Integration of different environmental valuation methods to estimate forest degradation in arid and semi-arid regions

Many factors are aggravating desertification and degradation of forests such as urbanization, droughts, exploitation of natural resources and climate change. The study aims at estimating and assessing the degradation of forests in arid and semi-arid regions. This task however is complicated since the impact of the degradation will be in different forms such as loss of wood, soil erosion and lost recreational areas. Nevertheless the dynamic impact of the degradation is increasing the complexity of analysis since forest once lost is a reduction of value for all subsequent years. This study is considering the value of damages over time and it is using the concept of three environmental valuation methods to estimate the whole impact of the degradation: the habitat equivalency analysis (HEA), the productivity method and the benefit transfer method. The methods were applied to specific values of forests, depending on the best applicability, and the results combined to an overall value loss. The costs are calculated based on the year 2014 with two time horizons: 30 and 100 years. To apply the valuation approach, Jordan as an arid and semi-arid country is chosen. The result shows that the annual costs of environmental degradation of Jordanian forest areas equal about 0.14% of GDP in 2013, proving the enormous value lost to forest degradation or deforestation. The valuation approach can be transferred to other arid or semi-arid areas and stimulate forest conservation activities to prevent further degradation and to save the forest ecosystem services for the future.     

Predation affects alarm call usage in female Diana monkeys (Cercopithecus diana diana)

Diana monkeys produce acoustically distinct calls to a number of external events, including different types of predators. In a previous study, we found population-wide differences in male alarm call production in Taï Forest, Ivory Coast, and on Tiwai Island, Sierra Leone, mostly likely originating from differences in predator experience. In Taï Forest, leopards (Panthera pardus) are common but on Tiwai Island they have been absent for decades, while the predation pressure from crowned eagles (Stephanoaetus coronatus) has been similar. To further evaluate the impact of predator experience, we here analyse the vocal behaviour of female Diana monkeys in both habitats. Female Diana monkeys produce predator-specific alarm calls, alert calls and contact calls in response to predators, suggesting that their calls serve in a broader range of functions compared to males. Results showed that females produced the same call types at both sites, despite the differences in predator fauna. Regarding call usage, leopard alarm calls were extremely rare on Tiwai Island, but not in Taï Forest, whereas we found no differences in eagle alarm call production. When comparing response latencies, Tiwai females were slower to respond to both predators compared to Taï females. Finally, we found no habitat-specific acoustic differences in the alert and predator-specific alarm calls, but significant differences in frequency-based parameters of contact calls. Overall, our results suggest that ontogenetic experience can affect primate vocal behaviour in both usage and acoustic structure but that the way in which particular call types are affected may be closely linked to function.     

Modelling spatial patterns of correlations between concentrations of heavy metals in mosses and atmospheric deposition in 2010 across Europe

Background

This paper aims to investigate the correlations between the concentrations of nine heavy metals in moss and atmospheric deposition within ecological land classes covering Europe. Additionally, it is examined to what extent the statistical relations are affected by the land use around the moss sampling sites. Based on moss data collected in 2010/2011 throughout Europe and data on total atmospheric deposition modelled by two chemical transport models (EMEP MSC-E, LOTOS-EUROS), correlation coefficients between concentrations of heavy metals in moss and in modelled atmospheric deposition were specified for spatial subsamples defined by ecological land classes of Europe (ELCE) as a spatial reference system. Linear discriminant analysis (LDA) and logistic regression (LR) were then used to separate moss sampling sites regarding their contribution to the strength of correlation considering the areal percentage of urban, agricultural and forestry land use around the sampling location. After verification LDA models by LR, LDA models were used to transform spatial information on the land use to maps of potential correlation levels, applicable for future network planning in the European Moss Survey.

Results

Correlations between concentrations of heavy metals in moss and in modelled atmospheric deposition were found to be specific for elements and ELCE units. Land use around the sampling sites mainly influences the correlation level. Small radiuses around the sampling sites examined (5 km) are more relevant for Cd, Cu, Ni, and Zn, while the areal percentage of urban and agricultural land use within large radiuses (75–100 km) is more relevant for As, Cr, Hg, Pb, and V. Most valid LDA models pattern with error rates of <?40% were found for As, Cr, Cu, Hg, Pb, and V. Land use-dependent predictions of spatial patterns split up Europe into investigation areas revealing potentially high (=?above-average) or low (=?below-average) correlation coefficients.

Conclusions

LDA is an eligible method identifying and ranking boundary conditions of correlations between atmospheric deposition and respective concentrations of heavy metals in moss and related mapping considering the influence of the land use around moss sampling sites.

     

Digital data sources and methods for conservation culturomics

Ongoing loss of biological diversity is primarily the result of unsustainable human behavior. Thus, the long-term success of biodiversity conservation depends on a thorough understanding of human–nature interactions. Such interactions are ubiquitous but vary greatly in time and space and are difficult to monitor efficiently at large spatial scales. However, the Information Age also provides new opportunities to better understand human–nature interactions because many aspects of daily life are recorded in a variety of digital formats. The emerging field of conservation culturomics aims to take advantage of digital data sources and methods to study human–nature interactions and thus to provide new tools for studying conservation at relevant temporal and spatial scales. Nevertheless, technical challenges associated with the identification, access, and analysis of relevant data hamper the wider adoption of culturomics methods. To help overcome these barriers, we propose a conservation culturomics research framework that addresses data acquisition, analysis, and inherent biases. The main sources of culturomic data include web pages, social media, and other digital platforms from which metrics of content and engagement can be obtained. Obtaining raw data from these platforms is usually desirable but requires careful consideration of how to access, store, and prepare the data for analysis. Methods for data analysis include network approaches to explore connections between topics, time-series analysis for temporal data, and spatial modeling to highlight spatial patterns. Outstanding challenges associated with culturomics research include issues of interdisciplinarity, ethics, data biases, and validation. The practical guidance we offer will help conservation researchers and practitioners identify and obtain the necessary data and carry out appropriate analyses for their specific questions, thus facilitating the wider adoption of culturomics approaches for conservation applications.     

Fusing strategic risk and futures methods to inform long-term strategic planning: case of water utilities

Risks and futures methods have complementary strengths as tools for managing strategic decisions under uncertainty. When combined, these tools increase organisational competency to evaluate and manage long-term risks, improving the flexibility and agility of the organisation to deal with gross uncertainties. Here, we set out a framework to guide the assessment of strategic risks for long-term business planning, based on its application at Portugal’s largest water utility, Empresa Portuguesa das Águas Livres. Our approach extends strategic risk assessment by incorporating scenario planning—a futures approach used to help the utility move beyond single point forecast of risks to focus on critical dimensions of uncertainty that are fundamental to the resilience of corporate objectives and their vulnerability to external pressures. We demonstrate how we combine two complementary approaches—risk and futures—and use them to assess (i) how a set of baseline strategic risks for a water utility evolves under alternative futures, (ii) the aggregate corporate-level risk exposure, and (iii) the process and responses needed to manage multiple, interdependent strategic risks. The framework offers a corporate approach to evolving strategic risks and improves a utility’s (i) knowledge of uncertainties, (ii) ability to assess the impacts of external developments over long time horizons and the consequences of actions and (iii) degree of flexibility to adapt to possible future challenges. The framework supports risk managers in their long-term strategic planning, through the appraisal and management of multiple, interdependent long-term strategic risks and can be replicated in other organisational contexts to bridge operational and corporate perspectives of enterprise risk.

     

In Vitro Degradation and Cytotoxicity Response of Biobased Nanoparticles Prepared by Thiol-ene Polymerization in Miniemulsion

Journal of Polymers and the Environment - Biodegradability is a key feature for the application of polymeric devices in medicine. This study reports an experimental and theoretical study of the...     

Thermoplasticized Pectin by Extrusion/Thermo-Compression for Film Industrial Application

Journal of Polymers and the Environment - Researches for the development of materials with less environmental impact have been more common. Pectin is a natural polysaccharide, presenting in plants...     

Biogeochemical characterization of surface waters in the Aljustrel mining area (South Portugal)

Aljustrel mining area (South Portugal) is a part of the Iberian Pyrite Belt and encloses six sulfide mineral masses. This mine is classified of high environmental risk due to the large tailings’ volume and acid mine drainage (AMD)-affected waters generated by sulfides’ oxidation. The use of biological indicators (e.g., diatoms) revealed to be an important tool to address the degree of AMD contamination in waters. Multivariate analysis has been used as a relevant approach for the characterization of AMD processes. Cluster analysis was used to integrate the significant amount and diversity of variables (physicochemical and biological), discriminating the different types of waters, characterized by the high complexity occurring in this region. The distinction of two main marked phenomena was achieved: (1) the circumneutral-Na-Cl water type (sites DA, PF, BX, BF, RO, CB), expressing the geological contributions of the Cenozoic sediments of Sado river basin, with high diatom diversity (predominating brackish diatoms as Entomoneis alata); and (2) the acid–metal-sulfated water type (sites BM, JU, RJ, AA, MR, BE, PC, AF), reflecting both the AMD contamination and the dissolution of minerals (e.g., silicates) from the hosting rocks, potentiated by the extremely low pH. This last group of sites showed lower diatom diversity but with typical diatoms from acid- and metal-contaminated waters (e.g., Pinnularia aljustrelica). In addition to these two water types, this hierarchical classification method also allowed to distinguish individual cases in subclusters, for example, treated dams (DC, DD), with alkaline substances (lime/limestone), that changed the physicochemical dynamics of the contaminated waters.

     

Distribution of potentially harmful elements in soils around a large coal-fired power plant

An understanding of the spatial distribution and contribution of a power plant to local soil contamination is important for the planning of soil use and prioritizing remedial actions for public safety. Consequently, the aim of this study was to map the spatial distribution of potentially hazardous elements (PHEs; Cu, Pb, Zn, Ni, Cr, Fe, Mn, Cd, As, and Se) in soils around a large (796 MW) coal-fired power plant in Brazil. For the purpose, 33 soil samples were collected in the area within a radius of approximately 17.5 km from the plant and subsequently analyzed for PHEs. The frequency and direction of winds were also obtained from a meteorological station in the region. The sampling area was divided into four quadrants (northwest: N-NW; northeast: N-NE; southeast: S-SE; southwest: S-SW), and there were significant negative correlations between the distance and the concentrations of Se in the S-SE quadrant and As in the S-SW and S-SE quadrants. There were positive correlations between distance from the plant and the concentration of Mn in the N-NE quadrant and the concentration of Cd in the S-SW quadrant. The dominant direction of the winds was N-NE. The indexes used in this study showed low-to-moderate enrichment factor, but detailed analysis of the dominant quadrant of the winds showed a correlation with higher concentrations in the soils closer to the power plant for at least seven of the PHEs analyzed, especially with regard to As. Therefore, we conclude that the distribution of the metalloid As can be used as a marker of the spatial distribution of contamination from the thermoelectric plant, but the dynamics of the other elements suggests that the presence of other sources of contamination may also compromise the quality of local soils.