Freshwater Fishes Maintain Multi-Trait Phenotypic Stability Across an Environmental Gradient in Aqueous Calcium.
JOURNAL OF FISH BIOLOGY(2023)
McGill Univ | Univ Quebec Montreal | Univ Sherbrooke | North Carolina State Univ
Abstract
Reductions in a limiting nutrient might be expected to necessitate compromises in the functional traits that depend on that nutrient; yet populations existing in locations with low levels of such nutrients often do not show the expected degradation of functional traits. Indeed, logperch (Percina caprodes), pumpkinseed sunfish (Lepomis gibbosus) and yellow perch (Perca flavescens) residing in low-calcium water in the Upper St. Lawrence River were all previously found to maintain levels of scale calcium comparable to those of conspecific populations in high-calcium water. Yet it remains possible that the maintenance of one functional trait (i.e., scale calcium) under nutrient-limited (i.e., low calcium) conditions could come at the expense of maintaining other functional traits that depend on the same nutrient. The present study therefore examines other calcium-dependent traits, specifically skeletal element sizes and bone densities in the same fish species in the same area. Using radiographs of 101 fish from the three species across four locations (two in high-calcium water and two in low-calcium water), this new work documents multi-trait "homeostasis" along the gradient of water calcium. That is, no effect of calcium regime (low-calcium vs. high-calcium) was detected on any of the measured variables. Further, effect sizes for the skeletal traits were very low - lower even than effect sizes previously documented for scale calcium. These results thus show that native fishes maintain phenotypic stability across a suite of functional traits linked to calcium regulation, perhaps pointing to an "organismal-level homeostasis" scenario rather than a "trait-level homeostasis" scenario.
MoreTranslated text
Key words
environmental gradients,freshwater ecosystems,functional traits,homeostasis,skeletal traits,water chemistry
求助PDF
上传PDF
View via Publisher
AI Read Science
AI Summary
AI Summary is the key point extracted automatically understanding the full text of the paper, including the background, methods, results, conclusions, icons and other key content, so that you can get the outline of the paper at a glance.
Example
Background
Key content
Introduction
Methods
Results
Related work
Fund
Key content
- Pretraining has recently greatly promoted the development of natural language processing (NLP)
- We show that M6 outperforms the baselines in multimodal downstream tasks, and the large M6 with 10 parameters can reach a better performance
- We propose a method called M6 that is able to process information of multiple modalities and perform both single-modal and cross-modal understanding and generation
- The model is scaled to large model with 10 billion parameters with sophisticated deployment, and the 10 -parameter M6-large is the largest pretrained model in Chinese
- Experimental results show that our proposed M6 outperforms the baseline in a number of downstream tasks concerning both single modality and multiple modalities We will continue the pretraining of extremely large models by increasing data to explore the limit of its performance
Upload PDF to Generate Summary
Must-Reading Tree
Example

Generate MRT to find the research sequence of this paper
Related Papers
CANADIAN JOURNAL OF FISHERIES AND AQUATIC SCIENCES 2024
被引用1
FRESHWATER BIOLOGY 2024
被引用0
Data Disclaimer
The page data are from open Internet sources, cooperative publishers and automatic analysis results through AI technology. We do not make any commitments and guarantees for the validity, accuracy, correctness, reliability, completeness and timeliness of the page data. If you have any questions, please contact us by email: report@aminer.cn
Chat Paper