Evidence map›Paper›PMID 41998283›Full record

ArticleNature ecology & evolution2026

Warming temperatures and shifting precipitation patterns may exacerbate pest damage in North American forests.

Hannah L Clipp, Kevin M Potter, Matthew P Peters, Anantha M Prasad, Stephen N Matthews, Andrew V Gougherty

Abstract read
PubMed Publisher
In one paragraph

Article in Nature ecology & evolution, 2026. 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

6 authors.

Hannah L ClippUSDA Forest Service Northern Research Station, Delaware, OH, USA.ORCID http://orcid.org/0000-0002-8555-7398
Kevin M PotterUSDA Forest Service Southern Research Station, Research Triangle Park, NC, USA.ORCID http://orcid.org/0000-0002-7330-5345
Matthew P PetersUSDA Forest Service Northern Research Station, Delaware, OH, USA.ORCID http://orcid.org/0000-0002-4793-0075
Anantha M PrasadUSDA Forest Service Northern Research Station, Delaware, OH, USA.
Stephen N MatthewsUSDA Forest Service Northern Research Station, Delaware, OH, USA.
Andrew V GoughertyUSDA Forest Service Northern Research Station, Delaware, OH, USA. andrew.gougherty@usda.gov.ORCID http://orcid.org/0000-0002-3905-8539

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Climate change is expected to alter the extent and severity of forest pest damage, with substantial economic and ecological consequences, but predicting future pest impacts is challenging because of complex feedbacks among climate, pests and host trees. Here we use 20 years of data from the conterminous USA to assess how bioclimatic and biotic factors have influenced forest damage by 30 high-impact pest species and to identify ecological signals in those relationships. We found consistency in pest damage responses to maximum temperature in the warmest month, including recent average conditions and shifts from a historical baseline. Mean damage from focal pest species tends to be higher in regions with moderate maximum temperatures and in regions with faster rates of warming. In certain cases, the direction and magnitude of relationships between climate and forest damage vary by pest guild, native status and region of occurrence. Our findings provide empirical support for expectations of climate-induced stress to host trees and temperature-boosted pest performance, leading to increased pest damage in future forests.

Indexed as

Climate ChangeForestsInsectaRainAnimalsTemperatureTreesUnited States

Identifiers

PMID41998283

What OpenQuestion holds

Textmetadata
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.