Expressed genes from two individual sibling specimens of Coleomegilla maculata (Coleoptera: Coccinellidae). One individual was fed only insect eggs as an adult, and one was fed only pollen as an adult. Two sequenced samples, total RNA from a single individual adult specimen of Coleomegilla maculata, a beneficial lady beetle common in agroecosystems and native to North America. One sample was an adult fed only insect eggs (carnivore diet) and one sample was an adult fed only pollen (plant-based diet); insects were reared from the same egg mass (siblings), fed identical diet while in larval stage. BioProject: Coleomegilla maculata strain:inbred Mississippi Transcriptome or Gene expression Taxonomy: Coleomegilla maculata Project data type: Transcriptome or Gene expression Scope: Multiisolate US Department of Agriculture Accession: PRJNA236444 ID: 236444

Field-based, partial life table data for immature stages of silverleaf whitefly, Bemisia argentifolii, on 6 host plants including alfalfa, broccoli, spring and fall cantaloupe, cotton, ornamental lantana, and several species of annual weeds in Maricopa, Marana and Yuma Arizona, USA. Data were collected on a total of 73 individual cohorts (each replicated 4 times) from November 2000 to April 2003 at all three study sites. For each cohort, data were generated on approximately 400 individual insects (200 eggs and 200 first instar nymphs). Data provide the marginal, cause-specific mortality for eggs, and 1st, 2nd, 3rd, and 4th instar nymphs collectively and stage-specific marginal mortality for each stage over all causes. Mortality was characterized as caused by inviability (eggs only), dislodgement, predation, parasitism (nymphs only), desiccation, and unknown. Detailed methods can be found in Naranjo and Ellsworth 2005 (Entomologia Experimentalis et Applicata 116(2): 93-108; https://doi.org/10.1111/j.1570-7458.2005.00297.x ; and Naranjo and Ellsworth 2017 (Journal of Visualized Experiments, 129; https://doi.org/10.3791/56150). The method takes advantage of the sessile nature of immature stages of this insect. Briefly, an observer follows individual eggs or settled first instar nymphs from natural populations on the underside of host plant leaves in the field with a hand lens and determines causes of death for each individual over time. Weather data was monitored using the University of Arizona AzMet system. Note that these life table data do not include adult mortality or reproduction. The life table data were used to generate survivorship curves for each cohort on each host plant based on a physiological time scale of accumulated degree-days above 10C from the initiation of each cohort.

Description: This dataset consists of field data (arthropods, nematodes and NDVI) collected over the course of 6 field excursions in 2015 and 2016 near TyTy, GA, in a field used for growing Miscanthus x giganteus. It also includes interpolated values of soil measurements collected in 2015 and meteorological data collected on an adjacent farm. Point-in-time measurements include all meteorological, NDVI, arthropod and nematode measurements and their derivatives. Fixed values were measurements that were held constant across all sampling dates, including location, terrain and soils measurements and their derivatives. Dawn Olson and Jason Schmidt collected and processed arthropod count data. Jason Schmidt collected and processed spider count data and computed spider diversity. Richard Davis collected and processed nematode count data. Alisa Coffin collected and processed NDVI data and positional locations. Tim Strickland collected and processed soils data and Alisa Coffin interpolated soils values using kriging to derive values at arthropod sample locations. David Bosch collected and processed meteorological data. Lynne Seymour provided statistical expertise in deriving any estimated values (phloem feeders, parasitoids, spiders, and natural enemies). Alisa Coffin derived terrain data (elevation, slope, aspect, and distances) from publicly available datasets, transformed values (SI, WI, etc), carried out the geographically weighted regression analysis and calculated C:SE values, harmonized the full dataset, and compiled it using Esri's ArcGIS Pro 2.5. Methods for most data are published in the accompanying paper and associated supplements. Questions about dataset development and management should be directed to Alisa Coffin (alisa.coffin@usda.gov). This work was accomplished as a joint USDA and University of Georgia project funded by a cooperative agreement (#6048-13000-026-21S). This research was a contribution from the Long-Term Agroecosystem Research (LTAR) network. LTAR is supported by the United States Department of Agriculture. At request of the author, the data resources are under embargo. The embargo will expire on Fri, Jan 01, 2021.