Enhancing wind erosion monitoring and assessment for U.S. rangelands

Wind erosion is a major resource concern for rangeland managers because it can impact soil health, ecosystem structure and function, hydrologic processes, agricultural production, and air quality. Despite its significance, little is known about which landscapes are eroding, by how much, and when. The National Wind Erosion Research Network was established in 2014 to develop tools for monitoring and assessing wind erosion and dust emissions across the United States. The Network, currently consisting of 13 sites, creates opportunities to enhance existing rangeland soil, vegetation, and air quality monitoring programs. Decision-support tools developed by the Network will improve the prediction and management of wind erosion across rangeland ecosystems. © 2017 The Author(s)The Rangelands archives are made available by the Society for Range Management and the University of Arizona Libraries. Contact [email protected] for further information

Sustaining Working Rangelands: Insights from Rancher Decision Making

Grazed rangeland ecosystems encompass diverse global land resources and are complex social-ecological systems from which society demands both goods (e.g., livestock and forage production) and services (e.g., abundant and high-quality water). Including the ranching community's perceptions, knowledge, and decision-making is essential to advancing the ongoing dialogue to define sustainable working rangelands. We surveyed 507 (33% response rate) California ranchers to gain insight into key factors shaping their decision-making, perspectives on effective management practices and ranching information sources, as well as their concerns. First, we found that variation in ranch structure, management goals, and decision making across California's ranching operations aligns with the call from sustainability science to maintain flexibility at multiple scales to support the suite of economic and ecological services they can provide. The diversity in ranching operations highlights why single-policy and management "panaceas" often fail. Second, the information resources ranchers rely on suggest that sustaining working rangelands will require collaborative, trust-based partnerships focused on achieving both economic and ecological goals. Third, ranchers perceive environmental regulations and government policies-rather than environmental drivers-as the major threats to the future of their operations

ManyBabies 3: A multi-lab study of infant algebraic rule learning

The ability to learn and apply rules lies at the heart of cognition. In a seminal study, Marcus, Vijayan, Rao, and Vishton (1999) reported that seven-month-old infants learned abstract rules over syllable sequences and were able to generalize those rules to novel syllable sequences. Dozens of studies have since extended on that research using different rules, modalities, stimuli, participants (human adults and non-human animals) and experimental procedures. Yet questions remain about the robustness of Marcus et al.’s (1999) core findings, as the presence of significant learning effects has been mixed. In the current study, we aimed to address this issue by testing XX infants of a wide age range (5;0-12;0 months) in a multi-laboratory (XX laboratories) replication of the Marcus et al. (1999) study

Indicators and Benchmarks for Wind Erosion Monitoring, Assessment and Management

Wind erosion and blowing dust threaten food security, human health and ecosystem services across global drylands. Monitoring wind erosion is needed to inform management, with explicit monitoring objectives being critical for interpreting and translating monitoring information into management actions. Monitoring objectives should establish quantitative guidelines for determining the relationship of wind erosion indicators to management benchmarks that reflect tolerable erosion and dust production levels considering impacts to, for example, ecosystem processes, species, agricultural production systems and human well-being. Here we: 1) critically review indicators of wind erosion and blowing dust that are currently available to practitioners; and 2) describe approaches for establishing benchmarks to support wind erosion assessments and management. We find that while numerous indicators are available for monitoring wind erosion, only a subset have been used routinely and most monitoring efforts have focused on air quality impacts of dust. Indicators need to be related to the causal soil and vegetation controls in eroding areas to directly inform management. There is great potential to use regional standardized soil and vegetation monitoring datasets, remote sensing and models to provide new information on wind erosion across landscapes. We identify best practices for establishing benchmarks for these indicators based on experimental studies, mechanistic and empirical models, and distributions of indicator values obtained from monitoring data at historic or existing reference sites. The approaches to establishing benchmarks described here have enduring utility as monitoring technologies change and enable managers to evaluate co-benefits and potential trade-offs among ecosystem services as affected by wind erosion management

Indicators and benchmarks for wind erosion monitoring, assessment and management

Wind erosion and blowing dust threaten food security, human health and ecosystem services across global drylands. Monitoring wind erosion is needed to inform management, with explicit monitoring objectives being critical for interpreting and translating monitoring information into management actions. Monitoring objectives should establish quantitative guidelines for determining the relationship of wind erosion indicators to management benchmarks that reflect tolerable erosion and dust production levels considering impacts to, for example, ecosystem processes, species, agricultural production systems and human well-being. Here we: 1) critically review indicators of wind erosion and blowing dust that are currently available to practitioners; and 2) describe approaches for establishing benchmarks to support wind erosion assessments and management. We find that while numerous indicators are available for monitoring wind erosion, only a subset have been used routinely and most monitoring efforts have focused on air quality impacts of dust. Indicators need to be related to the causal soil and vegetation controls in eroding areas to directly inform management. There is great potential to use regional standardized soil and vegetation monitoring datasets, remote sensing and models to provide new information on wind erosion across landscapes. We identify best practices for establishing benchmarks for these indicators based on experimental studies, mechanistic and empirical models, and distributions of indicator values obtained from monitoring data at historic or existing reference sites. The approaches to establishing benchmarks described here have enduring utility as monitoring technologies change and enable managers to evaluate co-benefits and potential trade-offs among ecosystem services as affected by wind erosion management

ManyBabies 5: A large-scale investigation of the proposed shift from familiarity preference to novelty preference in infant looking time

Much of our basic understanding of cognitive and social processes in infancy relies on measures of looking time, and specifically on infants’ visual preference for a novel or familiar stimulus. However, despite being the foundation of many behavioral tasks in infant research, the determinants of infants’ visual preferences are poorly understood, and differences in the expression of preferences can be difficult to interpret. In this large-scale study, we test predictions from the Hunter and Ames model of infants' visual preferences. We investigate the effects of three factors predicted by this model to determine infants’ preference for novel versus familiar stimuli: age, stimulus familiarity, and stimulus complexity. Drawing from a large and diverse sample of infant participants (N = XX), this study will provide crucial empirical evidence for a robust and generalizable model of infant visual preferences, leading to a more solid theoretical foundation for understanding the mechanisms that underlie infants’ responses in common behavioral paradigms. Moreover, our findings will guide future studies that rely on infants' visual preferences to measure cognitive and social processes

Long-term vegetation change provides evidence for alternate states in silver sagebrush

A key goal in land management is to prevent ecosystem shifts that affect human well-being. Like other types of sagebrush shrublands, large areas dominated by the common but little-studied mountain silver sagebrush may have shifted to a less productive shrub-dominated alternate state under heavy livestock grazing in the 19th century. The goals of this study are to 1) describe long-term vegetation change in a silver sagebrush mountain park and 2) evaluate evidence that these changes constitute alternate states. We examined vegetation change over the last 57 yr in California Park, Colorado, USA, using monitoring data from 15 permanent transects at six sites. We analyzed change in species composition over time and related it to management and climatic drivers using nonmetric multidimensional scaling. We found that management practices influenced species composition. Spraying herbicides resulted in decreases of sagebrush and a dominant, unpalatable forb (Wyethia amplexicaulis), but sagebrush recovered. Spraying also triggered a temporary increase in native palatable grasses and forbs. Native grasses have since decreased again, coinciding with increases in the cattle stocking rate and elk population. The nonnative pasture grass Phleum pratense has increased to become one of the dominant grasses in 2010. Sagebrush and herbaceous understory dynamics were not consistent with a shrub-dominated alternate state: changes were gradual and not persistent. However, historic Wyethia dominance and the widespread increase in the nonnative grass Phleum were persistent and may represent alternate states. We used these findings to update a state-and-transition model of high-elevation silver sagebrush shrubland dynamics for land management decision making. Our analysis differentiated gradual, nonpersistent changes from potentially irreversible changes, as is necessary for identifying alternate states that are important for land management and ecosystem function. The gradual but persistent increase in the nonnative grass Phleum reinforces others' observations that even incremental changes may lead to irreversible shifts. © 2014 The Society for Range Management.The Rangeland Ecology & Management archives are made available by the Society for Range Management and the University of Arizona Libraries. Contact [email protected] for further information

Gaussian Process Regression for Trajectory Analysis

Cognitive scientists have begun collecting the trajectories of hand movements as participants make decisions in experiments. These response trajectories offer a fine-grained glimpse into ongoing cognitive processes. For example, difficult decisions show more hesitation and deflection from the optimal path than easy decisions. However, many summary statistics used for trajectories throw away much information, or are correlated and thus partially redundant. To alleviate these issues, we introduce Gaussian process regression for the purpose of modeling trajectory data collected in psychology experiments. Gaussian processes are a well-developed statistical model that can find parametric differences in trajectories and their derivatives (e.g., velocity and acceleration) rather than a summary statistic. We show how Gaussian process regression can be implemented hierarchically across conditions and subjects, and used to model the actual shape and covariance of the trajectories. Finally, we demonstrate how to construct a generative hierarchical Bayesian model of trajectories using Gaussian processes