A climate-change vulnerability and adaptation assessment for Brazil's protected areas

Brazil hosts the largest expanse of tropical ecosystems within protected areas (PAs), which shelter biodiversity and support traditional human populations. We assessed the vulnerability to climate change of 993 terrestrial and coastal-marine Brazilian PAs by combining indicators of climatic-change hazard with indicators of PA resilience (size, native vegetation cover, and probability of climate-driven vegetation transition). This combination of indicators allows the identification of broad climate-change adaptation pathways. Seventeen PAs (20,611 km²) were highly vulnerable and located mainly in the Atlantic Forest (7 PAs), Cerrado (6), and the Amazon (4). Two hundred fifty-eight PAs (756,569 km²), located primarily in Amazonia, had a medium vulnerability. In the Amazon and western Cerrado, the projected severe climatic change and probability of climate-driven vegetation transition drove vulnerability up, despite the generally good conservation status of PAs. Over 80% of PAs of high or moderate vulnerability are managed by indigenous populations. Hence, besides the potential risks to biodiversity, the traditional knowledge and livelihoods of the people inhabiting these PAs may be threatened. In at least 870 PAs, primarily in the Atlantic Forest and Amazon, adaptation could happen with little or no intervention due to low climate-change hazard, high resilience status, or both. At least 20 PAs in the Atlantic Forest, Cerrado, and Amazonia should be targeted for stronger interventions (e.g., improvement of ecological connectivity), given their low resilience status. Despite being a first attempt to link vulnerability and adaptation in Brazilian PAs, we suggest that some of the PAs identified as highly or moderately vulnerable should be prioritized for testing potential adaptation strategies in the near future.     

Sampling strategies in the assessment of long‐term exposures to toxic substances in air

The decision to mitigate exposures from vapor intrusion (VI) is typically based on limited data from 24‐hour air samples. It is well documented that these data do not accurately represent long‐term average exposures linked to adverse health effects. Limited decision guidance is currently available to determine the most appropriate sampling strategy, considering the cost of sampling alternatives along with the economic consequences of exposure‐related health effects. We present a decision model that introduces economic and statistical considerations in evaluating alternative VI sampling methods. The model characterizes the best sampling method by factoring economic and health consequences of exposure, the variability of exposure, the cost of sampling and mitigation, and the likelihood of false‐negatives and false‐positives. Decision‐makers can use results to select the sample size that maximizes net benefit. Conceptual and mathematical models are presented linking biological, statistical, and economic considerations to assess the cost and effectiveness of different sampling strategies. The model relates an average exposure concentration, determined statistically, to abatement costs and to the monetary value of health deterioration. The value of the information provided by different strategies is calculated and used to select the optimum sampling method. Simulations show that longer‐term sampling methods tend to be more accurate and cost‐effective than short‐term samples. The ideal sampling strategy shows significant seasonal variation (it is typically optimal to use longer samples in the winter) and also varies significantly with the stringency of regulatory standards. Longer‐term sample collection provides a more accurate representation of average VI exposure and reduces the likelihood of type I and type II errors. This reduces expected costs of mitigation and exposure (e.g., health consequences, legal and regulatory penalties), which in some cases can be quite significant. The model herein shows how these savings are balanced against the additional costs of longer‐term sampling.     

Assessing the influence of altitude and temperature on biological monitoring of freshwater quality: A preliminary investigation

The effect of altitude and water temperature on biomonitoring of freshwater quality was examined along an unpolluted area (36 km in length) of the upper Río Tajo (central Spain). The macrobenthic and fish communities were studied, and the Biological Monitoring Water Quality (BMWQ) method was applied. As expected, values of altitude and temperature respectively decreased and increased with increasing distance from the river source; these two physical parameters exhibited a negative and significant (P<0.05) correlation coefficient between them. However, despite evident changes in the functional structure of both aquatic communities along the study area, BMWQ scores were similar at all sampling sites. Pearson correlation coefficients between physical and biological parameters were not significant (P>0.05). The BMWQ index only exhibited significant (positive) correlation coefficients with macrobenthic and fish biomasses, indicating that freshwater quality could affect the biological production of fluvial ecosystems. It is concluded that biomonitoring of freshwater quality may be independent of the influence of altitude and water temperature at local spatial scales. Nonetheless, further investigations would be needed to clearly differentiate between the effects of anthropogenic and natural causes on biological monitoring at larger spatial scales.     

Atmospheric pollution in Beijing, China, as recorded in sediments of the Kunming Lake

The fluxes of heavy metals and magnetite, a fly-ash component, from coal burning, to sediments of the Kunming Lake in Beijing have increased measurably over the last fifty years. Ages were introduced to the sediment strata through Pb-210 geochronologies. Even with a doubling of coal usage by the year 2000, the anthropogenic metal fluxes will still be less than those recorded in metropolitan Tokyo and U.S. lakes.     

Food justice youth development: using Photovoice to study urban school food systems*

How do youth learn through participation in efforts to study and change the school food system? Through our participatory youth action research (YPAR) project, we move beyond the “youth as consumer” frame to a food justice youth development (FJYD) approach. We track how a group of youth learned about food and the public policy process through their efforts to transform their own school food systems by conducting a participatory evaluation of farm-to-school efforts in collaboration with university and community partners. We used the Photovoice research method, placing cameras in the hands of young people so that they themselves could document and discuss their concerns and perspectives. The research was designed to gain insight about youths’ knowledge of food, health, and community food systems. Drawing upon the youth group’s insights, we build a framework for building critical consciousness through FJYD.     

Hydroponic root mats for wastewater treatment—a review

Hydroponic root mats (HRMs) are ecotechnological wastewater treatment systems where aquatic vegetation forms buoyant filters by their dense interwoven roots and rhizomes, sometimes supported by rafts or other floating materials. A preferential hydraulic flow is created in the water zone between the plant root mat and the bottom of the treatment system. When the mat touches the bottom of the water body, such systems can also function as HRM filter; i.e. the hydraulic flow passes directly through the root zone. HRMs have been used for the treatment of various types of polluted water, including domestic wastewater; agricultural effluents; and polluted river, lake, stormwater and groundwater and even acid mine drainage. This article provides an overview on the concept of applying floating HRM and non-floating HRM filters for wastewater treatment. Exemplary performance data are presented, and the advantages and disadvantages of this technology are discussed in comparison to those of ponds, free-floating plant and soil-based constructed wetlands. Finally, suggestions are provided on the preferred scope of application of HRMs.     

Environmental management intentions: An empirical investigation of Argentina's polluting firms

This paper builds on past behavioural research which explicitly recognises that ‘actions’ are preceded by ‘intentions’ which are in turn determined by individual mindsets, locus of control, principles of governances and context factors. More concretely, it presents a model that investigates the extent to which environmental behavioural intentions are explained by i) managers' core values, basic assumptions, and beliefs, ii) individual and socio-cognitive frames, iii) principles of governance, and iv) context factors. Context factors include obstacles and drivers of greener behaviours, market pressures, and firm demographics. The resulting theoretical framework is tested empirically through regression analyses that use data gathered from a survey of 536 Argentinean firms in polluting industries. The model performs well, explaining approximately 50% of the variations in the (pro) environmental behaviour of firms. Policy implications are briefly discussed.     

Ecotoxicity interspecies study of ionic liquids based on phosphonium and ammonium cations

Environmental Science and Pollution Research - This work studies the effects of different bromide-based ionic liquids, with phosphonium and ammonium cations, towards several environmental...     

Vegetation cover and rainfall seasonality impact nutrient loss via runoff and erosion in the Colombian Andes

Regional Environmental Change - Mountain ecosystems provide key services to a large portion of the population in the tropics. However, they are particularly vulnerable to regional environmental...     

A methodology to identify representative configurations of sensors for monitoring soil moisture

Soil moisture is the key link among hydroecological compartments, responding dynamically to sequences of atmospheric processes and management conditions and modulating physical, chemical, and biological processes in the soil. Currently, there are a variety of monitoring techniques to measure, directly or indirectly, the soil moisture. However, some practical issues remain open like the definition a priori of the number, location and depth of the monitoring points, and the impact of failing or poor performance soil moisture sensors. Here, we present a set of techniques, namely Δθ time series, wavelet filtering, and time stability, to identify representative points and monitoring depths through an analysis of hourly soil moisture time series for different configuration of the monitoring network. We used real data from a monitoring network consisting of seven monitoring points, each one with four EC-5 probes (Decagon Devices Inc., Pullman, WA) at 20, 40, 60, and 100?cm. The use of simple time series of Δθ allowed us to assess the spatiotemporal influence of the monitoring points, while the wavelet periodograms allowed us to get insight about the response of the monitoring points at different time scales. Both methods are easy to implement or adapt to specific conditions, being coherent to the results derived from time stability analysis. For our case study, we concluded that we could reallocate 16 sensors (out of 28) without a significant loss of information. However, the final decision strongly relies on a deep knowledge of the site features and the objectives of the monitoring network.