Sensitivity analysis of the asymptotic behavior of a model for the environmental movement of radionuclides

The asymptotic behavior of a linear compartment model for the environmental movement of radionuclides is investigated. Here, the expression asymptotic behavior is used to designate the behavior of q(t) as t → ∞, where q is the solution of a vector differential equation of the form dq/dt = h + Kq. The asymptotic behavior of such equations is described. For the model and conditions under consideration, each element of q converges monotonically to a steady-state value. A hydrologic system is defined and used to illustrate this behavior. An approach to sensitivity analysis employing Latin hypercube sampling, rank transformations and stepwise regression is presented and then applied to this system. A total of 20 independent variables is introduced and the following dependent variables are investigated for the various components of the system: amount of radionuclide present at steady state. concentration of radionuclide at steady state, and time required to reach 90% of steady state. Finally, an application of asymptotic behavior in the analysis of a hypothetical site for the geologic isolation of high-level radioactive waste is described and a brief discussion of differential sensitivity analysis is given.     

Application of k-means clustering to environmental risk zoning of the chemical industrial area

The homogeneous risk characteristics within a sub-area and the heterogeneous from one sub-area to another are unclear using existing environmental risk zoning methods. This study presents a new zoning method by determining and categorizing the risk characteristics using the k-means clustering data mining technology. The study constructs indices and develops index quantification models for environmental risk zoning by analyzing the mechanism of environmental risk occurrence. We calculate the source risk index, air risk field index, water risk field index, and target vulnerability of the study area with Nanjing Chemical Industrial Park using a 100 m - 100 m mesh grid as the basic zoning unit, and then use k-means clustering to analyze the environmental risk in the area. We obtain the optimal clustering number with the largest average silhouette coefficient by calculating the average silhouette coefficients of clustering at different k-values. The clustering result with the optimal clustering number is then used for the environmental risk zoning, and the zoning result is mapped using the geographic information system. The study area is divided into five sub-areas. The common environmental risk characteristics within the same sub-area, as well as the differences between sub- areas, are presented. The zoning is helpful in risk management and is convenient for decision makers to distribute limited resources to different sub-areas in the design of risk reducing intervention.     

Exploring the influence of lake water chemistry on chlorophyll a: A multivariate statistical model analysis

A multivariate statistical approach integrating the absolute principal components score (APCS) and multivariate linear regression (APCS-MLR), along with structural equation modeling (SEM), was used to model the influence of water chemistry variables on chlorophyll a (Chl a) in Lake Qilu, a severely polluted lake in southwestern China. Water quality was surveyed monthly from 2000 to 2005. APCS-MLR was used to identify key water chemistry variables, mine data for SEM, and predict Chl a. Seven principal components (PCs) were determined as eigenvalues >1, which explained 68.67% of the original variance. Four PCs were selected to predict Chl a using APCS-MLR. The results showed a good fit between the observed data and modeled values, with R² = 0.80. For SEM, Chl a and eight variables were used: NH₄-N (ammonia-nitrogen), total phosphorus (TP), Secchi disc depth (SD), cyanide (CN), arsenic (As), cadmium (Cd), fluoride (F), and temperature (T). A conceptual model was established to describe the relationships among the water chemistry variables and Chl a. Four latent variables were also introduced: physical factors, nutrients, toxic substances, and phytoplankton. In general, the SEM demonstrated good agreement between the sample covariance matrix of observed variables and the model-implied covariance matrix. Among the water chemistry factors, T and TP had the greatest positive influence on Chl a, whereas SD had the largest negative influence. These results will help researchers and decision-makers to better understand the influence of water chemistry on phytoplankton and to manage eutrophication adaptively in Lake Qilu.     

RANS simulation of neutral atmospheric boundary layer flows over complex terrain by proper imposition of boundary conditions and modification on the k-ε model

In this study, a modelling methodology is proposed for RANS simulations of neutral Atmospheric Boundary Layer (ABL) flows on the basis of the standard k-ε model, which allows the adoption of an arbitrary shear stress model. This modelling methodology is first examined in the context of an open flat terrain in an empty domain to ascertain there are no substantial changes in the prescribed profiles. The results show that relatively good homogeneity can be achieved with this modelling methodology for various sets of inflow boundary profiles. In addition, to extend the solutions derived from the standard k-ε model to RNG k-ε model, the RNG k-ε model is in detail assembly and tuned. Finally, the topographic effects on surface wind speeds over a complex terrain are assessed with the combined use of the proposed methodology and the modified RNG model. The numerical results are in good agreement with wind tunnel testing results and long-term field observations. A discussion of the effects of horizontal homogeneity and turbulence models on the simulated wind flows over a complex terrain is also given.     

Laboratory evaluation of kinetic parameters for lake sediment denitrification models

Laboratory experiments using the acetylene blockage technique showed that denitrification rates in sediments from Lake Okeechobee, Florida, are described by Michaelis-Menten nitrate dependence and Arrhenius temperature dependence (E_act = 15.5 kcal, but do not appear to be affected by seasonal differences in the supply of carbon substrates in this eutrophic lake. Peak nitrate concentrations in the sediments are in the range of the half-saturation constant, and thus, for a given temperature, k_d varies by a factor of approximately two over the typical range of nitrate concentrations. Most diagenetic sediment denitrification models employ a single-valued rate constant k_d, to describe nitrate dependence. However, the use of a constant k_d for eutrophic lake sediments may result in a significantly erroneous estimate of annual denitrification loss.     

Diffusional mass transfer coefficient at the water–sediment interface for wind-induced flow in very shallow lagoons

Very shallow lagoons that are a few centimeters deep are common in the arid Andes of Northern Chile, Argentina, Bolivia and Perú. The dynamics of these lagoons are dominated by the water–sediment interface (WSI) and strong afternoon winds. Although many studies have examined the diffusional mass transfer coefficients (k _t ) of open channel flows, estimates for wind-induced flows are still unknown. The aim of this article is to propose and validate an analytical expression for computing k _t at the WSI for wind-induced flow. The laboratory measurements were conducted in a wind tunnel with a water tank of variable depth located at its downwind end. Natural muddy sediments were placed in the middle of the tank so that the dissolved oxygen (DO) was consumed in the sediments. The diffusional mass transfer coefficient that characterizes the DO uptake in the sediment was obtained from DO micro-profiles measured with an OX-25 Unisense microelectrode. Water velocity profiles were measured with a 2D side-view Sontek acoustic doppler velocimetry (ADV), and the wind shear velocity was computed based on wind velocity profiles that were measured with an Extech hot-wire anemometer. A total of 16 experiments were conducted with different water depths and wind shear stresses. The constants required by the model were determined from these experiments, and the analytical expression was successfully validated by the laboratory observations. The analytical expression obtained for computing k _t was also validated with field observations that were conducted in October, 2012, in Salar del Huasco, Northern Chile (20.274° S, 68.883° W, 3800 m above sea level). The comparison between the observed and predicted values of k _t provides a determination coefficient of r ² = 0.48 and a p value < 0.01. The results show that the value of k _t for wind-induced flow is proportional to the wind shear velocity and the inverse of the Reynolds number of the wind-induced current.     

Mechanisms of moisture stress in a mid-latitude temperate forest: Implications for feedforward and feedback controls from an irrigation experiment

While it is well established that stomata close during moisture stress, strong correlations among environmental (e.g., vapor pressure deficit, soil moisture, air temperature, radiation) and internal (e.g., leaf water potential, sap flow, root-shoot signaling) variables obscure the identification of causal mechanisms from field experiments. Models of stomatal control fitted to field data therefore suffer from ambiguous parameter identification, with multiple acceptable (i.e., nearly optimal) model structures emphasizing different moisture status indicators and different processes. In an effort to minimize these correlations and improve parameter and process identification, we conducted an irrigation experiment on red maples (Acer rubrum L.) at Harvard Forest (summers of 2005 and 2006). Control and irrigated trees experienced similar radiative and boundary layer forcings, but different soil moisture status, and thus presumably different diurnal cycles of internal leaf water potential. Measured soil moisture and atmospheric forcing were used to drive a transient tree hydraulic model that incorporated a Jarvis-type leaf conductance in a Penman–Monteith framework with a Cowan-type (resistance and capacitance) tree hydraulic representation. The leaf conductance model included dependence on both leaf matric potential, Ψ_L (so-called feedback control) and on vapor pressure deficit, D (so-called feedforward control). Model parameters were estimated by minimizing the error between predicted and measured sap flow. The whole-tree irrigation treatment had the effect of elevating measured transpiration during summer dry-downs, demonstrating the limiting effect that subsurface resistance may have on transpiration during these times of moisture stress. From the best fitted model, we infer that during dry downs, moisture stress manifests itself in an increase of soil resistance with a resulting decrease in Ψ_L, leading to both feedforward and feedback controls in the control trees, but only feedforward control for the irrigated set. Increases in the sum-of-squares error when individual model components were disabled allow us to reject the following three null hypotheses: (1) the f(D) stress is statistically insignificant (p = 0.01); (2) the f(Ψ_L) stress is statistically insignificant (p = 0.07); and (3) plant storage capacitance is independent of moisture status (p = 0.07).     

Modeling a spatially restricted distribution in the Neotropics: How the size of calibration area affects the performance of five presence-only methods

We here examine species distribution models for a Neotropical anuran restricted to ombrophilous areas in the Brazilian Atlantic Forest hotspot. We extend the known occurrence for the treefrog Hypsiboas bischoffi (Anura: Hylidae) through GPS field surveys and use five modeling methods (BIOCLIM, DOMAIN, OM-GARP, SVM, and MAXENT) and selected bioclimatic and topographic variables to model the species distribution. Models were first trained using two calibration areas: the Brazilian Atlantic Forest (BAF) and the whole of South America (SA). All modeling methods showed good levels of predictive power and accuracy with mean AUC ranging from 0.77 (BIOCLIM/BAF) to 0.99 (MAXENT/SA). MAXENT and SVM were the most accurate presence-only methods among those tested here. All but the SVM models calibrated with SA predicted larger distribution areas when compared to models calibrated in BAF. OM-GARP dramatically overpredicted the species distribution for the model calibrated in SA, with a predicted area around 10⁶ km² larger than predicted by other SDMs. With increased calibration area (and environmental space), OM-GARP predictions followed changes in the environmental space associated with the increased calibration area, while MAXENT models were more consistent across calibration areas. MAXENT was the only method that retrieved consistent predictions across calibration areas, while allowing for some overprediction, a result that may be relevant for modeling the distribution of other spatially restricted organisms.     

Estimation of some parameters of large fish populations by capture-recapture experiments

A certain number of tagged fish is liberated and assumed to be distributed randomly among a natural fish population. The fish are subjected to a number of fishing experiments within relatively short periods, and lie between equal intervening periods of durationT. Untagged fish are retained, while tagged fish are released during the fishing experiments. Denoting the catchability of untagged fish byq _u and that for tagged fish byq _t , it is assumed that they are related by the equation “q _u =cq _t ” wherec is a constant. Denoting the survival rates of tagged fish and the effective fishing effort of commerical fisheries per unit time from the (k-1)^th to thek ^th experiments by _t S _k andf _k , respectively, it is assumed that they vary from period to period. Assuming that during thek ^th experiment, the number of untagged fish captured and the experimental fishing rate of tagged fish are denoted by _u X _k and _t P _k , respectively, then $$\begin{array}{*{20}c} {\frac{{(_u X_k )^2 }}{{[_u X_{(k - 1)} ][_u X_{(k + 1)} ]}} = \frac{{_t S_k }}{{_t S_{(k + 1)} }} \cdot \frac{{e^{ - (1 - c)q_t f_{(k + 1)} T} }}{{e^{ - (1 - c)q_t f_k T} }} \cdot } \\ {\frac{{1 - c_t P_{(k - 1)} }}{{1 - c_t P_k }} \cdot \frac{{(_t P_k )^2 }}{{[_t P_{(k - 1)} ][_t P_{(k + 1)} ]}}.} \\ \end{array}$$ The above equation containsc as a single unknown, while all other terms are supplied by the capture-recapture experiments, exceptf _k andf _(k+1) which may be obtained from fisheries statistics. A number of the above equations are obtained from several experiments and can be combined into a single equation to obtain an overall estimate forc which can be used to derive estimates for experimental fishing rates, abundance, and instantaneous natural and fishing mortality rates for natural fish populations. These estimates are free from type (A) tagging errors, and have the advantage of taking into consideration the probable different behaviour of tagged and untagged fish.     

Determining factors that influence the dispersal of a pelagic species: A comparison between artificial neural networks and evolutionary algorithms

Because of increasing transport and trade there is a growing threat of marine invasive species being introduced into regions where they do not presently occur. So that the impacts of such species can be mitigated, it is important to predict how individuals, particularly passive dispersers are transported and dispersed in the ocean as well as in coastal regions so that new incursions of potential invasive species are rapidly detected and origins identified. Such predictions also support strategic monitoring, containment and/or eradication programs. To determine factors influencing a passive disperser, around coastal New Zealand, data from the genus Physalia (Cnidaria: Siphonophora) were used. Oceanographic data on wave height and wind direction and records of occurrences of Physalia on swimming beaches throughout the summer season were used to create models using artificial neural networks (ANNs) and Na?ve Bayesian Classifier (NBC). First, however, redundant and irrelevant data were removed using feature selection of a subset of variables. Two methods for feature selection were compared, one based on the multilayer perceptron and another based on an evolutionary algorithm. The models indicated that New Zealand appears to have two independent systems driven by currents and oceanographic variables that are responsible for the redistribution of Physalia from north of New Zealand and from the Tasman Sea to their subsequent presence in coastal waters. One system is centred in the east coast of northern New Zealand and the other involves a dynamic system that encompasses four other regions on both coasts of the country. Interestingly, the models confirm, molecular data obtained from Physalia in a previous study that identified a similar distribution of systems around New Zealand coastal waters. Additionally, this study demonstrates that the modelling methods used could generate valid hypotheses from noisy and complicated data in a system about which there is little previous knowledge.     

A thermodynamic model of freshwater Antarctic lake ice

Antarctic lakes with simple plankton ecosystems are believed to be sensitive biological indicators of climate change. Models of the physical environment, in particular the ice layer, support understanding of how the ecosystems respond to meteorological variables. This paper describes how data from a previously reported automatic measuring probe and meteorological data from Davis station were used to develop a detailed thermodynamic model of the ice layer on Crooked Lake, one of the largest and deepest freshwater lakes in Antarctica. The general model structure is similar to a previously reported model of sea ice but with modifications specific to the Antarctic freshwater lake case informed by the data. The model inputs are atmospheric variables as well as water temperature, ice albedo and the radiation extinction coefficient for the ice. Heat and radiation fluxes at the ice–air and ice–water boundaries are calculated using equations chosen for their suitability for the Antarctic. In the case of shortwave radiation, equations were fitted to data from the automatic probe. Using the heat fluxes to establish boundary conditions, and incorporating the known thermodynamic properties of ice, the temperature profile within the ice and the resulting growth and melt of the ice can be calculated. The model uses a largely mechanistic approach, with most equations taken from established thermodynamic theories or empirical studies and only one adjustable parameter related to the sensible heat flux from the water, which is not easily calculated from the available data. It was found to accurately reproduce ice temperature and ice thickness data for the year 2003, with r² = 0.89, n = 2005. Finally, the model was simplified to run with air temperature as the only input variable and was shown to perform well—this suggests that freshwater lake ice is affected more by air temperature than any other variable, and is therefore a useful indicator of climate change in its own right.     

Diameter growth models for mixed-species stands of Coastal British Columbia including thinning and fertilization effects

In this study, diameter growth models for three species growing in mixed-stands of Coastal British Columbia (BC), Canada, under a variety of silvicultural treatments were developed. The three species were: Douglas-fir (Pseudotsuga menziesii var. menziesii (Mirb.) Franco), western hemlock (Tsuga heterophylla (Raf.) Sarg.), and western redcedar (Thuja plicata Donn). A Box and Lucas model (1959) was initially fitted to the diameter growth series for each tree, as this model is very flexible and was based on processes reflective of the metabolic processes governing tree growth. Next, a random coefficients modelling approach (i.e., parameter prediction approach) was used to modify the estimated parameters for each species using functions of tree size and stage of development, site productivity, and inter-tree competition variables, while accounting for temporal correlation within trees. Impacts of fertilization on diameter growth were estimated by including the time since fertilization as an additional variable. Since state variables that are changed as a result of thinning were already in the model, accurate results post-thinning were obtained with no changes to the model. For the combined effects of thinning and fertilization, a two-step additive approach was used, where the state variables were changed following thinning and the diameter increment was modified for fertilization using the time since fertilization variable. Results indicated that multiple treatments sustain a change in growth for a longer time period following treatment than thinning or fertilization alone.     

Assessment of canopy stomatal conductance models using flux measurements

Stomatal conductance (g) is a key parameter in controlling energy and water exchanges between canopy and the atmosphere. Stomatal conductance models proposed by Ball, Woodrow and Berry (BWB) and Leuning have been increasingly used in land surface schemes. In a recent study, a new diagnostic index was developed by Wang et al. to examine the response of g to humidity and new models were proposed to resolve problems identified in the BWB and Leuning models. This approach is theoretically sound, but relies on canopy latent heat and CO₂ fluxes and environmental variables at the leaf surface which are not available at most eddy correlation (EC) observation sites. In this study, we tested the diagnostic index by empirically correcting EC measurements to canopy-level fluxes and by replacing leaf surface variables by their corresponding ambient air variables, and re-examined the stomatal conductance models of BWB, Leuning, and Wang et al. We found that the impact of the above modifications on the evaluation of g–humidity relationships is very small. This study provides a practical approach to investigate the stomatal response to humidity using routine EC measurements.     

Short-term variability and control of phytoplankton photosynthetic activity in a macrotidal ecosystem (the Strait of Dover, eastern English Channel)

Short-term changes in phytoplankton photosynthetic activity were studied during different periods of the years 2009 and 2010 in the coastal waters of a macrotidal ecosystem (the Strait of Dover, eastern English Channel). During each sampling period, samples were taken every 1.45 h., from sunrise to sunset, during at least 5 days distributed along a complete spring–neap tide cycle. The photosynthetic parameters were obtained by measuring rapid light curves using pulse amplitude modulated fluorometry and were related to environmental conditions and phytoplankton taxonomic composition. The maximum quantum yield (F _v/F _m) showed clear light-dependent changes and could vary from physiological maxima (0.68–0.60) to values close to 0.30 during the course of 1 day, suggesting the operation of photoprotective mechanisms. The maximum electron transport rate (ETR_m) and maximal light utilization efficiency (α) were generally positively correlated and showed large diel variability. These parameters fluctuated significantly from hour to hour within each day and the intraday pattern of variation changed significantly among days of each sampling period. Stepwise multiple linear regressions analyses indicated that light fluctuations explained a part of this variability but a great part of variability stayed unexplained. F _v/F _m, ETR_m and α were not only dependent on the light conditions of the sampling day but also on those of the previous days. A time lag of 3 days in the effect of light on ETR_m and α variation was highlighted. At these time scales, changes in phytoplankton community structure seemed to have a low importance in the variability in photosynthetic parameters. The photoacclimation index E _k showed a lower variability and was generally different from the incident irradiance, indicating a limited acclimation capacity with a poor optimization of light harvesting during the day. However, in well-mixed systems such as the Strait of Dover, the short-term photoacclimation is disrupted by the high level of variability in environmental conditions. Also, the variability observed in the present study can be associated with a particular kind of photosynthetic response: the “E _k-independent” variability. The physiological basis of this photosynthetic response is largely unresolved and further researches on this subject are still required to better explain the dynamics of phytoplankton activity in the Strait of Dover.     

Diurnal changes in photosynthesis of Antarctic fast ice algal communities determined by pulse amplitude modulation fluorometry

The aim of this project was to determine both the diurnal changes in photosynthetic activity of Antarctic sea ice algae and also the protective mechanisms they use to mitigate the effects of in situ UV radiation. Changes in the diurnal photosynthetic parameters of fast ice algal communities at McMurdo Sound were measured in situ, using a custom designed monitoring pulse amplitude modulation fluorometer. The sea ice microalgae were able to adapt rapidly to either increasing or decreasing ambient irradiances. ΔF/F_m' values were between 0.2 and 0.51, while E_k varied between 2.1 and 18 μmol photons m^-2 s^-1. ΔF/F_m', E_k, and relative electron transfer rate (rETR) all varied sequentially over the course of a day. rETR and E_k were highest at midday at the highest irradiances, when there was apparent midday down regulation of photosynthesis, while ΔF/F_m' was highest at midnight. The effects of natural UV radiation on sea ice were examined, but it was not possible to detect the effect of either UVB or UVA and UVB on photosynthesis. This was considered to be largely because of the large spatial and temporal heterogeneity of the under ice community, changing irradiances throughout the day and the relatively small change caused by UV.     

A photolysis coefficient for characterizing the response of aqueous constituents to photolysis

UV photolysis and UV based advanced oxidation processes (AOPs) are gaining more and more attention for drinking water treatment. Quantum yield (ø) and molar absorption coefficient (ε) are the two critical parameters measuring the effectiveness of photolysis of a compound. The product of the two was proposed as a fundamental measure of a constituent’s amenability to transformation by photolysis. It was shown that this product, named the photolysis coefficient, k _p , can be determined using standard bench tests and captures the properties that govern a constituent’s transformation when exposed to light. The development showed the photolysis coefficient to be equally useful for microbiological, inorganic and organic constituents. Values of k _p calculated by the authors based on quantum yield and molar absorption coefficient data from the literature were summarized. Photolysis coefficients among microorganisms ranged from 8500 to more than 600000 and are far higher than for inorganic and organic compounds, which varied over a range of approximately 10 to 1000 and are much less sensitive to UV photolysis than the microorganisms.     

Flow and drag force around a free surface piercing cylinder for environmental applications

This paper investigates flows around a free surface piercing cylinder with Froude number F > 0.5 and Reynolds number around Re = 50,000. The aim of this work is to gain a better understanding of the flow behaviour in environmental systems such as fishways. The advances are based upon experimental and numerical results. Several flow discharges and slopes are tested to obtain both subcritical and supercritical flows. The drag force exerted on the cylinder is measured with the help of a torque gauge while the velocity field is obtained using particle velocimetry. For the numerical part, two URANS turbulence models are tested, the k-\(\omega\) SST and the RNG k-\(\varepsilon\) models using the OpenFOAM software suite for subcritical cases, and then compared with the corresponding experimental results. With fishways applications in mind, the changes in drag coefficient \(C_d\) versus Froude number and water depth are studied and experimental correlations proposed. We conclude that the most suitable URANS turbulence model for reproducing this kind of flow is the k-\(\omega\) SST model.     

Use of principal component scores in multiple linear regression models for prediction of Chlorophyll-a in reservoirs

Chlorophyll-a is a well-accepted index for phytoplankton abundance and population of primary producers in an aquatic environment. The relationships between Chlorophyll-a and 16 chemical, physical and biological water quality variables in Çamlıdere reservoir (Ankara, Turkey) were studied by using principal component scores (PCS) in multiple linear regression analysis (MLR) to predict Chlorophyll-a levels. Principal component analysis was used to simplify the complexity of relations between water quality variables. Score values obtained by PC scores were used as independent variables in the multiple linear regression models. Two approaches were used in the present statistical analysis. In the first approach, only five selected score values obtained by PC analysis were used for the prediction of Chlorophyll-a levels and predictive success (R²) of the model found as 56.3%. In the second approach, where all score values obtained from the PC analysis were used as independent variables, predictive power was turned out to be 90.8%. Both approaches could be used to predict Chlorophyll-a levels in reservoirs successfully.     

Accelerated degradation of orange G over a wide pH range in the presence of FeVO<Subscript>4</Subscript>

In this study, FeVO₄ was prepared and used as Fenton-like catalyst to degrade orange G (OG) dye. The removal of OG in an aqueous solution containing 0.5 g·L^–1 FeVO₄ and 15 mmol·L^–1 hydrogen peroxide at pH 7.0 reached 93.2%. Similar rates were achieved at pH 5.7 (k = 0.0471 min^–1), pH 7.0 (k = 0.0438 min^–1), and pH 7.7 (k = 0.0434 min^–1). The FeVO₄ catalyst successfully overcomes the problem faced in the heterogeneous Fenton process, i.e., the narrow working pH range. The data for the removal of OG in FeVO₄ systems containing H₂O₂ conform to the Langmuir–Hinshelwood model (R² = 0.9988), indicating that adsorption and surface reaction are the two basic mechanisms for OG removal in the FeVO₄–H₂O₂ system. Furthermore, the irradiation of FeVO₄ by visible light significantly increases the degradation rate of OG, which is attributed to the enhanced rates of the iron cycles and vanadium cycles.

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Levels of social behaviors and genetic structure in a population of round-tailed ground squirrels (Xerospermophilus tereticaudus)

Ground-dwelling sciurids exhibit a continuum of sociality and several models predict levels of sociality within this taxon. Models of ground squirrel sociality predict round-tailed ground squirrels (Xerospermophilus tereticaudus) to be solitary; however, previous behavioral studies suggest round-tailed ground squirrels have a matrilineal social structure. To resolve this discrepancy, we combined behavioral observations with genetic analyses of population structure. We assessed levels of agonistic and amicable behaviors combined with fine-scale population genetic structure of round-tailed ground squirrels in a multi-year study in AZ. Only 45 agonistic and 40 amicable interactions were observed between adults in over 137 h of observations. Overall rates of agonistic or amicable interactions between adults were low (≤0.69/h), with no relationship between relatedness of individuals and rates of either amicable or agonistic interactions. Interactions between juvenile littermates were predominantly amicable. Population substructure was not evident with Bayesian analyses, global or pairwise F _ST values; average relatedness among females was not different from males. However, in 2006, the year after a population reduction through targeted animal elimination, a population bottleneck was detected within at least five of seven loci. Contrary to previous behavioral studies, this population of round-tailed ground squirrels, although aggregated spatially, did not exhibit high levels of social behavior nor subpopulation genetic structure. Analyses of the genetic relationships and sociality along a continuum, particularly within aggregates of individuals, may lead to insights into the origin and maintenance of social behaviors by elucidating the mechanisms by which aggregates with intermediate social levels are formed and maintained.