Overlooked biodiversity loss in tropical smallholder agriculture

Smallholder agriculture is the main driver of deforestation in the western Amazon, where terrestrial biodiversity reaches its global maximum. Understanding the biodiversity value of the resulting mosaics of cultivated and secondary forest is therefore crucial for conservation planning. However, Amazonian communities are organized across multiple forest types that support distinct species assemblages, and little is known about smallholder impacts across the range of forest types that are essential for sustaining biodiversity. We addressed this issue with a large-scale field inventory of birds (point counts) and trees (transects) in primary forest and smallholder agriculture in northern Peru across 3 forest types that are key for Amazonian biodiversity. For birds smallholder agriculture supported species richness comparable to primary forest within each forest type, but biotic homogenization across forest types resulted in substantial losses of biodiversity overall. These overall losses are invisible to studies that focus solely on upland (terra firma) forest. For trees biodiversity losses in upland forests dominated the signal across all habitats combined and homogenization across habitats did not exacerbate biodiversity loss. Proximity to forest strongly predicted the persistence of forest-associated bird and tree species in the smallholder mosaic, and because intact forest is ubiquitous in our study area, our results probably represent a best-case scenario for biodiversity in Amazonian agriculture. Land-use planning inside and outside protected areas should recognize that tropical smallholder agriculture has pervasive biodiversity impacts that are not apparent in typical studies that cover a single forest type. The full range of forest types must be surveyed to accurately assess biodiversity losses, and primary forests must be protected to prevent landscape-scale biodiversity loss.     

Spatiotemporal modeling of irregularly spaced aerosol optical depth data

Many advancements have been introduced to tackle spatial and temporal structures in data. When the spatial and/or temporal domains are relatively large, assumptions must be made to account for the sheer size of the data. The large data size, coupled with realities that come with observational data, make it difficult for all of these assumptions to be met. In particular, air quality data are very sparse across geographic space and time, due to a limited air pollution monitoring network. These “missing” values make it difficult to incorporate most dimension reduction techniques developed for high-dimensional spatiotemporal data. This article examines aerosol optical depth (AOD), an indirect measure of radiative forcing, and air quality. The spatiotemporal distribution of AOD can be influenced by both natural (e.g., meteorological conditions) and anthropogenic factors (e.g., emission from industries and transport). After accounting for natural factors influencing AOD, we examine the spatiotemporal relationship in the remaining human influenced portion of AOD. The presented data cover a portion of India surrounding New Delhi from 2000–2006. The proposed method is demonstrated showing how it can handle the large spatiotemporal structure containing so much missing data for both meteorologic conditions and AOD over time and space.     

Enzymatic processing of municipal solid waste

The focus of this work was to investigate an enzymatic liquefaction of MSW organics, paper and cardboard. Liquefaction trials were conducted in different trial volumes: 50 g lab-scale trials and 50 kg vessel-tests and evaluated based on particle size and viscosity. The viscosity results showed that Celluclast 1.5 L had the singular significant effect on liquefaction of model MSW. No effect of α-amylase, protease and interaction in between and with cellulases on viscosity and particle size distribution was found in this study. Degradable material with a particle size above 1 mm after treatment was evaluated using SEM microscopy. These results showed that paper particles were the main obstacles needing additional treatment in order to become fully liquefied. In a pilot scale test treating authentic MSW; more than 90% of initial organic and paper dry matter (DM) was recovered as liquid slurry after sieving through a 5-mm sieve. These tests were performed at up to 35% DM, showing that this process can easily manage high DM loadings. MSW enzymatic liquefaction promotes the separation of organics and paper from solids, which facilitate the use of these degradable fractions, with minimal loss, capable to enter a biogas plant through existing pipes.     

Central power generation versus distributed generation – An air quality assessment in the South Coast Air Basin of California

This study assesses the air quality impacts of central power generation and compares them with the impacts of distributed generation (DG). The central power plant emissions factors used are from a newly installed combined cycle gas turbine system. Because location of power plants is a key parameter affecting air quality impacts, this study considers three potential locations for the installation of central power plants. Air quality impacts are evaluated for the South Coast Air Basin of California, in the year 2010, using a three-dimensional air quality model. Results are compared to air quality impacts from two potential DG scenarios to meet the same power demand as that of the central power plant case.Even though emissions from central generation are lower than emissions from the DG technology mix considered herein, central generation concentrates emissions in a small area, whereas DG spreads emissions throughout a larger cross-section of the air basin. As a result, air quality impacts from central generation are more significant than those from DG. The study also shows that assessment of air quality impacts from distributed and central generation should not only consider emissions levels, but also the spatial and temporal distribution of emissions and the air quality that results from atmospheric chemistry and transport – highly non-linear processes.Finally, analysis of population exposure to ozone and PM_2.5 shows that central generation located in coastal areas upwind from populated areas would cause the highest population exposure and even though emissions from central generation are considerably lower than DG emissions spread throughout the basin, results show that central generation causes a higher pollutant exposure than DG.     

A survey of DNA methylation across social insect species, life stages, and castes reveals abundant and caste-associated methylation in a primitively social wasp

DNA methylation plays an important role in the epigenetic control of developmental and behavioral plasticity, with connections to the generation of striking phenotypic differences between castes (larger, reproductive queens and smaller, non-reproductive workers) in honeybees and ants. Here, we provide the first comparative investigation of caste- and life stage-associated DNA methylation in several species of bees and vespid wasps displaying different levels of social organization. Our results reveal moderate levels of DNA methylation in most bees and wasps, with no clear relationship to the level of sociality. Strikingly, primitively social Polistes dominula paper wasps show unusually high overall DNA methylation and caste-related differences in site-specific methylation. These results suggest DNA methylation may play a role in the regulation of behavioral and physiological differences in primitively social species with more flexible caste differences.