scholarly journals Inter-Specific Variation in the Potential for Upland Rush Management Advocated by Agri-Environment Schemes to Increase Breeding Wader Densities

2021 ◽  
Vol 9 ◽  
Author(s):  
Leah A. Kelly ◽  
David J. T. Douglas ◽  
Mike P. Shurmer ◽  
Karl L. Evans
Keyword(s):  
Statistical Power ◽  
Breeding Habitat ◽  
Individual Species ◽  
Soil Conditions ◽  
Parameter Estimates ◽  
Short Term ◽  
Treatment Parameter ◽  
Vanellus Vanellus ◽  
Specific Variation ◽  
Common Snipe

Encroachment of rush Juncus spp. in the United Kingdom uplands poses a threat to declining wader populations due to taller, denser swards that can limit foraging and breeding habitat quality for some species. Rush management via cutting, implemented through agri-environment schemes (AESs), could thus increase wader abundance, but there is insufficient assessment and understanding of how rush management influences upland waders. Across two upland regions of England [South West Peak (SWP) and Geltsdale nature reserve, Cumbria], we surveyed waders over four visits in fields where rush was managed according to AES prescriptions (treatment; n = 21) and fields without rush management that were otherwise ecologically similar (control; n = 22) to assess how the densities of breeding wader pairs respond to rush management in the short-term. We find evidence for regional variation in the response of waders to rush management, with densities of Common Snipe Gallinago gallinago significantly higher in treatment than control fields in the SWP, but not Geltsdale. There were no statistically significant responses to treatment on densities of Eurasian Curlew Numenius arquata or Northern Lapwing Vanellus vanellus. The 95% confidence intervals for the treatment parameter estimates suggest that this may be due to limited statistical power in the case of Lapwing. For Curlew, however, any potential increases in densities are negligible. There was no evidence that variation in rush cover, which ranged from 10 to 70%, influenced densities of any of our three focal species. Our results suggest that rush management through AES prescriptions delivered in isolation of other interventions may not lead to general increases in breeding wader densities in the short-term, but benefits may arise in some situations due to regional and inter-specific variation in effectiveness. Rush management supported with interventions that improve soil conditions and thus food availability, or reduce predation pressure, may enable AES rush management to generate benefits. Additional research is required to maximise the potential benefits of rush management for each species through the development of prescriptions that tailor to individual species’ optimum sward structure.

Missing Data - Better "Not to Have Them", but What If You Do? (Part 1)

Marketing ZFP ◽  
2019 ◽  
Vol 41 (4) ◽  
pp. 21-32
Author(s):  
Dirk Temme ◽  
Sarah Jensen
Keyword(s):  
Missing Data ◽  
Statistical Power ◽  
Missing Values ◽  
Graphical Representation ◽  
Marketing Research ◽  
Likelihood Estimation ◽  
Parameter Estimates ◽  
Full Information Maximum Likelihood ◽  
Definition Of ◽  
Traditional Approaches

Missing values are ubiquitous in empirical marketing research. If missing data are not dealt with properly, this can lead to a loss of statistical power and distorted parameter estimates. While traditional approaches for handling missing data (e.g., listwise deletion) are still widely used, researchers can nowadays choose among various advanced techniques such as multiple imputation analysis or full-information maximum likelihood estimation. Due to the available software, using these modern missing data methods does not pose a major obstacle. Still, their application requires a sound understanding of the prerequisites and limitations of these methods as well as a deeper understanding of the processes that have led to missing values in an empirical study. This article is Part 1 and first introduces Rubin’s classical definition of missing data mechanisms and an alternative, variable-based taxonomy, which provides a graphical representation. Secondly, a selection of visualization tools available in different R packages for the description and exploration of missing data structures is presented.

scholarly journals Development of the reproduction number from coronavirus SARS-CoV-2 case data in Germany and implications for political measures

BMC Medicine ◽  
2021 ◽  
Vol 19 (1) ◽  
Author(s):  
Sahamoddin Khailaie ◽  
Tanmay Mitra ◽  
Arnab Bandyopadhyay ◽  
Marta Schips ◽  
Pietro Mascheroni ◽  
...  
Keyword(s):  
Structural Changes ◽  
Reproduction Number ◽  
National Level ◽  
Transmission Dynamics ◽  
Federal State ◽  
Parameter Estimates ◽  
Time Varying ◽  
Short Term ◽  
Robert Koch Institute ◽  
Federal States

Abstract Background SARS-CoV-2 has induced a worldwide pandemic and subsequent non-pharmaceutical interventions (NPIs) to control the spread of the virus. As in many countries, the SARS-CoV-2 pandemic in Germany has led to a consecutive roll-out of different NPIs. As these NPIs have (largely unknown) adverse effects, targeting them precisely and monitoring their effectiveness are essential. We developed a compartmental infection dynamics model with specific features of SARS-CoV-2 that allows daily estimation of a time-varying reproduction number and published this information openly since the beginning of April 2020. Here, we present the transmission dynamics in Germany over time to understand the effect of NPIs and allow adaptive forecasts of the epidemic progression. Methods We used a data-driven estimation of the evolution of the reproduction number for viral spreading in Germany as well as in all its federal states using our model. Using parameter estimates from literature and, alternatively, with parameters derived from a fit to the initial phase of COVID-19 spread in different regions of Italy, the model was optimized to fit data from the Robert Koch Institute. Results The time-varying reproduction number (Rt) in Germany decreased to <1 in early April 2020, 2–3 weeks after the implementation of NPIs. Partial release of NPIs both nationally and on federal state level correlated with moderate increases in Rt until August 2020. Implications of state-specific Rt on other states and on national level are characterized. Retrospective evaluation of the model shows excellent agreement with the data and usage of inpatient facilities well within the healthcare limit. While short-term predictions may work for a few weeks, long-term projections are complicated by unpredictable structural changes. Conclusions The estimated fraction of immunized population by August 2020 warns of a renewed outbreak upon release of measures. A low detection rate prolongs the delay reaching a low case incidence number upon release, showing the importance of an effective testing-quarantine strategy. We show that real-time monitoring of transmission dynamics is important to evaluate the extent of the outbreak, short-term projections for the burden on the healthcare system, and their response to policy changes.

Efficacy and Rate of Release of EPTC and Butylate from Starch Encapsulated Formulations Under Greenhouse Conditions

Weed Science ◽  
1978 ◽  
Vol 26 (6) ◽  
pp. 679-686 ◽  
Author(s):  
M. M. Schreiber ◽  
B. S. Shasha ◽  
M. A. Ross ◽  
P. L. Orwick ◽  
D. W. Edgecomb
Keyword(s):  
Controlled Release ◽  
Slow Release ◽  
Residual Activity ◽  
Biological Evaluation ◽  
Soil Conditions ◽  
Short Term ◽  
Rapid Release ◽  
Initial Release ◽  
Wet Chemical ◽  
Selection Of

Four starch-encapsulated formulations of EPTC(S-ethyl dipropylthiocarbamate) and of butylate(S-ethyl diisobutylthiocarbamate) were prepared and evaluated by comparison with their respective emulsifiable concentrate formulations for their slow-release capabilities and efficacies. Chemical and biological evaluation indicated that difference in controlled-release could be achieved by the selection of the starch xanthate and oxidant used in the formualtion process. EPTC and butylate released slower when formulated as starch-encapsulated granules than when formulated as emulsifiable concentrates under soil conditions that favored rapid release. The initial release was adequate for weed control and slow enough for desired residual activity. Repeated seeding and harvesting the treated soils and bioassays of treated soils generally produced release rate anticipated from short term dry and wet chemical tests.

scholarly journals Tracing Long- and Short-term Migrants for Participation in Demographic and Epidemiological Studies: Evidence from Senegal

Field Methods ◽  
2019 ◽  
Vol 32 (1) ◽  
pp. 38-57
Author(s):  
Mufaro Kanyangarara ◽  
Laetitia Douillot ◽  
Gilles Pison ◽  
Cheikh Tidiane Ndiaye ◽  
Valerie Delaunay ◽  
...  
Keyword(s):  
Rural Areas ◽  
Statistical Power ◽  
Epidemiological Studies ◽  
Adult Mortality ◽  
Short Term ◽  
Middle Income ◽  
Middle Income Countries ◽  
Contact Information

Migration of participants in demographic and epidemiological studies results in missing data. One approach to reduce resulting losses in statistical power and potential biases is to follow up migrants at their new residence. We describe the follow-up of migrants who were eligible for participation in a trial of a new questionnaire to measure adult mortality in Niakhar, Senegal. We conducted a short inquiry in the migrant’s last known household to obtain contact information and then attempted to contact and interview 661 migrants who resided in Dakar, Mbour, and rural areas close to Niakhar. About two-thirds of migrants were successfully enrolled in the study. Having a contact phone number and knowing the name of the head of compound at destination increased the likelihood of successful enrollment. Following up migrants in demographic studies is feasible in low- and middle-income countries, including long-term migrants who have not been contacted for extended periods of time.

scholarly journals Bayesian mixture structural equation modelling in multiple-trait QTL mapping

2010 ◽  
Vol 92 (3) ◽  
pp. 239-250 ◽  
Author(s):  
XIAOJUAN MI ◽  
KENT ESKRIDGE ◽  
DONG WANG ◽  
P. STEPHEN BAENZIGER ◽  
B. TODD CAMPBELL ◽  
...  
Keyword(s):  
Qtl Mapping ◽  
Structural Equation ◽  
Statistical Power ◽  
Bayes Factor ◽  
Causal Structure ◽  
Mapping Method ◽  
Parameter Estimates ◽  
Detection Accuracy ◽  
Multiple Traits ◽  
Multiple Trait

SummaryQuantitative trait loci (QTLs) mapping often results in data on a number of traits that have well-established causal relationships. Many multi-trait QTL mapping methods that account for correlation among the multiple traits have been developed to improve the statistical power and the precision of QTL parameter estimation. However, none of these methods are capable of incorporating the causal structure among the traits. Consequently, genetic functions of the QTL may not be fully understood. In this paper, we developed a Bayesian multiple QTL mapping method for causally related traits using a mixture structural equation model (SEM), which allows researchers to decompose QTL effects into direct, indirect and total effects. Parameters are estimated based on their marginal posterior distribution. The posterior distributions of parameters are estimated using Markov Chain Monte Carlo methods such as the Gibbs sampler and the Metropolis–Hasting algorithm. The number of QTLs affecting traits is determined by the Bayes factor. The performance of the proposed method is evaluated by simulation study and applied to data from a wheat experiment. Compared with single trait Bayesian analysis, our proposed method not only improved the statistical power of QTL detection, accuracy and precision of parameter estimates but also provided important insight into how genes regulate traits directly and indirectly by fitting a more biologically sensible model.

Short-Term Oil Price Forecasting Based on State Space Model

2011 ◽  
Vol 403-408 ◽  
pp. 2530-2534
Author(s):  
Wei Qi Li ◽  
Lin Wei Ma ◽  
Ya Ping Dai ◽  
Dong Hai Li
Keyword(s):  
State Space ◽  
Likelihood Function ◽  
State Space Model ◽  
The State ◽  
Oil Price ◽  
Filter Method ◽  
Parameter Estimates ◽  
Price Forecasting ◽  
Short Term ◽  
Space Model

In competitive petroleum markets, oil price forecasting has always been an important strategic tool for oil producers and consumers to predict market behavior. In this study, we researched the monthly crude oil price in the period between 1988 and 2009. Firstly, we present a state space model to represent oil price system. Secondly, we determine the parameter estimates of the state space model for oil price through a faster algorithm to compute the likelihood function. Lastly, we use the Kalman filter method to estimate the next three months’ oil price and compare it with the econometric structure model as a benchmark. Empirical results indicate that the state space model performs well in terms of some standard statistics indices, and it may be a promising method for short-term oil price forecasting.

scholarly journals Inverse modeling of hydrologic parameters using surface flux and runoff observations in the Community Land Model

2013 ◽  
Vol 17 (12) ◽  
pp. 4995-5011 ◽  
Author(s):  
Y. Sun ◽  
Z. Hou ◽  
M. Huang ◽  
F. Tian ◽  
L. Ruby Leung
Keyword(s):  
Inverse Modeling ◽  
Bayesian Model Averaging ◽  
Surface Flux ◽  
Sensitivity Analyses ◽  
Soil Conditions ◽  
Bayesian Inversion ◽  
Parameter Estimates ◽  
Model Parameters ◽  
Posterior Distributions ◽  
Community Land Model

Abstract. This study demonstrates the possibility of inverting hydrologic parameters using surface flux and runoff observations in version 4 of the Community Land Model (CLM4). Previous studies showed that surface flux and runoff calculations are sensitive to major hydrologic parameters in CLM4 over different watersheds, and illustrated the necessity and possibility of parameter calibration. Both deterministic least-square fitting and stochastic Markov-chain Monte Carlo (MCMC)-Bayesian inversion approaches are evaluated by applying them to CLM4 at selected sites with different climate and soil conditions. The unknowns to be estimated include surface and subsurface runoff generation parameters and vadose zone soil water parameters. We find that using model parameters calibrated by the sampling-based stochastic inversion approaches provides significant improvements in the model simulations compared to using default CLM4 parameter values, and that as more information comes in, the predictive intervals (ranges of posterior distributions) of the calibrated parameters become narrower. In general, parameters that are identified to be significant through sensitivity analyses and statistical tests are better calibrated than those with weak or nonlinear impacts on flux or runoff observations. Temporal resolution of observations has larger impacts on the results of inverse modeling using heat flux data than runoff data. Soil and vegetation cover have important impacts on parameter sensitivities, leading to different patterns of posterior distributions of parameters at different sites. Overall, the MCMC-Bayesian inversion approach effectively and reliably improves the simulation of CLM under different climates and environmental conditions. Bayesian model averaging of the posterior estimates with different reference acceptance probabilities can smooth the posterior distribution and provide more reliable parameter estimates, but at the expense of wider uncertainty bounds.

scholarly journals On the temporally flexible structure of plant-pollinator interaction networks

2020 ◽  
Author(s):  
Paul J. CaraDonna ◽  
Nickolas M. Waser
Keyword(s):  
Temporal Variation ◽  
Network Structure ◽  
Species Interactions ◽  
Interspecific Interactions ◽  
Activity Period ◽  
Individual Species ◽  
Ecological Communities ◽  
Short Term ◽  
Temporal Flexibility ◽  
Plant Pollinator

AbstractEcological communities consist of species that are joined in complex networks of interspecific interaction. The interactions that networks depict often form and dissolve rapidly, but this temporal variation is not well integrated into our understanding of the causes and consequences of network structure. If interspecific interactions exhibit temporal flexibility across time periods over which organisms co-occur, then the emergent structure of the corresponding network may also be temporally flexible, something that a temporally-static perspective would miss. Here, we use an empirical system to examine short-term flexibility in network structure (connectance, nestedness, and specialization), and in individual species interactions that contribute to that structure. We investigated weekly plant-pollinator networks in a subalpine ecosystem across three summer growing seasons. To link the interactions of individual species to properties of their networks, we examined weekly temporal variation in species’ contributions to network structure. As a test of the potential robustness of networks to perturbation, we also simulated the random loss of species from weekly networks. We then compared the properties of weekly networks to the properties of cumulative networks that aggregate field observations over each full season. A week-to-week view reveals considerable flexibility in the interactions of individual species and their contributions to network structure. For example, species that would be considered relatively generalized across their entire activity period may be much more specialized at certain times, and at no point as generalized as the cumulative network may suggest. Furthermore, a week-to-week view reveals corresponding temporal flexibility in network structure and potential robustness throughout each summer growing season. We conclude that short-term flexibility in species interactions leads to short-term variation in network properties, and that a season-long, cumulative perspective may miss important aspects of the way in which species interact, with implications for understanding their ecology, evolution, and conservation.

scholarly journals Species diversity of segetal communities in tuber crops and in winter and spring cereals

2013 ◽  
Vol 66 (3) ◽  
pp. 95-102
Author(s):  
Zofia Rzymowska ◽  
Maria Ługowska ◽  
Janina Skrzyczyńska
Keyword(s):  
Species Diversity ◽  
Species Abundance ◽  
Wiener Index ◽  
Species Number ◽  
Individual Species ◽  
Soil Conditions ◽  
Weed Communities ◽  
Spring Cereals ◽  
Dominance Indices ◽  
Tuber Crops

The work presents the results of studies on the diversity of weed communities in tuber crops as well as in winter and spring cereals under similar climatic and soil conditions. We examined overall species abundance in the groups analysed, the average species number per relevé, as well as weed cover of the study area. Additionally, species composition, number of individual species and their biomass were determined. Dominant species in each crop group were distinguished. Species diversity was determined based on the following ecological indices: the Shannon-Wiener index of biodiversity <em>H’</em> and Simpson’s index of dominance <em>C</em>. The indices were computed on the biomass and number-of-species basis. The objective of the work was to compare the structure and diversity of weed communities in the crops studied. The communities analysed differed in all the characteristics examined. Differences were found between biodiversity and dominance indices calculated for individual crop groups, but their significance depended on the method applied to calculate the indices.

scholarly journals Influence of short-term transfers on nitrogen fluxes, budgets and indirect N<sub>2</sub>O emissions in rural landscapes

2011 ◽  
Vol 8 (4) ◽  
pp. 7593-7622 ◽  
Author(s):  
S. Duretz ◽  
J.-L. Drouet ◽  
P. Durand ◽  
P. Cellier
Keyword(s):  
Landscape Scale ◽  
Soil Conditions ◽  
N2o Emissions ◽  
Spatial Interactions ◽  
Short Term ◽  
Rural Landscapes ◽  
Environmental Threats ◽  
Spatially Distributed ◽  
Simulation Results ◽  
Oligotrophic Ecosystems

Abstract. Spatial interactions at short-term may lead to large inputs of reactive nitrogen (Nr) to oligotrophic ecosystems and induce environmental threats such as additional N2O emissions and global warming. The paper presents a new methodology to estimate Nr fluxes, especially additional N2O emissions, at the landscape scale by taking into account spatial interactions between landscape elements. We used the NitroScape model which integrates processes of Nr transformation and short-term transfer in a dynamic and spatially distributed way to simulate Nr fluxes and budgets at the landscape scale. Four configurations of NitroScape were implemented by taking into account or not the atmospheric, hydrological or both pathways of Nr transfer. We simulated Nr fluxes, especially direct and indirect N2O emissions, within a test landscape including pig farms, croplands and unmanaged ecosystems. Simulation results showed the ability of NitroScape to simulate patterns of Nr losses and recapture for each landscape element and the whole landscape. They made it possible to quantify the contribution of both atmospheric and hydrological transfers in Nr fluxes and budgets. Indirect N2O emissions were estimated at almost 25 % of the total N2O emissions. They varied within the landscape according to land use, meteorological and soil conditions as well as topography. This first attempt has proved that the NitroScape model is a useful tool to estimate the effect of spatial interactions on Nr fluxes and budgets as well as indirect N2O emissions within landscapes. Our approach needs to be further tested by applying NitroScape to several spatial distributions of ecosystems within the landscape and to real and larger landscapes.

Sign in / Sign up

Export Citation Format

Share Document