Using Niche-Based Models to Improve the Sampling of Rare Species

Abstract:  Because data on rare species usually are sparse, it is important to have efficient ways to sample additional data. Traditional sampling approaches are of limited value for rare species because a very large proportion of randomly chosen sampling sites are unlikely to shelter the species. For these species, spatial predictions from niche-based distribution models can be used to stratify the sampling and increase sampling efficiency. New data sampled are then used to improve the initial model. Applying this approach repeatedly is an adaptive process that may allow increasing the number of new occurrences found. We illustrate the approach with a case study of a rare and endangered plant species in Switzerland and a simulation experiment. Our field survey confirmed that the method helps in the discovery of new populations of the target species in remote areas where the predicted habitat suitability is high. In our simulations the model-based approach provided a significant improvement (by a factor of 1.8 to 4 times, depending on the measure) over simple random sampling. In terms of cost this approach may save up to 70% of the time spent in the field.     

Behavioral influences on driver crash risks in Ghana: A qualitative study of commercial passenger drivers

Objectives: Though there is a growing body of literature on crash risks in the developed world, little is known about how well these models apply to motoring in developing countries, the context in which the majority of road traffic fatalities occur. This qualitative study explores factors perceived to influence crash risks for commercial drivers in Ghana.

Method: Twenty commercial drivers of varied ages and experience were sampled from 7 major lorry terminals in 3 regions (Greater Accra, Ashanti, and Volta) of Ghana. Data were collected through semistructured interviews.

Results: The participants identified some issues that are shared with drivers in the developed world, though moderated by the Ghanaian context. These included work pressures (e.g., fatigued driving), speeding, distracted driving, and inadequate vehicle maintenance. Other factors identified by participants are less frequently considered in research addressing driving behavior in developed countries. These included aggressive competition over passengers and corruption (e.g., improper licensing practices), among others.

Conclusion: The findings have implications for building a research base to support the development of road safety policy and interventions in developing countries.     

Regional environmental assessment (REA) and local Agenda 21 implementation

The implementation of sustainable development requires several support instruments. One of the major instruments in the Rio Declaration to support this process has been environmental assessment that has been given considerable emphasis as to its potential ability to help achieve more sustainable forms of development. Regional environmental assessment (REA) has shown to be effective in supporting local sustainable development process. Selected environmental assessment methods have been␣used to improve the REA exercise and provide reliable data for decision-making not only to correct environmental problems due to past unsustainable social-economic developments but also help local governments to implement Agenda 21 (AG21) plans and projects.     

PROBLEMS IN WEIGHTING OF HYETOGRAPHS1

ABSTRACT: It was found that the conventional weighting factor application to hyetograph ordinates results in artificially attenuated storm patterns. A modified weighting procedure is suggested which allows adjustments in the storm timing, peak intensity, and volume but conserves the storm pattern observed at the raingage nearest to the watershed point of interest. The systematic underestimation of peak flood flows, which result from conventional hyetograph weighting, can be avoided by conserving the hyetograph shape from the raingage nearest to any subarea of a modeled watershed and merely applying weighting factors to the rainfall volumes and temporal center of gravity of several hyetographs.     

Land Management in the American Southwest: A State-and-Transition Approach to Ecosystem Complexity

State-and-transition models are increasingly being used to guide rangeland management. These models provide a relatively simple, management-oriented way to classify land condition (state) and to describe the factors that might cause a shift to another state (a transition). There are many formulations of state-and-transition models in the literature. The version we endorse does not adhere to any particular generalities about ecosystem dynamics, but it includes consideration of several kinds of dynamics and management response to them. In contrast to previous uses of state-and-transition models, we propose that models can, at present, be most effectively used to specify and qualitatively compare the relative benefits and potential risks of different management actions (e.g., fire and grazing) and other factors (e.g., invasive species and climate change) on specified areas of land. High spatial and temporal variability and complex interactions preclude the meaningful use of general quantitative models. Forecasts can be made on a case-by-case basis by interpreting qualitative and quantitative indicators, historical data, and spatially structured monitoring data based on conceptual models. We illustrate how science- based conceptual models are created using several rangeland examples that vary in complexity. In doing so, we illustrate the implications of designating plant communities and states in models, accounting for varying scales of pattern in vegetation and soils, interpreting the presence of plant communities on different soils and dealing with our uncertainty about how those communities were assembled and how they will change in the future. We conclude with observations about how models have helped to improve management decision-making.     

Marine Eutrophication: A Proposed Data Analysis Procedure For Assessing Spatial Trends

A methodology for the discrimination of the different trophic levels at a spatial scale in the marine environment is proposedusing spatial analysis methods and non-parametric statistics. Phytoplankton cell number, being a representative parameter to express trophic trends in the marine ecosystem is selected forthe methodology development; Saronicos Gulf, Greece is used for the case study. The proposed stepwise methodology includes interpolation for assessing the spatial distribution of phytoplankton cell number, division of the Gulf into a number of quadrates, development of a scale characterising trophic levels and finally characterisation of the trophic state ofeach quadrate using non-parametric statistics. The advantages of this methodology and the potential applications in coastal management studies are also discussed.     

USING GEOLOGY TO IMPROVE FLOOD HAZARD MANAGEMENT ON ALLUVIAL FANS ‐ AN EXAMPLE FROM LAUGHLIN,NEVADA1

A study of the piedmont of the Newberry Mountains near Laughlin, Nevada, demonstrates that geologic information can improve the scientific basis of flood‐hazard management on alluvial fans in desert areas. Comparison of geologic information against flood insurance rate maps (FIRMs) reveals flaws in conventional methods for flood hazard delineation in this setting. Geologic evidence indicates that large parts of the Newberry piedmont have been isolated from significant flooding for at least the past 10,000 years. This contrasts with existing FIRMs that include large tracts of nonflood prone land in the 100‐year and 500‐year flood hazard zones and exclude areas of indisputably flood prone land from the regulatory flood plain. From the basis of the geology, flood hazards on at least one‐third of the piedmont are mischaracterized on the regulatory maps. The formal incorporation of geologic data into flood hazard studies on desert piedmonts could significantly reduce this type of discrepancy and substantially reduce the scope, hence cost, of more elaborate engineering studies and hazard mitigation strategies. The results of this study affirm the value of new Federal Emergency Management Agency (FEMA) recommendations for characterizing alluvial fan flood hazards and support an argument for mandating geological studies in the regulatory process.     

Spatiotemporal dynamics of spring and stream water chemistry in a high-mountain area

The present study deals with the application of the self-organizing map (SOM) technique in the exploration of spatiotemporal dynamics of spring and stream water samples collected in the Chocho?owski Stream Basin located in the Tatra Mountains (Poland). The SOM-based classification helped to uncover relationships between physical and chemical parameters of water samples and factors determining the quality of water in the studied high-mountain area. In the upper part of the Chocho?owski Stream Basin, located on the top of the crystalline core of the Tatras, concentrations of the majority of ionic substances were the lowest due to limited leaching. Significantly higher concentration of ionic substances was detected in spring and stream samples draining sedimentary rocks. The influence of karst-type springs on the quality of stream water was also demonstrated.     

Nitrogen concentrations in mosses indicate the spatial distribution of atmospheric nitrogen deposition in Europe

In 2005/6, nearly 3000 moss samples from (semi-)natural location across 16 European countries were collected for nitrogen analysis. The lowest total nitrogen concentrations in mosses (<0.8%) were observed in northern Finland and northern UK. The highest concentrations (≥1.6%) were found in parts of Belgium, France, Germany, Slovakia, Slovenia and Bulgaria. The asymptotic relationship between the nitrogen concentrations in mosses and EMEP modelled nitrogen deposition (averaged per 50 km × 50 km grid) across Europe showed less scatter when there were at least five moss sampling sites per grid. Factors potentially contributing to the scatter are discussed. In Switzerland, a strong (r² = 0.91) linear relationship was found between the total nitrogen concentration in mosses and measured site-specific bulk nitrogen deposition rates. The total nitrogen concentrations in mosses complement deposition measurements, helping to identify areas in Europe at risk from high nitrogen deposition at a high spatial resolution.     

Mosses as biomonitors of atmospheric heavy metal deposition: Spatial patterns and temporal trends in Europe

In recent decades, mosses have been used successfully as biomonitors of atmospheric deposition of heavy metals. Since 1990, the European moss survey has been repeated at five-yearly intervals. Although spatial patterns were metal-specific, in 2005 the lowest concentrations of metals in mosses were generally found in Scandinavia, the Baltic States and northern parts of the UK; the highest concentrations were generally found in Belgium and south-eastern Europe. The recent decline in emission and subsequent deposition of heavy metals across Europe has resulted in a decrease in the heavy metal concentration in mosses for the majority of metals. Since 1990, the concentration in mosses has declined the most for arsenic, cadmium, iron, lead and vanadium (52-72%), followed by copper, nickel and zinc (20-30%), with no significant reduction being observed for mercury (12% since 1995) and chromium (2%). However, temporal trends were country-specific with sometimes increases being found.