Ground- and excited-state properties of [Ru(tpy)(2)](2+), [Ru(tpy)(ttpy)](2+), and [Ru(ttpy)(2)](2+) (where tpy = 2,2':6',2″-terpyridine and ttpy = 4'-(4-methylphenyl)-2,2':6',2″-terpyridine) in room temperature acetonitrile have been investigated using linear absorption, electrochemical, and ultrafast transient pump-probe techniques. Spectroelectrochemistry was used to assign features observed in the transient spectra while single wavelength kinetics collected at a variety of probe wavelengths were used to monitor temporal evolution of the MLCT excited state. From these data, the excited-state lifetime of each complex was recovered and the rate limiting decay step was identified. In the bis-heteroleptic complex [Ru(tpy)(ttpy)](2+), photoexcitation to the (1)MLCT manifold generates both tpy-localized and ttpy-localized excited states. Accordingly, interligand electron transfer (ILET) from tpy-localized to the ttpy-localized (3)MLCT excited states is observable and the time scale has been measured to be 3 ps. For the homoleptic complex [Ru(tpy)(2)](2+), evidence for equilibration of the (3)MLCT excited-state population with the (3)MC has been observed and the time scale is reported at 2 ps.

Three new photoinduced electron donor-acceptor (D-A) systems are reported which juxtapose a Ru(II) excited-state donor with a bipyridinium acceptor via a conformationally active asymmetric aryl-substituted bipyridine ligand participating in the bridge between D and A. Across the series of complexes 1-3, steric bulk is sequentially added to tune the inter-ring dihedral angle theta between the bipyridine and the aryl substituent. Driving forces for photoinduced electron transfer (DeltaG(ET)) and back electron transfer (DeltaG(BET)) are reported based on electrochemical measurements of 1-3 as well as Franck-Condon analysis of emission spectra collected for three new donor model complexes 1'-3'. These preserve the substitution patterns on the aryl substituent in their respective D-A complexes but remove the bipyridinium acceptor. Both DeltaG(ET) and DeltaG(BET) are invariant to within 0.02 eV across the series. Upon visible photoexcitation of each of the D-A systems with approximately 100 fs laser pulses at 500 +/- 10 nm, an electron-transfer (ET) photoproduct is observed to form with a time constant of tau(ET) = 29 ps (1), 37 ps (2), and 57 ps (3). That ET remains relatively rapid throughout this series, even as steric bulk significantly increases the inter-ring dihedral angle theta, is attributed to the effects of ligand-based torsional dynamics driven by intraligand electron delocalization in the D*-A excited state manifold prior to ET. The lifetimes of the charge-separated states (tau(BET)) are also reported with tau(BET) = 98 ps (1), 217 ps (2), and 789 ps (3), representing a more than 8-fold increase across the series. This is attributed to reverse conformational dynamics in D(+)-A(-) driven by steric repulsions, which serves to minimize electronic coupling to the ground state. Steric control of ligand geometry and the range over which theta changes during conformational dynamics provides a new strategy to facilitate the formation and storage of charge-separated excited states.

Increasingly, drone-based photogrammetry has been used to measure size and body condition changes in marine megafauna. A broad range of platforms, sensors, and altimeters are being applied for these purposes, but there is no unified way to predict photogrammetric uncertainty across this methodological spectrum. As such, it is difficult to make robust comparisons across studies, disrupting collaborations amongst researchers using platforms with varying levels of measurement accuracy. Here we built off previous studies quantifying uncertainty and used an experimental approach to train a Bayesian statistical model using a known-sized object floating at the water’s surface to quantify how measurement error scales with altitude for several different drones equipped with different cameras, focal length lenses, and altimeters. We then applied the fitted model to predict the length distributions and estimate age classes of unknown-sized humpback whales Megaptera novaeangliae, as well as to predict the population-level morphological relationship between rostrum to blowhole distance and total body length of Antarctic minke whales Balaenoptera bonaerensis. This statistical framework jointly estimates errors from altitude and length measurements from multiple observations and accounts for altitudes measured with both barometers and laser altimeters while incorporating errors specific to each. This Bayesian model outputs a posterior predictive distribution of measurement uncertainty around length measurements and allows for the construction of highest posterior density intervals to define measurement uncertainty, which allows one to make probabilistic statements and stronger inferences pertaining to morphometric features critical for understanding life history patterns and potential impacts from anthropogenically altered habitats.

Photophysics of the MLCT excited-state of [Ru(bpy)(tpy)(OH2)](2+) (1) and [Ru(bpy)(tpy)(OD2)](2+) (2) (bpy = 2,2'-bipyridine and tpy = 2,2':6',2″-terpyridine) have been investigated in room-temperature H2O and D2O using ultrafast transient pump-probe spectroscopy. An inverse isotope effect is observed in the ground-state recovery for the two complexes. These data indicate control of excited-state lifetime via a pre-equilibrium between the (3)MLCT state that initiates H-bond dynamics with the solvent and the (3)MC state that serves as the principal pathway for nonradiative decay.

Quantifying the cumulative effects of stressors on individuals and populations can inform the development of effective management and conservation strategies. We developed a Bayesian state–space model to assess the effects of multiple stressors on individual survival and reproduction. In the model, stressor effects on vital rates are mediated by changes in underlying health, allowing for the comparison of effect sizes while accounting for intrinsic factors that might affect an individual's vulnerability and resilience. We applied the model to a 50‐year dataset of sightings, calving events and stressor exposure of critically endangered North Atlantic right whales Eubalaena glacialis. The viability of this population is threatened by a complex set of stressors, including vessel strikes, entanglement in fishing gear and fluctuating prey availability. We estimated that blunt and deep vessel strike injuries and severe entanglement injuries had the largest effect on the health of exposed individuals, reinforcing the urgent need for mitigation measures. Prey abundance had a smaller but protracted effect on health across individuals, and estimated long‐term trends in survival and reproduction followed the trend of the prey index, highlighting that long‐term ecosystem‐based management strategies are also required. Our approach can be applied to quantify the effects of multiple stressors on any long‐lived species where suitable indicators of health and long‐term monitoring data are available.

Body condition is a crucial and indicative measure of an animal’s fitness, reflecting overall foraging success, habitat quality, and balance between energy intake and energetic investment toward growth, maintenance, and reproduction. Recently, drone-based photogrammetry has provided new opportunities to obtain body condition estimates of baleen whales in one, two or three dimensions (1D, 2D, and 3D, respectively) – a single width, a projected dorsal surface area, or a body volume measure, respectively. However, no study to date has yet compared variation among these methods and described how measurement uncertainty scales across these dimensions. This associated uncertainty may affect inference derived from these measurements, which can lead to misinterpretation of data, and lack of comparison across body condition measurements restricts comparison of results between studies. Here we develop a Bayesian statistical model using known-sized calibration objects to predict the length and width measurements of unknown-sized objects (e.g., a whale). We use the fitted model to predict and compare uncertainty associated with 1D, 2D, and 3D photogrammetry-based body condition measurements of blue, humpback, and Antarctic minke whales – three species of baleen whales with a range of body sizes. The model outputs a posterior predictive distribution of body condition measurements and allows for the construction of highest posterior density intervals to define measurement uncertainty. We find that uncertainty does not scale linearly across multi-dimensional measurements, with 2D and 3D uncertainty increasing by a factor of 1.45 and 1.76 compared to 1D, respectively. Each standardized body condition measurement is highly correlated with one another, yet 2D body area index (BAI) accounts for potential variation along the body for each species and was the most precise body condition metric. We hope this study will serve as a guide to help researchers select the most appropriate body condition measurement for their purposes and allow them to incorporate photogrammetric uncertainty associated with these measurements which, in turn, will facilitate comparison of results across studies.

Climate change is a global phenomenon, yet impacts on resource availability to predators may be spatially and temporally diverse and asynchronous. As capital breeders, whales are dependent on dense, predictable prey resources during foraging seasons. An Unusual Mortality Event (UME) of Eastern North Pacific (ENP) gray whales (Eschrichtius robustus) was declared in 2019 due to a dramatic rise in stranded animals, many emaciated. Climate change impacts may have affected prey availability on the primary foraging grounds of ENP gray whales (~20,000 individuals) in the Arctic and sub-Arctic region and in coastal habitats between northern California, USA and British Columbia, Canada where a small sub-group of ENP whales called the Pacific Coast Feeding Group (PCFG; ~230 individuals) forages. To investigate variability of gray whale body condition relative to changing ocean conditions, we compare two datasets of gray whale aerial photogrammetry images collected via Unoccupied Aircraft Systems (UAS) on the ENP wintering grounds in San Ignacio Lagoon, Mexico (SIL; n=111) and on the PCFG feeding grounds in Oregon, USA (n=72) over the same three-year period (2017–2019). We document concurrent body condition improvement of PCFG whales in Oregon while body condition of whales in SIL declined. This result indicates that the UME may have affected ENP whales due to reduced energetic gain on some Arctic/sub-Arctic foraging grounds, while PCFG whales are recovering from poor prey conditions during the NE Pacific marine heatwave event of 2014–2016. Surprisingly, we found that PCFG whales in Oregon had significantly worse body condition than whales in SIL, even when accounting for year and phenology. We derive support for this unexpected finding via photogrammetry analysis of opportunistic aerial images of gray whales on Arctic foraging grounds (n=18) compared to PCFG whales in Oregon (n=30): the body condition of PCFG whales was significantly lower (t=2.96, p=0.005), which may cause PCFG whales to have reduced reproductive capacity or resilience to environmental perturbations compared to ENP whales. Overall, our study elucidates divergent gray whale body condition across sub-groups and time, and we demonstrate the value of UAS to effectively monitor and identify the physiological response of whales to climate change.

Compound identification by liquid chromatography-mass spectrometry (LC-MS) is a tedious process, mainly because authentic standards must be run on a user’s system to be able to confidently reject a potential identity from its retention time and mass spectral properties. Instead, it would be preferable to use shared retention time/index data to narrow down the identity, but shared data cannot be used to reject candidates with an absolute level of confidence because the data are strongly affected by differences between HPLC systems and experimental conditions. However, a technique called “retention projection” was recently shown to account for many of the differences. In this manuscript, we discuss an approach to calculate appropriate retention time tolerance windows for projected retention times, potentially making it possible to exclude candidates with an absolute level of confidence, without needing to have authentic standards of each candidate on hand. In a range of multi-segment gradients and flow rates run among seven different labs, the new approach calculated tolerance windows that were significantly more appropriate for each retention projection than global tolerance windows calculated for retention projections or linear retention indices. Though there were still some small differences between the labs that evidently were not taken into account, the calculated tolerance windows only needed to be relaxed by 50% to make them appropriate for all labs. Even then, 42% of the tolerance windows calculated in this study without standards were narrower than those required by WADA for positive identification, where standards must be run contemporaneously.