Integrating Environmental and Socio-Economic Indicators of a Linked Catchment–Coastal System Using Variable Environmental Intensity

Can we develop land use policy that balances the conflicting views of stakeholders in a catchment while moving toward long term sustainability? Adaptive management provides a strategy for this whereby measures of catchment performance are compared against performance goals in order to progressively improve policy. However, the feedback loop of adaptive management is often slow and irreversible impacts may result before policy has been adapted. In contrast, integrated modelling of future land use policy provides rapid feedback and potentially improves the chance of avoiding unwanted collapse events. Replacing measures of catchment performance with modelled catchment performance has usually required the dynamic linking of many models, both biophysical and socio-economic—and this requires much effort in software development. As an alternative, we propose the use of variable environmental intensity (defined as the ratio of environmental impact over economic output) in a loose coupling of models to provide a sufficient level of integration while avoiding significant effort required for software development. This model construct was applied to the Motueka Catchment of New Zealand where several biophysical (riverine water quantity, sediment, E. coli faecal bacteria, trout numbers, nitrogen transport, marine productivity) models, a socio-economic (gross output, gross margin, job numbers) model, and an agent-based model were linked. An extreme set of land use scenarios (historic, present, and intensive) were applied to this modelling framework. Results suggest that the catchment is presently in a near optimal land use configuration that is unlikely to benefit from further intensification. This would quickly put stress on water quantity (at low flow) and water quality (E. coli). To date, this model evaluation is based on a theoretical test that explores the logical implications of intensification at an unlikely extreme in order to assess the implications of likely growth trajectories from present use. While this has largely been a desktop exercise, it would also be possible to use this framework to model and explore the biophysical and economic impacts of individual or collective catchment visions. We are currently investigating the use of the model in this type of application.     

Social learning in a policy-mandated collaboration: community wildfire protection planning in the eastern United States

Policies such as the US Healthy Forests Restoration Act (HFRA) mandate collaboration in planning to create benefits such as social learning and shared understanding among partners. However, some question the ability of top-down policy to foster successful local collaboration. Through in-depth interviews and document analysis, this paper investigates social learning and transformative learning in three case studies of Community Wildfire Protection Planning (CWPP), a policy-mandated collaboration under HFRA. Not all CWPP groups engaged in social learning. Those that did learned most about organisational priorities and values through communicative learning. Few participants gained new skills or knowledge through instrumental learning. CWPP groups had to commit to learning, but the design of the collaborative-mandate influenced the type of learning that was most likely to occur. This research suggests a potential role for top-down policy in setting the structural context for learning at the local level, but also confirms the importance of collaborative context and process in fostering social learning.     

Climate Policy to Defeat the Green Paradox

Carbon dioxide emissions have accelerated since the signing of the Kyoto Protocol. This discouraging development may partly be blamed on accelerating world growth and on lags in policy instruments. However, it also raises serious question concerning whether policies to reduce CO₂ emissions are as effective as generally assumed. In recent years, a considerable number of studies have identified various feedback mechanisms of climate policies that often erode, and occasionally reinforce, their effectiveness. These studies generally focus on a few feedback mechanisms at a time, without capturing the entire effect. Partial accounting of policy feedbacks is common in many climate scenarios. The IPCC, for example, only accounts for direct leakage and rebound effects. This article attempts to map the aggregate effects of different types of climate policy feedback mechanisms in a cohesive framework. Controlling feedback effects is essential if the policy measures are to make any difference on a global level. A general conclusion is that aggregate policy feedback mechanisms tend to make current climate policies much less effective than is generally assumed. In fact, various policy measures involve a definite risk of ‘backfiring’ and actually increasing CO₂ emissions. This risk is particularly pronounced once effects of climate policies on the pace of innovation in climate technology are considered. To stand any chance of controlling carbon emissions, it is imperative that feedback mechanisms are integrated into emission scenarios, targets for emission reduction and implementation of climate policy. In many cases, this will reduce the scope for subsidies to renewable energy sources, but increase the scope for other measures such as schemes to return carbon dioxide to the ground and to mitigate emissions of greenhouse gases from wetlands and oceans. A framework that incorporates policy feedback effects necessitates rethinking the design of the national and regional emission targets. This leads us to a new way of formulating emission targets that include feedback effects, the global impact target. Once the full climate policy feedback mechanisms are accounted for, there are probably only three main routes in climate policy that stand a chance of mitigating global warming: (a) returning carbon to the ground, (b) technological leaps in zero-emission energy technology that make it profitable to leave much carbon in the ground even in Annex II countries and (c) international agreements that make it more profitable to leave carbon in the ground or in forests.     

Thirty year monitoring of PCBs, organochlorine pesticides and tetrabromodiphenylether in eel from The Netherlands

Because of their excellent properties as a biomonitor, yellow eels (Anguilla anguilla) have been used for time-trend monitoring of polychlorinated biphenyls (PCBs), organochlorine pesticides (OCPs) and tetrabrominated diphenylether (tetra-BDE). The program has now lasted for thirty years and has delivered valuable information on trends and spatial differences of these compounds in the delta of the rivers Rhine and Meuse and other Dutch canals, rivers and lakes. Specific local PCB, HCH and dieldrin contaminations were identified. Temporal trends show a slow decrease of PCB concentrations since 1977. Eels from the rivers Rhine and Meuse still exceed present European maximum residue limits for dioxin-like PCBs. Apart from some exceptions, OCP and tetra-BDE concentrations have also decreased, and more than those of PCBs. Fat contents of eel have decreased from an average of 21 to ca. 13%. This decrease in fat contents, coincides with the strong reduction of the European eel stock.     

Will photosynthetic capacity of aspen trees acclimate after long-term exposure to elevated CO2 and O3?

Photosynthetic acclimation under elevated carbon dioxide (CO₂) and/or ozone (O₃) has been the topic of discussion in many papers recently. We examined whether or not aspen plants grown under elevated CO₂ and/or O₃ will acclimate after 11 years of exposure at the Aspen Face site in Rhinelander, WI, USA. We studied diurnal patterns of instantaneous photosynthetic measurements as well as A/C_i measurements monthly during the 2004-2008 growing seasons. Our results suggest that the responses of two aspen clones differing in O₃ sensitivity showed no evidence of photosynthetic and stomatal acclimation under either elevated CO₂, O₃ or CO₂ + O₃. Both clones 42E and 271 did not show photosynthetic nor stomatal acclimation under elevated CO₂ and O₃ after a decade of exposure. We found that the degree of increase or decrease in the photosynthesis and stomatal conductance varied significantly from day to day and from one season to another.     

Appraisal of measurement methods, chemical composition and sources of fine atmospheric particles over six different areas of Northern Belgium

Daily and seasonal variation in the total elemental, organic carbon (OC) and elemental carbon (EC) content and mass of PM_2.5 were studied at industrial, urban, suburban and agricultural/rural areas. Continuous (optical Dustscan, standard tapered element oscillating micro-balance (TEOM), TEOM with filter dynamics measurement system), semi-continuous (Partisol filter-sampling) and non-continuous (Dekati-impactor sampling and gravimetry) methods of PM_2.5 mass monitoring were critically evaluated. The average elemental fraction accounted for 2-6% of the PM_2.5 mass measured by gravimetry. Metals, like K, Mn, Fe, Cu, Zn and Pb were strongly inter-correlated, also frequently with non-metallic elements (P, S, Cl and/or Br) and EC/OC. A high OC/EC ratio (2-9) was generally observed. The total carbon content of PM_2.5 ranged between 3 and 77% (averages: 12-32%), peaking near industrial/heavy trafficked sites. Principal component analysis identified heavy oil burning, ferrous/non-ferrous industry and vehicular emissions as the main sources of metal pollution.     

Identification of microcystins from three collection strains of Microcystis aeruginosa

Microcystins (MCs) are toxic cyclic heptapeptides produced by various cyanobacteria genera, especially Microcystis. We identified 10 out of 12 MCs produced by three Microcystis aeruginosa strains from cyanobacteria collections, UTEX 2666, UTEX 2670 and UAM 1303, by using two analytical methods: Matrix-assisted Laser Desorption Ionization Time of Flight Mass Spectrometry (MALDI-TOF/MS) and HPLC Photodiode Array Detector coupled to a hybrid Quadrupole Time of Flight Mass Spectrometry (HPLC-PDA-QTOF/MS). MALDI-TOF/MS failed to detect non-polar MCs, such as MC-LY and MC-LW. HPLC-QTOF/MS permitted the accurate identification of most MCs present in methanolic extracts. Besides, three new MCs, namely: [D-Glu(OCH₃)⁶, D-Asp³] MC-LAba, MC-YL and MC-YM were detected by HPLC-QTOF/MS.     

How life history contributes to stress response in the Manila clam <Emphasis Type="Italic">Ruditapes philippinarum</Emphasis>

Introduction  

Within the last decade, numerous studies have investigated the role of environmental history on tolerance to stress of many organisms. This study aims to assess if Manila clams Ruditapes philippinarum may react differently to cadmium exposure and trematode parasite infection (Himasthla elongata) depending on their origin and environmental history in Arcachon Bay (France).     

Modeling effects of traffic and landscape characteristics on ambient nitrogen dioxide levels in Connecticut

An integrated exposure model was developed that estimates nitrogen dioxide (NO(2)) concentration at residences using geographic information systems (GIS) and variables derived within residential buffers representing traffic volume and landscape characteristics including land use, population density and elevation. Multiple measurements of NO(2) taken outside of 985 residences in Connecticut were used to develop the model. A second set of 120 outdoor NO(2) measurements as well as cross-validation were used to validate the model. The model suggests that approximately 67% of the variation in NO(2) levels can be explained by: traffic and land use primarily within 2 km of a residence; population density; elevation; and time of year. Potential benefits of this model for health effects research include improved spatial estimations of traffic-related pollutant exposure and reduced need for extensive pollutant measurements. The model, which could be calibrated and applied in areas other than Connecticut, has importance as a tool for exposure estimation in epidemiological studies of traffic-related air pollution.     

Comparison of land-use regression models between Great Britain and the Netherlands

Land-use regression models have increasingly been applied for air pollution mapping at typically the city level. Though models generally predict spatial variability well, the structure of models differs widely between studies. The observed differences in the models may be due to artefacts of data and methodology or underlying differences in source or dispersion characteristics. If the former, more standardised methods using common data sets could be beneficial. We compared land-use regression models for NO₂ and PM_10, developed with a consistent protocol in Great Britain (GB) and the Netherlands (NL).Models were constructed on the basis of 2001 annual mean concentrations from the national air quality networks. Predictor variables used for modelling related to traffic, population, land use and topography. Four sets of models were developed for each country. First, predictor variables derived from data sets common to both countries were used in a pooled analysis, including an indicator for country and interaction terms between country and the identified predictor variables. Second, the common data sets were used to develop individual baseline models for each country. Third, the country-specific baseline models were applied after calibration in the other country to explore transferability. The fourth model was developed using the best possible predictor variables for each country.A common model for GB and NL explained NO₂ concentrations well (adjusted R² 0.64), with no significant differences in intercept and slopes between the two countries. The country-specific model developed on common variables for NL but not GB improved the prediction.The performance of models based upon common data was only slightly worse than models optimised with local data. Models transferred to the other country performed substantially worse than the country-specific models. In conclusion, care is needed both in transferring models across different study areas, and in developing large inter-regional LUR models.