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Locomotion is an important behavior in the life history of animals and is characterized by discrete gaits, which may be adopted for optimal energetic efficiency, fatigue resistance, or maneuverability. We evaluated the kinematics and electromyography of Bluegill Sunfish (Lepomis macrochirus) swimming at different gaits to evaluate which factors might influence gait choice. When placed in the flume, Bluegill adopted a steady swimming gait until speeds reached 2.0 BL/s. When swimming volitionally, either in a laboratory pool or the field, Bluegill adopted an intermittent swimming gait (burst phase followed by a glide phase) and swam at average speeds of 1.0-1.3 BL/s. No statistical relationship was found between the kinematics of the burst and glide phases in either the lab or the field, so the phases were considered uncoupled. Furthermore, since the kinematics (tailbeat frequency, glide-duty factor) of lab and field volitional swimming were statistically identical, the EMGs of volition swimming in the lab likely reflect field effort. When relativized to volitional swimming speeds, the EMG intensities for both gaits were statistically identical. These results suggest that intermittent swimming may not reflect a strategy for energetic efficiency. Instead, the decoupling between the burst and glide phase may improve maneuverability, since 75% of 3D tracked intermittent swimming bouts (n=129) in the field involved a directional change. Although previous research suggests that intermittent swimming may also provide fatigue resistance, we hypothesize that intermittent swimming evolved in Bluegill as an adaptive gait for navigating their densely vegetated habitat. 

Locomotion that is driven by muscle activity dominates the daily energetic expenditure in most animals. In fish, routine propulsion when swimming at low, steady speeds and at various gaits is powered primarily by red, oxidative muscle. In Bluegill Sunfish (Lepomis macrochirus), swimming speed is thought to reflect the most energetically efficient gait type. Since field observations of Bluegill suggest that intermittent swimming is the preferred gait, we hypothesized that intermittent locomotion would be more energetically efficient than steady swimming. To test this hypothesis, we used electromyography to analyze muscle activation intensity of Bluegill swimming steadily in a flume and volitionally intermittently in a pool. In the flume, muscle activation intensity and tailbeat frequency increased as a function of speed. However, when swimming volitionally in the pool, muscle activation intensity varied relative to average velocity and tailbeat frequency was lower than in the flume at the same velocities. Although we expected muscle activation intensity to be higher when steady swimming at a given speed, ~48% of fish (n=11) had higher muscle activation intensities when swimming volitionally when compared at the same speed in the flume. Also, there was a positive relationship between speed and glide duration, but there was no relationship between speed and muscle activation intensity when swimming intermittently. Instead, intermittent swimming may lower fatigue and enhance maneuverability, rather than increase energetic efficiency. 

Locomotion is vital to the survival and fitness of animals and dominates daily energy budgets. The main energy consuming process of locomotion is the muscle activity needed to maintain stability or generate propulsive forces. In fish, the speed of swimming is thought to depend on the gait type, which may reflect an energetically efficient locomotory behavior. Bluegill Sunfish (Lepomis macrochirus) exhibit either steady or intermittent (burst-coast) gaits when swimming in the field, but whether these gaits differ in their energetic efficiency is unknown. We analyzed the electromyography (EMG) of oxidative muscle in Bluegill swimming at low velocities to determine if steady swimming is more or less energetically efficient than intermittent swimming. EMG data were acquired using bipolar fine wire electrodes implanted into oxidative musculature at 2/3 tail length. Steady swimming EMGs were recorded in a flume (fish treadmill) at incrementally increasing speeds relative to body length, until nonoxidative muscle was recruited. As speed increased, EMG intensity increased, which corresponds to increased muscle recruitment. Fish reached maximum EMG intensity (100% oxidative muscle capacity) between 1.75 - 2.25 BL/s. Intermittent swimming EMGs were recorded while the fish swam volitionally in a pool. The burst phase consisted of 2-3 tailbeats, followed by a coast phase duration of 1 second or less. Based on preliminary results, fish in the pool swam at an average of 62.1% (n = 10) of their maximum oxidative capacity. When intermittently swimming, muscle activity was 37.9% more efficient than steady swimming at similar speeds. This demonstrates that when swimming volitionally Bluegill choose the most energetically effective gait. However, further analysis is needed to determine how individual variation affects swimming performance. Continued comparison of these methods of locomotion will broaden the understanding of energy decisions that fish make. These results suggest that intermittent swimming is the more energetically efficient form of aquatic locomotion. This work is supported by NSF grant award number 2135851. 

The growing number of multi-epoch optical and infrared sky surveys are uncovering unprecedented numbers of new variable stars, of an increasing number of types. The short interval between observations in adjacent near-infrared filters in the UKIDSS Galactic Plane Survey (UGPS) allows for the discovery of variability on the time-scale of minutes. We report on the nature of one such object, through the use of optical spectroscopy, time series photometry, and targeted X-ray observations. We propose that UGPS J194310.32+183851.8 is a magnetic cataclysmic variable star of novel character, probably featuring a longer than average spin period and an orbital period likely to be shorter than the period gap (i.e. Porb < 2 h). We reason that the star is likely a member of the short-period intermediate-polar subclass that exists below this period boundary, but with the additional feature that system’s spectral energy distribution is fainter and redder than other members of the group.

 

Climate change has lengthened wildfire seasons and transformed fire regimes throughout the world. Thus, capturing fuel and fire dynamics is critical for projecting Earth system processes in warmer and drier future. Recent advances in fire regime modeling have linked land surface models with fire behavior models. Such models often rely on fine surface fuels to drive fire behavior and effects, and while many models can simulate processes that control how these fuels change through time (i.e., fine fuel accumulation), fuel loading estimates remain highly uncertain, largely due to uncertainties in the algorithms controlling decomposition. Uncertainties are often amplified in climate change forecasts when initial conditions and feedbacks are not well represented. The goal of this review is to highlight fine fuel decomposition as a key uncertainty in model systems. We review the current understanding of mechanisms controlling decomposition, describe how they are incorporated into models, and evaluate the uncertainties associated with different approaches. We also use three state‐of‐the‐art land surface fire regime models to demonstrate the sensitivity of decomposition and subsequent wildfire projections to both parameter and model structure uncertainty and show that sensitivity can increase substantially under future climate warming. Given that many of the governing decomposition equations are based on individual case studies from a single location, and because key parameters are often hard coded, critical uncertainties are currently ignored. It is essential to be transparent about these uncertainties as the domain of land surface models is expanded to include the evaluation of future wildfire regimes.