Combining mesocosms with models to unravel the effects of global warming and ocean acidification on a temperate marine ecosystem

Ocean warming and species exploitation have already caused large-scale reorganization of biological communities across the world. Accurate projections of future biodiversity change require a comprehensive understanding of how entire communities respond to global change. We combined a time-dynamic integrated food web modelling approach (Ecosim) with previous data from community-level mesocosm experiments to determine the independent and combined effects of ocean warming and acidification, and fisheries exploitation, on a well-managed temperate coastal ecosystem. The mesocosm parameters enabled important physiological and behavioural responses to climate stressors to be projected for trophic levels ranging from primary producers to top predators, including sharks. Through model simulations, we show that under sustainable rates of exploitation, near-future warming or ocean acidification in isolation could benefit species biomass at higher trophic levels (e.g., mammals, birds, and demersal ..., Mesocosm Experiments
We utilized our previously published mesocosm experiments to investigate the implications of future climate change on marine food webs. These experiments were specifically designed as multilevel, species-rich mesocosms (Ullah et al., 2018; Pistevos et al., 2015).
 
Model Parameterization
For various functional groups, we extracted model parameters from our mesocosm study by Ullah et al. in 2018. The sole exception was for chondrichthyans, for which parameters were derived from external studies.
 
Consumer Composition in Mesocosms
Our focus was primarily on highly mobile omnivorous and carnivorous consumers, consisting of juvenile forms of six different fish species and two shrimp species. Initial population density in each mesocosm comprised 55 individuals, varying in size between 10-40 mm. These mesocosms were subjected to climate treatments for 4.5 months, allowing both trophic and competitive interactions to influence consumer composition. By the end of the exper..., , # Data from: Combining mesocosms with models to unravel the effects of global warming and ocean acidification on a temperate marine ecosystem

This README file was generated on 2024-02-24 by Hadayet Ullah.

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GENERAL INFORMATION

1. Title of Dataset: Combining Mesocosms and Models to Unravel Global Warming and Ocean Acidification Effects on a Temperate Marine Ecosystem. The dataset is organized into Excel files. Each file serves a distinct role in supporting the article's content.

2. Author Information:

A. First Author Contact information: Hadayet Ullah
Southern Seas Ecology Laboratories, School of Biological Sciences, University of Adelaide, Adelaide, Australia
B. Corresponding Author Contact information: Ivan Nagelkerken
Southern Seas Ecology Laboratories, School of Biological Sciences, University of Adelaide, Adelaide, Australia

1. Date of data collection (approximate date): 2017-2018; Data type: Both primary (mesocosm experiment) and secondary

2. Geographic location of pr...

海洋变暖与物种开发已在全球范围内引发生物群落的大规模重构。精准预测未来生物多样性变化，需要全面理解整个群落如何响应全球环境变化。本研究将时间动态整合食物网建模方法（Ecosim）与此前的群落中型实验（mesocosm experiment）数据相结合，以明确海洋变暖、酸化以及渔业开发对一个管理完善的温带近岸生态系统的独立与联合效应。该中型实验参数可用于模拟从初级生产者到鲨鱼等顶级捕食者各营养级生物对气候胁迫的重要生理与行为响应。通过模型模拟，我们发现：在可持续开发速率下，孤立的近未来海洋变暖或酸化，或可提升高营养级物种的生物量（例如哺乳类、鸟类以及底栖……）。

### 中型实验（Mesocosm Experiments）
我们利用已发表的中型实验数据，探究未来气候变化对海洋食物网的影响。此类实验专为构建多物种、高物种丰富度的中型生态系统而设计（Ullah等，2018；Pistevos等，2015）。

### 模型参数化（Model Parameterization）
针对多个功能群，我们从Ullah等人2018年的中型实验研究中提取模型参数；唯一例外是软骨鱼类（chondrichthyans），其参数源自外部已发表研究。

### 中型实验中的消费者组成（Consumer Composition in Mesocosms）
本研究主要关注高度移动的杂食性与肉食性消费者，包括6种鱼类和2种虾类的幼体。每个中型实验单元的初始种群密度为55个个体，体长介于10~40毫米之间。这些中型实验单元接受了为期4.5个月的气候胁迫处理，使得营养级与种间竞争相互作用均可影响消费者群落组成。实验结束时……

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## 数据集来源：结合中型实验与模型解析全球变暖和海洋酸化对温带海洋生态系统的影响
本README文件由Hadayet Ullah于2024年2月24日生成。

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### 基本信息（GENERAL INFORMATION）
1. 数据集标题：《结合中型实验与模型解析全球变暖和海洋酸化对温带海洋生态系统的影响》。本数据集以Excel文件组织，每个文件在支撑文章内容中承担独特作用。
2. 作者信息：
A. 第一作者联系方式：Hadayet Ullah
澳大利亚阿德莱德大学生物科学学院南海生态实验室
B. 通讯作者联系方式：Ivan Nagelkerken
澳大利亚阿德莱德大学生物科学学院南海生态实验室
3. 数据采集日期（近似）：2017-2018年；数据类型：包含原始数据（中型实验）与二手数据
4. 数据采集地理区域……