A methodological approach to develop “contaminant migration–population effects” models

The main aim of the present work is to discuss the methodological approaches that underpin the “contaminant migration–population effects” models for the evaluation of the detriment to populations of moving organisms in environmental systems with spatial and time dependent pollution levels. A technique to couple the equations controlling the population dynamics and the pollutant dispersion is described and discussed. The domain of application and the limitations of the methodology are analysed and illustrated by some examples. Possible alternative approaches are briefly presented.     

On the consequences of aggregation and balancing of networks on system properties derived from ecological network analysis

In the ecological network analysis (ENA) of complex flow food webs the assumption is often made that the models characterizing the flows and stocks of ecosystems occur in a steady state where inflows equals outflows. An assessment of the system indices derived from ENA of six balanced and unbalanced system models, respectively, indicate to differences between indices. The aggregation of highly articulated flow models into models with fewer compartments also has drastic effects on the system metrics, particularly on the information indices.     

Invasion, Disturbance, and Competition: Modeling the Fate of Coastal Plant Populations

Abstract:  Wetland habitats are besieged by biotic and abiotic disturbances such as invasive species, hurricanes, habitat fragmentation, and salinization. Predicting how these factors will alter local population dynamics and community structure is a monumental challenge. By examining ecologically similar congeners, such as Iris hexagona and I. pseudacorus (which reproduce clonally and sexually and tolerate a wide range of environmental conditions), one can identify life-history traits that are most influential to population growth and viability. We combined empirical data and stage-structured matrix models to investigate the demographic responses of native ( I. hexagona ) and invasive ( I. pseudacorus ) plant populations to hurricanes and salinity stress in freshwater and brackish wetlands. In our models I. hexagona and I. pseudacorus responded differently to salinity stress, and species coexistence was rare. In 82% of computer simulations of freshwater marsh, invasive iris populations excluded the native species within 50 years, whereas native populations excluded the invasive species in 99% of the simulations in brackish marsh. The occurrence of hurricanes allowed the species to coexist, and species persistence was determined by the length of time it took the ecosystem to recover. Rapid recovery (2 years) favored the invasive species, whereas gradual recovery (30 years) favored the native species. Little is known about the effects of hurricanes on competitive interactions between native and invasive plant species in marsh ecosystems. Our models contribute new insight into the relationship between environmental disturbance and invasion and demonstrate how influential abiotic factors such as climate change will be in determining interspecific interactions.     

Spatial smoothing techniques for the assessment of habitat suitability

Precise knowledge about factors influencing the habitat suitability of a certain species forms the basis for the implementation of effective programs to conserve biological diversity. Such knowledge is frequently gathered from studies relating abundance data to a set of influential variables in a regression setup. In particular, generalised linear models are used to analyse binary presence/absence data or counts of a certain species at locations within an observation area. However, one of the key assumptions of generalised linear models, the independence of observations is often violated in practice since the points at which the observations are collected are spatially aligned. In this paper, we describe a general framework for semiparametric spatial generalised linear models that allows for the routine analysis of non-normal spatially aligned regression data. The approach is utilised for the analysis of a data set of synthetic bird species in beech forests, revealing that ignorance of spatial dependence actually may lead to false conclusions in a number of situations.

GLOBAL CLIMATE CHANGE AND PUBLIC PERCEPTION: THE CHALLENGE OF TRANSLATION1

ABSTRACT: Global climate change is examined from the perspective of its relevancy and urgency as a public policy issue. Interpreting from literature specific to investigations into public awareness and concern, climate change is seen as a legitimate though less than urgent issue. The literature reveals that the general public holds surprising misconceptions about the processes contributing to climate change, including failure to grasp the fundamental connection to CO₂. General ambivalence is also suggested from the results of two surveys conducted by The Groundwater Foundation. They first asked participants in a recent Groundwater Guardian Conference to rate levels of discussion and concern for water resources implications in the participants' communities. A second survey polled national water resource organizations about the extent climate change has been a focus of their educational, investigative, or advocacy efforts. The paper concludes by describing basic barriers to stimulating public response to climate change, which education about the issue should address, and by offering a model to educate and involve citizens based on the Groundwater Guardian program developed by the The Groundwater Foundation.     

Choice of stakeholder groups and members in multicriteria decision models

Simplistic economic objectives such as maximisation of producer profits are of little relevance in generating information to assist in the management of natural resources beyond the individual firm level. To provide data and information to support decision-making in natural resource management, it is necessary to take into account the views of various stakeholder groups and the multiple objectives of each group, through the use of some form of multicriteria analysis (MCA). Important decisions arise in the choice of stakeholder, since this will influence the management advice generated. Many groups and individuals can be affected by resource management decisions, but it would be impractical to attempt to identify the objectives and estimate their importance for each group. Also, questions arise concerning whether or not to include government agencies (which represent the broader community) and researchers as stakeholders. A further issue concerns choosing representative samples of stakeholder groups, from which to obtain preference data. Discussions with modellers and a reading of the literature would suggest that the choice of stakeholder groups and representatives is conducted haphazardly and is perhaps biased, and that a more systematic approach is needed. This article explores the above issues with reference to a number of multicriteria analyses, including local studies.     

Using Expert and Non-expert Models of Climate Change to Enhance Communication

Climate change is a significant global risk that is predicted to be particularly devastating to coastal communities. Climate change adaptation and mitigation have been hindered by many factors, including psychological barriers, ineffective outreach and communication, and knowledge gaps. This qualitative study compares an expert model of climate change risks to county administrators' “mental” models of climate change and related coastal environmental hazards in Crystal River, Florida, USA. There were 24 common nodes in the expert and the combined non-expert models, mainly related to hurricanes, property damage, and economic concerns. Seven nodes mentioned by non-experts fit within, but were not a part of, the expert model, primarily related to ecological concerns about water quality. The findings suggest that effective climate outreach and communication could focus on compatible parts of the models and incorporate local concerns to find less controversial ways to discuss climate-related hazards.     

武汉城市圈土地利用空间关联的碳排放效率及其收敛性分析

通过测算武汉城市圈土地利用空间关联的碳排放效率及其收敛性,为该城市群提供碳减排方案。通过运用结合Bootstrap技术的Malmquist指数方法测算了武汉城市圈土地利用空间关联的碳排放效率及其技术进步和技术效率,并对该效率做σ-收敛和β-收敛分析。研究发现该城市圈土地利用空间关联的碳排放效率在2010年前呈上升趋势,之后出现下降;究其原因,虽然技术进步是持续的,但是不足以弥补技术效率的不断降低;将武汉城市圈按照土地类型分为三类城市,收敛性分析发现它们均出现了不同程度的收敛,而且收敛于较高的碳排放水平。根据以上的分析结果,结合该城市圈的产业布局,提出了相应的减碳方案。     

Evaluation of various global solar radiation models for Nigeria

This study assessed the performance of six solar radiation models. The objective was to determine the most accurate model for estimating global solar radiation on a horizontal surface in Nigeria. Twenty-two years meteorological data sets collected from the Nigerian Meteorological agency and the National Aeronautics and Space Administration for the three regions, covering the entire climatic zones in Nigeria were utilized for calibrating and validating the selected models for Nigeria. The accuracy and applicability of various models were determined for three locations (Abuja, Benin City, and Sokoto), which spread across Nigeria using seven viable statistical indices. This study found that the estimation results of considered models are statistically significant at the 95% confidence level, but their accuracy varies from one location to another. However, the multivariable regression relationship deduced in terms of sunshine ratio, air temperature ratio, maximum air temperature, and cloudiness performs better than other relationships. The multivariable relationship has the least root mean square error and mean absolute bias error, not exceeding 1.0854 and 0.8160 MJ m^?2 day^?1, respectively, and monthly relative percentage error in the range of ± 12% for the study areas.     

Scenario‐Based and Scenario‐Neutral Assessment of Climate Change Impacts on Operational Performance of a Multipurpose Reservoir

Scenario‐based and scenario‐neutral impacts assessment approaches provide complementary information about how climate change‐driven effects on streamflow may change the operational performance of multipurpose dams. Examining a case study of Cougar Dam in Oregon, United States, we simulated current reservoir operations under scenarios of plausible future hydrology. Streamflow projections from the CGCM3.1 general circulation model for the A1B emission scenario were used to generate stochastic reservoir inflows that were then further perturbed to simulate a potentially drier future. These were then used to drive a simple reservoir model. In the scenario‐based analysis, we found reservoir operations are vulnerable to climate change. Increases in fall and winter inflow could lead to more frequent flood storage, reducing flexibility to store incoming flood flows. Uncertainty in spring inflow volume complicates projection of future filling performance. The reservoir may fill more or less often, depending on whether springs are wetter or drier. In the summer, drawdown may occur earlier to meet conservation objectives. From the scenario‐neutral analysis, we identified thresholds of streamflow magnitude that can predict climate change impacts for a wide range of scenarios. Our results highlight projected operational challenges for Cougar Dam and provide an example of how scenario‐based and scenario‐neutral approaches may be applied concurrently to assess climate change impacts.