A Bayesian hierarchical approach to improve model parameter estimates and predictions of silage maize phenology in Germany

2021 ◽  
Author(s):  
Michelle Viswanathan ◽  
Tobias KD Weber ◽  
Andreas Scheidegger ◽  
Thilo Streck
Keyword(s):  
Environmental Conditions ◽  
Plant Phenology ◽  
Parameter Estimates ◽  
Crop Species ◽  
Bayesian Hierarchical ◽  
Crop Models ◽  
Hierarchical Framework ◽  
Silage Maize ◽  
Parameterized Model ◽  
Species Specific

<p>Crop models are used to evaluate the impact of climate change on food security by simulating plant phenology, yield, biomass and leaf area index. Plant phenology defines the timing of crucial growth stages and physiological processes that influence organ appearance and assimilate partitioning. It is governed by environmental factors such as solar radiation, temperature and water availability. Plant phenology is not only specific for the crop species, but also depends on the cultivar. Additionally, growth of a cultivar could vary depending on the environment. Common crop models cannot fully capture the influence of the environment on phenology, resulting in cultivar-specific parameters that are environment-dependent. These parameter estimates may be unreliable in case of limited data. Moreover, crucial species-specific information is ignored. On the other hand, in large regional-scale models covering multiple cultivars and environments, information about the cultivars grown is generally not available. In this case, a shared set of parameters for the crop species would suppress within-species differences leading to unreliable predictions.</p><p>A Bayesian hierarchical framework enables us to alleviate these problems by honouring the multi-level data structure. Additionally, we can reflect the uncertainty from different sources, for example, model inputs and measurements. In this study we implement a Bayesian hierarchical framework to estimate parameters of the Soil-Plant-Atmosphere System Simulation (SPASS) model for simulating phenological development of different cultivars of silage maize grown over all the contrasting climatological regions of Germany.</p><p>We used data from the German weather service on the phenological development stages of silage maize grown across Germany between 2009 and 2019. During this period, silage maize was grown in over 3000 unique location-year combinations. Maize crops were differentiated into early, mid-early, mid-late and late ripening groups and were further classified into cultivars within each ripening group. Within the hierarchical framework, we estimate maize species-specific parameters as well as parameters per ripening group and cultivar, through Bayesian model calibration. We analyse the influence of environmental conditions on parameter estimates, to further develop the hierarchical structure. We perform cross-validation to assess the prediction quality of the parameterized model.</p><p>With this approach, we show that robust parameter estimates account for differences between cultivars, ripening groups as well as different environmental conditions. The parameterized model can be used for large-scale phenology predictions of silage maize grown across Germany. These parameter estimates may perform better than independent species- or cultivar-specific estimates, in predicting phenology of future cultivars where specific cultivar characteristics are not known.</p>

scholarly journals Environmental and taxonomic controls of carbon and oxygen stable isotope composition in <i>Sphagnum</i> across broad climatic and geographic ranges

2018 ◽  
Vol 15 (16) ◽  
pp. 5189-5202 ◽  
Author(s):  
Gustaf Granath ◽  
Håkan Rydin ◽  
Jennifer L. Baltzer ◽  
Fia Bengtsson ◽  
Nicholas Boncek ◽  
...  
Keyword(s):  
Environmental Conditions ◽  
Large Scale ◽  
Net Primary Productivity ◽  
Isotope Composition ◽  
Explanatory Power ◽  
Isotopic Signature ◽  
Co2 Uptake ◽  
Δ13c Values ◽  
Site Variation ◽  
Species Specific

Abstract. Rain-fed peatlands are dominated by peat mosses (Sphagnum sp.), which for their growth depend on nutrients, water and CO2 uptake from the atmosphere. As the isotopic composition of carbon (12,13C) and oxygen (16,18O) of these Sphagnum mosses are affected by environmental conditions, Sphagnum tissue accumulated in peat constitutes a potential long-term archive that can be used for climate reconstruction. However, there is inadequate understanding of how isotope values are influenced by environmental conditions, which restricts their current use as environmental and palaeoenvironmental indicators. Here we tested (i) to what extent C and O isotopic variation in living tissue of Sphagnum is species-specific and associated with local hydrological gradients, climatic gradients (evapotranspiration, temperature, precipitation) and elevation; (ii) whether the C isotopic signature can be a proxy for net primary productivity (NPP) of Sphagnum; and (iii) to what extent Sphagnum tissue δ18O tracks the δ18O isotope signature of precipitation. In total, we analysed 337 samples from 93 sites across North America and Eurasia using two important peat-forming Sphagnum species (S. magellanicum, S. fuscum) common to the Holarctic realm. There were differences in δ13C values between species. For S. magellanicum δ13C decreased with increasing height above the water table (HWT, R2=17 %) and was positively correlated to productivity (R2=7 %). Together these two variables explained 46 % of the between-site variation in δ13C values. For S. fuscum, productivity was the only significant predictor of δ13C but had low explanatory power (total R2=6 %). For δ18O values, approximately 90 % of the variation was found between sites. Globally modelled annual δ18O values in precipitation explained 69 % of the between-site variation in tissue δ18O. S. magellanicum showed lower δ18O enrichment than S. fuscum (−0.83 ‰ lower). Elevation and climatic variables were weak predictors of tissue δ18O values after controlling for δ18O values of the precipitation. To summarize, our study provides evidence for (a) good predictability of tissue δ18O values from modelled annual δ18O values in precipitation, and (b) the possibility of relating tissue δ13C values to HWT and NPP, but this appears to be species-dependent. These results suggest that isotope composition can be used on a large scale for climatic reconstructions but that such models should be species-specific.

scholarly journals Spatiotemporal mapping and detection of mortality cluster due to cardiovascular disease with Bayesian hierarchical framework using integrated nested Laplace approximation: A discussion of suitable statistic applications in Kersa, Oromia, Ethiopia

2018 ◽  
Vol 13 (2) ◽  
Author(s):  
Melkamu Dedefo ◽  
Henry Mwambi ◽  
Sileshi Fanta ◽  
Nega Assefa
Keyword(s):  
Cause Of Death ◽  
Linear Models ◽  
Temporal Distribution ◽  
Mortality Data ◽  
Contributing Factors ◽  
Bayesian Hierarchical ◽  
Hierarchical Framework ◽  
Temporal Models ◽  
Spatio Temporal ◽  
Non Parametric

Cardiovascular diseases (CVDs) are the leading cause of death globally and the number one cause of death globally. Over 75% of CVD deaths take place in low- and middle-income countries. Hence, comprehensive information about the spatio-temporal distribution of mortality due to cardio vascular disease is of interest. We fitted different spatio-temporal models within Bayesian hierarchical framework allowing different space-time interaction for mortality mapping with integrated nested Laplace approximations to analyze mortality data extracted from the health and demographic surveillance system in Kersa District in Hararege, Oromia Region, Ethiopia. The result indicates that non-parametric time trends models perform better than linear models. Among proposed models, one with non-parametric trend, type II interaction and second order random walk but without unstructured time effect was found to perform best according to our experience and. simulation study. An application based on real data revealed that, mortality due to CVD increased during the study period, while administrative regions in northern and south-eastern part of the study area showed a significantly elevated risk. The study highlighted distinct spatiotemporal clusters of mortality due to CVD within the study area. The study is a preliminary assessment step in prioritizing areas for further and more comprehensive research raising questions to be addressed by detailed investigation. Underlying contributing factors need to be identified and accurately quantified.

scholarly journals LED light gradient as a screening tool for light quality responses in model plant species

2020 ◽  
Author(s):  
P. Lejeune ◽  
A. Fratamico ◽  
F. Bouché ◽  
S. Huerga Fernández ◽  
P. Tocquin ◽  
...  
Keyword(s):  
Brachypodium Distachyon ◽  
Production Costs ◽  
Fluorescent Light ◽  
Plant Responses ◽  
Light Spectrum ◽  
Crop Species ◽  
Phenotypic Data ◽  
Euphorbia Peplus ◽  
Light Gradient ◽  
Species Specific

AbstractCurrent developments in light-emitting diodes (LEDs) technologies have opened new perspectives for sustainable and highly efficient indoor cultivation. The introduction of LEDs not only allows a reduction in the production costs on a quantitative level, it also offers opportunities to manipulate and optimise qualitative traits. Indeed, while plants respond strongest to red and blue lights for photosynthesis, the whole light spectrum has an effect on plant shape, development, and chemical composition. In order to evaluate LEDs as an alternative to traditional lighting sources, the species-specific plant responses to distinct wavelengths need to be evaluated under controlled conditions. Here, we tested the possibility to use light composition gradients in combination with semi-automated phenotyping to rapidly explore the phenotypic responses of different species to variations in the light spectrum provided by LED sources. Plants of seven different species (Arabidopsis thaliana, Ocimum basilicum, Solanum lycopersicum, Brachypodium distachyon, Oryza sativa, Euphorbia peplus, Setaria viridis) were grown under standard white fluorescent light for 30 days, then transferred to a Red:Blue gradient for another 30 days and finally returned to white light. In all species, differences in terms of dimension, shape, and color were rapidly observed across the gradient and the overall response was widely species-dependent. The experiment yielded large amounts of imaging-based phenotypic data and we suggest simple data analysis methods to aggregate the results and facilitate comparisons between species. Similar experimental setups will help achieve rapid environmental optimization, screen new crop species and genotypes, or develop new gene discovery strategies.

scholarly journals A multi-disciplinary comparison of great ape gut microbiota in a central African forest and European zoo

2020 ◽  
Vol 10 (1) ◽  
Author(s):  
Victor Narat ◽  
Katherine R. Amato ◽  
Noémie Ranger ◽  
Maud Salmona ◽  
Séverine Mercier-Delarue ◽  
...  
Keyword(s):  
Gut Microbiota ◽  
Bacterial Diversity ◽  
Environmental Conditions ◽  
Participant Observation ◽  
Feeding Habits ◽  
Animal Health ◽  
Structured Interviews ◽  
Microbial Composition ◽  
Species Specific ◽  
Free Ranging

Abstract Comparisons of mammalian gut microbiota across different environmental conditions shed light on the diversity and composition of gut bacteriome and suggest consequences for human and animal health. Gut bacteriome comparisons across different environments diverge in their results, showing no generalizable patterns linking habitat and dietary degradation with bacterial diversity. The challenge in drawing general conclusions from such studies lies in the broad terms describing diverse habitats (“wild”, “captive”, “pristine”). We conducted 16S ribosomal RNA gene sequencing to characterize intestinal microbiota of free-ranging sympatric chimpanzees and gorillas in southeastern Cameroon and sympatric chimpanzees and gorillas in a European zoo. We conducted participant-observation and semi-structured interviews among people living near these great apes to understand better their feeding habits and habitats. Unexpectedly, bacterial diversity (ASV, Faith PD and Shannon) was higher among zoo gorillas than among those in the Cameroonian forest, but zoo and Cameroonian chimpanzees showed no difference. Phylogeny was a strong driver of species-specific microbial composition. Surprisingly, zoo gorilla microbiota more closely resembled that of zoo chimpanzees than of Cameroonian gorillas. Zoo living conditions and dietary similarities may explain these results. We encourage multidisciplinary approach integrating environmental sampling and anthropological evaluation to characterize better diverse environmental conditions of such investigations.

Comparison of settlement-era vegetation reconstructions for STEPPS and REVEALS pollen–vegetation models in the northeastern United States

2020 ◽  
Vol 95 ◽  
pp. 23-42 ◽  
Author(s):  
Mathias Trachsel ◽  
Andria Dawson ◽  
Christopher J. Paciorek ◽  
John W. Williams ◽  
Jason S. McLachlan ◽  
...  
Keyword(s):  
United States ◽  
Forest Dynamics ◽  
Pollen Dispersal ◽  
Parameter Estimates ◽  
Vegetation Composition ◽  
Northeastern United States ◽  
Bayesian Hierarchical ◽  
Pollen Productivity ◽  
Vegetation Models ◽  
Anthropogenic Land Use

AbstractReconstructions of prehistoric vegetation composition help establish natural baselines, variability, and trajectories of forest dynamics before and during the emergence of intensive anthropogenic land use. Pollen–vegetation models (PVMs) enable such reconstructions from fossil pollen assemblages using process-based representations of taxon-specific pollen production and dispersal. However, several PVMs and variants now exist, and the sensitivity of vegetation inferences to PVM selection, variant, and calibration domain is poorly understood. Here, we compare the reconstructions, parameter estimates, and structure of a Bayesian hierarchical PVM, STEPPS, both to observations and to REVEALS, a widely used PVM, for the pre–Euro-American settlement-era vegetation in the northeastern United States (NEUS). We also compare NEUS-based STEPPS parameter estimates to those for the upper midwestern United States (UMW). Both PVMs predict the observed macroscale patterns of vegetation composition in the NEUS; however, reconstructions of minor taxa are less accurate and predictions for some taxa differ between PVMs. These differences can be attributed to intermodel differences in structure and parameter estimates. Estimates of pollen productivity from STEPPS broadly agree with estimates produced for use in REVEALS, while comparison between pollen dispersal parameter estimates shows no significant relationship. STEPPS parameter estimates are similar between the UMW and NEUS, suggesting that STEPPS parameter estimates are transferable between floristically similar regions and scales.

scholarly journals Filling in knowledge gaps: Length–weight relations of 46 uncommon sharks and rays (Elasmobranchii) in the Mediterranean Sea

2021 ◽  
Vol 51 (3) ◽  
pp. 249-255
Author(s):  
Athanassios C. Tsikliras ◽  
Donna Dimarchopoulou
Keyword(s):  
Mediterranean Sea ◽  
Eastern Mediterranean ◽  
Global Scale ◽  
Biological Information ◽  
Knowledge Gap ◽  
Museum Collections ◽  
Bayesian Hierarchical ◽  
The Mediterranean ◽  
Species Specific ◽  
Bayesian Hierarchical Method

Large sharks and rays are generally understudied in the Mediterranean Sea, thus leading to a knowledge gap of basic biological characteristics that are important in fisheries management and ecosystem modeling. Out of the 76 sharks and rays inhabiting the Mediterranean Sea, the length–weight relations (LWR) are available for 28 (37%) of them, usually for common small-sized species that are not protected and may be marketed. The aim of the presently reported study was to fill in the knowledge gap through the estimation of LWR of rare and uncommon sharks and rays in the Mediterranean Sea using the information from single records or few individuals. The analysis was based on a Bayesian hierarchical method for estimating length–weight relations in fishes that has been recently proposed for data-deficient species or museum collections and uses the prior knowledge and existing LWR studies to derive species-specific LWR parameters by body form. The use of this method was applied to single records of rare and uncommon species and here we report the LWR of 46 uncommon sharks and ray species, 14 of which are first reported LWR at a global scale and 21 are the first reported LWR for the Mediterranean Sea; the remaining 11 species are first time records for the western or eastern Mediterranean regions. Museum collections and sporadic catch records of rare emblematic species may provide useful biological information with the use of appropriate Bayesian methods.

scholarly journals Stock assessment of the western winter-spring cohort of Ommastrephes bartramii in the Northwest Pacific Ocean using a Bayesian hierarchical DeLury model based on daily natural mortality during 2005-2015

2019 ◽  
Vol 83 (2) ◽  
pp. 155 ◽  
Author(s):  
Qi Ding ◽  
Jie Cao ◽  
Xinjun Chen
Keyword(s):  
Pacific Ocean ◽  
Environmental Conditions ◽  
Northwest Pacific ◽  
Natural Mortality ◽  
Ommastrephes Bartramii ◽  
Northwest Pacific Ocean ◽  
Bayesian Hierarchical ◽  
Stock Size ◽  
Neon Flying Squid ◽  
The Northwest Pacific Ocean

The purpose of this study was to evaluate the effect of the intensive commercial jigging fishery on the western winter-spring cohort of neon flying squid (Ommastrephes bartramii) in the Northwest Pacific Ocean and to estimate the exploitation status of this stock during the period 2005-2015. We applied a Bayesian hierarchical DeLury depletion model to the Chinese jigging fisheries data to estimate the stock abundance and catchability for each year, and sensitivity analysis on daily natural mortality (M) was conducted. The results indicated that M values had great impacts on the overall estimates of stock size. Initial annual population sizes varied from 66 to 662 million individuals with the M value of 0.003-0.01 per day during the study period. O. bartramii suffered from a certain degree of overexploitation in 2008. The proportional escapement values (M=0.003-0.01) were 8.94% to 19.82% in 2008, with an average of 13.74%, which may have led to a low abundance of O. bartramii and annual catch since 2009. As short-lived ecological opportunists, O. bartramii are extremely sensitive to changes in multi-scale environmental conditions, especially when anomalous environmental conditions occur, and significant between-year variations in the initial abundance resulted in O. bartramii suffering from a certain degree of overexploitation in 2010. Although the proportional escapement met the management target of 40% from 2011 to 2015, the stock size and annual catch still fluctuated at relatively low levels. Improved knowledge of the influences of environmental conditions on abundance of the western winter-spring cohort of neon flying squid can contribute to the sustainable management of this stock.

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