Evidence map›Paper›PMID 36523513›Full record

ArticleEcology and evolution2022

Understanding the temporal dynamics of estimated environmental niche hypervolumes for marine fishes.

Daniel Vilas, Robert J Fletcher, Zachary A Siders, David Chagaris

Abstract read
In one paragraph

Article in Ecology and evolution, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

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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

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2 · The registry

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3 · Its place in the literature

Who cites it

2 citing papers in PubMed.

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4 · The record

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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

4 authors.

Daniel VilasFisheries and Aquatic Sciences Program, School of Forest, Fisheries, and Geomatics Sciences University of Florida Gainesville Florida USA.ORCID https://orcid.org/0000-0002-2099-8280
Robert J FletcherDepartment of Wildlife Ecology and Conservation University of Florida Gainesville Florida USA.
Zachary A SidersFisheries and Aquatic Sciences Program, School of Forest, Fisheries, and Geomatics Sciences University of Florida Gainesville Florida USA.ORCID https://orcid.org/0000-0002-0798-9515
David ChagarisFisheries and Aquatic Sciences Program, School of Forest, Fisheries, and Geomatics Sciences University of Florida Gainesville Florida USA.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Understanding how species respond to the environment is essential in ecology, evolution, and conservation. Abiotic factors can influence species responses and the multi-dimensional space of abiotic factors that allows a species to grow represents the environmental niche. While niches are often assumed to be constant and robust, they are most likely changing over time and estimation can be influenced by population biology, sampling intensity, and computation methodology. Here, we used a 12-year time series of survey data to fit annual ecological niche models (ENMs) for 10 marine fish species by using two regression and two machine learning algorithms to evaluate the variation and differentiation of environmental niches. Fitted ENMs were used to develop multi-dimensional annual and pooled hypervolumes that were evaluated over time and across ENM algorithms, species, and years by computing volume, distance, and dissimilarity metrics for each annual estimated niche. We then investigated potential drivers of estimated hypervolume dynamics including species abundance, species occurrence, sampling effort, salinity, red tides severity, and algorithm. Overall, our results revealed that estimated niches varied over time and across ENM, species, and algorithms. Niche estimation was influenced over time by multiple factors suggesting high complexity on niche dynamics interpretation. Species with high occurrence tended to have a closer representation of the pooled niche and years with higher abundance tended to produce niche expansion. ENM algorithm, sampling effort, seawater salinity, and red tides explained the deviations from the pooled niche. Greater sampling effort led to more comprehensive and complete estimates of species niches. High red tides severity triggered niche contraction. Our results emphasize the predictable effects of population, sampling, and environment on species niche estimation and interpretation, and that each should be considered when performing and interpreting ecological niche analyses. Our niche analysis approach may contribute to effectively quantifying and assessing niche dynamics.

Indexed as

ecological niche modelGulf of Mexicohypervolumeniche shift

Identifiers

PMID36523513
PMCPMC9748244

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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.