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A mathematical technique is developed to investigate physicochemical property prediction of solution mixtures from the corresponding properties of the pure dissolved systems, as is often expressed in empirical ‘mixing rules’ such as those of Young and of Zdanovskii. A systematic method to distinguish between the inherent characteristics of such rules is needed because experimental studies have proved indecisive. Sound mixing rules must be found to support current efforts in thermodynamic modelling where conventional approaches like the Pitzer equations lack robustness. Density differences relative to pure water, osmotic coefficients and heat capacities are investigated with mixtures including NaCl + MgCl2(aq) and NaCl + Na2SO4(aq) as specific examples representing common-anion and common-cation asymmetric strong electrolyte solutions respectively. Water activity curves for hydrochloric acid and the alkali metal chloride solutions are also considered. The results confirm that, at the present state of the art, differences between mixing rules are for the most part insignificant at 25 °C, being about the same or less than would be expected from experimental uncertainty. As the predicted differences are even smaller at higher temperature, it can be posited that all reasonably well-established mixing rules in the literature will give approximately equivalent and satisfactory predictions of solution properties under superambient conditions. This is particularly important since the effects of temperature on the magnitude of ternary interactions are not well known from experiment.

The Joint Expert Speciation System (JESS) is presently the world’s largest single source of thermodynamic information about aqueous electrolyte solutions. Comprehensive and up-to-date thermodynamic models undoubtedly require such large databases but size alone, without well-designed data structures and good data assessment procedures, is insufficient. Computer databases are not like tables in a book; they should be constantly evolving, easy to search and specifically designed for processing by large-scale, automated facilities, including tests for careless errors and internal consistency. The maxim ‘garbage in, garbage out’ is today even more relevant than ever: without expert analysis and critical judgement, limitless storage capacity and computational power are likely just to add confusion rather than achieve meaningful insights into chemical problems. Several examples are provided to demonstrate the application of new methodologies to problems of differing size and complexity including harmonization of aqueous reaction equilibrium constants for more than 50,000 chemical species, systematic critical assessment of the thermophysical properties of aqueous glycine and its solid–liquid equilibria over wide ranges of temperature and pressure, and development of standalone programs for users lacking training in chemical speciation problems. Extension of these methods to new applications is discussed.

We report the speeds of sound in liquid toluene (methylbenzene) measured using double-path pulse-echo apparatus independently at The University of Western Australia (UWA) and Imperial College London (ICL). The UWA data were measured at temperatures between (306 and 423) K and at pressures up to 65 MPa with standard uncertainties of between (0.02 and 0.04)%. At ICL, measurements were made at temperatures between (283.15 and 473.15) K and at pressures up to 390 MPa with standard uncertainty of 0.06%. By means of thermodynamic integration, the measured sound-speed data were combined with initial density and isobaric heat capacity values obtained from extrapolated experimental data to derive a comprehensive set of thermodynamic properties of liquid toluene over the full measurement range. Extensive uncertainty analysis was performed by studying the response of derived properties to constant and dynamic perturbations of the sound-speed surface, as well as the initial density and heat capacity values. The relative expanded uncertainties at 95% confidence of derived density, isobaric heat capacity, isobaric expansivity, isochoric heat capacity, isothermal compressibility, isentropic compressibility, thermal pressure coefficient and internal pressure were estimated to be (0.2, 2.2, 1.0, 2.6, 0.6, 0.2, 1.0 and 2.7)%, respectively. Due to their low uncertainty, these data and derived properties should be well suited for developing a new and improved fundamental Helmholtz equation of state for toluene.

Knowledge of thermodynamic properties of aqueous solutions of CO 2 is crucial for various applications including climate science, carbon capture, utilisation and storage (CCUS), and seawater desalination. However, there is a lack of reliable experimental data, and the equation of state (EOS) predictions are not reliable, particularly for sound speeds in low CO 2 concentrations typical of water resources. For this reason, we have measured speeds of sound in three different aqueous solutions containing CO 2 . We report speeds of sound in the single-phase liquid region for binary mixtures of water and CO 2 for mole fractions of CO 2 of 0.0118, 0.0066 and 0.0015 at temperatures from 273.15 K to 313.15 K and at pressures up to 50 MPa, measured using a dual-path pulse-echo apparatus. The relative standard uncertainties of the sound speeds are 0.05 %, 0.03 % and 0.01 % at 0.0118, 0.0066 and 0.0015 CO 2 mole fractions, respectively. The change in sound speeds as functions of composition, pressure and temperature are analysed in this study. We find that dissolution of CO 2 in water increases its sound speeds at all conditions, with the greatest increase occurring at the highest mole fractions of CO 2 . Our sound speed data agree well with the limited available experimental data in the literature but deviate from the EOS-CG of Gernert and Span by up to 7 % at the lowest temperatures, highest pressures, and highest CO 2 mole fraction. The new low-uncertainty sound speed data presented in this work could provide a basis for development of an improved EOS and in establishing reliable predictions of the change in thermodynamic properties of seawater-like mixtures due to absorption of CO 2 gas.

The role of host movement in the spread of vector-borne diseases of livestock has been little studied. Here we develop a mathematical framework that allows us to disentangle and quantify the roles of vector dispersal and livestock movement in transmission between farms. We apply this framework to outbreaks of bluetongue virus (BTV) and Schmallenberg virus (SBV) in Great Britain, both of which are spread by Culicoides biting midges and have recently emerged in northern Europe. For BTV we estimate parameters by fitting the model to outbreak data using approximate Bayesian computation, while for SBV we use previously derived estimates. We find that around 90% of transmission of BTV between farms is a result of vector dispersal, while for SBV this proportion is 98%. This difference is a consequence of higher vector competence and shorter duration of viraemia for SBV compared with BTV. For both viruses we estimate that the mean number of secondary infections per infected farm is greater than one for vector dispersal, but below one for livestock movements. Although livestock movements account for a small proportion of transmission and cannot sustain an outbreak on their own, they play an important role in establishing new foci of infection. However, the impact of restricting livestock movements on the spread of both viruses depends critically on assumptions made about the distances over which vector dispersal occurs. If vector dispersal occurs primarily at a local scale (99% of transmission occurs <25 km), movement restrictions are predicted to be effective at reducing spread, but if dispersal occurs frequently over longer distances (99% of transmission occurs <50 km) they are not.

Mesopredator release theory suggests that dominant predators suppress subordinate carnivores and ultimately shape community dynamics, but the assumption that subordinate species are only negatively affected ignores the possibility of facilitation through scavenging. We examined the interplay within a carnivore community consisting of cougars, coyotes, black bears, and bobcats using contemporaneous Global Positioning System telemetry data from 51 individuals; diet analysis from 972 DNA-metabarcoded scats; and data from 128 physical investigations of cougar kill sites, 28 of which were monitored with remote cameras. Resource provisioning from competitively dominant cougars to coyotes through scavenging was so prolific as to be an overwhelming determinant of coyote behavior, space use, and resource acquisition. This was evident via the strong attraction of coyotes to cougar kill sites, frequent scavenging of cougar-killed prey, and coyote diets that nearly matched cougars in the magnitude of ungulate consumption. Yet coyotes were often killed by cougars and used space to minimize encounters, complicating the fitness benefits gained from scavenging. We estimated that 23% (95% CI: 8 to 55%) of the coyote population in our study area was killed by cougars annually, suggesting that coyote interactions with cougars are a complex behavioral game of risk and reward. In contrast, we found no indication that bobcat space use or diet was influenced by cougars. Black bears avoided cougars, but there was no evidence of attraction to cougar kill sites and much lower levels of ungulate consumption and carcass visitation than for coyotes. Interspecific interactions among carnivores are multifaceted, encompassing both suppression and facilitation.

The pursuit of ungulates as game animals, whether for recreation, cultural tradition, or meat, is a dominant activity on public and private lands in North America and much of the world. Strategic regulation of hunting is key for managing game population abundance, age and sex structure, and distribution, with harvest rates a function of both hunter success and participation. Hunter satisfaction is often linked to success and ultimately with hunter recruitment and retention, a growing concern for wildlife agencies. Yet knowledge is lacking about what hunter characteristics or behaviors are linked with success, and how these may differ among common hunt types. We used survey and spatial data from hunters (n = 416) during a 6-year observational study in northeastern Oregon, USA to characterize hunter traits associated with success for 3 hunt types for antlered males: rifle deer (Odocoileus spp.), archery elk (Cervus canadensis), and rifle elk. We modeled the success for rifle deer and rifle elk hunters using logistic regression models in a Bayesian hierarchical approach. Annual success rates were highly variable, ranging from 4 to 76% for rifle deer and 20 to 56% for rifle elk hunters, and from 0 to 14% for archery elk. Age distributions of hunters were similar across hunt types (x̅ = 47.2 years), and male hunters were ~8 times as common as females (n = 370 vs. n = 46, respectively). Success rates for men and women, however, were comparable within hunt types. Successful hunters spent more hours per day outside camp (x̅ = 7.4 vs. 6.4 for unsuccessful hunters) and expended a slightly larger percentage of their hunting effort on foot (x̅ = 87.8%) than did unsuccessful hunters (x̅ = 84.6%). The best model predicting success of rifle deer hunters was based on hours per day spent outside camp during the hunting hours, with each additional hour increasing odds of success by 26%. For rifle elk hunters, the best model included time outside camp and a binary covariate for scouting. The odds of success increased by 418% for hunters who scouted versus those who did not, and by 18% with each additional hour per day spent hunting outside of camp. Summed model weights indicated that hours per day outside camp and scouting were most informative, and that use of an all-terrain vehicle, age, and experience were unrelated to hunter success. Both models performed reasonably well (correct classification rates of 0.74 and 0.70 for rifle deer and rifle elk models, respectively). Our study augmented the relatively limited published information about behavioral factors associated with successful harvest of deer and elk, and we recommend additional research to better unravel the nexus of success and hunter characteristics and behavior to help sustain recreational hunting and big game populations.

Mule deer (Odocoileus hemionus) are widely hunted throughout western North America and are experiencing population declines across much of their range. Consequently, understanding the direct and indirect effects of hunting is important for management of mule deer populations. Managers can influence deer mortality rates through changes in hunting season length or authorized tag numbers. Little is known, however, about how hunting can affect site fidelity patterns and subsequent habitat use and movement patterns of mule deer. Understanding these patterns is especially important for adult females because changes in behavior may influence their ability to acquire resources and ultimately affect their productivity. Between 2008 and 2013, we obtained global positioning system locations for 42 adult female deer at the Starkey Experimental Forest and Range in northeast Oregon, USA, during 5-day control and treatment periods in which hunters were absent (pre-hunt), present but not actively hunting (scout and post-hunt), and actively hunting male mule deer (hunt) on the landscape. We estimated summer home ranges and 5-day use areas during pre-hunt and hunt periods and calculated overlap metrics across home ranges and use areas to assess site fidelity within and across years. We used step selection functions to evaluate whether female mule deer responded to human hunters by adjusting fine-scale habitat selection and movement patterns during the hunting season compared to the pre-hunt period. Mule deer maintained site fidelity despite disturbance by hunters with 72 ± 4% (SE) within-year overlap between summer home ranges and hunt use areas and 54 ± 7% inter-annual overlap among pre-hunt use areas and 56 ± 7% among hunt use areas. Mule deer diurnal movement rates, when hunters are active on the landscape, were higher during the hunting period versus pre-hunt or scout periods. In contrast, nocturnal movement rates, when hunters are inactive on the landscape, were similar between hunting and non-hunting periods. Additionally, during the hunt, female mule deer hourly movements increased in areas with high greenness values, indicating that mule deer spent less time in areas with more vegetative productivity. Female mule deer maintained consistent habitat selection patterns before and during hunts, selecting areas that offered more forest canopy cover and high levels of vegetative productivity. Our results indicate that deer at Starkey are adopting behavioral strategies in response to hunters by increasing their movement rates and selecting habitat in well-established ranges. Therefore, considering site fidelity behavior in management planning could provide important information about the spatial behavior of animals and potential energetic costs incurred, especially by non-target animals during hunting season.

Spatial capture–recapture (SCR) models have become the preferred tool for estimating densities of carnivores. Within this family of models are variants requiring identification of all individuals in each encounter (SCR), a subset of individuals only (generalized spatial mark–resight, gSMR), or no individual identification (spatial count or spatial presence– absence). Although each technique has been shown through simulation to yield unbiased results, the consistency and relative precision of estimates across methods in real-world settings are seldom considered. We tested a suite of models ranging from those only requiring detections of unmarked individuals to others that integrate remote camera, physical capture, genetic, and global positioning system (GPS) data into a hybrid model, to estimate population densities of black bears, bobcats, cougars, and coyotes. For each species, we genotyped fecal DNA collected with detection dogs during a 20-d period. A subset of individuals from each species was affixed with GPS collars bearing unique markings and resighted by remote cameras over 140 d contemporaneous with scat collection. Camera-based gSMR models produced density estimates that differed by <10% from genetic SCR for bears, cougars, and coyotes once important sources of variation (sex or behavioral status) were controlled for. For bobcats, SCR estimates were 33% higher than gSMR. The cause of the discrepancies in estimates was likely attributable to challenges designing a study compatible for species with disparate home range sizes and the difficulty of collecting sufficient data in a timeframe in which demographic closure could be assumed. Unmarked models estimated densities that varied greatly from SCR, but estimates became more consistent in models wherein more individuals were identifiable. Hybrid models containing all data sources exhibited the most precise estimates for all species. For studies in which only sparse data can be obtained and the strictest model assumptions are unlikely to be met, we suggest researchers use caution making inference from models lacking individual identity. For best results, we further recommend the use of methods requiring at least a subset of the population is marked and that multiple data sets are incorporated when possible.

Recurrent environmental changes often prompt animals to alter their behavior leading to predictable patterns across a range of temporal scales. The nested nature of circadian and seasonal behavior complicates tests for effects of rarer disturbance events like fire. Fire can dramatically alter plant community structure, with important knock-on effects at higher trophic levels, but the strength and timing of fire’s effects on herbivores remain unclear. We combined prescribed fire treatments with fine-scale location data to quantify herbivore responses to fire across three temporal scales. Between 2001 and 2003, 26 stands of fir (Abies spp.) and Douglas-fir (Pseudotsuga menziesii) were thinned and burned; 27 similar stands were left untreated as experimental controls. Analyzing female elk (Cervus canadensis) locations across 21 yr (1996—2016), we found crepuscular, seasonal, and successional shifts in behavioral responses to fire. Elk displayed “commuting” behavior, avoiding burns during the day, but selecting them at night. Elk selection for burns was strongest in early summer and the relative probability of elk using burns peaked quickly (5 yr post burn) before gradually returning to pre-treatment levels (15 yr post burn). Our results demonstrate that fire history has complex, persistent effects on herbivore behavior, and suggest that herbivores benefit from heterogeneous landscapes containing a range of successional stages.