Ozone profile measurements at McMurdo Station Antarctica during the spring of 1987

During the Antarctic spring of 1986, 33 ozone soundings were conducted from McMurdo Station. These data indicated that the springtime decrease in ozone occurred rapidly between the altitudes of 12 and 20 km. During 1987, these measurements were repeated with 50 soundings between 29 August and 9 November. Digital conversions of standard electrochemical cell ozonesondes were again employed. The ozonesonde pumps were individually calibrated for flow rate as the high altitude performance of these pumps have been in question. While these uncertainties are not large in the region of the ozone hole, they are significant at high altitude and apparently resulted in an underestimate of total ozone of about 7 percent (average) as compared to the Total Ozone Mapping Spectrometer (TOMS) in 1986, when the flow rate recommended by the manufacturer was used. At the upper altitudes (approx. 30 km) the flow rate may be overestimated by as much as 15 percent using recommended values (see Harder et al., The UW Digital Ozonesonde: Characteristics and Flow Rate Calibration, poster paper, this workshop). These upper level values are used in the extrapolation, at constant mixing ratio, required to complete the sounding for total ozone. The first sounding was on 29 August, prior to major ozone depletion, when 274 DU total ozone (25 DU extrapolated) was observed. By early October total ozone had decreased to the 150 DU range; it then increased during mid-October owing to motion of the vortex and returned to a value of 148 DU (29 DU extrapolated) on 27 October

MISSISSIPPI SANDHILL CRANE CONSERVATION UPDATE 2017-2019

To manage crane habitat on the Mississippi Sandhill Crane National Wildlife Refuge during 2017-2019, 5,822 ha were treated with prescribed burns, 648 ha of woody vegetation were removed, 97 ha of invasive plants were chemically treated, and 1.2 ha of crops were planted. Mississippi sandhill crane (Grus canadensis pulla) use responded to habitat treatment; 348 of 349 VHF radio locations were in treated areas. There were 316 target predators removed. Eighteen captive-reared juveniles were acclimated and released. We detected an average of 38 nests per year, including a record 40 nests in 2019. Fifteen chicks fledged in 2019, a 25% increase over numbers fledging during 2014-2016. The December 2019 population was 138 cranes, up 7% from the previous 3 years, including 98 banded. The total home area used by the crane population during the period was 25,552 ha

DRIVERS OF ANNUAL FLEDGING IN THE MISSISSIPPI SANDHILL CRANE POPULATION 1991-2018

We studied trends in nesting, number of chicks fledged annually, and their environmental and biotic drivers in the wild population of Mississippi sandhill cranes (Grus canadensis pulla) on Mississippi Sandhill Crane National Wildlife Refuge during 1991-2018. Population size, number of nests, and number of chicks fledged annually increased slowly but significantly over the course of the study. Increases in population size were related to both number of wild-reared chicks fledged annually and number of captive-reared chicks released each year, but wild-reared chicks had significantly higher survivorship than captive-reared chicks. Hurricanes transiently raised mortality rates but only Hurricane Katrina caused a sustained population decline among adult birds. Total population size was positively related to precipitation during the nesting season, while number of chicks fledged annually was negatively related to annual number of extreme heat days and estimates of bobcat (Lynx rufus) occurrence. Cranes displayed high philopatry to their initial nest location and nested repeatedly in the same general home range regardless of the time since an area had last been treated by prescribed burning. Number of chicks fledged annually occurred with approximately equal frequency across management units burned at different times prior to nesting. The results indicate that both biotic and abiotic factors drive population dynamics on the refuge and suggest that additional attention to prescribed burns, predator removal, and behavioral conditioning of captive-reared birds prior to release may promote faster population growth and establishment of a self-sustaining wild population in the future

NESTING ACTIVITY BUDGETS AND ANTIPREDATOR BEHAVIORS OF MISSISSIPPI SANDHILL CRANES

We studied activity budgets and antipredator behaviors of Mississippi sandhill cranes (Grus canadensis pulla) to determine if parental behavior influenced nest outcomes. We used infrared motion-activated cameras to capture behavioral sequences from 21 nests over a 2-year period. Overall activity budgets were similar among crane pairs regardless of nest outcome. Specific activity patterns did predict nest outcomes; pairs at unsuccessful nests spent more time away from the nest and more time manipulating nest contents than successful pairs, while pairs at nests that were lost to predation cooperated poorly and started the nest a month later on average than successful nests. Wild-reared birds gave more agonistic displays toward potential threats than captive-reared birds, but both wild- and captive-reared birds successfully defended nests from potential predators. The results suggest that behavior patterns of nesting pairs can be used to predict likely nest outcome, and that birds differ in their ability to defend nests from predators. We suggest that training in antipredator behavior during captive rearing may increase behavioral competence and reduce losses to nest predators

Understanding Evolutionary Impacts of Seasonality: An Introduction to the Symposium

Seasonality is a critically important aspect of environmental variability, and strongly shapes all aspects of life for organisms living in highly seasonal environments. Seasonality has played a key role in generating biodiversity, and has driven the evolution of extreme physiological adaptations and behaviors such as migration and hibernation. Fluctuating selection pressures on survival and fecundity between summer and winter provide a complex selective landscape, which can be met by a combination of three outcomes of adaptive evolution: genetic polymorphism, phenotypic plasticity, and bet-hedging. Here, we have identified four important research questions with the goal of advancing our understanding of evolutionary impacts of seasonality. First, we ask how characteristics of environments and species will determine which adaptive response occurs. Relevant characteristics include costs and limits of plasticity, predictability, and reliability of cues, and grain of environmental variation relative to generation time. A second important question is how phenological shifts will amplify or ameliorate selection on physiological hardiness. Shifts in phenology can preserve the thermal niche despite shifts in climate, but may fail to completely conserve the niche or may even expose life stages to conditions that cause mortality. Considering distinct environmental sensitivities of life history stages will be key to refining models that forecast susceptibility to climate change. Third, we must identify critical physiological phenotypes that underlie seasonal adaptation and work toward understanding the genetic architectures of these responses. These architectures are key for predicting evolutionary responses. Pleiotropic genes that regulate multiple responses to changing seasons may facilitate coordination among functionally related traits, or conversely may constrain the expression of optimal phenotypes. Finally, we must advance our understanding of how changes in seasonal fluctuations are impacting ecological interaction networks. We should move beyond simple dyadic interactions, such as predator prey dynamics, and understand how these interactions scale up to affect ecological interaction networks. As global climate change alters many aspects of seasonal variability, including extreme events and changes in mean conditions, organisms must respond appropriately or go extinct. The outcome of adaptation to seasonality will determine responses to climate change

Host Plant Adaptation in Drosophila mettleri Populations

The process of local adaptation creates diversity among allopatric populations, and may eventually lead to speciation. Plant-feeding insect populations that specialize on different host species provide an excellent opportunity to evaluate the causes of ecological specialization and the subsequent consequences for diversity. In this study, we used geographically separated Drosophila mettleri populations that specialize on different host cacti to examine oviposition preference for and larval performance on an array of natural and non-natural hosts (eight total). We found evidence of local adaptation in performance on saguaro cactus (Carnegiea gigantea) for populations that are typically associated with this host, and to chemically divergent prickly pear species (Opuntia spp.) in a genetically isolated population on Santa Catalina Island. Moreover, each population exhibited reduced performance on the alternative host. This finding is consistent with trade-offs associated with adaptation to these chemically divergent hosts, although we also discuss alternative explanations for this pattern. For oviposition preference, Santa Catalina Island flies were more likely to oviposit on some prickly pear species, but all populations readily laid eggs on saguaro. Experiments with non-natural hosts suggest that factors such as ecological opportunity may play a more important role than host plant chemistry in explaining the lack of natural associations with some hosts

Developing a robust geochemical and reactive transport model to evaluate possible sources of arsenic at the CO2 sequestration natural analog site in Chimayo, New Mexico

Migration of carbon dioxide (CO2) from deep storage formations into shallow drinking water aquifers is a possible system failure related to geologic CO2 sequestration. A CO2 leak may cause mineral precipitation/ dissolution reactions, changes in aqueous speciation, and alteration of pH and redox conditions leading to potential increases of trace metal concentrations above EPA National Primary Drinking Water Standards. In this study, the Chimayo site (NM) was examined for site-specific impacts of shallow groundwater interacting with CO2 from deep storage formations. Major ion and trace element chemistry for the site have been previously studied. This work focuses on arsenic (As), which is regulated by the EPA under the Safe Drinking Water Act and for which some wells in the Chimayo area have concentrations higher than the maximum contaminant level (MCL). Statistical analysis of the existing Chimayo groundwater data indicates that As is strongly correlated with trace metals U and Pb indicating that their source may be from the same deep subsurface water. Batch experiments and materials characterization, such as: X-ray diffraction (XRD), scanning electron microscopy (SEM), and synchrotron micro X-ray fluorescence (#2;-XRF), were used to identify As association with Fe-rich phases, such as clays or oxides, in the Chimayo sediments as the major factor controlling As fate in the subsurface. Batch laboratory experiments with Chimayo sediments and groundwater show that pH decreases as CO2 is introduced into the system and buffered by calcite. The introduction of CO2 causes an immediate increase in As solution concentration, which then decreases over time. A geochemical model was developed to simulate these batch experiments and successfully predicted the pH drop once CO2 was introduced into the experiment. In the model, sorption of As to illite, kaolinite and smectite through surface complexation proved to be the key reactions in simulating the drop in As concentration as a function of time in the batch experiments. Based on modeling, kaolinite precipitation is anticipated to occur during the experiment, which allows for additional sorption sites to form with time resulting in the slow decrease in As concentration. This mechanism can be viewed as trace metal “scavenging” due to sorption caused secondary mineral precipitation. Since deep geologic transport of these trace metals to the shallow subsurface by brine or CO2 intrusion is critical to assessing environmental impacts, the effective retardation of trace metal transport is an important parameter to estimate and it is dependent on multiple coupled reactions. At the field scale, As mobility is retarded due to the influence of sorption reactions, which can affect environmental performance assessment studies of a sequestration site

Comparison of bio-inspired algorithms applied to the coordination of mobile robots considering the energy consumption

Many applications, related to autonomous mobile robots, require to explore in an unknown environment searching for static targets, without any a priori information about the environment topology and target locations. Targets in such rescue missions can be fire, mines, human victims, or dangerous material that the robots have to handle. In these scenarios, some cooperation among the robots is required for accomplishing the mission. This paper focuses on the application of different bio-inspired metaheuristics for the coordination of a swarm of mobile robots that have to explore an unknown area in order to rescue and handle cooperatively some distributed targets. This problem is formulated by first defining an optimization model and then considering two sub-problems: exploration and recruiting. Firstly, the environment is incrementally explored by robots using a modified version of ant colony optimization. Then, when a robot detects a target, a recruiting mechanism is carried out to recruit a certain number of robots to deal with the found target together. For this latter purpose, we have proposed and compared three approaches based on three different bio-inspired algorithms (Firefly Algorithm, Particle Swarm Optimization, and Artificial Bee Algorithm). A computational study and extensive simulations have been carried out to assess the behavior of the proposed approaches and to analyze their performance in terms of total energy consumed by the robots to complete the mission. Simulation results indicate that the firefly-based strategy usually provides superior performance and can reduce the wastage of energy, especially in complex scenarios

A complete set of nascent transcription rates for yeast genes

The amount of mRNA in a cell is the result of two opposite reactions: transcription and mRNA degradation. These reactions are governed by kinetics laws, and the most regulated step for many genes is the transcription rate. The transcription rate, which is assumed to be exercised mainly at the RNA polymerase recruitment level, can be calculated using the RNA polymerase densities determined either by run-on or immunoprecipitation using specific antibodies. The yeast Saccharomyces cerevisiae is the ideal model organism to generate a complete set of nascent transcription rates that will prove useful for many gene regulation studies. By combining genomic data from both the GRO (Genomic Run-on) and the RNA pol ChIP-on-chip methods we generated a new, more accurate nascent transcription rate dataset. By comparing this dataset with the indirect ones obtained from the mRNA stabilities and mRNA amount datasets, we are able to obtain biological information about posttranscriptional regulation processes and a genomic snapshot of the location of the active transcriptional machinery. We have obtained nascent transcription rates for 4,670 yeast genes. The median RNA polymerase II density in the genes is 0.078 molecules/kb, which corresponds to an average of 0.096 molecules/gene. Most genes have transcription rates of between 2 and 30 mRNAs/hour and less than 1% of yeast genes have >1 RNA polymerase molecule/gene. Histone and ribosomal protein genes are the highest transcribed groups of genes and other than these exceptions the transcription of genes is an infrequent phenomenon in a yeast cell

Functional Maps of Protein Complexes from Quantitative Genetic Interaction Data

Recently, a number of advanced screening technologies have allowed for the comprehensive quantification of aggravating and alleviating genetic interactions among gene pairs. In parallel, TAP-MS studies (tandem affinity purification followed by mass spectroscopy) have been successful at identifying physical protein interactions that can indicate proteins participating in the same molecular complex. Here, we propose a method for the joint learning of protein complexes and their functional relationships by integration of quantitative genetic interactions and TAP-MS data. Using 3 independent benchmark datasets, we demonstrate that this method is >50% more accurate at identifying functionally related protein pairs than previous approaches. Application to genes involved in yeast chromosome organization identifies a functional map of 91 multimeric complexes, a number of which are novel or have been substantially expanded by addition of new subunits. Interestingly, we find that complexes that are enriched for aggravating genetic interactions (i.e., synthetic lethality) are more likely to contain essential genes, linking each of these interactions to an underlying mechanism. These results demonstrate the importance of both large-scale genetic and physical interaction data in mapping pathway architecture and function