Student or educator? Sign up with your school email and get 6 months of Pro free.
Cited by 376

The DOI matches its Crossref record; 3 of the 3 references it cites were found in a registry or an index.

Emerging opportunities and challenges in phenology: a review

Open access
Tang, Jianwu, Körner, Christian, Muraoka, Hiroyuki, Piao, Shilong, Shen, Miaogen, Thackeray, Stephen J., Yang, Xi·2016·Ecosphere

Abstract

Plant phenology research has gained increasing attention because of the sensitivity of phenology to climate change and its consequences for ecosystem function. Recent technological development has made it possible to gather invaluable data at a variety of spatial and ecological scales. Despite our ability to observe phenological change at multiple scales, the mechanistic basis of phenology is still not well understood. Integration of multiple disciplines, including ecology, evolutionary biology, climate science, and remote sensing, with long‐term monitoring data across multiple spatial scales is needed to advance understanding of phenology. We review the mechanisms and major drivers of plant phenology, including temperature, photoperiod, and winter chilling, as well as other factors such as competition, resource limitation, and genetics. Shifts in plant phenology have significant consequences on ecosystem productivity, carbon cycling, competition, food webs, and other ecosystem functions and services. We summarize recent advances in observation techniques across multiple spatial scales, including digital repeat photography, other complementary optical measurements, and solar‐induced fluorescence, to assess our capability to address the importance of these scale‐dependent drivers. Then, we review phenology models as an important component of earth system modeling. We find that the lack of species‐level knowledge and observation data leads to difficulties in the development of vegetation phenology models at ecosystem or community scales. Finally, we recommend further research to advance understanding of the mechanisms governing phenology and the standardization of phenology observation methods across networks. With the opportunity for “big data” collection for plant phenology, we envision a breakthrough in process‐based phenology modeling.

Overview

The claims and statistics of this paper haven’t been checked yet.

Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.

A few free checks a day · papers already verified open instantly · results are public

Integrity signals

Registry

Crossref · 10.1002/ecs2.1436

Cites

3 of 3 references verified0 citation errors · 0 not checkable

Statistics

Verification

Claims the paper makes

The claims and statistics of this paper haven’t been checked yet.

Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.

A few free checks a day · papers already verified open instantly · results are public

Self-check

Percentages, sums and reported differences re-computed from the paper’s own numbers.

The self-check needs the paper’s full text.

Citations

Cites

Show all 3 references

Cited by

See all 376

Metadata

Authors
Tang, J., Körner, C., Muraoka, H., Piao, S., Shen, M., Thackeray, S. J., & Yang, X.
Venue
Ecosphere
Publisher
Wiley
Published
2016-08
Volume
7
Issue
8
ISSN
2150-8925 (ISSN-L)
OpenAlex
W2514092235
Cited by
376
References
3
FWCI
18.74
Type
journal article
Language
en
Open access
gold

About these checks

Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.

Statistics and arithmetic are recomputed, not judged.

Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.

What counts as a claim ›How we measure confidence ›How we check this ›

Are you an author, or do you see a problem with this page? Request a review

How to cite

Cite CoChat for the checks on this page, and the paper for its own findings.

This page
CoChat. (2026). Citation check: Emerging opportunities and challenges in phenology: a review. https://app.cochat.ai/papers/10.1002/ecs2.1436
The paper
Tang, J., Körner, C., Muraoka, H., Piao, S., Shen, M., Thackeray, S. J., & Yang, X. (2016). Emerging opportunities and challenges in phenology: a review. Ecosphere. https://doi.org/10.1002/ecs2.1436

Data sources

Bibliographic data: Semantic Scholar, OpenAlex, Crossref.

Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).

Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.