Evidence map›Paper›PMID 30566478›Full record

ArticlePloS one2018

Penumbra: A spatially distributed, mechanistic model for simulating ground-level incident solar energy across heterogeneous landscapes.

Jonathan J Halama, Robert E Kennedy, James J Graham, Robert B McKane, Brad L Barnhart, Kevin S Djang, Paul B Pettus, Allen F Brookes, Patrick C Wingo

Abstract read
In one paragraph

Article in PloS one, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

2 citing papers in PubMed.

  1. Article
  2. Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

9 authors.

Jonathan J HalamaEnvironmental Science, Oregon State University, Corvallis, Oregon, United States of America.ORCID 0000-0003-3862-7629
Robert E KennedyCollege of Earth, Ocean, and Atmospheric Sciences, Oregon State University, Corvallis, Oregon, United States of America.
James J GrahamDepartment of Environmental Science and Management, Humboldt State University, Arcata, California, United States of America.
Robert B McKaneU.S. Environmental Protection Agency, Corvallis, Oregon, United States of America.
Brad L BarnhartU.S. Environmental Protection Agency, Corvallis, Oregon, United States of America.
Kevin S DjangCSRA, Corvallis, Oregon, United States of America.
Paul B PettusU.S. Environmental Protection Agency, Corvallis, Oregon, United States of America.
Allen F BrookesU.S. Environmental Protection Agency, Corvallis, Oregon, United States of America.
Patrick C WingoU.S. Environmental Protection Agency, Corvallis, Oregon, United States of America.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Landscape solar energy is a significant environmental driver, yet it remains complicated to model well. Several solar radiation models simplify the complexity of light by estimating it at discrete point locations or by averaging values over larger areas. These modeling approaches may be useful in certain cases, but they are unable to provide spatially distributed and temporally dynamic representations of solar energy across entire landscapes. We created a landscape-scale ground-level shade and solar energy model called Penumbra to address this deficiency. Penumbra simulates spatially distributed ground-level shade and incident solar energy at user-defined timescales by modeling local and distant topographic shading and vegetative shading. Spatially resolved inputs of a digital elevation model, a normalized digital surface model, and landscape object transmittance are used to estimate spatial variations in solar energy at user-defined temporal timesteps. The research goals for Penumbra included: 1) simulations of spatiotemporal variations of shade and solar energy caused by both objects and topographic features, 2) minimal user burden and parameterization, 3) flexible user defined temporal parameters, and 4) flexible external model coupling. We test Penumbra's predictive skill by comparing the model's predictions with monitored open and forested sites, and achieve calibrated mean errors ranging from -17.3 to 148.1 μmoles/m2/s. Penumbra is a dynamic model that can produce spatial and temporal representations of shade percentage and ground-level solar energy. Outputs from Penumbra can be used with other ecological models to better understand the health and resilience of aquatic, near stream terrestrial, and upland ecosystems.

Indexed as

Models, TheoreticalSolar Energy

Identifiers

PMID30566478
PMCPMC6300277

What OpenQuestion holds

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Registered trials

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.