Extensibility Based Multiagent Planner with Plan Diversity Metrics

Plant biodiversity is an important feature of grassland ecosystems, as it is related to the provision of many ecosystem services crucial for the human economy and well-being. Given the importance of grasslands, research has been carried out in recent years on the potential to monitor them with novel remote sensing techniques. In this study, the optical diversity (also called spectral diversity) approach was adopted to check the potential of using high-resolution hyperspectral images to estimate α-diversity in grassland ecosystems. In 2018 and 2019, grassland species composition was surveyed and canopy hyperspectral data were acquired at two grassland sites: Monte Bondone (IT-MBo; species-rich semi-natural grasslands) and an experimental farm of the University of Padova, Legnaro, Padua, Italy (IT-PD; artificially established grassland plots with a species-poor mixture). The relationship between biodiversity (species richness, Shannon’s, species evenness, and Simpson’s indices) and optical diversity metrics (coefficient of variation-CV and standard deviation-SD) was not consistent across the investigated grassland plant communities. Species richness could be estimated by optical diversity metrics with an R = 0.87 at the IT-PD species-poor site. In the more complex and species-rich grasslands at IT-MBo, the estimation of biodiversity indices was more difficult and the optical diversity metrics failed to estimate biodiversity as accurately as in IT-PD probably due to the higher number of species and the strong canopy spatial heterogeneity. Therefore, the results of the study confirmed the ability of spectral proxies to detect grassland α-diversity in man-made grassland ecosystems but highlighted the limitations of the spectral diversity approach to estimate biodiversity when natural grasslands are observed. Nevertheless, at IT-MBo, the optical diversity metric SD calculated from post-processed hyperspectral images and transformed spectra showed, in the red part of the spectrum, a significant correlation (up to R = 0.56, p = 0.004) with biodiversity indices. Spatial resampling highlighted that for the IT-PD sward the optimal optical pixel size was 1 cm, while for the IT-MBo natural grassland it was 1 mm. The random pixel extraction did not improve the performance of the optical diversity metrics at both study sites. Further research is needed to fully understand the links between α-diversity and spectral and biochemical heterogeneity in complex heterogeneous ecosystems, and to assess whether the optical diversity approach can be adopted at the spatial scale to detect β-diversity. Such insights will provide more robust information on the mechanisms linking grassland diversity and optical heterogeneity.

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A meta-analysis of the effect of organic and mineral fertilizers on soil microbial diversity

10.1101/2020.10.04.325373 ◽

2020 ◽

Author(s):

Daniel P. Bebber ◽

Victoria R. Richards

Keyword(s):

Microbial Biomass ◽

Microbial Diversity ◽

Meta Analysis ◽

Taxonomic Diversity ◽

Mineral Fertilizers ◽

Soil Microbial Diversity ◽

Soil Microbial ◽

Meta Analyses ◽

Fertilizer Regimes ◽

Diversity Metrics

ABSTRACTThe Green Revolution of agriculture was in part driven by application of synthetic mineral fertilizers, largely supplanting organic manure as a source of the major nutrients nitrogen, phosphorous and potassium (NPK). Though enhancing crop production and global food security, fertilizers have contributed to soil acidification, eutrophication of water bodies, and greenhouse gas emissions. Organic agriculture, employing manures or composts, has been proposed as a way of mitigating these undesirable effects. Of particular interest is the effect of fertilizer regime on soil microbes, which are key to nutrient cycling, plant health and soil structure. Meta-analyses of experimental studies indicate that mineral fertilizer increases soil microbial biomass over unfertilized controls, and that organic fertilizers increase microbial biomass and activity over mineral fertilizers. However, the effect of fertilizers on soil microbial diversity remains poorly understood. Since biological diversity is an important determinant of ecosystem function and a fundamental metric in community ecology, the effects of fertilizer regimes on soil microbial diversity are of theoretical and applied interest. Here, we conduct a meta-analysis of 31 studies reporting microbial diversity metrics in mineral fertilized (NPK), organically fertilized (ORG) and unfertilized control (CON) soils. Of these studies, 26 reported taxonomic diversity derived from sequencing, gradient gel electrophoresis, RFLP, or dilution plate assay. Functional diversity, derived from Biolog Ecoplate™ measures of carbon substrate metabolism, was reported in 8 studies, with 3 studies reporting both diversity metrics. We found that functional diversity was on average 2.6 % greater in NPK compared with CON, 6.8 % greater in ORG vs CON and 3.6 % greater in ORG vs NPK. Prokaryote taxonomic diversity was not significantly different between NPK and CON, 4.2 % greater in ORG vs CON and 4.6 % greater in ORG vs. NPK. Fungal taxonomic diversity was not significantly different between NPK or ORG vs CON, but 5.4 % lower between ORG and NPK. There was very high residual heterogeneity in all meta-analyses of soil diversity, suggesting that a large amount of further research with detailed analysis of soil properties is required to fully understand the influence of fertilizer regimes on microbial diversity and ecosystem function.

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Reshaping Diverse Planning

Proceedings of the AAAI Conference on Artificial Intelligence ◽

10.1609/aaai.v34i06.6543 ◽

2020 ◽

Vol 34 (06) ◽

pp. 9892-9899

Author(s):

Michael Katz ◽

Shirin Sohrabi

Keyword(s):

Recent Work ◽

Plan Quality ◽

Post Processing ◽

Predominant Role ◽

Solution Quality ◽

Optimization Criteria ◽

Novel Approach ◽

Key Factor ◽

Planning Task ◽

Diversity Metrics

The need for multiple plans has been established by various planning applications. In some, solution quality has the predominant role, while in others diversity is the key factor. Most recent work takes both plan quality and solution diversity into account under the generic umbrella of diverse planning. There is no common agreement, however, on a collection of computational problems that fall under that generic umbrella. This in particular might lead to a comparison between planners that have different solution guarantees or optimization criteria in mind. In this work we revisit diverse planning literature in search of such a collection of computational problems, classifying the existing planners to these problems. We formally define a taxonomy of computational problems with respect to both plan quality and solution diversity, extending the existing work. We propose a novel approach to diverse planning, exploiting existing classical planners via planning task reformulation and choosing a subset of plans of required size in post-processing. Based on that, we present planners for two computational problems, that most existing planners solve. Our experiments show that the proposed approach significantly improves over the best performing existing planners in terms of coverage, the overall solution quality, and the overall diversity according to various diversity metrics.

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Comparison of Oral Microbiota Collected Using Multiple Methods and Recommendations for New Epidemiologic Studies

mSystems ◽

10.1128/msystems.00156-20 ◽

2020 ◽

Vol 5 (4) ◽

Cited By ~ 2

Author(s):

Yukiko Yano ◽

Xing Hua ◽

Yunhu Wan ◽

Shalabh Suman ◽

Bin Zhu ◽

...

Keyword(s):

Beta Diversity ◽

Epidemiologic Studies ◽

Oral Microbiome ◽

Rrna Gene ◽

Oral Microbiota ◽

Collection Method ◽

Two Samples ◽

Relative Abundances ◽

Collection Methods ◽

Diversity Metrics

ABSTRACT Epidemiologic studies use various biosample collection methods to study associations between human oral microbiota and health outcomes. However, the agreement between the different methods is unclear. We compared a commercially available OMNIgene ORAL kit to three alternative collection methods: Saccomanno’s fixative, Scope mouthwash, and nonethanol mouthwash. Oral samples were collected from 40 individuals over 4 visits. Two samples were collected from each subject per visit: one with OMNIgene and one with an alternative method. DNA was extracted using the DSP DNA Virus Pathogen kit, and the V4 region of the 16S rRNA gene was PCR amplified and sequenced using MiSeq. Oral collection methods were compared based on alpha and beta diversity metrics and phylum- and genus-level relative abundances. All alpha diversity metrics were significantly lower for Saccomanno’s fixative than for OMNIgene (P < 0.001), whereas the two mouthwashes were more similar to OMNIgene. Principal-coordinate analysis (PCoA) using the Bray-Curtis and weighted UniFrac beta diversity matrices showed large differences in the microbial compositions of samples collected with Saccomanno’s compared to those with OMNIgene and the mouthwashes. Clustering by collection method was not observed in unweighted UniFrac PCoA plots, suggesting differences in relative abundances but not specific taxa detected by the collection methods. Relative abundances of most taxa were significantly different between OMNIgene and the other methods at each taxonomic level, with Saccomanno’s showing the least agreement with OMNIgene. There were clear differences in oral microbial communities between the four oral collection methods, particularly for Saccomanno’s fixative. IMPORTANCE We compared four different oral collection methods for studying the human oral microbiome: an OMNIgene ORAL kit, Scope mouthwash, nonethanol mouthwash, and Saccomanno’s fixative. Our study shows that the type of the collection method can have a large impact on the results of an oral microbiome analysis. We recommend that one consistent oral collection method should be used for all oral microbiome comparisons. While Scope and nonethanol mouthwashes are less expensive and provide results similar to those with OMNIgene, Saccomanno’s fixative may be unfavorable due to the microbial differences detected in this study. Our results will help guide the design of future oral microbiome studies.

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Diversity metrics for direct-coded variable-length chromosome shortest path problem evolutionary algorithms

Computing ◽

10.1007/s00607-020-00851-4 ◽

2020 ◽

Author(s):

Aiman Ghannami ◽

Jing Li ◽

Ammar Hawbani ◽

Naji Alhusaini

Keyword(s):

Evolutionary Algorithms ◽

Shortest Path ◽

Shortest Path Problem ◽

Variable Length ◽

Diversity Metrics

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Design of a multi-purpose fragment screening library using molecular complexity and orthogonal diversity metrics

Journal of Computer-Aided Molecular Design ◽

10.1007/s10822-011-9434-0 ◽

2011 ◽

Vol 25 (7) ◽

pp. 621-636 ◽

Cited By ~ 47

Author(s):

Wan F. Lau ◽

Jane M. Withka ◽

David Hepworth ◽

Thomas V. Magee ◽

Yuhua J. Du ◽

...

Keyword(s):

Fragment Screening ◽

Molecular Complexity ◽

Screening Library ◽

Diversity Metrics

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The Economization of Diversity

Sociology of Race and Ethnicity ◽

10.1177/2332649218793981 ◽

2018 ◽

Vol 5 (4) ◽

pp. 471-485

Author(s):

James M. Thomas

Keyword(s):

Human Capital ◽

Racial Inequality ◽

Racial Ideology ◽

Economic Values ◽

Affective Labor ◽

Flagship University ◽

Diversity Discourse ◽

The U.S ◽

Diversity Metrics

Through a case study of an ongoing diversity initiative at Diversity University (DU), a public, flagship university in the U.S. South, the author’s research advances understanding of the discursive relationship between neoliberalism and contemporary racial ideology. As part of a larger ethnographic project, the author draws on more than ten years worth of diversity discourse at DU to illuminate diversity’s economization: the process whereby specific formations of economic values, practices, and metrics are extended toward diversity as justification for DU’s efforts. The analysis responds to three questions: (1) How is diversity economized by the organization? (2) How is this economization articulated through organizational discourse on diversity? and (3) How does the economization of diversity potentially reconfigure race and racial subjectivities? The findings reveal three interrelated processes that facilitate diversity’s economization: diversity as investment, diversity metrics, and diversity as affective labor. Together these processes congeal and convert multicultural principles and practices into economic ones. Consequently, diversity’s economization recasts nonwhite racial subjectivity as human capital for DU and its white publics, minimizing and entrenching existing racial inequality in the process.

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