Application of a Random Forest algorithm to predict spatial distribution of the potential yield of Ruditapes philippinarum in the Venice lagoon, Italy

We present a modelling framework that combines machine learning techniques and Geographic Information Systems to support the management of an important aquaculture species, Manila clam (Ruditapes philippinarum). We use the Venice lagoon (Italy), the first site in Europe for the production of R. philippinarum, to illustrate the potential of this modelling approach. To investigate the relationship between the yield of R. philippinarum and a set of environmental factors, we used a Random Forest (RF) algorithm. The RF model was tuned with a large data set (n = 1698) and validated by an independent data set (n = 841). Overall, the model provided good predictions of site-specific yields and the analysis of marginal effect of predictors showed substantial agreement among the modelled responses and available ecological knowledge for R. philippinarum. The most influent environmental factors for yield estimation were percentage of sand in the sediment, salinity, and water depth. Our results agree with findings from other North Adriatic lagoons. The application of the fitted RF model to continuous maps of all the environmental variables allowed estimates of the potential yield for the whole basin. Such a spatial representation enabled site-specific estimates of yield in different farming areas within the lagoon. We present a possible management application of our model by estimating the potential yield under the current farming distribution and comparing it to a proposed re-organization of the farming areas. Our analysis suggests a reduction of total yield is likely to result from the proposed re-organization.     

Spatial mismatch between wild bee diversity hotspots and protected areas

Wild bees are critical for multiple ecosystem functions but are currently threatened. Understanding the determinants of the spatial distribution of wild bee diversity is a major research gap for their conservation. We modeled wild bee α and β taxonomic and functional diversity in Switzerland to uncover countrywide diversity patterns and determine the extent to which they provide complementary information, assess the importance of the different drivers structuring wild bee diversity, identify hotspots of wild bee diversity, and determine the overlap between diversity hotspots and the network of protected areas. We used site-level occurrence and trait data from 547 wild bee species across 3343 plots and calculated community attributes, including taxonomic diversity metrics, community mean trait values, and functional diversity metrics. We modeled their distribution with predictors describing gradients of climate, resource availability (vegetation), and anthropogenic influence (i.e., land-use types and beekeeping intensity). Wild bee diversity changed along gradients of climate and resource availability; high-elevation areas had lower functional and taxonomic α diversity, and xeric areas harbored more diverse bee communities. Functional and taxonomic β diversities diverged from this pattern, with high elevations hosting unique species and trait combinations. The proportion of diversity hotspots included in protected areas depended on the biodiversity facet, but most diversity hotspots occurred in unprotected land. Climate and resource availability gradients drove spatial patterns of wild bee diversity, resulting in lower overall diversity at higher elevations, but simultaneously greater taxonomic and functional uniqueness. This spatial mismatch among distinct biodiversity facets and the degree of overlap with protected areas is a challenge to wild bee conservation, especially in the face of global change, and calls for better integrating unprotected land. The application of spatial predictive models represents a valuable tool to aid the future development of protected areas and achieve wild bee conservation goals.     

Agroecosystem energy transitions in the old and new worlds: trajectories and determinants at the regional scale

Energy efficiency in biomass production is a major challenge for a future transition to sustainable food and energy provision. This study uses methodologically consistent data on agroecosystem energy flows and different metrics of energetic efficiency from seven regional case studies in North America (USA and Canada) and Europe (Spain and Austria) to investigate energy transitions in Western agroecosystems from the late nineteenth to the late twentieth centuries. We quantify indicators such as external final energy return on investment (EFEROI, i.e., final produce per unit of external energy input), internal final EROI (IFEROI, final produce per unit of biomass reused locally), and final EROI (FEROI, final produce per unit of total inputs consumed). The transition is characterized by increasing final produce accompanied by increasing external energy inputs and stable local biomass reused. External inputs did not replace internal biomass reinvestments, but added to them. The results were declining EFEROI, stable or increasing IFEROI, and diverging trends in FEROI. The factors shaping agroecosystem energy profiles changed in the course of the transition: Under advanced organic and frontier agriculture of the late nineteenth and early twentieth centuries, population density and biogeographic conditions explained both agroecosystem productivity and energy inputs. In industrialized agroecosystems, biogeographic conditions and specific socio-economic factors influenced trends towards increased agroecosystem specialization. The share of livestock products in a region’s final produce was the most important factor determining energy returns on investment.

     

Environmental assessment of solid waste landfilling technologies by means of LCA-modeling

By using life cycle assessment (LCA) modeling, this paper compares the environmental performance of six landfilling technologies (open dump, conventional landfill with flares, conventional landfill with energy recovery, standard bioreactor landfill, flushing bioreactor landfill and semi-aerobic landfill) and assesses the influence of the active operations practiced on these performances. The environmental assessments have been performed by means of the LCA-based tool EASEWASTE, whereby the functional unit utilized for the LCA is "landfilling of 1ton of wet household waste in a 10m deep landfill for 100 years". The assessment criteria include standard categories (global warming, nutrient enrichment, ozone depletion, photo-chemical ozone formation and acidification), toxicity-related categories (human toxicity and ecotoxicity) and impact on spoiled groundwater resources. Results demonstrate that it is crucially important to ensure the highest collection efficiency of landfill gas and leachate since a poor capture compromises the overall environmental performance. Once gas and leachate are collected and treated, the potential impacts in the standard environmental categories and on spoiled groundwater resources significantly decrease, although at the same time specific emissions from gas treatment lead to increased impact potentials in the toxicity-related categories. Gas utilization for energy recovery leads to saved emissions and avoided impact potentials in several environmental categories. Measures should be taken to prevent leachate infiltration to groundwater and it is essential to collect and treat the generated leachate. The bioreactor technologies recirculate the collected leachate to enhance the waste degradation process. This allows the gas collection period to be reduced from 40 to 15 years, although it does not lead to noticeable environmental benefits when considering a 100 years LCA-perspective. In order to more comprehensively understand the influence of the active operations (i.e., leachate recirculation, waste flushing and air injection) on the environmental performance, the time horizon of the assessment has been split into two time periods: years 0-15 and 16-100. Results show that if these operations are combined with gas utilization and leachate treatment, they are able to shorten the time frame that emissions lead to environmental impacts of concern.     

Environmental assessment of gas management options at the Old Ämmässuo landfill (Finland) by means of LCA-modeling (EASEWASTE)

The current landfill gas (LFG) management (based on flaring and utilization for heat generation of the collected gas) and three potential future gas management options (LFG flaring, heat generation and combined heat and power generation) for the Old Ämmässuo landfill (Espoo, Finland) were evaluated by life-cycle assessment modeling. The evaluation accounts for all resource utilization and emissions to the environment related to the gas generation and management for a life-cycle time horizon of 100 yr. The assessment criteria comprise standard impact categories (global warming, photo-chemical ozone formation, stratospheric ozone depletion, acidification and nutrient enrichment) and toxicity-related impact categories (human toxicity via soil, via water and via air, eco-toxicity in soil and in water chronic).The results of the life-cycle impact assessment show that disperse emissions of LFG from the landfill surface determine the highest potential impacts in terms of global warming, stratospheric ozone depletion, and human toxicity via soil. Conversely, the impact potentials estimated for other categories are numerically-negative when the collected LFG is utilized for energy generation, demonstrating that net environmental savings can be obtained. Such savings are proportional to the amount of gas utilized for energy generation and the gas energy recovery efficiency achieved, which thus have to be regarded as key parameters. As a result, the overall best performance is found for the heat generation option – as it has the highest LFG utilization/energy recovery rates – whereas the worst performance is estimated for the LFG flaring option, as no LFG is here utilized for energy generation.Therefore, to reduce the environmental burdens caused by the current gas management strategy, more LFG should be used for energy generation. This inherently requires a superior LFG capture rate that, in addition, would reduce fugitive emissions of LFG from the landfill surface, bringing further environmental benefits.     

A qualitative descriptive case study on home medical waste management in Brazil

Journal of Material Cycles and Waste Management - This work presents a survey on the management of the home medical care waste (HMCW) from the municipality of Caruaru, an important medical and...     

Matching biodiversity indicators to policy needs

At the global scale, biodiversity indicators are typically used to monitor general trends, but are rarely implemented with specific purpose or linked directly to decision making. Some indicators are better suited to predicting future change, others are more appropriate for evaluating past actions, but this is seldom made explicit. We developed a conceptual model for assigning biodiversity indicators to appropriate functions based on a common approach used in economics. Using the model, indicators can be classified as leading (indicators that change before the subject of interest, informing preventative actions), coincident (indicators that measure the subject of interest), or lagging (indicators that change after the subject of interest has changed and thus can be used to evaluate past actions). We classified indicators based on ecological theory on biodiversity response times and management objectives in 2 case studies: global species extinction and marine ecosystem collapse. For global species extinctions, indicators of abundance (e.g., the Living Planet Index or biodiversity intactness index) were most likely to respond first, as leading indicators that inform preventative action, while extinction indicators were expected to respond slowly, acting as lagging indicators flagging the need for evaluation. For marine ecosystem collapse, indicators of direct responses to fishing were expected to be leading, while those measuring ecosystem collapse could be lagging. Classification defines an active role for indicators within the policy cycle, creates an explicit link to preventative decision-making, and supports preventative action.     

Combined effects of life-history traits and human impact on extinction risk of freshwater megafauna

Megafauna species are intrinsically vulnerable to human impact. Freshwater megafauna (i.e., freshwater animals ≥30 kg, including fishes, mammals, reptiles, and amphibians) are subject to intensive and increasing threats. Thirty-four species are listed as critically endangered on the International Union for Conservation of Nature (IUCN). Red List of Threatened Species, the assessments for which are an important basis for conservation actions but remain incomplete for 49 (24%) freshwater megafauna species. Consequently, the window of opportunity for protecting these species could be missed. Identifying the factors that predispose freshwater megafauna to extinction can help predict their extinction risk and facilitate more effective and proactive conservation actions. Thus, we collated 8 life-history traits for 206 freshwater megafauna species. We used generalized linear mixed models to examine the relationships between extinction risk based on the IUCN Red List categories and the combined effect of multiple traits, as well as the effect of human impact on these relationships for 157 classified species. The most parsimonious model included human impact and traits related to species’ recovery potential including life span, age at maturity, and fecundity. Applying the most parsimonious model to 49 unclassified species predicted that 17 of them are threatened. Accounting for model predictions together with IUCN Red List assessments, 50% of all freshwater megafauna species are considered threatened. The Amazon and Yangtze basins emerged as global diversity hotspots of threatened freshwater megafauna, in addition to existing hotspots, including the Ganges-Brahmaputra and Mekong basins and the Caspian Sea region. Assessment and monitoring of those species predicted to be threatened are needed, especially in the Amazon and Yangtze basins. Investigation of life-history traits and trends in population and distribution, regulation of overexploitation, maintaining river connectivity, implementing protected areas focusing on freshwater ecosystems, and integrated basin management are required to protect threatened freshwater megafauna in diversity hotspots.     

Untersuchungen zur Eignung wildlebender Wanderratten (Rattus norvegicus) als Indikatoren der Schwermetallbelastung

Zusammenfassung  Durch die Quantifizierung von 12 chemischen Elementen im Organsystem von wildlebenden Ratten (Rattus norvegicus) aus dem Tierpark Zittau (Sachsen) sollte die Eignung dieser spezies als passiver Bioindikator untersucht werden. Neben der Ermittlung von sogenannten Hintergrund-konzentrationen standen insbesondere Fragen zur geschlechts-und altersspezifischen Akkumulation einzelner Elemente im Organsystem von Rattus norvegicus im Vordergrund. Spezifisch zeigten dabei einzelne Elemente unterschiedliche Affinit?ten zu den entsprechenden Geweben und Organen. Insbesondere die hierbei ermittelten geschlechts- und altersspezifischen Charakteristika einzelner Elemente macht eine detaillierte Ausarbeitung einer Beprobungsstrategie für den sp?teren Einsatz als passiver Bioindikator zwingend. Unter Berücksichtigung des durch die Berechnung des Body Burden (K?rperlast) im 2. Teil der Arbeit ermittelten typischen Verteilungsmusters einzelner Elemente ist Rattus norvegicus zum integrativen Monitoring-einsatz pr?destiniert. Bernd Markert ist Professor und Direktor des internationalen Hochschulinstitutes in Zittau und Lehrstuhlinhaber für Umweltverfahrenstechnik. Der Einsatz eines freilebenden, intelligenten ‘Sch?dlings’ für die Umweltüberwachung in der Bioindikation ergibt sich für ihn aus zwei zwingenden Gesichtspunkten: 1. Die Ratte als Nutztier (psychologisch/didaktischer Ansatz) 2. und als ‘missing link’ zwischen Wirbeltier und Mensch (bioindikativer/naturwissenschaftlicher Ansatz)     

An Evaluation of Air Pollution Health Impacts and Costs in São Paulo, Brazil

The need to determine cost estimates of the hazardous effects of diseases is important in order to establish the priorities of actions for prevention and health management. The evaluation of air pollution impacts on health, based on expenditures, has been carried out, but there are obvious comparison difficulties among countries, as the health-per-capita investment varies enormously. In order to achieve a standard indicator, we applied the Disability-Adjusted Life Years (DALY) method to estimate the health burden and cost estimate due to air pollution in São Paulo, Brazil. The basic methodology was the utilization of dose–response curves of epidemiological studies conducted in São Paulo to assess air pollution and its health effects. DALY attributable to air pollution in São Paulo added up to 28,212 years annually. An indirect health cost attributable to air pollution resulted in US$ 3,222,676. This estimate refers to the children and the elderly population. These results give a preliminary and underestimated value of the burden of diseases promoted by air pollution.