Recruitment, survival, and parasitism of monarch butterflies (Danaus plexippus) in milkweed gardens and conservation areas

Monarch butterflies (Danaus plexippus) are suffering from declining populations and conservationists have encouraged planting milkweed gardens in urban and suburban landscapes to help offset habitat loss across the breeding range. The effectiveness of gardens as a conservation strategy depends on their ability to attract ovipositing adults and the survival of monarch larvae in these gardens. Larvae are susceptible to a variety of predators as well as to parasitism by a tachinid fly (Lespesia archippivora) and a protozoan parasite (Ophryocystis elektroscirrha) which cause lethal or sublethal effects, yet the severity of these risks in gardens is not well understood. We compared egg abundance and larval survival in traditional conservation areas to gardens that incorporated milkweed to attract monarchs. Additionally, we collected late instar larvae and reared them in the lab to compare parasitism rates between monarch gardens and conservation areas. Both gardens and conservations sites varied widely in recruitment and survival of monarchs and there were no significant differences between the garden and conservation sites. Tachinid fly parasitism ranged from 30% of larvae from conservation sites in 2016 to 55% of larvae from gardens in 2017, but did not differ between the two categories of sites. Parasitism by O. elektroscirrha was detected in fewer than 2% of larvae. The density of milkweed had no effect on the number of monarch eggs in conservation areas or gardens in either year. Milkweed density had no effect on tachinid parasitism in conservation areas but had a significant effect in gardens with lower numbers of milkweed stems increasing tachinid parasitism in 2016. Gardeners planted a variety of species of milkweed and Asclepias syriaca was the most commonly used host plant for monarch larvae (85%). Overall, our results suggest that milkweed gardens have the potential to contribute to successful monarch reproduction. However, the variation among sites and the lack of recruitment from some gardens emphasizes that the realization of this potential contribution will depend on the quality of gardens

Postfledging habitat selection and survival of Henslow’s Sparrow: management implications for a critical life stage

Conserving populations of species that rely on rare habitat requires that managers understand which habitat characteristics will best support population growth across multiple life stages. For songbirds, management is most often aimed at nesting adult habitat associations. However, habitat that meets adult requirements may not be similarly suited to requirements for other life stages. Henslow’s Sparrow (Centronyx henslowii) is a tallgrass prairie songbird listed as threatened or endangered in 13 states. We examined survival and habitat selection of Henslow’s Sparrow during the postfledging period. During the nesting seasons in 2015 and 2016, we attached radio transmitters to 46 nestlings in a tallgrass prairie and modeled their survival and habitat selection as a function of habitat characteristics. Thirty-five percent of fledglings survived until two weeks postfledge. Survival was negatively associated with areas of sumac (Rhus copallinum) cover, positively associated with years since last burn, and decreased as the breeding season progressed. Snakes were the most common predator of fledglings. Independent fledglings used habitat that was different than that used by adults and dependent fledglings, with habitat used during the independent period having lower litter cover and increased forb cover compared to points used during the dependent period. During the dependent period, points used by fledglings were a mean distance of 40 m (± 11 SD) from the natal nest. Following independence, points used by fledglings were 236 m (± 89 SD) from the natal nest. Henslow’s Sparrow populations may benefit from removal of encroaching sumac in tallgrass prairie, and from consideration of the varying habitats used by the species during different life stages

Multiscale Modeling of Binary Polymer Mixtures: Scale Bridging in the Athermal and Thermal Regime

Obtaining a rigorous and reliable method for linking computer simulations of polymer blends and composites at different length scales of interest is a highly desirable goal in soft matter physics. In this paper a multiscale modeling procedure is presented for the efficient calculation of the static structural properties of binary homopolymer blends. The procedure combines computer simulations of polymer chains on two different length scales, using a united atom representation for the finer structure and a highly coarse-grained approach on the meso-scale, where chains are represented as soft colloidal particles interacting through an effective potential. A method for combining the structural information by inverse mapping is discussed, allowing for the efficient calculation of partial correlation functions, which are compared with results from full united atom simulations. The structure of several polymer mixtures is obtained in an efficient manner for several mixtures in the homogeneous region of the phase diagram. The method is then extended to incorporate thermal fluctuations through an effective chi parameter. Since the approach is analytical, it is fully transferable to numerous systems.Comment: in press, 13 pages, 7 figures, 6 table

Low cost infrared and near infrared sensors for UAVs

Thermal remote sensing has a wide range of applications, though the extent of its use is inhibited by cost. Robotic and computer components are now widely available to consumers on a scale that makes thermal data a readily accessible resource. In this project, thermal imagery collected via a lightweight remote sensing Unmanned Aerial Vehicle (UAV) was used to create a surface temperature map for the purpose of providing wildland firefighting crews with a cost-effective and time-saving resource. The UAV system proved to be flexible, allowing for customized sensor packages to be designed that could include visible or infrared cameras, GPS, temperature sensors, and rangefinders, in addition to many data management options. Altogether, such a UAV system could be used to rapidly collect thermal and aerial data, with a geographic accuracy of less than one meter

7-Carboxy-7-deazaguanine Synthase: A Radical

Radical S-adenosyl-L-methionine (SAM) enzymes are widely distributed and catalyze diverse reactions. SAM binds to the unique iron atom of a site-differentiated [4Fe-4S] cluster and is reductively cleaved to generate a 5'-deoxyadenosyl radical, which initiates turnover. 7-Carboxy-7-deazaguanine (CDG) synthase (QueE) catalyzes a key step in the biosynthesis of 7-deazapurine containing natural products. 6-Carboxypterin (6-CP), an oxidized analogue of the natural substrate 6-carboxy-5,6,7,8-tetrahydropterin (CPH4), is shown to be an alternate substrate for CDG synthase. Under reducing conditions that would promote the reductive cleavage of SAM, 6-CP is turned over to 6-deoxyadenosylpterin (6-dAP), presumably by radical addition of the 5'-deoxyadenosine followed by oxidative decarboxylation to the product. By contrast, in the absence of the strong reductant, dithionite, the carboxylate of 6-CP is esterified to generate 6-carboxypterin-5'-deoxyadenosyl ester (6-CP-dAdo ester). Structural studies with 6-CP and SAM also reveal electron density consistent with the ester product being formed in crystallo. The differential reactivity of 6-CP under reducing and nonreducing conditions highlights the ability of radical SAM enzymes to carry out both polar and radical transformations in the same active site

Using the Landsat data archive to assess long-term regional forest dynamics assessment in Eastern Europe, 1985-2012

Abstract. Dramatic political and economic changes in Eastern European countries following the dissolution of the “Eastern Bloc” and the collapse of the Soviet Union greatly affected land-cover and land-use trends. In particular, changes in forest cover dynamics may be attributed to the collapse of the planned economy, agricultural land abandonment, economy liberalization, and market conditions. However, changes in forest cover are hard to quantify given inconsistent forest statistics collected by different countries over the last 30 years. The objective of our research was to consistently quantify forest cover change across Eastern Europe from 1985 until 2012 using the complete Landsat data archive. We developed an algorithm for processing imagery from different Landsat platforms and sensors (TM and ETM+), aggregating these images into a common set of multi-temporal metrics, and mapping annual gross forest cover loss and decadal gross forest cover gain. Our results show that forest cover area increased from 1985 to 2012 by 4.7% across the region. Average annual gross forest cover loss was 0.41% of total forest cover area, with a statistically significant increase from 1985 to 2012. Most forest disturbance recovered fast, with only 12% of the areas of forest loss prior to 1995 not being recovered by 2012. Timber harvesting was the main cause of forest loss. Logging area declined after the collapse of socialism in the late 1980s, increased in the early 2000s, and decreased in most countries after 2007 due to the global economic crisis. By 2012, Central and Baltic Eastern European countries showed higher logging rates compared to their Western neighbours. Comparing our results with official forest cover and change estimates showed agreement in total forest area for year 2010, but with substantial disagreement between Landsat-based and official net forest cover area change. Landsat-based logging areas exhibit strong relationship with reported roundwood production at national scale. Our results allow national and sub-national level analysis of forest cover extent, change, and logging intensity and are available on-line as a baseline for further analyses of forest dynamics and its drivers

Inducible expression of large gRNA arrays for multiplexed CRISPRai applications

CRISPR gene activation and inhibition (CRISPRai) has become a powerful synthetic tool for influencing the expression of native genes for foundational studies, cellular reprograming, and metabolic engineering. Here we develop a method for near leak-free, inducible expression of a polycistronic array containing up to 24 gRNAs from two orthogonal CRISPR/Cas systems to increase CRISPRai multiplexing capacity and target gene flexibility. To achieve strong inducibility, we created a technology to silence gRNA expression within the array in the absence of the inducer, since we found that long gRNA arrays for CRISPRai can express themselves even without promoter. Using this method, we create a highly tuned and easy-to-use CRISPRai toolkit in the industrially relevant yeast, Saccharomyces cerevisiae, establishing the first system to combine simultaneous activation and repression, large multiplexing capacity, and inducibility. We demonstrate this platform by targeting 11 genes in central metabolism in a single transformation, achieving a 45-fold increase in succinic acid, which could be precisely controlled in an inducible manner. Our method offers a highly effective way to regulate genes and rewire metabolism in yeast, with principles of gRNA array construction and inducibility that should extend to other chassis organisms