The BIOTA Biodiversity Observatories in Africa—a standardized framework for large-scale environmental monitoring

The international, interdisciplinary biodiversity research project BIOTA AFRICA initiated a standardized biodiversity monitoring network along climatic gradients across the African continent. Due to an identified lack of adequate monitoring designs, BIOTA AFRICA developed and implemented the standardized BIOTA Biodiversity Observatories, that meet the following criteria (a) enable long-term monitoring of biodiversity, potential driving factors, and relevant indicators with adequate spatial and temporal resolution, (b) facilitate comparability of data generated within different ecosystems, (c) allow integration of many disciplines, (d) allow spatial up-scaling, and (e) be applicable within a network approach. A BIOTA Observatory encompasses an area of 1?km² and is subdivided into 100 1-ha plots. For meeting the needs of sampling of different organism groups, the hectare plot is again subdivided into standardized subplots, whose sizes follow a geometric series. To allow for different sampling intensities but at the same time to characterize the whole square kilometer, the number of hectare plots to be sampled depends on the requirements of the respective discipline. A hierarchical ranking of the hectare plots ensures that all disciplines monitor as many hectare plots jointly as possible. The BIOTA Observatory design assures repeated, multidisciplinary standardized inventories of biodiversity and its environmental drivers, including options for spatial up- and downscaling and different sampling intensities. BIOTA Observatories have been installed along climatic and landscape gradients in Morocco, West Africa, and southern Africa. In regions with varying land use, several BIOTA Observatories are situated close to each other to analyze management effects.     

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.     

Monitoring of marine mucilage formation in Italian seas investigated by infrared spectroscopy and independent component analysis

The aim of this study is to present and to discuss some characteristics of recalcitrant organic matter mechanism and formation. These aggregates called mucilages that are produced by the degradation reactions of several algae, have been investigated by infrared (FTIR) spectroscopy. FTIR spectra of macroaggregates produced by different algal samples have been daily collected in order to investigate the steps of aggregation. Afterwards, they have been elaborated by means of Independent Component Analysis (ICA). ICA investigation of FTIR spectra showed that the global aggregation process of marine mucilage always consisted of two different phases or independent components (ICs). One IC is related to the first degradation step of algal cells leading to the production of mono and oligosaccharides with aminoacids and oligopeptides. The second IC is related to the polymerization of oligosaccharides with aminoacids and oligopeptides and to their interaction with less polar compounds such as lipids thus producing supramolecular structures. The emerging mechanisms of anomalous size aggregates of organic matter match those of natural organic matter aggregation. The approach we suggest is to use synthetic mucilages which allows to monitor the macroaggregates formation because it can hardly be performed by means of natural marine macroaggregates.     

A simple linear model for estimating ozone AOT40 at forest sites from raw passive sampling data

A rapid, empirical method is described for estimating weekly AOT40 from ozone concentrations measured with passive samplers at forest sites. The method is based on linear regression and was developed after three years of measurements in Trentino (northern Italy). It was tested against an independent set of data from passive sampler sites across Italy. It provides good weekly estimates compared with those measured by conventional monitors (0.85 ≤R(2)≤ 0.970; 97 ≤ RMSE ≤ 302). Estimates obtained using passive sampling at forest sites are comparable to those obtained by another estimation method based on modelling hourly concentrations (R(2) = 0.94; 131 ≤ RMSE ≤ 351). Regression coefficients of passive sampling are similar to those obtained with conventional monitors at forest sites. Testing against an independent dataset generated by passive sampling provided similar results (0.86 ≤R(2)≤ 0.99; 65 ≤ RMSE ≤ 478). Errors tend to accumulate when weekly AOT40 estimates are summed to obtain the total AOT40 over the May-July period, and the median deviation between the two estimation methods based on passive sampling is 11%. The method proposed does not require any assumptions, complex calculation or modelling technique, and can be useful when other estimation methods are not feasible, either in principle or in practice. However, the method is not useful when estimates of hourly concentrations are of interest.     

PBDEs and PCBs in sediments of the Thi Nai Lagoon (Central Vietnam) and soils from its mainland

Concentration and distribution of PCBs, PCB 11, and PBDEs in both surficial sediment and soil samples, taken from a zone subject to recent accelerated development, were investigated to assess the environmental quality and understand both natural and anthropogenic processes that influence contaminant behaviors. Values of PCB and PBDE are in the lower range of those reported in literature, typical of low impacted coastal zones. This could be due to efficient processes of resuspension and removal. Contaminants in the lagoon showed higher concentrations in sediments from sites close to the city and the outfalls of the industrial area, while soils showed maximum values in the northern samples. In addition, congener patterns and statistical analyses suggest the presence of effective degradation processes, especially for PBDEs, with the exception of the most concentrated samples that may indicate a direct input. PCB 11 is a significant component (up to 18%) in most lagoon sediments. Its presence is strongly associated with fine particles, thus the distribution seems to be driven mainly by the system hydrodynamic and does not trace the sources. Due to evaporation, only flooded agricultural soils show a similar relative abundance of this congener.     

Kinetic behavior of anti-inflammatory drug ibuprofen in aqueous medium during its degradation by electrochemical advanced oxidation

The electrochemical abatement of the drug ibuprofen (2-(4-isobutylphenyl)propionic acid) from aqueous solution has been carried out by anodic oxidation. The electrolyses have been performed at constant current using a small, undivided cell equipped with a Pt or thin-film boron-doped diamond (BDD) anode and a carbon-felt cathode. The results have shown that ibuprofen has been destroyed under all the conditions tested, following pseudo-first-order kinetics; however, BDD enables higher removal rates than Pt, because the former produces greater quantity of ^?OH. Using BDD anode, the pseudo-first-order rate constant increased with applied current and when NaCl replaced Na₂SO₄ as supporting electrolyte, while it is almost unaffected by ibuprofen concentration. Mineralization of ibuprofen aqueous solutions was followed by total organic carbon (TOC) measurements. After 8 h of electrolysis, TOC removal varied from 91 % to 96 % applying a current in the range of 50–500 mA. The reaction by-products were quantified by chromatographic techniques, and in particular, aliphatic acids (oxalic, glyoxylic, formic, acetic, and pyruvic) have been the main intermediates formed during the electrolyses. The absolute rate constant for the oxidative degradation of ibuprofen have also been determined, by competition kinetic method, as 6.41?×?10⁹ M^?1?s^?1.     

The Fate of Priority Areas for Conservation in Protected Areas: A Fine-Scale Markov Chain Approach

Park managers in alpine areas must deal with the increase in forest coverage that has been observed in most European mountain areas, where traditional farming and agricultural practices have been abandoned. The aim of this study is to develop a fine-scale model of a broad area to support the managers of Paneveggio Nature Park (Italy) in conservation planning by focusing on the fate of priority areas for conservation in the next 50–100 years. GIS analyses were performed to assess the afforestation dynamic over time using two historical maps (from 1859 and 1936) and a series of aerial photographs and ortho-photos (taken from 1954 to 2006) covering a time span of 150 years. The results show an increase in the forest surface area of about 35%. Additionally, the forest became progressively more compact and less fragmented, with a consequent loss of ecotones and open habitats that are important for biodiversity. Markov chain-cellular automata models were used to project future changes, evaluating the effects on a habitat scale. Simulations show that some habitats defined as priority by the EU Habitat Directive will be compromised by the forest expansion by 2050 and suffer a consistent loss by 2100. This protocol, applied to other areas, can be used for designing long-term management measures with a focus on habitats where conservation status is at risk.     

The effect of environmental regulation on firms' competitive performance: the case of the building & construction sector in some EU regions

There is a considerable debate on the effects of environmental regulation on competitive performance. Based on survey data, this paper analyzesthe two main research questions, derived from literature, on the links between environmental regulation and competitiveness, by focusing on firms operating in the building and construction sector, i.e.: 1) whether environmental policy stringency affects the competitive performance of firms in the building and construction sector 2) and how a specific form of environmental regulation (direct regulation, economic instruments and soft instruments) affects this performance? By applying a regression analysis, we find that a more stringent environmental regulation, measured by inspection frequency, provides a positive impulse for increasing investments in advanced technological equipment and innovative products and on business performance. Moreover, a well-designed “direct regulation” appears to be the most effective policy instrument for prompting the positive impact of environmental policies on innovation and intangible performance while economic instruments do negatively affect business performance.     

Simulation and analysis of outbreaks of bark beetle infestations and their management at the stand level

Outbreaks of bark beetles in forests can result in substantial economic losses. Understanding the factors that influence the development and spread of bark beetle outbreaks is crucial for forest management and for predicting outbreak risks, especially with the expected global warming. Although much research has been done on the ecology and phenology of bark beetles, the complex interplay between beetles, host trees, beetle antagonists and forest management makes predicting beetle population development especially difficult. Using the recent infestations of the European Spruce Bark Beetle (Ips typographus L. Col. Scol.) in the Bavarian Forest National Park (Germany) as a case study, we developed a spatially explicit agent-based simulation model (SAMBIA) that takes into account individual trees and beetles. This model primarily provides a tool for analysing and understanding the spatial and temporal aspects of bark beetles outbreaks at the stand scale. Furthermore, the model should allow an estimation of the effectiveness of concurrent impacts of both antagonists and management to confine outbreak dynamics in practice. We also used the model to predict outbreak probabilities in various settings. The simulation results indicated a distinct threshold behaviour of the system in response to pressure by antagonists or management of the bark beetle population. Despite the different scenarios considered, we were able to extract from the simulations a simple rule of thumb for the successful control of an outbreak: if roughly 80% of individual beetles are killed by antagonists or foresters, outbreaks will rarely take place. Our model allows the core dynamics of this complex system to be reduced to this inherent common denominator.