Effective Engagement Techniques Across the Agricultural Conservation Practice Adoption Process.

Encouraging agricultural landowners to adopt conservation practices is crucial to enhancing ecosystem services in privately-owned farm landscapes. To improve engagement with landowners and increase adoption rates, much research has been dedicated to investigating how different psychological, social, economic, and political factors correlate with adoption. However, these studies largely measure adoption as a discrete, binary event. Doing so obscures sequences of landowner decisions and engagement techniques that conservation practitioners use to encourage landowners' progression through the adoption process. We report on two studies that contribute to the emerging literature on the agricultural conservation practice adoption process and the varying effectiveness of engagement techniques throughout. First, interviews with conservation practitioners in the Chesapeake Bay watershed, USA, yielded a preliminary model of the different stages in the adoption process and what techniques practitioners find effective at each stage. Second, an online experiment examined the effectiveness of a visualization intervention across two sequential outcomes in the adoption process, seeking further information and contacting a practitioner. Our results suggested that practitioners use a wide variety of engagement techniques, most of which are unique to a single stage in the adoption process, and that the effectiveness of the visualization technique varies substantially between different stages. Together these studies outline a suite of techniques that other practitioners may find effective at different stages of the adoption process, and suggest that research can better inform practice by accounting for variation in the effectiveness of different techniques across stages of adoption.

Introducing Elinor for monitoring the governance and management of area-based conservation.

Monitoring the governance and management effectiveness of area-based conservation has long been recognized as an important foundation for achieving national and global biodiversity goals and enabling adaptive management. However, there are still many barriers that prevent conservation actors, including those affected by governance and management systems from implementing conservation activities and programs and from gathering and using data on governance and management to inform decision-making across spatial scales and through time. We explored current and past efforts to assess governance and management effectiveness and barriers actors face in using the resulting data and insights to inform conservation decision-making. To help overcome these barriers, we developed Elinor, a free and open-source monitoring tool that builds on the work of Nobel Prize winner Elinor Ostrom to facilitate the gathering, storing, sharing, analyzing, and use of data on environmental governance and management across spatial scales and for areas under different governance and management types. We consider the process of codesigning and piloting Elinor with conservation scientists and practitioners and the main components of the assessment and online data system. We also consider how Elinor complements existing approaches by addressing governance and management in a single assessment at a high level for different types of area-based conservation, providing flexible options for data collection, and integrating a data system with an assessment that can support data use and sharing across different spatial scales, including global monitoring of the Global Biodiversity Framework. Although challenges will continue, the process of developing Elinor and the tool itself offer tangible solutions to barriers that prevent the systematic collection and use of governance and management data. With broader uptake, Elinor can play a valuable role in enabling more effective, inclusive, and durable area-based conservation.

Introducción de Elinor para el monitoreo de la gobernanza y la gestión de la conservación con base en zonas geográficas Resumen El monitoreo de la efectividad de la gobernanza y de la gestión de la conservación basada en zonas geográficas ha sido reconocido durante mucho tiempo como una base importante para alcanzar las metas nacionales y mundiales de la biodiversidad y permitir un manejo adaptativo. Sin embargo, todavía existen barreras que evitan que los actores de la conservación, incluidos aquellos afectados por los sistemas de gobernanza y gestión, implementen actividades y programas de conservación y recopilen y usen datos de la gobernanza y la gestión para informar las decisiones a lo largo de las escalas espaciales y a través del tiempo. Exploramos los esfuerzos hechos en la actualidad y en el pasado para evaluar la efectividad de la gobernanza y la gestión así como las barreras que los actores enfrentan al usar los datos y el conocimiento resultantes para informar la toma de decisiones de conservación. Para ayudar a derribar estas barreras desarrollamos Elinor, una herramienta de monitoreo gratuita y de software libre que parte del trabajo de la ganadora del Premio Nobel Elinor Ostrom, para facilitar la recopilación, almacenamiento, divulgación, análisis y uso de los datos sobre la gobernanza y la gestión ambiental en las escalas espaciales y para las zonas con diferentes tipos de gobernanza y gestión. Planteamos co­diseñar y pilotear Elinor con los científicos y practicantes de la conservación y usando los componentes principales del sistema de evaluación y de datos en línea. También planteamos cómo Elinor complementa las estrategias existentes al abordar la gobernanza y la gestión en una sola evaluación a un nivel elevado para diferentes tipos de conservación basada en zonas geográficas, lo que proporciona opciones flexibles para la colecta de datos, e integramos un sistema de datos con una evaluación que soporta el uso y divulgación de datos en diferentes escalas espaciales, incluido el Marco Mundial para la Biodiversidad. Aunque los retos seguirán existiendo, el proceso de desarrollo de Elinor y la propia herramienta ofrecen soluciones tangibles a las barreras que previenen la colecta sistemática y el uso de datos de la gobernanza y la gestión. Con una mayor aceptación, Elinor puede tener un papel importante en el momento de hacer posible una conservación basada en zonas geográficas más eficaz, integradora y duradera.

Design of Linear Block Copolymers and ABC Star Terpolymers That Produce Two Length Scales at Phase Separation.

Quasicrystals (materials with long-range order but without the usual spatial periodicity of crystals) were discovered in several soft matter systems in the last 20 years. The stability of quasicrystals has been attributed to the presence of two prominent length scales in a specific ratio, which is 1.93 for the 12-fold quasicrystals most commonly found in soft matter. We propose design criteria for block copolymers such that quasicrystal-friendly length scales emerge at the point of phase separation from a melt, basing our calculations on the Random Phase Approximation. We consider two block copolymer families: linear chains containing two different monomer types in blocks of different lengths, and ABC star terpolymers. In all examples, we are able to identify parameter windows with the two length scales having a ratio of 1.93. The models that we consider that are simplest for polymer synthesis are, first, a monodisperse ALBASB melt and, second, a model based on random reactions from a mixture of AL, AS, and B chains: both feature the length scale ratio of 1.93 and should be relatively easy to synthesize.

Assessing intervention effectiveness at promoting voluntary conservation practice adoption in agrienvironments.

Although implementing conservation practices on private farms and forests can produce substantial environmental benefits, these practices are not being adopted widely enough to result in measurable improvements at regional scales. Researchers have investigated the production and program factors influencing producer choices to voluntarily adopt these practices. However, the findings of reviews are inconsistent, raising questions about review methods, including the omission of relevant variables. Further, applying lessons from past work to promote adoption is difficult because many reviews investigated dispositional or demographic variables that practitioners and policy makers cannot directly observe or influence. We conducted a new review of 146 empirical studies that tested the effects of different interventions (e.g., financial incentives, outreach events, and nudges) on increasing the likelihood of producers adopting conservation practices. We conducted a metaregression of quantitative studies from diverse disciplines that filtered studies by quality (i.e., use of randomization and clear analysis reporting). We synthesized these results with a thematic analysis of qualitative studies on producer perspectives about conservation practices. Financial incentives had the strongest evidence of increasing producers' likelihood of adopting conservation practices (odds ratio 1.86, p < 0.05). However, this effect was only apparent after filtering by study quality, which also improved model fit and identified significant regional differences (odds ratio -1.69, p < 0.01). The thematic review of qualitative studies revealed that peer groups may be successful in reinforcing adoption behaviors due to homophily effects and that financial incentives not only offset implementation costs but also mitigated perceived risks of adoption. Given the problems we encountered in testing hypotheses about the magnitude of variability explained by intervention types and practice characteristics, we recommend additional experimental and longitudinal work that accounts for financial incentives and pairs qualitative and quantitative data to clarify relationships between program design and practice adoption rates.

Evaluación de la efectividad de las intervenciones en la promoción de la adopción de prácticas de conservación voluntaria en los agroecosistemas Resumen Aunque la implementación de prácticas de conservación en granjas y bosques privados puede producir beneficios ambientales sustanciales, estas prácticas no se adoptan lo suficiente como para tener mejoras medibles en escalas regionales. Los investigadores han estudiado los factores de producción y programación que influyen sobre la elección de los productores de adoptar voluntariamente estas prácticas. Sin embargo, los hallazgos de las revisiones son inconsistentes, lo que genera preguntas sobre los métodos de revisión, incluyendo la omisión de variables relevantes. Además, es complicado aplicar lo aprendido en trabajos previos para promover la adopción porque muchas revisiones investigaron las variables demográficas y de disposición que los practicantes y los formuladores de políticas no pueden observar o influir directamente. Realizamos una nueva revisión de 146 estudios empíricos que analizaron los efectos de diferentes intervenciones (p. ej.: incentivos económicos, eventos de divulgación, estímulos) sobre el incremento de la probabilidad de que los productores adopten prácticas de conservación. Realizamos la meta regresión de estudios cuantitativos a partir de diferentes disciplinas que filtraron los estudios por calidad (uso de aleatorización y reporte claro de análisis). Sintetizamos estos resultados con un análisis temático de los estudios cualitativos sobre las perspectivas que tienen los productores de las prácticas de conservación. Los incentivos económicos contaron con la evidencia más sólida de incrementar la probabilidad de que los productores adoptaran prácticas de conservación (proporción de probabilidades 1.86, p < 0.05). Sin embargo, este efecto sólo fue aparente después de filtrar según la calidad del estudio, lo que también mejoró el ajuste del modelo e identificó diferencias regionales significativas (proporción de probabilidades -1.69, p < 0.01). La revisión temática de los estudios cualitativos reveló que los grupos de referencia pueden tener éxito en el refuerzo de los comportamientos de adopción debido a los efectos de homofilia y el hecho de que los incentivos económicos no sólo compensan los costos de implementación, sino también mitigan los riesgos percibidos de la adopción. Ya que nos encontramos con problemas en la prueba de la hipótesis sobre la magnitud de la variabilidad explicada por los tipos de intervención y las características de la práctica, recomendamos una experimentación adicional y trabajo longitudinal que explique los incentivos económicos y empareje los datos cualitativos y cuantitativos para clarificar las relaciones entre el diseño del programa y las tasas de adopción de las prácticas.

Exploring private land conservation non-adopters' attendance at outreach events in the Chesapeake Bay watershed, USA.

BACKGROUND: Outreach events such as trainings, demonstrations, and workshops are important opportunities for encouraging private land operators to adopt voluntary conservation practices. However, the ability to understand the effectiveness of such events at influencing conservation behavior is confounded by the likelihood that attendees are already interested in conservation and may already be adopters. Understanding characteristics of events that draw non-adopters can aid in designing events and messaging that are better able to reach beyond those already interested in conservation. METHODS: For this study, we interviewed 101 operators of private agricultural lands in Maryland, USA, and used descriptive statistics and qualitative comparative analysis to investigate differences between the kinds of outreach events that adopters and non-adopters attended. RESULTS: Our results suggested that non-adopters, as compared to adopters, attended events that provided production-relevant information and were logistically easy to attend. Further, non-adopters were more selective when reading advertisements, generally preferring simplicity. Future research and outreach can build on these findings by experimentally testing the effectiveness of messages that are simple and relevant to farmers' production priorities.

Continuum mechanical parameterisation of cytoplasmic dynein from atomistic simulation.

Cytoplasmic dynein is responsible for intra-cellular transport in eukaryotic cells. Using Fluctuating Finite Element Analysis (FFEA), a novel algorithm that represents proteins as continuum viscoelastic solids subject to thermal noise, we are building computational tools to study the mechanics of these molecular machines. Here we present a methodology for obtaining the material parameters required to represent the flexibility of cytoplasmic dynein within FFEA from atomistic molecular dynamics (MD) simulations, and show that this continuum representation is sufficient to capture the principal dynamic properties of the motor.

Fluctuating viscoelasticity based on a finite number of dumbbells.

Two alternative routes are taken to derive, on the basis of the dynamics of a finite number of dumbbells, viscoelasticity in terms of a conformation tensor with fluctuations. The first route is a direct approach using stochastic calculus only, and it serves as a benchmark for the second route, which is guided by thermodynamic principles. In the latter, the Helmholtz free energy and a generalized relaxation tensor play a key role. It is shown that the results of the two routes agree only if a finite-size contribution to the Helmholtz free energy of the conformation tensor is taken into account. Using statistical mechanics, this finite-size contribution is derived explicitly in this paper for a large class of models; this contribution is non-zero whenever the number of dumbbells in the volume of observation is finite. It is noted that the generalized relaxation tensor for the conformation tensor does not need any finite-size correction.

Combined Force-Torque Spectroscopy of Proteins by Means of Multiscale Molecular Simulation.

Assessing the structural properties of large proteins is important to gain an understanding of their function in, e.g., biological systems or biomedical applications. We propose a method to examine the mechanical properties of proteins subject to applied forces by means of multiscale simulation. Both stretching and torsional forces are considered, and these may be applied independently of each other. As a proof of principle, we apply torsional forces to a coarse-grained continuum model of the antibody protein immunoglobulin G using fluctuating finite element analysis and use it to identify the area of strongest deformation. This region is essential to the torsional properties of the molecule as a whole because it represents the softest, most deformable domain. Zooming in, this part of the molecule is subjected to torques and stretching forces using molecular dynamics simulations on an atomistically resolved level to investigate its torsional properties. We calculate the torsional resistance as a function of the rotation of the domain while subjecting it to various stretching forces. From this, we assess how the measured twist-torque profiles develop with increasing stretching force and show that they exhibit torsion stiffening, in qualitative agreement with experimental findings. We argue that combining the twist-torque profiles for various stretching forces effectively results in a combined force-torque spectroscopy analysis, which may serve as a mechanical signature for a biological macromolecule.

Exploring the dynamics of flagellar dynein within the axoneme with Fluctuating Finite Element Analysis.

Flagellar dyneins are the molecular motors responsible for producing the propagating bending motions of cilia and flagella. They are located within a densely packed and highly organised super-macromolecular cytoskeletal structure known as the axoneme. Using the mesoscale simulation technique Fluctuating Finite Element Analysis (FFEA), which represents proteins as viscoelastic continuum objects subject to explicit thermal noise, we have quantified the constraints on the range of molecular conformations that can be explored by dynein-c within the crowded architecture of the axoneme. We subsequently assess the influence of crowding on the 3D exploration of microtubule-binding sites, and specifically on the axial step length. Our calculations combine experimental information on the shape, flexibility and environment of dynein-c from three distinct sources; negative stain electron microscopy, cryo-electron microscopy (cryo-EM) and cryo-electron tomography (cryo-ET). Our FFEA simulations show that the super-macromolecular organisation of multiple protein complexes into higher-order structures can have a significant influence on the effective flexibility of the individual molecular components, and may, therefore, play an important role in the physical mechanisms underlying their biological function.

KOBRA: a fluctuating elastic rod model for slender biological macromolecules.

KOBRA (KirchOff Biological Rod Algorithm) is an algorithm and software package designed to perform dynamical simulations of elongated biomolecules such as those containing alpha-helices and coiled-coils. It represents these as coarsely-discretised Kirchoff rods, with linear elements that can stretch, bend and twist independently. These rods can have anisotropic and inhomogeneous parameters and bent or twisted equilibrium structures, allowing for a coarse-grained parameterisation of complex biological structures. Each element is non-inertial and subject to thermal fluctuations. The speed and simplicity of the algorithm allows KOBRA rods to easily access timescales from nanoseconds to seconds. To demonstrate this functionality, a KOBRA rod was parameterised using data from all-atom simulations of the Ndc80 protein complex, and compared against these simulations and negative-stain EM images. The distribution of bend angles and principal components were highly correlated between KOBRA, all-atom molecular dynamics, and experimental data. The properties of a hinge region, thought to be found at an unstructured loop, were studied. A C++ implementation of KOBRA is available under the GNU GPLv3 free software licence.

PolySTRAND Model of Flow-Induced Nucleation in Polymers.

We develop a thermodynamic continuum-level model, polySTRAND, for flow-induced nucleation in polymers suitable for use in computational process modeling. The model's molecular origins ensure that it accounts properly for flow and nucleation dynamics of polydisperse systems and can be extended to include effects of exhaustion of highly deformed chains and nucleus roughness. It captures variations with the key processing parameters, flow rate, temperature, and molecular weight distribution. Under strong flow, long chains are over-represented within the nucleus, leading to superexponential nucleation rate growth with shear rate as seen in experiments.

Metastable room-temperature twist-bend nematic phases via photopolymerization.

The heliconical twist-bend nematic (N_{TB}) phase is a promising candidate for novel electro-optic and photonic applications. However, the phase generally exists at elevated temperatures and across a narrow temperature interval, limiting its implementation in device fabrication, which would ideally require the liquid crystal phase to be stable at room temperature. Here we report the formation of room-temperature N_{TB} phases by in situ photopolymerization. A complete phase diagram of the liquid crystal and monomer mixtures is presented and the nature of the polymerized samples is discussed in detail. In contrast to samples before polymerization-where the N_{TB} phases exist at elevated temperatures and across temperature intervals of width <10 °C-all photopolymerized N_{TB} samples are found to be stable at room temperature and exist over a temperature interval of up to 80 °C. Scanning electron microscopy of the polymerized N_{TB} phase shows that the polymer strands assemble at an angle with respect to the direction of the helical axis. This suggests that photopolymerized N_{TB} phases could be used to facilitate the tilt angle measurements in the twist-bend nematic phase.

The relationship between perfectionistic self-presentation and reactions to impairment and disability following spinal cord injury.

Univariate and multivariate relationships between perfectionistic self-presentation and reactions to impairment and disability following spinal cord injury were examined. A total of 144 adults with spinal cord injury ( M = 48.18 years old, SD = 15.96) completed self-report measures. Analyses revealed that, after controlling for time since injury and gender, perfectionistic self-presentation predicted six of eight reactions, shock, depression and internalised anger particularly strongly. In addition, at multivariate level, perfectionistic self-presentation was positively related to non-adaptive reactions and negatively related to adaptive reactions. The findings suggest that perfectionistic self-presentation may contribute to poorer psychosocial adaptation to spinal cord injury.

Fluctuating Finite Element Analysis (FFEA): A continuum mechanics software tool for mesoscale simulation of biomolecules.

Fluctuating Finite Element Analysis (FFEA) is a software package designed to perform continuum mechanics simulations of proteins and other globular macromolecules. It combines conventional finite element methods with stochastic thermal noise, and is appropriate for simulations of large proteins and protein complexes at the mesoscale (length-scales in the range of 5 nm to 1 µm), where there is currently a paucity of modelling tools. It requires 3D volumetric information as input, which can be low resolution structural information such as cryo-electron tomography (cryo-ET) maps or much higher resolution atomistic co-ordinates from which volumetric information can be extracted. In this article we introduce our open source software package for performing FFEA simulations which we have released under a GPLv3 license. The software package includes a C ++ implementation of FFEA, together with tools to assist the user to set up the system from Electron Microscopy Data Bank (EMDB) or Protein Data Bank (PDB) data files. We also provide a PyMOL plugin to perform basic visualisation and additional Python tools for the analysis of FFEA simulation trajectories. This manuscript provides a basic background to the FFEA method, describing the implementation of the core mechanical model and how intermolecular interactions and the solvent environment are included within this framework. We provide prospective FFEA users with a practical overview of how to set up an FFEA simulation with reference to our publicly available online tutorials and manuals that accompany this first release of the package.

Dielectric properties of liquid crystalline dimer mixtures exhibiting the nematic and twist-bend nematic phases.

A detailed investigation of the thermal and dielectric properties of a series of binary mixtures exhibiting the nematic (N) and twist-bend nematic (N_{TB}) liquid crystal phases is presented. The mixtures consist of an achiral, dimeric liquid crystal CB7CB, which forms the nematic and twist-bend nematic phases, and a calamitic liquid crystal 5CB, which shows the nematic phase. As the concentration of the calamitic liquid crystal is increased, the transition temperatures decrease linearly, and the width of the nematic phase increases. The enthalpies of phase transitions obtained from DSC measurements show that on increasing the concentration of 5CB in the binary mixtures, the enthalpy associated with the N-N_{TB} phase transitions reduces considerably compared to a clear first-order N-N_{TB} transition in pure CB7CB. The real and imaginary parts of the dielectric permittivity are measured as a function of frequency from 100 Hz to 2 MHz in the nematic and twist-bend nematic phases in planar and homeotropic devices. A significant decrease in the average dielectric permittivity as a function of temperature for mixtures forming the N_{TB} phase is observed. Measurements of the imaginary part of the dielectric permittivity show a relaxation peak in the measured frequency window for all of the mixtures exhibiting the N_{TB} phase. The activation energy associated with this relaxation process is calculated and is shown to remain constant irrespective of the composition of the mixtures.

Modelling biomacromolecular assemblies with continuum mechanics.

We have developed a continuum mechanical description of proteins using a finite element algorithm which has been generalized to include thermal fluctuations and which is therefore known as fluctuating finite element analysis (FFEA). Whereas conventional molecular dynamics (MD) simulations provide a trajectory in which each individual atomic position fluctuates, a FFEA trajectory shows how the overall shape of the protein changes due to thermal agitation. We describe the theoretical background to FFEA, its relationship to more established biomolecular modelling methods and provide examples of its application to the mesoscale biomolecular dynamics of the molecular motor dynein.

In pursuit of an accurate spatial and temporal model of biomolecules at the atomistic level: a perspective on computer simulation.

Despite huge advances in the computational techniques available for simulating biomolecules at the quantum-mechanical, atomistic and coarse-grained levels, there is still a widespread perception amongst the experimental community that these calculations are highly specialist and are not generally applicable by researchers outside the theoretical community. In this article, the successes and limitations of biomolecular simulation and the further developments that are likely in the near future are discussed. A brief overview is also provided of the experimental biophysical methods that are commonly used to probe biomolecular structure and dynamics, and the accuracy of the information that can be obtained from each is compared with that from modelling. It is concluded that progress towards an accurate spatial and temporal model of biomacromolecules requires a combination of all of these biophysical techniques, both experimental and computational.

Understanding the apparent stator-rotor connections in the rotary ATPase family using coarse-grained computer modeling.

Advances in structural biology, such as cryo-electron microscopy (cryo-EM) have allowed for a number of sophisticated protein complexes to be characterized. However, often only a static snapshot of a protein complex is visualized despite the fact that conformational change is frequently inherent to biological function, as is the case for molecular motors. Computer simulations provide valuable insights into the different conformations available to a particular system that are not accessible using conventional structural techniques. For larger proteins and protein complexes, where a fully atomistic description would be computationally prohibitive, coarse-grained simulation techniques such as Elastic Network Modeling (ENM) are often employed, whereby each atom or group of atoms is linked by a set of springs whose properties can be customized according to the system of interest. Here we compare ENM with a recently proposed continuum model known as Fluctuating Finite Element Analysis (FFEA), which represents the biomolecule as a viscoelastic solid subject to thermal fluctuations. These two complementary computational techniques are used to answer a critical question in the rotary ATPase family; implicit within these motors is the need for a rotor axle and proton pump to rotate freely of the motor domain and stator structures. However, current single particle cryo-EM reconstructions have shown an apparent connection between the stators and rotor axle or pump region, hindering rotation. Both modeling approaches show a possible role for this connection and how it would significantly constrain the mobility of the rotary ATPase family.

In Silico Molecular Design, Synthesis, Characterization, and Rheology of Dendritically Branched Polymers: Closing the Design Loop.

It has been a long held ambition of both industry and academia to understand the relationship between the often complex molecular architecture of polymer chains and their melt flow properties, with the goal of building robust theoretical models to predict their rheology. The established key to this is the use of well-defined, model polymers, homogeneous in chain length and architecture. We describe here for the first time, the in silico design, synthesis, and characterization of an architecturally complex, branched polymer with the optimal rheological properties for such structure-property correlation studies. Moreover, we demonstrate unequivocally the need for accurate characterization using temperature gradient interaction chromatography (TGIC), which reveals the presence of heterogeneities in the molecular structure that are undetectable by size exclusion chromatography (SEC). Experimental rheology exposes the rich pattern of relaxation dynamics associated with branched polymers, but the ultimate test is, of course, did the theoretical (design) model accurately predict the rheological properties of the synthesized model branched polymer? Rarely, if ever before, has such a combination of theory, synthesis, characterization, and analysis resulted in a "yes", expressed without doubt or qualification.