ReviewEcology letters2025
Linking Climate and Demography to Predict Population Dynamics and Persistence Under Global Change.
Review in Ecology letters, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.
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
1 citing paper in PubMed.
- Linking Climate and Demography to Predict Population Dynamics and Persistence Under Global Change.Ecology letters · 2025Review
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
18 authors.
Funding
Abstract
Predicting the effects of climate change on plant and animal populations is an urgent challenge for understanding the fate of biodiversity under global change. At the surface, quantifying how climate drives the vital rates that underlie population dynamics appears simple, yet many decisions are required to connect climate to demographic data. Competing approaches have emerged in the literature with little consensus around best practices. Here we provide a practical guide for how to best link vital rates to climate for the purposes of inference and projection of population dynamics. We first describe the sources of demographic and climate data underlying population models. We then focus on best practices to model the relationships between vital rates and climate, highlighting what we can learn from mechanistic and phenomenological models. Finally, we discuss the challenges of prediction and forecasting in the face of uncertainty about climate-demographic relationships as well as future climate. We conclude by suggesting ways forward to build this field of research into one that makes robust forecasts of population persistence, with opportunities for synthesis across species.
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.