ArticleScientific reports2026
How to optimally allocate sampling effort in experimental ecology.
Article in Scientific reports, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.
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.
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.
Who cites it
0 citing papers in PubMed.
No citing paper in PubMed yet.
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
7 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
A major aim of experimental ecology is to quantify responses to environmental change. Study designs which optimally capture response patterns are currently debated. A key point in the discussion is how a limited total number of samples should ideally be allocated to replication versus the number of locations along the environmental gradient. Here, we assess how to optimally allocate sampling effort for maximizing prediction accuracy in gradient designs. For this we performed artificial data simulations for different sampling approaches with or without a priori knowledge of the underlying patterns, and applied a set of commonly observed response shapes. Overall, unreplicated sampling with equidistant, systematic placement along the gradient of interest at as many locations or levels as affordable turned out to be the best approach for unknown response shapes. Replication was found to be beneficial when a priori knowledge exists about the underlying, simple (e.g. linear or humped) response shape.
Indexed as
Identifiers
What OpenQuestion holds
Registered trials
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.