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ABSTRACT Tissue identity determination is crucial for regeneration, and the planarian anteroposterior (AP) axis uses positional control genes expressed from body wall muscle to determine body regionalization. Canonical Wnt signaling establishes anterior versus posterior pole identities through notum and wnt1 signaling, and two Wnt/FGFRL signaling pathways control head and trunk domains, but their downstream signaling mechanisms are not fully understood. Here, we identify a planarian Src homolog that restricts head and trunk identities to anterior positions. src-1(RNAi) animals formed enlarged brains and ectopic eyes and also duplicated trunk tissue, similar to a combination of Wnt/FGFRL RNAi phenotypes. src-1 was required for establishing territories of positional control gene expression in Schmidtea mediterranea, indicating that it acts at an upstream step in patterning the AP axis. Double RNAi experiments and eye regeneration assays suggest src-1 can act in parallel to at least some Wnt and FGFRL factors. Co-inhibition of src-1 with other posterior-promoting factors led to dramatic patterning changes and a reprogramming of Wnt/FGFRLs into controlling new positional outputs. These results identify src-1 as a factor that promotes robustness of the AP positional system that instructs appropriate regeneration. 

West Antarctica hosts an unusually high geothermal gradient supported by hot, low-viscosity mantle which likely enhanced the lithospheric response to West Antarctic Ice Sheet [WAIS] cycles of growth and increased the sensitivity of thermochronometers to landscape evolution. Thus a valuable record of glacial landscape change might be recovered from apatite fission track [AFT 80-130°C range] and (U-Th)/He [AHe; 50-90°C]dating, provided that landscape evolution can be distinguished from tectonic signals, including the effects of faults. This study utilizes AFT-AHe thermochronology and thermo-kinematic Pecube modeling to investigate interactions between the hot geotherm, glacial erosion, and inferred crustal structures in the Ford Ranges and the DeVicq Glacier trough in Marie Byrd Land (MBL). The Ford Ranges host glacial troughs (up to 3km relief) dissecting a low-relief erosional surface. Previous work suggests a majority of bedrock exhumation and cooling occurred at/by 80 Ma. However, new data hint at renewed exhumation linked to glacial incision since WAIS formation at 34 or 20 Ma. Prior (U-Th)/He zircon dates from exposures of crystalline bedrock span 90 – 67 Ma. New AHe bedrock dates are 41 to 26 Ma, while two glacial erratics (presumed to be eroded from walls or floor of glacial troughs) yielded AHe dates of 37 Ma and 16 Ma. The DeVicq Glacier trough (>3.5km relief) likely coincides with a regional fault but lacks temperature-time information compared to other regions. The structure may have accommodated motion between elevated central MBL and the subdued crust of the Ford Ranges. We are acquiring AHe and AFT for onshore and offshore samples to compare uplift and exhumation rates for bedrock flanking DeVicq trough. Our new Pecube models test a series of thermal, tectonic, and landscape evolution scenarios against a suite of thermochronologic data, allowing us to assess the timing of glacial incision and WAIS initiation in the FordRanges, and to seek evidence of an inferred tectonic boundary at DeVicq Trough. Modeling efforts will be aided by new AHe analyses from ongoing work. These models combine topographic, tectonic, thermal, and key thermochronologic datasets to produce new insight into the unique cryosphere-lithosphere interactions affecting landscape change in West Antarctica. 

Understanding how environmental adaptations mediate plant and ecosystem responses becomes increasingly important under accelerating global environmental change. Multi-stemmed trees, for example, differ in form and function from single-stemmed trees and may possess physiological advantages that allow for persistence during stressful climatic events such as extended drought. Following the worst drought in Hawaii in a century, we examined patterns of stem abundance and turnover in a Hawaiian lowland dry forest (LDF) and a montane wet forest (MWF) to investigate how multi-stemmed trees might influence site persistence, and how stem abundance and turnover relate to key functional traits. We found stem abundance and multi-stemmed trees to be an important component for climate resilience within the LDF. The LDF had higher relative abundance of multi-stemmed trees, stem abundance, and mean stem abundance compared to a reference MWF. Within the LDF, multi-stemmed trees had higher relative stem abundance (i.e., percent composition of stems to the total number of stems in the LDF) and higher estimated aboveground carbon than single-stemmed trees. Stem abundance varied among species and tree size classes. Stem turnover (i.e., change in stem abundance between five-year censuses) varied among species and tree size classes and species mean stem turnover was correlated with mean species stem abundance per tree. At the plot level, stem abundance per tree is also a predictor of survival, though mortality did not differ between multiple- and single-stemmed trees. Lastly, species with higher mean stem abundance per tree tended to have traits associated with a higher light-saturated photosynthetic rate, suggesting greater productivity in periods with higher water supply. Identifying the traits that allow species and forest communities to persist in dry environments or respond to disturbance is useful for forecasting ecological climate resilience or potential for restoration in tropical dry forests. 

We explore the transfer of control from an automated vehicle to the driver. Based on data from N=19 participants who participated in a driving simulator experiment, we find evidence that the transfer of control often does not take place in one step. In other words, when the automated system requests the transfer of control back to the driver, the driver often does not simply stop the non-driving task. Rather, the transfer unfolds as a process of interleaving the non-driving and driving tasks. We also find that the process is moderated by the length of time available for the transfer of con- trol: interleaving is more likely when more time is available. Our interface designs for automated vehicles must take these results into account so as to allow drivers to safely take back control from automation. 

Drought is a prominent feature of Hawaiʻi’s climate. However, it has been over 30 years since the last comprehensive meteorological drought analysis, and recent drying trends have emphasized the need to better understand drought dynamics and multi-sector effects in Hawaiʻi. Here, we provide a comprehensive synthesis of past drought effects in Hawaiʻi that we integrate with geospatial analysis of drought characteristics using a newly developed 100-year (1920–2019) gridded Standardized Precipitation Index (SPI) dataset. The synthesis examines past droughts classified into five categories: Meteorological, agricultural, hydrological, ecological, and socioeconomic drought. Results show that drought duration and magnitude have increased significantly, consistent with trends found in other Pacific Islands. We found that most droughts were associated with El Niño events, and the two worst droughts of the past century were multi-year events occurring in 1998–2002 and 2007–2014. The former event was most severe on the islands of O’ahu and Kaua’i while the latter event was most severe on Hawaiʻi Island. Within islands, we found different spatial patterns depending on leeward versus windward contrasts. Droughts have resulted in over $80 million in agricultural relief since 1996 and have increased wildfire risk, especially during El Niño years. In addition to providing the historical context needed to better understand future drought projections and to develop effective policies and management strategies to protect natural, cultural, hydrological, and agricultural resources, this work provides a framework for conducting drought analyses in other tropical island systems, especially those with a complex topography and strong climatic gradients. 

Abstract A dry-air intrusion induced by the tropopause folding split the deep cloud into two layers resulting in a shallow orographic cloud with a supercooled liquid cloud top at around −15°C and an ice cloud above it on 19 January 2017 during the Seeded and Natural Orographic Wintertime Clouds: The Idaho Experiment (SNOWIE). The airborne AgI seeding of this case was simulated by the WRF Weather Modification (WRF-WxMod) Model with different configurations. Simulations at different grid spacing, driven by different reanalysis data, using different model physics were conducted to explore the ability of WRF-WxMod to capture the properties of natural and seeded clouds. The detailed model–observation comparisons show that the simulation driven by ERA5 data, using Thompson–Eidhammer microphysics with 30% of the CCN climatology, best captured the observed cloud structure and supercooled liquid water properties. The ability of the model to correctly capture the wind field was critical for successful simulation of the seeding plume locations. The seeding plume features and ice number concentrations within them from the large-eddy simulations (LES) are in better agreement with observations than non-LES runs mostly due to weaker AgI dispersion associated with the finer grid spacing. Seeding effects on precipitation amount and impacted areas from LES seeding simulations agreed well with radar-derived values. This study shows that WRF-WxMod is able to simulate and quantify observed features of natural and seeded clouds given that critical observations are available to validate the model. Observation-constrained seeding ensemble simulations are proposed to quantify the AgI seeding impacts on wintertime orographic clouds. Significance Statement Recent observational work has demonstrated that the impact of airborne glaciogenic seeding of orographic supercooled liquid clouds is detectable and can be quantified in terms of the extra ground precipitation. This study aims, for the first time, to simulate this seeding impact for one well-observed case. The stakes are high: if the model performs well in this case, then seasonal simulations can be conducted with appropriate configurations after validations against observations, to determine the impact of a seeding program on the seasonal mountain snowpack and runoff, with more fidelity than ever. High–resolution weather simulations inherently carry uncertainty. Within the envelope of this uncertainty, the model compares very well to the field observations.