Benchmarking farmers’ irrigation decisions using farm competition data and a crop growth model - Rintu Sen; Saleh Taghvaeian; Daran Rudnick; Christopher Proctor; Haishun Yang; Abia Katimbo; Chuck Burr; Derek Heeren (Irrigation Science, 2026)
Rising irrigation demand and declining groundwater resources threaten the sustainability of irrigated maize production in Nebraska. Benchmarking farmers’ applied irrigation against optimal amounts offers insight into management performance and highlights opportunities for improvement. However, the few benchmarking studies conducted in Nebraska have often relied on simplified modeling assumptions to estimate optimal irrigation, potentially overestimating the magnitude of differences from actual practices and overlooking factors that influence farmers’ decisions. This study applied the DSSAT CERES-Maize model to determine optimal irrigation using multi-year data from the University of Nebraska-Lincoln’s Testing Ag Performance Solutions (UNL-TAPS) program. The model, calibrated for cultivar traits and site-specific conditions, demonstrated strong agreement between simulated and observed phenology and yield during validation (NRMSE 0.80). The validated model was used to benchmark farmer teams’ irrigation decisions and quantify deviations from optimal irrigation. Seasonal differences between applied and optimal irrigation ranged from − 175 to 306 mm, with a mean of 4 mm. Fifty-four percent of the teams applied more water than optimal, with a mean over-irrigation of 58 mm, less than the extent and magnitude of over-irrigation reported in previous studies. The variability in optimal irrigation (CV = 21%) was lower than actual irrigation (CV = 44%), indicating that behavioral factors played an important role in irrigation decisions made by farmer teams. These findings provide evidence to support improved on-farm water management and the development of policies that encourage sustainable irrigation practices.

Population Genomics of a Cosmopolitan Weed Provides Insights Into Its Local Adaptation and Recent Demographic History - Marilia Souza Lucas; Christoph Rosche; Isabell Hensen; Stefan G. Michalski; Dávid U. Nagy; Diana Gamba; Renske E. Onstein; Karime Abidkulova; Mohammad Al‐Gharaibeh; Ali A. Al‐Namazi; Sirwan Babaei; Fernando Bastida; et al. (Molecular Ecology, 2026)
Invasive plant species present a growing ecological and economic challenge, and often adapt rapidly to their novel environments through complex demographic and evolutionary processes. Invasion genomics offers powerful tools to disentangle these processes, but most studies rely on geographically narrow sampling across native and non‐native ranges. Erigeron canadensis is a cosmopolitan weed native to North America that has successfully invaded diverse climates worldwide. We used double‐digest restriction site‐associated DNA sequencing (ddRADseq) to investigate the genetic diversity and structure of 280 E. canadensis populations across the Northern Hemisphere. We found that native and non‐native populations maintained comparable genetic diversity. Population structure analyses revealed four genetic clusters that were mainly differentiated along latitudinal and aridity gradients. However, one cluster was strongly overrepresented in the non‐native compared to the native range. In the native range, genetic differentiation was shaped by spatial and environmental gradients, while in non‐native regions human‐mediated dispersal and repeated introductions disrupted environmentally driven genetic structure. Migration network analyses revealed limited intercontinental connectivity and a possible role of long‐distance dispersal in within‐range expansions. Genomic offset analyses showed that genotype‐environment mismatches in non‐native populations associated with reduced growth and reproduction. Together, our results indicate that the invasion dynamics of E. canadensis were driven by multiple introductions, population admixture, and lineage sorting, while some genotypes contributed disproportionately to the spread of this invader. The presence of apparent maladaptation suggests that even long‐established invaders may still be evolving in response to their novel environment, raising concerns about potential future expansions.

The Wolverine Project: Evaluating Cumulative Effects Within the Land of Ktunaxa Using the One Heart Method - Nikki Heim; Ryan MacDonald; Christopher Horsethief; Chad Luke; Michael Proctor; Marlene Machmer; Vi Birdstone; Ray Warden; Curtis Wullum; Rachel Plewes; Matthew Chernos; Matt Carlson (Environmental Management, 2025)

Intra- and inter-annual variability of nitrogen and irrigation management effects on nitrate leaching and maize yield in the Bazile Groundwater Management Area, Nebraska - Arshdeep Singh; Daran Rudnick; Daniel Snow; Christopher Misar; Girma Birru; Christopher Proctor; Laila Puntel; Javed Iqbal (Agriculture, Ecosystems & Environment, 2025)

SNAPSHOT USA 2019–2023: The First Five Years of Data From a Coordinated Camera Trap Survey of the United States - Brigit Rooney; Roland Kays; Michael V. Cove; Alex Jensen; Benjamin R. Goldstein; Christopher Pate; Paula Castiblanco; Maggie E. Abell; Jessie Adley; Briana Agenbroad; Adam A. Ahlers; Peter D. Alexander; et al. (Global Ecology and Biogeography, 2025)
Motivation SNAPSHOT USA is an annual, multicontributor camera trap survey of mammals across the United States. The growing SNAPSHOT USA dataset is intended for tracking the spatial and temporal responses of mammal populations to changes in land use, land cover and climate. These data will be useful for exploring the drivers of spatial and temporal changes in relative abundance and distribution, as well as the impacts of species interactions on daily activity patterns. Main Types of Variables Contained SNAPSHOT USA 2019–2023 contains 987,979 records of camera trap image sequence data and 9694 records of camera trap deployment metadata. Spatial Location and Grain Data were collected across the United States of America in all 50 states, 12 ecoregions and many ecosystems. Time Period and Grain Data were collected between 1st August and 29th December each year from 2019 to 2023. Major Taxa and Level of Measurement The dataset includes a wide range of taxa but is primarily focused on medium to large mammals. Software Format SNAPSHOT USA 2019–2023 comprises two .csv files. The original data can be found within the SNAPSHOT USA Initiative in the Wildlife Insights platform.

SNAPSHOT USA 2021: A third coordinated national camera trap survey of the U nited S tates - Hila Shamon; Roi Maor; Michael V. Cove; Roland Kays; Jessie Adley; Peter D. Alexander; David N. Allen; Maximilian L. Allen; Cara L. Appel; Evan Barr; Erika L. Barthelmess; Carolina Baruzzi; et al. (Ecology, 2024)
SNAPSHOT USA is a multicontributor, long‐term camera trap survey designed to survey mammals across the United States. Participants are recruited through community networks and directly through a website application ( https://www.snapshot-usa.org/ ). The growing Snapshot dataset is useful, for example, for tracking wildlife population responses to land use, land cover, and climate changes across spatial and temporal scales. Here we present the SNAPSHOT USA 2021 dataset, the third national camera trap survey across the US. Data were collected across 109 camera trap arrays and included 1711 camera sites. The total effort equaled 71,519 camera trap nights and resulted in 172,507 sequences of animal observations. Sampling effort varied among camera trap arrays, with a minimum of 126 camera trap nights, a maximum of 3355 nights, a median 546 nights, and a mean 656 ± 431 nights. This third dataset comprises 51 camera trap arrays that were surveyed during 2019, 2020, and 2021, along with 71 camera trap arrays that were surveyed in 2020 and 2021. All raw data and accompanying metadata are stored on Wildlife Insights ( https://www.wildlifeinsights.org/ ), and are publicly available upon acceptance of the data papers. SNAPSHOT USA aims to sample multiple ecoregions in the United States with adequate representation of each ecoregion according to its relative size. Currently, the relative density of camera trap arrays varies by an order of magnitude for the various ecoregions (0.22–5.9 arrays per 100,000 km 2 ), emphasizing the need to increase sampling effort by further recruiting and retaining contributors. There are no copyright restrictions on these data. We request that authors cite this paper when using these data, or a subset of these data, for publication. Any use of trade, firm, or product names is for descriptive purposes only and does not imply endorsement by the US Government.

Irrigation increases on-farm soybean yields in water-limited environments without a trade-off in seed protein concentration - Walter D. Carciochi; Patricio Grassini; Seth Naeve; James E. Specht; Mitiku Mamo; Ron Seymour; Aaron Nygren; Nathan Mueller; Sarah Sivits; Christopher Proctor; Jenny Rees; Todd Whitney; et al. (Field Crops Research, 2023)

SNAPSHOT USA 2020: A second coordinated national camera trap survey of the United States during the COVID ‐19 pandemic - Roland Kays; Michael V. Cove; Jose Diaz; Kimberly Todd; Claire Bresnan; Matt Snider; Thomas E. Lee; Jonathan G. Jasper; Brianna Douglas; Anthony P. Crupi; Katherine C. B. Weiss; Helen Rowe; et al. (Ecology, 2022)
Managing wildlife populations in the face of global change requires regular data on the abundance and distribution of wild animals, but acquiring these over appropriate spatial scales in a sustainable way has proven challenging. Here we present the data from Snapshot USA 2020, a second annual national mammal survey of the USA. This project involved 152 scientists setting camera traps in a standardized protocol at 1485 locations across 103 arrays in 43 states for a total of 52,710 trap‐nights of survey effort. Most (58) of these arrays were also sampled during the same months (September and October) in 2019, providing a direct comparison of animal populations in 2 years that includes data from both during and before the COVID‐19 pandemic. All data were managed by the eMammal system, with all species identifications checked by at least two reviewers. In total, we recorded 117,415 detections of 78 species of wild mammals, 9236 detections of at least 43 species of birds, 15,851 detections of six domestic animals and 23,825 detections of humans or their vehicles. Spatial differences across arrays explained more variation in the relative abundance than temporal variation across years for all 38 species modeled, although there are examples of significant site‐level differences among years for many species. Temporal results show how species allocate their time and can be used to study species interactions, including between humans and wildlife. These data provide a snapshot of the mammal community of the USA for 2020 and will be useful for exploring the drivers of spatial and temporal changes in relative abundance and distribution, and the impacts of species interactions on daily activity patterns. There are no copyright restrictions, and please cite this paper when using these data, or a subset of these data, for publication.

The North Atlantic Aerosol and Marine Ecosystem Study (NAAMES): Science Motive and Mission Overview - Michael J. Behrenfeld; Richard H. Moore; Chris A. Hostetler; Jason Graff; Peter Gaube; Lynn M. Russell; Gao Chen; Scott C. Doney; Stephen Giovannoni; Hongyu Liu; Christopher Proctor; Luis M. Bolaños; et al. (Frontiers in Marine Science, 2019)

Reducing production of fumonisin mycotoxins in Fusarium verticillioides by RNA interference - Eric T. Johnson; Robert H. Proctor; Christopher A. Dunlap; Mark Busman (Mycotoxin Research, 2018)

Scaffolds for Tendon and Ligament Repair and Regeneration - Anthony Ratcliffe; David L. Butler; Nathaniel A. Dyment; Paul J. Cagle; Christopher S. Proctor; Seena S. Ratcliffe; Evan L. Flatow (Annals of Biomedical Engineering, 2015)

APPLICATIONS IN COASTAL MODELING AND FORECASTING - Pierre De Mey; Peter Craig; Fraser Davidson; Christopher Edwards; Yoichi Ishikawa; John Kindle; Roger Proctor; Keith Thompson; Jiang Zhu (Oceanography, 2009)

Integration of Mouse Phenome Data Resources - John M. Hancock; Niels C. Adams; Vassilis Aidinis; Andrew Blake; Judith A. Blake; Molly Bogue; Steve D. M. Brown; Elissa J. Chesler; Duncan Davidson; Christopher Duran; Janan T. Eppig; Valérie Gailus-Durner; et al. (Mammalian Genome, 2008)

Stalagmite lamina doublets: a 1000 year proxy record of severe winters in northwest Scotland? - Andy Baker; Christopher J. Proctor; William L. Barnes (International Journal of Climatology, 2002)
Stalagmites can contain annual luminescence laminae, and some samples provide long continuous chronologies from which climatic information can be extracted. One such site is Uamh an Tartair in Assynt, northwest Scotland, where most stalagmites contain continuous laminae sets for the last two to three millennia. At this site, the normal mode of deposition is for one luminescent lamina to be deposited in autumn, derived from luminescent organic matter that is flushed onto the sample from the overlying peat. However, in the stalagmite investigated here, 43 lamina doublets occur, where two laminae appear to be preserved in a winter. We argue, both from the timing of these events within the ‘Little Ice Age’, as well as from analogous situations in alpine streams, that the doublets occur due to the presence of a second, spring melt flush of organic matter. The interpretation of stalagmite double laminae, therefore, has considerable potential as a palaeoclimate proxy, and at our study site, we suggest one of severe winters over the last millennium. Copyright © 2002 Royal Meteorological Society.