TY - JOUR A1 - Ringel, Lisa Maria A1 - Somogyvári, Márk A1 - Jalali, Mohammadreza A1 - Bayer, Peter T1 - Comparison of hydraulic and tracer tomography for discrete fracture network inversion JF - Geosciences N2 - Fractures serve as highly conductive preferential flow paths for fluids in rocks, which are difficult to exactly reconstruct in numerical models. Especially, in low-conductive rocks, fractures are often the only pathways for advection of solutes and heat. The presented study compares the results from hydraulic and tracer tomography applied to invert a theoretical discrete fracture network (DFN) that is based on data from synthetic cross-well testing. For hydraulic tomography, pressure pulses in various injection intervals are induced and the pressure responses in the monitoring intervals of a nearby observation well are recorded. For tracer tomography, a conservative tracer is injected in different well levels and the depth-dependent breakthrough of the tracer is monitored. A recently introduced transdimensional Bayesian inversion procedure is applied for both tomographical methods, which adjusts the fracture positions, orientations, and numbers based on given geometrical fracture statistics. The used Metropolis-Hastings-Green algorithm is refined by the simultaneous estimation of the measurement error’s variance, that is, the measurement noise. Based on the presented application to invert the two-dimensional cross-section between source and the receiver well, the hydraulic tomography reveals itself to be more suitable for reconstructing the original DFN. This is based on a probabilistic representation of the inverted results by means of fracture probabilities. KW - hydraulic tomography KW - tracer tomography KW - DFN KW - Bayesian inversion KW - heterogeneity KW - fracture KW - hydrogeophysics Y1 - 2019 U6 - https://doi.org/10.3390/geosciences9060274 SN - 2076-3263 VL - 9 IS - 6 PB - MDPI CY - Basel ER - TY - JOUR A1 - Jeltsch, Florian A1 - Grimm, Volker A1 - Reeg, Jette A1 - Schlägel, Ulrike E. T1 - Give chance a chance BT - from coexistence to coviability in biodiversity theory JF - Ecosphere N2 - A large part of biodiversity theory is driven by the basic question of what allows species to coexist in spite of a confined number of niches. A substantial theoretical background to this question is provided by modern coexistence theory (MCT), which rests on mathematical approaches of invasion analysis to categorize underlying mechanisms into factors that reduce either niche overlap (stabilizing mechanisms) or the average fitness differences of species (equalizing mechanisms). While MCT has inspired biodiversity theory in the search for these underlying mechanisms, we feel that the strong focus on coexistence causes a bias toward the most abundant species and neglects the plethora of species that are less abundant and often show high local turnover. Given the more stochastic nature of their occurrence, we advocate a complementary cross-level approach that links individuals, small populations, and communities and explicitly takes into account (1) a more complete inclusion of environmental and demographic stochasticity affecting small populations, (2) intraspecific trait variation and behavioral plasticity, and (3) local heterogeneities, interactions, and feedbacks. Focusing on mechanisms that drive the temporary coviability of species rather than infinite coexistence, we suggest a new approach that could be dubbed coviability analysis (CVA). From a modeling perspective, CVA builds on the merged approaches of individual-based modeling and population viability analysis but extends them to the community level. From an empirical viewpoint, CVA calls for a stronger integration of spatiotemporal data on variability and noise, changing drivers, and interactions at the level of individuals. The resulting large volumes of data from multiple sources could be strongly supported by novel techniques tailored to the discovery of complex patterns in high-dimensional data. By complementing MCT through a stronger focus on the coviability of less common species, this approach can help make modern biodiversity theory more comprehensive, predictive, and relevant for applications. KW - behavioral plasticity KW - biodiversity KW - coexistence KW - community theory KW - coviability analysis KW - demographic noise KW - environmental noise KW - heterogeneity KW - individual-based modeling KW - intraspecific trait variation KW - modern coexistence theory KW - population viability analysis Y1 - 2019 U6 - https://doi.org/10.1002/ecs2.2700 SN - 2150-8925 VL - 10 IS - 5 PB - ESA CY - Ithaca, NY ER - TY - JOUR A1 - Dietrich, Julia A1 - Lazarides, Rebecca T1 - Gendered development of motivational belief patterns in mathematics across a school year and career plans in math-related fields JF - Frontiers in psychology N2 - Rooted in Eccles and colleagues' expectancy-value theory, this study aimed to examine how expectancies and different facets of task value combine to diverse profiles of motivational beliefs, how such complex profiles develop across a school year, and how they relate to gender and career plans. Despite abundant research on the association between gender and motivational beliefs, there is a paucity of knowledge regarding the gendered development of student motivational belief profiles in specific domains. Using latent-transition analysis in a sample of N = 751 ninth to tenth graders (55.9% girls), we investigated girls' and boys' development of motivational belief profiles (profile paths) in mathematics across a school year. We further analyzed the association between these profile paths and math-related career plans. The results revealed four motivational belief profiles: high motivation (intrinsic and attainment oriented), balanced above average motivation, average motivation (attainment and cost oriented), and low motivation (cost oriented). Girls were less likely than expected by chance to remain in the high motivation profile, while the opposite was true for boys. The math-relatedness of students' career plans was significantly higher in the "stable high motivation" profile path than in all other stable profile paths. KW - motivation in mathematics KW - latent transition analysis/latent profile analysis KW - expectancy-value theory KW - heterogeneity KW - adolescence Y1 - 2019 U6 - https://doi.org/10.3389/fpsyg.2019.01472 SN - 1664-1078 VL - 10 PB - Frontiers Research Foundation CY - Lausanne ER -