climate, demography, land cover/land use, and energy supply and demand. The results from the stakeholder research indicate that, for this region, iRESM should prioritize addressing adaptation alternatives in the water resources, urban infrastructure, and agriculture sectors, including water conservation, expanded water quality monitoring, altered reservoir releases, lowered water intakes, urban infrastructure upgrades, increased electric power reserves in urban areas, and land use management/crop selection changes. For mitigation in this region, the stakeholder research implies that iRESM should focus on policies affecting the penetration of renewable energy technologies, and the costs and effectiveness of energy efficiency, bioenergy production, wind energy, and carbon capture and sequestration.     

The Efficacy of a Programme of Landslide Risk Reduction in Areas of Unplanned Housing in the Eastern Caribbean

Poor countries are disproportionately affected by the cost of disasters. Yet there is evidence of the benefits of seeking to mitigate the impact of a disaster, compared with the costs incurred in ‘making good’ after a major event has occurred. This article reviews a programme of landslide risk reduction in unplanned communities in the Eastern Caribbean. The construction of appropriate surface water management measures, based on the application of scientific and engineering principles, has been demonstrated to reduce the hazard from rainfall-triggered landslides. Adopting a community-based approach additionally delivers social and environmental benefits relating to employment generation, improvements in the environmental conditions within the community, and improvements slope management practices. The sustained implementation of the community-based projects has provided the necessary evidence-base for these practices to influence Government policy and practice, and gain recognition from regional development agencies. The strategic and incremental uptake of the community-based methodology is demonstrated to be an effective means for delivering physical landslide risk reduction measures in the most ‘at risk’ areas of unplanned housing.     

The Real-World Safety Potential of Connected Vehicle Technology

Objective: This article estimates the safety potential of a current commercially available connected vehicle technology in real-world crashes.

Method: Data from the Centre for Automotive Safety Research's at-scene in-depth crash investigations in South Australia were used to simulate the circumstances of real-world crashes. A total of 89 crashes were selected for inclusion in the study. The crashes were selected as representative of the most prevalent crash types for injury or fatal crashes and had potential to be mitigated by connected vehicle technology. The trajectory, speeds, braking, and impact configuration of the selected in-depth cases were replicated in a software package and converted to a file format allowing “replay” of the scenario in real time as input to 2 Cohda Wireless MK2 onboard units. The Cohda Wireless onboard units are a mature connected vehicle technology that has been used in both the German simTD field trial and the U.S. Department of Transport's Safety Pilot project and have been tuned for low false alarm rates when used in the real world. The crash replay was achieved by replacing each of the onboard unit Global Positioning System (GPS) inputs with the simulated data of each of the involved vehicles. The time at which the Cohda Wireless threat detection software issued an elevated warning was used to calculate a new impact speed using 3 different reaction scenarios and 2 levels of braking.

Results: It was found that between 37 and 86% of the simulated crashes could be avoided, with highest percentage due a fully autonomous system braking at 0.7 g. The same system also reduced the impact speed relative to the actual crash in all cases. Even when a human reaction time of 1.2 s and moderate braking of 0.4 g was assumed, the impact speed was reduced in 78% of the crashes. Crash types that proved difficult for the threat detection engine were head-on crashes where the approach angle was low and right turn–opposite crashes.

Conclusions: These results indicate that connected vehicle technology can be greatly beneficial in real-world crash scenarios and that this benefit would be maximized by having the vehicle intervene autonomously with heavy braking. The crash types that proved difficult for the connected vehicle technology could be better addressed if controller area network (CAN) information is available, such as steering wheel angle, so that driver intent can be inferred sooner. More accurate positioning in the real world (e.g., combining satellite positioning and accelerometer data) would allow the technology to be more effective for near-collinear head-on and rear-end crashes, because the low approach angles that are common in such crashes are currently ignored in order to minimize false alarms due to positioning uncertainty.     

Responses of a soil bacterium, Pseudomonas chlororaphis O6 to commercial metal oxide nanoparticles compared with responses to metal ions

The toxicity of commercially-available CuO and ZnO nanoparticles (NPs) to pathogenic bacteria was compared for a beneficial rhizosphere isolate, Pseudomonas chlororaphis O6. The NPs aggregated, released ions to different extents under the conditions used for bacterial exposure, and associated with bacterial cell surface. Bacterial surface charge was neutralized by NPs, dependent on pH. The CuO NPs were more toxic than the ZnO NPs. The negative surface charge on colloids of extracellular polymeric substances (EPS) was reduced by Cu ions but not by CuO NPs; the EPS protected cells from CuO NPs-toxicity. CuO NPs-toxicity was eliminated by a Cu ion chelator, suggesting that ion release was involved. Neither NPs released alkaline phosphatase from the cells’ periplasm, indicating minimal outer membrane damage. Accumulation of intracellular reactive oxygen species was correlated with CuO NPs lethality. Environmental deposition of NPs could create niches for ion release, with impacts on susceptible soil microbes.     

Genetic structure of leopard shark (<Emphasis Type="Italic">Triakis semifasciata</Emphasis>) populations in California waters

The leopard shark (Triakis semifasciata) is an important predator in coastal marine ecosystems of California, targeted by recreational and commercial fishermen and of specific interest in fisheries management. From October 2003 to August 2006, 169 leopard sharks were collected from the coast of California (between 40.750°N and 32.678°N) and analyzed for mitochondrial and nuclear genetic structure. Analyses of mtDNA control region sequences revealed relatively low levels of genetic variation (five haplotypes, average pairwise divergence π = 0.0067). In contrast, leopard sharks were highly polymorphic for inter simple sequence repeats (ISSRs), which characterize a broad range of the nuclear genome. The null hypothesis of panmixia in California waters was rejected for both genetic markers, and ISSRs displayed a statistically significant pattern of isolation by distance (IBD) across the species range (P = 0.002). A variety of analyses showed that divergence is most pronounced in the northernmost population of Humboldt Bay. Natal philopatry in T. semifasciata was tested using Siegel-Tukey tests on data partitioned by breeding site status, and sex-specific philopatry was tested by comparing IBD plots between sexes. Although there was some evidence for natal philopatry in leopard sharks (P = 0.038), and population divergence may be related to the proximity of breeding sites (P = 0.064), we found no support for sex-specific philopatry. In addition to identifying a novel set of highly variable genetic markers for use in shark population studies, these results may be used to better inform management decisions for leopard sharks in California.     

Temporal variance of disturbance did not affect diversity and structure of a marine fouling community in north-eastern New Zealand

Natural heterogeneity in ecological parameters, like population abundance, is more widely recognized and investigated than variability in the processes that control these parameters. Experimental ecologists have focused mainly on the mean intensity of predictor variables and have largely ignored the potential to manipulate variances in processes, which can be considered explicitly in experimental designs to explore variation in causal mechanisms. In the present study, the effect of the temporal variance of disturbance on the diversity of marine assemblages was tested in a field experiment replicated at two sites on the northeast coast of New Zealand. Fouling communities grown on artificial settlement substrata experienced disturbance regimes that differed in their inherent levels of temporal variability and timing of disturbance events, while disturbance intensity was identical across all levels. Additionally, undisturbed assemblages were used as controls. After 150 days of experimental duration, the assemblages were then compared with regard to their species richness, abundance and structure. The disturbance effectively reduced the average total cover of the assemblages, but no consistent effect of variability in the disturbance regime on the assemblages was detected. The results of this study were corroborated by the outcomes from simultaneous replicate experiments carried out in each of eight different biogeographical regions around the world.     

Quantification and reduction of erroneous differences between images in remote sensing

The reliability of image data, along with the difficulty of accurately comparing images acquired at different times or from different sensors, is a generic problem in remote sensing. Measurement repeatability errors occur frequently and can substantially reduce the system’s ability to reliably quantify real spectral and spatial change in a target. This paper outlines methodologies for quantifying and reducing erroneous differences between monochrome and multispectral or hyperspectral images. [Each of these image types is acquired by an instrument that collects light photons across a variable range of the electromagnetic spectrum (often referred to as an image band). The hyperspectral image is often referred to as a hyperspectral cube with XY spatial dimensions and many Z bands (spectral demotions)]. In this paper, we specifically discuss the Pixel Block Transform (PBT), the Spectral Averaging Transform (SAT), and the Wavelet Transform (WAVEL). We briefly address sensor fusion. Results indicate that the PBT is a powerful cross-noise and repeatability error reducing tool, applicable to monochrome, multispectral, and hyperspectral images. The SAT is as powerful as the PBT in reducing error but is suitable only for hyperspectral imagery. WAVEL can reduce some of the finer scale noise, but it is not as powerful in reducing cross-noise as PBT or SAT and it requires some trial and error for selecting the appropriate wavelet function. It is important that those involved in developing statistically sound relationships between remotely sensed imagery and other data sources understand the problems and their solutions to prevent wasting time or developing relationships that are statistically insignificant or unstable, or that lead to faulty conclusions.     

Emission of oilseed rape volatiles after pollen beetle infestation; behavioural and electrophysiological responses in the parasitoid <Emphasis Type="Italic">Phradis morionellus</Emphasis>

Summary. The pollen beetle, Meligethes aeneus, is an important pest of oilseed rape, Brassica napus. Larvae of this species feed only in the buds and flowers of Brassicaceae. One important natural enemy of this beetle is the parasitoid Phradis morionellus that attacks larvae in buds and flowers and also feeds on the flowers. The preferences for odours of non-infested and infested rape were tested for both starved and fed parasitoids in Y-tube olfactometer experiments. The volatile blend released from pollen beetle-infested and non-infested flowering rape and from pollen beetle larvae was identified and quantified. Gas chromatography-electroantennodetection analyses were performed with female P. morionellus. Parasitoids in both treatment groups preferred infested rape, but the proportion of responding female P. morionellus was significantly lower for the group that was starved. Six of the 20 volatiles identified were released at higher rates from infested rape than from non-infested. None of these compounds was found in pollen beetle larvae headspace. P. morionellus antennae detected both major and minor components in the volatile blend. The volatiles released at a significantly higher rate from infested rape and detected by P. morionellus antennae were (Z)-3-hexenylacetate, (Z)-3-hexenol, 3-butenyl isothiocyanate and (E,E)-α-farnesene.     

Rainfall and soils modify plant community response to grazing in Serengeti National Park

Terrestrial plant community responses to herbivory depend on resource availability, but the separate influences of different resources are difficult to study because they often correlate across natural environmental gradients. We studied the effects of excluding ungulate herbivores on plant species richness and composition, as well as available soil nitrogen (N) and phosphorus (P), across eight grassland sites in Serengeti National Park (SNP), Tanzania. These sites varied independently in rainfall and available soil N and P. Excluding herbivores decreased plant species richness at all sites and by an average of 5.4 species across all plots. Although plant species richness was a unimodal function of rainfall in both grazed and ungrazed plots, fences caused a greater decrease in plant species richness at sites of intermediate rainfall compared to sites of high or low rainfall. In terms of the relative or proportional decreases in plant species richness, excluding herbivores caused the strongest relative decreases at lower rainfall and where exclusion of herbivores increased available soil P. Herbivore exclusion increased among-plot heterogeneity in species composition but decreased coexistence of congeneric grasses. Compositional similarity between grazed and ungrazed treatments decreased with increasing rainfall due to greater forb richness in exclosures and greater sedge richness outside exclosures and was not related to effects of excluding herbivores on soil nutrients. Our results show that plant resources, especially water and P, appear to modulate the effects of herbivores on tropical grassland plant diversity and composition. We show that herbivore effects on soil P may be an important and previously unappreciated mechanism by which herbivores influence plant diversity, at least in tropical grasslands.     

AIC model selection and multimodel inference in behavioral ecology: some background,observations, and comparisons

We briefly outline the information-theoretic (I-T) approaches to valid inference including a review of some simple methods for making formal inference from all the hypotheses in the model set (multimodel inference). The I-T approaches can replace the usual t tests and ANOVA tables that are so inferentially limited, but still commonly used. The I-T methods are easy to compute and understand and provide formal measures of the strength of evidence for both the null and alternative hypotheses, given the data. We give an example to highlight the importance of deriving alternative hypotheses and representing these as probability models. Fifteen technical issues are addressed to clarify various points that have appeared incorrectly in the recent literature. We offer several remarks regarding the future of empirical science and data analysis under an I-T framework.