A WATER POLICY-LAND USE COMPUTER SIMULATION MODEL1

ABSTRACT: This paper describes the philosophy, algorithms, and implementation of a computer-oriented land use forecasting-water policy simulation model. The model is applicable to SMSA's organized on a census tract basis by counties. The forecasts are macro to the census tract level for industrial, residential, commercial and public land uses, and are dynamically altered by hypothesized water management policies. Modeling is based on an economic data base of the region, and is extremely flexible for the user. An example set of simulations is included for illustrative purposes.     

Methods for synthesis of nonabromodiphenyl ethers and a chloro-nonabromodiphenyl ether

Polybrominated diphenyl ethers (PBDEs) have been used extensively as brominated flame retardants (BFRs) in textiles, upholstery and electronics. They are ubiquitous contaminants in wildlife and humans. A low concentration of nonabrominated diphenyl ethers (nonaBDEs) is present in commercial DecaBDE and they are also abiotic and biotic debromination products of decabromodiphenyl ether (BDE-209). The objective of the present work was to develop methods for synthesis of the three nonaBDEs, 2,2',3,3',4,4',5,5',6-nonabromodiphenyl ether (BDE-206), 2,2',3,3',4,4',5,6,6'-nonabromodiphenyl ether (BDE-207) and 2,2',3,3',4,5,5',6,6'-nonabromodiphenyl ether (BDE-208), with the intention of making them available as authentic standards for analytical, toxicological and stability studies, as well as studies regarding physical-chemical properties. Two methods were developed, one based on perbromination of phenoxyanilines and the other via reductive debromination of BDE-209 by sodium borohydride followed by chromatographic separation of the three nonaBDE isomers formed. An additional nonabrominated compound, 4'-chloro-2,2',3,3',4,5,5',6,6'-nonabromodiphenyl ether (Cl-BDE-208), was also synthesized in the present work. Cl-BDE-208, prepared by the perbromination of 4-chlorodiphenyl ether, may be used as an internal standard in analysis of highly brominated diphenyl ethers. BDE-206, BDE-207, BDE-208 and Cl-BDE-208 were characterized by 1H NMR, 13C NMR, electron ionization mass spectra and by their melting points. The structures of all three nonaBDEs have been characterized previously by X-ray crystallography.     

Using vertebrate environmental DNA from seawater in biomonitoring of marine habitats

Conservation and management of marine biodiversity depends on biomonitoring of marine habitats, but current approaches are resource-intensive and require different approaches for different organisms. Environmental DNA (eDNA) extracted from water samples is an efficient and versatile approach to detecting aquatic animals. In the ocean, eDNA composition reflects local fauna at fine spatial scales, but little is known about the effectiveness of eDNA-based monitoring of marine communities at larger scales. We investigated the potential of eDNA to characterize and distinguish marine communities at large spatial scales by comparing vertebrate species composition among marine habitats in Qatar, the Arabian Gulf (also known as the Persian Gulf), based on eDNA metabarcoding of seawater samples. We conducted species accumulation analyses to estimate how much of the vertebrate diversity we detected. We obtained eDNA sequences from a diverse assemblage of marine vertebrates, spanning 191 taxa in 73 families. These included rare and endangered species and covered 36% of the bony fish genera previously recorded in the Gulf. Sites of similar habitat type were also similar in eDNA composition. The species accumulation analyses showed that the number of sample replicates was insufficient for some sampling sites but suggested that a few hundred eDNA samples could potentially capture >90% of the marine vertebrate diversity in the study area. Our results confirm that seawater samples contain habitat-characteristic molecular signatures and that eDNA monitoring can efficiently cover vertebrate diversity at scales relevant to national and regional conservation and management.     

Enhanced science–stakeholder communication to improve ecosystem model performances for climate change impact assessments

In recent years, climate impact assessments of relevance to the agricultural and forestry sectors have received considerable attention. Current ecosystem models commonly capture the effect of a warmer climate on biomass production, but they rarely sufficiently capture potential losses caused by pests, pathogens and extreme weather events. In addition, alternative management regimes may not be integrated in the models. A way to improve the quality of climate impact assessments is to increase the science–stakeholder collaboration, and in a two-way dialog link empirical experience and impact modelling with policy and strategies for sustainable management. In this paper we give a brief overview of different ecosystem modelling methods, discuss how to include ecological and management aspects, and highlight the importance of science–stakeholder communication. By this, we hope to stimulate a discussion among the science–stakeholder communities on how to quantify the potential for climate change adaptation by improving the realism in the models.     

Deriving heart rate variability indices from cardiac monitoring—An indicator of driver sleepiness

Objective: Driver fatigue is considered to be a major contributor to road traffic crashes. Cardiac monitoring and heart rate variability (HRV) analysis is a candidate method for early and accurate detection of driver sleepiness. This study has 2 objectives: to evaluate the (1) suitability of different preprocessing strategies for detecting and removing outlier heartbeats and spectral transformation of HRV signals and their impact of driver sleepiness assessment and (2) relation between common HRV indices and subjective sleepiness reported by a large number of drivers in real driving situations, for the first time.

Methods: The study analyzed >3,500 5-min driving epochs from 76 drivers on a public motorway in Sweden. The electrocardiograph (ECG) data were recorded in 3 studies designed to evaluate the physiological differences between awake and sleepy drivers. The drivers reported their perceived level of sleepiness according to the Karolinska Sleepiness Scale (KSS) every 5?min. Two standard methods were used for identifying outlier heartbeats: (1) percentage change (PC), where outliers were defined as interbeat intervals deviating >30% from the mean of the four previous intervals and (2) standard deviation (SD), where outliers were defined as interbeat interval deviating >4 SD from the mean interval duration in the current epoch. Three standard methods were used for spectral transformation, which is needed for deriving HRV indices in the frequency domain: (1) Fourier transform; (2) autoregressive model; and (3) Lomb-Scargle periodogram. Different preprocessing strategies were compared regarding their impact on derivation of common HRV indices and their relation to KSS data distribution, using box plots and statistical tests such as analysis of variance (ANOVA) and Student’s t test.

Results: The ability of HRV indices to discriminate between alert and sleepy drivers does not differ significantly depending on which outlier detection and spectral transformation methods are used. As expected, with increasing sleepiness, the heart rate decreased, whereas heart rate variability overall increased. Furthermore, HRV parameters representing the parasympathetic branch of the autonomous nervous system increased. An unexpected finding was that parameters representing the sympathetic branch of the autonomous nervous system also increased with increasing KSS level. We hypothesize that this increment was due to stress induced by trying to avoid an incident, because the drivers were in real driving situations.

Conclusions: The association of HRV indices to KSS did not depend on the preprocessing strategy. No preprocessing method showed superiority for HRV association to driver sleepiness. This was also true for combinations of methods for frequency domain HRV indices. The results prove clear relationships between HRV indices and perceived sleepiness. Thus, HRV analysis shows promise for driver sleepiness detection.     

What limits predator detection in blue tits (<Emphasis Type="Italic">Parus caeruleus</Emphasis>): posture,task or orientation?

To detect threats and reduce predation risk prey animals need to be alert. Early predator detection and rapid anti-predatory action increase the likelihood of survival. We investigated how foraging affects predator detection and time to take-off in blue tits (Parus caeruleus) by subjecting them to a simulated raptor attack. To investigate the impact of body posture we compared birds feeding head-down with birds feeding head-up, but could not find any effect of posture on either time to detection or time to take-off. To investigate the impact of orientation we compared birds having their side towards the attacking predator with birds having their back towards it. Predator detection, but not time to take-off, was delayed when the back was oriented towards the predator. We also investigated the impact of foraging task by comparing birds that were either not foraging, foraging on chopped mealworms, or foraging on whole ones. Foraging on chopped mealworms did not delay detection compared to nonforaging showing that foraging does not always restrict vigilance. However, detection was delayed more than 150% when the birds were foraging on whole, live mealworms, which apparently demanded much attention and handling skill. Time to take-off was affected by foraging task in the same way as detection was. We show that when studying foraging and vigilance one must include the difficulty of the foraging task and prey orientation.Communicated by P.A. Bednekoff     

Lack of sequestration of host plant glucosinolates in <Emphasis Type="Italic">Pieris rapae</Emphasis> and <Emphasis Type="Italic">P. grarricae</Emphasis>

Summary. Sequestration of plant toxins in herbivores is often correlated with aposematic coloration and gregarious behaviour. Larvae of Pieris brassicae show these conspicuous morphological and behavioural characteristics and were thus suggested to sequester glucosinolates that are characteristic secondary metabolites of their host plants. P. rapaeare camouflaged and solitary, and are thus not expected to sequester. To test this hypothesis and to check the repeatabi-lity of a study that did report the presence of the glucosinolate sinigrin in P. brassicae, larvae were reared on three species of Brassicaceae (Sinapis alba, Brassica nigra and Barbarea stricta), and different leaf and insect samples were taken for glucosinolate analysis. The major host plant glucosinolates could only be found in traces or not at all in larval haemolymph, bled or starved larvae, faeces or pupae of both species or P. brassicae regurgitant. Haemolymph of both Pieris spp. was not rejected by the ant Myrmica rubra in dual-choice assays; the regurgitant of P. brassicae was rejected. This suggests the presence of compounds other than glucosinolates that might be sequestered in or produced by P. brassicae only. In faeces of both Pieris spp. a compound which yielded 4-hydroxybenzylcyanide (HBC) upon incubation with sulfatase was detected in high concentrations when larvae had been reared on S. alba. This compound may be derived from hydrolysis of sinalbin, the main glucosinolate of that plant. The unidentified HBC progenitor was apparently not sequestered in the two Pieris spp., and was not detected in faeces of larvae reared on B. nigra or B. stricta. Received 18 July 2002; accepted 11 September 2002.     

Assessing Risks to Biodiversity from Future Landscape Change

We examined the impacts of possible future land development patterns on the biodiversity of a landscape. Our landscape data included a remote sensing derived map of the current habitat of the study area and six maps of future habitat distributions resulting from different land development scenarios. Our species data included lists of all bird, mammal, reptile, and amphibian species in the study area, their habitat associations, and area requirements for each. We estimated the area requirements using home ranges, sampled population densities, or genetic area requirements that incorporate dispersal distances. Our measures of biodiversity were species richness and habitat abundance. We calculated habitat abundance in two ways. First, we computed the total habitat area for each species in each landscape. Second, we calculated the number of habitat units for each species in each landscape by dividing the size of each habitat patch in the landscape by the area requirement and summing over all patches. Species richness was based on presence of habitat. Species became extinct in the landscape if they had no habitat area or no habitat units, respectively. We then computed ratios of habitat abundance in each future landscape to habitat abundance in the present for each species. We also computed the ratio of future to present species richness. We then calculated summary statistics across all species. Species richness changed little from present to future. There were distinctly greater risks to habitat abundance in landscapes that extrapolated from present trends or zoning patterns, however, as opposed to landscapes in which land development activities followed more constrained patterns. These results were stable when tested using Monte Carlo simulations and sensitivity tests on the area requirements. We conclude that this methodology can begin to discriminate the effects of potential changes in land development on vertebrate biodiversity.