Predicting leadership using nutrient requirements and dominance rank of group members

Group members must decide collectively when and where to go despite their different nutrient requirements. One mechanism underlying consensus decisions is the proposition by one individual to move. The individual frequently initiating movements is often named a “leader”, and this individual may be the most dominant, the oldest or may have the greatest physiological needs. However, high-ranking individuals are often those with the highest body mass, and thus the highest nutrient requirements. In this study, we use a state-dependent model to assess the importance of dominance and nutrient requirements to the initiation of group movements, testing different combinations of effects of these interacting factors. We first show using a theoretical approach that whatever the correlation between the dominance hierarchy and body mass, all decision-making systems are viable (or stable). However, in most cases, one individual does become the leader, and nutrient requirements appear to be more important for determining which individual will emerge as the leader than pre-existing individual characteristics such as their dominance rank. We obtained the same result when we compared the simulated distributions of initiations to the observed distributions in three macaque species. Results of our comparison of three macaque groups suggest that we can predict which group member will be the leader simply by knowing its body mass and its reproductive state. Understanding the link between dominance, needs and leadership may be a key to understanding consensus decisions and collective motion in animal groups, and might provide insight into the management of animal groups and their conservation.     

Planning for change and sustainability in water development in Lao PDR and the Mekong River basin

With its recent opening to the global market economy, the natural resources of the Lao People's Democratic Republic (Lao PDR, referred to in this paper as Laos) – especially its water resources–have attracted external interest and investment. The overall level of water development is low. While even modest development would help Laos meet some of its urgent needs, past experience in Southeast Asia and other tropical regions suggests that fast-paced water development may damage the natural resource base. This article examines some efforts in water development from Southeast Asia and other regions and their relevance to water policy formulation in Laos. Future social and environmental changes in Laos are inevitable, but the nature and direction of these changes are uncertain. It thus makes sense to design policies that are flexible and can be adjusted to, and even take advantage of, a changing social and environmental context. Smaller-scale, deliberately-paced projects which merge local knowledge and external expertise fulfil the requirements of flexibility and adjustability, and are also appropriate for other important reasons: they do not require massive inputs of funding, and they do not initiate large-scale environmental and socio-economic changes. Current knowledge of the complex ecological and social systems in Laos is only sketchy. A slower-paced development will allow developers the necessary time to learn more about these important aspects.     

Reliability and input-data induced uncertainty of the EPIC model to estimate climate change impact on sorghum yields in the U.S. Great Plains

Crop simulation models are frequently used to estimate the impact of climate change on crop production. However, few studies have evaluated the model performance in ways that most researchers practiced in climate impact studies. In this article, we examined the reliability of the EPIC model in simulating grain sorghum (Sorghum bicolor (L.) Moench) yields in the U.S. Great Plains under different climate scenarios, namely in years with normal or extreme temperature and precipitation. We also investigated model uncertainties introduced by input data that are not site-specific but commonly used or available for climate change studies. Historical field trial data of sorghum at the Mead Experimental Center, NE, were used for model evaluations. The results showed that overall model reliability was about 56%. The mean absolute relative error (absRE) was about 29%. The degree of accuracy and reliability varied with climate-classes and nitrogen (N)-treatments. The largest bias occurred in drought years (RE = ?25%) and the most unreliable results were found in N-0 treatment (reliability = 32%). There was more than 69% probability that input-data-induced uncertainties were limited to less than 20% of absRE. Our results support the application of the EPIC model to climate change impact studies in the U.S. Great Plains. However, efforts are needed to improve the accuracy in simulating crop responses to extreme water- and nitrogen-stressed conditions.     

The multiphase optimization strategy (MOST) and the sequential multiple assignment randomized trial (SMART): two novel evaluation methods for developing optimal training programs

Current methodologies in training evaluation studies largely employ a single method entitled random confirmatory trials, prompting several concerns. First, practitioners and researchers often analyze the effectiveness of their entire omnibus training, rather than the individual elements or identifiable components of the training program. This slows the testing of theory and development of optimal training programs. Second, a common training is typically administered to all employees within an organization or workgroup; however, certain factors may cause individualized training to be more effective. Given these concerns, the current paper presents two training evaluation methodologies to overcome these problems: the multiphase optimization strategy and sequential multiple assignment randomized trials. The multiphase optimization strategy is a method to evaluate a standard training, which emphasizes the importance of a multi‐stage training evaluation process to analyze individual training elements. In contrast, sequential multiple assignment randomized trial is used to evaluate an adaptive training that varies over time and/or trainees. These methodologies jointly overcome the problems noted earlier, and they can be integrated to address several of the key challenges facing training researchers and practitioners. Copyright © 2016 John Wiley & Sons, Ltd.     

Mapping "old" vs. "young" pi?on-juniper stands with a predictive topo-climatic model

Pi?on pine and juniper woodlands in the southwestern United States are often represented as an expanding and even invasive vegetation type, a legacy of historic grazing, and culpable in the degradation of western rangelands. A long-standing emphasis on forage production, in combination with recent hazard fuel concerns, has prompted a new era of woodland management with stated restoration objectives. Yet the extent and dynamics of pi?on-juniper communities that predate intensive Euro-American settlement activities are poorly known or understood, while the intrinsic ecological, aesthetic, and economic values of old-growth woodlands are often overlooked. Historical changes in pi?on-juniper stands include two related, but poorly differentiated processes: recent tree expansion into grass- or shrub-dominated (i.e., non-woodland) vegetation and thickening or infilling of savanna or mosaic woodlands predating settlement. Our work addresses the expansion pattern, modeling the occurrence of "older" savanna and woodland stands extant prior to 1850 in contrast to "younger" pi?on-juniper growth of more recent, postsettlement origin. We present criteria in the form of a diagnostic key for distinguishing "older," pre-Euro-American settlement pi?on-juniper from "younger" (post-1850) stands and report results of predictive modeling and mapping efforts within a north-central New Mexico study area. Selected models suggest a primary role for soil moisture in the current distribution of "old" vs. "young" pi?on-juniper stands. Presettlement era woodlands are shown to occupy a discrete ecological space, defined by the interaction of effective (seasonal) moisture with landform setting and fine-scale (soil/water) depositional patterns. "Older" stands are generally found at higher elevations or on skeletal soils in upland settings, while "younger" stands (often dominated by one-seed juniper, Juniperus monosperma) are most common at lower elevations or in productive, depositional settings. Modeling at broad regional scales can enhance our general understanding of pi?on-juniper ecology, while predictive mapping of local areas has potential to provide products useful for land management. Areas of the southwestern United States with strong monsoonal (summer moisture) patterns appear to have been the most susceptible to historical woodland expansion, but even here the great majority of extant pi?on-juniper has presettlement origins (although widely thickened and infilled historically), and old-growth structure is not uncommon in appropriate upland settings.     

CLIMATE SCIENCE AND DROUGHT PLANNING: THE ARIZONA EXPERIENCE1

ABSTRACT: In response to recent severe drought conditions throughout the state, Arizona recently developed its first drought plan. The Governor's Drought Task Force focused on limiting the economic and social impacts of future droughts through enhanced adaptation and mitigation efforts. The plan was designed to maximize the use of new, scientific breakthroughs in climate monitoring and prediction and in vulnerability assessment. The long term objective of the monitoring system is to allow for evaluation of conditions in multiple sectors and at multiple scales. Stakeholder engagement and decision support are key objectives in reducing Arizona's vulnerability in light of the potential for severe, sustained drought. The drivers of drought conditions in Arizona include the El Nino‐Southern Oscillation, the Pacific Decadal Oscillation, and the Atlantic Multidecadal Oscillation.