利用温度相关种群模型预测北美草鱼的种群增长率

IF 2.6 3区 环境科学与生态学 Q2 ECOLOGY
Madison E Brook , Kim Cuddington
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引用次数: 0

摘要

入侵风险和影响与新引进物种的种群增长率有关。我们对与温度相关的年龄和大小结构积分预测模型(IPM)进行了参数化,以预测北美入侵草鱼(Ctenopharyngodon idella)的种群增长率。我们利用现有的草鱼成熟年龄和受精率随温度变化的数据建立了模型,发现温度越高,种群增长率越小。但是,这些模型没有包括其他生命史变量(如体细胞生长率、最大体型和存活率)的潜在温度依赖性,而这些变量没有草鱼的特定数据。将模拟的温度依赖性纳入这些重要变量中,可以扭转种群增长率和温度的趋势,这取决于哪些生命史特征组合与温度有关。弹性分析强调,在所有情况下,成鱼存活率都是保持较小种群增长率的良好管理目标。我们建议,未来有关气候对种群增长影响的研究需要详细研究温度依赖性对各种生活史特征的影响,以便得出可靠的结论。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Using a temperature-dependent population model to predict the population growth rates of grass carp across North America
Invasion risk and impact are related to the population growth rate of newly introduced species. We parameterized a temperature dependent age- and size-structured integral projection model (IPM) to predict the population growth rate of invasive grass carp (Ctenopharyngodon idella) in North America. We formulated models using available data on temperature dependence in the age at maturity and fecundity for grass carp and found a small increase in population growth rate at higher temperatures. However, these models did not include potential temperature-dependence in other life history variables (e.g., somatic growth rate, maximum size, and survival) for which there is no data specific to grass carp. Inclusion of simulated temperature dependence in these important variables can reverse the trend in population growth rate and temperature, depending on which combination of life history traits are temperature-dependent. Elasticity analysis highlighted adult survival as a good management target to keep population growth rates small in all cases. We suggest that future studies regarding climate impacts on population growth will require detailed study of the impacts of temperature dependence on various life history traits in order to reach robust conclusions.
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来源期刊
Ecological Modelling
Ecological Modelling 环境科学-生态学
CiteScore
5.60
自引率
6.50%
发文量
259
审稿时长
69 days
期刊介绍: The journal is concerned with the use of mathematical models and systems analysis for the description of ecological processes and for the sustainable management of resources. Human activity and well-being are dependent on and integrated with the functioning of ecosystems and the services they provide. We aim to understand these basic ecosystem functions using mathematical and conceptual modelling, systems analysis, thermodynamics, computer simulations, and ecological theory. This leads to a preference for process-based models embedded in theory with explicit causative agents as opposed to strictly statistical or correlative descriptions. These modelling methods can be applied to a wide spectrum of issues ranging from basic ecology to human ecology to socio-ecological systems. The journal welcomes research articles, short communications, review articles, letters to the editor, book reviews, and other communications. The journal also supports the activities of the [International Society of Ecological Modelling (ISEM)](http://www.isemna.org/).
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