Where do functional traits come from? The role of theory and models
Where do functional traits come from? The role of theory and models
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功能性特征从何而来？
DOI：
10.1111/1365-2435.13829
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发表时间：
2021
影响因子：
5.2
通讯作者：
Chown SL
中科院分区：
文献类型：
--
作者：
Kearney MR;Jusup M;McGeoch MA;Kooijman SALM;Chown SL
在生态学和生物多样性信息学中，性状的使用越来越多，并采取措施整理性状数据并将其纳入生物多样性数据库。需要开发更好的预测能力，以了解物种如何应对环境变化，这在一定程度上推动了这一重点。功能性特征是最重要的--那些与个体生存、发育、生长和繁殖有明确联系的特征。决定优先考虑哪些功能性特征以及如何消除这些特征，是一个不容忽视的挑战。在这里，我们讨论了一个理论的角度来定义功能性状的能量和质量交换的动力系统模型的背景下，连接生物体到他们的环境中的优势。我们认为，建立这种模型的理论框架（生物物理生态学、代谢理论）提供了明确的标准来决定功能性状定义、测量要求和相关的元数据，通过它们与模型参数和状态变量的数学联系，从而与系统性能联系起来（生存，发展，生长和繁殖）。我们将“描述性”特征与“功能性”特征区分开来，将后者分为四类-参数，模型，阈值和估计-根据是否为模型参数，定义模型结构，是阈值状态变量或可用于估计模型参数。我们开发了一个决策树，这种分类，并说明它在哺乳动物热交换的背景下，但强调该计划的通用性，任何一种生物。我们展示了如何一个理论这一观点可能会改变我们如何以不一定更难实现的方式优先考虑收集和数据库的特征，特别是在新技术的情况下，并为必要的元数据提供明确的指导。使用理论驱动的标准，优先收集功能性状数据将最大限度地提高性状数据库的通用性，质量和一致性进行比较分析。这些数据库将同时促进从个人到生态系统的多个组织规模的集成预测建模框架的开发。可以在本文的支持信息中找到免费的简明语言摘要。
The use of traits is growing in ecology and biodiversity informatics, with initiatives to collate trait data and integrate it into biodiversity databases. A need to develop better predictive capacity for how species respond to environmental change has in part motivated this focus. Functional traits are of most interest—those with a defined link to individual survival, development, growth and reproduction.Non‐trivial challenges arise immediately in deciding which functional traits to prioritise and how to characterise them. Here we discuss the advantages of a theoretical perspective for defining functional traits in the context of dynamical systems models of energy and mass exchange that link organisms to their environments. We argue that the theoretical frameworks upon which such models are built (biophysical ecology, metabolic theory) provide clear criteria to decide upon functional trait definitions, measurement requirements and associated metadata, via their mathematical connection to model parameters and state variables, and thus to system performance (survival, development, growth and reproduction).We distinguish ‘descriptive’ traits from ‘functional’ traits by dividing the latter into four classes—parameter, model, threshold and estimation—according to whether they are model parameters, define model structure, are threshold state variables or can be used to estimate model parameters.We develop a decision tree for this classification and illustrate it in the context of mammalian heat exchange but emphasise the scheme's generality to any kind of organism.We show how a theoretical perspective may change how we prioritise traits for collection and databasing in ways that are not necessarily more difficult to achieve, especially with new technologies, and provide clear guidance for requisite metadata. The use of theoretically driven criteria for prioritising the collection of functional trait data will maximise the generality, quality and consistency of trait databases for comparative analyses. Such databases will simultaneously facilitate the development of integrated predictive modelling frameworks across multiple organisational scales from individuals to ecosystems.A free Plain Language Summary can be found within the Supporting Information of this article.
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影响因子：
4.8
作者：
R. Nisbet;E. Muller;K. Lika;S. Kooijman
通讯作者：
R. Nisbet;E. Muller;K. Lika;S. Kooijman
影响因子：
4.3
作者：
Marques GM;Augustine S;Lika K;Pecquerie L;Domingos T;Kooijman SALM
通讯作者：
Kooijman SALM
抗水损失的物理计算改进了物种范围模型：回复。
影响因子：
4.8
作者：
E. Riddell;M. Sears
通讯作者：
M. Sears
影响因子：
3.9
作者：
Khaliq, Imran;Fritz, Susanne A.;Hof, Christian
通讯作者：
Hof, Christian
DOI：
10.5962/bhl.title.160223
发表时间：
2007
期刊：
--
影响因子：
--
作者：
E. Warming;M. Vahl;P. Groom;I. Balfour
通讯作者：
I. Balfour