Evidence map›Paper›PMID 41832143›Full record

ArticleNature communications2026

Biological traits predict species' time-varying responses to multiple global change drivers.

Takehiro Sasaki, Yuki Iwachido, Orlando Lam-Gordillo, Katie M Cook, Emily J Douglas, Rebecca V Gladstone-Gallagher, Barry Greenfield, Sarah Hailes, Kelly Carter, Naohiro I Ishii and 6 more

Abstract read
In one paragraph

Article in Nature communications, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing 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

1 citing paper in PubMed.

  1. 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

16 authors.

Takehiro SasakiGraduate School of Environment and Information Sciences, Yokohama National University, Yokohama, Japan. sasaki-takehiro-kw@ynu.ac.jp.ORCID http://orcid.org/0000-0001-8727-9152
Yuki IwachidoGraduate School of Environment and Information Sciences, Yokohama National University, Yokohama, Japan.
Orlando Lam-GordilloEarth Sciences New Zealand, Hamilton, New Zealand.ORCID http://orcid.org/0000-0001-6805-6260
Katie M CookEarth Sciences New Zealand, Hamilton, New Zealand.ORCID http://orcid.org/0000-0002-2401-3522
Emily J DouglasEarth Sciences New Zealand, Hamilton, New Zealand.ORCID http://orcid.org/0000-0002-9728-6943
Rebecca V Gladstone-GallagherUniversity of Auckland, Auckland, New Zealand.ORCID http://orcid.org/0000-0002-1745-2084
Barry GreenfieldEarth Sciences New Zealand, Hamilton, New Zealand.
Sarah HailesEarth Sciences New Zealand, Hamilton, New Zealand.
Kelly CarterEarth Sciences New Zealand, Hamilton, New Zealand.
Naohiro I IshiiArid Land Research Center, Tottori University, Tottori, Japan.
Yoshiki TakayamaGraduate School of Environment and Information Sciences, Yokohama National University, Yokohama, Japan.
Shinji ShimodeGraduate School of Environment and Information Sciences, Yokohama National University, Yokohama, Japan.
Maiko KagamiGraduate School of Environment and Information Sciences, Yokohama National University, Yokohama, Japan.
Judi E HewittUniversity of Auckland, Auckland, New Zealand.
Simon F ThrushUniversity of Auckland, Auckland, New Zealand.ORCID http://orcid.org/0000-0002-4005-3882
Andrew M LohrerInstitute for Multidisciplinary Sciences, Yokohama National University, Yokohama, Japan. drew.lohrer@niwa.co.nz.ORCID http://orcid.org/0000-0002-3893-6539

Funding

Asahi Glass Foundation n/aMEXT | Japan Society for the Promotion of Science (JSPS) JPJSBP120241001MEXT | JST | Core Research for Evolutional Science and Technology (CREST) JPMJCR24J2Tottori University 06B2005
6 · The paper itself

Abstract

Multiple drivers of global change are causing rapid biodiversity loss worldwide. However, predicting species' trajectories remains challenging due to the dynamic and state-dependent nature of ecological responses in real-world ecosystems. Here, we leverage nonlinear time series analysis of a multi-decadal, high-resolution dataset encompassing climate, freshwater, and sediment variables, alongside estuarine macroinvertebrate abundance. Our analysis shows that key biological traits, including body size, mobility, and lifespan predict the mean and variability of the time-varying sensitivity of species to specific environmental drivers. Species with smaller body sizes or lower mobility exhibit consistently negative responses to warming. The temporal variability of species sensitivity, an aspect often overlooked in previous studies of species' environmental responses, is strongly associated with lifespan, with shorter-lived species showing greater fluctuations over time. These findings did not always align with results from controlled laboratory or short-term field experiments, highlighting the complex, state-dependent responses of species shaped by multiple drivers of global change. We introduce a framework that links biological traits to long-term environmental responses, providing a predictive basis for trait-sensitivity relationships.

Indexed as

BiodiversityClimate ChangeInvertebratesAnimalsBody SizeClimateEcosystemFresh WaterSpecies SpecificityTime Factors

Identifiers

PMID41832143
PMCPMC13133263

What OpenQuestion holds

Textmetadata
LicenceCC BY-NC-ND
Read underepoch 390

Registered trials

None linked

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.