Heavy metals, polycyclic aromatic hydrocarbons and polychlorinated biphenyls in surface sediments of the Naples harbour (southern Italy)

The Naples's harbour is one of the largest and most important commercial and tourist port of the Mediterranean basin. It is located on the southeast coast of Italy and receives industrial and municipal wastewaters from the city of Naples. Due to its social and economic impact, a comprehensive assessment of levels and sources of contamination of bottom sediments in this area of the Mediterranean basin is essential to identify potential danger due to mobilization of contaminants produced by managing of the same sediments. In this study, superficial sediments collected from 189 sampling sites were analyzed for grain size, heavy metals (Cr, Cu, Ni, Pb, V, Zn, Co, Sn, Cd, Hg, As, Al and Fe), 16 priority polycyclic aromatic hydrocarbons (PAHs) and perylene and 38 individual polychlorinated biphenyl (PCB) congeners. Compared to the estimated local background, Cu, Zn, Pb, Cd, Sn and Hg show enrichment factors >3 and only Hg evidences a median value higher than the NOAA (effects range - median) guidelines. Principal component analysis allowed us to clearly discriminate two areas mainly affected by heavy metals contamination and influenced by different sources related to industrial, commercial and/or urban activities. Priority PAHs are predominantly represented by three-five-ring compounds with concentrations ranging between 9 and 31774 ng g(-1) and frequently higher than the NOAA ER-M index. A prevalent pyrolitic origin of PAH was assessed on the basis of the relative abundance of the different congeners and selected isomer ratios. The concentrations of PCBs, as sum of the 38 congeners, ranged from 1 to 899 ng g(-1), with a predominance of highly chlorinated (tetra- and penta-chlorobiphenyls) congeners. WHO-TEQ values, calculated for the PCDD-like PCB congeners, suggest a relatively high level of toxicity. Generally, the concentration of PAHs and PCBs were higher near the sites of intense industrial, shipping and/or commercial activities suggesting a direct influence of these sources on the pollutant distribution patterns.     

Dynamics of trace metals in organisms and ecosystems: prediction of metal bioconcentration in different organisms and estimation of exposure risks

Metal ions interact with biological materials and their decomposition products by ligation (coordination complex-formation with certain moieties containing O, N, S, etc.). The extent of this interaction depends on the identities of both ligand and metal ion and can be described by some equation derived from perturbation theory. Uptake of metal ions - including highly toxic ones - from soils is controlled by a competition between root exudate components and soil organic matter (SOM) for the ions. SOM consists of a variety of potential ligands which evolve during humification towards more efficient binding (retention) of metals such as Cu, Ni, Cr but also of toxicants like U, Cd. The actual way of interaction can be inferred from stoichiometry of the involved compounds and the C/N ratio in the soil, providing predictions as to which metals will be most efficiently shuttled into green plants or fungi, respectively. The latter, selective process is crucial for closing nutrient cycles and sensitively depends on C/N ratio and the extent of "forcing" by onfalling leaf or needle litter. Therefore, analytical data on the soil can be used to predict possible risks of exposition to toxic metals also for human consumption of plant parts.     

A model-based assessment of the environmental impact of land-use change across scales in Southern Amazonia

Regional Environmental Change - This article describes the design of a new model-based assessment framework to identify and analyse possible future trajectories of agricultural development 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.     

Effects of anthropogenic disturbance on primate density at the landscape scale

Accurate estimations of the abundance of threatened animal populations are required for assessment of species’ status and vulnerability and conservation planning. However, density estimation is usually difficult and resource demanding, so researchers often collect data at local scales. However, anthropogenic pressures most often have landscape-level effects, for example, through habitat loss and fragmentation. We applied hierarchical distance sampling (HDS) to transect count data to determine the effect of habitat and anthropogenic factors on the density of 3 arboreal primate species inhabiting 5 distinct tropical forests across a landscape of 19,000 km² in the Udzungwa Mountains of Tanzania. We developed a novel, multiregion extension of HDS that allowed us to model density and detectability jointly across forests without losing site-specific information. For all species, the effect of anthropogenic disturbance on density was overwhelmingly negative among metapopulations: −0.63 Angolan colobus (Colobus angolensis palliatus) (95% Bayesian CI −1.03 to −0.27), −0.54 Udzungwa red colobus (Procolobus gordonorum) (−0.89 to −0.22), and −0.33 Sykes' monkey (Cercopithecus mitis monoides) (−0.63 to −0.07). Some responses to habitat factors were shared, notably the negative effect of elevation and the positive effect of climber coverage. These results are important for conservation science and practice because: the among-populations negative responses to anthropogenic disturbance provides a foundation for development of conservation plans that hold at the landscape scale, which is a comprehensive and cost-efficient approach; the among-species consistency in responses suggests conservation measures may be generalized at the guild level, which is especially relevant given the functional importance of primates in tropical rainforests; and the greater primate densities in areas at low elevation, which are closer to human settlements, point to specific management recommendations, such as the creation of buffer zones and prioritization of areas for protection.     

Seasonal decline of offspring quality in the European starling Sturnus vulgaris: an immune challenge experiment

In seasonally fluctuating environments, timing of reproduction is a crucial determinant of fitness. Studies of birds show that late breeding attempts generally result in offspring of lower reproductive value, with lower recruitment and long-term survival prospects. Several proximate mechanisms, including a seasonal decline of immune system functioning, may lead to a seasonal decline of offspring fitness. We investigated seasonal variation in offspring quality by subjecting first- and second-brood chicks of a sexually size dimorphic species, the European starling Sturnus vulgaris, to an immune challenge with a bacterial endotoxin (LPS), and evaluated their growth and physiological response in terms of total plasma antioxidant capacity (TAC), concentration of reactive oxygen metabolites and hematocrit. LPS challenge did not affect chick growth or oxidative status. However, hematocrit of second-brood chicks was higher in LPS chicks compared to controls. Body mass halfway through the rearing period (days?8–9 post-hatching), TAC and hematocrit were lower among second- vs. first-brood chicks. Interestingly, sexual dimorphism in body mass at days?8–9 post-hatching markedly differed between broods, first-brood males being 4.7% and second-brood males 22.7% heavier than their sisters, respectively. Pre-fledging mortality occurred among second-brood chicks only and was strongly female-biased. Our findings suggest that starling chicks, even if in poor conditions, are little affected by a bacterial challenge, at least in the short-term. Moreover, our study indicates that sex differences in body size, possibly mediated by sex-specific maternal investment in egg size, may heavily impact on pre-fledging survival in a different way in the course of the breeding season, resulting in sex-specific seasonal decline of offspring fitness. Finally, we suggest that levels of circulating antioxidants should be regarded among the proximate causes of the association between timing of fledging and long-term survival in avian species.     

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.

     

Evaluating mortality rates with a novel integrated framework for nonmonogamous species

The conservation of wildlife requires management based on quantitative evidence, and especially for large carnivores, unraveling cause‐specific mortalities and understanding their impact on population dynamics is crucial. Acquiring this knowledge is challenging because it is difficult to obtain robust long‐term data sets on endangered populations and, usually, data are collected through diverse sampling strategies. Integrated population models (IPMs) offer a way to integrate data generated through different processes. However, IPMs are female‐based models that cannot account for mate availability, and this feature limits their applicability to monogamous species only. We extended classical IPMs to a two‐sex framework that allows investigation of population dynamics and quantification of cause‐specific mortality rates in nonmonogamous species. We illustrated our approach by simultaneously modeling different types of data from a reintroduced, unhunted brown bear (Ursus arctos) population living in an area with a dense human population. In a population mainly driven by adult survival, we estimated that on average 11% of cubs and 61% of adults died from human‐related causes. Although the population is currently not at risk, adult survival and thus population dynamics are driven by anthropogenic mortality. Given the recent increase of human‐bear conflicts in the area, removal of individuals for management purposes and through poaching may increase, reversing the positive population growth rate. Our approach can be generalized to other species affected by cause‐specific mortality and will be useful to inform conservation decisions for other nonmonogamous species, such as most large carnivores, for which data are scarce and diverse and thus data integration is highly desirable.     

Agricultural waste as household fuel: Techno-economic assessment of a new rice-husk cookstove for developing countries

In many rural contexts of the developing world, agricultural residues and the organic fraction of waste are often burned in open-air to clear the lands or just to dispose them. This is a common practice which generates uncontrolled emissions, while wasting a potential energy resource. This is the case of rice husk in the Logone Valley (Chad/Cameroon). In such a context household energy supply is a further critical issue. Modern liquid fuel use is limited and traditional solid fuels (mainly wood) are used for daily cooking in rudimentary devices like 3-stone fires, resulting in low efficiency fuel use, huge health impacts, increasing exploitation stress for the local natural resources. Rice husk may be an alternative fuel to wood for household energy supply. In order to recover such a biomass, the authors are testing a proper stove with an original design. Its lay-out (featuring a metal-net basket to contain the fuel and a chimney to force a natural air draft) allows a mix of combustion/gasification of the biomass occurring in a completely burning fire, appropriate for cooking tasks. According to results obtained with rigorous test protocols (Water Boiling Test), different lay-outs have been designed to improve the performance of the stove. Technical and economic issues have been addressed in the development of such a model; building materials have been chosen in order to guarantee a cost as low as possible, using locally available items. The feasibility of the introduction of the stove in the studied context was assessed through an economic model that keeps into account not only the technology and fuel costs, but also the energy performance. According to the model, the threshold for the trade-off of the stove is the use of rice husk to cover 10–15% of the household energy needs both with traditional fireplaces or with improved efficiency cookstoves. The use of the technology proposed in combination with improved woodstove would provide householders with an appropriate and convenient cooking technology portfolio, increasing the opportunities of choice of the preferred energy system for the user and allowing significant savings for the family budget (up to 50% of the total annual cooking energy expenditure). The proposed model may be used also as a tool for the evaluation of the affordability or for the comparison of different cooking technologies also in other similar contexts, given their specific techno-economic parameter values.     

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.