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At least 19 records

Effects of group size and group density on trade–offs in resource selection by a group–territorial central–place foraging woodpecker

Trade-offs in resource selection by central-place foragers are driven by the need to balance the benefits of selecting resources against the costs of travel from the central place. For group-territorial central-place foraging birds, trade-offs in resource selection are likely to be complicated by a competitive advantage for larger groups at high group density that may limit accessibility of high-quality distant resources to small groups. We used the group-territorial, central-place foraging Red-cockaded Woodpecker Leuconotopicus borealis (RCW) as a case study to test predictions that increases in group density lead to differences in foraging distances and resource selection for groups of different sizes. We used GPS tracking and LiDAR-derived habitat data to model effects of group size on foraging distances and selection for high-quality pines (≥ 35.6 cm diameter at breast height (dbh)) and lower quality pines (25.4–35.6 cm dbh) by RCW groups across low ( n = 14), moderate ( n = 10) and high group density ( n = 10) conditions. At low and moderate group density, all RCW groups selected distant high-quality pines in addition to those near the central place because competition for resources was low. In contrast, at high group density, larger groups travelled further to select high-quality pines, whereas smaller groups selected high-quality pines only when they were close to the central place and, conversely, were more likely to select lower quality pines at greater distances from the central place. Selection for high-quality pines only when close to the cavity tree cluster at high group density is important to long-term fitness of small RCW groups because it allows them to maximize benefits from both territorial defence and selecting high-quality resources while minimizing costs of competition. Furthermore these relationships suggest that intraspecific competition at high group density entails substantive costs to smaller groups of territorial central-place foragers by limiting accessibility of distant high-quality foraging resources.

60 APPLIED LIFE SCIENCES↗

Solving the sample size problem for resource selection functions

Abstract Sample size sufficiency is a critical consideration for estimating resource selection functions (RSFs) from GPS‐based animal telemetry. Cited thresholds for sufficiency include a number of captured animals and as many relocations per animal N as possible. These thresholds render many RSF‐based studies misleading if large sample sizes were truly insufficient, or unpublishable if small sample sizes were sufficient but failed to meet reviewer expectations. We provide the first comprehensive solution for RSF sample size by deriving closed‐form mathematical expressions for the number of animals M and the number of relocations per animal N required for model outputs to a given degree of precision. The sample sizes needed depend on just 3 biologically meaningful quantities: habitat selection strength, variation in individual selection and a novel measure of landscape complexity, which we define rigorously. The mathematical expressions are calculable for any environmental dataset at any spatial scale and are applicable to any study involving resource selection (including sessile organisms). We validate our analytical solutions using globally relevant empirical data including 5,678,623 GPS locations from 511 animals from 10 species (omnivores, carnivores and herbivores living in boreal, temperate and tropical forests, montane woodlands, swamps and Arctic tundra). Our analytic expressions show that the required M and N must decline with increasing selection strength and increasing landscape complexity, and this decline is insensitive to the definition of availability used in the analysis. Our results demonstrate that the most biologically relevant effects on the utilization distribution (i.e. those landscape conditions with the greatest absolute magnitude of resource selection) can often be estimated with much fewer than animals. We identify several critical steps in implementing these equations, including (a) a priori selection of expected model coefficients and (b) regular sampling of background (pseudoabsence) data within a given definition of availability. We discuss possible methods to identify a priori expectations for habitat selection coefficients, effects of scale on RSF estimation and caveats for rare species applications. We argue that these equations should be a mandatory component for all future RSF studies.

Street, Garrett M.↗

Stochastic Programming Approach for Resource Selection under Demand Uncertainty

Cost-efficient selection and scheduling of a subset of geographically distributed resources to meet the demands of a scientific workflow is a challenging problem. The problem is exacerbated by uncertainties in demand and availability of resources. In this paper, we present a stochastic optimization based framework for robust decision making in the selection of distributed resources over a planning horizon under demand uncertainty. We present a novel two-stage stochastic programming model for resource selection, and implement an L-shaped decomposition algorithm to solve this model. A Sample Average Approximation algorithm is integrated to enable stochastic optimization to solve problems with a large number of scenarios. Using the metric of stochastic solution, we demonstrate up to 30% cost reduction relative to solutions without explicit consideration of demand uncertainty for a 24-month problem. We also demonstrate up to 54% cost reduction relative to a previously developed solution for a 36-month problem. We further argue that the composition of resources selected is superior to solutions computed without explicit consideration of uncertainties. Given the importance of resource selection and scheduling of complex scientific workflows, especially in the context of commercial cloud computing, we believe that our novel stochastic programming framework will benefit many researchers as well as users of distributed computing resources.

scientific workflows, task scheduling, optimizatio↗

Home range and resource selection of Virginia opossums in the rural southeastern United States

The Virginia opossum (Didelphis virginiana) has a rapidly expanding distribution in North America, but many aspects of its ecology remain relatively understudied, particularly in rural areas of its core range. We collected GPS telemetry data from 93 opossums in a rural, non-agricultural landscape in South Carolina, USA (2018–2019) to examine factors influencing space use and resource selection. Estimated male home ranges (99% utilization distributions) were on average 50% larger than those of females (mean home range 115.9 ± 103.7 ha vs 76.7 ± 75.0 ha). The home range size decreased on average by 20% with each 20% increase in deciduous land cover but was not affected by season or other landscape factors. Core area sizes (65% utilization distributions) were not influenced by sex (mean core area size 29.1 ± 23.7 ha and 22.4 ha ± 13.8 for males and females, respectively) or season, but the core area size decreased by 14% with each 400 m increase in distance from a permanent water source. Resource selection by opossums primarily occurred at the landscape level. Both males and females generally selected for wetlands while avoiding pine forests and developed/open areas, likely the result of differences in resource availability and predation risk between habitats. Opossums also tended to select for linear features such as unpaved roads and edge habitat, which may facilitate movement across the landscape. Finally, the home ranges we documented are among the largest recorded for opossums in the USA, likely the result of the relatively low resource abundance throughout our study area due to comparatively minimal anthropogenic influence.

59 BASIC BIOLOGICAL SCIENCES↗

Resource selection functions based on hierarchical generalized additive models provide new insights into individual animal variation and species distributions

Habitat selection studies are designed to generate predictions of species distributions or inference regarding general habitat associations and individual variation in habitat use. Such studies frequently involve either individually indexed locations gathered across limited spatial extents and analyzed using resource selection functions (RSFs) or spatially extensive locational data without individual resolution typically analyzed using species distribution models. Both analytical methodologies have certain desirable features, but analyses that combine individual- and population-level inference with flexible non-linear functions may provide improved predictions while accounting for individual variation. Here, we describe how RSFs can be fit using hierarchical generalized additive models (HGAMs) using widely available software, providing a means to explore individual variation in habitat associations and to generate species distribution maps. We used GPS tracking data from golden eagles Aquila chrysaetos from across eastern North America with four environmental predictors to generate monthly distribution models. We considered three model structures that assumed different amounts of individual variation in the functional relationship between predictors and habitat use and used k-fold cross-validation to compare model performance. Models accounting for individual variability in shape and smoothness of functional responses performed best. Eagles exhibited the least amount of individual variation in response to land cover variables during winter months, with most individuals more closely adhering to the population-level trend. During the summer months, eagles exhibited more substantial individual variation in shape and smoothness of the functional relationships, suggesting some need to account for individual variation in eagle habitat use for both inferential and predictive purposes, during this time of year. Because they allow users to blend flexible functions with random effects structures and are well-supported by a variety of software platforms, we believe that HGAMs provide a useful addition to the suite of analyses used for modeling habitat associations or predicting species distributions.

54 ENVIRONMENTAL SCIENCES↗

Resource selection and species interactions between native and non‐native fishes in a simulated stream system

Abstract Effective fishery management necessitates understanding of resource partitioning by fishes that inhabit complex systems composed of biotic and abiotic features. Evaluations of non‐native species introductions have continually demonstrated adverse effects associated with abundance and distribution of native fishes. Therefore, understanding resource selection and interactions between native and non‐native species is important for recovery efforts. Habitat use by two native fish species (largescale sucker Catostomus macrocheilus [Girard] and mountain whitefish Prosopium williamsoni [Girard]) and one non‐native fish species (pumpkinseed Lepomis gibbosus [Linnaeus]) of the Kootenai River, Idaho, were evaluated in a laboratory stream system. Trials were conducted in allopatry and in sympatry with and without the presence of wood to describe habitat selection in the context of on‐going habitat rehabilitation efforts. Interactions were evident between native largescale sucker and non‐native pumpkinseed concerning use of a woody structure and current velocity. Mountain whitefish used low‐velocity habitats and selected locations that were further from wood when in sympatry with pumpkinseed. Our research suggests that habitat use of native, large‐river fishes may be influenced by the presence of a non‐native species, and that considering such interactions is critical when designing and implementing habitat rehabilitation efforts in river ecosystems.

Branigan, Philip R.↗

Behavioral state resource selection in invasive wild pigs in the Southeastern United States

Elucidating correlations between wild pig ( Sus scrofa ) behavior and landscape attributes can aid in the advancement of management strategies for controlling populations. Using GPS data from 49 wild pigs in the southeastern U.S., we used hidden Markov models to define movement path characteristics and assign behaviors (e.g., resting, foraging, travelling). We then explored the connection between these behaviors and resource selection for both sexes between two distinct seasons based on forage availability (i.e., low forage, high forage). Females demonstrated a crepuscular activity pattern in the high-forage season and a variable pattern in the low-forage season, while males exhibited nocturnal activity patterns across both seasons. Wild pigs selected for bottomland hardwoods and dense canopy cover in all behavioral states in both seasons. Males selected for diversity in vegetation types while foraging in the low-forage season compared to the high-forage season and demonstrated an increased use of linear anthropogenic features across seasons while traveling. Wild pigs can establish populations and home ranges in an array of landscapes, but our results demonstrate male and female pigs exhibit clear differences in movement behavior and there are key resources associated with common behaviors that can be targeted to improve the efficiency of management programs.

54 ENVIRONMENTAL SCIENCES↗

BReW: Blackbox Resource Selection for e-Science Workflows

Workflows are commonly used to model data intensive scientific analysis. As computational resource needs increase for eScience, emerging platforms like clouds present additional resource choices for scientists and policy makers. We introduce BReW, a tool enables users to make rapid, highlevel platform selection for their workflows using limited workflow knowledge. This helps make informed decisions on whether to port a workflow to a new platform. Our analysis of synthetic and real eScience workflows shows that using just total runtime length, maximum task fanout, and total data used and produced by the workflow, BReW can provide platform predictions comparable to whitebox models with detailed workflow knowledge.

97 MATHEMATICS AND COMPUTING↗

A2Cloud‐RF : A random forest based statistical framework to guide resource selection for high‐performance scientific computing on the cloud

Summary This article proposes a random‐forest based A2Cloud framework to match scientific applications with Cloud providers and their instances for high performance. The framework leverages four engines for this task: PERF engine, Cloud trace engine, A2Cloud‐ext engine, and the random forest classifier (RFC) engine. The PERF engine profiles the application to obtain performance characteristics, including the number of single‐precision (SP) floating‐point operations (FLOPs), double‐precision (DP) FLOPs, x87 operations, memory accesses, and disk accesses. The Cloud trace engine obtains the corresponding performance characteristics of the selected Cloud instances including: SP floating point operations per second (FLOPS), DP FLOPS, x87 operations per second, memory bandwidth, and disk bandwidth. The A2Cloud‐ext engine uses the application and Cloud instance characteristics to generate objective scores that represent the application‐to‐Cloud match. The RFC engine uses these objective scores to generate two types of random forests to assist users with rapid analysis: application‐specific random forests (ARF) and application‐class based random forests. The ARF consider only the input application's characteristics to generate a random forest and provide numerical ratings to the selected Cloud instances. To generate the application‐class based random forests, the RFC engine downloads the application profiles and scores of previously tested applications that perform similar to the input application. Using these data, the RFC engine creates a random forest for instance recommendation. We exhaustively test this framework using eight real‐world applications across 12 instances from different Cloud providers. Our tests show significant statistical agreement between the instance ratings given by the framework and the ratings obtained via actual Cloud executions.

Samuel, David↗

Evidence of niche differentiation for two sympatric vulture species in the Southeastern United States

As obligate scavengers utilizing similar habitats, interspecific competition undoubtedly occurs between resident black (Coragyps atratus) and turkey (Cathartes aura) vultures. In the interest of exploring how sympatric species coexist through habitat segregation, we examined resource selection of resident black and turkey vultures in the southeastern United States (US) for evidence of niche differentiation. Using fine-scale movement data, we assessed interspecific seasonal differences in monthly roost reuse frequency and roost site fidelity, as well as monthly flight, roost, and diurnal rest site resource selection based on > 2.8 million locations of 9 black vultures and 9 turkey vultures tracked from September 2013 to August 2015 using Groupe Spécial Mobile/Global Positioning System (GSM/GPS) transmitters. Black vultures generally exhibited greater roost fidelity as well as a greater maximum number of nights spent at a single roost than turkey vultures. Patterns of flight, roost, and resting habitat selection within the home range varied monthly as well as between species, providing evidence for habitat segregation and niche differentiation by sympatric vultures. In particular, our results indicate the importance of wooded wetlands for resting and roosting locations for both species, and revealed clear differences in the use of forested habitats between species during flight, resting, and roosting behavioral states. By examining differences in resource selection and spatial ecology of black and turkey vultures across a range of behaviors, this study demonstrates mechanisms of niche differentiation in these ecologically similar species, and enhances potential for conservation and informed management of this important group of birds.

59 BASIC BIOLOGICAL SCIENCES↗

Use of LiDAR to define habitat thresholds for forest bird conservation

Quantifying species-habitat relationships provides guidance for establishment of recovery standards for endangered species, but research on forest bird habitat has been limited by availability of fine-grained forest structure data across broad extents. New tools for collection of data on forest bird response to fine-grained forest structure provide opportunities to evaluate habitat thresholds for forest birds. We used LiDAR-derived estimates of habitat attributes and resource selection to evaluate foraging habitat thresholds for recovery of the federally endangered red-cockaded woodpecker (Leuconotopicus borealis; RCW) on the Savannah River Site, South Carolina.

60 APPLIED LIFE SCIENCES↗

Sedimentary Geothermal Resources in Nevada, Utah, Colorado, and Texas

The objectives of this project were to (1) perform a literature review of sedimentary geothermal resources, (2) identify data sources and develop data-collection methodologies that characterize selected resources, (3) screen sedimentary basins and formations for sedimentary geothermal potential, and (4) evaluate the technical feasibility of one or more selected locations. Numerous publications have characterized geothermal resources within sedimentary basins. A literature search reviewed publications describing resources located in Colorado, Louisiana, Nevada, Texas, Utah, and Wyoming. The most attractive resources have high temperature gradients, low drilling costs, and reservoir permeabilities greater than 10 millidarcies (mD). Prospects in Colorado, Nevada, Texas, and Utah exhibit attractive characteristics and were chosen for further analysis. Sedimentary resources in Nevada and Utah are most attractive, followed by tested resources in Texas and untested resources in Colorado. The identified resources in Wyoming and Louisiana had lower geothermal gradients and were not evaluated. Reservoir modeling and techno-economic analysis were performed at Marys River Basin–North in Nevada. Geothermal energy production at this location is expected to have a levelized cost of energy (LCOE) ranging between 10 and 20 cents/kWh. Additional work may result in lower LCOE estimates at this location and at other attractive prospects in these three regions. The Great Basin carbonate and alluvial aquifer system of eastern Nevada and western Utah includes a lower carbonate aquifer unit, which has the potential for hosting both conduction- and convection-dominated geothermal systems. Mapping has identified lateral thickness variability expressed as a roughly 120–150-km-wide central corridor, which hosts the thickest and most continuous formations and extends from near Las Vegas north to the Idaho border. Purchase and analysis of privately held legacy seismic data could potentially compensate for the lack of sufficient data documenting measured depth to the lower carbonate aquifer unit. Multiple orogenies, extension episodes, and intrusive events have deformed and displaced the target formations of the lower carbonate aquifer unit. This structural complexity and potential for dipping reservoirs emphasizes the need for detailed geological, geophysical, and reservoir modeling. Heat flow within three Colorado sedimentary basins reviewed as part of this study was calculated in targeted studies by the Colorado Geologic Survey and Colorado School of Mines. These calculations are based on bottom-hole temperature data sets with significant limitations and some variability but produce values consistently higher than the global continental average of 65 mW/m2 for all three basins. Heat flow in the Raton Basin is the highest; however, permeability measurements from specific sedimentary formations with high heat flow have not been obtained. Promising formations for sedimentary geothermal systems were found in all three regions studied—Nevada-Utah, Colorado, and Texas. The next steps for developing sedimentary geothermal resources vary due to differences in available data and resource uncertainties. Additional scopes of work are recommended for identified basins in these three regions.

15 GEOTHERMAL ENERGY↗

Promoting environmental sustainability via an expert elicitation process

Environmental sustainability (ES) planning was applied to the 981-mile, commercially navigable Ohio River. Navigation improvement needs were identified within the broad study along with actions to restore aquatic and riparian ecological resources to a higher state of sustainability. The actions were identified via an Expert Elicitation Process (EEP) involving aquatic and riparian/terrestrial experts knowledgeable of Ohio River resources. The received information was synthesized into goals for the selected resources (Valued Ecosystem Components - or VECs), actions or measures to attain the goals, and monitoring to evaluate conditions. Finally, 26 types of ES actions were identified and classified into three ES alternatives. These alternatives were then evaluated relative to key decision criteria, and such evaluations, based on pertinent decision criteria, were also conducted for four navigation improvement alternatives. Finally, the best combination of ES and navigation alternatives was identified. The key lessons derived from this use of EEP were that: (1) EEP can support the preliminary identification of ES measures; however, more detailed study of specific designs and cost evaluations will be necessary; (2) the method promotes collaboration between key scientists and policymakers from governmental agencies and private sectors, and such collaboration will ultimately provide the foundation for implementation of sustainability actions; and (3) an effective EEP does not occur by accident, it requires careful planning, implementation, and documentation. - Research Highlights: > Use of an Expert Elicitation Process (EEP) is demonstrated in this study. > EEP was used to identify Environmental Sustainability (ES) needs for the Ohio River. > EEP helped develop consensus among resource experts on ES needs. > EEP promotes collaboration to identify and contribute to common resource goals. > EEP may be used in assessing cumulative effects and formulating restoration plans.

54 ENVIRONMENTAL SCIENCES↗

Habitat quality influences trade-offs in animal movement along the exploration–exploitation continuum

Abstract To successfully establish itself in a novel environment, an animal must make an inherent trade-off between knowledge accumulation and exploitation of knowledge gained (i.e., the exploration–exploitation dilemma). To evaluate how habitat quality affects the spatio-temporal scale of switching between exploration and exploitation during home range establishment, we conducted experimental trials comparing resource selection and space-use of translocated animals to those of reference individuals using reciprocal translocations between habitat types of differing quality. We selected wild pigs ( Sus scrofa ) as a model species to investigate hypotheses related to the movement behavior of translocated individuals because they are globally distributed large mammals that are often translocated within their introduced range to facilitate recreational hunting. Individuals translocated to higher quality habitat (i.e. higher proportions of bottomland hardwood habitats) exhibited smaller exploratory movements and began exploiting resources more quickly than those introduced to lower quality areas, although those in lower-quality areas demonstrated an increased rate of selection for preferred habitat as they gained knowledge of the landscape. Our data demonstrate that habitat quality mediates the spatial and temporal scale at which animals respond behaviorally to novel environments, and how these processes may determine the success of population establishment.

59 BASIC BIOLOGICAL SCIENCES↗

TU-CD-213-00: Administrative Aspects of Medical Physics

As part of the AAPM’s Scope of Practice, medical physicists are expected to collaborate effectively with practioners and allied health care providers. Interpersonal skills such as communication, negotiation and persuasion are vital for successful collaboration to achieve shared goals. This session will provide some theoretical background of these interpersonal skills as well as specific techniques and practical tools to influence others. Applications of these interpersonal skills for administrative and human resource management purposes vital to medical physicists will be shared. Session attendees will gain knowledge and tools to help them effectively collaborate with administrative and physician leaders in areas such as capital and human resource selection, prioritization, and implementation. Participants will hear methods of how to articulate their goals and to understand the goals of administration, helping ensure alignment of purpose. Session speakers will present one of the topics: equipment selection, budget creation, contracts, and program-related policy development. Specifics may include designing a business case in language that administrators understand, calculating the prioritization of budget requests, and influencing policies for safe and effective care. Human resource topics may include staffing justification, recruitment for fit, employment contracts, and benefits. Speakers will provide examples in both radiation therapy and diagnostic imaging departments and will share experiences and outcomes of their approaches for better results. Learning Objectives: After this course attendees will be better able to Understand the shared goal between administrative and physicist leadership. Articulate the “why” of the technical or human resource need. Utilize communication, negotiation and persuasion tools to improve collaboration.

60 APPLIED LIFE SCIENCES↗

TU-CD-213-01: Communication, Negotiation, and Persuasion: Approaches for Better Results

As part of the AAPM’s Scope of Practice, medical physicists are expected to collaborate effectively with practioners and allied health care providers. Interpersonal skills such as communication, negotiation and persuasion are vital for successful collaboration to achieve shared goals. This session will provide some theoretical background of these interpersonal skills as well as specific techniques and practical tools to influence others. Applications of these interpersonal skills for administrative and human resource management purposes vital to medical physicists will be shared. Session attendees will gain knowledge and tools to help them effectively collaborate with administrative and physician leaders in areas such as capital and human resource selection, prioritization, and implementation. Participants will hear methods of how to articulate their goals and to understand the goals of administration, helping ensure alignment of purpose. Session speakers will present one of the topics: equipment selection, budget creation, contracts, and program-related policy development. Specifics may include designing a business case in language that administrators understand, calculating the prioritization of budget requests, and influencing policies for safe and effective care. Human resource topics may include staffing justification, recruitment for fit, employment contracts, and benefits. Speakers will provide examples in both radiation therapy and diagnostic imaging departments and will share experiences and outcomes of their approaches for better results. Learning Objectives: After this course attendees will be better able to Understand the shared goal between administrative and physicist leadership. Articulate the “why” of the technical or human resource need. Utilize communication, negotiation and persuasion tools to improve collaboration.

60 APPLIED LIFE SCIENCES↗

TU-CD-213-02: Communication, Negotiation, and Persuasion: Approaches for Better Results

As part of the AAPM’s Scope of Practice, medical physicists are expected to collaborate effectively with practioners and allied health care providers. Interpersonal skills such as communication, negotiation and persuasion are vital for successful collaboration to achieve shared goals. This session will provide some theoretical background of these interpersonal skills as well as specific techniques and practical tools to influence others. Applications of these interpersonal skills for administrative and human resource management purposes vital to medical physicists will be shared. Session attendees will gain knowledge and tools to help them effectively collaborate with administrative and physician leaders in areas such as capital and human resource selection, prioritization, and implementation. Participants will hear methods of how to articulate their goals and to understand the goals of administration, helping ensure alignment of purpose. Session speakers will present one of the topics: equipment selection, budget creation, contracts, and program-related policy development. Specifics may include designing a business case in language that administrators understand, calculating the prioritization of budget requests, and influencing policies for safe and effective care. Human resource topics may include staffing justification, recruitment for fit, employment contracts, and benefits. Speakers will provide examples in both radiation therapy and diagnostic imaging departments and will share experiences and outcomes of their approaches for better results. Learning Objectives: After this course attendees will be better able to Understand the shared goal between administrative and physicist leadership. Articulate the “why” of the technical or human resource need. Utilize communication, negotiation and persuasion tools to improve collaboration.

60 APPLIED LIFE SCIENCES↗

TU-CD-213-03: Communication, Negotiation, and Persuasion: Approaches for Better Results

As part of the AAPM’s Scope of Practice, medical physicists are expected to collaborate effectively with practioners and allied health care providers. Interpersonal skills such as communication, negotiation and persuasion are vital for successful collaboration to achieve shared goals. This session will provide some theoretical background of these interpersonal skills as well as specific techniques and practical tools to influence others. Applications of these interpersonal skills for administrative and human resource management purposes vital to medical physicists will be shared. Session attendees will gain knowledge and tools to help them effectively collaborate with administrative and physician leaders in areas such as capital and human resource selection, prioritization, and implementation. Participants will hear methods of how to articulate their goals and to understand the goals of administration, helping ensure alignment of purpose. Session speakers will present one of the topics: equipment selection, budget creation, contracts, and program-related policy development. Specifics may include designing a business case in language that administrators understand, calculating the prioritization of budget requests, and influencing policies for safe and effective care. Human resource topics may include staffing justification, recruitment for fit, employment contracts, and benefits. Speakers will provide examples in both radiation therapy and diagnostic imaging departments and will share experiences and outcomes of their approaches for better results. Learning Objectives: After this course attendees will be better able to Understand the shared goal between administrative and physicist leadership. Articulate the “why” of the technical or human resource need. Utilize communication, negotiation and persuasion tools to improve collaboration.

60 APPLIED LIFE SCIENCES↗