ArticleInternational journal of biometeorology2025
Evaluating potential direct and carry-over weather effects on production performance in a divergently selected Merino flock.
Article in International journal of biometeorology, 2025. 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
4 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Climate change and the associated changing weather patterns provide a global challenge to livestock producers. Due to the lack of information on the exact relationship between weather patterns and production output, livestock producers may struggle to adjust to these changing environmental conditions. This study therefore evaluated the feasibility of modelling the impact of weather conditions both within and across production seasons on production output in two divergently selected lines of Merino ewes. Production data collected from the high and low line of the Elsenburg Merino flock between 1993 and 2021 were related to weather data recorded by a weather station on the farm. The weather data included temperature, relative humidity and rainfall readings. Multiple linear regressions between uncorrelated weather variables and production parameters (conception, lambing, multiple offspring and survival percentages, average weaning weight and weight weaned per ewe) were derived to quantify the relationship between weather and production. Within production season, weather conditions during mating significantly affected lambing (R2 = 0.332) and multiple offspring percentages (R2 = 0.316) in the high line and lambing percentage (R2 = 0.205) in the low line. Lambing period weather affected average weaning weight in the high line (R2 = 0.230) and survival percentage in the low line (R2 = 0.193). Significant amounts of the variation (R2 = 0.180–0.306) in various production traits for both lines were also accounted for by the fitting of regression models of weather conditions in the preceding year to current production performance. This indicates the presence of weather-related carry-over effects. It therefore appears that using weather data to predict production output, both within and between production seasons, may be a viable management tool to aid producers in decision making. More work is required before these models are suitable for general uptake.
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.