scholarly journals Bayesian characterization of uncertainty in species interaction strengths

2015 ◽  
Author(s):  
Christopher Wolf ◽  
Mark Novak ◽  
Alix I. Gitelman
Keyword(s):  
Species Interactions ◽  
Statistical Significance ◽  
Interaction Strength ◽  
Species Interaction ◽  
Superior Performance ◽  
Empirical Estimation ◽  
Statistical Significance Testing ◽  
Estimation Uncertainty ◽  
Point Estimates

Considerable effort has been devoted to the empirical estimation of species interaction strengths. This effort has focused primarily on statistical significance testing and on obtaining point estimates of parameters that contribute to interaction strength magnitude, leaving characterizations of estimation uncertainty and distinctions between the deterministic and stochastic contributions to variation largely unconsidered. Here we consider a means of quantifying interaction strength uncertainty by formulating an observational method for estimating per capita attack rates as a Bayesian statistical model. This formulation permits the explicit incorporation of multiple sources of uncertainty. In doing so we highlight the informative nature of several so-called non-informative prior choices in modeling the sparse data typical of predator feeding surveys and provide evidence for the superior performance of a new neutral prior choice. A case study application shows that while Bayesian point estimates may be made to correspond with those obtained by frequentist approaches, estimation uncertainty as described by the 95% intervals is more biologically realistic using the Bayesian method in that the lower bounds of the Bayesian posterior intervals for the attack rates do not include zero when the occurrence of a given predator-prey interaction is in fact observed. This contrasts with bootstrap confidence intervals that often do contain zero in such cases. The Bayesian approach provides a straightforward, probabilistic characterization of interaction strength uncertainty. In doing so it provides a framework for considering both the deterministic and stochastic drivers of species interactions and their impact on food web dynamics.

scholarly journals Bayesian characterization of uncertainty in species interaction strengths

2015 ◽  
Author(s):  
Christopher Wolf ◽  
Mark Novak ◽  
Alix I. Gitelman
Keyword(s):  
Species Interactions ◽  
Statistical Significance ◽  
Interaction Strength ◽  
Species Interaction ◽  
Superior Performance ◽  
Empirical Estimation ◽  
Statistical Significance Testing ◽  
Estimation Uncertainty ◽  
Point Estimates

Considerable effort has been devoted to the empirical estimation of species interaction strengths. This effort has focused primarily on statistical significance testing and on obtaining point estimates of parameters that contribute to interaction strength magnitude, leaving characterizations of estimation uncertainty and distinctions between the deterministic and stochastic contributions to variation largely unconsidered. Here we consider a means of quantifying interaction strength uncertainty by formulating an observational method for estimating per capita attack rates as a Bayesian statistical model. This formulation permits the explicit incorporation of multiple sources of uncertainty. In doing so we highlight the informative nature of several so-called non-informative prior choices in modeling the sparse data typical of predator feeding surveys and provide evidence for the superior performance of a new neutral prior choice. A case study application shows that while Bayesian point estimates may be made to correspond with those obtained by frequentist approaches, estimation uncertainty as described by the 95% intervals is more biologically realistic using the Bayesian method in that the lower bounds of the Bayesian posterior intervals for the attack rates do not include zero when the occurrence of a given predator-prey interaction is in fact observed. This contrasts with bootstrap confidence intervals that often do contain zero in such cases. The Bayesian approach provides a straightforward, probabilistic characterization of interaction strength uncertainty. In doing so it provides a framework for considering both the deterministic and stochastic drivers of species interactions and their impact on food web dynamics.

scholarly journals Towards an Essential Biodiversity Variable for Species Interactions

2018 ◽  
Vol 2 ◽  
pp. e25409
Author(s):  
Quentin Groom ◽  
Robert Guralnick ◽  
W. Daniel Kissling
Keyword(s):  
Species Interactions ◽  
Interaction Strength ◽  
Species Traits ◽  
Species Interaction ◽  
Ecological Networks ◽  
Microbial Interactions ◽  
Ecosystem Structure ◽  
State Variables ◽  
Flower Visitation ◽  
Wide Range

Can Essential Biodiversity Variables (EBVs) be developed to monitor changes in species interactions? That was the difficult question asked at the GLOBIS-B workshop in February, 2017 in which >50 experts participated. EBVs can be defined as harmonized measurements that allow us to inform policy about essential changes in biodiversity. They can be seen as biological state variables from which more refined indicators may be derived. They have been presented as a means to monitor global biodiversity change and as a concept to drive the gathering, sharing, and standardisation of data on our biota (Geijzendorffer et al. 2015, Kissling et al. 2017, Pereira et al. 2013). There are different classes of EBVs that characterize, for example, the state of species populations, species traits and ecosystem structure and function. It has also been proposed that there should be EBVs related to species interactions. However, until now there has been little progress formulating what these should be, even though species interactions are central to ecology. Species interactions cover a wide range of important processes, from mutualisms, such as pollination, to different forms of heterotrophic nutrition, such as the predator-prey relationship. Indeed, ecological interactions are critical to understand why an ecosystem is more than the sum of its parts. Nevertheless, direct observation of species interactions is often difficult and time consuming work, which makes it difficult to monitor them in the long-term. For this reason the workshop focused on those species interactions that are feasible to study and are most relevant to policy. To bring focus to our discussions we concentrated on pollination, predation and microbial interactions. Taking pollination as an example, there was recognition of the importance of ecological networks and that network metrics may be a sensitive indicator of change. Potential EBVs might be the number of pairwise interactions between species or the modularity and interaction diversity of the whole network. This requires standardised data collection and reporting (e.g. standardization of measures of interaction strength or minimum data specifications for ecological networks) and sufficient data across time to regularly calculate these metrics. Other simpler surrogates for pollination might also prove useful, such as flower visitation rates or the proportion of fruit set. Finally, there was a recognition that we do not yet have enough tools to monitor some important interactions. Many interactions, particular among microbes, can currently only be inferred from the co-occurrence of taxa. However, technology is rapidly developing and it is possible to foresee a future where even these interactions can be monitored efficiently. Species interactions are essential to understanding ecology, but they are also difficult to monitor. Yet, delegates at the workshop left with a positive outlook that it is valuable to develop standardisation and harmonization of species interaction data to make them suitable for EBV production.

scholarly journals Dynamics of species interaction strength in space, time and with developmental stage

2010 ◽  
Vol 278 (1713) ◽  
pp. 1804-1813 ◽  
Author(s):  
Rebecca L. Kordas ◽  
Steve Dudgeon
Keyword(s):  
Species Interactions ◽  
Community Dynamics ◽  
Gulf Of Maine ◽  
Interaction Strength ◽  
Species Interaction ◽  
Priority Effects ◽  
Rocky Shores ◽  
Target Populations ◽  
Geographical Regions ◽  
Per Capita

Quantifying species interaction strengths enhances prediction of community dynamics, but variability in the strength of species interactions in space and time complicates accurate prediction. Interaction strengths can vary in response to density, indirect effects, priority effects or a changing environment, but the mechanism(s) causing direction and magnitudes of change are often unclear. We designed an experiment to characterize how environmental factors influence the direction and the strength of priority effects between sessile species. We estimated per capita non-trophic effects of barnacles ( Semibalanus balanoides ) on newly settled germlings of the fucoid, Ascophyllum nodosum , in the presence and absence of consumers in experiments on rocky shores throughout the Gulf of Maine, USA. Per capita effects on germlings varied among environments and barnacle life stages, and these interaction strengths were largely unaltered by changing consumer abundance. Whereas previous evidence shows adult barnacles facilitate fucoids, here, we show that recent settlers and established juveniles initially compete with germlings. As barnacles mature, they switch to become facilitators of fucoids. Consumers caused variable mortality of germlings through time comparable to that from competition. Temporally variable effects of interactors (e.g. S. balanoides ), or spatial variation in their population structure, in different regions differentially affect target populations (e.g. A. nodosum ). This may affect abundance of critical stages and the resilience of target species to environmental change in different geographical regions.

Validation of Polarimetric Hail Detection

2006 ◽  
Vol 21 (5) ◽  
pp. 839-850 ◽  
Author(s):  
Pamela L. Heinselman ◽  
Alexander V. Ryzhkov
Keyword(s):  
Confidence Level ◽  
Statistical Significance ◽  
Ground Truth ◽  
Heavy Rain ◽  
Detection Algorithm ◽  
Probability Of Detection ◽  
Superior Performance ◽  
False Alarms ◽  
Statistical Significance Testing ◽  
Light Rain

Abstract This study describes, illustrates, and validates hail detection by a simplified version of the National Severe Storms Laboratory’s fuzzy logic polarimetric hydrometeor classification algorithm (HCA). The HCA uses four radar variables: reflectivity, differential reflectivity, cross-correlation coefficient, and “reflectivity texture” to classify echoes as rain mixed with hail, ground clutter–anomalous propagation, biological scatterers (insects, birds, and bats), big drops, light rain, moderate rain, and heavy rain. Diagnostic capabilities of HCA, such as detection of hail, are illustrated for a variety of storm environments using polarimetric radar data collected mostly during the Joint Polarimetric Experiment (JPOLE; 28 April–13 June 2003). Hail classification with the HCA is validated using 47 rain and hail reports collected by storm-intercept teams during JPOLE. For comparison purposes, probability of hail output from the Next-Generation Weather Radar Hail Detection Algorithm (HDA) is validated using the same ground truth. The anticipated polarimetric upgrade of the Weather Surveillance Radar-1988 Doppler network drives this direct comparison of performance. For the four examined cases, contingency table statistics show that the HCA outperforms the HDA. The superior performance of the HCA results primary from the algorithm’s lack of false alarms compared to the HDA. Statistical significance testing via bootstrapping indicates that differences in the probability of detection and critical success index between the algorithms are statistically significant at the 95% confidence level, whereas differences in the false alarm rate and Heidke skill score are statistically significant at the 90% confidence level.

scholarly journals Food web networks shift across a precipitation gradient due to changes in community composition and species interactions

2018 ◽  
Author(s):  
Laura Melissa Guzman ◽  
Bram Vanschoenwinkel ◽  
Vinicius F. Farjalla ◽  
Anita Poon ◽  
Diane Srivastava
Keyword(s):  
Community Composition ◽  
Species Interactions ◽  
Environmental Gradients ◽  
Interaction Strength ◽  
Species Interaction ◽  
Ecological Networks ◽  
Water Volume ◽  
Brazilian Coast ◽  
Markov Network ◽  
Water Volumes

AbstractEcological networks change across spatial and environmental gradients due to (i) changes in species composition or (ii) changes in the frequency or strength of interactions. Here we use the communities of aquatic invertebrates inhabiting clusters of bromeliad phytotelms along the Brazilian coast as a model system for examining turnover in the properties of ecological networks. We first document the variation in the species pools of sites across a geographical climate gradient. Using the same sites, we also explored the geographic variation in species interaction strength using a newly developed Markov network approach. We found that community composition differed along a gradient of water volume within bromeliads due to the turnover of some species. From the Markov network analysis, we found that the top-down effects of certain predators differed geographically, which could also be explained by geographic differences in bromeliad water volumes. Overall, this study illustrates how a network can change across an environmental gradient through both changes in both species and their interactions.

scholarly journals EXPRESS: Efficacy and Safety of Tadalafil in a Pediatric Population with Pulmonary Arterial Hypertension: Phase 3 randomized, Double Blind Placebo-Controlled Study

2021 ◽  
pp. 204589402110249
Author(s):  
David D Ivy ◽  
Damien Bonnet ◽  
Rolf MF Berger ◽  
Gisela Meyer ◽  
Simin Baygani ◽  
...  
Keyword(s):  
Pediatric Patients ◽  
Statistical Significance ◽  
Significance Testing ◽  
Efficacy And Safety ◽  
Phase 3 ◽  
Statistical Significance Testing ◽  
Double Blind ◽  
Double Blind Placebo ◽  
Treatment Groups ◽  
Pulmonary Arterial

Objective: This study evaluated the efficacy and safety of tadalafil in pediatric patients with pulmonary arterial hypertension (PAH). Methods: This phase-3, international, randomized, multicenter (24 weeks double-blind placebo controlled period; 2-year, open-labelled extension period), add-on (patient’s current endothelin receptor antagonist therapy) study included pediatric patients aged <18 years with PAH. Patients received tadalafil 20 mg or 40 mg based on their weight (Heavy-weight: ≥40 kg; Middle-weight: ≥25—<40 kg) or placebo orally QD for 24 weeks. Primary endpoint was change from baseline in 6-minute walk (6MW) distance in patients aged ≥6 years at Week 24. Sample size was amended from 134 to ≥34 patients, due to serious recruitment challenges. Therefore, statistical significance testing was not performed between treatment groups. Results: Patient demographics and baseline characteristics (N=35; tadalafil=17; placebo=18) were comparable between treatment groups; median age was 14.2 years (6.2 to 17.9 years) and majority (71.4%, n=25) of patients were in HW cohort. Least square mean (SE) changes from baseline in 6MW distance at Week 24 was numerically greater with tadalafil versus placebo (60.48 [20.41] vs 36.60 [20.78] meters; placebo-adjusted mean difference [SD] 23.88 [29.11]). Safety of tadalafil treatment was as expected without any new safety concerns. During study period 1, two patients (1 in each group) discontinued due to investigator’s reported clinical worsening, and no deaths were reported. Conclusions: The statistical significance testing was not performed between the treatment groups due to low sample size, however, the study results show positive trend in improvement in non invasive measurements, commonly utilized by clinicians to evaluate the disease status for children with PAH. Safety of tadalafil treatment was as expected without any new safety signals.

Significance tests: Necessary but not sufficient

1998 ◽  
Vol 21 (2) ◽  
pp. 221-222
Author(s):  
Louis G. Tassinary
Keyword(s):  
Effect Size ◽  
Scientific Community ◽  
Statistical Significance ◽  
Significance Tests ◽  
Experimental Control

Chow (1996) offers a reconceptualization of statistical significance that is reasoned and comprehensive. Despite a somewhat rough presentation, his arguments are compelling and deserve to be taken seriously by the scientific community. It is argued that his characterization of literal replication, types of research, effect size, and experimental control are in need of revision.

scholarly journals Machine learning powered ellipsometry

2021 ◽  
Vol 10 (1) ◽  
Author(s):  
Jinchao Liu ◽  
Di Zhang ◽  
Dianqiang Yu ◽  
Mengxin Ren ◽  
Jingjun Xu
Keyword(s):  
Machine Learning ◽  
Optical Constants ◽  
Optical Characterization ◽  
Superior Performance ◽  
Trial And Error ◽  
Powerful Method ◽  
Human In The Loop ◽  
Ill Posed ◽  
Fully Automatic

AbstractEllipsometry is a powerful method for determining both the optical constants and thickness of thin films. For decades, solutions to ill-posed inverse ellipsometric problems require substantial human–expert intervention and have become essentially human-in-the-loop trial-and-error processes that are not only tedious and time-consuming but also limit the applicability of ellipsometry. Here, we demonstrate a machine learning based approach for solving ellipsometric problems in an unambiguous and fully automatic manner while showing superior performance. The proposed approach is experimentally validated by using a broad range of films covering categories of metals, semiconductors, and dielectrics. This method is compatible with existing ellipsometers and paves the way for realizing the automatic, rapid, high-throughput optical characterization of films.

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