Global and regional potential for bioenergy from agricultural and forestry residue biomass

As co-products, agricultural and forestry residues represent a potential low cost, low carbon, source for bioenergy. A method is developed for estimating the maximum sustainable amount of energy potentially available from agricultural and forestry residues by converting crop production statistics into associated residue, while allocating some of this resource to remain on the field to mitigate erosion and maintain soil nutrients. Currently, we estimate that the world produces residue biomass that could be sustainably harvested and converted into nearly 50 EJ yr⁻¹ of energy. The top three countries where this resource is estimated to be most abundant are currently net energy importers: China, the United States (US), and India. The global potential from residue biomass is estimated to increase to approximately 50–100 EJ yr⁻¹ by mid- to late- century, depending on physical assumptions such as of future crop yields and the amount of residue sustainably harvestable. The future market for biomass residues was simulated using the Object-Oriented Energy, Climate, and Technology Systems Mini Climate Assessment Model (O^bjECTS MiniCAM). Utilization of residue biomass as an energy source is projected for the next century under different climate policy scenarios. Total global use of residue biomass is estimated to be 20–100 EJ yr⁻¹ by mid- to late- century, depending on the presence of a climate policy and the economics of harvesting, aggregating, and transporting residue. Much of this potential is in developing regions of the world, including China, Latin America, Southeast Asia, and India.     

Efficient Delineation of Nested Depression Hierarchy in Digital Elevation Models for Hydrological Analysis Using Level‐Set Method

In terrain analysis and hydrological modeling, surface depressions (or sinks) in a digital elevation model (DEM) are commonly treated as artifacts and thus filled and removed to create a depressionless DEM. Various algorithms have been developed to identify and fill depressions in DEMs during the past decades. However, few studies have attempted to delineate and quantify the nested hierarchy of actual depressions, which can provide crucial information for characterizing surface hydrologic connectivity and simulating the fill‐merge‐spill hydrological process. In this paper, we present an innovative and efficient algorithm for delineating and quantifying nested depressions in DEMs using the level‐set method based on graph theory. The proposed level‐set method emulates water level decreasing from the spill point along the depression boundary to the lowest point at the bottom of a depression. By tracing the dynamic topological changes (i.e., depression splitting/merging) within a compound depression, the level‐set method can construct topological graphs and derive geometric properties of the nested depressions. The experimental results of two fine‐resolution Light Detection and Ranging‐derived DEMs show that the raster‐based level‐set algorithm is much more efficient (~150 times faster) than the vector‐based contour tree method. The proposed level‐set algorithm has great potential for being applied to large‐scale ecohydrological analysis and watershed modeling.     

Wetland Flowpaths Mediate Nitrogen and Phosphorus Concentrations across the Upper Mississippi River Basin

Eutrophication, harmful algal blooms, and human health impacts are critical environmental challenges resulting from excess nitrogen and phosphorus in surface waters. Yet we have limited information regarding how wetland characteristics mediate water quality across watershed scales. We developed a large, novel set of spatial variables characterizing hydrological flowpaths from wetlands to streams, that is, “wetland hydrological transport variables,” to explore how wetlands statistically explain the variability in total nitrogen (TN) and total phosphorus (TP) concentrations across the Upper Mississippi River Basin (UMRB) in the United States. We found that wetland flowpath variables improved landscape-to-aquatic nutrient multilinear regression models (from R² = 0.89 to 0.91 for TN; R² = 0.53 to 0.84 for TP) and provided insights into potential processes governing how wetlands influence watershed-scale TN and TP concentrations. Specifically, flowpath variables describing flow-attenuating environments, for example, subsurface transport compared to overland flowpaths, were related to lower TN and TP concentrations. Frequent hydrological connections from wetlands to streams were also linked to low TP concentrations, which likely suggests a nutrient source limitation in some areas of the UMRB. Consideration of wetland flowpaths could inform management and conservation activities designed to reduce nutrient export to downstream waters.     

Spatial and social connectivity of fish-eating “Resident” killer whales (Orcinus orca) in the northern North Pacific

The productive North Pacific waters of the Gulf of Alaska, Aleutian Islands and Bering Sea support a high density of fish-eating “Resident” type killer whales (Orcinus orca), which overlap in distribution with commercial fisheries, producing both direct and indirect interactions. To provide a spatial context for these interactions, we analyzed a 10-year dataset of 3,058 whale photo-identifications from 331 encounters within a large (linear ~4,000 km) coastal study area to investigate the ranging and social patterns of 532 individually identifiable whales photographed in more than one encounter. Although capable of large-scale movements (maximum 1,443 km), we documented ranges generally <200 km, with high site fidelity across summer sampling intervals and also re-sightings during a winter survey. Bayesian analysis of pair-wise associations identified four defined clusters, likely representing groupings of stable matrilines, with distinct ranging patterns, that combined to form a large network of associated whales that ranged across most of the study area. This provides evidence of structure within the Alaska stock of Resident killer whales, important for evaluating ecosystem and fisheries impacts. This network included whales known to depredate groundfish from longline fisheries, and we suggest that such large-scale connectivity has facilitated the spread of depredation.     

Temporal changes in the trophic ecology of the asymbiotic gorgonian Leptogorgia virgulata

Gorgonians are widespread sub-littoral benthic suspension feeders in the world oceans. However, data on their trophic ecology and role in benthic–pelagic coupling and biogeochemical cycles remain limited. This study assesses the trophic ecology of Leptogorgia virgulata in the Skidaway River estuary, USA (31.9896N, 81.0242W) by analysing carbon and nitrogen isotopic signatures of its soft tissue and different-sized fractions of particulate organic matter (POM) in its environment. Samples were taken in 5 April, 2 August, and 15 October 2012 and 11 January 2013. Results support a distinct temporal shift in the diet of L. virgulata from the POM fraction <10 µm (i.e. pico- and nanoplankton) to the 10–63-µm fraction (i.e. microplankton). This trophic regime is likely associated with the natural abundance of prey items within these size classes, thus suggesting that L. virgulata may be an opportunistic feeder, and seasonal shifts in food availability in the water column affect its diet. As such small prey items affect the bioenergetics of L. virgulata, it is important to understand the implications of changes in food availability associated with environmental drivers on the physiology and population dynamics of this dominant species in the western Atlantic Ocean.     

A constrained least-squares approach to combine bottom-up and top-down CO2 flux estimates

Terrestrial CO₂ flux estimates are obtained from two fundamentally different methods generally termed bottom-up and top-down approaches. Inventory methods are one type of bottom-up approach which uses various sources of information such as crop production surveys and forest monitoring data to estimate the annual CO₂ flux at locations covering a study region. Top-down approaches are various types of atmospheric inversion methods which use CO₂ concentration measurements from monitoring towers and atmospheric transport models to estimate CO₂ flux over a study region. Both methods can also quantify the uncertainty associated with their estimates. Historically, these two approaches have produced estimates that differ considerably. The goal of this work is to construct a statistical model which sensibly combines estimates from the two approaches to produce a new estimate of CO₂ flux for our study region. The two approaches have complementary strengths and weaknesses, and our results show that certain aspects of the uncertainty associated with each of the approaches are greatly reduced by combining the methods. Our model is purposefully simple and designed to take the two approaches’ estimates and measures of uncertainty at ‘face value’. Specifically, we use a constrained least-squares approach to appropriately weigh the estimates by the inverse of their variance, and the constraint imposes agreement between the two sources. Our application involves nearly 18,000 flux estimates for the upper midwest United States. The constrained dependencies result in a non-sparse covariance matrix, but computation requires only minutes due to the structure of the model.     

Efficient preparation of greener N-doped carbon nanotube composites for water treatment by the microwave polyol method

N-doped carbon nanotubes have unique structures and strong interactions with metal nanoparticles due to the presence of nitrogen. There is actually a need for nanoparticles to treat water, without leaching of toxic metals. Here, we synthesized nanocomposites by deposition of Ag and Fe nanoparticles on N-doped carbon nanotubes with a surface area of 52 m²/g and 2 % N content to form nanocomposites. Transmission electron microscopy (TEM) of the nanocomposites revealed that the best dispersion of the deposited nanoparticles was achieved by the microwave-assisted polyol method. The Ag and Fe nanoparticles were indeed monodispersed and uniformly distributed on the surface of the N-doped carbon nanotubes. Deposition could be achieved in 5 min. The wet impregnation and deposition–precipitation methods gave composites with agglomerated nanoparticles. We observed that leaching of Fe and Ag into water was also influenced by the preparation method. No leaching of nanoparticles was observed when the composites were prepared by the microwave polyol method. This synthesis is therefore efficient with less energy and time. The strong metal/N-doped carbon nanotube interactions render these composites suitable for use in water purification.     

Assessment of the red-crowned crane habitat in the Yellow River Delta Nature Reserve, East China

As wildlife habitat is in constant evolution, periodic monitoring is essential to assess its quality. In this study, the change to the red-crowned crane habitat in the Yellow River Delta Nature Reserve was detected from multi-temporal remote sensing data from 1992 to 2008 in a geographic information system. Habitat fragmentation was derived from both physical constraints and human disturbance. The changing habitat quality was assessed against five landscape indices. The results obtained from Landsat TM images indicate that potential habitat shrank 37.9 % during 1992–2001, but recovered 99.4 % by 2008. Suitable habitat shrank by 4,329 ha to a level below that of 1992 despite an increase of 4,747 ha in potential habitat due to an increase of 9,075 ha in fragmented areas. Both landscape indices and the red-crowned crane population reveal that suitable habitat was the most fragmented in 2001, but the least fragmented in 1992. Therefore, it is inadequate to just restore wetland through artificial diversion of channel flow to the Reserve to preserve the crane habitat. Commensurate efforts should also be directed at improving habitat quality by minimizing human activities and spatially juxtaposing water and reed marshes harmoniously inside the Reserve.     

Evaluating the sustainability potential of a white goods refurbishment program

A sustainable national policy on waste electronic and electrical equipment reuse has to ensure an integrated environmental economic and social approach. In this paper, a quantitative model is developed that permits a comparative analysis of re-use and non-re-use scenarios from an environmental and economic perspective. The model demonstrates the importance of considering user consumption profiles and the changing national electricity generation portfolio in determining the best end-of-life strategy, whether it should be reuse or recycling. A case study of Ireland is used to demonstrate the model. From a social perspective, qualitative aspects of reuse, such as the job creation potential and the impact on prosperity for low income families, are also considered. Reuse of white goods, if conducted through social enterprises, will create more employment than an equivalent amount of recycling for those most vulnerable to unemployment. Any environmental and social dividends from re-use can be realized only in the context of an economically sustainable system. This would include such factors as a secure supply of suitable equipment, a competitive cost base and sufficient revenues from sales and other sources in order for the business to survive. In an attempt to examine whether a white goods re-use program could possibly operate in a competitive manner with new appliances, this study has examined examples of comparable businesses operating in the EU as well as interpreting data on consumer demand.     

Quantifying secondary pest outbreaks in cotton and their monetary cost with causal-inference statistics

Secondary pest outbreaks occur when the use of a pesticide to reduce densities of an unwanted target pest species triggers subsequent outbreaks of other pest species. Although secondary pest outbreaks are thought to be familiar in agriculture, their rigorous documentation is made difficult by the challenges of performing randomized experiments at suitable scales. Here, we quantify the frequency and monetary cost of secondary pest outbreaks elicited by early-season applications of broad-spectrum insecticides to control the plant bug Lygus spp. (primarily L. hesperus) in cotton grown in the San Joaquin Valley, California, USA. We do so by analyzing pest-control management practices for 969 cotton fields spanning nine years and 11 private ranches. Our analysis uses statistical methods to draw formal causal inferences from nonexperimental data that have become popular in public health and economics, but that are not yet widely known in ecology or agriculture. We find that, in fields that received an early-season broad-spectrum insecticide treatment for Lygus, 20.2% +/- 4.4% (mean +/- SE) of late-season pesticide costs were attributable to secondary pest outbreaks elicited by the early-season insecticide application for Lygus. In 2010 U.S. dollars, this equates to an additional $6.00 +/- $1.30 (mean +/- SE) per acre in management costs. To the extent that secondary pest outbreaks may be driven by eliminating pests' natural enemies, these figures place a lower bound on the monetary value of ecosystem services provided by native communities of arthropod predators and parasitoids in this agricultural system.