184 research outputs found
Mark-recapture estimators for dual frame population size of prominent nesting structures: the effect of uncertain detection probability
The combined mark-recapture and line transect sampling methodology proposed by Alpizar-
Jara and Pollock [Journal of Environmental and Ecological Statistics, 3(4), 311â327, 1996; In
Marine Mammal Survey and Assessment Methods Symposium. G.W. Garner, S.C. Amstrup,
J.L. Laake, B.F.J. Manly, L.L. McDonald, and D.C. Robertson (Eds.), A.A. Balkema,
Rotterdam, Netherlands, pp. 99â114, 1999] is used to illustrate the estimation of population size
for populations with prominent nesting structures (i.e., bald eagle nests). In the context of a bald
eagle population, the number of nests in a list frame corresponds to a ââpre-markedââ sample of
nests, and an area frame corresponds to a set of transect strips that could be regularly monitored.
Unlike previous methods based on dual frame methodology using the screening estimator
[Haines and Pollock (Journal of Environmental and Ecological Statistics, 5, 245â256, 1998a;
Survey Methodology, 24(1), 79â88, 1998b)], we no longer need to assume that the area frame is
complete (i.e., all the nests in the sampled sites do not need to be seen). One may use line transect
sampling to estimate the probability of detection in a sampled area. Combining information
from list and area frames provides more efficient estimators than those obtained by using data
from only one frame. We derive an estimator for detection probability and generalize the
screening estimator. A simulation study is carried out to compare the performance of the
Chapman modification of the LincolnâPetersen estimator to the screening estimator. Simulation
results show that although the Chapman estimator is generally less precise than the screening
estimator, the latter can be severely biased in presence of uncertain detection. The screening
estimator outperforms the Chapman estimator in terms of mean squared error when detection
probability is near 1 wheareas the Chapman estimator outperforms the screening estimator when
detection probability is lower than a certain threshold value depending on particular scenarios
Mark-recapture estimators for dual frame population size of prominent nesting structures: the effect of uncertain detection probability
Milagrito: a TeV air-shower array
Milagrito, a large, covered water-Cherenkov detector, was the world's first
air-shower-particle detector sensitive to cosmic gamma rays below 1 TeV. It
served as a prototype for the Milagro detector and operated from February 1997
to May 1998. This paper gives a description of Milagrito, a summary of the
operating experience, and early results that demonstrate the capabilities of
this technique.Comment: 38 pages including 24 figure
Guidelines for Modeling and Reporting Health Effects of Climate Change Mitigation Actions
Background:
Modeling suggests that climate change mitigation actions can have substantial human health benefits that accrue quickly and locally. Documenting the benefits can help drive more ambitious and health-protective climate change mitigation actions; however, documenting the adverse health effects can help to avoid them. Estimating the health effects of mitigation (HEM) actions can help policy makers prioritize investments based not only on mitigation potential but also on expected health benefits. To date, however, the wide range of incompatible approaches taken to developing and reporting HEM estimates has limited their comparability and usefulness to policymakers.
Objective:
The objective of this effort was to generate guidance for modeling studies on scoping, estimating, and reporting population health effects from climate change mitigation actions.
Methods:
An expert panel of HEM researchers was recruited to participate in developing guidance for conducting HEM studies. The primary literature and a synthesis of HEM studies were provided to the panel. Panel members then participated in a modified Delphi exercise to identify areas of consensus regarding HEM estimation. Finally, the panel met to review and discuss consensus findings, resolve remaining differences, and generate guidance regarding conducting HEM studies.
Results:
The panel generated a checklist of recommendations regarding stakeholder engagement: HEM modeling, including model structure, scope and scale, demographics, time horizons, counterfactuals, health response functions, and metrics; parameterization and reporting; approaches to uncertainty and sensitivity analysis; accounting for policy uptake; and discounting.
Discussion:
This checklist provides guidance for conducting and reporting HEM estimates to make them more comparable and useful for policymakers. Harmonization of HEM estimates has the potential to lead to advances in and improved synthesis of policy-relevant research that can inform evidence-based decision making and practice
2017 HRS/EHRA/ECAS/APHRS/SOLAECE expert consensus statement on catheter and surgical ablation of atrial fibrillation
TRY plant trait database â enhanced coverage and open access
Plant traitsâthe morphological, anatomical, physiological, biochemical and phenological characteristics of plantsâdetermine how plants respond to environmental factors, affect other trophic levels, and influence ecosystem properties and their benefits and detriments to people. Plant trait data thus represent the basis for a vast area of research spanning from evolutionary biology, community and functional ecology, to biodiversity conservation, ecosystem and landscape management, restoration, biogeography and earth system modelling. Since its foundation in 2007, the TRY database of plant traits has grown continuously. It now provides unprecedented data coverage under an open access data policy and is the main plant trait database used by the research community worldwide. Increasingly, the TRY database also supports new frontiers of traitâbased plant research, including the identification of data gaps and the subsequent mobilization or measurement of new data. To support this development, in this article we evaluate the extent of the trait data compiled in TRY and analyse emerging patterns of data coverage and representativeness. Best species coverage is achieved for categorical traitsâalmost complete coverage for âplant growth formâ. However, most traits relevant for ecology and vegetation modelling are characterized by continuous intraspecific variation and traitâenvironmental relationships. These traits have to be measured on individual plants in their respective environment. Despite unprecedented data coverage, we observe a humbling lack of completeness and representativeness of these continuous traits in many aspects. We, therefore, conclude that reducing data gaps and biases in the TRY database remains a key challenge and requires a coordinated approach to data mobilization and trait measurements. This can only be achieved in collaboration with other initiatives
Sq and EEJâA Review on the Daily Variation of the Geomagnetic Field Caused by Ionospheric Dynamo Currents
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