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Dryland ecosystems cover nearly 45% of the Earth’s land area and account for large proportions of terrestrial net primary production and carbon pools. However, predicting rates of plant litter decomposition in these vast ecosystems has proven challenging due to their distinctly dry and often hot climate regimes, and potentially unique physical drivers of decomposition. In this study, we elucidated the role of photopriming, i.e. exposure of standing dead leaf litter to solar radiation prior to litter drop that would chemically change litter and enhance biotic decay of fallen litter. We exposed litter substrates to three different UV radiation treatments simulating three-months of UV radiation exposure in southern New Mexico: no light, UVA+UVB+Visible, and UVA+Visible. There were three litter types: mesquite leaflets (Prosopis glandulosa, litter with high nitrogen (N) concentration), filter paper (pure cellulose), and basswood (Tilia spp, high lignin concentration). We deployed the photoprimed litter in the field within a large scale precipitation manipulation experiment: ∼50% precipitation reduction, ∼150% precipitation addition, and ambient control. Our results revealed the importance of litter substrate, particularly N content, for overall decomposition in drylands, as neither filter paper nor basswood exhibited measurable mass loss over the course of the year-long study, while high N-containing mesquite litter exhibited potential mass loss. We saw no effect of photopriming on subsequent microbial decay. We did observe a precipitation effect on mesquite where the rate of decay was more rapid in ambient and precipitation addition treatments than in the drought treatment. Overall, we found that precipitation and N played a critical role in litter mass loss. In contrast, photopriming had no detected effects on mass loss over the course of our year-long study. These results underpin the importance of biotic-driven decomposition, even in the presence of photopriming, for understanding litter decomposition and biogeochemical cycles in drylands. [ABSTRACT FROM AUTHOR]

This paper investigates the consequences of ignoring the clustered data structure on allometric models. Clustered data, in the form of multiple trees sampled from multiple forest stands is commonly used to develop biomass allometric models. Of 102 reviewed papers published between 2012 and 2016 that reported biomass allometric models, 84 (82%) have used a clustered sampling design. However, in as many as 80% of these, the clustered data structure was ignored, potentially violating the independence assumption in ordinary least squares methods. The consequences of ignoring clustered data structure were empirically validated using two clustered biomass datasets (of 110 and 220 trees, with the cluster size of 5 and 10 trees respectively). We showed that when Intraclass Correlation Coefficient (ICC) was higher than zero, ignoring the clustered data structure returned underestimated standard errors, affecting further the confidence interval and t-test results. The underestimation level depended on ICC (which shows the variance proportion that was caused by the forest stand) and on cluster size (the number of trees sampled from one forest stand). We also showed that using first-order autocorrelation tests, such as the traditional Durbin-Watson statistic, to detect the autocorrelation due to clustered structure could be misleading as the test may show lack of autocorrelation even though ICC is different from zero. In conclusion, when ICC is higher than zero, ignoring the clustered data structure yields over-confident biomass predictions (due to underestimated confidence interval) and/or incorrect research conclusions (due to overestimated evidence against null hypothesis in t-test). Therefore, using a modelling approach that accounts for the hierarchical structure of the data is highly recommended when any form of clustering can be identified, even if the autocorrelation is not significant. [ABSTRACT FROM AUTHOR]

This paper presents an integrated hybrid optimization algorithm for training the radial basis function neural network (RBF NN). Training of neural networks is still a challenging exercise in machine learning domain. Traditional training algorithms in general suffer and trap in local optima and lead to premature convergence, which makes them ineffective when applied for datasets with diverse features. Training algorithms based on evolutionary computations are becoming popular due to their robust nature in overcoming the drawbacks of the traditional algorithms. Accordingly, this paper proposes a hybrid training procedure with differential search (DS) algorithm functionally integrated with the particle swarm optimization (PSO). To surmount the local trapping of the search procedure, a new population initialization scheme is proposed using Logistic chaotic sequence, which enhances the population diversity and aid the search capability. To demonstrate the effectiveness of the proposed RBF hybrid training algorithm, experimental analysis on publicly available 7 benchmark datasets are performed. Subsequently, experiments were conducted on a practical application case for wind speed prediction to expound the superiority of the proposed RBF training algorithm in terms of prediction accuracy. [ABSTRACT FROM AUTHOR]

Regulating ecosystem services provided by urban forests are of great importance for the quality of life among city dwellers. To reach a maximum contribution to well-being in cities, the urban regulating ecosystem services (URES) must match with the demands in terms of space and time. If we understand the matches or mismatches between the current urban dwellers’ desired quality conditions (demand) and the supply of URES by urban forests (UF) in the cities, this will facilitate integrating the concepts of ecosystem services in urban planning and management, but such an assessment has suffered from major knowledge limitations. Since it is complex and problematic to identify the direct demands for URES and the spatiotemporal patterns therein, improving the demand indicators can help to determine the actual requirements. In this paper, a methodological approach based on indicators is presented and demonstrated for two important URES: air quality improvement and global climate change mitigation provided by urban trees and shrubs. Four air quality standards and greenhouse gas reduction targets were used and compared to supplies of the URES in Tabriz, Iran. Our results show that the mean contribution of the URES supply to air quality standards and greenhouse gas reduction targets is modest. Hence, in Tabriz, there is a strong mismatch between demand and supply. Mismatches at the city scale will have to be reduced by both a reduction in pollutant emissions and an increased provisioning of URES supply through urban greenery. The presented assessment approach and the results for Tabriz make it explicit how different the demands and supplies of the two studied URES are, and we expect similar mismatches in many other cities. Therefore, our approach, relatively simple but still realistic and easy-to-apply, can raise awareness about, and the utility of, the ecosystem services concepts for urban planning and policymaking. [ABSTRACT FROM AUTHOR]

This paper studies the heterogeneous effects of exchange rate and stock market on carbon emission allowance price in four emissions trading scheme pilots in China. We employ a panel quantile regression model, which can describe both individual and distributional heterogeneity. The empirical results illustrate that the effects of explanatory variables on carbon emission allowance price is heterogeneous along the whole quantiles. Specifically, exchange rate has a negative effect on carbon emission allowance price at lower quantiles, while becomes a positive effect at higher quantiles. In addition, a negative effect exists between domestic stock market and carbon emission allowance price, and the intensity decreasing along with the increase of quantile. By contrast, an increasing positive effect is discovered between European stock market and domestic carbon emission allowance prices. Finally, heterogeneous effects on carbon emission allowance price can also be proved in European Union Emission Trading Scheme (EU-ETS). [ABSTRACT FROM AUTHOR]

Introduction: In connection to food insecurity, adaptation of new techniques or alteration of regular behavior is executed that translates to coping strategies. This paper has used data from food security and nutrition surveillance project (FSNSP), which collects information from a nationally representative sample in Bangladesh on coping behaviors associated with household food insecurity. To complement the current understanding of different coping strategies implemented by the Bangladeshi households, the objective of this paper has been set to examine the demographic and socio-economic characteristics of the food insecure households which define their propensity towards adaptation of different types of coping strategies. Methodology: FSNSP follows a repeated cross-sectional survey design. Information of 23,374 food insecure households available from February 2011 to November 2013 was selected for the analyses. Coping strategies were categorized as financial, food compromised and both. Multinomial logistic regression was employed to draw inference. Results: Majority of the households were significantly more inclined to adopt both multiple financial and food compromisation coping strategies. Post-aman season, educational status of the household head and household women, occupation of the household’s main earner, household income, food insecurity status, asset, size and possession of agricultural land were found to be independently and significantly associated with adaptation of both financial and food compromisation coping strategies relative to only financial coping strategies. The relative risk ratio of adopting food compromisation coping relative to financial coping strategies when compared to mildly food insecure households, was 4.54 times higher for households with moderate food insecurity but 0.3 times lower when the households were severely food insecure. Whereas, households were 8.04 times and 4.98 times more likely to adopt both food compromisation and financial relative to only financial coping strategies if moderately and severely food insecure respectively when compared to being mildly food insecure. Conclusion: Households suffering from moderate and severe food insecurity, are more likely to adopt both financial and food compromisation coping strategies. [ABSTRACT FROM AUTHOR]

Plant cell walls development is an integrated process during which several components are deposited successively. In the cell walls in grass, the accessibility of structural polysaccharides is limited by the cell walls structure and composition mainly as a result of phenolic compounds. Here, we studied the patterns of cell walls establishment in the internode supporting the ear in three distinct maize genotypes. The developmental patterns observed in the internode cell walls in terms of its composition are reported with an emphasis on lignification, p-coumaroylation and feruloylation. We combined biochemical and histological approaches and revealed that internode cell walls development in maize before flowering is characterized by the rapid deposition of secondary cell walls components and robust lignification in both the pith and the rind. After flowering and until silage maturity, the slow deposition of secondary walls components occurs in the cortical region, and the deposited lignins are rich in β-O-4 bonds and are highly p-coumaroylated. We conclude the paper by proposing a revised spatiotemporal model based on that proposed by Terashima et al. (1993) for cell walls development in grass. [ABSTRACT FROM AUTHOR]

This paper investigates how former hunter-gatherers living along the southern North Sea coast in NW Europe adapted to long-term and short-term climatic and environmental changes at the beginning of the Holocene. It is argued that contemporaneous hunter-gatherers repeatedly changed their hunting equipment in response to changing climate and environment, not just for functional reasons but mainly driven by socio-territorial considerations. Based on a Bayesian analysis of 122 critically selected radiocarbon dates a broad chronological correlation is demonstrated between rapid changes in the design and technology of stone projectiles and short but abrupt cooling events, occurring at 10.3, 9.3 and 8.2 ka cal BP. Combined with the rapid sea level rises and increased wildfires these climatic events probably impacted the lifeways of hunter-gatherers in such a way that they increasingly faced resource stress and competition, forcing them to invest in the symbolic defense of their social territories. [ABSTRACT FROM AUTHOR]

Compared with the idealized isotropic coal seam, the effectively cracking distances of deep-hole pre-splitting blasting in different directions have significant difference in the structural anisotropy of coal seam. In this paper, based on the test results of coal mechanical parameters in different coring directions, the blasting crack distances in these coring directions of coal seam are theoretically calculated and analyzed, and then a new method of blasthole layout in coal seam is designed and the blasting crack effect is investigated according to the test data of gas drainage. The research results show that both compressive strength and tensile strength of the direction of perpendicular to bedding are larger than that in other directions, especially parallel to bedding. The blasting crack distances of calculation results are in great agreement with that of underground in-situ measurement, so the blasting crack zone caused by the differences of mechanical properties in different directions can be approximately treated as an ellipse. Comparing the conventional method of blasthole layout, the blasting crack effect with new method has greatly enhanced the methane concentration and gas drainage quantity. Pure methane quantities with the new method and conventional method are about 2.8 times and 1.67 times as large as that before blasting, and pure methane quantity with the new method is about 1.46 times that with the conventional method. Therefore, considering the anisotropic characteristics of coal seams, the reasonable blasthole layout plays an important role for enhancing gas drainage in low permeability and outburst working face. [ABSTRACT FROM AUTHOR]

Understanding the causality between energy consumption, carbon emissions and economic growth is helpful for policymakers to formulate energy, environmental and economic policies. For the first time, based on nonlinear dynamics, this paper employs multispatial convergent cross mapping (CCM) to revisit the energy-carbon-economy causation for China, India and the G7 countries using both aggregate data and per capita data. The findings indicate that there are significant differences between developing countries and developed countries. A bidirectional nexus between energy consumption, carbon emissions and economic growth is found in China and India, but various causal relationships are identified in the G7 countries, including bidirectional, unidirectional and neutral nexus. The results confirm that the decoupling phenomenon is common in most G7 countries. By leveraging a variety of samples and a new approach, this study provides new evidence for policy authorities to formulate country-specific policies to obtain better environmental quality while achieving sustainable economic growth. [ABSTRACT FROM AUTHOR]

This paper aims to develop a novel computational technique for the detection of the transit through the anaerobic threshold. This technique uses only cardiac intervals derived from the electrocardiogram and is based on algebraic relationships between RR and QRS intervals. Electrocardiograms are measured during the load and the recovery processes. Algebraic relationships between cardiac intervals are used not only to identify the anaerobic threshold but also to characterise individual features of the person during the transit through the threshold. The ratio between carbon dioxide and oxygen in the exhaled air is used to validate the results. The algebraic relationship between cardiac intervals serves as a stand-alone indicator for both the determination of the anaerobic threshold and the characterization of the performance of the person during the load and the recovery processes. [ABSTRACT FROM AUTHOR]

The production of concrete for construction purposes is a major source of anthropogenic CO2 emissions. One promising avenue towards a more sustainable construction industry is to make use of naturally occurring mineral-microbe interactions, such as microbial-induced carbonate precipitation (MICP), to produce solid materials. In this paper, we present a new process where calcium carbonate in the form of powdered limestone is transformed to a binder material (termed BioZEment) through microbial dissolution and recrystallization. For the dissolution step, a suitable bacterial strain, closely related to Bacillus pumilus, was isolated from soil near a limestone quarry. We show that this strain produces organic acids from glucose, inducing the dissolution of calcium carbonate in an aqueous slurry of powdered limestone. In the second step, the dissolved limestone solution is used as the calcium source for MICP in sand packed syringe moulds. The amounts of acid produced and calcium carbonate dissolved are shown to depend on the amount of available oxygen as well as the degree of mixing. Precipitation is induced through the pH increase caused by the hydrolysis of urea, mediated by the enzyme urease, which is produced in situ by the bacterium Sporosarcina pasteurii DSM33. The degree of successful consolidation of sand by BioZEment was found to depend on both the amount of urea and the amount of glucose available in the dissolution reaction. [ABSTRACT FROM AUTHOR]

The fragile ecological environment near mines provide advantageous conditions for the development of landslides. Mine landslide susceptibility mapping is of great importance for mine geo-environment control and restoration planning. In this paper, a total of 493 landslides in Shangli County, China were collected through historical landslide inventory. 16 spectral, geomorphic and hydrological predictive factors, mainly derived from Landsat 8 imagery and Global Digital Elevation Model (ASTER GDEM), were prepared initially for landslide susceptibility assessment. Predictive capability of these factors was evaluated by using the value of variance inflation factor and information gain ratio. Three models, namely artificial neural network (ANN), support vector machine (SVM) and information value model (IVM), were applied to assess the mine landslide sensitivity. The receiver operating characteristic curve (ROC) and rank probability score were used to validate and compare the comprehensive predictive capabilities of three models involving uncertainty. Results showed that ANN model achieved higher prediction capability, proving its advantage of solve nonlinear and complex problems. Comparing the estimated landslide susceptibility map with the ground-truth one, the high-prone area tends to be located in the middle area with multiple fault distributions and the steeply sloped hill. [ABSTRACT FROM AUTHOR]

When assessing the short-term effect of air pollution on health outcomes, it is common practice to consider one pollutant at a time, due to their high correlation. Multi pollutant methods have been recently proposed, mainly consisting of collapsing the different pollutants into air quality indexes or clustering the pollutants and then evaluating the effect of each cluster on the health outcome. A major drawback of such approaches is that it is not possible to evaluate the health impact of each pollutant. In this paper we propose the use of the Bayesian hierarchical framework to deal with multi pollutant concentrations in a two-component model: a pollutant model is specified to estimate the ‘true’ concentration values for each pollutant and then such concentration is linked to the health outcomes in a time-series perspective. Through a simulation study we evaluate the model performance and we apply the modelling framework to investigate the effect of six pollutants on cardiovascular mortality in Greater London in 2011-2012. [ABSTRACT FROM AUTHOR]

The data collected by mobile methane (CH4) sensors can be used to find natural gas (NG) leaks in urban distribution systems. Extracting actionable insights from the large volumes of data collected by these sensors requires several data processing steps. While these survey platforms are commercially available, the associated data processing software largely constitute a black box due to their proprietary nature. In this paper we describe a step-by-step algorithm for developing leak indications using data from mobile CH4 surveys, providing an under-the-hood look at the choices and challenges associated with data analysis. We also describe how our algorithm has evolved over time, and the data-driven insights that have prompted these changes. Applying our algorithm to data collected in 15 cities produced more than 6100 leak indications and estimates of the leaks’ size. We use these results to characterize the distribution of leak sizes in local NG distribution systems. Mobile surveys are already an effective and necessary tool for managing NG distribution systems, but improvements in the technology and software will continue to increase its value. [ABSTRACT FROM AUTHOR]

This paper examines search and rescue and backcountry medical response constraints in the Canadian Arctic and potential for unmanned aerial vehicles (UAV) to aid in response and preparedness. Semi-structured interviews (n = 18) were conducted with search and rescue responders, Elders, and emergency management officials to collect data on current emergency response and potential for UAV use. UAV test flights (n = 17) were undertaken with community members. We analyzed five years of weather data to examine UAV flight suitability. Numerous challenges face Arctic search and rescue and backcountry emergency response. Changing social and environmental conditions were described as increasing vulnerability to backcountry emergencies. Responders desired additional first aid and emergency training. Legal and weather restrictions were found to limit where, when and who could fly UAVs. UAVs were demonstrated to have potential benefits for hazard monitoring but not for SAR or medical response due to legal restrictions, weather margins, and local capacity. We find that communities are ill-prepared for ongoing SAR demands, let alone a larger disaster. There are numerous limitations to the use of consumer UAVs by Arctic communities. Prevention of backcountry medical emergencies, building resilience to disasters, and first responder training should be prioritized over introducing UAVs to the response system. [ABSTRACT FROM AUTHOR]

While the 2016 Paris Agreement is in many ways an important attainment with the potential to represent a milestone in humanity’s path towards sustainable development, and avoid thus a potential calamitous and destructive future, the achievement of the goals set in the agreement is a long way off. This paper investigates one of the most important worldwide hurdles frustrating the implementation of the policies required to limit environmental degradation and limit pollution, namely the still insufficient public support for the necessary environmental policies and their associated cost. Using a comparative database generated through an experimental study on tax compliance and policy preferences run in five countries (USA, UK, Italy, Sweden and Romania), I will evaluate five explanatory models of the degree to which people support environmentally friendly policies by accepting higher tax burdens and increased collective solidarity. [ABSTRACT FROM AUTHOR]

The multi-period (~38,000–6000 cal BP) site of Franchthi Cave, located in the Argolid peninsula of southern mainland Greece, is unique in the Eastern Mediterranean for preserving a long archaeological sequence extending from the Upper Palaeolithic through to the end of the Neolithic period. In this paper, we present new anthracological (carbonized fuel wood waste) evidence from Franchthi Cave with which we reconstruct the changing ecology of woodland vegetation in its environs during the late Pleistocene and the early-mid Holocene. The integrated archaeobotanical record (charred wood and non-wood macro-remains) demonstrates that in the Lateglacial the now-submerged coastal shelf of the southern Argolid peninsula was covered by steppe grassland vegetation dominated by junipers, almonds, cereals and legumes. The rapid climatic amelioration that marked the start of the Holocene brought about the disappearance of juniper and the expansion of deciduous woodland, cereals and lentils. This woodland-grassland biome bears no analogues in the modern and historical vegetation ecology of the Aegean basin. Instead, it is directly comparable to the steppe woodland biomes exploited by late Pleistocene and early Holocene hunter-gatherers in Southwest Asia, and points to the convergent evolution of late Pleistocene and early Holocene plant exploitation strategies between the two regions. Continuous sea-level rise during the early Holocene led to the gradual extinction of this unique palaeohabitat, which acted as the catalyst for the selective introduction of domesticated cereal crops at Franchthi Cave in the early 9th millennium cal BP. Our meta-analysis of the non-wood archaeobotanical data puts into question the concept of the wholesale introduction of a crop “package” by pioneer settler groups arriving from the East. It is proposed instead that selective cereal crop introduction formed part of a complex pattern of sociocultural interactions that brought together indigenous and immigrant groups into new communities. [ABSTRACT FROM AUTHOR]

The energy consumption-growth nexus has been widely studied in the empirical literature, though results have been inconclusive regarding the direction, or even the existence, of causality. These inconsistent results can be explained by two important limitations of the literature. First, the use of bivariate models, which fail to detect more complex causal relations, or the ad hoc approach to selecting variables in a multivariate framework; and, second, the use of linear causal models, which are unable to capture more complex nonlinear causal relationships. In this paper, we aim to overcome both limitations by analysing the energy consumption-growth nexus using a Flexible Fourier form due to Enders and Jones (2016). The analysis focuses on the US over the period 1949 to 2014. From our results we can conclude that, where the linear methodology supports the neutrality hypothesis (no causality between energy consumption and growth), the Flexible Fourier form points to the existence of causality from energy consumption to growth. This is contrary to the linear analysis, suggesting that lowering energy consumption would adversely affect US economic growth. Thus, by employing the Flexible Fourier form we find the conclusions can be quite different. [ABSTRACT FROM AUTHOR]

Power demands are set to increase by two-fold within the current century and a high fraction of that demand should be met by carbon free sources. Among the renewable energies, solar energy is among the fastest growing; therefore, a comprehensive and accurate design methodology for solar systems and how they interact with the local environment is vital. This paper addresses the environmental effects of solar panels on an unirrigated pasture that often experiences water stress. Changes to the microclimatology, soil moisture, water usage, and biomass productivity due to the presence of solar panels were quantified. The goal of this study was to show that the impacts of these factors should be considered in designing the solar farms to take advantage of potential net gains in agricultural and power production. Microclimatological stations were placed in the Rabbit Hills agrivoltaic solar arrays, located in Oregon State campus, two years after the solar array was installed. Soil moisture was quantified using neutron probe readings. Significant differences in mean air temperature, relative humidity, wind speed, wind direction, and soil moisture were observed. Areas under PV solar panels maintained higher soil moisture throughout the period of observation. A significant increase in late season biomass was also observed for areas under the PV panels (90% more biomass), and areas under PV panels were significantly more water efficient (328% more efficient). [ABSTRACT FROM AUTHOR]

Maintaining crop outputs to feed its large population with limited resources while simultaneously mitigating carbon emissions are great challenges for China. Improving the efficiency of resource use in crop production is important in reducing carbon emissions. This paper constructs a methodological framework combining emergy-based indicator accounting and a nonseparable undesirable output slack-based measurement (SBM) data envelopment analysis (DEA) model. This framework is used to explore the efficiency of inputs and outputs and the greenhouse gas (GHG) emissions reduction potential for crop production systems, using Zhejiang province, China, as a case study. It is found that an emergy synthesis and a nonseparable undesirable output SBM-DEA framework is compatible with the case study. Crop production in Zhejiang province has relied heavily on an increase in agrochemical inputs to maintain agricultural output. Energy and chemical fertilizer use are determined as the province’s major carbon emissions sources. Although carbon emissions per unit of monetary output has decreased sharply, the carbon emissions per unit emergy output has increased, demonstrating a high carbon intensity reality. The DEA highlighted the differences in crop production efficiency, resource factor redundancy and carbon mitigation potential in the different prefectures of the province. To conclude this research, policies to support low carbon agriculture development, including subsidizing low carbon agriculture technology development and expansion and the cancellation of subsidies to high carbon production factors, such as chemical fertilizer production and sales, are discussed to conclude the research. [ABSTRACT FROM AUTHOR]

This paper presents preliminary results about Turin’s air quality before, during and after the realization of the infrastructure projects for the Turin 2006 XX Winter Olympic Games. We compared the 3-year in-operam (work in progress) period (i.e. 2003–2005, when all infrastructures needed for the organization were built) with the periods before (ante-operam) and after (post-operam): 2000–2002 and 2006–2008, respectively. In particular, we analyzed the concentrations of the primary pollutants (nitrogen dioxide, carbon monoxide and fine particulate matter, PM10) in Turin and Milan. In this way, we could use the measurements from Milan as a control dataset for comparison with the atmospheric pollution conditions in Turin. We found that infrastructural work for the Olympic Games in Turin affected NO2 and PM10 atmospheric concentrations, determining a peak in the average values during the in-operam period (probably due to caterpillar tractor emissions and excavation). This pattern did not emerge from the Milan data, where a decreasing trend can be seen between the ante-operam and the post-operam periods. On the other hand, a negative effect on CO levels was not observed: the decreasing trend, more evident in Turin compared to Milan, can be linked to the expansion during the same period of limited traffic areas created to facilitate the infrastructural work. [ABSTRACT FROM AUTHOR]

Background: Climate change is affecting food systems globally, with implications for food security, nutrition, and the health of human populations. There are limited data characterizing the current and future consequences of climate change on local food security for populations already experiencing poor nutritional indicators. Indigenous Amazonian populations have a high reported prevalence of nutritional deficiencies. This paper characterizes the food system of the Shawi of the Peruvian Amazon, climatic and non-climatic drivers of their food security vulnerability to climate change, and identifies potential maladaptation trajectories. Methods and findings: Semi-structured interviews with key informants (n = 24), three photovoice workshops (n = 17 individuals), transect walks (n = 2), a food calendar exercise, and two community dissemination meetings (n = 30 individuals), were conducted within two Shawi communities in Balsapuerto District in the Peruvian Loreto region between June and September of 2014. The Shawi food system was based on three main food sub-systems (forest, farming and externally-sourced). Shawi reported collective, gendered, and emotional notions related to their food system activities. Climatic and non-climatic drivers of food security vulnerability among Shawi participants acted at proximal and distal levels, and mutually reinforced key maladaptation trajectories, including: 1) a growing population and natural resource degradation coupled with limited opportunities to increase incomes, and 2) a desire for education and deforestation reinforced by governmental social and food interventions. Conclusion: A series of maladaptive trajectories have the potential to increase social and nutritional inequities for the Shawi. Transformational food security adaptation should include consideration of Indigenous perceptions and priorities, and should be part of Peruvian food and socioeconomic development policies. [ABSTRACT FROM AUTHOR]

This paper demonstrates the impact of an endemic fossorial animal, plateau pika (Ochotona curzoniae), on soil properties and N2O flux at the Zoige Wetland. Pika burrow and control sites without disturbance by pika were selected to measure the soil water content, bulk density, soil organic matter (SOM), NH4-N content and NO3-N content in August 2012. N2O fluxes were measured with static opaque chambers at these sites in June and August 2012. Pika burrowing altered soil aeration by transferring deeper soil to the surface and by constructing underground burrows, which significantly increased bulk density, and reduced soil water content, SOM and NH4-N content at 0–10 cm and 10–20 cm soil depth. N2O flux had a significant correlation with bulk density, SOM and NH4-N content. Pika burrowing significantly influenced N2O flux by increasing N2O flux at the control site from near zero to 0.063±0.011 mg m-2 h-1. Our findings described how pika burrowing influences the soil traits and significantly increases the principal greenhouse gas N2O emission. As plateau pika was commonly considered as a pest, our findings give a novel clue to effectively manage populations of plateau pika on the Qinghai-Tibet Plateau from the perspective of greenhouse gas emission. [ABSTRACT FROM AUTHOR]

The body of science evaluating the potential impacts of unconventional natural gas development (UNGD) has grown significantly in recent years, although many data gaps remain. Still, a broad empirical understanding of the impacts is beginning to emerge amidst a swell of research. The present categorical assessment provides an overview of the peer-reviewed scientific literature from 2009–2015 as it relates to the potential impacts of UNGD on public health, water quality, and air quality. We have categorized all available original research during this time period in an attempt to understand the weight and direction of the scientific literature. Our results indicate that at least 685 papers have been published in peer-reviewed scientific journals that are relevant to assessing the impacts of UNGD. 84% of public health studies contain findings that indicate public health hazards, elevated risks, or adverse health outcomes; 69% of water quality studies contain findings that indicate potential, positive association, or actual incidence of water contamination; and 87% of air quality studies contain findings that indicate elevated air pollutant emissions and/or atmospheric concentrations. This paper demonstrates that the weight of the findings in the scientific literature indicates hazards and elevated risks to human health as well as possible adverse health outcomes associated with UNGD. There are limitations to this type of assessment and it is only intended to provide a snapshot of the scientific knowledge based on the available literature. However, this work can be used to identify themes that lie in or across studies, to prioritize future research, and to provide an empirical foundation for policy decisions. [ABSTRACT FROM AUTHOR]

One of the main manifestations of climate change will be increased rainfall variability. How to deal with this in agriculture will be a major societal challenge. In this paper we explore flexibility in land use, through deliberate seasonal adjustments in cropped area, as a specific strategy for coping with rainfall variability. Such adjustments are not incorporated in hydro-meteorological crop models commonly used for food security analyses. Our paper contributes to the literature by making a comprehensive model assessment of inter-annual variability in crop production, including both variations in crop yield and cropped area. The Ganges basin is used as a case study. First, we assessed the contribution of cropped area variability to overall variability in rice and wheat production by applying hierarchical partitioning on time-series of agricultural statistics. We then introduced cropped area as an endogenous decision variable in a hydro-economic optimization model (WaterWise), coupled to a hydrology-vegetation model (LPJmL), and analyzed to what extent its performance in the estimation of inter-annual variability in crop production improved. From the statistics, we found that in the period 1999–2009 seasonal adjustment in cropped area can explain almost 50% of variability in wheat production and 40% of variability in rice production in the Indian part of the Ganges basin. Our improved model was well capable of mimicking existing variability at different spatial aggregation levels, especially for wheat. The value of flexibility, i.e. the foregone costs of choosing not to crop in years when water is scarce, was quantified at 4% of gross margin of wheat in the Indian part of the Ganges basin and as high as 34% of gross margin of wheat in the drought-prone state of Rajasthan. We argue that flexibility in land use is an important coping strategy to rainfall variability in water stressed regions. [ABSTRACT FROM AUTHOR]

This paper presents the results of research into pathways leading to the production of methane (CH4) and carbon dioxide (CO2) in sediments of two eutrophic reservoirs (Maziarnia and Nielisz), located in south-eastern Poland. In seeking to identify the pathways in question, use was made of analysis of stable carbon isotopes in CH4 and CO2 dissolved in pore water. This determined that CH4 is mainly produced through acetate fermentation, though the hydrogenotrophic methanogenic process may also be of importance, especially in deeper layers of sediments. Both the presence of autochthonous organic matter and increased pH values are shown to favour acetate fermentation. In turn, methanogenesis in sediments is assessed as capable of accounting for the generation of a considerable amount of CO2. Indeed, the role of methanogenesis in CO2 production is increasingly important further down in the layers of sediment, where allochthonous organic matter is predominant. [ABSTRACT FROM AUTHOR]

Accurate reporting and forecasting of PM2.5 concentration are important for improving public health. In this paper, we propose a partial differential equation (PDE) model, specially, a linear diffusive equation, to describe the spatial-temporal characteristics of PM2.5 in order to make short-term prediction. We analyze the temporal and spatial patterns of a real dataset from China’s National Environmental Monitoring and validate the PDE-based model in terms of predicting the PM2.5 concentration of the next day by the former days’ history data. Our experiment results show that the PDE model is able to characterize and predict the process of PM2.5 transport. For example, for 300 continuous days of 2016, the average prediction accuracy of the PDE model over all city-regions is 93% or 83% based on different accuracy definitions. To our knowledge, this is the first attempt to use PDE-based model to study PM2.5 prediction in both temporal and spatial dimensions. [ABSTRACT FROM AUTHOR]

Mitigating extreme heat in urban areas is beneficial and sometimes critical to human health. Thriving plant communities in community parks play an important role in mitigating extreme heat through providing cooling effect, while inevitably affecting how people perceive the benefits of using community parks for recreation. Thus, the impacts of plant communities on the thermal environment should be quantified to determine the optimal structure of the plant community. The goal would be to harmonize the functions of improving the thermal environment with the preferences people have related to the recreational benefits of plant communities with various levels of vegetation density. In this paper, the correlations between the structural characteristics of plant communities and their function in mitigating the thermal environment were investigated on calm summer days in Xincheng Central Park, Minhang District, Shanghai, China. In addition to analyzing the plant communities present and their effects on the park microclimate, a questionnaire was employed to determine the plant community preferences of recreational park users. The results showed that plant communities could reduce the air temperature by 1.23–2.42 °C and increase the relative humidity by 2.4–4.2% during the daytime. The microclimate conditions in plant communities with varying vegetation densities were significantly different. The canopy density and leaf area index primarily controlled the temperature reduction, while the canopy density and total canopy cover ratio primarily controlled the increase in humidity; meanwhile, these correlations varied at different times of the day. Moreover, most of the park users preferred a moderately dense plant community which met their environmental perceptions for recreation in parks. Age or education level variables of park users would also predict preferences for different plant community densities. Ultimately, one plant community pattern with appropriate canopy density (60%), leaf area index (≥3) and canopy cover ratio (total 0.80–1.20, with 0.6–0.75 for trees and 0.20–0.45 for shrubs/woodland area) was recommended, which would harmonize the functions of the mitigation of the thermal environment with most people’s perception of a desirable vegetation density. [ABSTRACT FROM AUTHOR]

In environmental epidemiology, it is often encountered that multiple time series data with a long-term trend, including seasonality, cannot be fully adjusted by the observed covariates. The long-term trend is difficult to separate from abnormal short-term signals of interest. This paper addresses how to estimate the long-term trend in order to recover short-term signals. Our case study demonstrates that the current spline smoothing methods can result in significant positive and negative cross-correlations from the same dataset, depending on how the smoothing parameters are chosen. To circumvent this dilemma, three classes of time series smoothers are proposed to detrend time series data. These smoothers do not require fine tuning of parameters and can be applied to recover short-term signals. The properties of these smoothers are shown with both a case study using a factorial design and a simulation study using datasets generated from the original dataset. General guidelines are provided on how to discover short-term signals from time series with a long-term trend. The benefit of this research is that a problem is identified and characteristics of possible solutions are determined. [ABSTRACT FROM AUTHOR]

The role of forest management in mitigating climate change is a central concern for the Canadian province of British Columbia. The successful implementation of forest management activities to achieve climate change mitigation in British Columbia will be strongly influenced by public support or opposition. While we now have increasingly clear ideas of the management opportunities associated with forest mitigation and some insight into public support for climate change mitigation in the context of sustainable forest management, very little is known with respect to the levels and basis of public support for potential forest management strategies to mitigate climate change. This paper, by describing the results of a web-based survey, documents levels of public support for the implementation of eight forest carbon mitigation strategies in British Columbia’s forest sector, and examines and quantifies the influence of the factors that shape this support. Overall, respondents ascribed a high level of importance to forest carbon mitigation and supported all of the eight proposed strategies, indicating that the British Columbia public is inclined to consider alternative practices in managing forests and wood products to mitigate climate change. That said, we found differences in levels of support for the mitigation strategies. In general, we found greater levels of support for a rehabilitation strategy (e.g. reforestation of unproductive forest land), and to a lesser extent for conservation strategies (e.g. old growth conservation, reduced harvest) over enhanced forest management strategies (e.g. improved harvesting and silvicultural techniques). We also highlighted multiple variables within the British Columbia population that appear to play a role in predicting levels of support for conservation and/or enhanced forest management strategies, including environmental values, risk perception, trust in groups of actors, prioritized objectives of forest management and socio-demographic factors. [ABSTRACT FROM AUTHOR]

Understanding Earth surface responses in terms of sediment dynamics to climatic variability and tectonics forcing is hindered by limited ability of current models to simulate long-term evolution of sediment transfer and associated morphological changes. This paper presents pyBadlands, an open-source python-based framework which computes over geological time (1) sediment transport from landmasses to coasts, (2) reworking of marine sediments by longshore currents and (3) development of coral reef systems. pyBadlands is cross-platform, distributed under the GPLv3 license and available on GitHub (). Here, we describe the underlying physical assumptions behind the simulated processes and the main options already available in the numerical framework. Along with the source code, a list of hands-on examples is provided that illustrates the model capabilities. In addition, pre and post-processing classes have been built and are accessible as a companion toolbox which comprises a series of workflows to efficiently build, quantify and explore simulation input and output files. While the framework has been primarily designed for research, its simplicity of use and portability makes it a great tool for teaching purposes. [ABSTRACT FROM AUTHOR]

Super-critical carbon dioxide energy-storage (SC-CCES) technology is a new type of gas energy-storage technology. This paper used orthogonal method and variance analysis to make significant analysis on the factors which would affect the thermodynamics characteristics of the SC-CCES system and obtained the significant factors and interactions in the energy-storage process, the energy-release process and the whole energy-storage system. Results have shown that the interactions in the components have little influence on the energy-storage process, the energy-release process and the whole energy-storage process of the SC-CCES system, the significant factors are mainly on the characteristics of the system component itself, which will provide reference for the optimization of the thermal properties of the energy-storage system. [ABSTRACT FROM AUTHOR]

The paper presents the results of an experiment on the effect of pre-sowing stimulation of seeds with atmospheric pressure plasma jet operating with dielectric barrier discharge (DBD plasma jet) on the process of germination of Thuringian Mallow (Lavatera thuringiaca L.). Five groups of seeds characterized by a different exposure times (1, 2, 5, 10 and 15 minutes) as well as untreated seeds—control were used. Pre-sowing plasma stimulation of seeds improved germination parameters such as: germination capacity and germination energy for all tested groups relative to control. The highest germination parameters were obtained for seeds stimulated with plasma for the exposure times of 2 and 5 min. The analysis of the contact surface angle indicated the decrease of its’ mean values upon seed stimulation while no statistical effects were observed. Analysis of the SEM scans revealed the increase in seed pattern intensity which could be attributed to removing of the surface parts of cuticle possibly covered with wax upon short time—2 and 5 min plasma treatment. Such a phenomenon can act similarly to mechanical scarification of seeds. Longer exposure of seeds to plasma resulted in affecting the deeper zone of cuticle and damage or fracture of some parts of the cuticle. Lower germination parameters of seeds upon longer exposure times to plasma may indicate mechanical damage of the seeds. [ABSTRACT FROM AUTHOR]

Local and indigenous knowledge is being transformed globally, particularly being eroded when pertaining to ecology. In many parts of the world, rural and indigenous communities are facing tremendous cultural, economic and environmental changes, which contribute to weaken their local knowledge base. In the face of profound and ongoing environmental changes, both cultural and biological diversity are likely to be severely impacted as well as local resilience capacities from this loss. In this global literature review, we analyse the drivers of various types of local and indigenous ecological knowledge transformation and assess the directionality of the reported change. Results of this analysis show a global impoverishment of local and indigenous knowledge with 77% of papers reporting the loss of knowledge driven by globalization, modernization, and market integration. The recording of this loss, however, is not symmetrical, with losses being recorded more strongly in medicinal and ethnobotanical knowledge. Persistence of knowledge (15% of the studies) occurred in studies where traditional practices were being maintained consiously and where hybrid knowledge was being produced as a resut of certain types of incentives created by economic development. This review provides some insights into local and indigenous ecological knowledge change, its causes and implications, and recommends venues for the development of replicable and comparative research. The larger implication of these results is that because of the interconnection between cultural and biological diversity, the loss of local and indigenous knowledge is likely to critically threaten effective conservation of biodiversity, particularly in community-based conservation local efforts. [ABSTRACT FROM AUTHOR]

Urbanization is a global process that has taken billions of people from the rural countryside to concentrated urban centers, adding pressure to existing water resources. Many cities are specifically reliant on renewable freshwater regularly refilled by precipitation, rather than fossil groundwater or desalination. A precipitationshed can be considered the “watershed of the sky” and identifies the origin of precipitation falling in a given region. In this paper, we use this concept to determine the sources of precipitation that supply renewable water in the watersheds of the largest cities of the world. We quantify the sources of precipitation for 29 megacities and analyze their differences between dry and wet years. Our results reveal that 19 of 29 megacities depend for more than a third of their water supply on evaporation from land. We also show that for many of the megacities, the terrestrial dependence is higher in dry years. This high dependence on terrestrial evaporation for their precipitation exposes these cities to potential land-use change that could reduce the evaporation that generates precipitation. Combining indicators of water stress, moisture recycling exposure, economic capacity, vegetation-regulated evaporation, land-use change, and dry-season moisture recycling sensitivity reveals four highly vulnerable megacities (Karachi, Shanghai, Wuhan, and Chongqing). A further six megacities were found to have medium vulnerability with regard to their water supply. We conclude that understanding how upwind landscapes affect downwind municipal water resources could be a key component for understanding the complexity of urban water security. [ABSTRACT FROM AUTHOR]

The selection of seismic attributes is a key process in reservoir prediction because the prediction accuracy relies on the reliability and credibility of the seismic attributes. However, effective selection method for useful seismic attributes is still a challenge. This paper presents a novel selection method of seismic attributes for reservoir prediction based on the gray relational degree (GRD) and support vector machine (SVM). The proposed method has a two-hierarchical structure. In the first hierarchy, the primary selection of seismic attributes is achieved by calculating the GRD between seismic attributes and reservoir parameters, and the GRD between the seismic attributes. The principle of the primary selection is that these seismic attributes with higher GRD to the reservoir parameters will have smaller GRD between themselves as compared to those with lower GRD to the reservoir parameters. Then the SVM is employed in the second hierarchy to perform an interactive error verification using training samples for the purpose of determining the final seismic attributes. A real-world case study was conducted to evaluate the proposed GRD-SVM method. Reliable seismic attributes were selected to predict the coalbed methane (CBM) content in southern Qinshui basin, China. In the analysis, the instantaneous amplitude, instantaneous bandwidth, instantaneous frequency, and minimum negative curvature were selected, and the predicted CBM content was fundamentally consistent with the measured CBM content. This real-world case study demonstrates that the proposed method is able to effectively select seismic attributes, and improve the prediction accuracy. Thus, the proposed GRD-SVM method can be used for the selection of seismic attributes in practice. [ABSTRACT FROM AUTHOR]

This paper offers new high-resolution oxygen and carbon isotope data from Stalagmite S1 from Mavri Trypa Cave, SW Peloponnese. Our data provide the climate background to the destruction of the nearby Mycenaean Palace of Nestor at Pylos at the transition from Late Helladic (LH) IIIB to LH IIIC, ~3150–3130 years before present (before AD 1950, hereafter yrs BP) and the subsequent period. S1 is dated by 24 U-Th dates with an averaged precision of ±26 yrs (2σ), providing one of the most robust paleoclimate records from the eastern Mediterranean for the end of the Late Bronze Age (LBA). The δ18O record shows generally wetter conditions at the time when the Palace of Nestor at Pylos was destroyed, but a brief period of drier conditions around 3200 yrs BP may have disrupted the Mycenaean agricultural system that at the time was likely operating close to its limit. Gradually developing aridity after 3150 yrs BP, i.e. subsequent to the destruction, probably reduced crop yields and helped to erode the basis for the reinstitution of a central authority and the Palace itself. [ABSTRACT FROM AUTHOR]

Coal mining is one of the core industries that contribute to the economic development of a country but deteriorate the environment. Being the primary source of energy, coal has become essential to meet the energy demand of a country. It is excavated by both opencast and underground mining methods and affects the environment, especially hydrological cycle, by discharging huge amounts of mine water. Natural hydrological processes have been well known to be vulnerable to human activities, especially large scale mining activities, which inevitably generate surface cracks and subsidence. It is therefore valuable to assess the impact of mining on river runoff for the sustainable development of regional economy. In this paper, the impact of coal mining on river runoff is assessed in one of the national key coal mining sites, Gujiao mining area, Shanxi Province, China. The characteristics of water cycle are described, the similarities and differences of runoff formation are analyzed in both coal mining and pre-mining periods. The integrated distributed hydrological model named MIKE SHE is employed to simulate and evaluate the influence of coal mining on river runoff. The study shows that mining one ton of raw coal leads to the reduction of river runoff by 2.87 m3 between 1981 and 2008, of which the surface runoff decreases by 0.24 m3 and the baseflow by 2.63 m3. The reduction degree of river runoff for mining one ton of raw coal shows an increasing trend over years. The current study also reveals that large scale coal mining initiates the formation of surface cracks and subsidence, which intercepts overland flow and enhances precipitation infiltration. Together with mine drainage, the natural hydrological processes and the stream flows have been altered and the river run off has been greatly reduced. [ABSTRACT FROM AUTHOR]

Over the 20th century, urbanization has substantially shaped the surface of Earth. With population rapidly shifting from rural locations towards the cities, urban areas have dramatically expanded on a global scale and represent crystallization points of social, cultural and economic assets and activities. This trend is estimated to persist for the next decades, and particularly the developing countries are expected to face rapid urban growth. The management of this growth will require good governance strategies and planning. By threatening the livelihoods, assets and health as foundations of human activities, another major global change contributor, climate change, became an equally important concern of stakeholders. Based on the climate trends observed over the 20th century, and a spatially explicit model of urbanization, this paper investigates the impacts of climate change in relation to different stages of development of urban areas, thus evolving a more integrated perspective on both processes. As a result, an integrative measure of climate change trends and impacts is proposed and estimated for urban areas worldwide. We show that those areas facing major urban growth are to a large extent also hotspots of climate change. Since most of these hotspots are located in the Global South, we emphasize the need for stakeholders to co-manage both drivers of global change. The presented integrative perspective is seen as a starting point to foster such co-management, and furthermore as a means to facilitate communication and knowledge exchange on climate change impacts. [ABSTRACT FROM AUTHOR]

Climate change and land use change are two major elements of human-induced global environmental change. In temperate grasslands and woodlands, increasing frequency of extreme weather events like droughts and increasing severity of wildfires has altered the structure and dynamics of vegetation. In this paper, we studied the impact of wildfires and the year-to-year differences in precipitation on species composition changes in semi-arid grasslands of a forest-steppe complex ecosystem which has been partially disturbed by wildfires. Particularly, we investigated both how long-term compositional dissimilarity changes and species richness are affected by year-to-year precipitation differences on burnt and unburnt areas. Study sites were located in central Hungary, in protected areas characterized by partially-burnt, juniper-poplar forest-steppe complexes of high biodiversity. Data were used from two long-term monitoring sites in the Kiskunság National Park, both characterized by the same habitat complex. We investigated the variation in species composition as a function of time using distance decay methodology. In each sampling area, compositional dissimilarity increased with the time elapsed between the sampling events, and species richness differences increased with increasing precipitation differences between consecutive years. We found that both the long-term compositional dissimilarity, and the year-to-year changes in species richness were higher in the burnt areas than in the unburnt ones. The long-term compositional dissimilarities were mostly caused by perennial species, while the year-to-year changes of species richness were driven by annual and biennial species. As the effect of the year-to-year variation in precipitation was more pronounced in the burnt areas, we conclude that canopy removal by wildfires and extreme inter-annual variability of precipitation, two components of global environmental change, act in a synergistic way. They enhance the effect of one another, resulting in greater long-term and year-to-year changes in the composition of grasslands. [ABSTRACT FROM AUTHOR]

Fluctuations in environmental parameters are increasingly being recognized as essential features of any habitat. The quantification of whether environmental fluctuations are prevalently predictable or unpredictable is remarkably relevant to understanding the evolutionary responses of organisms. However, when characterizing the relevant features of natural habitats, ecologists typically face two problems: (1) gathering long-term data and (2) handling the hard-won data. This paper takes advantage of the free access to long-term recordings of remote sensing data (27 years, Landsat TM/ETM+) to assess a set of environmental models for estimating environmental predictability. The case study included 20 Mediterranean saline ponds and lakes, and the focal variable was the water-surface area. This study first aimed to produce a method for accurately estimating the water-surface area from satellite images. Saline ponds can develop salt-crusted areas that make it difficult to distinguish between soil and water. This challenge was addressed using a novel pipeline that combines band ratio water indices and the short near-infrared band as a salt filter. The study then extracted the predictable and unpredictable components of variation in the water-surface area. Two different approaches, each showing variations in the parameters, were used to obtain the stochastic variation around a regular pattern with the objective of dissecting the effect of assumptions on predictability estimations. The first approach, which is based on Colwell’s predictability metrics, transforms the focal variable into a nominal one. The resulting discrete categories define the relevant variations in the water-surface area. In the second approach, we introduced General Additive Model (GAM) fitting as a new metric for quantifying predictability. Both approaches produced a wide range of predictability for the studied ponds. Some model assumptions–which are considered very different a priori–had minor effects, whereas others produced predictability estimations that showed some degree of divergence. We hypothesize that these diverging estimations of predictability reflect the effect of fluctuations on different types of organisms. The fluctuation analysis described in this manuscript is applicable to a wide variety of systems, including both aquatic and non-aquatic systems, and will be valuable for quantifying and characterizing predictability, which is essential within the expected global increase in the unpredictability of environmental fluctuations. We advocate that a priori information for organisms of interest should be used to select the most suitable metrics for estimating predictability, and we provide some guidelines for this approach. [ABSTRACT FROM AUTHOR]

Background: Climate change is arguably a major threat to biodiversity conservation and there are several methods to assess its impacts on species potential distribution. Yet the extent to which different approaches on species distribution modeling affect species richness patterns at biogeographical scale is however unaddressed in literature. In this paper, we verified if the expected responses to climate change in biogeographical scale—patterns of species richness and species vulnerability to climate change—are affected by the inputs used to model and project species distribution. Methods: We modeled the distribution of 288 vertebrate species (amphibians, birds and mammals), all endemic to the Amazon basin, using different combinations of the following inputs known to affect the outcome of species distribution models (SDMs): 1) biological data type, 2) modeling methods, 3) greenhouse gas emission scenarios and 4) climate forecasts. We calculated uncertainty with a hierarchical ANOVA in which those different inputs were considered factors. Results: The greatest source of variation was the modeling method. Model performance interacted with data type and modeling method. Absolute values of variation on suitable climate area were not equal among predictions, but some biological patterns were still consistent. All models predicted losses on the area that is climatically suitable for species, especially for amphibians and primates. All models also indicated a current East-western gradient on endemic species richness, from the Andes foot downstream the Amazon river. Again, all models predicted future movements of species upwards the Andes mountains and overall species richness losses. Conclusions: From a methodological perspective, our work highlights that SDMs are a useful tool for assessing impacts of climate change on biodiversity. Uncertainty exists but biological patterns are still evident at large spatial scales. As modeling methods are the greatest source of variation, choosing the appropriate statistics according to the study objective is also essential for estimating the impacts of climate change on species distribution. Yet from a conservation perspective, we show that Amazon endemic fauna is potentially vulnerable to climate change, due to expected reductions on suitable climate area. Climate-driven faunal movements are predicted towards the Andes mountains, which might work as climate refugia for migrating species. [ABSTRACT FROM AUTHOR]

Since wind power is integrated into the thermal power operation system, dynamic economic emission dispatch (DEED) has become a new challenge due to its uncertain characteristics. This paper proposes an adaptive grid based multi-objective Cauchy differential evolution (AGB-MOCDE) for solving stochastic DEED with wind power uncertainty. To properly deal with wind power uncertainty, some scenarios are generated to simulate those possible situations by dividing the uncertainty domain into different intervals, the probability of each interval can be calculated using the cumulative distribution function, and a stochastic DEED model can be formulated under different scenarios. For enhancing the optimization efficiency, Cauchy mutation operation is utilized to improve differential evolution by adjusting the population diversity during the population evolution process, and an adaptive grid is constructed for retaining diversity distribution of Pareto front. With consideration of large number of generated scenarios, the reduction mechanism is carried out to decrease the scenarios number with covariance relationships, which can greatly decrease the computational complexity. Moreover, the constraint-handling technique is also utilized to deal with the system load balance while considering transmission loss among thermal units and wind farms, all the constraint limits can be satisfied under the permitted accuracy. After the proposed method is simulated on three test systems, the obtained results reveal that in comparison with other alternatives, the proposed AGB-MOCDE can optimize the DEED problem while handling all constraint limits, and the optimal scheme of stochastic DEED can decrease the conservation of interval optimization, which can provide a more valuable optimal scheme for real-world applications. [ABSTRACT FROM AUTHOR]

Biomass gasification stations are facing many hazard factors, therefore, it is necessary to make hazard assessment for them. In this study, a novel hazard assessment method called extended set pair analysis (ESPA) is proposed based on set pair analysis (SPA). However, the calculation of the connection degree (CD) requires the classification of hazard grades and their corresponding thresholds using SPA for the hazard assessment. In regard to the hazard assessment using ESPA, a novel calculation algorithm of the CD is worked out when hazard grades and their corresponding thresholds are unknown. Then the CD can be converted into Euclidean distance (ED) by a simple and concise calculation, and the hazard of each sample will be ranked based on the value of ED. In this paper, six biomass gasification stations are introduced to make hazard assessment using ESPA and general set pair analysis (GSPA), respectively. By the comparison of hazard assessment results obtained from ESPA and GSPA, the availability and validity of ESPA can be proved in the hazard assessment for biomass gasification stations. Meanwhile, the reasonability of ESPA is also justified by the sensitivity analysis of hazard assessment results obtained by ESPA and GSPA. [ABSTRACT FROM AUTHOR]

The objective of this work is to develop a simple methodology for high resolution crop suitability analysis under current and future climate, easily applicable and useful in Least Developed Countries. The approach addresses both regional planning in the context of climate change projections and pre-emptive short-term rural extension interventions based on same-year agricultural season forecasts, while implemented with off-the-shelf resources. The developed tools are applied operationally in a case-study developed in three regions of Guinea-Bissau and the obtained results, as well as the advantages and limitations of methods applied, are discussed. In this paper we show how a simple approach can easily generate information on climate vulnerability and how it can be operationally used in rural extension services. [ABSTRACT FROM AUTHOR]

Anthropogenic climate change is predicted to have profound effects on species distributions over the coming decades. In this paper, we used maximum entropy modelling (Maxent) to estimate the effects of projected changes in climate on extent of climatically-suitable habitat for two Nepenthes pitcher plant species in Borneo. The model results predicted an increase in area of climatically-suitable habitat for the lowland species Nepenthes rafflesiana by 2100; in contrast, the highland species Nepenthes tentaculata was predicted to undergo significant loss of climatically-suitable habitat over the same period. Based on the results of the models, we recommend that research be undertaken into practical mitigation strategies, as approximately two-thirds of Nepenthes are restricted to montane habitats. Highland species with narrow elevational ranges will be at particularly high risk, and investigation into possible mitigation strategies should be focused on them. [ABSTRACT FROM AUTHOR]

Shortwave solar radiation is an important component of the surface energy balance and provides the principal source of energy for terrestrial ecosystems. This paper presents a machine learning approach in the form of a random forest (RF) model for estimating daily downward solar radiation flux at the land surface over complex terrain using MODIS (MODerate Resolution Imaging Spectroradiometer) remote sensing data. The model-building technique makes use of a unique network of 16 solar flux measurements in the semi-arid Reynolds Creek Experimental Watershed and Critical Zone Observatory, in southwest Idaho, USA. Based on a composite RF model built on daily observations from all 16 sites in the watershed, the model simulation of downward solar radiation matches well with the observation data (r2 = 0.96). To evaluate model performance, RF models were built from 12 of 16 sites selected at random and validated against the observations at the remaining four sites. Overall root mean square errors (RMSE), bias, and mean absolute error (MAE) are small (range: 37.17 W/m2-81.27 W/m2, -48.31 W/m2-15.67 W/m2, and 26.56 W/m2-63.77 W/m2, respectively). When extrapolated to the entire watershed, spatiotemporal patterns of solar flux are largely consistent with expected trends in this watershed. We also explored significant predictors of downward solar flux in order to reveal important properties and processes controlling downward solar radiation. Based on the composite RF model built on all 16 sites, the three most important predictors to estimate downward solar radiation include the black sky albedo (BSA) near infrared band (0.858 μm), BSA visible band (0.3–0.7 μm), and clear day coverage. This study has important implications for improving the ability to derive downward solar radiation through a fusion of multiple remote sensing datasets and can potentially capture spatiotemporally varying trends in solar radiation that is useful for land surface hydrologic and terrestrial ecosystem modeling. [ABSTRACT FROM AUTHOR]

Impact of changes in land cover and land use on hydrological service of tropical watersheds is one of the focal research tropics in both hydrology and Land Cover Land Use Changes (LCLUC). Land fragmentation is an important feature of LCLUC, however, its impact on hydrological service of tropical watershed is unclear despite a few theoretical frameworks. In this paper, we described a simulation study of eight tropical watersheds in Puerto Rico using the Soil Water Assessment Tool. Annual average stream discharge was derived according to the simulations with the land cover maps in 1977, 1991, and 2000. Annual big stream discharge with risks of flooding and severe soil erosion was computed as the sum of daily discharge greater than 95th percentile. The impacts of changes in land cover and fragmentation represented by perimeter-to-area ratio of land patches on annual average and big discharges were further analyzed by means of the linear mixed-effects model. Most mountainous watersheds were characterized by reforestation in 1977–1991 but slight deforestation in 1991–2000. Forest perimeter-to-area ratio was significantly correlated with covers of forest (correlation coefficient of -0.97), pasture (0.94), and urban (0.95). Thus forest fragmentation was reduced by reforestation but increased by deforestation. The annual average and big discharges were significantly reduced by forest cover and forest perimeter-to-area ratio. The enhanced edge effect by forest fragmentation may have incurred more effective interception of the subsurface flow by forest root system, and promoted forest transpiration, thus reduced stream flows. Land cover change plays more important roles in regulating the big discharges than altering the annual average discharges. Due to the negative correlation between forest cover and fragmentation, the decreased forest fragmentation accompanied with reforestation offsets the impact of reforestation on lessening freshwater supply and flooding risk. [ABSTRACT FROM AUTHOR]

Today, China is facing a very serious issue of Air Pollution due to its dreadful impact on the human health as well as the environment. The urban cities in China are the most affected due to their rapid industrial and economic growth. Therefore, it is of extreme importance to come up with new, better and more reliable forecasting models to accurately predict the air quality. This paper selected Beijing, Tianjin and Shijiazhuang as three cities from the Jingjinji Region for the study to come up with a new model of collaborative forecasting using Support Vector Regression (SVR) for Urban Air Quality Index (AQI) prediction in China. The present study is aimed to improve the forecasting results by minimizing the prediction error of present machine learning algorithms by taking into account multiple city multi-dimensional air quality information and weather conditions as input. The results show that there is a decrease in MAPE in case of multiple city multi-dimensional regression when there is a strong interaction and correlation of the air quality characteristic attributes with AQI. Also, the geographical location is found to play a significant role in Beijing, Tianjin and Shijiazhuang AQI prediction. [ABSTRACT FROM AUTHOR]