Economic incentives for biodiversity conservation: what is the evidence for motivation crowding?

As economic incentives for biodiversity and ecosystem service protection (e.g., payments for ecosystem services) have become widespread in environmental science and policy, a major concern among conservationists and environmental scientists is that economic incentives may undermine people’s intrinsic motivations to conserve biodiversity. In this paper we review the theoretical insights and empirical findings on motivation crowding effects with economic instruments for biodiversity protection. First, we synthesize the psychological mechanisms behind motivation crowding effects relevant for environmental behavior as identified in the specialized literature. We then conduct a systematic review of the empirical evidence. Our results show that, although several empirical studies suggest the existence of crowding-out and crowding-in effects, evidence remains inconclusive due to i) methodological limitations for empirical studies to demonstrate crowding effects, ii) lack of adequate baseline information about pre-existing intrinsic motivations, iii) weak comparability of results across case studies resulting from inconsistent terminology and methods, and iv) the complexity stemming from cultural and contextual heterogeneity. We conclude that, as economic instruments for conservation are increasingly implemented, it becomes paramount to develop robust methodologies for assessing pre-existing intrinsic motivations and changes in people’s motivational structures. To address possible detrimental long term effects for conservation outcomes we call for caution in situations where high uncertainties remain

On the effect of thin film growth mechanisms on the specular reflectance of aluminum thin films deposited via filtered cathodic vacuum arc

The optimisation of the specular reflectance of solar collectors is a key parameter to increase the global yield of concentrated solar power (CSP) plants. In this work, the influence of filtered cathodic vacuum arc deposition parameters, particularly working pressure and deposition time, on the specular and diffuse reflectance of aluminium thin films, was studied. Changes in specular reflectance, measured by ultraviolet–visible and near-infrared spectroscopy (UV-vis-NIR) spectro photometry, were directly correlated with thin film elemental concentration depth profiles, obtained by Rutherford backscattering spectrometry (RBS), and surface and cross-sectional morphologies as measured by scanning electron microscopy (SEM) and profilometry. Finally, atomic force microscopy (AFM) provided information on the roughness and growth mechanism of the films. The two contributions to the total reflectance of the films, namely diffuse and specular reflectance, were found to be deeply influenced by deposition conditions. It was proven that working pressure and deposition time directly determine the predominant factor. Specular reflectance varied from 12 to 99.8% of the total reflectance for films grown at the same working pressure of 0.1 Pa and with different deposition times. This transformation could not be attributed to an oxidation of the films as stated by RBS, but was correlated with a progressive modification of the roughness, surface, and bulk morphology of the samples over the deposition time. Hence, the evolution in the final optical properties of the films is driven by different growth mechanisms and the resulting microstructures. In addition to the originally addressed CSP applications the potential of the developed aluminium films for other application rather than CSP, such as, for example, reference material for spectroscopic diffuse reflectance measurements, is also discussed

Mixed-Variable Bayesian Optimization

The optimization of expensive to evaluate, black-box, mixed-variable functions, i.e. functions that have continuous and discrete inputs, is a difficult and yet pervasive problem in science and engineering. In Bayesian optimization (BO), special cases of this problem that consider fully continuous or fully discrete domains have been widely studied. However, few methods exist for mixed-variable domains and none of them can handle discrete constraints that arise in many real-world applications. In this paper, we introduce MiVaBo, a novel BO algorithm for the efficient optimization of mixed-variable functions combining a linear surrogate model based on expressive feature representations with Thompson sampling. We propose an effective method to optimize its acquisition function, a challenging problem for mixed-variable domains, making MiVaBo the first BO method that can handle complex constraints over the discrete variables. Moreover, we provide the first convergence analysis of a mixed-variable BO algorithm. Finally, we show that MiVaBo is significantly more sample efficient than state-of-the-art mixed-variable BO algorithms on several hyperparameter tuning tasks, including the tuning of deep generative models.Comment: IJCAI 2020 camera-ready; 17 pages, extended version with supplementary materia

Characterization of attaching and effacing Escherichia coli (AEEC) isolated from pigs and sheep

BACKGROUND: Attaching and effacing Escherichia coli (AEEC) are characterized by their ability to cause attaching-and-effacing (A/E) lesions in the gut mucosa of human and animal hosts leading to diarrhoea. The genetic determinants for the production of A/E lesions are located on the locus of enterocyte effacement (LEE), a pathogenicity island that also contains the genes encoding intimin (eae). This study reports data on the occurrence of eae positive E. coli carried by healthy pigs and sheep at the point of slaughter, and on serotypes, intimin variants, and further virulence factors of isolated AEEC strains. RESULTS: Faecal samples from 198 finished pigs and 279 sheep were examined at slaughter. The proportion of eae positive samples was 89% for pigs and 55% for sheep. By colony dot-blot hybridization, AEEC were isolated from 50 and 53 randomly selected porcine and ovine samples and further characterized. Strains of the serotypes O2:H40, O3:H8 and O26:H11 were found in both pigs and sheep. In pigs O2:H40, O2:H49, O108:H9, O145:H28 and in sheep O2:H40, O26:H11, O70:H40, O146:H21 were the most prevalent serotypes among typable strains. Eleven different intimin types were detected, whereas gamma2/theta was the most frequent, followed by beta1, epsilon and gamma1. All but two ovine strains tested negative for the genes encoding Shiga toxins. All strains tested negative for the bfpA gene and the EAF plasmid. EAST1 (astA) was present in 18 of the isolated strains. CONCLUSION: Our data show that pigs and sheep are a source of serologically and genetically diverse intimin-harbouring E. coli strains. Most of the strains show characteristics of atypical enteropathogenic E. coli. Nevertheless, there are stx-negative AEEC strains belonging to serotypes and intimin types that are associated with classical enterohaemorrhagic E. coli strains (O26:H11, beta1; O145:H28, gamma1)

Reo + mCRL2: A Framework for Model-checking Dataflow in Service Compositions

The paradigm of service-oriented computing revolutionized the field of software engineering. According to this paradigm, new systems are composed of existing stand-alone services to support complex cross-organizational business processes. Correct communication of these services is not possible without a proper coordination mechanism. The Reo coordination language is a channel-based modeling language that introduces various types of channels and their composition rules. By composing Reo channels, one can specify Reo connectors that realize arbitrary complex behavioral protocols. Several formalisms have been introduced to give semantics to Reo. In their most basic form, they reflect service synchronization and dataflow constraints imposed by connectors. To ensure that the composed system behaves as intended, we need a wide range of automated verification tools to assist service composition designers. In this paper, we present our framework for the verification of Reo using the toolset. We unify our previous work on mapping various semantic models for Reo, namely, constraint automata, timed constraint automata, coloring semantics and the newly developed action constraint automata, to the process algebraic specification language of , address the correctness of this mapping, discuss tool support, and present a detailed example that illustrates the use of Reo empowered with for the analysis of dataflow in service-based process models

Reo + mCRL2: A Framework for Model-Checking Dataflow in Service Compositions

The paradigm of service-oriented computing revolutionized the field of software engineering. According to this paradigm, new systems are composed of existing stand-alone services to support complex cross-organizational business processes. Correct communication of these services is not possible without a proper coordination mechanism. The Reo coordination language is a channel-based modeling language that introduces various types of channels and their composition rules. By composing Reo channels, one can specify Reo connectors that realize arbitrary complex behavioral protocols. Several formalisms have been introduced to give semantics to Reo. In their most basic form, they reflect service synchronization and dataflow constraints imposed by connectors. To ensure that the composed system behaves as intended, we need a wide range of automated verification tools to assist service composition designers. In this paper, we present our framework for the verification of Reo using the mCRL2 toolset. We unify our previous work on mapping various semantic models for Reo, namely, constraint automata, timed constraint automata, coloring semantics and the newly developed action constraint automata, to the process algebraic specification language of mCRL2, address the correctness of this mapping, discuss tool support, and present a detailed example that illustrates the use of Reo empowered with mCRL2 for the analysis of dataflow in service-based process models

Molecular basis of synaptic vesicle cargo recognition by the endocytic sorting adaptor stonin 2

Synaptic transmission depends on clathrin-mediated recycling of synaptic vesicles (SVs). How select SV proteins are targeted for internalization has remained elusive. Stonins are evolutionarily conserved adaptors dedicated to endocytic sorting of the SV protein synaptotagmin. Our data identify the molecular determinants for recognition of synaptotagmin by stonin 2 or its Caenorhabditis elegans orthologue UNC-41B. The interaction involves the direct association of clusters of basic residues on the surface of the cytoplasmic domain of synaptotagmin 1 and a β strand within the μ–homology domain of stonin 2. Mutation of K783, Y784, and E785 to alanine within this stonin 2 β strand results in failure of the mutant stonin protein to associate with synaptotagmin, to accumulate at synapses, and to facilitate synaptotagmin internalization. Synaptotagmin-binding–defective UNC-41B is unable to rescue paralysis in C. elegans stonin mutant animals, suggesting that the mechanism of stonin-mediated SV cargo recognition is conserved from worms to mammals

Resonant X-ray emission spectroscopy reveals d–d ligand-field states involved in the self-assembly of a square-planar platinum complex

Resonant X-ray Emission Spectroscopy (RXES) is used to characterize the ligand field states of the prototypic self-assembled square-planar complex, [Pt(tpy)Cl]Cl (tpy=2,2′:6′,2′′-terpyridine), and determine the effect of weak metal-metal and π-π interactions on their energy. © 2012 the Owner Societies