Erratum to “Poor relationships between NEON airborne observation platform data and field-based vegetation traits at a mesic grassland”

IF 4.4 2区环境科学与生态学 Q1 ECOLOGY

Ecology Pub Date : 2025-01-29 DOI:10.1002/ecy.4497

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引用次数: 0

Abstract

Pau, S., J. B. Nippert, R. Slapikas, D. Griffith, S. Bachle, B. R. Helliker, R. C. O'Connor, W. J. Riley, C. J. Still, and M. Zaricor. 2022. “Poor Relationships Between NEON Airborne Observation Platform Data and Field-Based Vegetation Traits at a Mesic Grassland.” Ecology 103(2): e03590. https://doi.org/10.1002/ecy.3590.

Two of the four NEON Aerial Observation Platform (AOP)–derived data products analyzed in this paper, canopy nitrogen (DP3.30018.001; accessed June 1, 2020) and total biomass (DP3.30016.001; accessed June 1, 2020), were suspended while this article was in revision. These data suspensions were noted in the published code, and the authors affirm the data suspensions do not affect the primary results or conclusions.

Finally, none of the analyses, results, or conclusions based on the full orthorectified raw surface reflectance data (DP3.30006.001; accessed June 1, 2020; not currently suspended) are affected by the data suspensions.

Overall, the authors' results demonstrate that the AOP data they analyzed cannot be used to infer certain vegetation traits without extensive ground validation at their diverse, high-biomass grassland site at 1-m spatial resolution.

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来源期刊

Ecology 环境科学-生态学

CiteScore

8.30

自引率

2.10%

发文量

332

审稿时长

3 months

期刊介绍： Ecology publishes articles that report on the basic elements of ecological research. Emphasis is placed on concise, clear articles documenting important ecological phenomena. The journal publishes a broad array of research that includes a rapidly expanding envelope of subject matter, techniques, approaches, and concepts: paleoecology through present-day phenomena; evolutionary, population, physiological, community, and ecosystem ecology, as well as biogeochemistry; inclusive of descriptive, comparative, experimental, mathematical, statistical, and interdisciplinary approaches.