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Use this package to calculate estimated relative volatility index values for organic compounds based on functional group contributions. Calculation uses the SIMPOL.1 method (Prankow and Asher, 2008) or modified SIMPOL.1 method as in Meredith et al. (2023). 

Habitat fragmentation remains a major focus of research by ecologists decades after being put forward as a threat to the integrity of ecosystems. While studies have documented myriad biotic changes in fragmented landscapes, including the local extinction of species from fragments, the demographic mechanisms underlying these extinctions are rarely known. However, many of them – especially in lowland tropical forests – are thought to be driven by one of two mechanisms: (1) reduced recruitment in fragments resulting from changes in the diversity or abundance of pollinators and seed dispersers or (2) increased rates of individual mortality in fragments due to dramatically altered abiotic conditions, especially near fragment edges. Unfortunately, there have been few tests of these potential mechanisms due to the paucity of long-term and comprehensive demographic data collected in both forest fragments and continuous forest sites. Here we report 11 years (1998-2009) of demographic data from populations of the Amazonian understory herb Heliconia acuminata (LC Rich.) found at Brazil’s Biological Dynamics of Forest Fragments Project (BDFFP). The resulting data set comprises 66000 plant×year records of 8586 plants, including 3464 seedlings that became established after the initial census. Seven populations were in experimentally isolated fragments (one in each of four 1-ha fragments and one in each of three 10-ha fragments), with the remaining six populations in continuous forest. Each population was in a 50×100m permanent plot, with the distance between plots ranging from 500 m-60 km. The plants in each plot were censused annually, at which time we recorded, identified, marked, and measured new seedlings, identified any previously marked plants that died, and recorded the size of surviving individuals. Each plot was also surveyed 4-5 times during the flowering season to identify reproductive plants and record the number of inflorescences each produced. These data have been used to investigate topics ranging from the way fragmentation-related reductions in germination influence population dynamics to statistical methods for analyzing reproductive rates. This breadth of prior use reflects the value of these data to future researchers. In addition to analyses of plant responses to habitat fragmentation, these data can be used to address fundamental questions in plant demography, the evolutionary ecology of tropical plants, and for developing and testing demographic models and tools. Though we welcome opportunities to collaborate with interested users, there are no restrictions on the use this data set. However, we do request that those using the data for teaching or research inform us of how they are doing so and cite this paper and the data archive when appropriate. Any publication using the data must also include a BDFFP Technical Series Number in the Acknowledgments. Authors can request this series number upon the acceptance of their article by contacting the BDFFP’s Scientific Coordinator or E. M. Bruna. 

Agent-based modeling (ABM) has many applications in the social sciences, biology, computer science, and robotics. One of the most important and challenging phases in agent-based model development is the calibration of model parameters and agent behaviors. Unfortunately, for many models this step is done by hand in an ad-hoc manner or is ignored entirely, due to the complexity inherent in ABM dynamics. In this paper we present a general-purpose, automated optimization system to assist the model developer in the calibration of ABM parameters and agent behaviors. This system combines two popular tools: the MASON agent-based modeling toolkit and the ECJ evolutionary optimization library. Our system distributes the model calibration task over very many processors and provides a wide range of stochastic optimization algorithms well suited to the calibration needs of agent-based models. 

Studies of horse evolution arose during the middle of the 19th century, and several hypotheses have been proposed for their taxonomy, paleobiogeography, paleoecology and evolution. The present contribution represents a collaboration of 19 multinational experts with the goal of providing an updated summary of Pliocene and Pleistocene North, Central and South American, Eurasian and African horses. At the present time, we recognize 114 valid species across these continents, plus 4 North African species in need of further investigation. Our biochronology and biogeography sections integrate Equinae taxonomic records with their chronologic and geographic ranges recognizing regional biochronologic frameworks. The paleoecology section provides insights into paleobotany and diet utilizing both the mesowear and light microscopic methods, along with calculation of body masses. We provide a temporal sequence of maps that render paleoclimatic conditions across these continents integrated with Equinae occurrences. These records reveal a succession of extinctions of primitive lineages and the rise and diversification of more modern taxa. Two recent morphological-based cladistic analyses are presented here as competing hypotheses, with reference to molecular-based phylogenies. Our contribution represents a state-of-the art understanding of Plio-Pleistocene Equus evolution, their biochronologic and biogeographic background and paleoecological and paleoclimatic contexts. 

Agent-based models can present special challenges to model calibration due in part to their high parameter count, tunable agent behaviors, complex emergent macrophenomena, and potentially long runtimes. However, due to this difficulty, these models are most often calibrated by hand, or with hand-coded optimization tools customized per-problem if at all. As simulations increase in complexity, we will require general-purpose, distributed model calibration tools tailored for the needs of agent-based models. In this paper, we present the results of a system we have developed which combines two popular tools, the MASON agent-based modeling toolkit, and the ECJ evolutionary optimization library. This system distributes the model calibration task over many processors, provides many stochastic optimization algorithms well suited to the calibration needs of agent-based models, and offers the ability to optimize not just model parameters but agent behaviors. 

Abstract One key evolutionary innovation that separates vertebrates from invertebrates is the notochord, a central element that provides the stiffness needed for powerful movements. Later, the notochord was further stiffened by the vertebrae, cartilaginous and bony elements, surrounding the notochord. The ancestral notochord is retained in modern vertebrates as intervertebral material, but we know little about its mechanical interactions with surrounding vertebrae. In this study, the internal shape of the vertebrae—where this material is found—was quantified in sixteen species of fishes with various body shapes, swimming modes, and habitats. We used micro-computed tomography to measure the internal shape. We then created and mechanically tested physical models of intervertebral joints. We also mechanically tested actual vertebrae of five species. Material testing shows that internal morphology of the centrum significantly affects bending and torsional stiffness. Finally, we performed swimming trials to gather kinematic data. Combining these data, we created a model that uses internal vertebral morphology to make predictions about swimming kinematics and mechanics. We used linear discriminant analysis (LDA) to assess the relationship between vertebral shape and our categorical traits. The analysis revealed that internal vertebral morphology is sufficient to predict habitat, body shape, and swimming mode in our fishes. This model can also be used to make predictions about swimming in fishes not easily studied in the lab, such as deep sea and extinct species, allowing the development of hypotheses about their natural behavior.