Adaptive patch foraging in deep reinforcement learning agents

Patch foraging is one of the most heavily studied behavioral optimization challenges in biology. However, despite its importance to biological intelligence, this behavioral optimization problem is understudied in artificial intelligence research. Patch foraging is especially amenable to study given that it has a known optimal solution, which may be difficult to discover given current techniques in deep reinforcement learning. Here, we investigate deep reinforcement learning agents in an ecological patch foraging task. For the first time, we show that machine learning agents can learn to patch forage adaptively in patterns similar to biological foragers, and approach optimal patch foraging behavior when accounting for temporal discounting. Finally, we show emergent internal dynamics in these agents that resemble single-cell recordings from foraging non-human primates, which complements experimental and theoretical work on the neural mechanisms of biological foraging. This work suggests that agents interacting in complex environments with ecologically valid pressures arrive at common solutions, suggesting the emergence of foundational computations behind adaptive, intelligent behavior in both biological and artificial agents.Comment: Published in Transactions on Machine Learning Research (TMLR). See: https://openreview.net/pdf?id=a0T3nOP9s

Low-Tech Riparian and Wet Meadow Restoration Increases Vegetation Productivity and Resilience Across Semiarid Rangelands

Restoration of riparian and wet meadow ecosystems in semiarid rangelands of the western United States is a high priority given their ecological and hydrological importance in the region. However, traditional restoration approaches are often intensive and costly, limiting the extent over which they can be applied. Practitioners are increasingly trying new restoration techniques that are more cost‐effective, less intensive, and can more practically scale up to the scope of degradation. Unfortunately, practitioners typically lack resources to undertake outcome‐based evaluations necessary to judge the efficacy of these techniques. In this study, we use freely available, satellite remote sensing to explore changes in vegetation productivity (normalized difference vegetation index) of three distinct, low‐tech, riparian and wet meadow restoration projects. Case studies are presented that range in geographic location (Colorado, Oregon, and Nevada), restoration practice (Zeedyk structures, beaver dam analogs, and grazing management), and time since implementation. Restoration practices resulted in increased vegetation productivity of up to 25% and increased annual persistence of productive vegetation. Improvements in productivity with time since restoration suggest that elevated resilience may further enhance wildlife habitat and increase forage production. Long‐term, documented outcomes of conservation are rare; we hope our findings empower practitioners to further monitor and explore the use of low‐tech methods for restoration of ecohydrologic processes at meaningful spatial scales

The Effects of Ultra-Long-Range Flights on the Alertness and Performance of Aviators

This investigation assessed the impact of ultra-long-range (ULR) simulator flights, departing either in the morning or late evening, on the alertness and performance of 17 commercial aviators. Immediately prior to and throughout each flight, alertness and performance were assessed via a computerized test of sustained attention, subjective questionnaires, and "hand-flying" tasks. There were fatigue-related effects on the majority of assessments, and the nature of these effects was consistent across the vigilance and self-report measures. However, the operational "hand-flying" manuevers proved insensitive to the impact of fatigue probably due to procedural factors. Regardless, the results of the present study suggest that fatigue associated with prolonged wakefulness in ULR flight operations will interact with flight schedules due to circadian and homeostatic influences. In this study, the pilots departing at night were at a greater initial disadvantage (during cruise) than pilots who departed earlier in the day; whereas those who departed earlier tended to be most impaired towards the end of the flight prior to landing. In real-world operations, airlines should consider the ramifications of flight schedules and what is known about human sleep and circadian rhythms to optimize safety

Seeing plants as never before

Authors of the article assert that imaging has long supported our ability to understand the inner life of plants, their development, and response to a dynamic environment. The purpose of this review was to provide the scientific community with an overview of current imaging methods, which rely variously on either nuclear magnetic resonance (NMR), mass spectrometry (MS) or infrared (IR) spectroscopy, and to present some examples of their application in order to illustrate their utility

Seasonal patterns and controls on net ecosystem CO2 exchange in a boreal peatland complex

We measured seasonal patterns of net ecosystem exchange (NEE) of CO2 in a diverse peatland complex underlain by discontinuous permafrost in northern Manitoba, Canada, as part of the Boreal Ecosystems Atmosphere Study (BOREAS). Study sites spanned the full range of peatland trophic and moisture gradients found in boreal environments from bog (pH 3.9) to rich fen (pH 7.2). During midseason (July‐August, 1996), highest rates of NEE and respiration followed the trophic sequence of bog (5.4 to −3.9 μmol CO2 m−2 s−1) \u3c poor fen (6.3 to −6.5 μmol CO2 m−2 s−1) \u3c intermediate fen (10.5 to −7.8 μmol CO2 m−2 s−1) \u3c rich fen (14.9 to −8.7 μmol CO2m−2 s−1). The sequence changed during spring (May‐June) and fall (September‐October) when ericaceous shrub (e.g., Chamaedaphne calyculata) bogs and sedge (Carex spp.) communities in poor to intermediate fens had higher maximum CO2 fixation rates than deciduous shrub‐dominated (Salix spp. and Betula spp.) rich fens. Timing of snowmelt and differential rates of peat surface thaw in microtopographic hummocks and hollows controlled the onset of carbon uptake in spring. Maximum photosynthesis and respiration were closely correlated throughout the growing season with a ratio of approximately 1/3 ecosystem respiration to maximum carbon uptake at all sites across the trophic gradient. Soil temperatures above the water table and timing of surface thaw and freeze‐up in the spring and fall were more important to net CO2 exchange than deep soil warming. This close coupling of maximum CO2 uptake and respiration to easily measurable variables, such as trophic status, peat temperature, and water table, will improve models of wetland carbon exchange. Although trophic status, aboveground net primary productivity, and surface temperatures were more important than water level in predicting respiration on a daily basis, the mean position of the water table was a good predictor (r2 = 0.63) of mean respiration rates across the range of plant community and moisture gradients. Q10 values ranged from 3.0 to 4.1 from bog to rich fen, but when normalized by above ground vascular plant biomass, the Q10 for all sites was 3.3

Identification of SARS-CoV-2-induced pathways reveals drug repurposing strategies.

The global outbreak of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) necessitates the rapid development of new therapies against coronavirus disease 2019 (COVID-19) infection. Here, we present the identification of 200 approved drugs, appropriate for repurposing against COVID-19. We constructed a SARS-CoV-2-induced protein network, based on disease signatures defined by COVID-19 multiomics datasets, and cross-examined these pathways against approved drugs. This analysis identified 200 drugs predicted to target SARS-CoV-2-induced pathways, 40 of which are already in COVID-19 clinical trials, testifying to the validity of the approach. Using artificial neural network analysis, we classified these 200 drugs into nine distinct pathways, within two overarching mechanisms of action (MoAs): viral replication (126) and immune response (74). Two drugs (proguanil and sulfasalazine) implicated in viral replication were shown to inhibit replication in cell assays. This unbiased and validated analysis opens new avenues for the rapid repurposing of approved drugs into clinical trials