The primary objective of this study was the isolation of low-density polyethylene (LDPE)-degrading microorganisms. Soil samples were obtained from an aged municipal landfill in Tehran, Iran, and enrichment culture procedures were performed using LDPE films and powder. Screening steps were conducted using linear paraffin, liquid ethylene oligomer, and LDPE powder as the sole source of carbon. Two landfill-source isolates, identified as 'Lysinibacillus xylanilyticus' XDB9 (T) strain S7-10F and 'Aspergillus niger' strain F1-16S, were selected as super strains. Photo-oxidation (25 days under ultraviolet [UV] irradiation) was used as a pretreatment of the LDPE samples without pro-oxidant additives. The PE biodegradation process was performed for 56 days in a liquid mineral medium using UV-irradiated pure LDPE films without pro-oxidant additives in the presence of the bacterial isolate, the fungal isolate, and the mixture of the two isolates. The process was monitored by measuring the fungal biomass, the bacterial growth, and the pH of the medium. During the process, the fungal biomass and the bacterial growth increased, and the pH of the medium decreased, which suggests the utilization of the preoxidized PE by the selected isolates as the sole source of carbon. Carbonyl and double bond indices exhibited the highest amount of decrement and increment, respectively, in the presence of the fungal isolate, and the lowest indices were obtained from the treatment of a mixture of both fungal and bacterial isolates. Fourier transform infrared (FT-IR), x-ray diffraction (XRD), and scanning electron microscopy (SEM) analyses showed that the selected isolates modified and colonized preoxidized pure LDPE films without pro-oxidant additives.

In this study, two strains of 'Aspergillus' sp. and 'Lysinibacillus' sp. with remarkable abilities to degrade low-density polyethylene (LDPE) were isolated from landfill soils in Tehran using enrichment culture and screening procedures. The biodegradation process was performed for 126 days in soil using UV- and non-UV-irradiated pure LDPE films without pro-oxidant additives in the presence and absence of mixed cultures of selected microorganisms. The process was monitored by measuring the microbial population, the biomass carbon, pH and respiration in the soil, and the mechanical properties of the films. The carbon dioxide measurements in the soil showed that the biodegradation in the un-inoculated treatments were slow and were about 7.6% and 8.6% of the mineralisation measured for the non-UV-irradiated and UV-irradiated LDPE, respectively, after 126 days. In contrast, in the presence of the selected microorganisms, biodegradation was much more efficient and the percentages of biodegradation were 29.5% and 15.8% for the UV-irradiated and non-UV-irradiated films, respectively. The percentage decrease in the carbonyl index was higher for the UV-irradiated LDPE when the biodegradation was performed in soil inoculated with the selected microorganisms. The percentage elongation of the films decreased during the biodegradation process. The Fourier transform infra-red (FT-IR), x-ray diffraction (XRD) and scanning electron microscopy (SEM) were used to determine structural, morphological and surface changes on polyethylene. These analyses showed that the selected microorganisms could modify and colonise both types of polyethylene. This study also confirmed the ability of these isolates to utilise virgin polyethylene without pro-oxidant additives and oxidation pretreatment, as the carbon source.

'Aim': To model the areas becoming and remaining highly suitable for 'Aspergillus niger' growth over the next ninety years by future climate alteration, in relation to the species' potential enhancement of Low Density Polyethylene (LDPE) biodegradation in soil. 'Location': Global scale 'Methods': Projections of 'A. niger' growth suitability for 2030, 2050, 2070 and 2100 were made using the A2 emissions scenario together with two Global Climate Models (GCMs): the CSIRO-Mk3.0 (CS) model and the MIROC-H (MR) model through CLIMEX software. Subsequently the outputs of the two GCMs were overlaid to extract common areas in each period of time, providing higher certainty concerning areas which will become highly suitable to 'A. niger' in the future. Afterwards, GIS software was employed to extract sustainable regions for this species growth from present time up to 2100. 'Results': Central and eastern Argentina, Uruguay, southern Brazil, eastern United States, southern France, northern Spain, central and southern Italy, southern Hungary, eastern Albania, south western Russia, central and eastern China, eastern Australia, south east of South Africa, central Zambia, Rwanda, Burundi, central Kenya, central Ethiopia and north eastern Oman will be highly suitable for 'A. niger' growth from present time up to 2100. 'Main conclusions': Accurately evaluating the impact of landfilling on land use and predicting future climate are vital components for effective long-term planning of waste management. From a social and economic perspective, utilization of our mapped projections to detect suitable regions for establishing landfills in areas highly sustainable for microorganisms like 'A. niger' growth will allow a significant cost reduction and improve the performance of biodegradation of LDPE over a long period of time, through making use of natural climatic and environmental factors.

The levels of inaccuracy in projections of global climate model outputs can be reduced by identification of the correlations between the output results of a number of models, which include common assumptions. Some of the invasive pathogen of 'Fusarium oxysporum' f. spp. pose risks to a number of cash crops such as banana, tomato, palm and garlic while some have a symbiotic relation varying from pathogenic to commensal (null effect), up to beneficial effect. Limitation of occurrence records of many single species such as 'F. oxysporum' f. sp. 'cubense', 'F. oxysporum' f. sp. 'albedinis', 'F. oxysporum' f. sp. 'lycopersici' and 'F. 'oxysporum' f. sp. 'vasinfectum' necessitated this study to model the future distribution of 'F. oxysporum' f. spp. rather than individual species. The future distribution of 'F. oxysporum' f. spp. was modeled by CSIRO-Mk3.0 (CS) and MIROC-H (MR) GCMs, and the results were correlated to identify areas suitable for 'F. oxysporum' f. spp. growth for North Africa, Middle Eastern and European countries for the years 2050 and 2100. The projections established that a number of countries will become highly conducive to this fungus, while others are projected to produce marginal levels of conduciveness by 2050 and 2100. We also demonstrate that refining CLIMEX outputs with a combination of a number of alternative GCMs results ensures that modeled projections become more robust, rather than producing purely hypothetical findings.

Invasive weed species (IWS) threaten ecosystems, the distribution of specific plant species, as well as agricultural productivity. Predicting the impact of climate change on the current and future distributions of these unwanted species forms an important category of ecological research. Our study investigated 32 globally important IWS to assess whether climate alteration may lead to spatial changes in the overlapping of specific IWS globally. We utilized the versatile species distribution model MaxEnt, coupled with Geographic Information Systems, to evaluate the potential alterations (gain/loss/static) in the number of potential ecoregion invasions by IWS, under four Representative Concentration Pathways, which differ in terms of predicted year of peak greenhouse gas emission. We based our projection on a forecast of climatic variables (extracted from WorldClim) from two global circulation models (CCSM4 and MIROC-ESM). Initially, we modeled current climatic suitability of habitat, individually for each of the 32 IWS, identifying those with a common spatial range of suitability. Thereafter, we modeled the suitability of all 32 species under the projected climate for 2050, incorporating each of the four Representative Concentration Pathways (2.6, 4.5, 6.0, and 8.5) in separate models, again examining the common spatial overlaps. The discrimination capacity and accuracy of the model were assessed for all 32 IWS individually, using the area under the curve and true skill statistic rate, with results averaging 0.87 and 0.75 respectively, indicating a high level of accuracy. Our final methodological step compared the extent of the overlaps and alterations under the current and future projected climates. Our results mainly predicted decrease on a global scale, in areas of habitat suitable for most IWS, under future climatic conditions, excluding European countries, northern Brazil, eastern US, and south-eastern Australia. The following should be considered when interpreting these results: there are many inherent assumptions and limitations in presence-only data of this type, as well as with the modeling techniques projecting climate conditions, and the envelopes themselves, such as scale and resolution mismatches, dispersal barriers, lack of documentation on potential disturbances, and unknown or unforeseen biotic interactions.

Analyses of knowledge gaps can highlight imbalances in research, encouraging greater proportionality in the distribution of research efforts. In this research we used generalized linear mixed models (GLMM) with the aim to determine if research efforts for the period 2005–2015 for terrestrial vertebrates of Amphibia, Aves, Mammalia and Reptilia in the South Pacific region were correlated with conservation status (critically endangered (CR), endangered (EN), vulnerable (VU), least concern (LC) and near threatened (NT)) or population trends (increasing, stable, decreasing and unknown) through the International Union for Conservation of Nature (IUCN) database. Our results showed that research distribution was uneven across different classes. Out of 633623 investigated papers, the average number of publications per species was 43.7, 306.7, 717.6 and 115.3 for Amphibia (284 species), Aves (1306 species), Mammalia (243 species) and Reptilia (400 species), respectively. Consistently, the lower publication effort on Amphibia compared to other taxonomic classes was revealed as significant by GLMM analysis. There was no significant differences in research effort among levels of conservation status. However, we found significantly different publication efforts among population trends of all examined species in that species with "unknown" population trends gained significantly lower researchers' attention compared to species with "decreasing" trend. Results also indicated that, although it was not significant, the highest attention is given to species with "increasing" population trend over all taxonomic classes. Using the Information Theoretic approach we also generated a set of competing models to identify most important factors influencing research efforts, revealing that the highest ranked model included taxonomic class and population.

In the Universal Soil Loss Equation (USLE), the soil erodibility factor ('K') corresponds to the collective effects of the detachment susceptibility of soil and the sediment transportability as well as the amount and rate of runoff under a given rainfall erosivity. Based on the USLE equation, 'K' is sensitive to the particle size distribution ('M'), the percentage of organic matter (%'OM'), soil structure ('Z'), and soil permeability ('perm'). This study evaluated the sensitivity of 'K' to lime content (%'lime') in the soil and slope (%'slope') of the site. Although the effects of the slope factor ('S') on the amount of soil loss ('A') have been independently taken into account in the USLE, our results and other studies showed that 'K' is highly sensitive to other factors including %'lime' and %'slope'. To evaluate the appropriateness of the USLE nomograph and other methods for estimating 'K' and to develop a 'K' estimation method for limy soils, a set of 'K' values were measured in northern Iran using standard plots and natural precipitation events, for four different land uses (forest, rangeland, irrigated farming, and dry farming) and three slope categories (3-8%, 8-18% and 18-40%). Results indicated that there was considerable association between 'K' and soil properties including the contents of sand, silt, very fine sand, organic matter and particularly lime, as well as slope inclination. A strong linear relationship was observed between the 'K' values estimated from our model and the measured 'K' was observed (adjusted 'R'² = 0.89), indicating that considering lime and slope gives a better estimate of 'K'.